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. 2020 Oct 21;4(10):e00272. doi: 10.1002/pld3.272

A curated list of genes that affect the plant ionome

Lauren Whitt 1, Felipe Klein Ricachenevsky 2, Greg Ziegler Ziegler 1, Stephan Clemens 3, Elsbeth Walker 4, Frans J M Maathuis 5, Philip Kear 6, Ivan Baxter 1,✉
PMCID: PMC7576880  PMID: 33103043

Abstract

Understanding the mechanisms underlying plants’ adaptation to their environment will require knowledge of the genes and alleles underlying elemental composition. Modern genetics is capable of quickly, and cheaply indicating which regions of DNA are associated with particular phenotypes in question, but most genes remain poorly annotated, hindering the identification of candidate genes. To help identify candidate genes underlying elemental accumulations, we have created the known ionome gene (KIG) list: a curated collection of genes experimentally shown to change uptake, accumulation, and distribution of elements. We have also created an automated computational pipeline to generate lists of KIG orthologs in other plant species using the PhytoMine database. The current version of KIG consists of 176 known genes covering 5 species, 23 elements, and their 1588 orthologs in 10 species. Analysis of the known genes demonstrated that most were identified in the model plant Arabidopsis thaliana, and that transporter coding genes and genes altering the accumulation of iron and zinc are overrepresented in the current list.

Keywords: curated, ionomics, mineral nutrition

1. INTRODUCTION

Understanding the complex relationships that determine plant adaptation will require detailed knowledge of the action of individual genes, the environment, and their interactions. One of the fundamental processes that plants must accomplish is to manage the uptake, distribution, and storage of elements from the environment. Many different physiological, chemical, biochemical, and cell biology processes are involved in moving elements, implicating thousands of genes in every plant species. Modern genetic techniques have made it easy and inexpensive to identify hundreds to thousands of loci for traits, such as the elemental composition (or ionome) of plant tissues. However, moving from loci to genes is still difficult as the number of possible candidates is often extremely large and the ability of researchers to identify a candidate gene from its functional annotations is limited by our current knowledge and inherent biases about what is worth studying (Stoeger et al., 2018; Baxter, 2020).

The most obvious candidates for genes affecting the ionome in a species are orthologs of genes that have been shown to affect elemental accumulation in another species. Indeed, there are multiple examples of orthologs affecting elemental accumulation in distantly related species, such as Arabidopsis thaliana and rice (Oryza sativa), including Na+ transporters from the HKT family (Ren et al., 2005; Baxter et al., 2010); the heavy metal transporters AtHMA3 and OsHMA3 (Chao et al., 2012; Yan et al., 2016); E3 ubiquitin ligase BRUTUS and OsHRZs that regulate the degradation of iron uptake factors (Selote et al., 2015; Hindt et al., 2017; Kobayashi et al., 2013) and the K+ channel AKT1 (Ahmad et al., 2016; Lagarde et al., 1996). To our knowledge, no comprehensive list of genes known to affect elemental accumulation in plants exists. To ameliorate this deficiency, we sought to create a curated list of genes based on peer‐reviewed literature along with a pipeline to identify orthologs of the genes in any plant species and a method for continuously updating the list. Here we present version 1.0 of the known ionome gene (KIG) list.

2. MATERIALS AND METHODS

The list includes all functionally characterized genes from the literature that are linked to changes in the ionome. Criteria for inclusion in the primary KIG list were as follows:

  1. The function or levels of the gene are unambiguously altered (i.e., a confirmed knockout, knockdown or overexpressor). For double mutants, both genes are listed.

  2. The levels of at least one element are significantly altered in plant tissue.

  3. Publication in the form of a peer‐reviewed manuscript.

Note that our definition excludes genes that are linked to metal tolerance or sensitivity but do not alter the ionome, or genes where the levels of the transcript are correlated with elemental accumulation. In order to identify the KIG genes, we created a Google survey that was distributed to members of the Ionomicshub research coordination network (NSF DBI‐0953433), as well as advertising on Twitter and in oral presentations by the authors. We asked submitters to provide the species, gene name (or names where alleles of two genes were required for a phenotype), gene ID(s), tissue(s), element(s) altered, and a DOI link for the primary literature support. Subsequently, authors FKR and LW did an extensive literature search.

2.1. Creating the inferred orthologs list

The known ionome gene list contains known genes from the primary list and their orthologous genes inferred by InParanoid (v4.1) pairwise species comparisons (Remm et al., 2001). The InParanoid files were downloaded from Phytozome for each organism‐to‐organism combination of species in the primary list, plus Glycine max, Sorghum bicolor, Setaria italica, Setaria viridis, and Populus trichocarpa. Orthologs of the primary genes were labeled as “inferred” genes. If a primary gene was also found as an ortholog to a primary gene in another species, the status was changed to “Primary/Inferred” in both species. It is important to note that only primary genes can infer genes; inferred genes cannot infer other genes. The pipeline for transforming the primary list into the known ionomics gene list can be found at https://github.com/baxterlab/KIG.

2.2. Gene Enrichment analysis

Overrepresentation analysis (released July 11, 2019) was performed on the primary and inferred genes in A. thaliana using the GO Consortium's web‐based GO Enrichment Analysis tool powered by the PANTHER (v14) classification system tool (Ashburner et al., 2000; Mi et al., 2017; The Gene Ontology Consortium, 2017). We restricted overrepresentation analysis to A. thaliana because of its dominance in the KIG list and our lack of confidence in the functional annotation of the other species on the list. An analysis performed by Wimalanathan et al. (2018) found that maize gene annotations in databases like Gramene and Phytozome lacked GO annotations outside of automatically assigned, electronic annotations (IEA). IEA annotations are not curated and have the least amount of support out of all the evidence codes (Harris et al., 2004). A. thaliana annotations come from a variety of evidence types, showing a higher degree of curation compared to maize (Wimalanathan et al., 2018). The whole‐genome Arabidopsis thaliana gene list from the PANTHER database was used as the reference list.

We tested both the PANTHER GO‐slim and the GO complete datasets for biological processes, molecular function, and cellular component. GO‐Slim datasets contain a selected subset of terms that give a broad summary of the gene list, whereas the complete dataset contains all the terms returned for a more detailed analysis. The enriched terms (fold enrichment >1 and with a false discovery rate <0.05) from the complete dataset were sorted into five specific categories relating to the ionome based annotation terms:

  1. Ion homeostasis ‐ terms include homeostasis, stress, detoxification, regulation of an ion

  2. Ion transport ‐ terms specifically state transport, export, import or localization of ion(s). Does not include hydrogen ion transport

  3. Metal ion chelation ‐ terms relating to phytochelatins, other chemical reactions or pathways of metal chelator synthesis

  4. Response to ions—vaguely states response to ions, but does not have any parent annotation terms that offer any more clarification (ie. stress response). Broadly this is referring to any change in the state or activity of cell secretion, expression, movement, or enzyme production (Carbon et al., 2009)

  5. Other transport—annotation stating the transfer of anything that is not an ion (glucose, peptides, etc.)

Genes may belong to more than one category, but if they belong to a parent and child term in the same category, they are only counted once.

3. RESULTS

The current primary list (v1.0) consists of 176 genes from A. thaliana, O. sativa, Medicago truncatula, Triticum aestivum, and Zea mays with the majority coming from A. thaliana and O. sativa (Table 1, Figure 1).

TABLE 1.

Primary known ionome genes

Species GeneID GeneName Elements Tissue Citation(s)
A. thaliana AT1G01340 CNGC10 K, Ca, Mg Roots, shoots Guo et al. (2010)
A. thaliana AT1G01580 FRO2 Fe Root Robinson et al. (1999)
A. thaliana AT1G07600 MT1A Cd, Zn, As Shoots Zimeri et al. (2005)
A. thaliana AT1G08490 CPNIFS Se, S Roots, shoots Van Hoewyk et al. (2005)
A. thaliana AT1G12640 LPCAT1 P Leaf Kisko et al. (2018)
A. thaliana AT1G14040 PHO1;H3 P Shoots Khan et al. (2014)
A. thaliana AT1G14870 PCR2 Zn Shoots Song et al. (2010)
A. thaliana AT1G18910 BTSL2 Fe, Mn, Zn Leaf Hindt et al. (2017)
A. thaliana AT1G20110 FYVE1 Fe, Zn, Co, Mn Root Barberon et al. (2014)
A. thaliana AT1G30270 CIPK23 K Shoots Xu et al. (2006)
A. thaliana AT1G30400 ABCC1 Cd Shoots Park et al. (2012)
A. thaliana AT1G30450 CCC Ca, K, Na,S seeds McDowell et al. (2013)
A. thaliana AT1G31885 NIP3;1 As Shoots Xu et al. (2015)
A. thaliana AT1G32450 AtNRT1.5/ AtNPF7.3 K, NO3‐ Shoots, Roots Li et al. (2017)
A. thaliana AT1G36370 AtMSA1 S, Se Shoots Huang, et al. (2016)
A. thaliana AT1G56160 myb72 Fe, Cd, Zn, Co, Mo Leaf Palmer et al. (2013)
A. thaliana AT1G56430 NAS4 Fe, Cd, Co, Mo Leaf Palmer et al. (2013)
A. thaliana AT1G59870 PEN3 Cd Shoots, roots Kim et al. (2007)
A. thaliana AT1G60960 AtIRT3 Fe Roots Lin et al. (2009)
A. thaliana AT1G62180 AtAPR2 S, Se Shoots Loudet et al. (2007); Chao, et al. (2014)
A. thaliana AT1G63440 AtHMA5 Cu Shoots Andrés‐Colás et al. (2006)
A. thaliana AT1G66240 AtAX1 Cu Shoots Shin et al. (2012)
A. thaliana AT1G68320 MYB62 P Roots, shoots Devaiah et al. (2009)
A. thaliana AT1G71200 AtCITF1 Cu Shoots, Anthers Yan et al. (2017)
A. thaliana AT1G74770 BTSL1 Fe, Mn, Zn Leaf Hindt et al. (2017)
A. thaliana AT1G76430 PHT1;9 P, As Roots, shoots Remy et al. (2012)
A. thaliana AT1G80760 NIP6;1 B Leaves,shoots Tanaka et al. (2008)
A. thaliana AT1G80830 AtNRAMP1 Mn Shoots, roots Cailliatte et al. (2010)
A. thaliana AT2G01770 VIT1 Fe Seed Kim et al. (2006)
A. thaliana AT2G01980 SOS1/NHX7 Na Shoots Shi et al. (2003)
A. thaliana AT2G13540 ABH1 S seeds McDowell et al. (2013)
A. thaliana AT2G16770 AtbZIP23 Zn Shoots, roots Assunção et al. (2010)
A. thaliana AT2G19110 AtHMA4 Zn Shoots, seeds Hussain et al. (2004); Olsen et al. (2016)
A. thaliana AT2G21045 AtHAC1 As Shoots Chao, et al. (2014)
A. thaliana AT2G23150 AtNRAMP3 Fe, Mn, Zn Shoots Lanquar et al. (2010)
A. thaliana AT2G23240 AtMT4b Cu, Zn Seeds Ren et al. (2012)
A. thaliana AT2G25680 MOT1 Mo Leaf Baxter, Muthukumar, et al., 2008; Baxter, Vitek, et al., 2008
A. thaliana AT2G28160 FRU Fe Shoots Yuan et al. (2008)
A. thaliana AT2G28670 ESB1 Ca, Mn, Zn, Na, S, K, As, Se, Mo Leaf Baxter et al. (2009)
A. thaliana AT2G32830 PHT1;5 P Roots Nagarajan et al. (2011)
A. thaliana AT2G33770 PHO2 P Roots, shoots Liu et al. (2012)
A. thaliana AT2G37430 ZAT11 Ni Shoots Liu et al. (2014)
A. thaliana AT2G38460 FPN1 Co Leaf Morrissey et al. (2009)
A. thaliana AT2G38940 PHT1;4 P Roots, shoots Shin et al. (2004)
A. thaliana AT2G39450 AtMTP11 Mn Shoots, roots Peiter et al. (2007)
A. thaliana AT2G42000 AtMT4a Cu, Zn Seeds Ren et al. (2012)
A. thaliana AT2G46430 CNGC3 K Leaf Gobert et al. (2006)
A. thaliana AT2G46800 AtMTP1 Zn Shoots Desbrosses‐Fonrouge et al. (2005)
A. thaliana AT2G47160 BOR1 B Shoots Miwa et al. (2006)
A. thaliana AT3G01310 VIH2 P Shoots Zhu et al. (2019)
A. thaliana AT3G06060 TSC10a Na, K, Rb, Mg, Ca, Fe, Mo Leaf Chao et al. (2011)
A. thaliana AT3G06100 NIP7 As NA Lindsay and Maathuis (2016; Isayenkov and Maathuis (2008)
A. thaliana AT3G08040 FRD3/MAN1 Mn Leaf Delhaize (1996)
A. thaliana AT3G12750 AtZIP1 Mn Roots Milner et al. (2013)
A. thaliana AT3G12820 myb10 Fe, Cd, Zn, Co, Mo Leaf Palmer et al. (2013)
A. thaliana AT3G13320 CAX2 Mn, Fe, K, P Seed Connorton et al. (2012)
A. thaliana AT3G13405 mir169a N Root Zhao et al. (2011)
A. thaliana AT3G14280 S seeds McDowell et al. (2013)
A. thaliana AT3G15380 AtCTL1 Na, Fe, Zn, Mn, Mo Shoots, Roots Gao et al. (2017)
A. thaliana AT3G18290 BTS Fe, Zn, Mn Leaf Hindt et al. (2017)
A. thaliana AT3G22890 AtATPS1 S Shoos Koprivova et al. (2013)
A. thaliana AT3G23210 bHLH34 Fe Root, shoot Li et al. (2016)
A. thaliana AT3G23430 PHO1 P Shoots Khan et al. (2014)
A. thaliana AT3G43790 ZIFL2 Cs Leaf Remy et al. (2015)
A. thaliana AT3G47640 PYE Fe, Zn, Mn, Co Root Long et al. (2010)
A. thaliana AT3G47950 AHA4 Na Root Vitart et al. (2001)
A. thaliana AT3G51860 CAX3 P, K Seed Connorton et al. (2012)
A. thaliana AT3G51895 SULTR3;1 S Leaf Cao et al. (2013)
A. thaliana AT3G56970 bHLH38 Fe Shoots Yuan et al. (2008)
A. thaliana AT3G56980 bHLH39 Fe Shoots Yuan et al. (2008)
A. thaliana AT3G58060 AtMTP8 Mn Shoots, seeds Eroglu et al. (2016, Eroglu et al. (2017)
A. thaliana AT3G58810 AtMTP3 Zn Shoots Arrivault et al. (2006)
A. thaliana AT3G58970 MGT6 Mg Roots, shoots Mao et al. (2014)
A. thaliana AT3G62270 BOR2 B Shoots Miwa et al. (2013)
A. thaliana AT4G02780 GA1 Fe Root Wild et al. (2016)
A. thaliana AT4G10310 AtHKT1;1 Na Leaf Baxter et al. (2010)
A. thaliana AT4G10380 NIP5;1 B Roots, shoots Takano et al. (2006)
A. thaliana AT4G13420 HAK5 Rb, Cs Roots Rubio et al. (2008; Qi et al. (2008)
A. thaliana AT4G14410 bHLH104 Fe Root, shoot Li et al. (2016)
A. thaliana AT4G16370 OPT3 Fe, Cd Leaf Zhai et al. (2014)
A. thaliana AT4G19690 IRT1 Fe, Mn, Co, Cd, Zn Root Eide et al. (1996)
A. thaliana AT4G23100 GSH1 Cd, As Shoots Guo et al. (2008)
A. thaliana AT4G24120 YSL1 Fe, Zn, Cu NA Waters et al. (2006)
A. thaliana AT4G28610 AtPHR1 P Shoots Nilsson et al. (2007)
A. thaliana AT4G30110 AtHMA2 Zn Shoots, seeds Hussain et al. (2004; Olsen et al. (2016)
A. thaliana AT4G30120 AtHMA3 Cd, Zn Leaf Chao et al. (2012; Pita‐Barbosa et al. (2019)
A. thaliana AT4G33000 CBL10 K Shoots Ren et al. (2013)
A. thaliana AT4G35040 AtbZIP19 Zn Shoots, roots Assunção et al. (2010)
A. thaliana AT4G37270 HMA1 Zn Shoots Kim et al. (2009)
A. thaliana AT5G02600 NaKR1 Na, K, Rb Leaf Tian et al. (2010)
A. thaliana AT5G03455 ACR2 As, P Roots, shoots Dhankher et al. (2006)
A. thaliana AT5G03570 FPN2 Co, Ni Leaf Morrissey et al. (2009); Schaaf et al. (2006)
A. thaliana AT5G09690 MGT7 Mg Shoots Kamiya et al. (2012)
A. thaliana AT5G13740 ZIF1 Zn, Fe Shoots Haydon et al. (2012)
A. thaliana AT5G15070 VIH1 P Shoots Zhu et al. (2019)
A. thaliana AT5G15410 CNGC2/DND1 Ca, Mg seeds McDowell et al. (2013)
A. thaliana AT5G17290 APG5 Fe, Mn, Zn Leaf, shoots, seeds Pottier et al. (2019)
A. thaliana AT5G18830 AtSPL7 Cu Shoots, roots Bernal et al. (2012)
A. thaliana AT5G20650 COPT5 Cu Shoots, roots, seeds Klaumann et al. (2011)
A. thaliana AT5G35410 SOS2 Na Seeds McDowell et al. (2013)
A. thaliana AT5G42130 AtMfl1 Fe Leaves, shoots Tarantino et al. (2011)
A. thaliana AT5G43350 PHT1;1 P, As Shoots Shin et al. (2004; Catarecha et al. (2007)
A. thaliana AT5G44070 PCS1 Zn, Cd, As Leaf Kühnlenz et al. (2016; Guo et al. (2008)
A. thaliana AT5G53130 CNGC1 Pb Leaf Sunkar et al. (2000)
A. thaliana AT5G53550 YSL3 Fe, Zn, Cu NA Waters et al. (2006)
A. thaliana AT5G54680 ILR3 Cd, Co, Fe, Mn, Zn Leaf Rampey et al. (2006)
A. thaliana AT5G54810 AtTSB1 Cd Roots,shoots Sanjaya et al. (2008)
A. thaliana AT5G57620 AtMYB36 Li, B, Na, Mg, K, Ca, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr, Mo, Cd Shoots Kamiya et al. (2015)
A. thaliana AT5G59030 COPT1 Cu Seed, Leaf Sancenón et al. (2004)
A. thaliana AT5G64930 CPR5 K Leaf Borghi et al. (2011)
A. thaliana AT5G67330 AtNRAMP3 Fe, Mn, Zn Shoots Lanquar et al. (2010)
M. truncatula Medtr1g010270 MtMOT1.2 Mo Nodules Gil‐Díez et al. (2018)
M. truncatula Medtr3g088460 MtNramp1 Fe Nodules Tejada‐Jiménez et al. (2015)
M. truncatula Medtr3g464210 MtMOT1.3 Mo Nodules Tejada‐Jiménez et al. (2017)
M. truncatula Medtr4g019870 MtCOPT1 Cu Nodules Senovilla et al. (2018)
M. truncatula Medtr4g064893 MtMTP2 Zn Nodules León‐Mediavilla et al. (2018)
M. truncatula Medtr4g083570 MtZIP6 Zn Nodules Abreu et al. (2017)
O. sativa LOC_Os01g03914 OsMTP9 Mn Shoots Ueno et al. (2015)
O. sativa LOC_Os01g20160 OsHKT1;5 Na Leaf, shoots Kobayashi et al. (2017)
O. sativa LOC_Os01g45990 AKT1 K NA Ahmad, et al. (2016)
O. sativa LOC_Os01g64250 OsHORZ1 Fe Shoots,seeds Kobayashi et al. (2013)
O. sativa LOC_Os01g64890 OsMGT1 Mg,Na Roots, shoots Chen, et al. (2017)
O. sativa LOC_Os02g06290 OsHAC4 As Seed Xu et al. (2017)
O. sativa LOC_Os02g10290 OsHMA4 Cu Roots, shoots, seeds Huang, et al. (2016)
O. sativa LOC_Os02g13870 OsNIP1;1 As Shoots Sun et al. (2018)
O. sativa LOC_Os02g43370 OsYSL2 Fe, Mn Seeds Ishimaru et al. (2010)
O. sativa LOC_Os02g43410 OsYSL15 Fe Roots, shoots, seeds Lee et al. (2009)
O. sativa LOC_Os02g51110 LSI1 Se Roots, shoots Zhao et al. (2010)
O. sativa LOC_Os02g53490 OsMTP8.2 Mn Shoots, roots Takemoto et al. (2017)
O. sativa LOC_Os02g56510 OsPHO1;2 P Shoots Secco et al. (2010)
O. sativa LOC_Os03g05640 OsPT2 Se Roots, shoots Zhang et al. (2014)
O. sativa LOC_Os03g09140 OsRab6a Fe, Zn Seeds, shoot, roots Yang and Zhang (2016)
O. sativa LOC_Os03g12530 OsMTP8.1 Mn Shoots, roots Chen et al. (2013)
O. sativa LOC_Os03g18550 OsMIT Fe Shoots Bashir et al. (2011)
O. sativa LOC_Os03g19420 OsNAS2 Fe Seeds Lee et al. (2012)
O. sativa LOC_Os03g21240 OsPHR2 P Shoots Zhou et al. (2008)
O. sativa LOC_Os04g32920 OsHAK1 Cs Shoots, seeds Rai et al. (2017)
O. sativa LOC_Os04g38940 OsVIT1 Fe,Zn Shoots, seeds Zhang et al. (2012)
O. sativa LOC_Os04g45860 OsYSL9 Fe Shoots, seeds Senoura et al. (2017)
O. sativa LOC_Os04g45900 OsYSL16 Cu Roots, shoots, seeds Zheng et al. (2012)
O. sativa LOC_Os04g46940 OsHMA5 Cu Roots,s hoots Deng et al. (2013)
O. sativa LOC_Os04g52310 OsZIP3 Zn Shoots Sasaki et al. (2015)
O. sativa LOC_Os04g52900 OsABCC1 As Seeds Song et al. (2014)
O. sativa LOC_Os04g56430 OsRMC Fe,Mn,Cu Root, shoot, seeds Yang et al. (2013)
O. sativa LOC_Os05g34290 OsPCS1* As Seeds Hayashi et al. (2017)
O. sativa LOC_Os05g39560 OsZIP5 Zn Leaf Lee et al. (2010)
O. sativa LOC_Os05g47780 OsHRZ2 Fe Shoots, seeds Kobayashi et al. (2013)
O. sativa LOC_Os05g48390 OsPHO2 P Leaf Wang et al. (2009)
O. sativa LOC_Os06g01260 OsPCS2* As, Cd Seeds Uraguchi et al. (2017)
O. sativa LOC_Os06g05160 SPDT P Seed Yamaji et al. (2017)
O. sativa LOC_Os06g48720 OsHMA2 Zn Shoots, roots Takahashi et al. (2012)
O. sativa LOC_Os06g48810 OsHKT2;1 Na Roots, shoots Horie et al. (2007)
O. sativa LOC_Os07g01810 TPKb K Leaf, root Ahmad et al. (2016)
O. sativa LOC_Os07g09000 OsPHF1 P Leaf, root Chen et al. (2011)
O. sativa LOC_Os07g12900 OsHMA3 Cd Shoots, seeds Tanaka et al. (2016)
O. sativa LOC_Os07g15370 NRAMP5 Fe,Mn,Cd Leaf Sasaki et al. (2012)
O. sativa LOC_Os08g01120 OsMOT1;1 Mo Shoots, Seed Huang et al. (2019)
O. sativa LOC_Os08g04390 OsPRI1 Fe Shoots, roots Zhang et al. (2017)
O. sativa LOC_Os08g05590 OsNIP3;2 As Roots Chen, Sun, et al. (2017a); Chen, Yamaji, et al. (2017b)
O. sativa LOC_Os08g05600 OsNIP3;3 As Shoots Sun et al. (2018)
O. sativa LOC_Os08g10480 OsATX1 Cu Shoots, roots, seeds Zhang, Cao, et al. (2018); Zhang, Chen, et al. (2018)
O. sativa LOC_Os09g23300 OsVIT2 Fe, Zn Shoots, seeds Zhang et al. (2012)
O. sativa LOC_Os12g03899 ZIFL12 Fe Shoots Che et al. (2019)
O. sativa LOC_Os12g18410 OsMIR Fe Shoots, Roots, seeds Ishimaru et al. (2009)
O. sativa LOC_Os12g32400 OsbHLH133 Fe Leaf, root, shoot Wang, Sun, et al. (2013a); Wang, Ying, et al. (2013b)
O. sativa LOC_Os12g37840 OsBOR1 B Shoots Nakagawa et al. (2007)
O. sativa Os01g0689300 OsHRZ1 Fe Shoots, seeds Kobayashi et al. (2013)
T. aestivum 2Al‐TRIAE_CS42_ 2AL_TGACv1_095050_AĂ410 TaIPK1 Fe, Zn Seed Aggarwal et al. (2018)
T. aestivum Traes_4AS_7220D33B3 Ta‐PHR1 P Shoots Wang, Sun, et al. (2013a); Wang, Ying, et al. (2013b)
T. aestivum Traes_4BL_7091749BF TaABCC13 Ca Seed Bhati et al. (2016)
T. aestivum Traes_4DL_3F8034BFD HKT2;1 Na Roots Laurie et al. (2002)
Z. mays GRMZM2G047616 ZmHKT1 Na Leaf Zhang, Cao, et al. (2018); Zhang, Chen, et al. (2018)
Z. mays GRMZM2G060952 YS1 Fe Root Von Wiren et al. (1994)
Z. mays GRMZM2G063306 YS3 Fe Leaf Chan‐Rodriguez and Walker (2018)
Z. mays GRMZM2G084779 ZmHAK5 K Roots, shoots Qin et al. (2019)
Z. mays GRMZM2G176209 TLS1 B Shoots, roots, anthers Durbak et al. (2014)
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FIGURE 1.

FIGURE 1

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Number of genes for each species that are primary, inferred from other primary genes in other species, or both

Most primary genes have orthologs in other species. Less than 10% of primary genes in A. thaliana, 12% in O. sativa, and one of the four primary genes in wheat (T. aestivum) lack orthologs (Table 2). G. max, P. trichocarpa, S. bicolor, S. italica, and S. viridis currently contain only inferred genes (Table 2, Figure 1).

TABLE 2.

Break down of primary/inferred genes in each species

Species Total genes Primary genes Primary/inferred genes Inferred genes Primary & primary/inferred genes without orthologs
A. thaliana 136 65.44% 16.18% 18.38% 9.91%
O. sativa 141 20.57% 14.89% 64.54% 12.00%
M. truncatula 176 1.70% 1.70% 96.59% 0.00%
T. aestivum 267 0.75% 0.75% 98.50% 25.00%
Z. mays 152 1.32% 1.97% 96.71% 0.00%
G. max 268 0.00% 0.00% 100.00% 0.00%
P. trichocarpa 197 0.00% 0.00% 100.00% 0.00%
S. bicolor 135 0.00% 0.00% 100.00% 0.00%
S. italica 146 0.00% 0.00% 100.00% 0.00%
S. viridis 146 0.00% 0.00% 100.00% 0.00%
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The YSL genes in A. thaliana and O. sativa are an example that provides evidence for the validity of the KIG list pipeline: AtYSL3, OsYSL9, and OsYSL16 were listed in their respective species as primary genes (Table 1) and after the ortholog search was annotated as primary/inferred genes, referencing each other (Table S1). AtYSL2 in A. thaliana, was not listed as primary gene, but was inferred through its rice orthologs OsYSL9 and OsYSL16. Additionally, AtYSL1 in A. thaliana is not a paralog of AtYSL3 or an ortholog of OsYSL9 and OsYSL16 according to PhytoMine's InParanoid results and is not listed as an ortholog to either of the O. sativa YSL genes in the KIG list. Other examples include AtVIT1 and OsVIT1/OsVIT2 (Kim et al., 2006; Zhang et al., 2012), and the vacuolar Mn transporters AtMTP8 and OsMTP8 (Eroglu et al., 2016; Chen et al., 2013). Thus, we can reliably generate inferred genes and create a species‐specific KIG list for any species in PhytoMine.

The primary list covers 23 elements (Figure 2) according to the reported elements from authors in the primary list, which is more elements than predicted by the GO term annotations for those genes. Some GO annotations for these genes mention only a portion of elements listed by the literature on the primary list. This may be due to GO annotation evidence codes lacking curation or biological data (IEA, ND, NAS) (Wimalanathan et al., 2018), or it may be due to alterations in one element leading to alterations in other elements (Baxter, Muthukumar, et al., 2008; Baxter, Vitek, et al., 2008).

FIGURE 2.

FIGURE 2

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Number of primary genes from each species listing each element

A. thaliana is the only species to have a primary gene listing for each element. There is a bias toward manganese, zinc, and iron which have two, three, and four times more associated genes than the average 13 ± 12 genes of other elements. Iron is the only element to contain genes from all five species in the primary list. In addition to biases toward certain elements, our primary list is also skewed toward an overrepresentation of ionome genes in above‐ground tissue studies (Figure 3). This is likely due to the difficulties in studying the elemental content of below‐ground tissues. All M. truncatula genes come from studies of the nodule in this model legume species.

FIGURE 3.

FIGURE 3

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Number of primary genes each type of tissue contributes to the known ionome gene list. Above ground is a summary of anther, leaf, seed, and shoot, while below ground is a summary of root and nodule

Querying the manually curated PANTHER GO‐slim biological process database (PANTHER v14.1, released March 12, 2019) and the GO complete biological process database (GO Ontology database, released October 08, 2019) with the A. thaliana KIG genes returned significantly (FDR < 0.05) overrepresented annotation terms related to the transport, response, and homeostasis of iron, zinc, copper and manganese ions. Additionally, the GO complete results had terms for cadmium, nickel, cobalt, sulfur, arsenic, lead, selenium, boron, magnesium, phosphorus, sodium, potassium, and calcium; covering most of the elements in the KIG list (Figure 4). Even though some genes were annotated as associated in the “other transport” of glycoside, glucose, oligopeptides, or phloem transport, the citations that have added them into our primary list show that their mutant alleles altered elemental accumulation. AtABCC1 is annotated as encoding a glycoside transporter protein, but Park et al. (2012) found overexpression of AtABCC1 increased cadmium concentrations in shoot tissue. The YSL genes and OPT3 are annotated as genes encoding oligopeptide transporters, but more specifically they are encoding predicted phloem‐localized metal‐nicotianamine complex and iron/cadmium transporters, respectively (Waters et al., 2006; Zhai et al., 2014). Last, NRT1.5/NPF7.3 is also annotated as encoding an oligopeptide transporter, but Li et al., (2017) identified it as a xylem loading potassium ion antiporter.

FIGURE 4.

FIGURE 4

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Known ionome genes relating to different terms from the GO complete biological process dataset. Ontology groups of GO Enrichment Analysis from PANTHER

The PANTHER GO‐slim molecular function annotation database found a significant overrepresentation for iron and potassium cation transmembrane transporter activity in the A. thaliana genes. The results using the GO complete molecular function database supported this and additionally included terms for arsenic, cadmium, zinc, boron, manganese, phosphate, sulfur, and magnesium ion transmembrane transporter activity. The GO complete molecular database also returned overrepresented terms for metal ion‐binding and cyclic nucleotide‐binding annotations. The cyclic nucleotide‐binding annotation genes were more specifically cyclic nucleotide ion gated channel genes (Gobert et al., 2006). The PANTHER GO‐slim cell component and GO complete cell component annotation database both returned significant overrepresentation for vacuoles and the plasma membrane, both known to be critical for elemental movement and storage (Barkla & Pantoja, 1996). The molecular function and cell component results are further evidence that our list is dominated by ion transporters.

To test the completeness of the KIG list, we searched PANTHER’s biological processes annotations for the number of A. thaliana genes encoding predicted elemental transporters. We found 618 A. thaliana genes predicted to encode elemental transport, and only 40 of these PANTHER genes are listed in the KIG list. We checked these results against ThaleMine (v1.10.4, updated on June 13, 2017) genes with the term “ion transport” in the gene name, description, or GO annotation and found only 358 genes, with 52 of these genes listed in the A. thaliana known ionome gene list. Interestingly, 219 of the genes from ThaleMine were not found in the 634 from PANTHER.

4. DISCUSSION

Here we have produced a curated list of genes known to alter the elemental composition of plant tissues. We envision several possible uses for this list:

  1. Researchers can use the list to identify candidate genes in loci from QTL and GWAS experiments.

  2. This list can serve as a gold standard for computational approaches.

  3. The list can serve as a reading list for those interested in learning about elemental accumulation.

It is important to highlight that the inferred genes lists are not likely to be perfect predictors of the causal genes. Our use of InParanoid orthologs may exclude homologs that are likely candidates. Additionally, the reasons that some genes have been studied could be the result of human bias toward research topics (Baxter, 2020). The list is highly enriched for (a) transporters, (b) genes that affect elemental accumulation in above‐ground tissues, and (c) genes that affect the accumulation of Fe and Zn. Transporter genes became obvious candidates for studying plant nutrition when disruption allele collections were produced (McDowell et al., 2013). Above‐ground tissues are easier to study without contamination from the soil, and such studies are, therefore, more prevalent. Finally, while Fe and Zn are important biochemical cofactors, these elements are likely enriched in the KIG list due to their considerable interest in the community where the ionomics approach was developed. This is further illustrated in the PANTHER GO‐slim databases, where Fe was the only element to have its overrepresented response, homeostasis, and transport‐related GO terms show up in the PANTHER GO‐slim biological process and molecular function databases, which are selected subsets of terms meant to broadly summarize data. Overrepresented terms related to other KIG list elements are only found in the GO complete databases. Taken together, these factors warn against forming conclusions about the nature of all elemental accumulation genes based on this limited dataset.

Most entries on this list are derived from model organisms, suggesting that most of our knowledge about genes that affect elemental accumulation comes from these species. A. thaliana and M. truncatula account for 64% of the primary genes list, which is probably a lower bound for the influence of knowledge generated in model organisms. Several of the genes in crop plants were found due to being orthologs of genes in the model organisms (Ahmad, et al., 2016; Xu et al., 2017), and on closer inspection of the 50 papers identifying primary genes in rice, 38 cited a gene in Arabidopsis (not necessarily the direct ortholog) as a source for why the gene was investigated. The higher quality of the GO terms in Arabidopsis, when compared to other species, is another reflection of this disparity of knowledge and a significant hindrance when trying to clone genes in other organisms.

4.1. Call for more submissions

While we have done our best to ensure that the current list is useful and thorough, it is possible we are still missing genes. We ask readers who know of genes that we are missing to contribute by submitting them here: https://docs.google.com/forms/d/e/1FAIpQLSdmS_zeOlxTOLmq2wB45BuSQml1LMKtKnWSatmFRGR2Q1o0Ew/viewform?c=0&w=1 or email corresponding author. KIG lists v1.0 for each of the species can be viewed in Table S1, and future updates to the list can be found at https://docs.google.com/spreadsheets/d/1XI2l1vtVJiHrlXLeOS5yTQQnLYq7BOHpmjuC‐kUejUU/edit?usp=sharing.

AUTHORS CONTRIBUTIONS

Contributed genes: IB, FKR, FM, SC, EW, PK. Analyzed data: LW, GZ. Wrote paper: LW, FKR, IB. Edited paper: FKR, FM, SC, EW, PK, GZ, LW, IB.

Supporting information

Table S1

Click here for additional data file. (722.2KB, xlsx)

ACKNOWLEDGMENTS

The authors thank the editors and reviewers for their consideration and comments.

Whitt L, Ricachenevsky FK, Ziegler G, et al. A curated list of genes that control elemental accumulation in plants. Plant Direct. 2020;4:1–15. 10.1002/pld3.272

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