Skip to main content
PMC home page
BMC Genomics logoLink to BMC Genomics
. 2007 May 9;8:113. doi: 10.1186/1471-2164-8-113

Discovery and characterization of 91 novel transcripts expressed in cattle placenta

Charu G Kumar 1, Joshua H Larson 1, Mark R Band 1,2, Harris A Lewin 1,3,✉
PMCID: PMC1884150  PMID: 17488528

Abstract

Background

Among the eutherian mammals, placental architecture varies to a greater extent than any other tissue. The diversity of placental types, even within a single mammalian order suggests that genes expressed in placenta are under strong Darwinian selection. Thus, the ruminant placenta may be a rich source of genes to explore adaptive evolutionary responses in mammals. The aim of our study was to identify novel transcripts expressed in ruminant placenta, and to characterize them with respect to their expression patterns, organization of coding sequences in the genome, and potential functions.

Results

A combination of bioinformatics, comparative genomics and transcript profiling was used to identify and characterize 91 novel transcripts (NTs) represented in a cattle placenta cDNA library. These NTs have no significant similarity to any non-ferungulate DNA or RNA sequence. Proteins longer than 100 aa were predicted for 29 NTs, and 21 are candidate non-coding RNAs. Eighty-six NTs were found to be expressed in one or more of 18 different tissues, with 39 (42%) showing tissue-preference, including six that were expressed exclusively in placentome. The authenticity of the NTs was confirmed by their alignment to cattle genome sequence, 42 of which showed evidence of mRNA splicing. Analysis of the genomic context where NT genes reside revealed 61 to be in intergenic regions, whereas 30 are within introns of known genes. The genes encoding the NTs were found to be significantly associated with subtelomeric regions.

Conclusion

The 91 lineage-specific transcripts are a useful resource for studying adaptive evolutionary responses of the ruminant placenta. The presence of so many genes encoding NTs in cattle but not primates or rodents suggests that gene loss and gain are important mechanisms of genome evolution in mammals. Furthermore, the clustering of NT genes within subtelomeric regions suggests that such regions are highly dynamic and may foster the birth of novel genes. The sequencing of additional vertebrate genomes with defined phylogenetic relationships will permit the search for lineage-specific genes to take on a more evolutionary context that is required to understand their origins and functions.

Background

The primary function of the placenta is to regulate the transport of gases, nutrients and waste products between mother and fetus [1]. The placenta also serves as an endocrine organ, producing estrogens, progesterone and placental lactogens that are important for the maintenance of pregnancy [1]. While these functions have been conserved in all eutherian mammals, the relatively large variation in placental architecture [2] makes the placenta an attractive model system for studying adaptive evolutionary changes [3]. Placentae are classified on the basis of their gross shape and the distribution of contact points between the fetal tissues and the maternal endometrium [2]. The synepitheliochorial cotyledonary placenta of ruminants has three distinct tissue layers and is regarded as the most complex as compared to other placental types [2]. By contrast, in the discoid hemochorial placenta of primates and rodents, the fetal chorionic epithelium is directly bathed in maternal blood because the three maternal tissues layers are degraded. The molecular basis for these anatomical changes and their adaptive significance remain largely unknown.

Recent studies demonstrating that phenotypic changes with adaptive significance can be caused by the action of individual genes provide an important rationale for the identification of genes that may be highly divergent or unique to a specific lineage or clade [eg, [4]]. Furthermore, there is a relative abundance of novel or lineage-specific transcripts (NTs) [5] and lineage-specific regulatory non-coding RNAs (ncRNAs) [6-8] in the transcriptomes of different eukaryotes. However, little is known about the role of divergent genes and lineage-specific transcripts in adaptive evolution. In ruminants, there is unequivocal evidence for lineage-specific and highly divergent genes expressed in the placenta and/or trophoblast e.g., genes encoding interferon-tau [9], the placental lactogens [10], the pregnancy associated glycoproteins [11] and the prolactin related proteins [12]. All of these highly divergent proteins appear to play adaptive roles in the reproductive biology of ruminants.

Given the unique adaptations of the reproductive system of ruminants, our goal is to use comparative genomics to identify genes and ncRNAs that are responsible for these evolutionary changes. Toward that end, we recently developed a bioinformatics strategy to mine collections of expressed sequence tags (ESTs) for divergent homologs and novel transcripts [13]. This strategy led to the discovery of the ULBP gene cluster and eight divergent homologs in cattle [12,14]. Herein, we describe the application and extension of our approach for identifying and characterizing NTs expressed in mammalian tissues. Using this approach, 91 NTs were identified in a collection of cattle placenta ESTs and then verified by in silico extension with DNA sequences in the public domain databases, gene expression profiling, and alignment to whole genome sequence.

Results

Identification and characterization of novel transcripts in cattle placenta

A collection of 12,614 5' ESTs from a cattle term placenta cDNA library was reduced to a working set of 373 putative NTs and divergent homologs using pairwise BLASTN [15] searches against non-cetartiodactyl EST and genome databases (October 2005 freezes), followed by in silico extension and full-clone sequencing of cDNA inserts (Table 1). Analysis of the sequence-extended EST-containing clones using TBLASTX searches against human and mouse UniGene [16], and against ESTs from non-cetartiodactyl species, permitted the distinction of divergent (N = 75) from unknown (N = 298) transcripts (Table 1). Repetition of in silico extension of EST sequences followed by removal of homologs using subsequently updated databases (April 2006 freezes) removed an additional 134 ESTs, thus leaving 164 putative NTs. Using the 6.2× Btau_2.0 cattle genome assembly [17] as a reference, 73 transcripts were found likely to represent priming from poly A tracts of genomic DNA. These artifacts were subsequently removed, bringing the final working set to 91 NTs that have an average length of 993 bp (Table 1; Additional file 1). The definition of a transcript as novel thus indicates that the nucleotide sequence or hypothetical proteins encoded by it does not have similarity to any non-cetartiodactyl DNA or protein sequence at the time the databases were searched. The operational term is not meant to imply an evolutionary mechanism, such as gene loss or rapid divergence.

Table 1.

Bioinformatics scheme for identifying novel transcripts

Steps in the scheme Number of sequences
Removed Remaining
Starting set of 5' placenta ESTs 12,614
PipeBLASTN (automated BLASTN analysis) 10,235 2,379
In silico extension of 5' ESTs with public cattle ESTs, followed by PipeBLASTN 581 1,798
3' reads from single-pass sequencing using anchored oligodT primer 618 1,180
PipeBLASTN of 3' reads 404 776
Assembly of 3' and extended 5' mates NAa 493
Full-clone sequencing of unassembled 3' ESTs NA 283
In silico extension of 493 mate-pairs followed by PipeBLASTN 171 322
In silico extension of 283 primer-walked clones, followed by PipeBLASTN 232 51
Working set of divergent homologs and novel transcripts (322+51) NA 373
TBLASTX against UniGene databases to separate novel transcripts from divergent homologs 75 298
In silico extension followed by PipeBLASTN using updated databases to yield final set of NTs. 134 164
Screening for internal poly A tracts 73 91
Open in a new tab

a NA; not applicable.

Alignment to the cattle genome sequence assembly allowed polyA signals to be identified within 50 bp downstream from the end of the aligned NT. Polyadenylation signals were found in 86/91 (95%) of the NTs (Additional file 2). The consensus signal, AATAAA, was present in 54 (59%) of the NTs; 15 (16%) had the less conserved signal ATTAAA, and 17 (19%) had rare polyadenylation signals experimentally identified in human mRNA [18]. A polyadenylation signal was not detected in 5 (5%) of the NTs, likely representing incomplete transcripts.

Analysis of the 91 NTs revealed 64 NTs with one or more open reading frames (ORFs) >33 codons (Figure 1). Among these 64 NTs there are 78 predicted ORFs >33 codons, all of which were considered as candidates for encoding novel proteins (Figure 1; Additional file 3). The cDNA clone with the longest ORF, BTC1_14RD, contains 235 codons. TBLASTN of the translated ORFs against all predicted cattle transcripts resulted in 24 unique hits, of which seven are to hypothetical proteins, 15 are to predicted proteins (having some supporting molecular evidence), and two have similarity to known cattle proteins (Additional file 2). While all ORFs >33 codons terminate in a stop codon, 19 (21%) do not possess an ATG start codon, suggesting that at least some of the NTs represent 3' regions of genes or have ORFs with alternate start codons. The ORFs possessing an ATG start codon were analyzed for the presence of the Kozak consensus sequence RMC-ATG-G, a signal for eukaryotic translation initiation [19], where R is a purine and M is [AC]. One ORF matched this consensus pattern and 24 ORFs matched the less restricted Kozak pattern R-N-N-ATG-R, where N is any nucleotide, and R is a purine.

Figure 1.

Figure 1

Open in a new tab

Length distribution of ORFs. Length distribution of 78 ORFs (orange bars) predicted in 64 NTs with >33 codons. The expected frequency of false positives (yellow bars) was calculated according to Frishman et al. [52].

Protein motifs are predicted in the translated ORFs of four NTs (Additional file 2, Table 2). In addition, a transmembrane helix (TMH) was identified in one ORF (BTC1_403NG) predicted to contain a single-span TMH. Signal peptides are predicted in four ORFs with no concomitant TMH prediction (Additional file 2) thus indicating that these transcripts encode soluble/secreted proteins. Functional elements located in untranslated regions (UTRs) are predicted in 25 NTs (Additional file 2, Table 2). The NT BTC1_43PW contains a predicted selenocysteine insertion sequence (SECIS) element. These elements are required for translation of the UGA codon as selenocysteine in mRNAs of selenoproteins, several of which are species-specific and participate in peroxide degradation and antioxidant reactions [20]. The UTR sequence region corresponding to the SECIS prediction was manually verified for the appropriate secondary structure (Additional file 4). Two sequences, BTC1_40PW and BTC1_14RD, are predicted to contain conserved ncRNA secondary structural elements within their 3' UTRs thus implicating them in regulatory functions.

Table 2.

Evidence of functionality in 91 NTsa

Type of functional element No. of NTs
Protein motif 4
Coiled-coil repeats 1
Transmembrane (TMHMM, SMART) 1
Novel protein domain 1
Signal peptide (SignalP-NN, SignalP-HMM, SMART) 4
UTR elements 13
Inverse repeats 12
G-quartets 7
CpG Islands 30
Non-coding RNA structural elements 2
ncRNA 21
Open in a new tab

a Sequences annotated with the above elements can be found in Additional file 2.

The GC-content average of the NTs, mRNAs and genomic DNA sequence is 0.50 (range 0.33 to 0.7), 0.51, and 0.45, respectively (Additional file 2). Ten percent of NTs have low GC content average (<0.4) as compared to 12% of full length mRNAs and 31% of genomic scaffold sequence that contains the NTs. Candidate exonic CpG islands were identified in 5' ends of four NTs (Table 3, Additional file 2). Criteria for CpG islands were length >200 bp, GC content ≥ 53% and observed/expected CpG ratio ≥ 0.63 [21]. Anchoring the NTs to the 6.2× draft cattle genome sequence allowed the identification of 26 additional NTs with CpG islands upstream of their start sites. Other NTs with regulatory sequence features included 12 with inverted repeats of at least 11 bp. The longest inverted repeats are 18 bp and separated by approximately 300 bp. In addition, 7 NTs contain G-quartets, which are tetrads of guanine/purine tetramers that are implicated in transcription pausing, mRNA stability, recombination hotspots, stability of chromosomes and interactions of telomeres [reviewed in [22]].

Table 3.

Sample feature table for 91 NTs

NT Ida GenBank accessionb length (bp) ORF_length aac speciesd No. exons poly A signale motiff tissue preference Hg17 locus BTAU_2.0 assignment Cattle genome contextg Segmental locationh
BTC1_14FL (XM_873204) CK394134 868 63 4 AATAAA CpG muscle 7p13 chr4:43, 188,679–43,191, 770 intergenic interstitial
BTC1_15FL AY563860 630 none C 1 AATAAA ncRNA none 14q11.2 scaffold3389:59,086–59,711 inter genie interstitial
BTC1_33FL CK394175 691 35 C 5 ATTAAA CpG none 6q14.3 scaffold4626:20,602–22,398 intergenic interstitial
BTC1_34FL CK394179 977 100 K A 3 AATAAA ADH_DRE, GY-Box, signalP placentome 9q32 scaffold9964:10,570–17,798 intergenic interstitial
BTC1_53FL AY563751 525 106 C 1 AATAAA none none 19q13.31 chr6:49, 142,506–49,143,026 intergenic interstitial
BTC1_55FL AY563756 777 82 K A 2 AATAGA signalP none 16q22.1 chr18:13,861,852–13,862,619 intergenic boundary
BTC1_57FL AY563869 911 none C 1 AATAAA none thymus 7p22.1 chr25:33,360,786–33,361,318 ZnF447 interstitial
BTC1_58FL AY563762 1544 64 A 2 ATTAAA ADH_DRE, GY-Box none 11q12.2 chr29:31,601,481–31,607,081 RAB3 interstitial
BTC1_71FL AY563803 691 none C 1 AATAAA none 3p21.31 chr22:42,680,522–42,681,188 SACMIL interstitial
BTC1_77FL AY563824 1095 84 C 1 AATAAA GY-Box; CpG thymus 18q21.33 chr24:44,739,526–44,740,613 HDGFRP2 subtelomeric
BTC1_78FL CK394028 1736 91 K A 1 AATAAA GY-Box; IR mesenteric lymphnode, thymus 1p36.13 chr2:85,996,428–85,997,304 intergenic subtelomeric
BTC1_79FL AY563826 732 none C 4 TATAAA CpG; ncRNA cerebrum 2p11.2 chr11:34,570,339–34,575,174 intergenic interstitial
BTC1_92FL (XM_587188) CK394038 933 93 K; 127 C 1 TGTAAA none cerebrum 17q25.1 chr19:49,709,796–49,710,719 intergenic interstitial
BTC1_93FL AY563890 1269 147 K C 1 AATAAA GY-Box thymus 22q12.2 chr17:42,667,501–42,668,530 SEC14L4 interstitial
BTC1_95FL AY563713 2492 108 C 1 AATAAA none skin 6p21.2 chr23:8,629,884–8,632,373 intergenic interstitial
BTC1_102FL AY563714 795 38 K C 1 AATAAA G-quartet; IR none 10q11.21 chr28:33,147,612–33,148,436 intergenic subtelomeric
BTC1_113FL (XM_611248) CK394057 659 69 K C 5 AATAAA CpG thalamus 1p35.3 chr2:76,776,847–76,779,658 intergenic interstitial
BTC1_115FL CK394060 962 36; 35 C 1 AATAAA none thymus 1p34.1 chr3:67,576,355–67,577,638 LRRC41 interstitial
BTC1_130FL (XM_611254) CK394181 664 125 K; 65 K A 3 AATAAA none adrenal, cerebellum, thalamus 19q13.43 chr18:55591568–55593819 ZIM2 subtelomeric
BTC1_132FL CK394199 2174 none A 1 AATAAA IR; ncRNA thymus Xq25 scaffold4717:48,263–50,399 ERVK6 interstitial
BTC3_7JE CK393999 548 35 A 5 AATAAA none muscle 7p22.1 chr4:43,188,676–43,191,750 intergenic interstitial
BTC1_22JE CK394011 1569 none A 1 ATTAAA IR; ncRNA placentome 5q33.3 scaffold399:92,975–94,544 TIMD4 interstitial
BTC2_43JE CK394035 1043 none C 2 AAACAA G-quartet; CpG cerebrum, thalamus 8q24.3 scaffold12671:9,483–10,533 JRK interstitial
BTC1_51JE CK394043 958 130 C 2 AATAAA none skin 11p15.5 scaffold2079:18,521–19,645 intergenic interstitial
BTC1_100JE CK394097 2381 92 K C 1 GATAAA GY-Box none 19p13.11 chr7:5,772,691–5,775,068 intergenic interstitial
BTC1_104JE (XM_883284) CK394101 619 59; 68 A 5 AATAAA None placentome none scaffold6598:22994–33093 intergenic interstitial
BTC1_113JE CK394107 830 none A 2 AATAAA CpG; ncRNA none 1p13.2 scaffold1237:214289–215207 intergenici interstitial
BTC1_118JE CK394113 2257 50; 92 C 1 AATAAA GY-Box none 22q13.2 scaffold9684:8273–9215 intergenic interstitial
BTC1_144JE CK394138 832 150 K C 1 AATAAA none none 1p36.33 chr16:37642343–37643174 intergenic boundary
BTC1_146JE CK394139 2206 none A 3 ATTAAA IR; ncRNA muscle, skin 14q32.31 chr21:45,674,164–45,678,931 intergenic interstitial
BTC1_203JE CK394182 773 129 K C 3 ATTAAA CpG heart 8q21.2 chr14:46,885,318–46,890,350 intergenic interstitial
BTC1_215JE CK394201 1038 109 K C 1 AATAAA Eu_thiol protease none 2p25.3 scaffold473:40,328–41,349 intergenic interstitial
BTC1_8NG AY563705 703 71 K A 4 AATATA none thalamus none chr19:48,755,357–48,757,924 ATP1a2a interstitial
BTC1_39NG AY563711 767 172 K C 2 AATAAA Proline-rich with_coiled-coil none 1p31.3 scaffold997:257,434–259,042 INADL interstitial
BTC1_58NG AY563715 562 49 C 1 AATAAA CpG cerebrum 13q34 chr12:48,063,584–48,064,091 CDC16: subtelomeric
BTC1_63NG AY563716 483 142 K C 2 unknown signalP; ATPaseE1. E2 none 16p13.12 chr25:14,893,445–14,897,173 intergenic interstitial
BTC1_104NG AY563722 728 144 K; 149 K C 1 AATAAA TOP none 14q32.32 chr21:48,386,644–48,387,349 MKNK2 i subtelomeric
BTC1_149NG AY563726 690 35 C 1 TATAAA CpG skin, testis 22q11.21 chr17:45,366,139–45,366,804 RFNG subtelomeric
BTC1_237NG AY563754 622 67 C 1 AATAAA CpG cerebrum 17q25.3 chr19:47,237,560–47,238,117 intergenic interstitial
BTC1_255NG (XM_596632) AY563763 651 64 C 2 AATAAA CpG;Heavy metal_ion transport muscle 3q29 chr1:43,207,885–43,208,506 intergenic interstitial
BTC1_269NG AY563771 716 116 C 1 ATTAAA CpG none 11q13.3 chr29:41,407,248–41,407,965 intergenic boundary
BTC1_286NG (XM_870778) AY563780 788 36; 184 K C 1 unknown CpG placentome none chr14:662,313–663,087 MAPK8IP2 subtelomeric
Open in a new tab

a number in parenthesis is the GenBank accession of the cattle RefSeq prediction matching the NT.

b GenBank accession No. of 3' sequence including primer-walked sequence.

c K denotes start-codon of ORF flanked by Kozak consensus.

dC, cattle-specific; A, cetartiodactyla-specific

e 'Unknown' indicates that a polyadenylation signal could not be identified.

f 'IR' indicates presence of an inverse repeat; ADH_DRE, GY-box, K-box, Brd box and CPE are functional UTR elements.

gene symbol indicates NT is located in an intron of that gene.

h "Boundary" indicates that the NT anchors within 1 Mbp of the end of a homologous synteny boundary on a human chromosome as defined in [23];

"Subtelomeric" indicates that the NT aligns within 2 Mbp from the end of a cattle chromosome.

Twenty-one NTs qualified as candidate ncRNAs (Table 3, Additional file 2). These NTs have no ORF >33 codons, and no predicted exon within 5 kb of flanking cattle genome sequence. Among these, 20 contain a known polyadenylation signal, of which seven are spliced, and 14 align to the genome sequence along the transcript's entire length with >95% identity (Additional file 2).

Genomic context of the NTs

The genomic organization of the NT genes was determined by BLASTN against the 6.2× cattle genome draft sequence. All 91 NTs have matches in the cattle genome (Additional file 2), 49 of which have ≥98% identity over >95% of their length and 48 have polyadenylation signals (intronless transcripts). The remaining 42 NTs have well-defined intron-exon boundaries indicative of mRNA splicing (an average of 3 exons), of which 40 possess a polyadenylation signal (Table 4; Additional file 2). CpG islands were located upstream of 16 of these 40 transcripts. Of the 91 NTs, 68 were mapped in silico to chromosome locations in the cattle genome on the basis of existing radiation hybrid (RH) and comparative mapping information [23] (Additional file 2). The remaining 23 were located on unmapped scaffolds. Among the 68 mapped NTs, 10 were located on BTA19 (P > 0.05). This analysis also revealed that 61 (67%) of the NTs are located within "intergenic" regions and 30 (33%) of the NTs are within introns of known genes (Table 3, Additional file 2). Three of the NTs on BTA19 (BTC1_390NG, BTC1_28PW, BTC1_8NG) were located within introns of the developmentally regulated genes HOXB3, JAF1 and ATP1a2a. In addition, 24 NTs (26%) are located either in subtelomeric regions or at the boundaries of homologous synteny blocks as defined by Everts van der Wind et al. [23] (Table 3; Additional file 2). The distribution of NTs was positively associated (P < 0.05) with the subtelomeric regions (< 2 Mbp from telomere) as compared to the distribution of randomly chosen RefSeq genes.

Table 4.

Lineage specificity and expression features of 91 cattle NTs

Lineage specificity Predicted ORF (>100 bp) No. of NTs Expressiona Evidence for transcript splicingb
Cetartiodactyla-specific transcriptsc No 7 7 3
Yes 16 14 15
Novel transcriptsd No 20 19 6
Yes 48 46 18
Open in a new tab

a Gene expression validated by microarray analysis.

b Splice-site analysis was conducted using est2genome. Some of the NTs had missing exons due to gaps in the sequence scaffolds, or due to alignment reaching the end of a scaffold.

c BLASTN hits with E ≤ 10-05 to cetartiodactyl EST database.

d Sequences that have BLASTN hits with E > 10-05 and TBLASTX hits with E > 10-10

Among the 91 NTs, 71 have no NCBI [24] annotation. The 20 annotated NTs that aligned to the cattle genome were analyzed in greater detail. Each of them was found to have a gene model and a cattle RefSeq identification number (Additional file 2). Most appear to be either alternatively spliced variants, antisense to the predicted genes, or long and divergent 3' ends of predicted genes. The 20 annotated NTs were examined further by comparing full-length mRNA sequence from the cattle RefSeq prediction to the human genome. Similarity between the full-length cattle RefSeq predictions and human genes was found only for 12 of the NT-containing RefSeq genes (BLASTN E value < 10-10). Among these 12 cattle RefSeq genes with putative human orthologs, the NTs contained within them represent novel splice products, whereas three are novel antisense products. In silico comparative mapping confirmed homologous positions within the cattle and human genomes, thus providing additional supporting evidence that these 12 NTs are part of highly divergent genes and/or genes created de novo (Additional file 2).

It was also possible to predict locations where genes encoding the NTs should be in the human genome (Additional file 2; Figures 2, 3, 4). This was accomplished by identifying the cattle genome sequence flanking the NTs with significant nucleotide similarity in the human genome (although the NTs themselves did not match the human genome using a BLASTN and TBLASTX E-value threshold of 10-10). Anchoring the NTs to the human genome using conserved flanking sequences revealed that 69% have an assumptive location in intergenic regions or within an intron of a known human gene. The genomic context for all 91 NTs is given in Additional file 2. A detailed description of the genomic context of three NTs is presented below. The number that can be presented is limited by available space (all alignments can be found in Additional file 5).

Figure 2.

Figure 2

Open in a new tab

Genomic context of BTC1_14RD and BTC1_130FL. Top panel (A). A modified image from the UCSC cow genome browser (March 2005, Btau_2.0) showing BTC1_14RD and its alternately spliced product BTC1_130FL aligned to the cattle genome (Contig455) [GenBank:AAFC02000448]. Cattle BAC AC146804 [25] aligned to the same region using BLAT (regions of similarity shown with vertical bars). A track for human proteins is shown to demonstrate that there are no known human homologs in this region. A scaled track for cattle ESTs (partial representation of "squish mode" due to the large number of ESTs) shows high support for alternatively spliced cattle transcripts encoded in this region. Bottom panel (B). A modified image from the UCSC human genome browser (May 2004, Hg17) showing the in silico anchoring of BTC1_14RD, represented as a block arrow, to a subtelomeric region of HSA19q on the basis of flanking sequence similarity in cattle BAC AC146804. This region is syntenic to a segment of BTA18 (shown as a separate track at the top). BTC1_130FL anchors in the same region (not shown to maintain clarity of the figure). The assumptive map location of the gene encoding the artiodactyl-specific transcript Ast1 [GenBank:AY427788] is also shown. No significant flanking match was identified in Contig455 (due to its shorter length). Unmodified UCSC Genome Browser tracks for known human proteins, Genscan genes, retroposed genes, conserved sequences, and segmental duplication are shown.

Figure 3.

Figure 3

Open in a new tab

Genomic context of BTC1_146JE. Top panel (A). A modified image from the UCSC cow genome browser (March 2005, Btau_2.0) showing BTC1_146JE aligned to the cattle genome (Contig54150) [GenBank:AAFC02053608]. Cow ESTs are shown in a scaled "squish" mode to conserve space due to the large number of ESTs aligning in the region. Bottom panel (B). Anchoring of BTC1_146JE, represented as a block arrow, to HSA14q32.31 (May 2004, Hg17). BTC1_146JE was anchored on the basis of its complete alignment to contig54150 and similarity of flanking sequence in the contig to the human genome shown as a vertical line along the track. This region is syntenic to a segment of BTA21 (shown as a separate track), consistent with RH mapping data [23]. UCSC Genome Browser tracks for known human proteins, Genscan genes, sno/miRNA, conserved sequences, and segmental duplication are unmodified.

Figure 4.

Figure 4

Open in a new tab

Genomic context of BTC1_113FL. Top panel (A). A modified image from the UCSC cow genome browser (March 2005, Btau_2.0) showing BTC1_113FL aligned to the cow genome (Contig74653; GenBank accession no. AAFC02073929). A track for cattle ESTs ("squish mode") shows high support for alternatively spliced cattle transcripts encoded in this region and the presence of 3' exons of SECP43. Genscan predicts a gene within the alignment of BTC1_113FL but does not predict all of the exons from ESTs. A CpG island is located at the 5' end of the predicted gene. Bottom panel (B). Anchoring of BTC1_113FL represented as a block arrow, to HSA1p35.3 (May 2004, Hg17). BTC1_113FL, was anchored on the basis of its complete alignment to cattle contig74653 and similarity of flanking sequence in the contig to the human genome (shown as vertical lines along the track). This region is syntenic to a segment of BTA2 (shown as a separate track), consistent with RH mapping data [23]. UCSC Genome Browser tracks for known human proteins, Genscan genes, sno/miRNA, conserved sequences, and segmental duplication are unmodified.

BTC1_14RD and BTC1_130FL: alternatively spliced mRNAs of a novel, paralogous gene residing amongst known transcription factors

BTC1_14RD (GenBank:XM_611254) and BTC1_130FL have 93% and 92% nucleotide identity, respectively, to artiodactyla-specific transcript 1 (Ast1) identified by Kim and coworkers [25]. Neither gene has an ortholog in the human or mouse genome. The three transcripts, Ast1, BTC1_14RD and BTC1_130FL, were aligned to BAC AC146804 (Figure 2; Additional file 6). Both BTC1_14RD and BTC1_130FL mapped at position BTA18:55591560–55600453, 5.4 kb from Ast1 (Figure 2). Genscan [26] also predicts a cattle gene in this region, which is supported by alignment of numerous cattle ESTs and a CpG island flanking the transcription start site (Figure 2). From the alignments it is apparent that BTC1_130FL is an alternatively spliced form of BTC1_14RD and that both transcripts represent a gene that is paralogous (>90% similar) to Ast1 (Additional file 6). The assumptive human genome context of BTC_14RD and BTC1_130FL was then investigated by anchoring to the human genome, conserved sequences flanking the NTs in the cattle BAC AC146804 (on BTA18). Nucleotide similarity was used to anchor BTC1_14RD, BTC1_130FL and Ast1 mRNAs to HSA19q, between the human genes ZNF71 and ZIM2 (Figure 2). This region of the human genome is rich in retrotransposed sequences, imprinted genes (PEG3 and Zim2) and genes encoding zinc-finger proteins thus indicating a high level of evolutionary and biological activity.

BTC1_146JE: a putative non coding RNA

BTC1_146JE is a 2206 bp transcript that contains an inverse repeat, and is found only in cattle and bottleneck dolphin (cetartiodactyl-specific). There is no ORF and no BLAST hit to any non-cetartiodactyl exon within 5 kb of flanking genomic sequence 5' and 3' of the NT gene on BTA21 (Figure 3; Table 3). A large number of unannotated, spliced cattle ESTs align to contig54150 in the same position further supporting its characterization as a novel spliced transcript.

The genomic DNA sequence flanking BTC1_146JE in contig54150 permitted comparative anchoring to HSA14q32.31 in an intergenic, non-conserved region containing a cluster of small nucleolar RNAs (snoRNAs; Figure 3). These snoRNAs are encoded in the introns of the non-coding maternally expressed gene MEG8 [27]. MEG8 is currently not included in the UCSC [28] database of known genes and thus not shown in Figure 3. To test the possibility that BTC1_146JE represents the pre-processed RNA for a snoRNA, a BLASTN search was carried out using the cluster of snoRNAs as query sequences (word size 7 and E-value threshold of 0.01). The 71 bp snoRNAs 14q(II-8) and 14q(11-9) [27] aligned with BTC1_146JE with short matches (23/26 and 27/30 identities, respectively). This suggests that BTC1_146JE represents a precursor RNA from which a cetartiodactyl-specific snoRNA (or miRNA) is processed.

BTC1_113FL: a novel transcript expressed preferentially in the thalamus

BTC1_113FL (GenBank:XM_611248) is a 659 bp transcript found only in cattle. It encodes a hypothetical protein 69 aa in length and whose gene is located on BTA2 (Table 3). Alignment of BTC1_113FL to cattle contig74653 reveals a gene with five exons (Figure 4). The gene is located within 1.5 Kbp of the 3' end of and in opposite orientation to SECP43. The presence of a gene in this location is strongly supported by a large number of spliced ESTs containing at least one GT/AG splice site, a Genscan prediction of 2 exons, a CpG island that spans the first exon and the probable transcription start site (Figure 4), and detection of expression in multiple tissues. DNA sequence flanking the gene corresponding to BTC1_113FL on contig74653 anchors it to HSA1p35.3, consistent with the available comparative mapping data [23]. Visual inspection indicates that BTC1_113FL should fall in a region of the human genome occupied by MGC45806 (GenBank:NM_152304), a RAB GTPase oncogene involved in vesicle-trafficking; however, BLASTN, TBLASTX and TBLASTN searches of BTC1_113FL against MGC45806 sequence resulted in no significant matches, demonstrating a lack of detectable homology between the exons of the two transcripts. BLAT [28] alignment of this NT against the human genome also reveals no alignment anywhere within the chromosome cytogenetic band where the NT is anchored by its flanking sequence. These data provide evidence that BTC1_113FL is a lineage-specific novel transcript.

Expression and tissue distribution of NTs

Expression levels of the NTs were analyzed in 17 tissues from a one week-old Jersey calf and a term placentome. Expression of 86/91 NTs could be analyzed (5 had no representative cDNA element on the microarray). The expressed NTs were categorized with respect to the presence or absence of ORF(s) as well as with expression levels classified as high, moderate or low on the basis of an arbitrary scale (Table 5). Among the 60 expressed NTs with ORFs, 55% were expressed at a low level in all 18 tissues, and 45% were expressed at moderate or high levels in one or more tissues (Table 5). A similar distribution of expression levels in tissues was found among the NTs without ORFs. Tissue-preference in expression patterns of NTs was analyzed further by determining those NTs that were expressed greater than two-fold in any one tissue compared to at least 13 out of 17 other tissues (Figure 5; Additional file 2). A total of 39 NTs show tissue preference in their expression pattern. Of these, 28 were preferentially expressed in a single tissue. Six NTs were preferentially expressed in placentome, of which two were predicted to be ncRNAs. Ten different tissues showed exclusive expression of one or more of the NTs, with placentome and thymus having the largest number.

Table 5.

Expression levels of 86 NTs

Expression Levela NTs with ORFs NTs with no identifiable ORF
High 12 (14%) 5 (6%)
Moderate 14 (16%) 10 (11%)
Low 33 (38%) 12 (14%)
Open in a new tab

a See Materials and Methods for definition

Figure 5.

Figure 5

Open in a new tab

Preferential expression of 39 NTs in 18 sampled tissues. Orange bars indicate NTs with no ORF and preferential expression in more than one tissue. Yellow bars indicate NTs with ORFs and preferential expression in more than one tissue. Blue bars represent NTs with no ORF and preferential expression in a single tissue. Purple bars represent NTs with ORFs and preferential expression in a single tissue. M.L.; mesenteric lymph node.

Discussion

Comparative genomics, bioinformatics and microarray analysis were used to identify 91 transcripts encoded in the cattle genome, but not encoded in the genomes of non-ferungulate mammals (see further discussion below concerning the dog genome). The yield of NTs from the original EST collection is 91/12,614 = 0.8%, suggesting that NTs are relatively rare. Among the 91 NTs, 78 ORFs were identified, of which 48 are <100 codons and 30 are >100 codons (Figure 1; Additional file 3). The latter have a high probability of coding for a protein [29]. Using InterProScan [30], the lack of Pfam HMM matches for 99% of NT ORFs is strong evidence for absence of homology to known proteins. Anchoring the NTs to the cattle genome allowed identification of 30 transcripts having CpG islands upstream of their start sites (Additional file 2), providing additional support for their classification as protein-coding genes or ncRNAs. Specific protein functional motifs were identified in 10 predicted proteins encoded by the NTs, and 29 have functional non-coding motifs (Table 2; Additional file 2). All but five of the NTs showed evidence of active transcription in one or more tissues, and six were found to be preferentially expressed in cattle placentome, which is the source tissue of the EST collection used to mine for NTs. These results collectively provide the first conclusive evidence for an abundance of lineage- and tissue-specific transcripts encoded in the cattle genome.

The 21 NTs identified as high-probability ncRNAs provide a useful set of probes for exploring gene regulation in placental development and function [5,6]. Five of the putative ncRNAs are preferentially expressed in tissues that comprise the brain-immune-endocrine axis; placentome, thymus, thalamus, cerebrum or cerebellum. Seven contain inverted repeats that may be involved in internal base-pairing and gene regulation [31]. These putative ncRNAs may thus represent spliced, single-exon, primary snoRNA or microRNA transcripts [6]. Although microRNAs (miRNAs), snoRNAs and other ncRNAs that are not polyadenylated, may have been filtered out using our methods, on the basis of our findings, it is clear that placenta is a rich source of ncRNAs. Further studies are needed to clarify their functions in placental physiology.

The availability of a draft of the cattle genome sequence provided an opportunity to study the comparative genomic organization of the NTs, to confirm their authenticity, and to distill evidence for their origin, evolution and function. For the examples presented, as well as others in the dataset, the genes encoding the NTs are flanked by genes that are conserved in the human genome. This allowed us to identify a presumptive human genome context for the NTs. The recent availability of a 7.6× draft of the dog genome sequence allowed us to ask ex post facto whether the NTs are present in the dog genome. It was interesting to find that only five of the NTs (BTC_55FL, BTC1_102FL, BTC1_390NG, BTC1_21PW, and BTC1_40RD) matched sequences in the dog genome, suggesting that the sequences encoding these NTs were present in a ferungulate ancestor. The most parsimonious explanation for the presence of NTs in the cattle genome but not in other non-ferungulate mammalian genomes is that the NT genes were deleted from a common ancestor of primates and rodents after its divergence from the ferungulates (assuming that these five NTs will be found in other ferungulate genomes as well). Thus, in total, 65 NTs were identified that are (to date) only found in cattle, and 21 were identified in cattle and other cetartiodactyla (Table 4). Among the ruminants, this could represent the de novo formation of genes by overprinting [32], more recent gene deletion, extreme divergence, or the lack of complete genome sequence information for the other species. Other proposed mechanisms for the appearance of lineage-specific genes, such as retrotransposition [reviewed in [33]], are not excluded by our analysis. Further study of the phylogenetic distribution of the NT genes will provide a better understanding of their origin, and the timing of gene loss/gain in ancestral species.

The cetartiodactyl NTs BTC1_14RD and BTC1_130FL represent interesting examples of transcripts that are encoded within a highly dynamic genomic context (Figure 2). BTC1_14RD/BTC1_130FL and Ast1 (artiodactyl-specific transcript1) are located in a region of the cattle genome that is surrounded by genes encoding zinc-finger proteins. Ast1 and its neighboring genes, PEG3 and ZIM2, were previously shown to undergo lineage-specific imprinting, and PEG3 and ZIM2 are thought to have undergone rearrangements independently in different lineages [25]. Roughly 80 Kbp of the cattle genome between PEG3 and ZIM2 (BTA18:55,580 Kbp – 55,655 Kbp) spanning BTC1_14RD and Ast1 is absent in the human genome, and there are a large number of segmental duplications in this region. The entire locus maps ~1 Mbp from the telomere of BTA18. It is known that telomeric and subtelomeric regions are highly active in segmental duplications and the formation of novel genes [34]. Thus, the artiodactyl-specific genes for Ast1 and BTC1_14RD appear to have been created by a segmental duplication. Analysis of other ferungulate genomes will shed greater light on the origin and evolution of these interesting genes. Given their genomic context and imprinting status these genes may play an adaptive role in placental function.

The significant number of novel transcripts expressed preferentially in cattle placenta and in other tissues raises the question of their role in adaptive evolution. Are the genes encoding these transcripts lost in other genomes because they are dispensable or do they have adaptive evolutionary significance? Is gene gain by insertion, segmental duplication and/or chromosome duplication a driving mechanism of adaptive evolution? Evolutionary theory has long held that adaptive phenotypic change is realized through changes in developmental processes [35]. The genes that control these developmental processes are known to be highly conserved [36] and it is believed that adaptive evolutionary change is fueled by mutations that modify the expression of these conserved regulatory loci [36,37]. We and others have proposed that rapidly evolving genes, "novel" or lineage-specific genes, and ncRNAs play a role in mediating changes in gene expression that affect regulatory genes controlling fundamental developmental processes [13,38-40]. Lineage-specific genes can appear as a result of non-homologous recombination of exons between different genes [32,41-43], or from fast-evolving duplicated genes that have lost significant sequence similarity even within relatively short evolutionary time-spans [44,45]. Keese and Gibbs [32] provided numerous examples of genes that are created de novo by translation of previously unused reading frames of existing coding and non-coding genomic DNA, a mechanism that has been called "overprinting" [46,47]. Each of the NTs has its own evolutionary history, and understanding their origins will require sequence information from additional mammalian genomes. Whether they are rapidly evolving and dispensable [48] and/or have adaptive functions can only be determined by experimentation [37].

Conclusion

The 91 lineage-specific transcripts discovered in the present study are a new resource for studies of adaptive changes in placental architecture and function. The tissue distribution of the NTs suggests that many of them also have adaptive roles in other tissues. The presence of so many lineage-specific genes in cattle and their association with subtelomeric regions, which are hotspots for chromosome rearrangements and recombination, suggests that gene loss and gain are important mechanisms of genome evolution in mammals. The sequencing of additional vertebrate genomes with defined phylogenetic relationships will enable the search for lineage-specific genes to take on a more evolutionary perspective that is required to understand their origins and functions.

Methods

Identification and characterization of novel transcripts expressed in cattle placenta

A collection of 12,614 5' ESTs from a normalized and subtracted cattle placenta cDNA library was selected as an EST resource for novel transcript discovery [49]. The repeat-masked ESTs were analyzed for similarity to non-cetartiodactyl ESTs and genomic sequences using BLASTN [15] at a threshold E (expectation value) <10-05, and NCBI dbEST and non-redundant DNA sequence databases from which cetartiodactyl sequences were removed. All ESTs that matched non-cetartiodactyl sequences at E < 10-05 were removed from the starting set (Table 1). Another BLASTN search against human draft sequences at E < 10-10 removed additional ESTs from the set. The entire process of searching, parsing, and subtraction was carried out iteratively with a set of pipelined Perl scripts (PipeBLASTN).

PipeBLASTN was followed by in silico extension of the remaining placenta ESTs using public domain cattle ESTs. The ESTs were extended using a custom clustering algorithm and the CAP3 [50] assembly program. The clusters were created using stringent parameters (minimum overlap length of 40 bp and 95% minimum sequence identity). CAP3 was run with default parameters, on each EST cluster. The in silico extended ESTs were run through PipeBLASTN again to remove any non-cetartiodactyl homologs. The in-house source clones of the remaining 5' extended ESTs were sequenced in the 3' direction using an anchored oligodT primer. The 3' ESTs were vector- and quality-trimmed, repeat-masked, and assembled to their 5' extended counterparts to obtain full-length clone sequences. Those 5'-3' pairs that did not overlap were subjected to additional rounds of primer-walking until complete sequences were obtained.

To extend the newly assembled sequences further the process of clustering and assembly with public domain cattle ESTs followed by PipeBLASTN was carried out again to yield a set of putative NTs and divergent orthologs. The assembled sequences were manually edited and proofed for spurious assemblies, un-called bases, and reverse-complementarity. The divergent homologs were separated from the putative NTs by interrogating the sequences for distant homology in other species using BLASTX against non-redundant proteins (NCBI, April 2006), and TBLASTX against human and mouse UniGene (Build 190 and 152, respectively) and ESTs from other species (NCBI, April 2006). Sequences that aligned to database sequences below an empirically chosen E-value threshold of 10-10 were designated as putative divergent homologs [12], and those that scored above this threshold were designated NTs. The NTs with similarity to cetartiodactyl-specific genes were identified by BLAST against a database of cetartiodactyl-specific non-redundant sequences and ESTs. Sequence data from this article have been deposited with the DDBJ/EMBL/GenBank data libraries and the accession numbers are listed in Additional file 2.

The second assembly (March 2005, Btau_2.0; BCM-HGSC) of the 6.2× cow genome draft sequence [17] was used to determine how many NT source clones were primed from an internal polyA tract during their sequencing from the 3' direction with an anchored oligodT primer. To do this, each NT contig was manually checked to ensure the terminal positioning of the 3' EST within the contig. The NTs were then aligned to the scaffold sequence. The aligned region of the scaffold and flanking 100 bp was extracted for each of the aligned NTs. If the 3' EST of a NT was primed by an internal polyA tract, it would be visible in the scaffold downstream from the 3' end of the aligned NT. These NTs were removed from the set. In addition, trimming of low-quality sequences from 3' ESTs may have resulted in complete or partial removal of the polyadenylation signal. Each of the corresponding scaffold sequences was scanned for the presence of a polyadenylation signal within 50 bp downstream from the end of an aligned NT.

Identification and characterization of ORFs

High-probability ORFs were identified in the NTs using NCBI's ORFfinder [51]. The locations of start and stop signals were determined in all the three reading frames for NTs with a known polyadenylation signal, and in all six reading frames for NTs with no identifiable polyadenylation signal. The most probable complete or longest partial ORFs were selected using a threshold length of 100 bp. The manual analysis of all the six reading frames involved choosing the longest ORF that either contained more than one downstream stop codon, or one or more juxtaposed downstream start and stop signals within 20 codons of each other. The selected ORF contained at most two upstream stop signals, and one upstream ORF < 30 codons in length. The use of a six-frame analysis to select ORFs that were clearly demarcated by strong start and stop signals helped to reduce the probability of picking false ORFs even though we used 33 codons as a threshold. The complete ORFs that had a start and a stop codon were analyzed for the presence of the Kozak consensus, the eukaryotic translation start site context [19]. False positives in ORFs were predicted by randomizing the NT and then predicting ORFs in these sequences using the same rules for ORF prediction [52]. Because ORFS between 33 and 100 codons are predicted to have ~50% false positive rate [52], all ORFs >33 codons were considered as candidates for encoding small novel proteins. The sequences of the NTs and their predicted proteins can be found in Additional files 1 and 3.

The ORFs were analyzed for protein motifs and domains using InterProScan [30]. Only those motifs with a precision rate >93% were reported [53]. Additionally, ORFs were searched for transmembrane helices using TMHMMv2.0 [54] and SVMtm [55], and for signal peptides using SignalP with both neural networks and hidden Markov models [56]. Conflicting predictions of a signal peptide and a transmembrane region in the same sequence were resolved as follows: i) if the prediction was within 15 codons from the 5' end then the prediction was counted as a signal peptide; ii) if the signal peptide was predicted anywhere else, Phobius [57] was used to confirm either prediction.

The ORFs were searched for novel repeated protein domains using the methodology and software described by Yeats et al. [58]. Prospero was used to self-search the ORFs for occurrence of internal duplications. Alignments with a length of less than 30 residues (threshold length of a protein domain) were removed. To search for repeated domains, alignments in which the start points of each sub-sequence were separated by less than 45 residues were discarded. The alignments generated by Prospero were used as an initial alignment to make profile Hidden Markov models using HMMER [59], and the resulting alignments were scanned against the Swiss-Prot database.

Characterization of non-coding regions

The NT sequences were scanned for functional UTR elements using UTRScan [60]. To identify UTR elements that may occur in NTs by chance, the NTs were randomized using the program shuffle in SQUID software [61], and searched for motifs using UTRScan. This was repeated 10 times. The observed frequency of a motif was compared to that found in the randomized NT sequences. The motif was reported if its observed frequency was at least 4 times greater in the NTs as in the randomized NT sequences. The GC-content of each sequence was estimated with the program geecee from the EMBOSS suite [62]. Candidate CpG islands in 5' exons and non-coding regions were identified by aligning NTs to the cattle genome. The aligned scaffold region and 200 bp upstream from the start of the alignment were extracted. These sequences were searched with the command-line version of CpG Island Searcher [21] using a minimum CpG island length of 200 bp, minimum GC-content of 53%, and observed/expected CpG ratio of 0.63. The choice of parameter values was based on the averages found by Takai and Jones [21] for exonic CpG islands. Additionally, each NT sequence was searched against itself to identify IRs and confirmed independently using the einverted program [62].

The NTs were analyzed for guanine-rich sequence motifs capable of forming three-dimensional structures called G-quadruplexes or G-quartets [22]. On the basis of the algorithm by D'Antonio and Bagga [63], a program was written to identify the G-quartet motif in the NTs. The results were compared with results obtained using shuffled sequences as a control. QRNA [64] was used to search for conserved ncRNA structures amongst the NTs. The input to QRNA was a file containing the search results from a BLASTN of NTs against the non-redundant DNA sequence database. Default parameters were used, and the results were compared with another run of QRNA using shuffled data as a control.

Microarray expression analysis

The gene expression data for the NTs was extracted from a larger microarray data set obtained by profiling total RNA from 17 different tissues collected by vivisection of a one week-old Jersey calf (NCBI Gene Expression Omnibus series entry GSE3029) and term placentome. Expression patterns were obtained using a microarray containing approximately 7000 cattle placenta cDNAs spotted in duplicate on glass slides [65]. The expression profiles for each tissue were obtained by comparing expression of each gene to a reference standard comprised of RNAs from bovine brain and three different cell lines [65]. In order for a gene to be included in the analysis, its fluorescence intensity had to be greater than three standard deviations (SD) above the background in either the sample or reference standard. All but five of the NTs were represented on this array by a cDNA clone.

The NTs were further categorized based on their fluorescence intensity values. Expression was considered as "high" if the fluorescence intensity was greater than 5000 +3SD above background in at least one tissue, "moderate" if fluorescence intensity was between 1000 and 5000 in at least one tissue, and "low" if the fluorescence intensity was between 50 and 1000 +3SD above background in all 18 tissues.

To determine the number of transcripts that were preferentially expressed in the eighteen tissues, the ratio of the normalized intensity ratio was calculated for every pair of tissues (ratio-of-ratios) using a Perl script. For a transcript to be considered as preferentially expressed in a given tissue t, the following relationship had to hold true in at least 13 out of 17 other tissues:

R (t)/R (any other tissue) > 2,

where R is the normalized intensity ratio (tissue:reference).

Analysis of the cattle and assumptive human genome context of NTs

The number of NTs with matches in the cattle genome and those showing evidence of splicing were determined using a BLASTN search against all cattle genome sequences, including the draft assembly (March 2005, Btau_2.0, BCM-HGSC; and NCBI BACs). The NTs having evidence of "split matches" were analyzed using est2genome [62] in order to determine exon-intron boundaries. An NT was classified as spliced if, after alignment to genomic sequence, the intron-exon boundary had a GT/AG splice site.

To identify candidate ncRNAs amongst the NTs that lacked an ORF, the NTs were aligned to the cattle genome assembly. Whenever possible, the aligned region and 5 kb of flanking sequences was extracted from each of the aligned scaffolds. The extracted region was searched for the presence of exons by doing a BLASTX search against Swiss-Prot and non-redundant protein databases using an E-value threshold of 10-03. All NTs that lacked an ORF and aligned to sequence scaffolds with no BLASTX hits were characterized as candidate ncRNAs.

The NTs were mapped in silico to the cattle genome using BLASTN search of the NTs against the cattle genome assembly and repeat-masked cattle genome scaffolds (March 2005, Btau_2.0, BCM-HGSC). The scaffolds containing the NTs were searched for similarity to the human genome, (NCBI Build 35; E < 10-05). The chromosome number, start and end positions, and orientation were parsed for the top human BLASTN hit to the cattle assembly sequences (Additional file 5). Custom tracks were generated using these data, and loaded onto the UCSC Genome Browser [66,28]. Using the cattle-human comparative map [23] also available on the UCSC Human Genome Browser, the position of the NTs on cattle chromosomes could be accurately placed. The cattle-human comparative map was also used to identify NTs that were located within 1 Mbp of evolutionary breakpoints, and within 2 Mbp of telomeres. The distribution of the 91 NTs was compared to the distribution of 91 random RefSeq genes by simulation as performed by Murphy et al. [67]. Chi-square test was performed to determine if NTs are associated with subtelomeric regions.

In order to estimate where the genes encoding the NTs would be if they were present in the human genome, conserved sequences in cattle contigs flanking each NT were used to anchor them in the human genome. The orientation and distance of the NT in the cattle assembly was used to juxtapose the NT in the human genome sequence. The annotation of each NT in the cattle and human genomes can be found in Additional file 2.

Note added in proof

The authors recognize that the annotation of the 91 NTs may change with updated versions of RefSeq and other genome databases. A table containing updates to the annotation of these sequences will be available at the Laboratory of Mammalian Genome Biology website [68].

Authors' contributions

CGK participated in the design of the study, wrote the computer programs for the pipeline, EST clustering, expression and genome analysis, conducted the sequence analysis and interpretation of data, and drafted the manuscript. JHL participated in the design of the study, and assisted in the collection and analysis of DNA sequence data. MRB contributed microarray data. HAL supervised the research, participated in the design of the study, interpretation of data and drafting of the manuscript. All authors have read the manuscript, provided critical reviews of content, and approved the final manuscript.

Supplementary Material

Additional file 1

FASTA formatted full-length clone sequence for 91 NTs

Click here for file (105KB, txt)
Additional file 2

Feature table for 91 NTs

Click here for file (53KB, xls)
Additional file 3

FASTA formatted predicted protein sequence for 64 NTs

Click here for file (11.1KB, txt)
Additional file 4

Secondary structure of the class 2 SECIS element identified in the NT BTC1_43PW. The element contains a characteristic conserved SECIS core followed by an 11 bp stem. All the conserved bases are shown in bold.

Click here for file (10KB, pdf)
Additional file 5

Cattle genome BLAT alignments to NTs, and cattle contig BLAT alignments to human genome

Click here for file (43.5KB, xls)
Additional file 6

Alignment of BTC1_14RD, BTC1_130FL and Ast1 transcripts to cattle genomic sequence. A) Pipmaker [69] output depicts the alignment of the three transcripts to the cattle BAC sequence AC146804 [25]. The artiodactyl-specific transcript, Ast1 [GenBank:AY427788] [25], is organized as 4 exons. The NT BTC1_14RD is organized as 7 exons. Ast1 has a predicted ORF length of 152 codons and BTC1_14RD has a predicted ORF length of 235 codons. B) Pipmaker output depicts the alignment of BTC1_130FL, an alternate spliced variant to BTC1_14D, to cattle BAC sequence AC146804. The transcript is organized as 3 exons, and has an ORF length of 135 codons.

Click here for file (54.5KB, doc)

Acknowledgments

Acknowledgements

The authors thank Dr. Robin Everts for placentome microarray data, and Dr. Denis Larkin for assistance with comparative mapping. This study and the authors' contributions to it were funded by a grant to HAL from the USDA National Research Initiative (AG2002-35205-11625). These funding bodies played no role in the design, collection, analysis, interpretation, writing, or the decision to submit the manuscript for publication.

Contributor Information

Charu G Kumar, Email: cgkumar@uiuc.edu.

Joshua H Larson, Email: jhlarson@uiuc.edu.

Mark R Band, Email: markband@uiuc.edu.

Harris A Lewin, Email: h-lewin@uiuc.edu.

References

  1. Schneider H. Placental transport function. Reprod Fertil Dev. 1991;3:345–353. doi: 10.1071/rd9910345. [DOI] [PubMed] [Google Scholar]
  2. Mossman HW. Vertebrate Fetal Membranes. Houndmills: MacMillan; 1987. pp. 288–290. [Google Scholar]
  3. Crespi B, Semeniuk C. Parent-offspring conflict in the evolution of vertebrate reproductive mode. Am Nat. 2004;163:635–53. doi: 10.1086/382734. [DOI] [PubMed] [Google Scholar]
  4. Clark NL, Swanson WJ. Pervasive adaptive evolution in primate seminal proteins. PLoS Genet. 2005;1:0335–0342. doi: 10.1371/journal.pgen.0010035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Carninci P, Kasukawa T, Katayama S, Gough J, Frith MC, Maeda N, Oyama R, Ravasi T, Lenhard B, Wells C, FANTOM Consortium; RIKEN Genome Exploration Research Group and Genome Science Group (Genome Network Project Core Group) The transcriptional landscape of the mammalian genome. Science. 2005;309:1559–1563. doi: 10.1126/science.1112014. [DOI] [PubMed] [Google Scholar]
  6. Mattick JS. Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms. Bioessays. 2003;25:930–939. doi: 10.1002/bies.10332. [DOI] [PubMed] [Google Scholar]
  7. Martens JA, Laprade L, Winston F. Intergenic transcription is required to repress the Saccharomyces cerevisiae SER3 gene. Nature. 2004;429:571–574. doi: 10.1038/nature02538. [DOI] [PubMed] [Google Scholar]
  8. Tupy JL, Bailey AM, Dailey G, Evans-Holm M, Siebel CW, Misra S, Celniker SE, Rubin GM. Identification of putative noncoding polyadenylated transcripts in Drosophila melanogaster. Proc Natl Acad Sci USA. 2005;102:5495–5500. doi: 10.1073/pnas.0501422102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Roberts RM, Ealy AD, Alexenko AP, Han C-S, Ezashi T. Trophoblast interferons. Placenta. 1999;20:259–264. doi: 10.1053/plac.1998.0381. [DOI] [PubMed] [Google Scholar]
  10. Byatt JC, Shimomura K, Duello TM, Bremel RD. Isolation and characterization of multiple forms of bovine placental lactogen from secretory granules of the fetal cotyledon. Endocrinology. 1986;119:1343–1350. doi: 10.1210/endo-119-3-1343. [DOI] [PubMed] [Google Scholar]
  11. Xie S, Green J, Bixby JB, Szafranska B, DeMartini JC, Hecht S, Roberts RM. The diversity and evolutionary relationships of the pregnancy-associated glycoproteins, an aspartic proteinase subfamily consisting of many trophoblast-expressed genes. Proc Natl Acad Sci USA. 1997;94:12809–12816. doi: 10.1073/pnas.94.24.12809. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Larson JH, Kumar CG, Everts RE, Green C, Everts-van der Wind A, Band MR, Lewin HA. Discovery of eight novel divergent homologs expressed in cattle placenta. Physiol Genomics. 2006;25:405–413. doi: 10.1152/physiolgenomics.00307.2005. [DOI] [PubMed] [Google Scholar]
  13. Lewin HA, Larson JH, Kumar CG. From Comparative mammalian genomics and adaptive evolution: divergent homologs and novel genes in the cattle genome. In: Wasser SP, editor. Evolutionary Theory and Processes: Modern Horizons, Papers in Honour of Eviatar Nevo. The Netherlands: Kluwer Academic Publishers; 2004. pp. 139–152. [Google Scholar]
  14. Larson JH, Marron BM, Beever JE, Roe BA, Lewin HA. Genomic organization and evolution of the ULBP genes in cattle. BMC Genomics. 2006;7:227–241. doi: 10.1186/1471-2164-7-227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–410. doi: 10.1016/S0022-2836(05)80360-2. [DOI] [PubMed] [Google Scholar]
  16. Wheeler DL, Church DM, Lash AE, Leipe DD, Madden TL, Pontius JU, Schuler GD, Schriml LM, Tatusova TA, Wagner L, Rapp BA. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2001;29:11–16. doi: 10.1093/nar/29.1.11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Baylor College of Medicine http://www.hgsc.bcm.tmc.edu/projects/bovine
  18. Beaudoing E, Freier S, Wyatt JR, Claverie J-M, Gautheret D. Patterns of variant polyadenylation signal usage in human genes. Genome Res. 2000;10:1001–1010. doi: 10.1101/gr.10.7.1001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kozak M. Possible role of flanking nucleotides in recognition of the AUG initiator codon by eukaryotic ribosomes. Nucleic Acids Res. 1981;9:5233–5252. doi: 10.1093/nar/9.20.5233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Grundner-Culemann E, Martin GW, 3rd, Harney JW, Berry MJ. Two distinct SECIS structures capable of directing selenocysteine incorporation in eukaryotes. RNA. 1999;5:625–635. doi: 10.1017/s1355838299981542. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Takai D, Jones PA. The CpG island searcher: a new WWW resource. In Silico Biol. 2003;3:235–240. [PubMed] [Google Scholar]
  22. Simonsson T. G-quadruplex DNA structures – variations on a theme. Biol Chem. 2001;382:621–628. doi: 10.1515/BC.2001.073. [DOI] [PubMed] [Google Scholar]
  23. Everts-van der Wind A, Larkin DM, Green CA, Elliott JS, Olmstead CA, Chiu R, Schein JE, Marra MA, Womack JE, Lewin HA. A high-resolution whole-genome cattle-human comparative map reveals details of mammalian chromosome evolution. Proc Natl Acad Sci USA. 2005;102:18526–18531. doi: 10.1073/pnas.0509285102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. National Center for Biotechnology Information http://www.ncbi.nlm.nih.gov/
  25. Kim J, Bergmann A, Lucas S, Stone R, Stubbs L. Lineage-specific imprinting and evolution of the zinc-finger gene ZIM2. Genomics. 2004;84:47–58. doi: 10.1016/j.ygeno.2004.02.007. [DOI] [PubMed] [Google Scholar]
  26. Burge C, Karlin S. Prediction of complete gene structures in human genomic DNA. J Mol Biol. 1997;268:78–94. doi: 10.1006/jmbi.1997.0951. [DOI] [PubMed] [Google Scholar]
  27. snoRNA-LBME-db http://www-snorna.biotoul.fr/index.php
  28. UCSC Genome Browser http://genome.ucsc.edu/
  29. Sharp PM, Cowe E. Synonymous codon usage in Saccharomyces cerevisiae. Yeast. 1991;7:657–678. doi: 10.1002/yea.320070702. [DOI] [PubMed] [Google Scholar]
  30. Mulder NJ, Apweiler R, Attwood TK, Bairoch A, Barrell D, Bateman A, Binns D, Biswas M, Bradley P, Bork P, et al. The InterPro Database, 2003 brings increased coverage and new features. Nucleic Acids Res. 2003;31:315–318. doi: 10.1093/nar/gkg046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. LeBlanc MD, Aspeslagh G, Buggia NP, Dyer BD. An annotated catalog of inverted repeats of Caenorhabditis elegans chromosomes III and X, with observations concerning odd/even biases and conserved motifs. Genome Res. 2000;10:1381–1392. doi: 10.1101/gr.122700. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Keese PK, Gibbs A. Origin of genes: "Big Bang" or continuous creation? Proc Natl Acad Sci USA. 1992;89:9489–9493. doi: 10.1073/pnas.89.20.9489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Long M, Betrán E, Thornton K, Wang W. The origin of new genes: glimpses from the young and old. Nat Rev Genet. 2003;4:865–875. doi: 10.1038/nrg1204. [DOI] [PubMed] [Google Scholar]
  34. Linardopoulou EV, Williams EM, Fan Y, Friedman C, Young JM, Trask BJ. Human subtelomeres are hot spots of interchromosomal recombination and segmental duplication. Nature. 2005;437:94–100. doi: 10.1038/nature04029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. de Beer GR. Embryos and Ancestors. Oxford: Clarendon Press; 1951. pp. 19–20. [Google Scholar]
  36. Raff RA. The Shape of Life: Genes, Development, and the Evolution of Animal Form. Chicago: The University of Chicago Press; 1996. [Google Scholar]
  37. McDonald JF. The molecular basis of adaptation: A critical review of relevant ideas and observations. Ann Rev Ecol Syst. 1983;14:77–102. [Google Scholar]
  38. Brosius J. RNAs from all categories generate retrosequences that may be exapted as novel genes or regulatory elements. Gene. 1999;238:115–134. doi: 10.1016/s0378-1119(99)00227-9. [DOI] [PubMed] [Google Scholar]
  39. Hughes AL, Green JA, Garbayo JM, Roberts RM. Adaptive diversification within a large family of recently duplicated placentally expressed genes. Proc Natl Acad Sci USA. 2000;97:3319–3323. doi: 10.1073/pnas.050002797. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Schmid KJ, Aquadro CF. The evolutionary analysis of "orphans" from the Drosophila genome identifies rapidly diverging and incorrectly annotated genes. Genetics. 2001;159:589–598. doi: 10.1093/genetics/159.2.589. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Gilbert W, deSouza SJ, Long M. Origin of genes. Proc Natl Acad Sci USA. 1997;94:7698–7703. doi: 10.1073/pnas.94.15.7698. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Olson MV. When less is more: gene loss as an engine of evolutionary change. Am J Hum Genet. 1999;64:18–23. doi: 10.1086/302219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Yamauchi A, Nakashima T, Tokuriki N, Hosokawa M, Nogami H, Arioka S, Urabe I, Yomo T. Evolvability of random polypeptides through functional selection within a small library. Protein Eng. 2002;15:619–626. doi: 10.1093/protein/15.7.619. [DOI] [PubMed] [Google Scholar]
  44. Schmid KJ, Tautz D. A screen for fast evolving genes from Drosophila. Proc Natl Acad Sci USA. 1997;94:9746–9750. doi: 10.1073/pnas.94.18.9746. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Domazet-Loso T, Tautz D. An evolutionary analysis of orphan genes in Drosophila. Genome Res. 2003;13:2213–2219. doi: 10.1101/gr.1311003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Grassé P-P. Evolution of Living Organisms. New York: Academic Press; 1977. p. 297. [Google Scholar]
  47. Ohno S. Birth of a unique enzyme from an alternative reading frame of the preexisted, internally repetitious coding sequence. Proc Natl Acad Sci USA. 1984;81:2421–2425. doi: 10.1073/pnas.81.8.2421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Zhang J, He X. Significant impact of protein dispensability on the instantaneous rate of protein evolution. Mol Biol Evol. 2005;22:1147–55. doi: 10.1093/molbev/msi101. [DOI] [PubMed] [Google Scholar]
  49. Band MR, Olmstead C, Everts RE, Liu ZL, Lewin HA. A 3800 gene microarray for cattle functional genomics: comparison of gene expression in spleen, placenta and brain. Anim Biotechnol. 2002;3:163–172. doi: 10.1081/ABIO-120005779. [DOI] [PubMed] [Google Scholar]
  50. Huang X. An improved sequence assembly program. Genomics. 2002;33:21–31. doi: 10.1006/geno.1996.0155. [DOI] [PubMed] [Google Scholar]
  51. NCBI's ORF finder http://www.ncbi.nlm.nih.gov/gorf/gorf.html
  52. Frishman D, Mironov A, Mewes HW, Gelfand M. Combining diverse evidence for gene recognition in completely sequenced bacterial genomes. Nucleic Acids Res. 1998;26:2941–2947. doi: 10.1093/nar/26.12.2941. Erratum in: Nucleic Acids Res 1998, 26: 3870. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Prosite http://expasy.org/prosite/
  54. Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001;305:567–580. doi: 10.1006/jmbi.2000.4315. [DOI] [PubMed] [Google Scholar]
  55. Yuan Z, Mattick JS, Teasdale RD. SVMtm: Support vector machines to predict transmembrane segments. J Comput Chem. 2004;25:632–636. doi: 10.1002/jcc.10411. [DOI] [PubMed] [Google Scholar]
  56. Nielsen H, Krogh A. Prediction of signal peptides and signal anchors by a hidden Markov model. Proc Int Conf Intell Syst Mol Biol. 1998;6:122–130. [PubMed] [Google Scholar]
  57. Käll L, Krogh A, Sonnhammer ELL. A combined transmembrane topology and signal peptide prediction method. J Mol Biol. 2004;338:1027–1036. doi: 10.1016/j.jmb.2004.03.016. [DOI] [PubMed] [Google Scholar]
  58. Yeats C, Bentley S, Bateman A. New knowledge from old: In silico discovery of novel protein domains in Streptomyces coelicolor. BMC Microbiol. 2003;3:3–23. doi: 10.1186/1471-2180-3-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Eddy SR, Mitchison G, Durbin R. Maximum discrimination hidden Markov models of sequence consensus. J Comput Biol. 1995;2:9–23. doi: 10.1089/cmb.1995.2.9. [DOI] [PubMed] [Google Scholar]
  60. Pesole G, Gissi C, Catalano D, Grillo G, Licciulli F, Liuni S, Attimonelli M, Saccone C. MitoNuc and MitoAln: two related databases of nuclear genes coding for mitochondrial proteins. Nucleic Acids Res. 2000;28:163–165. doi: 10.1093/nar/28.1.163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Eddy lab http://selab.wustl.edu/cgi-bin/selab.pl?mode=software#squid
  62. Rice P, Longden I, Bleasby A. EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet. 2000;16:276–277. doi: 10.1016/s0168-9525(00)02024-2. [DOI] [PubMed] [Google Scholar]
  63. D'Antonio L, Bagga P. Computational methods for predicting intramolecular G-quadruplexes in nucleotide sequences. Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference (CSB'04) 2004. pp. 561–562.
  64. Rivas E, Eddy SR. Non-coding RNA gene detection using comparative sequence analysis. BMC Bioinformatics. 2001;2:8–27. doi: 10.1186/1471-2105-2-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Everts RE, Band MR, Lewis ZL, Kumar CG, Liu L, Loor JL, Oliveira R, Lewin HA. A 7,872 cDNA Microarray and its use in bovine functional genomics. Vet Immunol Immunopathol. 2005;105:235–245. doi: 10.1016/j.vetimm.2005.02.003. [DOI] [PubMed] [Google Scholar]
  66. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D. The human genome browser at UCSC. Genome Res. 2002;12:996–1006. doi: 10.1101/gr.229102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Murphy WJ, Larkin DM, Everts-van der Wind A, Bourque G, Tesler G, Auvil L, Beever JE, Chowdhary BP, Galibert F, Gatzke L, et al. Dynamics of mammalian chromosome evolution inferred from multispecies comparative maps. Science. 2005;309:613–617. doi: 10.1126/science.1111387. [DOI] [PubMed] [Google Scholar]
  68. Laboratory of Mammalian Genome Biology http://lewinlab.igb.uiuc.edu/Research/NovelGenes.html
  69. Schwartz S, Zhang Z, Frazer KA, Smit A, Riemer C, Bouck J, Gibbs R, Hardison R, Miller W. PipMaker – a web server for aligning two genomic DNA sequences. Genome Res. 2000;10:577–586. doi: 10.1101/gr.10.4.577. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1

FASTA formatted full-length clone sequence for 91 NTs

Click here for file (105KB, txt)
Additional file 2

Feature table for 91 NTs

Click here for file (53KB, xls)
Additional file 3

FASTA formatted predicted protein sequence for 64 NTs

Click here for file (11.1KB, txt)
Additional file 4

Secondary structure of the class 2 SECIS element identified in the NT BTC1_43PW. The element contains a characteristic conserved SECIS core followed by an 11 bp stem. All the conserved bases are shown in bold.

Click here for file (10KB, pdf)
Additional file 5

Cattle genome BLAT alignments to NTs, and cattle contig BLAT alignments to human genome

Click here for file (43.5KB, xls)
Additional file 6

Alignment of BTC1_14RD, BTC1_130FL and Ast1 transcripts to cattle genomic sequence. A) Pipmaker [69] output depicts the alignment of the three transcripts to the cattle BAC sequence AC146804 [25]. The artiodactyl-specific transcript, Ast1 [GenBank:AY427788] [25], is organized as 4 exons. The NT BTC1_14RD is organized as 7 exons. Ast1 has a predicted ORF length of 152 codons and BTC1_14RD has a predicted ORF length of 235 codons. B) Pipmaker output depicts the alignment of BTC1_130FL, an alternate spliced variant to BTC1_14D, to cattle BAC sequence AC146804. The transcript is organized as 3 exons, and has an ORF length of 135 codons.

Click here for file (54.5KB, doc)

Articles from BMC Genomics are provided here courtesy of BMC

RESOURCES