Skip to main content
NCBI home page
PeerJ logoLink to PeerJ
. 2013 Feb 12;1:e2. doi: 10.7717/peerj.2

Malleable ribonucleoprotein machine: protein intrinsic disorder in the Saccharomyces cerevisiae spliceosome

Maria de Lourdes Coelho Ribeiro 1,2, Julio Espinosa 2, Sameen Islam 2, Osvaldo Martinez 2, Jayesh Jamnadas Thanki 2, Stephanie Mazariegos 2, Tam Nguyen 2, Maya Larina 3, Bin Xue 2, Vladimir N Uversky 2,4,5,✉
Editor: Emanuele Paci
PMCID: PMC3628832  PMID: 23638354

Abstract

Recent studies revealed that a significant fraction of any given proteome is presented by proteins that do not have unique 3D structures as a whole or in significant parts. These intrinsically disordered proteins possess dramatic structural and functional variability, being especially enriched in signaling and regulatory functions since their lack of fixed structure defines their ability to be involved in interaction with several proteins and allows them to be re-used in multiple pathways. Among recognized disorder-based protein functions are interactions with nucleic acids and multi-target binding; i.e., the functions ascribed to many spliceosomal proteins. Therefore, the spliceosome, a multimegadalton ribonucleoprotein machine catalyzing the excision of introns from eukaryotic pre-mRNAs, represents an attractive target for the focused analysis of the abundance and functionality of intrinsic disorder in its proteinaceous components. In yeast cells, spliceosome consists of five small nuclear RNAs (U1, U2, U4, U5, and U6) and a range of associated proteins. Some of these proteins constitute cores of the corresponding snRNA-protein complexes known as small nuclear ribonucleoproteins (snRNPs). Other spliceosomal proteins have various auxiliary functions. To gain better understanding of the functional roles of intrinsic disorder, we have studied the prevalence of intrinsically disordered proteins in the yeast spliceosome using a wide array of bioinformatics methods. Our study revealed that similar to the proteins associated with human spliceosomes (Korneta & Bujnicki, 2012), proteins found in the yeast spliceosome are enriched in intrinsic disorder.

Keywords: Spliceosome, Intrinsically disordered protein, Protein structure, RNA–protein complex, Protein–protein interaction, Intrinsic disorder, Protein–RNA interaction, Protein hub, Splicing, Protein function

Introduction

Eukaryotic genes are typically characterized by a mosaic architecture, being organized into a line of alternating exons and introns. The EXONs are those EXpressed regiONs that become the mRNA, and the INTRONs are those INTRagenic regiONs that are located inside the gene and are removed in the process of making a mature messenger RNA (mRNA) from its precursor (pre-mRNA). Therefore, the process of eukaryotic mRNA maturation includes a very important step of splicing, which takes place after or concurrently with pre-mRNA transcription, and which ensures that introns are removed and exons are joined. Here, the pre-mRNA is spliced at splice junctions found at the extreme ends of each and every intron. Although some exons are constitutively spliced; i.e., they are present in every mRNA produced from a given pre-mRNA, there are multiple ways of how exons are joined during the RNA splicing, and many pre-mRNAs are alternatively spliced to generate variable forms of mRNA from a single pre-mRNA species.

Alternative (or differential) splicing is very ubiquitous in eukaryotes (e.g., ∼95% of multiexonic genes in humans are alternatively spliced (Pan et al., 2008)), where it is believed to contribute to the greatly increased biodiversity of proteins that can be encoded by the genome (Black, 2003). In fact, since the different mRNAs generated from a single pre-mRNA can be translated into different protein isoforms, a single gene may code for multiple proteins. For example, > 500 isoforms of the calcium-activated potassium channel Slo that are translated from the different mRNAs produced by the alternative splicing of a single slo gene define the ability of ears to detect a remarkable range of frequencies (Black, 1998; Graveley, 2001; Xu et al., 2007). The Drosophila melanogaster gene Dscam (a drosophila homolog of human Down syndrome cell adhesion molecule, DSCAM) could potentially have 38,016 splice variants which are crucial for the specificity of neuronal connectivity (Schmucker et al., 2000; Celotto & Graveley, 2001; Kreahling & Graveley, 2005). In human titin, which is an extremely large elastic protein ( > 4,200 kDa) found in heart and skeletal muscle, over a million splice pathways can be potentially derived from the PEVK region alone (so called for its high content of proline (P), glutamate (E), valine (V), and lysine (K) residues) (Wang, 1996; Maruyama, 1997; Gregorio et al., 1999; LeWinter et al., 2007; Guo et al., 2010). Therefore, alternative splicing defines the increased diversity of eukaryotic proteomes compared to their corresponding genomes (Nilsen & Graveley, 2010). Also, aberrant pre-mRNA splicing constitutes the basis of some human diseases or contributes to the severity of other human maladies (Novoyatleva et al., 2006; Ward & Cooper, 2010).

Pre-mRNA splicing takes place in all eukaryotic organisms investigated to date, from yeast to metazoans. Although in some organisms splicing might occur spontaneously, where the pre-mRNA acts as a ribozyme, being able to fold on itself, cleave itself, and then remove the intron by itself, for the majority of eukaryotic introns, splicing of pre-mRNA is done in a series of reactions catalyzed by the multimegadalton ribonucleoprotein (RNP) complex known as spliceosome (Brow, 2002; Wahl, Will & Luhrmann, 2009). The canonical assembly of the spliceosome occurs anew on each pre-mRNA that contains specific sequence elements (such as the 5’ end splice, the branch point sequence, the polypyrimidine tract, and the 3’ end splice site) that are recognized and utilized during spliceosome assembly.

There are two spliceosome types, the major spliceosome, which contains five small nuclear ribonucleoproteins (snRNPs, often pronounced as snurps, the U1, U2, U4/U6, and U5 snRNPs) as the main building blocks, and which is responsible for removing the vast majority of pre-mRNA introns; and the minor spliceosome, which is present in some metazoan species and plants, and which is composed of the compositionally distinct but functionally analogous U11/U12 and U4atac/U6atac snRNPs, with the U5 snRNP shared between the machineries (Patel & Steitz, 2003). The major spliceosome is composed of five small nuclear RNA (snRNA) molecules: U1, U2, U4, U5 and U6, and a number of core proteins. A common feature of all spliceosomal snRNPs except U6 is the presence of seven mutually related Sm proteins. U6 contains a set of related “like-Sm” (Lsm) proteins (Veretnik et al., 2009). In the spliceosomal snRNPs, the Sm or Lsm proteins form a ring structure whereas a U-rich sequence in the snRNA binds in the positively charged central hole of this ring (Kambach, Walke & Nagai, 1999; Kambach et al., 1999). This core structure is further enhanced by 80–150 proteins that are abundant in the human spliceosome and are essential to the process of spliceosome-dependent splicing (Agafonov et al., 2011).

Based on the proteomic analysis of yeast spliceosome it has been concluded that the yeast splicing machinery likely contains the evolutionarily conserved core set of spliceosomal proteins that are required for constitutive splicing (Fabrizio et al., 2009). On the other hand, the number of proteins found in the yeast B, Bact and C complexes was noticeably lower than that in the corresponding metazoan complex (Fabrizio et al., 2009; Will & Luhrmann, 2011). For example, there were only ∼60 proteins in yeast pre-catalytic B complexes (compared to ∼110 in humans and D. melanogaster spliceosomes), including essentially all U1, U2, and U4/U6.U5 tri-snRNP proteins together with proteins of the nineteen complex (NTC) and mRNA retention and splicing (RES) complex (Fabrizio et al., 2009). Similarly, yeast C complexes contained only ∼50 proteins compared to ∼110 in metazoan C complexes. Therefore, this analysis revealed that yeast spliceosomes contain ∼90 proteins, almost all of which have homologs in higher eukaryotes (Fabrizio et al., 2009). Many of the remaining ∼80 proteins found in human and D. melanogaster spliceosomes but not detected in yeast were shown to play a role in alternative splicing, a process that is essentially absent in yeast (Fabrizio et al., 2009). The much lower number of proteins in yeast spliceosome compared to the metazoan counterpart suggests that yeast possesses a different, or at least simplified splicing mechanism. For example, it is likely that this reduction can be related to the extremely low number of spliceable genetic material (there are only about 250 introns in S. cerevisiae).

The highly dynamic conformation and composition of the spliceosomal proteins determine the accuracy and flexibility of the splicing machinery (Will & Luhrmann, 2011). The major constituents and regulators of the spliceosome (snRNPs and related non-snRNP proteins) are mostly conserved from yeast to metazoan (Fabrizio et al., 2009). In yeast, the spliceosome assembly on its pre-mRNA substrate represents a highly ordered and regulated process that starts with recognition of the 5’ end of the intron (5’ splice site, 5’ss) of the pre-mRNA by the U1 snRNP. Next, the U2 snRNP binds to the pre-mRNA’s branch site, forming complex A. This complex A then binds the preformed U4/U6.U5 tri-snRNP to produce penta-snRNP complex B, which contains a full set of five snRNAs in a pre-catalytic state. Complex B is then activated for catalysis by a major rearrangement of its RNA network and by global changes of its overall structure, where the association of U4 with U6 is destabilized, enabling U6 to isomerize into a base-pairing interaction with U2 to form part of the catalytic center of the spliceosome. This remodeling also includes dissociation of the U1 and U4 snRNAs and binding of a set of specific proteins leading to the formation of the activated spliceosome (Bact). Step 1 of splicing takes place in catalytically activated complex, B∗. Here, the adenosine at the branch site attacks the 5’ss site of the pre-mRNA, generating a cleaved 5’-exon and intron-3’-exon intermediate. Finally, the complex C is formed via binding another set of specific proteins. This complex C catalyzes step 2 of splicing, in which the intron is cleaved at the 3’-splice-site (3’ss) with concomitant ligation of the 5’ and 3’ exons (Fabrizio et al., 2009; Will & Luhrmann, 2011).

Importantly, although the RNA acts as a catalyst in snRNPs, the spliceosomal proteins are not just passive building blocks that hold the RNA in the correct configuration to stabilize it, but carry out essential recognition and catalytic functions during the assembly of the spliceosome and splicing-related catalytic reactions (Abelson, 2008; Pyle, 2008; Fabrizio et al., 2009), and also play a crucial role in the selection of intron substrates during the alternative splicing (Caceres & Kornblihtt, 2002). It is also important to remember that in addition to the five snRNAs, pre-mRNA splicing requires the activity of a large number of proteins, often called pre-mRNA processing proteins (Prps). Many spliceosomal and non-spliceosomal proteins are believed to have important activities related to the specificity, accuracy, and regulation of the spliceosome (Russell et al., 2000). Since these proteins are involved in numerous protein–protein and protein-RNA interactions, there is a great chance that at least some of them might belong to the class of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) or intrinsically disordered protein regions (IDPRs) lack stable tertiary and/or secondary structure under physiological conditions in vitro (Wright & Dyson, 1999; Uversky, Gillespie & Fink, 2000; Dunker et al., 2001; Dunker & Obradovic, 2001; Dunker et al., 2002; Dunker, Brown & Obradovic, 2002; Dyson & Wright, 2002; Tompa, 2002; Uversky, 2002a; Uversky, 2002b; Uversky, 2003; Tompa & Csermely, 2004; Daughdrill et al., 2005; Dunker et al., 2005; Dyson & Wright, 2005; Oldfield et al., 2005a; Tompa, 2005; Tompa, Szasz & Buday, 2005; Uversky, Oldfield & Dunker , 2005; Radivojac et al., 2007; Vucetic et al., 2007; Xie et al., 2007a; Xie et al., 2007b; Cortese, Uversky & Dunker, 2008; Dunker et al., 2008a; Dunker et al., 2008b; Dunker & Uversky, 2008; Oldfield et al., 2008; Russell & Gibson, 2008; Tompa & Fuxreiter, 2008; Uversky, Oldfield & Dunker, 2008; Tompa et al., 2009; Wright & Dyson, 2009; Uversky & Dunker, 2010). They are highly abundant in nature, with ∼25%–30% of eukaryotic proteins being mostly disordered, and with > 50% of eukaryotic proteins and > 70% of signaling proteins having long disordered regions (Dunker et al., 2000; Ward et al., 2004; Uversky, 2010; Schad, Tompa & Hegyi, 2011; Xue, Dunker & Uversky, 2012). Functional repertoire of IDPs is very broad and complements functions of ordered proteins, and functions of IDPs may arise from the specific disorder form, from inter-conversion of disordered forms, or from transitions between disordered and ordered conformations (Dunker et al., 2001; Dunker & Obradovic, 2001; Uversky, 2002a; Uversky, 2002b; Uversky & Dunker, 2010). The choice between these conformations is determined by the peculiarities of the protein environment, and many IDPs possess an exceptional ability to fold in a template dependent manner, where a single IDPR can bind to multiple partners gaining very different structures in the bound state (Oldfield et al., 2008; Hsu et al., 2012). Often, IDPs are involved in regulation, signaling and control pathways, where binding to multiple partners and high-specificity/low-affinity interactions play a crucial role and where IDPs/IDPRs play different roles in regulation of the function of their binding partners and in promotion of the assembly of supra-molecular complexes (Wright & Dyson, 1999; Dunker et al., 2001; Dunker et al., 2002; Dunker, Brown & Obradovic, 2002; Dyson & Wright, 2002; Dunker et al., 2005; Dyson & Wright, 2005; Uversky, Oldfield & Dunker , 2005; Cortese, Uversky & Dunker, 2008; Dunker et al., 2008a; Dunker et al., 2008b; Dunker & Uversky, 2008; Oldfield et al., 2008; Uversky & Dunker, 2010). In a bioinformatics analysis performed in 2008, it was found that out of the 711 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated (Vucetic et al., 2007; Xie et al., 2007a; Xie et al., 2007b).

IDPs and IDPRs are the key players in various protein–protein interaction networks, being especially abundant among hub proteins and their binding partners (Dunker et al., 2005; Dosztanyi et al., 2006; Ekman et al., 2006; Haynes et al., 2006; Patil & Nakamura, 2006; Singh et al., 2006). Furthermore, regions of pre-mRNA which undergo alternative splicing commonly encode for the disordered regions (Romero et al., 2006). This association of alternative splicing and intrinsic disorder helps proteins to avoid folding difficulties and provides a novel mechanism for developing tissue-specific protein interaction networks (Romero et al., 2006; Uversky, Oldfield & Dunker, 2008).

The hypothesis that the spliceosomal proteins might be enriched in intrinsic disorder is supported by the aforementioned results of the bioinformatics analysis of the correlation between the Swiss-Prot functional keywords and protein intrinsic disorder which clearly showed that mRNA processing and mRNA splicing were among 20 top biological processes associated with protein intrinsic disorder (Xie et al., 2007a). Furthermore, the functional keyword spliceosome was at the position #4 of the top 20 cellular components strongly correlated with predicted disorder (Vucetic et al., 2007). Also, there are several case studies, where intrinsic disorder was found in some spliceosomal proteins. For example, NMR analysis revealed that the flanking N- (residues 1–20) and C-terminal regions (residues 100–125) of the protein p14 (which is a subunit of the essential splicing factor 3b (SF3b) present in both the major and minor spliceosomes (Will et al., 1999; Will et al., 2001; Will et al., 2004), and which is located near the catalytic center of the spliceosome and is responsible for the first catalytic step of the splicing reaction (Query, Strobel & Sharp, 1996; Will et al., 2004)) are unstructured (Spadaccini et al., 2006). Serine/arginine-rich (SR) splicing factors are important spliceosomal IDPs, which, besides their significance for both constitutive and alternative splicing (Zahler et al., 1992), play key roles in the spliceosome assembly by facilitating recruitment of components of the spliceosome via protein–protein interactions (Roscigno & Garcia-Blanco, 1995) that are potentially mediated by the disordered SR domains of these splicing factors (Haynes & Iakoucheva, 2006). Finally, a recently reported systematic bioinformatics analysis of the abundance of intrinsic disorder in the proteome of the human spliceosome provided a strong support to the “disordered spliceosome” hypothesis (Korneta & Bujnicki, 2012).

Since metazoan spliceosomes are rather different from the yeast counterparts (for example, yeast spliceosomes have radically fewer proteins than metazoan spliceosomes, possessing typically less than half proteins per spliceosomal complex (Fabrizio et al., 2009)), and since the protein sequence homology between yeast and human spliceosomal proteins ranges from 36 to a little over 50% (Ben-Yehuda et al., 2000), data on the abundance of intrinsic disorder in human spliceosomal proteome cannot be directly projected to the yeast proteomes. Therefore, in the present work we have studied the prevalence of intrinsic disorder in the yeast spliceosome using a wide array of bioinformatics methods. Our study showed that similar to the proteins associated with human spliceosomes (Korneta & Bujnicki, 2012), proteins found in the yeast spliceosome are relatively enriched in intrinsic disorder.

Materials and Methods

Dataset

In this work we studied the presence of intrinsic disordered proteins (IDP) in the yeast spliceosome. The first step was to search of the UniProt database (http://www.uniprot.org) for known proteins in the baking yeast’s (Saccharomyces cerevisiae) spliceosome. This query resulted in 140 proteins, from which 109 reviewed entries were selected to make sure that the proteins chosen for analysis were manually annotated and reviewed by UniProtKB curators. The amino acid sequences in FASTA format of all these 109 yeast spliceosomal proteins were retrieved from the UniProt database and used in subsequent analysis.

At the next stage, we compared this dataset with a set of yeast spliceosomal proteins found via the comprehensive proteomic analysis of the yeast spliceosomal complex B, activated Bact, and step 1 complex C (Fabrizio et al., 2009). This experimentally determined set contained 89 proteins directly assigned to different spliceosomal components and complexes. Table 1 groups these proteins according to their functional/structural annotations and also lists 20 extra spliceosomal proteins found via the UniProt search.

Table 1.

Major structural characteristics and disorder propensities of the proteins from the Saccharomyces cerevisiae spliceosome analyzed in this study.

Yeast protein name Gene name UniProt ID PDB ID (residues) MW (kDa) Length PONDR-FIT score PONDR VLXT score FoldIndex score RONN score MoRFs AIBSs Human protein name
Sm proteins
B YER029C P40018 22.4 196 0.64 0.65 0.73 0.63 79-94 B
102-109
167-184 134-196
D1 YGR074W Q02260 16.3 146 0.36 0.54 0.29 0.47 92-109 D1
D2 YLR275W Q06217 12.9 110 0.32 0.40 0.14 0.18 D2
D3 YLR147C P43321 11.2 101 0.33 0.48 0.28 0.17 66-79 D3
E YOR159C Q12330 10.4 94 0.23 0.31 0.00 0.15 E
F YPR182W P54999 9.66 86 0.22 0.26 0.00 0.19 F
1N9R (1-86)
G YFL017W-A P40204 8.46 77 0.34 0.39 0.00 0.00 G
U1 snRNP proteins
Prp39 YML046W P39682 77.7 629 0.04 0.05 0.21 0.07
Snu71 YGR013W P53207 71.4 620 0.45 0.36 0.68 0.48 3-8 S164
270-287 275-295
316-333 315-327
379-396 372-384
387-402
407-424 405-428
450-474
495-507
566-577
Prp40 YKL012W P33203 69.1 583 0.13 0.26 0.86 0.35 93-99 FBP11
1O6W (1-75) 497-506
2B7E (134-189)
2KFD (489-552)
Prp42 YDR235W Q03776 65.1 544 0.05 0.07 0.21 0.04 526-543
Nam8 YHR086W Q00539 57.0 523 0.44 0.37 0.19 0.46 1-18 1-13 TIA1/TIAR
39-44
227-234
440-446
Snu56 YDR240C Q03782 56.5 492 0.25 0.22 0.47 0.24 9-26 1-16
42-49
320-331
345-362 342-347
Snp1 YIL061C Q00916 34.4 300 0.44 0.50 0.77 0.49 1-18 1-12 U1-70K
44-53
53-70
211-228
240-257 245-283
Mud1 YBR119W P32605 34.3 298 0.46 0.56 0.57 0.27 1-6 U1-A
119-136
222-239
155-167
Luc7 YDL087C Q07508 30.2 261 0.17 0.38 0.51 0.43 14-31 LUC7B1
45-51
201-207
222-229
Yhc1 YLR298C Q05900 27.1 231 0.64 0.43 0.89 0.48 25-46 U1-C
71-88 73-92
102-133
185-202 185-203
223-231
U2 snRNP proteins
Rse1 YML049C Q04693 153.8 1,361 0.12 0.19 0.16 0.16 814-822 SF3b130
851-862
Hsh155 YMR288W P49955 110.0 971 0.14 0.23 0.17 0.16 3-20 1-41 SF3b155
63-80 63-74
124-145
Prp9 YDL030W P19736 63.0 530 0.29 0.28 0.75 0.36 77-94 77-84 SF3a60
4DGW (1-389) 335-352
409-414
449-455
512-529 520-530
Cus1 YMR240C Q02554 50.3 436 0.50 0.52 0.79 0.60 14-31 17-36 SF3b145
53-72
80-97 88-98
143-166
192-209
362-372
401-413
419-436 429-436
Prp21 YJL203W P32524 33.1 280 0.26 0.29 0.81 0.27 79-84 SF3a120
4DGW (87-237)
Prp11 YDL043C Q07350 29.9 266 0.24 0.38 0.74 0.47 58-76 SF3a66
4DGW (149-266) 93-100
135-141
Lea1 YPL213W Q08963 27.2 238 0.19 0.39 0.17 0.40 130-140 U2- A′
198-204
232-238
Hsh49 YOR319W Q99181 24.5 213 0.12 0.07 0.13 0.03 SF3b49
Msl1 YIR009W P40567 12.8 111 0.29 0.27 0.27 0.25 U2- B″
Rds3 YPR094W Q06835 12.3 107 0.17 0.38 0.00 0.04 SF3b14b
2K0A (2-107)
Ysf3 YNL138W-A P0C074 10.0 85 0.41 0.29 0.99 0.32 12-19 SF3b10
U5 snRNP proteins
Prp8 YHR165C P33334 279.5 2,413 0.13 0.26 0.40 0.21 1-20 220K
3SBG (1836-2397) 28-49
3E66 (1822-2095) 58-72
83-109
160-174
235-252
Brr2 YER172C P32639 246.2 2,163 0.10 0.17 0.23 0.18 24-41 11-34 200K
3IM1 (1839-2163) 56-71
102-110
139-148
174-192
205-212
227-232
285-291
Snu114 YKL173W P36048 114.0 1,008 0.14 0.24 0.18 0.17 1-18 1-21 116K
61-78 53-77
485-491
543-550
Prp6 YBR055C P19735 104.2 899 0.18 0.33 0.29 0.22 15-32 1-34 102K
45-55
63-80 68-81
105-122 100-121
144-161 145-158
172-189
200-217 199-205
Prp28 YDR243C P23394 66.6 588 0.16 0.21 0.31 0.24 6-23 1-17 100K
27-35
60-77 62-69
109-120
Lin1 YHR156C P38852 40.4 340 0.45 0.42 0.66 0.52 1-17 1-11 52K
31-48 25-48
63-80
94-111 89-111
122-140
Dib1 YPR082C Q06819 16.8 143 0.11 0.12 0.06 0.00 15K
U4/U6 snRNP proteins
Prp31 YGR091W P49704 56.3 494 0.36 0.36 0.39 0.41 17-34 61K
301-312
338-355
383-400 371-388
404-423
438-455 434-463
470-487 468-477
487-494
Prp3 YDR473C Q03338 55.9 469 0.48 0.45 0.87 0.47 15-32 16-27 90K
39-65
51-68
85-98
109-126
157-174
218-235 228-237
258-265
272-289 274-281
336-353 336-344
Prp4 YPR178W P20053 52.4 465 0.22 0.31 0.32 0.22 1-8 60K
71-88
110-127
149-166
Snu13 YEL026W P39990 13.6 126 0.14 0.18 0.00 0.05 15.5K
2ALE (1-126)
U4/U6.U5 snRNP proteins
Snu66 YOR308C Q12420 66.4 587 0.76 0.70 0.94 0.81 19-37 17-28 110K
3PLU (6-24) 44-58
3PLV (37-57) 87-104 77-99
109-119
146-163 141-156
160-169
208-215
228-245 228-247
251-269 256-264
275-282
299-316 299-310
367-384 360-386
400-417
446-463 439-466
504-521 496-506
523-534
538-555 542-554
564-569
580-587
Sad1 YFR005C P43589 52.2 448 0.08 0.10 0.22 0.26 65K
Spp381 YBR152W P38282 33.8 291 0.87 0.69 1.00 0.82 1-18 1-17
36-53 26-54
113-130 93-158
151-168
166-175
215-232
230-238
264-281
Prp38 YGR075C Q00723 28.0 242 0.21 0.15 0.25 0.26 hPRP38
Snu23 YDL098C Q12368 22.7 194 0.28 0.26 0.90 0.40 126-143 hSNU23/ZMAT2
Lsm proteins
LSm4 YER112W P40070 21.3 187 0.74 0.59 0.70 0.65 65-91 LSm4
106-116
120-125
163-180 134-187
LSm7 YNL147W P53905 13.0 115 0.62 0.61 0.32 0.21 26-34 LSm7
46-53
LSm8 YJR022W P47093 12.4 109 0.18 0.23 0.28 0.16 LSm8
LSm2 YBL026W P38203 11.2 95 0.23 0.10 0.29 0.11 LSm2
LSm5 YER146W P40089 10.4 93 0.33 0.45 0.14 0.00 LSm5
LSm3 YLR438C P57743 10.0 89 0.32 0.52 0.38 0.09 LSm3
3BW1 (1-89)
LSm6 YDR378C Q06406 9.38 86 0.21 0.20 0.00 0.27 LSm6
RES proteins
Bud13/ YGL174W P46947 30.5 266 0.63 0.44 0.98 0.73 1-18 1-10 MGC13125
Cwc26 36-45
59-76 56-64
66-75
79-86
104-112
157-174
209-214
Pml1 YLR016C Q07930 23.7 204 0.16 0.42 0.56 0.30 11-28 SNIP1 ?
3ELV (1-204)
Ist/Snu17 YIR005W P40565 17.1 148 0.18 0.20 0.77 0.03 CGI-79 ?
NTC/Prp19 Complex
Syf1 YDR416W Q04048 100.2 859 0.09 0.18 0.27 0.10 hSYF1/XAB2
Clf1 YLR117C Q12309 82.4 687 0.04 0.18 0.51 0.07 32-49 CRNKL1
Cef1 YMR213W Q03654 67.7 590 0.44 0.57 0.76 0.58 94-103 CDC5L
116-124
152-160
193-201
210-228 212-226
240-248
284-301 292-303
310-315
316-333 319-337
362-379 359-374
427-439
453-463
489-506
543-549
558-566
Prp19 YLL036C P32523 56.6 503 0.13 0.23 0.23 0.24 1-6 hPRP19
1N87 (1-56)
3LRV (165-503)
Isy1/Ntc30 YJR050W P21374 28.0 235 0.39 0.48 1.00 0.52 9-14 KIAA1160
167-173
185-190
Syf2 YGR129W P53277 24.8 215 0.84 0.67 1.00 0.75 1-7 GCIP p29
63-80 66-78
96-113 93-113
151-168 153-169
187-204 186-198
Snt309 YPR101W Q06091 20.7 175 0.24 0.44 0.61 0.21 58-65 SPF27
Ntc20 YBR188C P38302 16.0 140 0.34 0.47 0.94 0.60 1-7
6-23
35-49
91-112
121-127
NTC-Related Proteins
Prp46 YPL151C Q12417 50.7 451 0.06 0.17 0.15 0.26 25-30 PRL1
Prp45 YAL032C P28004 42.5 379 0.32 0.62 0.82 0.59 1-18 SKIP1
32-41
71-81
103-112
121-133
165-172
178-185
191-208 200-208
225-231
261-278 271-278
304-310
325-344
Ecm2 YBR065C P38241 40.9 364 0.16 0.26 0.15 0.21 1-18 RBM22 ?
347-364 359-364
Cwc2 YDL209C Q12046 38.4 339 0.28 0.38 0.50 0.40 181-187 AD-002/HSPC148
3U1L (1-240) 218-235
246-263 243-255
291-308 284-292
302-307
319-336 326-334
Cwc15 YDR163W Q03772 19.9 175 0.80 0.59 1.00 0.83 27-44 11-53 RBM22
96-113 93-102
128-138
148-165 150-175
Bud31 YCR063W P25337 18.4 157 0.34 0.34 0.98 0.45 14-31 G10
Early Splicing Factors
Prp5 YBR237W P21372 96.4 849 0.43 0.51 0.48 0.47 1-18 hPRP5
22-33
30-47
103-120 100-107
116-122
145-162 156-172
661-678
683-700
735-740
Urn1 YPR152C Q06525 54.1 465 0.39 0.45 0.80 0.37 6-23 TCERG1
2JUC (212-266) 56-71
104-112
126-135
163-174
194-206
216-231
293-303
Known Splicing Factors
Prp2 YNR011C P20095 99.8 876 0.18 0.25 0.30 0.23 1-6 DDX16
13-32
46-64
100-105
117-129
169-186 168-181
Cwc22 YGR278W P53333 67.3 577 0.19 0.28 0.37 0.24 462-471 KIAA1604
525-542 520-532
540-548
571-577
Cwc27 YPL064C Q02770 35.0 301 0.38 0.51 0.65 0.42 217-225 NY-CO-10
233-241
284-301 283-301
Cwc23 YGL128C P52868 33.2 283 0.09 0.21 0.37 0.19 DNAJ A1 ?
Yju2/ YKL095W P28320 32.3 278 0.69 0.63 0.90 0.64 7-24 CCDC130
Cwc16 76-88
147-164
162-173
186-206
214-231 212-228
236-253 245-278
261-278
Cwc24 YLR323C P53769 29.7 259 0.56 0.34 0.85 0.55 1-18 1-8 RNF113A
20-37 23-31
41-51
61-78 71-77
108-125
Spp2 YOR148C Q02521 20.6 185 0.59 0.40 0.76 0.77 1-18 1-8 GPKOW/T54
104-114
141-171
Cwc25 YNL245C P53854 20.4 179 0.91 0.72 0.00 0.83 10-27 1-13 CCDC49
72-89 69-83
92-104
116-127
129-149
162-179
Cwc21 YDR482C Q03375 15.8 135 1.00 0.94 1.00 1.00 1-18 1-27 Srm300
44-66
99-116 96-106
117-123
Step 2 proteins
Prp22 YER013W P24384 130.0 1.145 0.18 0.27 0.34 0.38 190-200 hPRP22
230-250
297-316
319-330
368-385 370-407
388-405
446-455
1115-1132
Prp16 YKR086W P15938 121.6 1.071 0.19 0.28 0.29 0.32 2-19 hPRP16
55-52
59-68
89-99
119-137
166-183 178-185
197-203
284-290
353-360
1064-1071
Prp17 YDR364C P40968 52.1 455 0.23 0.23 0.57 0.28 1-9 hPRP17
17-34
91-99
118-135
146-151
Slu7 YDR088C Q02775 44.6 382 0.57 0.50 0.99 0.69 35-52 14-46 hSLU7
69-87
95-111
111-128 115-126
147-164
170-187 177-182
213-230 218-226
298-305
327-338
353-359
377-382
Prp18 YGR006W P33411 28.4 251 0.43 0.38 0.34 0.46 1-14 hPRP18
1DVK (80-251) 12-29
23-37
Disassembly proteins
Prp43 YGL120C P53131 87.6 767 0.15 0.39 0.34 0.23 1-9 hPRP43
2XAU (1-767) 17-32
42-54
81-89
106-112
339-345
385-391
Spp382 YLR424W Q06411 83.1 708 0.13 0.21 0.31 0.23 14-31 11-20 TFIP11
57-74 60-77
102-107
Ntr2 YKR022C P36118 36.7 322 0.59 0.69 0.90 0.62 1-0
29-35
46-59
61-78 77-83
96-113 96-114
126-143 136-145
208-215
CBP proteins
Sto1 YMR125W P34160 100.0 861 0.06 0.21 0.20 0.08 1-18 CBP80
Cbc2 YPL178W Q08920 23.8 208 0.42 0.34 0.65 0.43 3-21 CBP20
151-163
180-197 186-196
Other proteins
Prp5 A6ZLH6 96.4 849 0.35 0.44 0.49 0.46 1-18
29-46 22-32
103-120 100-107
117-122
145-162 156-171
661-678
675-683
683-700
735-742
Usa1 YML029W Q03714 96.7 838 0.12 0.23 0.22 0.19 359-365
414-426
828-838
Sqs1 YNL224C P53866 87.0 767 0.47 0.57 0.82 0.58 1-39
49-54
61-78 65-86
105-122 110-140
124-141
153-174
202-213
222-232
237-251
275-289
319-336 312-329
350-358
506-523 505-512
542-559 540-545
589-598
598-615
629-637
675-680
698-715
747-756
Exo84 YBR102C P38261 85.5 753 0.43 0.47 0.42 0.40 1-18 1-22
2D2S (523-753) 41-58 41-106
129-152
173-185
281-298
462-479
502-519 502-516
583-600
Snu71 A6ZV04 71.4 620 0.45 0.36 0.68 0.48 270-287 275-295
316-333 315-327
379-396 372-384
387-402
407-424 405-428
450-474
495-507
566-577
Mud2 YKL074C P36084 60.5 527 0.44 0.37 0.39 0.34 30-47 9-48
57-63
88-105 66-113
146-163 144-158
172-199
Msl5 YLR116W Q12186 53.0 476 0.50 0.58 0.62 0.67 1-7
62-79
12-136
163-168
215-220
233-239
274-291
294-304
300-317
333-355
363-375
381-391
397-417
422-476
Thp3 YPR045C Q12049 53.7 470 0.37 0.33 0.44 0.34 1-9
34-51
25-52
69-86
121-138 88-133
170-187 170-176
Sub2 YDL084W Q07478 50.3 446 0.15 0.24 0.09 0.15 3-27
56-80
Sub2 A6ZXP4 50.3 446 0.15 0.24 0.09 0.15 3-27
57-80
Prp24 YMR268C P49960 50.0 444 0.17 0.28 0.36 0.30 58-64
2GHP (1-291) 252-259
2L9W (292-400) 269-287
437-444
Csn12 YJR084W P47130 49.5 423 0.15 0.33 0.26 0.20 41-58
Npl3 YDR432W Q01560 45.4 414 0.67 0.63 0.79 0.72 1-52
2JVO (114-201) 71-88 55-90
2JVR (193-282) 120-137 120-136
141-146
155-164
262-279 261-267
301-318 291-310
323-342
358-368
386-403 377-405
Swt21 YNL187W P53873 40.3 357 0.04 0.19 0.16 0.14
Brr1 YPR057W Q99177 39.9 341 0.14 0.27 0.49 0.23 13-20
Cus2 YNL286W P53830 32.3 285 0.37 0.41 0.68 0.42 111-123
184-195
255-261
Mer1 YNL210W P16523 31.1 270 0.12 0.19 0.03 0.16
Spp381 A6ZL94 25.2 216 0.86 0.72 1.00 0.80 1-18 1-16
27-53
87-112
107-124
141-158 120-152
164-181 160-169
199-216
Rpl30 YGL030W P14120 11.4 105 0.28 0.32 0.00 0.03
1NMU (2-31)
Hub1 YNR032C-A Q6Q546 8.3 73 0.22 0.19 0.00 0.00
3PLV (1-73)
Open in a new tab

Notes.

Proteins that have information on 3-D structures for entire proteins or some of their parts are highlighted in light blue. Highly disordered proteins selected for detailed functional and structural analysis are highlighted in light red. Highly disordered proteins selected for detailed functional analysis that have information on 3-D structures are highlighted in light pink.

Analysis of the amino acid composition of yeast spliceosomal proteins

To gain insight into the relationships between sequence and disorder, amino acid compositions of different datasets were compared using an approach recently developed for IDPs (Dunker et al., 2001; Vacic et al., 2007a). To this end, the fractional difference in composition between a given set of proteins and a set of reference proteins (either a set of yeast spliceosomal proteins or a set of disordered proteins from DisProt database (Vucetic et al., 2005; Sickmeier et al., 2007)) was calculated for each amino acid residue. The fractional difference was calculated as (CX−Corder)/Corder, where CX is the content of a given amino acid in a query protein set, and Corder is the corresponding content in a set of ordered proteins and plotted for each amino acid. In corresponding plots, the amino acids were arranged from the most order-promoting to the most disorder-promoting (Radivojac et al., 2007).

Evaluation of the intrinsic disorder propensities

Per residue disorder scores

The intrinsic disorder propensities of the spliceosomal proteins were evaluated by several different disorder predictors, such as PONDR® VLXT (Dunker et al., 2001), PONDR® VSL2 (Peng et al., 2005), PONDR® VL3 (Peng et al., 2006), FoldIndex (Prilusky et al., 2005), IUPred (Dosztanyi et al., 2005a), TopIDP (Campen et al., 2008), RONN (Yang et al., 2005), and PONDR® FIT (Xue et al., 2010). These predictors are briefly described below.

PONDR® VLXT applies various compositional probabilities and hydrophobic measures of amino acid as the input features of artificial neural networks for the prediction (Romero et al., 2001). PONDR® VLXT applies three different neural networks, one for each terminal region and one for the internal region of the sequence. Each neural network is trained by a specific dataset containing only the amino acid residues of that specific region. The final prediction result uses the individual predictors in their respective regions. The transition from one predictor to another is accomplished by computing the average scores of the two predictors for a short region of overlap at the boundary between the two regions. The input features of neural networks include selected compositions and profiles from the primary sequences. PONDR® VLXT may underestimate the occurrence of long disordered regions in proteins. Although it is no longer the most accurate predictor, it is very sensitive to the local compositional biases. Hence, this method has significant advantages in finding potential binding sites (Oldfield et al., 2005a; Cheng et al., 2007).

PONDR® VL3 employs ten neural networks and selects the final prediction by simple major voting. The input features of these predictors are various sequence profiles. This predictor has higher accuracy in predicting longer disordered regions (Peng et al., 2006).

PONDR® VSL2 is a combination of neural network predictors for both short and long disordered regions. A length limit of 30 residues divides short and long disordered regions. Each individual predictor is trained by the dataset containing sequences of that specific length. And the final prediction is a weighted average determined by a second layer predictor. PONDR® VSL2 applies not only the sequence profile, but also the result of sequence alignments from PSI-blast and secondary structure prediction from PHD and PSI-pred. This predictor is one the most accurate predictor in the PONDR family (Peng et al., 2005).

IUPred assumes that globular proteins have larger numbers of effective inter-residue interactions (negative free energy) than disordered proteins due to the different types of amino acids involved in possible residue contacts. Based on this idea, a composition-based pair-wise interaction matrix was shown to give values similar to those obtained from a structure-based interaction matrix. Structured and disordered proteins were compared by this approach, with the structured proteins found to have a significantly lower free energy estimate, thus giving a means to predict whether a protein is structured or disordered using amino acid sequence as input (Dosztanyi et al., 2005a).

FoldIndex is a method developed from charge-hydropathy plots (Uversky, Gillespie & Fink, 2000) by rearranging the terms in the basic equation and by adding the technique of sliding windows (Prilusky et al., 2005). The charge-hydropathy plot was designed to determine if a protein is disordered or not. By applying a sliding window of 21 amino acids centered at a specific residue, the position of this segment on charge-hydrophobicity plot can be calculated, and the distance of this position away from the boundary line is taken as an indication whether the central residue is disordered or not (Prilusky et al., 2005).

TopIDP is a numerical scale giving the order–disorder propensity for each amino acid. This scale was determined by maximizing the differences in conditional probabilities for structured versus disordered regions of proteins for the central residues in windows of 21 residues (Campen et al., 2008).

PONDR® FIT (Xue et al., 2010) is a meta-predictor that combines six individual predictors, which are PONDR® VLXT (Romero et al., 2001), PONDR® VSL2 (Peng et al., 2005), PONDR® VL3 (Peng et al., 2006), FoldIndex (Prilusky et al., 2005), IUPred (Dosztanyi et al., 2005a), TopIDP (Campen et al., 2008). This meta-predictor is moderately more accurate than each of the component predictors.

RONN is the regional order neural network software that applies the “biobasis function neural network” pattern recognition algorithm for the detection of natively disordered regions in proteins. It predicts disordered structures based on the sequence alignments (Yang et al., 2005).

Binary disorder predictions. Cumulative distribution function curves or CDF curves (Oldfield et al., 2005b) were generated for each dataset using PONDR® FIT scores for each of the spliceosomal proteins. CDF analysis discriminates between order and disorder by means of a boundary value (Xue et al., 2009). This value can be interpreted as a measure of proportion of residues with low and high disorder predictions. Additionally, charge-hydropathy distributions (CH-plots) were also analyzed for these proteins using methods as described in Uversky, Gillespie & Fink (2000).

α-MoRF predictions. The predictor of α-helix forming Molecular Recognition Features, α-MoRF, is based on observations that predictions of order in otherwise highly disordered proteins corresponds to protein regions that mediate interaction with other proteins or nucleic acids. This predictor focuses on short binding regions within long regions of disorder that are likely to form helical structure upon binding (Oldfield et al., 2005a). It uses a stacked architecture, where PONDR® VLXT is used to identify short predictions of order within long predictions of disorder and then a second level predictor determines whether the order prediction is likely to be a binding site based on attributes of both the predicted ordered region and the predicted surrounding disordered region. An α-MoRF prediction indicates the presence of a relatively short (20 residues), loosely structured helical region within a largely disordered sequence (Oldfield et al., 2005a; Cheng et al., 2007). Such regions gain functionality upon a disorder-to-order transition induced by binding to partners (Mohan et al., 2006; Vacic et al., 2007b).

ANCHOR analysis. In addition to MoRF identifiers, potential binding sites in disordered regions can be identified by the ANCHOR algorithm (Dosztanyi, Meszaros & Simon, 2009; Meszaros, Simon & Dosztanyi, 2009). This approach relies on the pairwise energy estimation approach developed for the general disorder prediction method IUPred (Dosztanyi et al., 2005a; Dosztanyi et al., 2005b), being based on the hypothesis that long regions of disorder contain localized potential binding sites that cannot form enough favorable intrachain interactions to fold on their own, but are likely to gain stabilizing energy by interacting with a globular protein partner (Dosztanyi, Meszaros & Simon, 2009; Meszaros, Simon & Dosztanyi, 2009). Here we are using the term ANCHOR-indicated binding site (AIBS) to identify a region of a protein suggested by the ANCHOR algorithm to have significant potential to be a binding site for an appropriate but typically unidentified partner protein.

Structural and functional annotation of selected proteins

We selected the 24 most disordered spliceosomal proteins according to an average between the disorder scores calculated by different predictors for more focused analysis of their structures, disorder propensities, and functions. In addition to the level of predicted intrinsic disorder, these proteins were chosen to represent all the major components and complexes comprising the yeast spliceosome. These proteins were researched for their function, structures, location within the spliceosome, etc. This information was obtained from the UniProtKB, and validated through the literature search.

Results and Discussion

Evaluation of the abundance of intrinsic disorder in yeast spliceosomal proteins

To test for a correlation between the yeast spliceosomal proteins and intrinsic disorder, a dataset of 109 proteins associated with the yeast spliceosome was extracted from UniProt as described in Materials and Methods. Next, this set of proteins was analyzed using a broad spectrum of computational tools for the evaluation of intrinsic disorder in proteins. Results of this analysis are discussed below.

Analysis of the compositional biases. Since the amino acid sequences and compositions of IDPs and IDPRs are significantly different from those of ordered proteins and folded domains, a simple analysis of the amino acid composition biases can provide interesting information on the nature of a protein. For example, the amino acid compositions of extended IDPs (i.e., those disordered proteins that do not have almost any residual structure and behave as native coils and native pre-molten globules (Dunker et al., 2001; Uversky, 2002a; Uversky, 2002b; Uversky, 2003; Uversky & Dunker, 2010)) are characterized by low mean hydropathy and high mean net charge, which define the highly unstructured and extended state of these proteins, since high net charge leads to strong electrostatic repulsion, and low hydropathy prevents efficient compaction (Uversky, Gillespie & Fink, 2000). Overall, IDPs/IDPRs are known to be significantly depleted in so-called order-promoting amino acids, C, W, I, Y, F, L, H, V, and N, and substantially enriched in disorder-promoting residues, A, G, R, T, S, K, Q, E, and P (Dunker et al., 2001; Romero et al., 2001; Williams et al., 2001; Radivojac et al., 2007; Vacic et al., 2007a). Therefore, the evaluation of the amino acid biases in a set of proteins can be used as a fast and informative way to evaluate their intrinsically disordered nature. This analysis can be done using a computational tool, Composition Profiler (Vacic et al., 2007a), which is based on the calculation of a normalized composition of a given protein or protein dataset in the (Cx−Corder)/Corder form, where Cx is a content of a given residue in a query dataset, and Corder is the corresponding value for the set of ordered proteins from PDB Select 25 (Berman et al., 2000).

Results of this analysis are shown in Fig. 1A, which illustrates that, in comparison with typical ordered proteins, yeast spliceosomal proteins are moderately depleted in some order-promoting residues (e.g., C, W, Y, F, H, and V, see orange bars in Fig. 1A) and are moderately enriched in some major disorder-promoting residues (e.g., D, K, Q, S and E). On the other hand, some order-promoting residues (I, L and M) are rather common in these proteins, whereas some disorder-promoting residues (G, A, and P) are clearly underrepresented in yeast spliceosome. Both depletion in major order-promoting residues and enrichment in major disorder-promoting residues suggest that the yeast spliceosomal proteins might contain multiple signatures characteristic for the disordered proteins.

Figure 1. Evaluation of abundance of intrinsic disorder in the yeast spliceosome.

Figure 1

Open in a new tab

A. Fractional difference in the amino acid composition between the different yeast spliceosomal proteins and a set of completely ordered proteins calculated for each amino acid residue (compositional profiles). The fractional difference was evaluated as (Cx−Corder)/Corder, where Cx is the content of a given amino acid in a query set, and Corder is the corresponding content in the dataset of fully ordered proteins. Composition profile of typical IDPs from the DisProt database is shown for comparison (black bars). Positive bars correspond to residues found more abundantly in histones, whereas negative bars show residues, in which histones are depleted. Amino acid types are ranked according to their increasing disorder-promoting potential (Radivojac et al., 2007). B. Abundance of predicted long disordered regions in yeast spliceosomal proteins (black bars) in comparison with long disordered regions in 2,329 proteins involved in cellular signaling (AfCS, red bars), 53,630 eukaryotic proteins from SWISS-PROT (EU_SW, green bars), and 1,138 sequences corresponding to ordered parts of proteins from PDB Seect 25 (O_PDB_S25, yellow bars).

Abundance of long disordered regions in yeast spliceosomal proteins. Previous study revealed that intrinsic disorder is very abundant in signaling proteins, and this abundance can be evaluated by estimating the fraction of proteins with long disordered regions (Iakoucheva et al., 2002). In fact, the application of PONDR® VLXT (Romero et al., 2001) showed that 66% of cell-signaling proteins contain predicted regions of disorder of 30 residues or longer (Iakoucheva et al., 2002). Therefore, we applied similar approach and systematically analyzed the intrinsic disorder tendencies in four protein datasets: (1) 109 yeast spliceosomal proteins (spliceosome); (2) 2,329 signaling proteins collected by the Alliance for Cellular Signaling (AfCS); (3) 53,630 eukaryotic proteins from UniProt (EU_UP); and (4) a set of 1,138 non-homologous protein segments with well-defined 3-D structure from the Protein Data Bank Select 25 (O_PDB_S25). Figure 1B illustrates that intrinsic disorder is prevalent in the yeast spliceosomal proteins, being comparable with the prevalence observed for signaling and eukaryotic proteins. In fact, the percentages of proteins with 30 or more consecutive residues predicted to be disordered were 53% for the spliceosomal proteins, 66% for AfCS, 47% for EU_SW, and 13% for O_PDB_S25. In other words, the fraction of yeast spliceosomal proteins with long regions of predicted disorder is 4-fold higher than that of non-homologous ordered proteins from PDB (Iakoucheva et al., 2002), being also a bit higher than the corresponding fraction in eukaryotic proteins.

Disorder propensity of yeast spliceosomal proteins studied by the binary disorder predictors. Sequences of the 109 yeast spliceosomal proteins were used to predict whether these proteins are likely to be mostly disordered using two binary predictors of intrinsic disorder: charge-hydropathy plot (CH-plot) (Uversky, Gillespie & Fink, 2000; Oldfield et al., 2005b) and cumulative distribution function analysis (CDF) (Oldfield et al., 2005b). Both these methods perform binary classification of whole proteins as either mostly disordered or mostly ordered, where mostly ordered indicates proteins that contain more ordered residues than disordered residues and mostly disordered indicates proteins that contain more disordered residues than ordered residues (Oldfield et al., 2005b).

Figure 2 represents the results of the combined CH-CDF analysis of the spliceosomal proteins and shows that ∼50% of these proteins are mostly disordered. In this plot, the coordinates of each spot are calculated as a distance of the corresponding protein in the CH-plot (charge-hydropathy plot) from the boundary (Y-coordinate) and an average distance of the respective cumulative distribution function (CDF) curve from the CDF boundary (X-coordinate) (Mohan et al., 2008; Xue et al., 2009; Huang et al., 2012). The primary difference between these two binary predictors (i.e., predictors which evaluate the predisposition of a given protein to be ordered or disordered as a whole) is that the CH-plot is a linear classifier that takes into account only two parameters of the particular sequence (charge and hydropathy), whereas CDF analysis is dependent on the output of the PONDR® predictor, a nonlinear classifier, which was trained to distinguish order and disorder based on a significantly larger feature space. According to these methodological differences, CH-plot analysis is predisposed to discriminate proteins with substantial amount of extended disorder (random coils and pre-“molten globules”) from proteins with compact conformations (“molten globule”-like and rigid well-structured proteins). On the other hand, PONDR-based CDF analysis may discriminate all disordered conformations, including molten globules and mixed proteins containing both disordered and ordered regions, from rigid well-folded proteins. Therefore, this discrepancy in the disorder prediction by CDF and CH-plot provides a computational tool to discriminate proteins with extended disorder from potential molten globules and mixed proteins.

Figure 2. CH-CDF analysis of the yeast spliceosomal proteins.

Figure 2

Open in a new tab

Here, the coordinates of each point were calculated as a distance of the corresponding protein in the CH-plot from the boundary (Y-coordinate) and an average distance of the respective CDF curve from the CDF boundary (X-coordinate). The four quadrants correspond to the following predictions: Q1, proteins predicted to be disordered by CH-plots, but ordered by CDFs; Q2, ordered proteins; Q3, proteins predicted to be disordered by CDFs, but compact by CH-plots (i.e., putative molten globules or mixed proteins); Q4, proteins predicted to be disordered by both methods (i.e., proteins with extended disorder).

Positive and negative Y values in Fig. 2 correspond to proteins predicted within CH-plot analysis to be natively unfolded or compact, respectively. On the other hand, positive and negative X values are attributed to proteins predicted within the CDF analysis to be ordered or intrinsically disordered, respectively. Thus, the resultant quadrants of CDF-CH phase space correspond to the following expectations: Q1, proteins predicted to be disordered by CH-plots, but ordered by CDFs; Q2, ordered proteins; Q3, proteins predicted to be disordered by CDFs, but compact by CH-plots (i.e., putative molten globules or mixed proteins); Q4, proteins predicted to be disordered by both methods (i.e., proteins with extended disorder).

Figure 2 shows that ∼50% of the yeast spliceosomal proteins are predicted to be disordered as a whole, with 33% and 13.8% of them being found in quadrants Q4 and Q3, respectively, and are therefore expected to behave as native coils or native pre-molten globules or native molten globules or mixed proteins in their unbound states. The fact that 46.7% of the spliceosomal proteins are expected to be mostly disordered (being located within quadrants Q3 and Q4) is a very important observation since this value noticeably exceeds the corresponding value evaluated for the yeast proteins in general (13.3%) (Mohan et al., 2008).

Combined analysis of intrinsic disorder propensity by several computational tools. It was emphasized that the combined analysis of the intrinsic disorder propensity by several computational tools (especially by tools that utilizes different attributes) provides additional advantages (Ferron et al., 2006; Bourhis, Canard & Longhi, 2007; He et al., 2009), allowing, for example, better visualization of the differences between the various protein groups (Uversky et al., 2006). Figure 3A illustrates the power of this approach and represents a plot where disorder contents in the yeast spliceosomal proteins were evaluated by PONDR-FIT, which is a meta-predictor that provides more accurate disorder content predictions when compared to several other recent disorder predictors (Xue et al., 2010), and PONDR® VLXT (Romero et al., 2001), which is no longer the most accurate predictor, but is very sensitive to the local compositional biases and is capable of identifying potential molecular interaction motifs (Oldfield et al., 2005a; Cheng et al., 2007). In our analysis, we used two arbitrary cutoffs for the levels of intrinsic disorder to classify proteins as highly ordered ([IDP score] < 10%), moderately disordered (30% > [IDP score] > 10%) and highly disordered ([IDP score] > 30%) (Rajagopalan et al., 2011). According to this separation, just 9% of the proteins were predicted to be highly ordered by PONDR-FIT, with 48% and 52% of proteins classified as moderately and highly disordered, respectively (see Fig. 3A). This grouping suggests that most of the proteins in the spliceosome are intrinsically disordered.

Figure 3. Combined analysis of intrinsic disorder propensities of the yeast spliceosomal proteins using the outputs of different disorder prediction tools.

Figure 3

Open in a new tab

A. PONDR-FIT vs. PONDR® VLXT plot representing the correlation between the disorder content evaluated by PONDR-FIT (y-axis) (Xue et al., 2010) and by PONDR® VLXT (x-axis) (Romero et al., 2001). Two arbitrary cutoffs for the levels of intrinsic disorder were used to classify proteins as highly ordered ([IDP score] < 10%, blue field), moderately disordered (30% > [IDP score] > 10%, pink field) and highly disordered ([IDP score] > 30%, red field) (Rajagopalan et al., 2011). Color coding of spliceosomal proteins reflects their relation to different components and complexes. B. 3D disorder distribution plot representing the PONDR-FIT vs. RONN vs. FoldIndex dependence.

Since PONDR-FIT is a metapredictor that includes PONDR® VLXT as one of its components, a linear relationship between the results of these two predictors was expected. Therefore, we used a more complex analysis, where the outputs of three truly independent approaches were compared. Figure 3B represents the results of this analysis and shows the 3D disorder distribution plot, where the outputs of PONDR-FIT, RONN and FoldIndex are used as three dimensions. This representation clearly shows that the outputs of three very different computational tools (see Materials and Methods for the description of these tools) are generally agree with each other, since the points corresponding to the different spliceosomal proteins are mostly located on the diagonal of the FIT-RONN-FoldIndex space.

Functions of IDPs and IDPRs in yeast spliceosome

Distribution of IDPs in different components of the yeast spliceosome. The spliceosome of any organism is a protein-rich molecular machine (Fabrizio et al., 2009). In fact, the major spliceosome contains five uridine-rich small nuclear RNAs (U1, U2, U4, U5, and U6) that are responsible for the catalysis of the pre-mRNA splicing and that are assisted by a wide array of proteins, number of which ranges from ∼100 (in yeast) to more than 200 (in metazoan). Depending on their involvement in the formation of snRNPs, spliceosomal proteins can be grouped into two major categories, proteins associated with snRNPs and non-snRNP spliceosomal proteins. Since the spliceosome is a highly dynamic machine, the number of the spliceosome’s protein complement varies substantially from one stage of the splicing cycle to another (Fabrizio et al., 2009). For example, the transition from the complex B to complex C is accompanied not only by the dissociation of U1 and U4 snRNAs from the spliceosme but by the dramatic perturbation in the protein composition, where ∼35 proteins are removed and new 12 spliceosomal proteins are added to the complex (Bessonov et al., 2008; Fabrizio et al., 2009).

Figure 4 illustrates compositional changes that take place at the different stages of the spliceosome assembly and action and shows the protein compositions of the yeast B, Bact, and C complexes determined by mass spectrometry (Fabrizio et al., 2009). Here, the involved proteins are color coded according to their intrinsic disorder content evaluated by PONDR-FIT, with highly ordered (ID score < 10%), moderately disordered (30% > ID score > 10%) and highly disordered proteins (DP score > 30%) being shown as blue, pink and red bars, respectively. Details of this analysis are further summarized in Table 1, which in addition to the major structural properties of the spliceosomal proteins lists their intrinsic disorder scores evaluated by four different disorder predictors.

Figure 4. Compositional changes taking place at the different stages of the spliceosome assembly (Fabrizio et al., 2009).

Figure 4

Open in a new tab

The proteins are color coded according to their intrinsic disorder content evaluated by PONDR-FIT, with highly ordered ([IDP score] < 10%), moderately disordered (30% > [IDP score] > 10%) and highly disordered proteins ([IDP score] > 30%) being shown as blue, pink and red bars, respectively. Gray bars correspond to proteins that are present in the complex B only and are not seeing at subsequent stages; i.e., excluded from complexes Bact and C.

Predictions of potential disorder-based binding sites, α-MoRFs. Often, intrinsically disordered regions in proteins are involved in protein–protein interactions and molecular recognitions (Dunker et al., 2001; Dunker et al., 2002; Dunker, Brown & Obradovic, 2002; Tompa, 2002; Daughdrill et al., 2005; Dunker et al., 2005; Uversky, Oldfield & Dunker , 2005; Radivojac et al., 2007; Dunker et al., 2008a; Dunker & Uversky, 2008; Uversky & Dunker, 2010; Uversky, 2011; Uversky, 2012). Many flexible proteins or regions undergo disorder-to-order transitions upon binding, which is crucial for recognition, regulation, and signaling (Wright & Dyson, 1999; Uversky, Gillespie & Fink, 2000; Dunker et al., 2001; Dyson & Wright, 2002; Dyson & Wright, 2005; Oldfield et al., 2005a; Mohan et al., 2006; Vacic et al., 2007b). A correlation has been established between the specific pattern in the PONDR® VLXT curve and the ability of a given short disordered regions to undergo disorder-to-order transitions on binding (Garner et al., 1999). Based on these specific features in the protein’s disorder profile and a set of attributes of both the predicted ordered region and the predicted surrounding disordered region specific predictors of α-helix forming Molecular Recognition Features, α-MoRFs, were developed (Oldfield et al., 2005a; Cheng et al., 2007). An α-MoRF prediction indicates the presence of a relatively short, loosely structured helical region within a largely disordered sequence (Oldfield et al., 2005a). Such regions gain functionality upon a disorder-to-order transition induced by binding to partners (Mohan et al., 2006; Vacic et al., 2007b).

Application of the α-MoRF predictors reveals that molecular recognition features are highly abundant in yeast spliceosomal proteins, and Table 1 shows that ∼61% spliceosomal proteins contain α-MoRFs. This value is almost 3-fold larger than the corresponding value evaluated for the yeast proteins in general (21.1%) (Mohan et al., 2008). On average, each protein associated with east spliceosome contains 1.75 α-MoRFs, which is noticeably larger than 0.39 α-MoRFs per yeast protein in general (Mohan et al., 2008). Also, on average, each protein in the yeast proteome that was predicted to possess α-MoRFs was shown to have 1.84 molecular recognition features (Mohan et al., 2008). In spliceosome, MoRF-possessing proteins contain 2.58 α-MoRFs per protein (see Table 1). Importantly, some long, highly disordered spliceosomal proteins have multiple predicted α-MoRF regions (Table 1) that may potentially serve as binding sites for multiple proteins. For example, Snu66 (687 amino acid residues) has 11 predicted α-MoRFs, whereas there are 7, 6, and 5 predicted α-MoRFs in Prp3 (469 amino acid residues), Spp381 (191 amino acids), and Yju2 (278 residues) respectively. All this suggests that the spliceosomal proteins are extremely enriched in disorder-based binding sites and therefore are involved in extensive interaction networks.

Predictions of potential disorder-based binding sites, AIBSs. In addition to the PONDR-based MoRF identifiers which find disorder-driven binding sites using the peculiarities of predicted disorder propensity distribution within a protein sequence, potential binding sites in disordered regions can be identified by the ANCHOR algorithm (Dosztanyi, Meszaros & Simon, 2009; Meszaros, Simon & Dosztanyi, 2009). In order to predict disordered binding regions, ANCHOR identifies segments (ANCHOR-identified binding sites, AIBSs) that reside in disordered regions, cannot form enough favorable intrachain interactions to fold on their own, and are likely to gain stabilizing energy by interacting with a globular protein partner (Dosztanyi, Meszaros & Simon, 2009; Meszaros, Simon & Dosztanyi, 2009). Therefore, methodologically and logistically, ANCHOR is very different from the MoRF identifiers.

Table 1 represents the results of the ANCHOR-based analysis of the yeast spliceosomal proteins and shows AIBSs are very common in these proteins. In fact, of the 109 yeast spliceosomal proteins analyzed in this study 77 contained at least one AIRS. Therefore, AIBSs were found in ∼71% yeast spliceosomal proteins. Analysis data shown in Table 1 shows that there is generally a good agreement between the results of binding sites predictions by MoRF identifiers and ANCHOR. For proteins containing disorder-based binding sites, there are typically more AIBSs than MoRFs. This is an expected result since MoRF identifiers are designed to find disordered regions that fold into α-helices at interaction with the binding partners, whereas ANCHOR is a more general method which is not biased toward any type of the protein secondary structure in the bound state.

Structures and functions of some highly disordered spliceosomal proteins

Spliceosome assembly is a multistep process that involves sequential binding of snRNPs to the pre-mRNA in an order of U1, U2, then U4/U6 and U5 as a preformed tri-snRNP particle. A subsequent conformational rearrangement results in dissociation of U1 and U4, accompanied by new base pair formation between U2 and U6 and between U6 and the 5’ splice site, leading to the formation of the active spliceosome on which the catalytic reactions take place (Chen et al., 2001). snRNAs (which are the central structural and functional units of spliceosomal snRNPs) have important roles in recognition and alignment of splice sites mediated through base pair interactions between snRNAs and the intron sequences during spliceosome assembly (Chen et al., 2001). Furthermore, it is believed that snRNAs of these snRNPs act as ribozymes, being responsible for the catalysis of the intron excision (Abelson, 2008; Pyle, 2008; Fabrizio et al., 2009). However, all the steps related to the spliceosome assembly and actions are known to be accompanied by the dramatic rearrangements of the spliceosomal protein composition. This suggests that protein-based interactions are crucial for the spliceosome function.

From the 109 proteins studies in this work, 24 highly disordered spliceosomal proteins (Cwc21, Ntc20, Isy1/Ntc30, Prp45, Snu66, Cwc15, Spp381, Syf2, Cwc26, Slu7, Yju2/Cwc16, Ntr2, Npl3, Spp2, Bud31, SmB, Yhc1, Cus1, Lin1, Prp3, Lsm4, Prp5, Cbc2, and Msl5) were selected for more focused analysis of their structures, disorder propensities, functions, post-translational modifications, and the presence or lack of 3-D structures solved for the entire proteins or for some of their parts. In addition to the level of predicted intrinsic disorder, these proteins were chosen to represent all the major components of the yeast spliceosome.

Pre-mRNA-splicing factor Cwc21 or complexed with Cef1 protein 21 (UniProt ID: Q03375). Cwc21 protein is a part of the U2-type spliceosome complex and its putative role is the stabilization of the catalytic site or the position of RNA substrate during the splicing process. In S. cerevisiae, Cwc21 binds to two key splicing factors, namely, Prp8 and Snu114, and docks directly to U5 snRNP. It was demonstrated that SRm300, the only SR-related protein known to be at the core of human catalytic spliceosomes, is a functional ortholog of Cwc21, which also interacts directly with Prp8 and Snu114 (Grainger et al., 2009). Thus, the function of Cwc21 is likely to be conserved from yeast to humans. Cwc21 also shows affinity for the protein Isy1, a splicing fidelity factor, indicating that, even though it is not an essential protein for the function and formation of the spliceosome (Hogg, McGrail & O’Keefe, 2010), it is required for the correct splicing (Khanna et al., 2009). Cwc21 is a small highly basic protein (pI 9.67, 135 residues), that interacts with Prp8 via SCwid domain (53-97 region) and Snu114 (via C-terminus) (Grainger et al., 2009). Figure 5A and Table 1 show that Cwc21 is predicted to be highly disordered by PONDR-FIT and possesses two α-MoRFs, one of which partially overlaps with the experimentally established Prp8 and Snu114 binding sites.

Figure 5. Analysis of disorder distribution in illustrative spliceosomal proteins.

Figure 5

Open in a new tab

A. Cwc21; B. Ntc20; C. Isy1/Ntc30; D. Prp45; E. Snu66; F. Cwc15; G. Spp381; H. Syf2; I. Cwc26; J. Slu7; K. Yju2/Cwc16; L. Ntr2; M, Npl3; N. Spp2; O. Bud31; P. SmB; Q. Yhc1; R. Cus1; S. Lin1; T. Prp3; U. LSm4; V. Prp5; W. Cbc2; and X. Msl5. For all these proteins, the disorder propensity was evaluated by PONDR® FIT (red curves); PONDR® VLXT (blue curves); PONDR® VSL2B (dark green curves); and IUPred (dark cyan curves). Shadow around PONDR® FIT curves represents distribution of statistical errors. Bold pink lines correspond to the predicted α-MoRFs.

Pre-mRNA-splicing factor Ntc20 or Prp19-associated complex protein 20 (UniProt ID:P38302) and pre-mRNA-splicing factor Isy1 or Ntc30 (UniProt ID:P21374). The yeast S. cerevisiae Prp19 protein is an essential splicing factor and an important spliceosomal component. It is not tightly associated with small nuclear RNAs (snRNAs) but represents a core of a protein complex (NTC complex) consisting of at least eight proteins. Two of this NTC/Prp19-associated complex, proteins Ntc30 and Ntc20, associate to the spliceosome to mediate conformational rearrangement or to stabilize the structure of the spliceosome after U4 snRNA dissociation, which leads to spliceosome maturation (Ben-Yehuda et al., 2000; Chen et al., 2001; Chen et al., 2002; Chan et al., 2003). Null NTC30 or NTC20 mutants do not show obvious growth phenotype. However, simultaneous deletion of both genes impaired yeast growth resulting in accumulation of precursor mRNA, suggesting that Ntc30 and Ntc20 are auxiliary splicing factors the functions of which may be related to the modulation of the NTC complex function required for stable association of U5 and U6 with the spliceosome after U4 is dissociated (Chen et al., 2001).

Ntc20 is a small acidic protein (pI 5.93, 140 residues), whereas Ntc30 (also known as Isy1) is an average size basic protein (pI 9.35, 235 residues). Ntc20 interacts with Cef1, Clf1, Isy1/Ntc30, Prp46, and Syf1 proteins, which are components of the NTC complex (Ben-Yehuda et al., 2000; Chen et al., 2001). Exact locations of the potential binding sites are known, but Ntc20 was shown to be phosphorylated at position Ser139 (Albuquerque et al., 2008). Ntc30 interacts with Cef1, Cwc2, Clf1, and Syf1 (Dix et al., 1999; Ben-Yehuda et al., 2000; Chen et al., 2001). Both Ntc30 and Ntc20 are predicted to contain significant amount of disorder (see Table 1 and Figs. 5B and 5C).

Pre-mRNA-processing protein 45, Prp45 (UniProt ID: P28004). Prp45 is the yeast ortholog of the human Snw1/Skip transcription co-regulator, which regulates transcription elongation and alternative splicing, and was shown to genetically interacts with alleles of the NTC family members Syf1, Clf1/Syf3, Ntc20, and Cef1, and the second step splicing factors Slu7, Prp17, Prp18, and Prp22 (Gahura et al., 2009). Prp45 was suggested to contribute to splicing efficiency of substrates non-conforming to the consensus via its interaction with the second step-proofreading helicase Prp22 (Gahura et al., 2009). The functional equivalency of Prp45 and Skip was verified by the rescue of the Prp45 deleted lethal mutants by the insertion of a functional copy of the Skip gene in yeast (Figueroa & Hayman, 2004). It was shown that Prp45 interacts with Prp46 in vitro, demonstrating that these proteins are spliceosome-associated throughout the splicing process and both are essential for pre-mRNA splicing (Albers et al., 2003). Prp45 is known to be associated with the spliceosome throughout the splicing reactions, until after the second catalytic step (Martinkova et al., 2002; Albers et al., 2003). Prp45 is a basic protein (pI 9.15) that consists of 379 residues. It is predicted to contain significant amount of intrinsic disorder and contain three α-MoRFs (see Table 1 and Fig. 5D).

66 kDa U4/U6.U5 small nuclear ribonucleoprotein component (UniProt ID: Q12420). The yeast U4/U6.U5 tri-snRNP is a 25S snRNP particle similar in size, composition, and morphology to its counterpart in human cells (Stevens & Abelson, 1999). Stevens and Abelson purified this complex and showed that there are at least 24 proteins stably associated with this particle. In addition to the seven canonical core Sm proteins, there are a set of U6 snRNP specific Sm proteins, eight previously described U4/U6.U5 snRNP proteins, and four novel proteins. Two of the novel proteins have likely RNA binding properties, one has been implicated in the cell cycle, and one has no identifiable sequence homologues or functional motifs. One of the proteins associated with U4/U6.U5 tri-snRNP is Snu66, which is required for pre-mRNA splicing (van Nues & Beggs, 2001) being involved in interactions with the pre-mRNA-splicing helicase Brr2 and the ubiquitin-like modifier Hub1 (van Nues & Beggs, 2001; Wilkinson et al., 2004). Snu66 is a relatively large slightly acidic protein (with pI 6.35) that consists of 587 residues. Figure 5E and Table 1 shows that this protein is predicted to be highly disordered and possesses large number of α-MoRFs, clearly indicating that this disordered protein evolved to be involved in a large number of protein–protein interactions. In agreement with this hypothesis, recent study showed that the N-terminal region of Snu66 contains two Hub1 binding motifs, which are highly similar HIND elements (72% identity) arranged in tandem (Mishra et al., 2011). The crystal structures of Hub1 in complexes with HIND-I (residues 1-31) and HIND-II (32-62) elements of Snu66 were solved (Mishra et al., 2011). Figures 6A and 6B show that both HIND-I and HIND-II elements adopt α-helical structure in the bound form, therefore providing experimental support to the α-MoRF computationally identified in this region.

Figure 6. 3D-structures of fragments and domains of two highly disordered spliceosomal proteins, Snu66 (plots A and B) and Npl13 (plots C and D).

Figure 6

Open in a new tab

Structure visualizations were done with the VMD 1.8.7 (Humphrey, Dalke & Schulten, 1996). A. Crystal structure of Hub1 (shown as blue surface) in a complex with HIND-I element of Snu66 (residues 1-31, shown as the red ribbon) (PDB ID: 3PLU). B. Crystal structure of Hub1 (shown as blue surface) in a complex with HIND-II element of Snu66 (residues 32-62, shown as the red ribbon) (PDB ID: 3PLV). C. Solution structure the first RRM domain of the nucleolar protein Npl3 (residues 114-201) determined by NMR (PDB ID: 2JVO). D. Solution structure the second RRM domain of the nucleolar protein Npl3 (residues 193-282) determined by NMR (PDB ID: 2JVR).

Pre-mRNA-splicing factor Cwc15 (UniProt ID: Q03772). Cwc15 belongs to the CWC complex (or Cef1-associated complex), which is a spliceosome sub-complex similar to the late-stage spliceosome composed of the U2, U5 and U6 snRNAs and a set of at least 43 spliceosomal proteins, such as Bud13, Brr2, Cdc40, Cef1, Clf1, Cus1, Cwc2, Cwc15, Cwc21, Cwc22, Cwc23, Cwc24, Cwc25, Cwc27, Ecm2, Hsh155, Ist3, Isy1, Lea1, Msl1, Ntc20, Prp8, Prp9, Prp11, Prp19, Prp21, Prp22, Prp45, Prp46, Slu7, Smb1, Smd1, Smd2, Smd3, Smx2, Smx3, Snt309, Snu114, Spp2, Syf1, Syf2, Rse1, and Yju2. Although the exact function of Cwc15 is still poorly understood, previous studies revealed that this protein positively contributes to Cdc5p/Cef1p function (Ohi et al., 2002), suggesting that Cwc15 is potentially associated with the U2 snRNP. Cwc15 is a small highly basic protein (pI 9.06, 175 residues) which is predicted to be highly disordered and contain two α-MoRFs, further strengthening its potential role in protein–protein interactions (see Table 1 and Fig. 5F).

Pre-mRNA-splicing factor Spp381 (UniProt ID: P38282). Over-expression of Spp381 has been shown to rescue temperature-sensitive mutants of the gene Prp38, which plays an important role is the U4 subunit release from the spliceosome (Lybarger et al., 1999). An over-expressed Spp381 however does not rescue a null Prp38 allele, indicating that these two proteins cooperate but are not interchangeable. Spp381 is believed to interact with both the spliceosome and the RNA to be spliced. Immuno-precipitation experiments showed that, similar to Prp38, Spp381 is present in the U4/U6.U5 tri-snRNPs particle and two-hybrid analyses support the view that the C-terminal half of Spp381 directly interacts with the Prp38 protein (Lybarger et al., 1999). There is also a putative PEST motif within Spp381, which is one of the hallmarks of IDPs that are known to require tight regulation of their intracellular concentrations (Singh et al., 2006). Figure 5G shows that Spp381 (an acidic protein (pI 5.52) consisting of 291 residues) is predicted to be highly disordered and contain 6 potential α-MoRFs.

Pre-mRNA-splicing factor Syf2 (UniProt ID: P53277). This protein is involved in pre-mRNA splicing and cell cycle control. It is another component of the NTC complex (or Prp19-associated complex), associates to the spliceosome to mediate conformational rearrangement and/or to stabilize the structure of the spliceosome after U4 snRNA dissociation, which leads to spliceosome maturation (Russell et al., 2000). Cells with defective Syf2 proteins suffer from cell cycle arrest, possibly due to the inefficient splicing of α-tubulin (Tub1) (Dahan & Kupiec, 2002). Syf2 was shown to interact with other spliceosomal proteins, such as Cef1, Clf1, Ntc20, Prp19, and Syf1. No crystal structure has been determined as of yet for this protein, and Syf2 is known to possess 4 phosphoserines. Syf2 has 215 residues, pI of 9.34, high level of intrinsic disorder and four α-MoRFs (see Table 1 and Fig. 5H).

Pre-mRNA-splicing factor Cwc26 (UniProt ID: P46947). This protein belongs to the pre-mRNA retention and splicing complex (Vincent et al., 2003), RES, a protein complex that is required for efficient splicing, and prevents leakage of unspliced pre-mRNAs from the nucleus (named for pre-mRNA REtention and Splicing) (Dziembowski et al., 2004). In yeast, the complex consists of Ist3p, Bud13p, and Pml1p. It has no posttranslational modification sites and no known crystal structure. It has been shown to interact with the protein Ist3 and Pml1 (Dziembowski et al., 2004). Cwc26 is also known as Bud13 protein, since it may also be involved in positioning the proximal bud pole signal (Zahner, Harkins & Pringle, 1996; Ni & Snyder, 2001; Vincent et al., 2003; Dziembowski et al., 2004). It has 266 residues and is highly basic (pI 9.31). Its N-terminal half is predicted to be very disordered and is expected to contain two α-MoRFs (see Table 1 and Fig. 5I).

Pre-mRNA-splicing factor Slu7 (UniProt ID: Q02775). This is an essential protein which is involved in the second catalytic step of the pre-mRNA splicing, participating in the selection of 3’-type splice sites. This selection could be done via a 3’-splice site-binding factor, Prp16 (Frank & Guthrie, 1992; Ansari & Schwer, 1995; James, Turner & Schwer, 2002). The order of recruitment is believed to be Slu7, Prp18 and then Prp22. All three proteins are released from the spliceosome after step 2 concomitantly with the release of mature mRNA. Slu7 protein contains two functionally important domains: a zinc knuckle (122CRNCGEAGHKEKDC 135) and a Prp18-interaction domain (215EIELMKLELY 224) (Frank & Guthrie, 1992; Ansari & Schwer, 1995; James, Turner & Schwer, 2002). It has three phosphoserines and does not have a crystal structure determined. Slu7 consists of 382 residues and is characterized by a pI of 8.89. Figure 5J shows that Slu7 is rather disordered and contains a number of α-MoRFs located in its N-terminal half. It is important to emphasize here that two of the predicted α-MoRFs (located at regions 111-128 and 213-230) significantly overlap with the aforementioned functional domains of Slu7 protein.

Protein Cwc16 (UniProt ID : P28320). Similar to Cwc15 discussed above, Cwc16 (also known as Yju2) is a part of the CWC complex. It was shown that splicing factor Yju2 participates in spliceosome assembly, is associated with the components of the Prp19-associated complex (NineTeen Complex [NTC])) and is required for pre-mRNA splicing (Liu et al., 2007). NTC is known to be essential for pre-mRNA splicing, being required for the spliceosome activation by specifying interactions of U5 and U6 with pre-mRNA on the spliceosome after the release of U4. NTC contains at least eight protein components, including two tetratricopeptide repeat (TPR)-containing proteins, Ntc90 and Ntc77 (Chang, Chen & Cheng, 2009). Although Yju2 interacts with the spliceosome at almost the same time as NTC during the spliceosome assembly, these two spliceosome components are not entirely in association with each other (Liu et al., 2007). Furthermore, Yju2 is not required for the NTC binding to the spliceosome or for NTC-mediated spliceosome activation (Liu et al., 2007). However, Yju2 was shown to promote the first catalytic reaction of pre-mRNA splicing after Prp2-mediated structural rearrangement of the spliceosome (Liu et al., 2007). It is believed that Yju2 is recruited to spliceosome by the Ntc90 protein (Chang, Chen & Cheng, 2009). Cwc16/Yju2 is a medium-size, highly basic protein (pI 9.41, 278 residues) that is predicted to be highly disordered and contain five α-MoRFs (see Table 1 and Fig. 5K). Cwc16 is involved in interaction with Syf2 and is predicted to have two nuclear localization signals (NLSs, residues 242-258 and 260-278). Importantly, these NLSs coincide with the two C-terminal α-MoRFs.

Pre-mRNA-splicing factor Ntr2 (UniProt ID: P36118). Ntr2 is a part of the NTR complex (NTC-related complex), which is composed of Ntr1, Ntr2 and Prp43. Ntr2 is known to interact with Clf1, Ntr1 and Prp43, and, along with Ntr1, is involved in the pre-mRNA splicing and spliceosome disassembly, promoting the release of excised intron from the spliceosome by acting as a receptor for Prp43, possibly assisted by the Ntr1 protein (Tsai et al., 2005; Boon et al., 2006). This specific Prp43 targeting leads to the disassembly of the spliceosome with the separation of the U2, U5, U6 snRNPs and the NTC complex (Tsai et al., 2005; Boon et al., 2006). Ntr2 has two phosphoserines and no known crystal structure. This is a medium-size acidic protein (pI 5.51, 322 residues) that is predicted to be very disordered and to contain three α-MoRFs (see Table 1 and Fig. 5L).

Nucleolar protein 3 (UniProtID: Q01560). Npl3 contains two RRM (RNA recognition motifs) at the positions 125-195 and 200-275, indicating that it interacts directly with the Poly(A) regions mRNA (Wilson et al., 1994; Burkard & Butler, 2000). It has 5 phosphoserines and Arg/Gly-rich region at position 280-398. Nlp3 can interact with the riboexonuclease Rrp6, which plays a role in 5.8S rRNA 39-end processing and whose defective mutants suppress the growth defect associated with an mRNA polyadenylation defect (Burkard & Butler, 2000). Npl3 consists of 414 residues and has a pI of 5.38. It is predicted to be mostly disordered and is expected to contain five α-MoRFs (see Table 1 and Fig. 5M). Solution structures of two domains containing RRMs (residues 114-201 and 193-282) have been determined using a novel expressed protein ligation protocol (Skrisovska & Allain, 2008). The resulting structures are shown in Figs. 6C and 5D.

Pre-mRNA-splicing factor Spp2 (UniProt ID: Q02521). Pre-mRNA processing occurs by assembly of splicing factors on the substrate pre-mRNA to form the spliceosome followed by two consecutive RNA cleavage-ligation reactions. The Spp2 protein belongs to the CWC complex (or CEF1-associated complex) and interacts with Prp2 (Silverman et al., 2004). Spp2 is important for the pre-mRNA splicing, playing a role at the final stages of the spliceosome maturation by promoting the first step of splicing (Roy et al., 1995). Although this first reaction is controlled by the Prp2 protein that hydrolyzes ATP, a model was proposed in which Spp2 binds to the spliceosome complex I (composed of mRNA, U1, U2, U4, U5, and U6 smRNPs) in the absence of Prp2p or ATP. This would be followed by Prp2p binding and subsequent ATP hydrolysis leading to the catalytic reaction resulting in the formation of complex II and the release of both proteins from the spliceosome (Roy et al., 1995). The Spp2 protein has one phosphoserine and no known crystal structure. Spp2 is a small moderately basic protein (pI 8.79, 185 residues) that possesses a G-patch domain (residues 100-149) and is predicted to have one α-MoRF and be mostly disordered (see Table 1 and Fig. 5N).

Bud site selection protein 31, Bud31 (UniProt ID: P25337). Bud31 is one of the NTC-related proteins which also a component of the Cef1p sub-complex. Although it is better known for its role in the bud site selection in yeast replication, Bud31 also appears to play a role in the yeast spliceosome through interaction with the protein Cef1, as well as interaction with the precatalytic B complex, and interaction with catalytically active complexes with stably bound U2, U5, and U6 smRNPs (Saha et al., 2012b). Recently, Bud31 was shown to be important for the efficient progression to the first catalytic step and to be required for the second catalytic step in reactions at higher temperatures (Saha et al., 2012b). Bud31 plays a role in both cell cycle transitions and pre-mRNA splicing. It was shown recently that Bud31 promotes transition through the G1-S regulatory point (Start) but is not needed for G2-M transition or for exit from mitosis (Saha et al., 2012a). By analyzing the splicing status of transcripts that encode proteins involved in yeast budding, Bud31 was shown to facilitate the efficient splicing of only some of these pre-mRNAs (Saha et al., 2012a). Bud31 is a small basic protein (pI 9.64, 157 residues) that contains an N-terminally located NLS (residues 2-11), has no posttranslational modification sites and no known crystal structure. This protein is predicted to be moderately disordered and to possess one α-MoRF (see Table 1 and Fig. 5O).

smRNP-associated protein B, SmB (UniProt ID: P40018). SmB protein is also referred to as snRNP-associated protein B, snRNP-B. SmB is involved in pre-mRNA splicing, along with other Sm core proteins:  SmB’, SmD1, SmD2, SmD3, SmE, SmF, and SmG. It binds to U1, U2, U4, U5 snRNA, all containing a highly conserved region, referred to as the Sm binding site. It belongs to the SmB and SmN family, and is located in the cell nucleus. Sm core proteins have an important role during the formation of snRNPs. The SmB protein is an important part of the Sm core complex, as it is found in immunoprecipitates of U1, U2, U4, and U5 snRNAs (Camasses et al., 1998). Along with other Sm proteins, SmB contains a common sequence motif, which helps forming the globular core of the spliceosome snRNPs (U1, U2, U5, and U4/U6) (Walke et al., 2001). SmB possesses a nuclear localization signal (NLS) located in the C-terminal half of the protein (region 105-132). When this portion of the sequence is either deleted or mutated, SmB function is lost, suggesting that the C-terminal part of this Sm protein has been evolutionary conserved, and its function determines nuclear localization (Bordonne, 2000). This protein consists of 196 residues, has a pI of 10.37, contains one α-MoRF, and shows high levels of disorder, especially in it C-terminal part (see Table 1 and Fig. 5P). When analyzed by seven disorder predictors, PONDR® FIT, PONDR® VLXT, PONDR® VL3, PONDR® VSL2B, IUPred, Foldindex, and TopIDP, its corresponding levels of disorder are 0.643, 0.648, 0.724, 0.760, 0.571, 0.628, and 0.719, respectively.

U1 snRNP protein C, Yhc1 (UniProt ID: Q05900). Yhc1 (also known as U1-C protein) is an important component of the spliceosome subcomplex U1 snRNP (Tang et al., 1997), which is composed of the 7 core Sm proteins common to all spliceosomal snRNPs, and at least 10 particle-specific proteins (see Table 1 and Fig. 4), and which is essential for recognition of the pre-mRNA 5’ splice-site and the subsequent assembly of the spliceosome (Fabrizio et al., 2009). The major functional role of Yhc1 is the initial 5’ splice-site recognition for both constitutive and alternative splicing. Yhc1 interacts with the U1 snRNA and the 5’ splice-site region of the pre-mRNA, therefore stimulating the commitment complex formation by stabilizing the base pairing of the 5’ end of the U1 snRNA and the 5’ splice-site region (Tang et al., 1997; Zhang & Rosbash, 1999). It was shown that Yhc1 can recognize the 5’ splice-site in the absence of base-pairing between the pre-mRNA and the U1 snRNA (Du & Rosbash, 2002). Yhc1 is a highly basic protein (pI 10.11) that consists of 231 residues and contains a matrin-type zinc finger domain (residues 4-36). Yhc1 is predicted to be moderately disordered and is expected to contain two α-MoRFs (see Table 1 and Fig. 5Q).

U2 snRNP protein Cus1 (UniProt ID: Q02554). Cus1, also known as cold sensitive U2 snRNA suppressor, is a 436 residues long protein that is required for the U2 snRNP binding to pre-mRNA during spliceosome assembly (Pauling, McPheeters & Ares, 2000). Cus1 is a homologue of the human Sap145 protein that is present in the 17S form of the human U2 snRNP. Yeast Cus1 interacts with U2 snRNA, with Hsh49 via the 82-amino-acid-long region located between positions 229 and 311 and with Hsh155 (Pauling, McPheeters & Ares, 2000). Based on these observations it was proposed that Cus1, Hsh49, and Hsh155 form a stable protein complex which can exchange with a core U2 snRNP and which is necessary for U2 snRNP function in pre-spliceosome assembly (Pauling, McPheeters & Ares, 2000). Although Cus1 is a moderately basic protein (pI 8.67), one of its characteristic features is a highly acidic nature of its C-terminal tail, where nearly half of the last 59 residues are acidic (23 are E or D) (Pauling, McPheeters & Ares, 2000). Both N-terminal and C-terminal tails of Cus1 are predicted to be highly disordered and contain a number of potential disorder-based binding sites (see Table 1 and Fig. 5R).

U5 snRNP protein Lin1 (UniProt ID: P38852). Lin1 is a multifunctional protein involved in several different processes. Compartmentalization of Lin1 with U5 snRNP was inferred from a direct assay (Stevens et al., 2001). Based on its association with the Irr1/Scc3 component of the cohesin complex involved in cohesion and separation of chromosomes during mitosis and its interaction with Prp8, Slx5, Siz2, Wss1, Rfc1, and YIL149w proteins, which are known to participate in mRNA splicing, DNA replication, chromosome condensation, chromatid separation and alternative cohesion, Lin1 was proposed to serve as a functional and physical link among these processes (Bialkowska & Kurlandzka, 2002). Lin1 is an acidic protein (pI 5.01) consisting of 340 residues. Figure 5S show that the N-terminal half of the Lin1 protein is predicted to be very disordered and is expected to have four α-MoRFs (see also Table 1), whereas the C-terminal half is expected to be ordered. The last sixty residues of Lin1 (residues 282-340) correspond to a glycine-tyrosine-phenylalanine (GYF) domain which contains a conserved GP[YF]xxxx[MV]xxWxxx[GN]YF motif which can be involved in the recognition of proline-rich sequences (Freund et al., 1999). Since many proline-rich proteins are IDPs, Lin1 utilizes two different modes of intrinsic disorder-based protein–protein recognition, where it relies on the intrinsic disorder of its N-terminal half to interact with some partners and also uses intrinsic disorder of other partners to interact with ordered C-terminal region.

U4/U6 snRNP protein Prp3 (UniProt ID: Q03338). Prp3 is large moderately basic protein (pI 8.69, 469 residues), which is a component of the yeast U4/U6 snRNP and is also present in the U4/U6.U5 tri-snRNP (Anthony, Weidenhammer & Woolford, 1997). It was shown that Prp3 is necessary for both the formation of stable U4/U6 snRNPs and for the assembly of the U4/U6.U5 tri-snRNP from its component snRNPs. In fact, the Prp3 inactivation diminishes the spliceosome assembly from the pre-spliceosome due to the absence of intact U4/U6.U5 tri-snRNPs (Anthony, Weidenhammer & Woolford, 1997). Homology between the yeast Prp3 protein and the human protein 90K (which is a component of the human U4/U6 snRNPs) represents an illustrative example of the conservation of splicing factors between yeast and metazoans (Anthony, Weidenhammer & Woolford, 1997). Prp3 is predicted to contain significant amount of disorder (especially in its first 350 residues) and is expected to be a promiscuous binder, since it has seven α-MoRFs (see Table 1 and Fig. 5T).

U6 snRNA-associated Sm-like Protein LSm4 (UniProt ID: P40070). Sm-like (LSm) heptameric complex is one of the important spliceosomal components, which exists in two different forms, the nuclear form and the cytoplasmic form, each comprising of different subunits (Reijns, Auchynnikava & Beggs, 2009). The nuclear form, LSm2-8 complex, consists of subunits from LSm2 to LSm8, is closely associated with the U6 snRNP, interacts with the Prp24, and works together with the neighboring proteins to create a functional spliceosome. The cytoplasmic form is the composed of LSm1 to LSm7 and is involved in mRNA turnover and also promotes the mRNA decapping and decay (Spiller et al., 2007). One of the roles of the LSm2-8 complex is to promote the U4/U6 di-snRNP assembly (Reijns, Auchynnikava & Beggs, 2009). It is also involved in the processing and stabilization of ribosomal RNAs and determines the nuclear localization of the U6 snRNP (Spiller et al., 2007). LSm4 is a component of both LSm1-7 and LSm2-8 complexes. Among different functions ascribed to LSm4 are specific binding to the 3’-terminal U-tract of U6 snRNA, participation in processing of pre-tRNAs, pre-rRNAs and U3 snoRNA, and involvement in maturing of the precursor of the RNA component of RNase P (pre-P RNA) (Bouveret et al., 2000; Tharun et al., 2000; Kufel et al., 2002; Kufel et al., 2003; Kufel et al., 2004). LSm4 is a small basic protein (pI 9.45, 187 residues) with highly disordered C-terminal domain that contains one α-MoRF and one phosphoserine at position 181 (Albuquerque et al., 2008) (see Table 1 and Fig. 5U).

Early splicing factor Prp5 (UniProt ID: P21372). Prp5 is a large slightly basic (pI 8.22) ATP-dependent RNA helicase consisting of 850 residues (O’Day, Dalbadie-McFarland & Abelson, 1996). Prp5 is involved in spliceosome assembly, nuclear splicing, and catalysis of the ATP-dependent conformational change of U2 snRNP (Ruby, Chang & Abelson, 1993; Wells & Ares, 1994; O’Day, Dalbadie-McFarland & Abelson, 1996; Abu Dayyeh et al., 2002). It is believed that this protein might be involved in bridging U1 and U2 snRNPs and might promote stable interaction between the U2 snRNP and intron RNA (Xu et al., 2004). Prp5 contains a helicase domain (residues 287-661) which is divided in the helicase ATP-binding and helicase C-terminal subdomains (residues 287-467 and 502-661, respectively). There are also several functionally important motifs in Prp5, such as nucleotide binding motif (residues 300-307), coiled-coil (residues 13-81), NLS (residues 90-96), Q motif (residues 255-284) and the DEAD-box motif (residues 415-418). Despite the fact that Prp5 is an enzyme and therefore is expected to be mostly ordered, Table 1 and Fig. 5V shows that this protein is predicted to have significant amount of disorder (mostly located in the first N-terminal 200 residues) and also to possess six α-MoRFs.

CBP protein Cbc2 (UniProt ID: Q08920). Cbc2 is a component of the nuclear cap-binding complex (CBC), which is a heterodimer that co-transcriptionally interacts with the cap of pre-mRNAs and is composed of the Sto1/Cbc1 and Cbc2 proteins. CBC complex is crucial for the efficient pre-mRNA splicing through its participation in the formation of the commitment complex and spliceosome. It is involved in maturation, export and degradation of nuclear mRNAs (Lewis, Gorlich & Mattaj, 1996; Fortes et al., 1999). Cbc2 binds the m7G cap of the RNA and a large CBC subunit Sto1 that interacts with karyopherins, and is believed to be responsible for splicing control during meiosis (Qiu et al., 2012). Cbc2 is an acidic protein (pI 5.02) that is composed of 208 residues and contains RRM domain that is involved in single-stranded RNA binding (residues 46-124) and three mRNA cap-binding regions (residues 118-122, 129-133, and 139-140). Figure 5W shows that Cbc2 is predicted to have long disordered tails and two α-MoRF located within these intrinsically disordered N- and C-termini (see also Table 1).

Msl5 protein (UniProt ID: Q12186). Msl5 is the branch point-bridging protein, which is required for the pre-spliceosome formation, playing a role in the creation of the commitment complex 2 (CC2) where it binds to the snRNP U1-associated protein Prp40, bridging the U1 snRNP-associated 5’-splice site and the Msl5-associated branch point 3’ intron splice site (Abovich & Rosbash, 1997; Rutz & Seraphin, 1999). As a part of the CC2 complex, Msl5 is involved in the nuclear retention of pre-mRNA (Rutz & Seraphin, 2000). It interacts with Mud2 and Prp40 (Abovich & Rosbash, 1997; Rutz & Seraphin, 1999), and the proline-rich region of Msl5 (residues 363-474) binds to the GYF domains of Smy2 and Syh1 (Kofler, Motzny & Freund, 2005). Figure 5X shows that the Msl5 region responsible for the interaction with the GYF domains of Smy2 and Syh1 is a part of the long, highly disordered tail. There are two α-MoRFs in this basic (pI 9.72), 476 residue-long protein (see Table 1 and Fig. 5X).

Highly disordered spliceosomal proteins might act as important hubs

Protein-protein interaction networks contain many proteins with only a few links and a few proteins with many links. These highly connected or promiscuous proteins are known as hubs, the binding mechanisms of which can be reasonably explained based on the molecular recognition via disorder-to-order transitions upon binding (Dunker et al., 2005). With respect to timing issues, some proteins have multiple, simultaneous interactions (“party hubs”) (Han et al., 2004) while others have multiple sequential interactions (“date hubs”) (Han et al., 2004). Perhaps date hubs connect biological modules to each other (Hartwell et al., 1999) while party hubs form scaffolds that enable the assembly of functional modules (Silverman et al., 2004). The overall importance of intrinsic disorder for function of hub proteins was analyzed in several recent bioinformatics publications (Dosztanyi et al., 2006; Ekman et al., 2006; Haynes et al., 2006; Patil & Nakamura, 2006; Singh et al., 2006). Disorder appears to be more clearly associated with date hubs (Ekman et al., 2006; Singh et al., 2006) than with party hubs. However, some protein complexes clearly use long regions of disorder as a scaffold for assembling an interacting group of proteins (Hohenstein & Giles, 2003; Jaffe, Aspenstrom & Hall, 2004; Luo & Lin, 2004; Rui et al., 2004; Wong & Scott, 2004; Jaffe & Hall, 2005; Marinissen & Gutkind, 2005; Salahshor & Woodgett, 2005; Carpousis, 2007).

Due to their malleable nature, IDPs and IDPRs are predisposed to be hubs. In fact, they are commonly involved in one-to-many and in many-to-one binding scenarios. Both of these interaction modes are specific cases of the date hubs, which can bind different proteins, but not at the same time. In the first mechanism, one unfolded segment is used by a protein to interact with multiple unrelated binding partners. In the second mechanism, many unrelated unfolded fragments are used by unrelated proteins to interact with the same partner (Dunker et al., 1998; Oldfield et al., 2008).

To check the set of highly disordered spliceosomal proteins for “hubness”, we utilized the STRING database, which acts as a ‘one-stop shop’ for all information on functional links between proteins (Szklarczyk et al., 2011). Version 9.0 of STRING (accessible at http://string-db.org) covers more than 1100 completely sequenced organisms, including Saccharomyces cerevisiae. Figure 7 represents results of the STRING’ing for the 24 yeast spliceosomal proteins considered in a previous section. Here, the interactome of each of these proteins is shown as an interaction network, where proteins are represented by spheres (note that in each network, the red sphere corresponds to a query protein) and connections between two proteins are shown by lines. The fundamental unit stored in STRING is the “functional association”; i.e., the specific and biologically meaningful functional connection between two proteins (Szklarczyk et al., 2011). These functional associations are based on the seven types of evidence, such as fusion evidence, neighborhood evidence, co-occurrence evidence, experimental evidence, text mining evidence, database evidence, and co-expression evidence (Szklarczyk et al., 2011). These different types of evidence are shown by the lines of different color. It is necessary to emphasize that Fig. 7 is used here with a strictly illustrative purpose; i.e., to show that all of the analyzed spliceosomal proteins are involved in multiple interactions and therefore can be considered as hubs. Since these 24 proteins contain significant amount of predicted disorder and since almost all of them interacts with other spliceosomal proteins many of which are also predicted to be mostly disordered, Fig. 7 suggests that hubness of spliceosomal proteins is related to their intrinsically disordered nature and/or by the intrinsic disorder of their partners.

Figure 7. STRING analysis of the interactomes of illustrative spliceosomal proteins.

Figure 7

Open in a new tab

A. Cwc21; B. Ntc20; C. Isy1/Ntc30; D. Prp45; E. Snu66; F. Cwc15; G. Spp381; H. Syf2; I. Cwc26; J. Slu7; K. Yju2/Cwc16; L. Ntr2; M. Npl3; N. Spp2; O. Bud31; P. SmB; Q. Yhc1; R. Cus1; S. Lin1; T. Prp3; U. LSm4; V. Prp5; W. Cbc2; and X. Msl5. STRING database is the online database resource Search Tool for the Retrieval of Interacting Genes, which provides both experimental and predicted interaction information (Szklarczyk et al., 2011). For each protein, STRING produces the network of predicted associations for a particular group of proteins. The network nodes are proteins. The edges represent the predicted functional associations. An edge may be drawn with up to 7 differently colored lines – these lines represent the existence of the seven types of evidence used in predicting the associations. A red line indicates the presence of fusion evidence; a green line – neighborhood evidence; a blue line – co-occurrence evidence; a purple line – experimental evidence; a yellow line – text mining evidence; a light blue line – database evidence; a black line – co-expression evidence (Szklarczyk et al., 2011).

Concluding Remarks

In this work we have studied the prevalence of intrinsic disorder in the yeast spliceosome in order to test if this complex ribonucleoprotein machine had an enhanced predisposition for intrinsic disorder in comparison with the average proteome. Our results showed that the prevalence of IDPs/IDPRs in the spliceosome was not significantly different from the averaged disorderedness of the eukaryotic proteins. However, being compared with the behavior of an averaged yeast protein, yeast spliceosomal proteins were noticeably more disordered. For example, 46.7% of the spliceosomal proteins were shown to be mostly disordered, whereas the entire yeast proteome contained significantly smaller amount of such proteins (13.3%). Furthermore, ∼61% spliceosomal proteins were shown to possess α-MoRFs, while there were 21.1% of MoRF-containing proteins in the entire yeast proteome. This suggests that the spliceosomal proteins are often engaged in interactions with their protein and RNA partners via disordered regions. More detailed analysis of the most disordered spliceosomal proteins revealed that they are in fact involved in multiple interactions and therefore can be considered as disordered hubs.

Our findings are in a good agreement with the earlier published results on the peculiarities of intrinsic disorder distribution and functions in known human spliceosomal proteins (Korneta & Bujnicki, 2012). The authors of that study concluded that about half of the residues in the human spliceosomal proteome are expected to be intrinsically disordered. Furthermore, a correlation was found between the type of protein disorder and its function and localization within the spliceosome, with the spliceosomal components involved in earlier stages of the splicing process being more disordered than components acting at the later stages (Korneta & Bujnicki, 2012). This enrichment of early proteins in disorder was proposed to play a significant functional role, since proteins of the components of the spliceosome that act earlier in the process are crucial for the establishing a network of interactions (Korneta & Bujnicki, 2012). In agreement with these conclusions Fig. 4 and Table 1 show that yeast spliceosomal proteins related to the complex B are expected to be more disordered than proteins related to the spliceosomal components engaged at the later stages. Therefore, intrinsic disorder is abundant in the yeast spliceosome and is important to assembly and action of this malleable ribonucleoprotein machine.

Funding Statement

This work was supported in part by the Programs of the Russian Academy of Sciences for the “Molecular and Cellular Biology” (to VNU). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Additional Information and Declarations

Competing Interests

Vladimir N. Uversky and Bin Xue are Academic Editors for PeerJ. We do not have other competing interests.

Author Contributions

Maria de Lourdes Coelho Ribeiro and Julio Espinosa performed the experiments, analyzed the data, wrote the paper.

Sameen Islam, Osvaldo Martinez, Jayesh Jamnadas Thanki, Stephanie Mazariegos and Tam Nguyen performed the experiments, wrote the paper.

Maya Larina performed the experiments.

Bin Xue performed the experiments, analyzed the data, contributed reagents/materials/analysis tools.

Vladimir N. Uversky conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper.

References

  • Abelson (2008).Abelson J. Is the spliceosome a ribonucleoprotein enzyme? Nature Structural & Molecular Biology. 2008;15:1235–1237. doi: 10.1038/nsmb1208-1235. [DOI] [PubMed] [Google Scholar]
  • Abovich & Rosbash (1997).Abovich N, Rosbash M. Cross-intron bridging interactions in the yeast commitment complex are conserved in mammals. Cell. 1997;89:403–412. doi: 10.1016/S0092-8674(00)80221-4. [DOI] [PubMed] [Google Scholar]
  • Abu Dayyeh et al. (2002).Abu Dayyeh BK, Quan TK, Castro M, Ruby SW. Probing interactions between the U2 small nuclear ribonucleoprotein and the DEAD-box protein, Prp5. Journal of Biological Chemistry. 2002;277:20221–20233. doi: 10.1074/jbc.M109553200. [DOI] [PubMed] [Google Scholar]
  • Agafonov et al. (2011).Agafonov DE, Deckert J, Wolf E, Odenwalder P, Bessonov S, Will CL, Urlaub H, Luhrmann R. Semiquantitative proteomic analysis of the human spliceosome via a novel two-dimensional gel electrophoresis method. Molecular and Cellular Biology. 2011;31:2667–2682. doi: 10.1128/MCB.05266-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Albers et al. (2003).Albers M, Diment A, Muraru M, Russell CS, Beggs JD. Identification and characterization of Prp45p and Prp46p, essential pre-mRNA splicing factors. RNA. 2003;9:138–150. doi: 10.1261/rna.2119903. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Albuquerque et al. (2008).Albuquerque CP, Smolka MB, Payne SH, Bafna V, Eng J, Zhou H. A multidimensional chromatography technology for in-depth phosphoproteome analysis. Molecular and Cellular Proteomics. 2008;7:1389–1396. doi: 10.1074/mcp.M700468-MCP200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Ansari & Schwer (1995).Ansari A, Schwer B. SLU7 and a novel activity, SSF1, act during the PRP16-dependent step of yeast pre-mRNA splicing. The EMBO Journal. 1995;14:4001–4009. doi: 10.1002/j.1460-2075.1995.tb00071.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Anthony, Weidenhammer & Woolford (1997).Anthony JG, Weidenhammer EM, Woolford JL., Jr The yeast Prp3 protein is a U4/U6 snRNP protein necessary for integrity of the U4/U6 snRNP and the U4/U6.U5 tri-snRNP. RNA. 1997;3:1143–1152. [PMC free article] [PubMed] [Google Scholar]
  • Ben-Yehuda et al. (2000).Ben-Yehuda S, Dix I, Russell CS, McGarvey M, Beggs JD, Kupiec M. Genetic and physical interactions between factors involved in both cell cycle progression and pre-mRNA splicing in Saccharomyces cerevisiae. Genetics. 2000;156:1503–1517. doi: 10.1093/genetics/156.4.1503. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Berman et al. (2000).Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The protein data bank. Nucleic Acids Research. 2000;28:235–242. doi: 10.1093/nar/28.1.235. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Bessonov et al. (2008).Bessonov S, Anokhina M, Will CL, Urlaub H, Luhrmann R. Isolation of an active step I spliceosome and composition of its RNP core. Nature. 2008;452:846–850. doi: 10.1038/nature06842. [DOI] [PubMed] [Google Scholar]
  • Bialkowska & Kurlandzka (2002).Bialkowska A, Kurlandzka A. Proteins interacting with Lin 1p, a putative link between chromosome segregation, mRNA splicing and DNA replication in Saccharomyces cerevisiae. Yeast. 2002;19:1323–1333. doi: 10.1002/yea.919. [DOI] [PubMed] [Google Scholar]
  • Black (1998).Black DL. Splicing in the inner ear: a familiar tune, but what are the instruments? Neuron. 1998;20:165–168. doi: 10.1016/S0896-6273(00)80444-4. [DOI] [PubMed] [Google Scholar]
  • Black (2003).Black DL. Mechanisms of alternative pre-messenger RNA splicing. Annual Review of Biochemistry. 2003;72:291–336. doi: 10.1146/annurev.biochem.72.121801.161720. [DOI] [PubMed] [Google Scholar]
  • Boon et al. (2006).Boon KL, Auchynnikava T, Edwalds-Gilbert G, Barrass JD, Droop AP, Dez C, Beggs JD. Yeast ntr1/spp382 mediates prp43 function in postspliceosomes. Molecular and Cellular Biology. 2006;26:6016–6023. doi: 10.1128/MCB.02347-05. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Bordonne (2000).Bordonne R. Functional characterization of nuclear localization signals in yeast Sm proteins. Molecular and Cellular Biology. 2000;20:7943–7954. doi: 10.1128/MCB.20.21.7943-7954.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Bourhis, Canard & Longhi (2007).Bourhis JM, Canard B, Longhi S. Predicting protein disorder and induced folding: from theoretical principles to practical applications. Current Protein Peptide Science. 2007;8:135–149. doi: 10.2174/138920307780363451. [DOI] [PubMed] [Google Scholar]
  • Bouveret et al. (2000).Bouveret E, Rigaut G, Shevchenko A, Wilm M, Seraphin B. A Sm-like protein complex that participates in mRNA degradation. The EMBO Journal. 2000;19:1661–1671. doi: 10.1093/emboj/19.7.1661. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Brow (2002).Brow DA. Allosteric cascade of spliceosome activation. Annual Review of Genetics. 2002;36:333–360. doi: 10.1146/annurev.genet.36.043002.091635. [DOI] [PubMed] [Google Scholar]
  • Burkard & Butler (2000).Burkard KT, Butler JS. A nuclear 3’-5’ exonuclease involved in mRNA degradation interacts with Poly(A) polymerase and the hnRNA protein Npl3p. Molecular and Cellular Biology. 2000;20:604–616. doi: 10.1128/MCB.20.2.604-616.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Caceres & Kornblihtt (2002).Caceres JF, Kornblihtt AR. Alternative splicing: multiple control mechanisms and involvement in human disease. Trends in Genetics. 2002;18:186–193. doi: 10.1016/S0168-9525(01)02626-9. [DOI] [PubMed] [Google Scholar]
  • Camasses et al. (1998).Camasses A, Bragado-Nilsson E, Martin R, Seraphin B, Bordonne R. Interactions within the yeast Sm core complex: from proteins to amino acids. Molecular and Cellular Biology. 1998;18:1956–1966. doi: 10.1128/mcb.18.4.1956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Campen et al. (2008).Campen A, Williams RM, Brown CJ, Meng J, Uversky VN, Dunker AK. TOP-IDP-scale: a new amino acid scale measuring propensity for intrinsic disorder. Protein Peptide Letters. 2008;15:956–963. doi: 10.2174/092986608785849164. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Carpousis (2007).Carpousis AJ. The RNA degradosome of Escherichia coli: a multiprotein mRNA-degrading machine assembled on RNase E. Annual Review of Microbiology. 2007;61:71–87. doi: 10.1146/annurev.micro.61.080706.093440. [DOI] [PubMed] [Google Scholar]
  • Celotto & Graveley (2001).Celotto AM, Graveley BR. Alternative splicing of the Drosophila Dscam pre-mRNA is both temporally and spatially regulated. Genetics. 2001;159:599–608. doi: 10.1093/genetics/159.2.599. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Chan et al. (2003).Chan SP, Kao DI, Tsai WY, Cheng SC. The Prp19p-associated complex in spliceosome activation. Science. 2003;302:279–282. doi: 10.1126/science.1086602. [DOI] [PubMed] [Google Scholar]
  • Chang, Chen & Cheng (2009).Chang KJ, Chen HC, Cheng SC. Ntc90 is required for recruiting first step factor Yju2 but not for spliceosome activation. RNA. 2009;15:1729–1739. doi: 10.1261/rna.1625309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Chen et al. (2001).Chen CH, Tsai WY, Chen HR, Wang CH, Cheng SC. Identification and characterization of two novel components of the Prp19p-associated complex, Ntc30p and Ntc20p. Journal of Biological Chemistry. 2001;276:488–494. doi: 10.1074/jbc.M006958200. [DOI] [PubMed] [Google Scholar]
  • Chen et al. (2002).Chen CH, Yu WC, Tsao TY, Wang LY, Chen HR, Lin JY, Tsai WY, Cheng SC. Functional and physical interactions between components of the Prp19p-associated complex. Nucleic Acids Research. 2002;30:1029–1037. doi: 10.1093/nar/30.4.1029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Cheng et al. (2007).Cheng Y, Oldfield CJ, Meng J, Romero P, Uversky VN, Dunker AK. Mining alpha-helix-forming molecular recognition features with cross species sequence alignments. Biochemistry. 2007;46:13468–13477. doi: 10.1021/bi7012273. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Cortese, Uversky & Dunker (2008).Cortese MS, Uversky VN, Dunker AK. Intrinsic disorder in scaffold proteins: getting more from less. Progress in Biophysics and Molecular Biology. 2008;98:85–106. doi: 10.1016/j.pbiomolbio.2008.05.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Dahan & Kupiec (2002).Dahan O, Kupiec M. Mutations in genes of Saccharomyces cerevisiae encoding pre-mRNA splicing factors cause cell cycle arrest through activation of the spindle checkpoint. Nucleic Acids Research. 2002;30:4361–4370. doi: 10.1093/nar/gkf563. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Daughdrill et al. (2005).Daughdrill GW, Pielak GJ, Uversky VN, Cortese MS, Dunker AK. Natively disordered proteins. In: Buchner J, Kiefhaber T, editors. Handbook of protein folding. Weinheim, Germany: Wiley-VCH, Verlag GmbH and Co.; 2005. pp. 271–353. [Google Scholar]
  • Dix et al. (1999).Dix I, Russell C, Yehuda SB, Kupiec M, Beggs JD. The identification and characterization of a novel splicing protein, Isy1p, of Saccharomyces cerevisiae. RNA. 1999;5:360–368. doi: 10.1017/S1355838299981396. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Dosztanyi, Meszaros & Simon (2009).Dosztanyi Z, Meszaros B, Simon I. ANCHOR: web server for predicting protein binding regions in disordered proteins. Bioinformatics. 2009;25:2745–2746. doi: 10.1093/bioinformatics/btp518. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Dosztanyi et al. (2005a).Dosztanyi Z, Csizmok V, Tompa P, Simon I. IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics. 2005a;21:3433–3434. doi: 10.1093/bioinformatics/bti541. [DOI] [PubMed] [Google Scholar]
  • Dosztanyi et al. (2005b).Dosztanyi Z, Csizmok V, Tompa P, Simon I. The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. Journal of Molecular Biology. 2005b;347:827–839. doi: 10.1016/j.jmb.2005.01.071. [DOI] [PubMed] [Google Scholar]
  • Dosztanyi et al. (2006).Dosztanyi Z, Chen J, Dunker AK, Simon I, Tompa P. Disorder and sequence repeats in hub proteins and their implications for network evolution. Journal of Proteome Research. 2006;5:2985–2995. doi: 10.1021/pr060171o. [DOI] [PubMed] [Google Scholar]
  • Du & Rosbash (2002).Du H, Rosbash M. The U1 snRNP protein U1C recognizes the 5’ splice site in the absence of base pairing. Nature. 2002;419:86–90. doi: 10.1038/nature00947. [DOI] [PubMed] [Google Scholar]
  • Dunker & Obradovic (2001).Dunker AK, Obradovic Z. The protein trinity–linking function and disorder. Nature Biotechnology. 2001;19:805–806. doi: 10.1038/nbt0901-805. [DOI] [PubMed] [Google Scholar]
  • Dunker & Uversky (2008).Dunker AK, Uversky VN. Signal transduction via unstructured protein conduits. Nature Chemical Biology. 2008;4:229–230. doi: 10.1038/nchembio0408-229. [DOI] [PubMed] [Google Scholar]
  • Dunker, Brown & Obradovic (2002).Dunker AK, Brown CJ, Obradovic Z. Identification and functions of usefully disordered proteins. Advances in Protein Chemistry. 2002;62:25–49. doi: 10.1016/S0065-3233(02)62004-2. [DOI] [PubMed] [Google Scholar]
  • Dunker et al. (2008a).Dunker AK, Silman I, Uversky VN, Sussman JL. Function and structure of inherently disordered proteins. Current Opinion in Structural Biology. 2008a;18:756–764. doi: 10.1016/j.sbi.2008.10.002. [DOI] [PubMed] [Google Scholar]
  • Dunker et al. (2000).Dunker AK, Obradovic Z, Romero P, Garner EC, Brown CJ. Intrinsic protein disorder in complete genomes. Genome Inform Ser Workshop Genome Inform. 2000;11:161–171. [PubMed] [Google Scholar]
  • Dunker et al. (2002).Dunker AK, Brown CJ, Lawson JD, Iakoucheva LM, Obradovic Z. Intrinsic disorder and protein function. Biochemistry. 2002;41:6573–6582. doi: 10.1021/bi012159+. [DOI] [PubMed] [Google Scholar]
  • Dunker et al. (2005).Dunker AK, Cortese MS, Romero P, Iakoucheva LM, Uversky VN. Flexible nets: the roles of intrinsic disorder in protein interaction networks. FEBS Journal. 2005;272:5129–5148. doi: 10.1111/j.1742-4658.2005.04948.x. [DOI] [PubMed] [Google Scholar]
  • Dunker et al. (1998).Dunker AK, Garner E, Guilliot S, Romero P, Albrecht K, Hart J, Obradovic Z, Kissinger C, Villafranca JE. Protein disorder and the evolution of molecular recognition: theory, predictions and observations. Pacific Symposium on Biocomputing. 1998:473–484. [PubMed] [Google Scholar]
  • Dunker et al. (2008b).Dunker AK, Oldfield CJ, Meng J, Romero P, Yang JY, Chen JW, Vacic V, Obradovic Z, Uversky VN. The unfoldomics decade: an update on intrinsically disordered proteins. BMC Genomics. 2008b;9(Suppl 2):S1. doi: 10.1186/1471-2164-9-S2-S1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Dunker et al. (2001).Dunker AK, Lawson JD, Brown CJ, Williams RM, Romero P, Oh JS, Oldfield CJ, Campen AM, Ratliff CM, Hipps KW, Ausio J, Nissen MS, Reeves R, Kang C, Kissinger CR, Bailey RW, Griswold MD, Chiu W, Garner EC, Obradovic Z. Intrinsically disordered protein. Journal of Molecular Graphics & Modelling. 2001;19:26–59. doi: 10.1016/S1093-3263(00)00138-8. [DOI] [PubMed] [Google Scholar]
  • Dyson & Wright (2002).Dyson HJ, Wright PE. Coupling of folding and binding for unstructured proteins. Current Opinion in Structural Biology. 2002;12:54–60. doi: 10.1016/S0959-440X(02)00289-0. [DOI] [PubMed] [Google Scholar]
  • Dyson & Wright (2005).Dyson HJ, Wright PE. Intrinsically unstructured proteins and their functions. Nature Reviews. Molecular Cell Biology. 2005;6:197–208. doi: 10.1038/nrm1589. [DOI] [PubMed] [Google Scholar]
  • Dziembowski et al. (2004).Dziembowski A, Ventura AP, Rutz B, Caspary F, Faux C, Halgand F, Laprevote O, Seraphin B. Proteomic analysis identifies a new complex required for nuclear pre-mRNA retention and splicing. The EMBO Journal. 2004;23:4847–4856. doi: 10.1038/sj.emboj.7600482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Ekman et al. (2006).Ekman D, Light S, Bjorklund AK, Elofsson A. What properties characterize the hub proteins of the protein–protein interaction network of Saccharomyces cerevisiae? Genome Biology. 2006;7 doi: 10.1186/gb-2006-7-6-r45. R45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Fabrizio et al. (2009).Fabrizio P, Dannenberg J, Dube P, Kastner B, Stark H, Urlaub H, Luhrmann R. The evolutionarily conserved core design of the catalytic activation step of the yeast spliceosome. Molecular Cell. 2009;36:593–608. doi: 10.1016/j.molcel.2009.09.040. [DOI] [PubMed] [Google Scholar]
  • Ferron et al. (2006).Ferron F, Longhi S, Canard B, Karlin D. A practical overview of protein disorder prediction methods. Proteins. 2006;65:1–14. doi: 10.1002/prot.21075. [DOI] [PubMed] [Google Scholar]
  • Figueroa & Hayman (2004).Figueroa JD, Hayman MJ. The human Ski-interacting protein functionally substitutes for the yeast PRP45 gene. Biochemical and Biophysical Research Communications. 2004;319:1105–1109. doi: 10.1016/j.bbrc.2004.05.096. [DOI] [PubMed] [Google Scholar]
  • Fortes et al. (1999).Fortes P, Kufel J, Fornerod M, Polycarpou-Schwarz M, Lafontaine D, Tollervey D, Mattaj IW. Genetic and physical interactions involving the yeast nuclear cap-binding complex. Molecular and Cellular Biology. 1999;19:6543–6553. doi: 10.1128/mcb.19.10.6543. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Frank & Guthrie (1992).Frank D, Guthrie C. An essential splicing factor, SLU7, mediates 3’ splice site choice in yeast. Genes and Development. 1992;6:2112–2124. doi: 10.1101/gad.6.11.2112. [DOI] [PubMed] [Google Scholar]
  • Freund et al. (1999).Freund C, Dotsch V, Nishizawa K, Reinherz EL, Wagner G. The GYF domain is a novel structural fold that is involved in lymphoid signaling through proline-rich sequences. Nature Structural Biology. 1999;6:656–660. doi: 10.1038/10712. [DOI] [PubMed] [Google Scholar]
  • Gahura et al. (2009).Gahura O, Abrhamova K, Skruzny M, Valentova A, Munzarova V, Folk P, Puta F. Prp45 affects Prp22 partition in spliceosomal complexes and splicing efficiency of non-consensus substrates. Journal of Cellular Biochemistry. 2009;106:139–151. doi: 10.1002/jcb.21989. [DOI] [PubMed] [Google Scholar]
  • Garner et al. (1999).Garner E, Romero P, Dunker AK, Brown C, Obradovic Z. Predicting binding regions within disordered proteins. Genome Inform Ser Workshop Genome Inform. 1999;10:41–50. [PubMed] [Google Scholar]
  • Grainger et al. (2009).Grainger RJ, Barrass JD, Jacquier A, Rain JC, Beggs JD. Physical and genetic interactions of yeast Cwc21p, an ortholog of human SRm300/SRRM2, suggest a role at the catalytic center of the spliceosome. RNA. 2009;15:2161–2173. doi: 10.1261/rna.1908309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Graveley (2001).Graveley BR. Alternative splicing: increasing diversity in the proteomic world. Trends in Genetics. 2001;17:100–107. doi: 10.1016/S0168-9525(00)02176-4. [DOI] [PubMed] [Google Scholar]
  • Gregorio et al. (1999).Gregorio CC, Granzier H, Sorimachi H, Labeit S. Muscle assembly: a titanic achievement? Current Opinion in Cell Biology. 1999;11:18–25. doi: 10.1016/S0955-0674(99)80003-9. [DOI] [PubMed] [Google Scholar]
  • Guo et al. (2010).Guo W, Bharmal SJ, Esbona K, Greaser ML. Titin diversity–alternative splicing gone wild. Journal of Biomedical Biotechnology. 2010;2010:753675. doi: 10.1155/2010/753675. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Han et al. (2004).Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M. Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature. 2004;430:88–93. doi: 10.1038/nature02555. [DOI] [PubMed] [Google Scholar]
  • Hartwell et al. (1999).Hartwell LH, Hopfield JJ, Leibler S, Murray AW. From molecular to modular cell biology. Nature. 1999;402 doi: 10.1038/35011540. C47–52. [DOI] [PubMed] [Google Scholar]
  • Haynes & Iakoucheva (2006).Haynes C, Iakoucheva LM. Serine/arginine-rich splicing factors belong to a class of intrinsically disordered proteins. Nucleic Acids Research. 2006;34:305–312. doi: 10.1093/nar/gkj424. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Haynes et al. (2006).Haynes C, Oldfield CJ, Ji F, Klitgord N, Cusick ME, Radivojac P, Uversky VN, Vidal M, Iakoucheva LM. Intrinsic disorder is a common feature of hub proteins from four eukaryotic interactomes. PLoS Computational Biology. 2006;2 doi: 10.1371/journal.pcbi.0020100. e100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • He et al. (2009).He B, Wang K, Liu Y, Xue B, Uversky VN, Dunker AK. Predicting intrinsic disorder in proteins: an overview. Cell Research. 2009;19:929–949. doi: 10.1038/cr.2009.87. [DOI] [PubMed] [Google Scholar]
  • Hogg, McGrail & O’Keefe (2010).Hogg R, McGrail JC, O’Keefe RT. The function of the NineTeen Complex (NTC) in regulating spliceosome conformations and fidelity during pre-mRNA splicing. Biochemical Society Transactions. 2010;38:1110–1115. doi: 10.1042/BST0381110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Hohenstein & Giles (2003).Hohenstein P, Giles RH. BRCA1: a scaffold for p53 response? Trends in Genetics. 2003;19:489–494. doi: 10.1016/S0168-9525(03)00193-8. [DOI] [PubMed] [Google Scholar]
  • Hsu et al. (2012).Hsu WL, Oldfield C, Meng J, Huang F, Xue B, Uversky VN, Romero P, Dunker AK. Intrinsic protein disorder and protein–protein interactions. Pacific Symposium on Biocomputing. 2012:116–127. [PubMed] [Google Scholar]
  • Huang et al. (2012).Huang F, Oldfield C, Meng J, Hsu WL, Xue B, Uversky VN, Romero P, Dunker AK. Subclassifying disordered proteins by the ch-cdf plot method. Pacific Symposium on Biocomputing. 2012:128–139. [PubMed] [Google Scholar]
  • Humphrey, Dalke & Schulten (1996).Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. Journal of Molecular Graphics & Modelling. 1996;14:27–28. doi: 10.1016/0263-7855(96)00018-5. [DOI] [PubMed] [Google Scholar]
  • Iakoucheva et al. (2002).Iakoucheva LM, Brown CJ, Lawson JD, Obradovic Z, Dunker AK. Intrinsic disorder in cell-signaling and cancer-associated proteins. Journal of Molecular Biology. 2002;323:573–584. doi: 10.1016/S0022-2836(02)00969-5. [DOI] [PubMed] [Google Scholar]
  • Jaffe & Hall (2005).Jaffe AB, Hall A. Rho GTPases: biochemistry and biology. Annual Review of Cell and Developmental Biology. 2005;21:247–269. doi: 10.1146/annurev.cellbio.21.020604.150721. [DOI] [PubMed] [Google Scholar]
  • Jaffe, Aspenstrom & Hall (2004).Jaffe AB, Aspenstrom P, Hall A. Human CNK1 acts as a scaffold protein, linking Rho and Ras signal transduction pathways. Molecular and Cellular Biology. 2004;24:1736–1746. doi: 10.1128/MCB.24.4.1736-1746.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • James, Turner & Schwer (2002).James SA, Turner W, Schwer B. How Slu7 and Prp18 cooperate in the second step of yeast pre-mRNA splicing. RNA. 2002;8:1068–1077. doi: 10.1017/S1355838202022033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kambach, Walke & Nagai (1999).Kambach C, Walke S, Nagai K. Structure and assembly of the spliceosomal small nuclear ribonucleoprotein particles. Current Opinion in Structural Biology. 1999;9:222–230. doi: 10.1016/S0959-440X(99)80032-3. [DOI] [PubMed] [Google Scholar]
  • Kambach et al. (1999).Kambach C, Walke S, Young R, Avis JM, de la Fortelle E, Raker VA, Luhrmann R, Li J, Nagai K. Crystal structures of two Sm protein complexes and their implications for the assembly of the spliceosomal snRNPs. Cell. 1999;96:375–387. doi: 10.1016/S0092-8674(00)80550-4. [DOI] [PubMed] [Google Scholar]
  • Khanna et al. (2009).Khanna M, Van Bakel H, Tang X, Calarco JA, Babak T, Guo G, Emili A, Greenblatt JF, Hughes TR, Krogan NJ, Blencowe BJ. A systematic characterization of Cwc21, the yeast ortholog of the human spliceosomal protein SRm300. RNA. 2009;15:2174–2185. doi: 10.1261/rna.1790509. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kofler, Motzny & Freund (2005).Kofler M, Motzny K, Freund C. GYF domain proteomics reveals interaction sites in known and novel target proteins. Molecular and Cellular Proteomics. 2005;4:1797–1811. doi: 10.1074/mcp.M500129-MCP200. [DOI] [PubMed] [Google Scholar]
  • Korneta & Bujnicki (2012).Korneta I, Bujnicki JM. Intrinsic disorder in the human spliceosomal proteome. PLoS Computational Biology. 2012;8 doi: 10.1371/journal.pcbi.1002641. e1002641. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kreahling & Graveley (2005).Kreahling JM, Graveley BR. The iStem, a long-range RNA secondary structure element required for efficient exon inclusion in the Drosophila Dscam pre-mRNA. Molecular and Cellular Biology. 2005;25:10251–10260. doi: 10.1128/MCB.25.23.10251-10260.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kufel et al. (2004).Kufel J, Bousquet-Antonelli C, Beggs JD, Tollervey D. Nuclear pre-mRNA decapping and 5’ degradation in yeast require the Lsm2-8p complex. Molecular and Cellular Biology. 2004;24:9646–9657. doi: 10.1128/MCB.24.21.9646-9657.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kufel et al. (2002).Kufel J, Allmang C, Verdone L, Beggs JD, Tollervey D. Lsm proteins are required for normal processing of pre-tRNAs and their efficient association with La-homologous protein Lhp1p. Molecular and Cellular Biology. 2002;22:5248–5256. doi: 10.1128/MCB.22.14.5248-5256.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kufel et al. (2003).Kufel J, Allmang C, Petfalski E, Beggs J, Tollervey D. Lsm Proteins are required for normal processing and stability of ribosomal RNAs. Journal of Biological Chemistry. 2003;278:2147–2156. doi: 10.1074/jbc.M208856200. [DOI] [PubMed] [Google Scholar]
  • LeWinter et al. (2007).LeWinter MM, Wu Y, Labeit S, Granzier H. Cardiac titin: structure, functions and role in disease. Clinica Chimica ACTA. 2007;375:1–9. doi: 10.1016/j.cca.2006.06.035. [DOI] [PubMed] [Google Scholar]
  • Lewis, Gorlich & Mattaj (1996).Lewis JD, Gorlich D, Mattaj IW. A yeast cap binding protein complex (yCBC) acts at an early step in pre-mRNA splicing. Nucleic Acids Research. 1996;24:3332–3336. doi: 10.1093/nar/24.17.3332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Liu et al. (2007).Liu YC, Chen HC, Wu NY, Cheng SC. A novel splicing factor, Yju2, is associated with NTC and acts after Prp2 in promoting the first catalytic reaction of pre-mRNA splicing. Molecular and Cellular Biology. 2007;27:5403–5413. doi: 10.1128/MCB.00346-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Luo & Lin (2004).Luo W, Lin SC. Axin: a master scaffold for multiple signaling pathways. Neurosignals. 2004;13:99–113. doi: 10.1159/000076563. [DOI] [PubMed] [Google Scholar]
  • Lybarger et al. (1999).Lybarger S, Beickman K, Brown V, Dembla-Rajpal N, Morey K, Seipelt R, Rymond BC. Elevated levels of a U4/U6.U5 snRNP-associated protein, Spp381p, rescue a mutant defective in spliceosome maturation. Molecular and Cellular Biology. 1999;19:577–584. doi: 10.1128/mcb.19.1.577. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Marinissen & Gutkind (2005).Marinissen MJ, Gutkind JS. Scaffold proteins dictate Rho GTPase-signaling specificity. Trends in Biochemical Sciences. 2005;30:423–426. doi: 10.1016/j.tibs.2005.06.006. [DOI] [PubMed] [Google Scholar]
  • Martinkova et al. (2002).Martinkova K, Lebduska P, Skruzny M, Folk P, Puta F. Functional mapping of Saccharomyces cerevisiae Prp45 identifies the SNW domain as essential for viability. Journal of Biochemistry. 2002;132:557–563. doi: 10.1093/oxfordjournals.jbchem.a003257. [DOI] [PubMed] [Google Scholar]
  • Maruyama (1997).Maruyama K. Connectin/titin, giant elastic protein of muscle. FASEB Journal. 1997;11:341–345. doi: 10.1096/fasebj.11.5.9141500. [DOI] [PubMed] [Google Scholar]
  • Meszaros, Simon & Dosztanyi (2009).Meszaros B, Simon I, Dosztanyi Z. Prediction of protein binding regions in disordered proteins. PLoS Computational Biology. 2009;5 doi: 10.1371/journal.pcbi.1000376. e1000376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Mishra et al. (2011).Mishra SK, Ammon T, Popowicz GM, Krajewski M, Nagel RJ, Ares M, Jr, Holak TA, Jentsch S. Role of the ubiquitin-like protein Hub1 in splice-site usage and alternative splicing. Nature. 2011;474:173–178. doi: 10.1038/nature10143. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Mohan et al. (2008).Mohan A, Sullivan WJ, Jr, Radivojac P, Dunker AK, Uversky VN. Intrinsic disorder in pathogenic and non-pathogenic microbes: discovering and analyzing the unfoldomes of early-branching eukaryotes. Molecular Biosystems. 2008;4:328–340. doi: 10.1039/b719168e. [DOI] [PubMed] [Google Scholar]
  • Mohan et al. (2006).Mohan A, Oldfield CJ, Radivojac P, Vacic V, Cortese MS, Dunker AK, Uversky VN. Analysis of molecular recognition features (MoRFs) Journal of Molecular Biology. 2006;362:1043–1059. doi: 10.1016/j.jmb.2006.07.087. [DOI] [PubMed] [Google Scholar]
  • Ni & Snyder (2001).Ni L, Snyder M. A genomic study of the bipolar bud site selection pattern in Saccharomyces cerevisiae. Molecular Biological Cell. 2001;12:2147–2170. doi: 10.1091/mbc.12.7.2147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Nilsen & Graveley (2010).Nilsen TW, Graveley BR. Expansion of the eukaryotic proteome by alternative splicing. Nature. 2010;463:457–463. doi: 10.1038/nature08909. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Novoyatleva et al. (2006).Novoyatleva T, Tang Y, Rafalska I, Stamm S. Pre-mRNA missplicing as a cause of human disease. Progress in Molecular and Subcellular Biology. 2006;44:27–46. doi: 10.1007/978-3-540-34449-0_2. [DOI] [PubMed] [Google Scholar]
  • O’Day, Dalbadie-McFarland & Abelson (1996).O’Day CL, Dalbadie-McFarland G, Abelson J. The Saccharomyces cerevisiae Prp5 protein has RNA-dependent ATPase activity with specificity for U2 small nuclear RNA. Journal of Biological Chemistry. 1996;271:33261–33267. doi: 10.1074/jbc.271.52.33261. [DOI] [PubMed] [Google Scholar]
  • Ohi et al. (2002).Ohi MD, Link AJ, Ren L, Jennings JL, McDonald WH, Gould KL. Proteomics analysis reveals stable multiprotein complexes in both fission and budding yeasts containing Myb-related Cdc5p/Cef1p, novel pre-mRNA splicing factors, and snRNAs. Molecular and Cellular Biology. 2002;22:2011–2024. doi: 10.1128/MCB.22.7.2011-2024.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Oldfield et al. (2005a).Oldfield CJ, Cheng Y, Cortese MS, Romero P, Uversky VN, Dunker AK. Coupled folding and binding with alpha-helix-forming molecular recognition elements. Biochemistry. 2005a;44:12454–12470. doi: 10.1021/bi050736e. [DOI] [PubMed] [Google Scholar]
  • Oldfield et al. (2005b).Oldfield CJ, Cheng Y, Cortese MS, Brown CJ, Uversky VN, Dunker AK. Comparing and combining predictors of mostly disordered proteins. Biochemistry. 2005b;44:1989–2000. doi: 10.1021/bi047993o. [DOI] [PubMed] [Google Scholar]
  • Oldfield et al. (2008).Oldfield CJ, Meng J, Yang JY, Yang MQ, Uversky VN, Dunker AK. Flexible nets: disorder and induced fit in the associations of p53 and 14-3-3 with their partners. BMC Genomics. 2008;9(Suppl 1):S1. doi: 10.1186/1471-2164-9-S1-S1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Pan et al. (2008).Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nature Genetics. 2008;40:1413–1415. doi: 10.1038/ng.259. [DOI] [PubMed] [Google Scholar]
  • Patel & Steitz (2003).Patel AA, Steitz JA. Splicing double: insights from the second spliceosome. Nature Reviews. Molecular Cell Biology. 2003;4:960–970. doi: 10.1038/nrm1259. [DOI] [PubMed] [Google Scholar]
  • Patil & Nakamura (2006).Patil A, Nakamura H. Disordered domains and high surface charge confer hubs with the ability to interact with multiple proteins in interaction networks. FEBS Letters. 2006;580:2041–2045. doi: 10.1016/j.febslet.2006.03.003. [DOI] [PubMed] [Google Scholar]
  • Pauling, McPheeters & Ares (2000).Pauling MH, McPheeters DS, Ares M., Jr Functional Cus1p is found with Hsh155p in a multiprotein splicing factor associated with U2 snRNA. Molecular and Cellular Biology. 2000;20:2176–2185. doi: 10.1128/MCB.20.6.2176-2185.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Peng et al. (2006).Peng K, Radivojac P, Vucetic S, Dunker AK, Obradovic Z. Length-dependent prediction of protein intrinsic disorder. BMC Bioinformatics. 2006;7:208. doi: 10.1186/1471-2105-7-208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Peng et al. (2005).Peng K, Vucetic S, Radivojac P, Brown CJ, Dunker AK, Obradovic Z. Optimizing long intrinsic disorder predictors with protein evolutionary information. Journal of Bioinformatics and Computational Biology. 2005;3:35–60. doi: 10.1142/S0219720005000886. [DOI] [PubMed] [Google Scholar]
  • Prilusky et al. (2005).Prilusky J, Felder CE, Zeev-Ben-Mordehai T, Rydberg EH, Man O, Beckmann JS, Silman I, Sussman JL. FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics. 2005;21:3435–3438. doi: 10.1093/bioinformatics/bti537. [DOI] [PubMed] [Google Scholar]
  • Pyle (2008).Pyle AM. Translocation and unwinding mechanisms of RNA and DNA helicases. Annual Review of Biophysics. 2008;37:317–336. doi: 10.1146/annurev.biophys.37.032807.125908. [DOI] [PubMed] [Google Scholar]
  • Qiu et al. (2012).Qiu ZR, Chico L, Chang J, Shuman S, Schwer B. Genetic interactions of hypomorphic mutations in the m7G cap-binding pocket of yeast nuclear cap binding complex: an essential role for Cbc2 in meiosis via splicing of MER3 pre-mRNA. RNA. 2012;18:1996–2011. doi: 10.1261/rna.033746.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Query, Strobel & Sharp (1996).Query CC, Strobel SA, Sharp PA. Three recognition events at the branch-site adenine. The EMBO Journal. 1996;15:1392–1402. [PMC free article] [PubMed] [Google Scholar]
  • Radivojac et al. (2007).Radivojac P, Iakoucheva LM, Oldfield CJ, Obradovic Z, Uversky VN, Dunker AK. Intrinsic disorder and functional proteomics. Biophysical Journal. 2007;92:1439–1456. doi: 10.1529/biophysj.106.094045. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Rajagopalan et al. (2011).Rajagopalan K, Mooney SM, Parekh N, Getzenberg RH, Kulkarni P. A majority of the cancer/testis antigens are intrinsically disordered proteins. Journal of Cellular Biochemistry. 2011;112:3256–3267. doi: 10.1002/jcb.23252. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Reijns, Auchynnikava & Beggs (2009).Reijns MA, Auchynnikava T, Beggs JD. Analysis of Lsm1p and Lsm8p domains in the cellular localization of Lsm complexes in budding yeast. FEBS Journal. 2009;276:3602–3617. doi: 10.1111/j.1742-4658.2009.07080.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Romero et al. (2001).Romero P, Obradovic Z, Li X, Garner EC, Brown CJ, Dunker AK. Sequence complexity of disordered protein. Proteins. 2001;42:38–48. doi: 10.1002/1097-0134(20010101)42:1&#x0003c;38::AID-PROT50&#x0003e;3.0.CO;2-3. [DOI] [PubMed] [Google Scholar]
  • Romero et al. (2006).Romero PR, Zaidi S, Fang YY, Uversky VN, Radivojac P, Oldfield CJ, Cortese MS, Sickmeier M, LeGall T, Obradovic Z, Dunker AK. Alternative splicing in concert with protein intrinsic disorder enables increased functional diversity in multicellular organisms. Proceedings of the National Academy of Sciences of the United States of America. 2006;103:8390–8395. doi: 10.1073/pnas.0507916103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Roscigno & Garcia-Blanco (1995).Roscigno RF, Garcia-Blanco MA. SR proteins escort the U4/U6.U5 tri-snRNP to the spliceosome. RNA. 1995;1:692–706. [PMC free article] [PubMed] [Google Scholar]
  • Roy et al. (1995).Roy J, Kim K, Maddock JR, Anthony JG, Woolford JL., Jr The final stages of spliceosome maturation require Spp2p that can interact with the DEAH box protein Prp2p and promote step 1 of splicing. RNA. 1995;1:375–390. [PMC free article] [PubMed] [Google Scholar]
  • Ruby, Chang & Abelson (1993).Ruby SW, Chang TH, Abelson J. Four yeast spliceosomal proteins (PRP5, PRP9, PRP11, and PRP21) interact to promote U2 snRNP binding to pre-mRNA. Genes and Development. 1993;7:1909–1925. doi: 10.1101/gad.7.10.1909. [DOI] [PubMed] [Google Scholar]
  • Rui et al. (2004).Rui Y, Xu Z, Lin S, Li Q, Rui H, Luo W, Zhou HM, Cheung PY, Wu Z, Ye Z, Li P, Han J, Lin SC. Axin stimulates p53 functions by activation of HIPK2 kinase through multimeric complex formation. The EMBO Journal. 2004;23:4583–4594. doi: 10.1038/sj.emboj.7600475. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Russell et al. (2000).Russell CS, Ben-Yehuda S, Dix I, Kupiec M, Beggs JD. Functional analyses of interacting factors involved in both pre-mRNA splicing and cell cycle progression in Saccharomyces cerevisiae. RNA. 2000;6:1565–1572. doi: 10.1017/S1355838200000984. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Russell & Gibson (2008).Russell RB, Gibson TJ. A careful disorderliness in the proteome: sites for interaction and targets for future therapies. FEBS Letters. 2008;582:1271–1275. doi: 10.1016/j.febslet.2008.02.027. [DOI] [PubMed] [Google Scholar]
  • Rutz & Seraphin (1999).Rutz B, Seraphin B. Transient interaction of BBP/ScSF1 and Mud2 with the splicing machinery affects the kinetics of spliceosome assembly. RNA. 1999;5:819–831. doi: 10.1017/S1355838299982286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Rutz & Seraphin (2000).Rutz B, Seraphin B. A dual role for BBP/ScSF1 in nuclear pre-mRNA retention and splicing. The EMBO Journal. 2000;19:1873–1886. doi: 10.1093/emboj/19.8.1873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Saha et al. (2012a).Saha D, Banerjee S, Bashir S, Vijayraghavan U. Context dependent splicing functions of Bud31/Ycr063w define its role in budding and cell cycle progression. Biochemical and Biophysical Research Communications. 2012a;424:579–585. doi: 10.1016/j.bbrc.2012.06.156. [DOI] [PubMed] [Google Scholar]
  • Saha et al. (2012b).Saha D, Khandelia P, O’Keefe RT, Vijayraghavan U. Saccharomyces cerevisiae NineTeen complex (NTC)-associated factor Bud31/Ycr063w assembles on precatalytic spliceosomes and improves first and second step pre-mRNA splicing efficiency. Journal of Biological Chemistry. 2012b;287:5390–5399. doi: 10.1074/jbc.M111.298547. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Salahshor & Woodgett (2005).Salahshor S, Woodgett JR. The links between axin and carcinogenesis. Journal of Clinical Pathology. 2005;58:225–236. doi: 10.1136/jcp.2003.009506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Schad, Tompa & Hegyi (2011).Schad E, Tompa P, Hegyi H. The relationship between proteome size, structural disorder and organism complexity. Genome Biology. 2011;12 doi: 10.1186/gb-2011-12-12-r120. R120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Schmucker et al. (2000).Schmucker D, Clemens JC, Shu H, Worby CA, Xiao J, Muda M, Dixon JE, Zipursky SL. Drosophila Dscam is an axon guidance receptor exhibiting extraordinary molecular diversity. Cell. 2000;101:671–684. doi: 10.1016/S0092-8674(00)80878-8. [DOI] [PubMed] [Google Scholar]
  • Sickmeier et al. (2007).Sickmeier M, Hamilton JA, LeGall T, Vacic V, Cortese MS, Tantos A, Szabo B, Tompa P, Chen J, Uversky VN, Obradovic Z, Dunker AK. DisProt: the database of disordered proteins. Nucleic Acids Research. 2007;35 doi: 10.1093/nar/gkl893. D786–793. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Silverman et al. (2004).Silverman EJ, Maeda A, Wei J, Smith P, Beggs JD, Lin RJ. Interaction between a G-patch protein and a spliceosomal DEXD/H-box ATPase that is critical for splicing. Molecular and Cellular Biology. 2004;24:10101–10110. doi: 10.1128/MCB.24.23.10101-10110.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Singh et al. (2006).Singh GP, Ganapathi M, Sandhu KS, Dash D. Intrinsic unstructuredness and abundance of PEST motifs in eukaryotic proteomes. Proteins. 2006;62:309–315. doi: 10.1002/prot.20746. [DOI] [PubMed] [Google Scholar]
  • Skrisovska & Allain (2008).Skrisovska L, Allain FH. Improved segmental isotope labeling methods for the NMR study of multidomain or large proteins: application to the RRMs of Npl3p and hnRNP L. Journal of Molecular Biology. 2008;375:151–164. doi: 10.1016/j.jmb.2007.09.030. [DOI] [PubMed] [Google Scholar]
  • Spadaccini et al. (2006).Spadaccini R, Reidt U, Dybkov O, Will C, Frank R, Stier G, Corsini L, Wahl MC, Luhrmann R, Sattler M. Biochemical and NMR analyses of an SF3b155-p14-U2AF-RNA interaction network involved in branch point definition during pre-mRNA splicing. RNA. 2006;12:410–425. doi: 10.1261/rna.2271406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Spiller et al. (2007).Spiller MP, Boon KL, Reijns MA, Beggs JD. The Lsm2-8 complex determines nuclear localization of the spliceosomal U6 snRNA. Nucleic Acids Research. 2007;35:923–929. doi: 10.1093/nar/gkl1130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Stevens & Abelson (1999).Stevens SW, Abelson J. Purification of the yeast U4/U6.U5 small nuclear ribonucleoprotein particle and identification of its proteins. Proceedings of the National Academy of Sciences of the United States of America. 1999;96:7226–7231. doi: 10.1073/pnas.96.13.7226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Stevens et al. (2001).Stevens SW, Barta I, Ge HY, Moore RE, Young MK, Lee TD, Abelson J. Biochemical and genetic analyses of the U5, U6, and U4/U6 x U5 small nuclear ribonucleoproteins from Saccharomyces cerevisiae. RNA. 2001;7:1543–1553. [PMC free article] [PubMed] [Google Scholar]
  • Szklarczyk et al. (2011).Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P, Jensen LJ, von Mering C. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Research. 2011;39 doi: 10.1093/nar/gkq973. D561–568. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Tang et al. (1997).Tang J, Abovich N, Fleming ML, Seraphin B, Rosbash M. Identification and characterization of a yeast homolog of U1 snRNP-specific protein C. The EMBO Journal. 1997;16:4082–4091. doi: 10.1093/emboj/16.13.4082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Tharun et al. (2000).Tharun S, He W, Mayes AE, Lennertz P, Beggs JD, Parker R. Yeast Sm-like proteins function in mRNA decapping and decay. Nature. 2000;404:515–518. doi: 10.1038/35006676. [DOI] [PubMed] [Google Scholar]
  • Tompa (2002).Tompa P. Intrinsically unstructured proteins. Trends in Biochemical Sciences. 2002;27:527–533. doi: 10.1016/S0968-0004(02)02169-2. [DOI] [PubMed] [Google Scholar]
  • Tompa (2005).Tompa P. The interplay between structure and function in intrinsically unstructured proteins. FEBS Letters. 2005;579:3346–3354. doi: 10.1016/j.febslet.2005.03.072. [DOI] [PubMed] [Google Scholar]
  • Tompa & Csermely (2004).Tompa P, Csermely P. The role of structural disorder in the function of RNA and protein chaperones. The FASEB Journal. 2004;18:1169–1175. doi: 10.1096/fj.04-1584rev. [DOI] [PubMed] [Google Scholar]
  • Tompa & Fuxreiter (2008).Tompa P, Fuxreiter M. Fuzzy complexes: polymorphism and structural disorder in protein–protein interactions. Trends in Biochemical Sciences. 2008;33:2–8. doi: 10.1016/j.tibs.2007.10.003. [DOI] [PubMed] [Google Scholar]
  • Tompa, Szasz & Buday (2005).Tompa P, Szasz C, Buday L. Structural disorder throws new light on moonlighting. Trends in Biochemical Sciences. 2005;30:484–489. doi: 10.1016/j.tibs.2005.07.008. [DOI] [PubMed] [Google Scholar]
  • Tompa et al. (2009).Tompa P, Fuxreiter M, Oldfield CJ, Simon I, Dunker AK, Uversky VN. Close encounters of the third kind: disordered domains and the interactions of proteins. Bioessays. 2009;31:328–335. doi: 10.1002/bies.200800151. [DOI] [PubMed] [Google Scholar]
  • Tsai et al. (2005).Tsai RT, Fu RH, Yeh FL, Tseng CK, Lin YC, Huang YH, Cheng SC. Spliceosome disassembly catalyzed by Prp43 and its associated components Ntr1 and Ntr2. Genes and Development. 2005;19:2991–3003. doi: 10.1101/gad.1377405. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Uversky (2002a).Uversky VN. What does it mean to be natively unfolded? European Journal of Biochemistry. 2002a;269:2–12. doi: 10.1046/j.0014-2956.2001.02649.x. [DOI] [PubMed] [Google Scholar]
  • Uversky (2002b).Uversky VN. Natively unfolded proteins: a point where biology waits for physics. Protein Science. 2002b;11:739–756. doi: 10.1110/ps.4210102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Uversky (2003).Uversky VN. Protein folding revisited. A polypeptide chain at the folding-misfolding-nonfolding cross-roads: which way to go? Cellular and Molecular Life Science. 2003;60:1852–1871. doi: 10.1007/s00018-003-3096-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Uversky (2010).Uversky VN. The mysterious unfoldome: structureless, underappreciated, yet vital part of any given proteome. Journal of Biomedical Biotechnology. 2010 doi: 10.1155/2010/568068. 568068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Uversky (2011).Uversky VN. Multitude of binding modes attainable by intrinsically disordered proteins: a portrait gallery of disorder-based complexes. Chemical Society Review. 2011;40:1623–1634. doi: 10.1039/c0cs00057d. [DOI] [PubMed] [Google Scholar]
  • Uversky (2012).Uversky VN. Disordered competitive recruiter: fast and foldable. Journal of Molecular Biology. 2012;418:267–268. doi: 10.1016/j.jmb.2012.02.034. [DOI] [PubMed] [Google Scholar]
  • Uversky & Dunker (2010).Uversky VN, Dunker AK. Understanding protein non-folding. Biochimica et Biophysica ACTA. 2010;1804:1231–1264. doi: 10.1016/j.bbapap.2010.01.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Uversky, Gillespie & Fink (2000).Uversky VN, Gillespie JR, Fink AL. Why are “natively unfolded” proteins unstructured under physiologic conditions? Proteins. 2000;41:415–427. doi: 10.1002/1097-0134(20001115)41:3&#x0003c;415::AID-PROT130&#x0003e;3.0.CO;2-7. [DOI] [PubMed] [Google Scholar]
  • Uversky, Oldfield & Dunker (2005).Uversky VN, Oldfield CJ, Dunker AK. Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling. Journal of Molecular Recognition. 2005;18:343–384. doi: 10.1002/jmr.747. [DOI] [PubMed] [Google Scholar]
  • Uversky, Oldfield & Dunker (2008).Uversky VN, Oldfield CJ, Dunker AK. Intrinsically disordered proteins in human diseases: introducing the D2 concept. Annual Review of Biophysics. 2008;37:215–246. doi: 10.1146/annurev.biophys.37.032807.125924. [DOI] [PubMed] [Google Scholar]
  • Uversky et al. (2006).Uversky VN, Roman A, Oldfield CJ, Dunker AK. Protein intrinsic disorder and human papillomaviruses: increased amount of disorder in E6 and E7 oncoproteins from high risk HPVs. Journal of Proteome Research. 2006;5:1829–1842. doi: 10.1021/pr0602388. [DOI] [PubMed] [Google Scholar]
  • Vacic et al. (2007a).Vacic V, Uversky VN, Dunker AK, Lonardi S. Composition profiler: a tool for discovery and visualization of amino acid composition differences. BMC Bioinformatics. 2007a;8:211. doi: 10.1186/1471-2105-8-211. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Vacic et al. (2007b).Vacic V, Oldfield CJ, Mohan A, Radivojac P, Cortese MS, Uversky VN, Dunker AK. Characterization of molecular recognition features, MoRFs, and their binding partners. Journal of Proteome Research. 2007b;6:2351–2366. doi: 10.1021/pr0701411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • van Nues & Beggs (2001).van Nues RW, Beggs JD. Functional contacts with a range of splicing proteins suggest a central role for Brr2p in the dynamic control of the order of events in spliceosomes of Saccharomyces cerevisiae. Genetics. 2001;157:1451–1467. doi: 10.1093/genetics/157.4.1451. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Veretnik et al. (2009).Veretnik S, Wills C, Youkharibache P, Valas RE, Bourne PE. Sm/Lsm genes provide a glimpse into the early evolution of the spliceosome. PLoS Computational Biology. 2009;5 doi: 10.1371/journal.pcbi.1000315. e1000315. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Vincent et al. (2003).Vincent K, Wang Q, Jay S, Hobbs K, Rymond BC. Genetic interactions with CLF1 identify additional pre-mRNA splicing factors and a link between activators of yeast vesicular transport and splicing. Genetics. 2003;164:895–907. doi: 10.1093/genetics/164.3.895. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Vucetic et al. (2007).Vucetic S, Xie H, Iakoucheva LM, Oldfield CJ, Dunker AK, Obradovic Z, Uversky VN. Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions. Journal of Proteome Research. 2007;6:1899–1916. doi: 10.1021/pr060393m. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Vucetic et al. (2005).Vucetic S, Obradovic Z, Vacic V, Radivojac P, Peng K, Iakoucheva LM, Cortese MS, Lawson JD, Brown CJ, Sikes JG, Newton CD, Dunker AK. DisProt: a database of protein disorder. Bioinformatics. 2005;21:137–140. doi: 10.1093/bioinformatics/bth476. [DOI] [PubMed] [Google Scholar]
  • Wahl, Will & Luhrmann (2009).Wahl MC, Will CL, Luhrmann R. The spliceosome: design principles of a dynamic RNP machine. Cell. 2009;136:701–718. doi: 10.1016/j.cell.2009.02.009. [DOI] [PubMed] [Google Scholar]
  • Walke et al. (2001).Walke S, Bragado-Nilsson E, Seraphin B, Nagai K. Stoichiometry of the Sm proteins in yeast spliceosomal snRNPs supports the heptamer ring model of the core domain. Journal of Molecular Biology. 2001;308:49–58. doi: 10.1006/jmbi.2001.4549. [DOI] [PubMed] [Google Scholar]
  • Wang (1996).Wang K. Titin/connectin and nebulin: giant protein rulers of muscle structure and function. Advances in Biophysics. 1996;33:123–134. doi: 10.1016/0065-227X(96)81668-6. [DOI] [PubMed] [Google Scholar]
  • Ward & Cooper (2010).Ward AJ, Cooper TA. The pathobiology of splicing. Journal of Pathology. 2010;220:152–163. doi: 10.1002/path.2649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Ward et al. (2004).Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT. Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. Journal of Molecular Biology. 2004;337:635–645. doi: 10.1016/j.jmb.2004.02.002. [DOI] [PubMed] [Google Scholar]
  • Wells & Ares (1994).Wells SE, Ares M., Jr Interactions between highly conserved U2 small nuclear RNA structures and Prp5p, Prp9p, Prp11p, and Prp21p proteins are required to ensure integrity of the U2 small nuclear ribonucleoprotein in Saccharomyces cerevisiae. Molecular and Cellular Biology. 1994;14:6337–6349. doi: 10.1128/MCB.14.9.6337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Wilkinson et al. (2004).Wilkinson CR, Dittmar GA, Ohi MD, Uetz P, Jones N, Finley D. Ubiquitin-like protein Hub1 is required for pre-mRNA splicing and localization of an essential splicing factor in fission yeast. Current Biology. 2004;14:2283–2288. doi: 10.1016/j.cub.2004.11.058. [DOI] [PubMed] [Google Scholar]
  • Will & Luhrmann (2011).Will CL, Luhrmann R. Spliceosome structure and function. Cold Spring Harb Perspect Biology. 2011;3:a003707. doi: 10.1101/cshperspect.a003707. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Will et al. (1999).Will CL, Schneider C, Reed R, Luhrmann R. Identification of both shared and distinct proteins in the major and minor spliceosomes. Science. 1999;284:2003–2005. doi: 10.1126/science.284.5422.2003. [DOI] [PubMed] [Google Scholar]
  • Will et al. (2001).Will CL, Schneider C, MacMillan AM, Katopodis NF, Neubauer G, Wilm M, Luhrmann R, Query CC. A novel U2 and U11/U12 snRNP protein that associates with the pre-mRNA branch site. The EMBO Journal. 2001;20:4536–4546. doi: 10.1093/emboj/20.16.4536. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Will et al. (2004).Will CL, Schneider C, Hossbach M, Urlaub H, Rauhut R, Elbashir S, Tuschl T, Luhrmann R. The human 18S U11/U12 snRNP contains a set of novel proteins not found in the U2-dependent spliceosome. RNA. 2004;10:929–941. doi: 10.1261/rna.7320604. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Williams et al. (2001).Williams RM, Obradovi Z, Mathura V, Braun W, Garner EC, Young J, Takayama S, Brown CJ, Dunker AK. The protein non-folding problem: amino acid determinants of intrinsic order and disorder. Pacific Symposium on Biocomputing. 2001:89–100. doi: 10.1142/9789814447362_0010. [DOI] [PubMed] [Google Scholar]
  • Wilson et al. (1994).Wilson SM, Datar KV, Paddy MR, Swedlow JR, Swanson MS. Characterization of nuclear polyadenylated RNA-binding proteins in Saccharomyces cerevisiae. Journal of Cellular Biochemistry. 1994;127:1173–1184. doi: 10.1083/jcb.127.5.1173. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Wong & Scott (2004).Wong W, Scott JD. AKAP signalling complexes: focal points in space and time. Nature Reviews. Molecular Cell Biology. 2004;5:959–970. doi: 10.1038/nrm1527. [DOI] [PubMed] [Google Scholar]
  • Wright & Dyson (1999).Wright PE, Dyson HJ. Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm. Journal of Molecular Biology. 1999;293:321–331. doi: 10.1006/jmbi.1999.3110. [DOI] [PubMed] [Google Scholar]
  • Wright & Dyson (2009).Wright PE, Dyson HJ. Linking folding and binding. Current Opinion in Structural Biology. 2009;19:31–38. doi: 10.1016/j.sbi.2008.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Xie et al. (2007a).Xie H, Vucetic S, Iakoucheva LM, Oldfield CJ, Dunker AK, Uversky VN, Obradovic Z. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. Journal of Proteome Research. 2007a;6:1882–1898. doi: 10.1021/pr060392u. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Xie et al. (2007b).Xie H, Vucetic S, Iakoucheva LM, Oldfield CJ, Dunker AK, Obradovic Z, Uversky VN. Functional anthology of intrinsic disorder. 3. Ligands, post-translational modifications, and diseases associated with intrinsically disordered proteins. Journal of Proteome Research. 2007b;6:1917–1932. doi: 10.1021/pr060394e. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Xu et al. (2007).Xu T, Nie L, Zhang Y, Mo J, Feng W, Wei D, Petrov E, Calisto LE, Kachar B, Beisel KW, Vazquez AE, Yamoah EN. Roles of alternative splicing in the functional properties of inner ear-specific KCNQ4 channels. Journal of Biological Chemistry. 2007;282:23899–23909. doi: 10.1074/jbc.M702108200. [DOI] [PubMed] [Google Scholar]
  • Xu et al. (2004).Xu YZ, Newnham CM, Kameoka S, Huang T, Konarska MM, Query CC. Prp5 bridges U1 and U2 snRNPs and enables stable U2 snRNP association with intron RNA. The EMBO Journal. 2004;23:376–385. doi: 10.1038/sj.emboj.7600050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Xue, Dunker & Uversky (2012).Xue B, Dunker AK, Uversky VN. Orderly order in protein intrinsic disorder distribution: disorder in 3500 proteomes from viruses and the three domains of life. Journal of Biomolecular Structure and Dynamics. 2012;30:137–149. doi: 10.1080/07391102.2012.675145. [DOI] [PubMed] [Google Scholar]
  • Xue et al. (2009).Xue B, Oldfield CJ, Dunker AK, Uversky VN. CDF it all: consensus prediction of intrinsically disordered proteins based on various cumulative distribution functions. FEBS Letters. 2009;583:1469–1474. doi: 10.1016/j.febslet.2009.03.070. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Xue et al. (2010).Xue B, Dunbrack RL, Williams RW, Dunker AK, Uversky VN. PONDR-FIT: a meta-predictor of intrinsically disordered amino acids. Biochimica et Biophysica ACTA. 2010;1804:996–1010. doi: 10.1016/j.bbapap.2010.01.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Yang et al. (2005).Yang ZR, Thomson R, McNeil P, Esnouf RM. RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins. Bioinformatics. 2005;21:3369–3376. doi: 10.1093/bioinformatics/bti534. [DOI] [PubMed] [Google Scholar]
  • Zahler et al. (1992).Zahler AM, Lane WS, Stolk JA, Roth MB. SR proteins: a conserved family of pre-mRNA splicing factors. Genes and Development. 1992;6:837–847. doi: 10.1101/gad.6.5.837. [DOI] [PubMed] [Google Scholar]
  • Zahner, Harkins & Pringle (1996).Zahner JE, Harkins HA, Pringle JR. Genetic analysis of the bipolar pattern of bud site selection in the yeast Saccharomyces cerevisiae. Molecular and Cellular Biology. 1996;16:1857–1870. doi: 10.1128/mcb.16.4.1857. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Zhang & Rosbash (1999).Zhang D, Rosbash M. Identification of eight proteins that cross-link to pre-mRNA in the yeast commitment complex. Genes and Development. 1999;13:581–592. doi: 10.1101/gad.13.5.581. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from PeerJ are provided here courtesy of PeerJ, Inc

RESOURCES