Cowpea [Vigna unguiculata (L.) Walp.] is one of the most important food and forage legumes in the semi-arid tropics because of its ability to tolerate drought and grow on poor soils. It is cultivated mostly by poor farmers in developing countries, with 80% of production taking place in the dry savannah of tropical West and Central Africa. Cowpea is largely an underexploited crop with relatively little genomic information available for use in applied plant breeding. The goal of the Cowpea Genomics Initiative (CGI), funded by the Kirkhouse Trust, a UK-based charitable organization, is to leverage modern molecular genetic tools for gene discovery and cowpea improvement. One aspect of the initiative is the sequencing of the gene-rich region of the cowpea genome (termed the genespace) recovered using methylation filtration technology and providing annotation and analysis of the sequence data.
CGKB is an integrated and annotated resource for cowpea GSS with features of homology-based and HMM-based annotations, enzyme and pathway annotations, GO term annotation, toolkits, and a large number of other facilities to perform complex queries. The cowpea GSS, chloroplast sequences, mitochondrial sequences, retroelements, and SSR sequences are available as FASTA formatted files and downloadable at CGKB. This database and web interface are publicly accessible at .
Medicago truncatula has been chosen as a model species for genomic studies. It is closely related to an important legume, alfalfa. Transporters are a large group of membrane-spanning proteins. They deliver essential nutrients, eject waste products, and assist the cell in sensing environmental conditions by forming a complex system of pumps and channels. Although studies have effectively characterized individual M. truncatula transporters in several databases, until now there has been no available systematic database that includes all transporters in M. truncatula.
The M. truncatula transporter database (MTDB) contains comprehensive information on the transporters in M. truncatula. Based on the TransportTP method, we have presented a novel prediction pipeline. A total of 3,665 putative transporters have been annotated based on International Medicago Genome Annotated Group (IMGAG) V3.5 V3 and the M. truncatula Gene Index (MTGI) V10.0 releases and assigned to 162 families according to the transporter classification system. These families were further classified into seven types according to their transport mode and energy coupling mechanism. Extensive annotations referring to each protein were generated, including basic protein function, expressed sequence tag (EST) mapping, genome locus, three-dimensional template prediction, transmembrane segment, and domain annotation. A chromosome distribution map and text-based Basic Local Alignment Search Tools were also created. In addition, we have provided a way to explore the expression of putative M. truncatula transporter genes under stress treatments.
In summary, the MTDB enables the exploration and comparative analysis of putative transporters in M. truncatula. A user-friendly web interface and regular updates make MTDB valuable to researchers in related fields. The MTDB is freely available now to all users at http://bioinformatics.cau.edu.cn/MtTransporter/.
MicroRNAs (miRNA) are ∼21 nucleotide-long non-coding small RNAs, which function as post-transcriptional regulators in eukaryotes. miRNAs play essential roles in regulating plant growth and development. In recent years, research into the mechanism and consequences of miRNA action has made great progress. With whole genome sequence available in such plants as Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Glycine max, etc., it is desirable to develop a plant miRNA database through the integration of large amounts of information about publicly deposited miRNA data. The plant miRNA database (PMRD) integrates available plant miRNA data deposited in public databases, gleaned from the recent literature, and data generated in-house. This database contains sequence information, secondary structure, target genes, expression profiles and a genome browser. In total, there are 8433 miRNAs collected from 121 plant species in PMRD, including model plants and major crops such as Arabidopsis, rice, wheat, soybean, maize, sorghum, barley, etc. For Arabidopsis, rice, poplar, soybean, cotton, medicago and maize, we included the possible target genes for each miRNA with a predicted interaction site in the database. Furthermore, we provided miRNA expression profiles in the PMRD, including our local rice oxidative stress related microarray data (LC Sciences miRPlants_10.1) and the recently published microarray data for poplar, Arabidopsis, tomato, maize and rice. The PMRD database was constructed by open source technology utilizing a user-friendly web interface, and multiple search tools. The PMRD is freely available at http://bioinformatics.cau.edu.cn/PMRD. We expect PMRD to be a useful tool for scientists in the miRNA field in order to study the function of miRNAs and their target genes, especially in model plants and major crops.
Legumes play a vital role in maintaining the nitrogen cycle of the biosphere. They conduct symbiotic nitrogen fixation through endosymbiotic relationships with bacteria in root nodules. However, this and other characteristics of legumes, including mycorrhization, compound leaf development and profuse secondary metabolism, are absent in the typical model plant Arabidopsis thaliana. We present LegumeIP (http://plantgrn.noble.org/LegumeIP/), an integrative database for comparative genomics and transcriptomics of model legumes, for studying gene function and genome evolution in legumes. LegumeIP compiles gene and gene family information, syntenic and phylogenetic context and tissue-specific transcriptomic profiles. The database holds the genomic sequences of three model legumes, Medicago truncatula, Glycine max and Lotus japonicus plus two reference plant species, A. thaliana and Populus trichocarpa, with annotations based on UniProt, InterProScan, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases. LegumeIP also contains large-scale microarray and RNA-Seq-based gene expression data. Our new database is capable of systematic synteny analysis across M. truncatula, G. max, L. japonicas and A. thaliana, as well as construction and phylogenetic analysis of gene families across the five hosted species. Finally, LegumeIP provides comprehensive search and visualization tools that enable flexible queries based on gene annotation, gene family, synteny and relative gene expression.
PlantRNA database (http://plantrna.ibmp.cnrs.fr/) compiles transfer RNA (tRNA) gene sequences retrieved from fully annotated plant nuclear, plastidial and mitochondrial genomes. The set of annotated tRNA gene sequences has been manually curated for maximum quality and confidence. The novelty of this database resides in the inclusion of biological information relevant to the function of all the tRNAs entered in the library. This includes 5′- and 3′-flanking sequences, A and B box sequences, region of transcription initiation and poly(T) transcription termination stretches, tRNA intron sequences, aminoacyl-tRNA synthetases and enzymes responsible for tRNA maturation and modification. Finally, data on mitochondrial import of nuclear-encoded tRNAs as well as the bibliome for the respective tRNAs and tRNA-binding proteins are also included. The current annotation concerns complete genomes from 11 organisms: five flowering plants (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Medicago truncatula and Brachypodium distachyon), a moss (Physcomitrella patens), two green algae (Chlamydomonas reinhardtii and Ostreococcus tauri), one glaucophyte (Cyanophora paradoxa), one brown alga (Ectocarpus siliculosus) and a pennate diatom (Phaeodactylum tricornutum). The database will be regularly updated and implemented with new plant genome annotations so as to provide extensive information on tRNA biology to the research community.
Maize (Zea mays ssp. mays L.) is an important model for plant basic and applied research. In 2009, the B73 maize genome sequencing made a great step forward, using clone by clone strategy; however, functional annotation and gene classification of the maize genome are still limited. Thus, a well-annotated datasets and informative database will be important for further research discoveries. Signal transduction is a fundamental biological process in living cells, and many protein families participate in this process in sensing, amplifying and responding to various extracellular or internal stimuli. Therefore, it is a good starting point to integrate information on the maize functional genes involved in signal transduction.
Here we introduce a comprehensive database 'ProFITS' (Protein Families Involved in the Transduction of Signalling), which endeavours to identify and classify protein kinases/phosphatases, transcription factors and ubiquitin-proteasome-system related genes in the B73 maize genome. Users can explore gene models, corresponding transcripts and FLcDNAs using the three abovementioned protein hierarchical categories, and visualize them using an AJAX-based genome browser (JBrowse) or Generic Genome Browser (GBrowse). Functional annotations such as GO annotation, protein signatures, protein best-hits in the Arabidopsis and rice genome are provided. In addition, pre-calculated transcription factor binding sites of each gene are generated and mutant information is incorporated into ProFITS. In short, ProFITS provides a user-friendly web interface for studies in signal transduction process in maize.
ProFITS, which utilizes both the B73 maize genome and full length cDNA (FLcDNA) datasets, provides users a comprehensive platform of maize annotation with specific focus on the categorization of families involved in the signal transduction process. ProFITS is designed as a user-friendly web interface and it is valuable for experimental researchers. It is freely available now to all users at http://bioinfo.cau.edu.cn/ProFITS.
The PlantTribes database (http://fgp.huck.psu.edu/tribe.html) is a plant gene family database based on the inferred proteomes of five sequenced plant species: Arabidopsis thaliana, Carica papaya, Medicago truncatula, Oryza sativa and Populus trichocarpa. We used the graph-based clustering algorithm MCL [Van Dongen (Technical Report INS-R0010 2000) and Enright et al. (Nucleic Acids Res. 2002; 30: 1575–1584)] to classify all of these species’ protein-coding genes into putative gene families, called tribes, using three clustering stringencies (low, medium and high). For all tribes, we have generated protein and DNA alignments and maximum-likelihood phylogenetic trees. A parallel database of microarray experimental results is linked to the genes, which lets researchers identify groups of related genes and their expression patterns. Unified nomenclatures were developed, and tribes can be related to traditional gene families and conserved domain identifiers. SuperTribes, constructed through a second iteration of MCL clustering, connect distant, but potentially related gene clusters. The global classification of nearly 200 000 plant proteins was used as a scaffold for sorting ∼4 million additional cDNA sequences from over 200 plant species. All data and analyses are accessible through a flexible interface allowing users to explore the classification, to place query sequences within the classification, and to download results for further study.
The comparative transcriptional analysis of highly syntenic regions in six different organ types between Medicago truncatula (barrel medic) and Glycine max (soybean), using nucleotide tiling microarrays, provides insights into genome organization and transcriptional regulation in these legume plants.
Legumes are the third largest family of flowering plants and are unique among crop species in their ability to fix atmospheric nitrogen. As a result of recent genome sequencing efforts, legumes are now one of a few plant families with extensive genomic and transcriptomic data available in multiple species. The unprecedented complexity and impending completeness of these data create opportunities for new approaches to discovery.
We report here a transcriptional analysis in six different organ types of syntenic regions totaling approximately 1 Mb between the legume plants barrel medic (Medicago truncatula) and soybean (Glycine max) using oligonucleotide tiling microarrays. This analysis detected transcription of over 80% of the predicted genes in both species. We also identified 499 and 660 transcriptionally active regions from barrel medic and soybean, respectively, over half of which locate outside of the predicted exons. We used the tiling array data to detect differential gene expression in the six examined organ types and found several genes that are preferentially expressed in the nodule. Further investigation revealed that some collinear genes exhibit different expression patterns between the two species.
These results demonstrate the utility of genome tiling microarrays in generating transcriptomic data to complement computational annotation of the newly available legume genome sequences. The tiling microarray data was further used to quantify gene expression levels in multiple organ types of two related legume species. Further development of this method should provide a new approach to comparative genomics aimed at elucidating genome organization and transcriptional regulation.
The genus Populus includes poplars, aspens and cottonwoods, which will be collectively referred to as poplars hereafter unless otherwise specified. Poplars are the dominant tree species in many forest ecosystems in the Northern Hemisphere and are of substantial economic value in plantation forestry. Poplar has been established as a model system for genomics studies of growth, development, and adaptation of woody perennial plants including secondary xylem formation, dormancy, adaptation to local environments, and biotic interactions.
As part of the poplar genome sequencing project and the development of genomic resources for poplar, we have generated a full-length (FL)-cDNA collection using the biotinylated CAP trapper method. We constructed four FLcDNA libraries using RNA from xylem, phloem and cambium, and green shoot tips and leaves from the P. trichocarpa Nisqually-1 genotype, as well as insect-attacked leaves of the P. trichocarpa × P. deltoides hybrid. Following careful selection of candidate cDNA clones, we used a combined strategy of paired end reads and primer walking to generate a set of 4,664 high-accuracy, sequence-verified FLcDNAs, which clustered into 3,990 putative unique genes. Mapping FLcDNAs to the poplar genome sequence combined with BLAST comparisons to previously predicted protein coding sequences in the poplar genome identified 39 FLcDNAs that likely localize to gaps in the current genome sequence assembly. Another 173 FLcDNAs mapped to the genome sequence but were not included among the previously predicted genes in the poplar genome. Comparative sequence analysis against Arabidopsis thaliana and other species in the non-redundant database of GenBank revealed that 11.5% of the poplar FLcDNAs display no significant sequence similarity to other plant proteins. By mapping the poplar FLcDNAs against transcriptome data previously obtained with a 15.5 K cDNA microarray, we identified 153 FLcDNA clones for genes that were differentially expressed in poplar leaves attacked by forest tent caterpillars.
This study has generated a high-quality FLcDNA resource for poplar and the third largest FLcDNA collection published to date for any plant species. We successfully used the FLcDNA sequences to reassess gene prediction in the poplar genome sequence, perform comparative sequence annotation, and identify differentially expressed transcripts associated with defense against insects. The FLcDNA sequences will be essential to the ongoing curation and annotation of the poplar genome, in particular for targeting gaps in the current genome assembly and further improvement of gene predictions. The physical FLcDNA clones will serve as useful reagents for functional genomics research in areas such as analysis of gene functions in defense against insects and perennial growth. Sequences from this study have been deposited in NCBI GenBank under the accession numbers EF144175 to EF148838.
Comprehensive integration of large-scale omics resources such as genomes, transcriptomes and metabolomes will provide deeper insights into broader aspects of molecular biology. For better understanding of plant biology, we aim to construct a next-generation sequencing (NGS)-derived gene expression network (GEN) repository for a broad range of plant species. So far we have incorporated information about 745 high-quality mRNA sequencing (mRNA-Seq) samples from eight plant species (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, Sorghum bicolor, Vitis vinifera, Solanum tuberosum, Medicago truncatula and Glycine max) from the public short read archive, digitally profiled the entire set of gene expression profiles, and drawn GENs by using correspondence analysis (CA) to take advantage of gene expression similarities. In order to understand the evolutionary significance of the GENs from multiple species, they were linked according to the orthology of each node (gene) among species. In addition to other gene expression information, functional annotation of the genes will facilitate biological comprehension. Currently we are improving the given gene annotations with natural language processing (NLP) techniques and manual curation. Here we introduce the current status of our analyses and the web database, PODC (Plant Omics Data Center; http://bioinf.mind.meiji.ac.jp/podc/), now open to the public, providing GENs, functional annotations and additional comprehensive omics resources.
Correspondence analysis; Database; Gene expression network; Manual curation; Natural language processing (NLP); Omics
Diverse plant genome sequencing projects coupled with powerful bioinformatics tools have facilitated massive data analysis to construct specialized databases classified according to cellular function. However, there are still a considerable number of genes encoding proteins whose function has not yet been characterized. Included in this category are small proteins (SPs, 30–150 amino acids) encoded by short open reading frames (sORFs). SPs play important roles in plant physiology, growth, and development. Unfortunately, protocols focused on the genome-wide identification and characterization of sORFs are scarce or remain poorly implemented. As a result, these genes are underrepresented in many genome annotations. In this work, we exploited publicly available genome sequences of Phaseolus vulgaris, Medicago truncatula, Glycine max, and Lotus japonicus to analyze the abundance of annotated SPs in plant legumes. Our strategy to uncover bona fide sORFs at the genome level was centered in bioinformatics analysis of characteristics such as evidence of expression (transcription), presence of known protein regions or domains, and identification of orthologous genes in the genomes explored. We collected 6170, 10,461, 30,521, and 23,599 putative sORFs from P. vulgaris, G. max, M. truncatula, and L. japonicus genomes, respectively. Expressed sequence tags (ESTs) available in the DFCI Gene Index database provided evidence that ~one-third of the predicted legume sORFs are expressed. Most potential SPs have a counterpart in a different plant species and counterpart regions or domains in larger proteins. Potential functional sORFs were also classified according to a reduced set of GO categories, and the expression of 13 of them during P. vulgaris nodule ontogeny was confirmed by qPCR. This analysis provides a collection of sORFs that potentially encode for meaningful SPs, and offers the possibility of their further functional evaluation.
gene annotation; legume genomes; short open reading frames
Legumes (Leguminosae or Fabaceae) play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA) web server for this purpose.
The Medicago truncatula Gene Expression Atlas (MtGEA) web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible at: http://bioinfo.noble.org/gene-atlas/.
The MtGEA web server has a well managed rich data set, and offers data retrieval and analysis tools provided in the web platform. It's proven to be a powerful resource for plant biologists to effectively and efficiently identify Medicago transcripts of interest from a multitude of aspects, formulate hypothesis about gene function, and overall interpret the Medicago genome from a systematic point of view.
Transcription factors (TFs) are key regulatory proteins that enhance or repress the transcriptional rate of their target genes by binding to specific promoter regions (i.e. cis-acting elements) upon activation or de-activation of upstream signaling cascades. TFs thus constitute master control elements of dynamic transcriptional networks. TFs have fundamental roles in almost all biological processes (development, growth and response to environmental factors) and it is assumed that they play immensely important functions in the evolution of species. In plants, TFs have been employed to manipulate various types of metabolic, developmental and stress response pathways. Cross-species comparison and identification of regulatory modules and hence TFs is thought to become increasingly important for the rational design of new plant biomass. Up to now, however, no computational repository is available that provides access to the largely complete sets of transcription factors of sequenced plant genomes.
PlnTFDB is an integrative plant transcription factor database that provides a web interface to access large (close to complete) sets of transcription factors of several plant species, currently encompassing Arabidopsis thaliana (thale cress), Populus trichocarpa (poplar), Oryza sativa (rice), Chlamydomonas reinhardtii and Ostreococcus tauri. It also provides an access point to its daughter databases of a species-centered representation of transcription factors (OstreoTFDB, ChlamyTFDB, ArabTFDB, PoplarTFDB and RiceTFDB). Information including protein sequences, coding regions, genomic sequences, expressed sequence tags (ESTs), domain architecture and scientific literature is provided for each family.
We have created lists of putatively complete sets of transcription factors and other transcriptional regulators for five plant genomes. They are publicly available through . Further data will be included in the future when the sequences of other plant genomes become available.
In the contexts of genomics, post-genomics and systems biology approaches, data integration presents a major concern. Databases provide crucial solutions: they store, organize and allow information to be queried, they enhance the visibility of newly produced data by comparing them with previously published results, and facilitate the exploration and development of both existing hypotheses and new ideas.
The FLAGdb++ information system was developed with the aim of using whole plant genomes as physical references in order to gather and merge available genomic data from in silico or experimental approaches. Available through a JAVA application, original interfaces and tools assist the functional study of plant genes by considering them in their specific context: chromosome, gene family, orthology group, co-expression cluster and functional network. FLAGdb++ is mainly dedicated to the exploration of large gene groups in order to decipher functional connections, to highlight shared or specific structural or functional features, and to facilitate translational tasks between plant species (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Vitis vinifera).
Combining original data with the output of experts and graphical displays that differ from classical plant genome browsers, FLAGdb++ presents a powerful complementary tool for exploring plant genomes and exploiting structural and functional resources, without the need for computer programming knowledge. First launched in 2002, a 15th version of FLAGdb++ is now available and comprises four model plant genomes and over eight million genomic features.
The Rice Annotation Project Database (RAP-DB, http://rapdb.dna.affrc.go.jp/) has been providing a comprehensive set of gene annotations for the genome sequence of rice, Oryza sativa (japonica group) cv. Nipponbare. Since the first release in 2005, RAP-DB has been updated several times along with the genome assembly updates. Here, we present our newest RAP-DB based on the latest genome assembly, Os-Nipponbare-Reference-IRGSP-1.0 (IRGSP-1.0), which was released in 2011. We detected 37,869 loci by mapping transcript and protein sequences of 150 monocot species. To provide plant researchers with highly reliable and up to date rice gene annotations, we have been incorporating literature-based manually curated data, and 1,626 loci currently incorporate literature-based annotation data, including commonly used gene names or gene symbols. Transcriptional activities are shown at the nucleotide level by mapping RNA-Seq reads derived from 27 samples. We also mapped the Illumina reads of a Japanese leading japonica cultivar, Koshihikari, and a Chinese indica cultivar, Guangluai-4, to the genome and show alignments together with the single nucleotide polymorphisms (SNPs) and gene functional annotations through a newly developed browser, Short-Read Assembly Browser (S-RAB). We have developed two satellite databases, Plant Gene Family Database (PGFD) and Integrative Database of Cereal Gene Phylogeny (IDCGP), which display gene family and homologous gene relationships among diverse plant species. RAP-DB and the satellite databases offer simple and user-friendly web interfaces, enabling plant and genome researchers to access the data easily and facilitating a broad range of plant research topics.
Gene family; Gene phylogeny; Literature-based curation; Next-generation sequencing; Rice
The homeodomain leucine zipper (HD-Zip) transcription factor family is one of the largest plant specific superfamilies, and includes genes with roles in modulation of plant growth and response to environmental stresses. Many HD-Zip genes are characterized in Arabidopsis (Arabidopsis thaliana), and members of the family are being investigated for abiotic stress responses in rice (Oryza sativa), maize (Zea mays), poplar (Populus trichocarpa) and cucumber (Cucmis sativus). Findings in these species suggest HD-Zip genes as high priority candidates for crop improvement.
In this study we have identified members of the HD-Zip gene family in soybean cv. ‘Williams 82’, and characterized their expression under dehydration and salt stress. Homology searches with BLASTP and Hidden Markov Model guided sequence alignments identified 101 HD-Zip genes in the soybean genome. Phylogeny reconstruction coupled with domain and gene structure analyses using soybean, Arabidopsis, rice, grape (Vitis vinifera), and Medicago truncatula homologues enabled placement of these sequences into four previously described subfamilies. Of the 101 HD-Zip genes identified in soybean, 88 exist as whole-genome duplication-derived gene pairs, indicating high retention of these genes following polyploidy in Glycine ~13 Mya. The HD-Zip genes exhibit ubiquitous expression patterns across 24 conditions that include 17 tissues of soybean. An RNA-Seq experiment performed to study differential gene expression at 0, 1, 6 and 12 hr soybean roots under dehydration and salt stress identified 20 differentially expressed (DE) genes. Several of these DE genes are orthologs of genes previously reported to play a role under abiotic stress, implying conservation of HD-Zip gene functions across species. Screening of HD-Zip promoters identified transcription factor binding sites that are overrepresented in the DE genes under both dehydration and salt stress, providing further support for the role of HD-Zip genes in abiotic stress responses.
We provide a thorough description of soybean HD-Zip genes, and identify potential candidates with probable roles in dehydration and salt stress. Expression profiles generated for all soybean genes, under dehydration and salt stress, at four time points, will serve as an important resource for the soybean research community, and will aid in understanding plant responses to abiotic stress.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-950) contains supplementary material, which is available to authorized users.
Soybean; HD-Zip; Transcription factor; Gene family; Whole-genome duplication; RNA-Seq; Dehydration stress; Salt stress; Abiotic stress
SOMATIC EMBRYOGENESIS RECEPTOR-LIKE KINASE (SERK) genes are part of the regulation of diverse signalling events in plants. Current evidence shows SERK proteins function both in developmental and defence signalling pathways, which occur in response to both peptide and steroid ligands. SERKs are generally present as small gene families in plants, with five SERK genes in Arabidopsis. Knowledge gained primarily through work on Arabidopsis SERKs indicates that these proteins probably interact with a wide range of other receptor kinases and form a fundamental part of many essential signalling pathways. The SERK1 gene of the model legume, Medicago truncatula functions in somatic and zygotic embryogenesis, and during many phases of plant development, including nodule and lateral root formation. However, other SERK genes in M. truncatula and other legumes are largely unidentified and their functions unknown.
To aid the understanding of signalling pathways in M. truncatula, we have identified and annotated the SERK genes in this species. Using degenerate PCR and database mining, eight more SERK-like genes have been identified and these have been shown to be expressed. The amplification and sequencing of several different PCR products from one of these genes is consistent with the presence of splice variants. Four of the eight additional genes identified are upregulated in cultured leaf tissue grown on embryogenic medium. The sequence information obtained from M. truncatula was used to identify SERK family genes in the recently sequenced soybean (Glycine max) genome.
A total of nine SERK or SERK-like genes have been identified in M. truncatula and potentially 17 in soybean. Five M. truncatula SERK genes arose from duplication events not evident in soybean and Lotus. The presence of splice variants has not been previously reported in a SERK gene. Upregulation of four newly identified SERK genes (in addition to the previously described MtSERK1) in embryogenic tissue cultures suggests these genes also play a role in the process of somatic embryogenesis. The phylogenetic relationship of members of the SERK gene family to closely related genes, and to development and defence function is discussed.
Although the overwhelming majority of genes found in angiosperms are members of gene families, and both gene- and genome-duplication are pervasive forces in plant genomes, some genes are sufficiently distinct from all other genes in a genome that they can be operationally defined as 'single copy'. Using the gene clustering algorithm MCL-tribe, we have identified a set of 959 single copy genes that are shared single copy genes in the genomes of Arabidopsis thaliana, Populus trichocarpa, Vitis vinifera and Oryza sativa. To characterize these genes, we have performed a number of analyses examining GO annotations, coding sequence length, number of exons, number of domains, presence in distant lineages, such as Selaginella and Physcomitrella, and phylogenetic analysis to estimate copy number in other seed plants and to demonstrate their phylogenetic utility. We then provide examples of how these genes may be used in phylogenetic analyses to reconstruct organismal history, both by using extant coverage in EST databases for seed plants and de novo amplification via RT-PCR in the family Brassicaceae.
There are 959 single copy nuclear genes shared in Arabidopsis, Populus, Vitis and Oryza ["APVO SSC genes"]. The majority of these genes are also present in the Selaginella and Physcomitrella genomes. Public EST sets for 197 species suggest that most of these genes are present across a diverse collection of seed plants, and appear to exist as single or very low copy genes, though exceptions are seen in recently polyploid taxa and in lineages where there is significant evidence for a shared large-scale duplication event. Genes encoding proteins localized in organelles are more commonly single copy than expected by chance, but the evolutionary forces responsible for this bias are unknown.
Regardless of the evolutionary mechanisms responsible for the large number of shared single copy genes in diverse flowering plant lineages, these genes are valuable for phylogenetic and comparative analyses. Eighteen of the APVO SSC single copy genes were amplified in the Brassicaceae using RT-PCR and directly sequenced. Alignments of these sequences provide improved resolution of Brassicaceae phylogeny compared to recent studies using plastid and ITS sequences. An analysis of sequences from 13 APVO SSC genes from 69 species of seed plants, derived mainly from public EST databases, yielded a phylogeny that was largely congruent with prior hypotheses based on multiple plastid sequences. Whereas single gene phylogenies that rely on EST sequences have limited bootstrap support as the result of limited sequence information, concatenated alignments result in phylogenetic trees with strong bootstrap support for already established relationships. Overall, these single copy nuclear genes are promising markers for phylogenetics, and contain a greater proportion of phylogenetically-informative sites than commonly used protein-coding sequences from the plastid or mitochondrial genomes.
Putatively orthologous, shared single copy nuclear genes provide a vast source of new evidence for plant phylogenetics, genome mapping, and other applications, as well as a substantial class of genes for which functional characterization is needed. Preliminary evidence indicates that many of the shared single copy nuclear genes identified in this study may be well suited as markers for addressing phylogenetic hypotheses at a variety of taxonomic levels.
Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials.
According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level.
The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those associated with annual/perennial life history. Although we acknowledge current limitations of this kind of study, mainly due to a small sample size available and a distant taxonomic relationship of the model organisms, our results indicate that the genome-wide survey is a promising approach toward further understanding of the mechanism determining the molecular evolutionary rate at the genomic level.
Alternative polyadenylation (APA) plays an important role in the post-transcriptional regulation of gene expression. Little is known about how APA sites may evolve in homologous genes in different plant species. To this end, comparative studies of APA sites in different organisms are needed. In this study, a collection of poly(A) sites in Medicago truncatula, a model system for legume plants, has been generated and compared with APA sites in Arabidopsis thaliana.
The poly(A) tags from a deep-sequencing protocol were mapped to the annotated M. truncatula genome, and the identified poly(A) sites used to update the annotations of 14,203 genes. The results show that 64% of M. truncatula genes possess more than one poly(A) site, comparable to the percentages reported for Arabidopsis and rice. In addition, the poly(A) signals associated with M. truncatula genes were similar to those seen in Arabidopsis and other plants. The 3′-UTR lengths are correlated in pairs of orthologous genes between M. truncatula and Arabidopsis. Very little conservation of intronic poly(A) sites was found between Arabidopsis and M. truncatula, which suggests that such sites are likely to be species-specific in plants. In contrast, there is a greater conservation of CDS-localized poly(A) sites in these two species. A sizeable number of M. truncatula antisense poly(A) sites were found. A high percentage of the associated target genes possess Arabidopsis orthologs that are also associated with antisense sites. This is suggestive of important roles for antisense regulation of these target genes.
Our results reveal some distinct patterns of sense and antisense poly(A) sites in Arabidopsis and M. truncatula. In so doing, this study lends insight into general evolutionary trends of alternative polyadenylation in plants.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-615) contains supplementary material, which is available to authorized users.
Alternative polyadenylation; RNA processing; Antisense; Evolutionary conservation; Legume; Medicago truncatula
Regulation of gene expression at the level of transcription is a major control point in many biological processes. Transcription factors (TFs) can activate and/or repress the transcriptional rate of target genes and vascular plant genomes devote approximately 7% of their coding capacity to TFs. Global analysis of TFs has only been performed for three complete higher plant genomes – Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa) and rice (Oryza sativa). Presently, no large-scale analysis of TFs has been made from a member of the Solanaceae, one of the most important families of vascular plants. To fill this void, we have analysed tobacco (Nicotiana tabacum) TFs using a dataset of 1,159,022 gene-space sequence reads (GSRs) obtained by methylation filtering of the tobacco genome. An analytical pipeline was developed to isolate TF sequences from the GSR data set. This involved multiple (typically 10–15) independent searches with different versions of the TF family-defining domain(s) (normally the DNA-binding domain) followed by assembly into contigs and verification. Our analysis revealed that tobacco contains a minimum of 2,513 TFs representing all of the 64 well-characterised plant TF families. The number of TFs in tobacco is higher than previously reported for Arabidopsis and rice.
TOBFAC is an expandable knowledgebase of tobacco TFs with data currently available for over 2,513 TFs from 64 gene families. TOBFAC integrates available sequence information, phylogenetic analysis, and EST data with published reports on tobacco TF function. The database provides a major resource for the study of gene expression in tobacco and the Solanaceae and helps to fill a current gap in studies of TF families across the plant kingdom. TOBFAC is publicly accessible at .
MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs.
A novel classification model based on a support vector machine (SVM) was trained to identify real and pseudo plant pre-miRNAs together with their miRNAs. An initial set of 152 novel features related to sequential structures was used to train the model. By applying feature selection, we obtained the best subset of 47 features for use with the Back Support Vector Machine-Recursive Feature Elimination (B-SVM-RFE) method for the classification of plant pre-miRNAs. Using this method, 63 features were obtained for plant miRNA classification. We then developed an integrated classification model, miPlantPreMat, which comprises MiPlantPre and MiPlantMat, to identify plant pre-miRNAs and their miRNAs. This model achieved approximately 90% accuracy using plant datasets from nine plant species, including Arabidopsis thaliana, Glycine max, Oryza sativa, Physcomitrella patens, Medicago truncatula, Sorghum bicolor, Arabidopsis lyrata, Zea mays and Solanum lycopersicum. Using miPlantPreMat, 522 Solanum lycopersicum miRNAs were identified in the Solanum lycopersicum genome sequence.
We developed an integrated classification model, miPlantPreMat, based on structure-sequence features and SVM. MiPlantPreMat was used to identify both plant pre-miRNAs and the corresponding mature miRNAs. An improved feature selection method was proposed, resulting in high classification accuracy, sensitivity and specificity.
Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0423-x) contains supplementary material, which is available to authorized users.
MiRNA; Pre-miRNA; Prediction; SVM; Feature selection
Arabidopsis thaliana is an important model species for studies of plant gene functions. Research on Arabidopsis has resulted in the generation of high-quality genome sequences, annotations and related post-genomic studies. The amount of annotation, such as gene-coding regions and structures, is steadily growing in the field of plant research. In contrast to the genomics resource of animals and microorganisms, there are still some difficulties with characterization of some gene functions in plant genomics studies. The acquisition of information on protein structure can help elucidate the corresponding gene function because proteins encoded in the genome possess highly specific structures and functions. In this study, we calculated multiple physicochemical and secondary structural parameters of protein sequences, including length, hydrophobicity, the amount of secondary structure, the number of intrinsically disordered regions (IDRs) and the predicted presence of transmembrane helices and signal peptides, using a total of 208,333 protein sequences from the genomes of six representative plant species, Arabidopsis thaliana, Glycine max (soybean), Populus trichocarpa (poplar), Oryza sativa (rice), Physcomitrella patens (moss) and Cyanidioschyzon merolae (alga). Using the PASS tool and the Rosetta Stone method, we annotated the presence of novel functional regions in 1,732 protein sequences that included unannotated sequences from the Arabidopsis and rice proteomes. These results were organized into the Plant Protein Annotation Suite database (Plant-PrAS), which can be freely accessed online at http://plant-pras.riken.jp/.
Database; Gene function; Physicochemical property; Plant protein; Protein property
Cowpea, Vigna unguiculata (L.) Walp., is one of the most important food and forage legumes in the semi-arid tropics because of its drought tolerance and ability to grow on poor quality soils. Approximately 80% of cowpea production takes place in the dry savannahs of tropical West and Central Africa, mostly by poor subsistence farmers. Despite its economic and social importance in the developing world, cowpea remains to a large extent an underexploited crop. Among the major goals of cowpea breeding and improvement programs is the stacking of desirable agronomic traits, such as disease and pest resistance and response to abiotic stresses. Implementation of marker-assisted selection and breeding programs is severely limited by a paucity of trait-linked markers and a general lack of information on gene structure and organization. With a nuclear genome size estimated at ~620 Mb, the cowpea genome is an ideal target for reduced representation sequencing.
We report here the sequencing and analysis of the gene-rich, hypomethylated portion of the cowpea genome selectively cloned by methylation filtration (MF) technology. Over 250,000 gene-space sequence reads (GSRs) with an average length of 610 bp were generated, yielding ~160 Mb of sequence information. The GSRs were assembled, annotated by BLAST homology searches of four public protein annotation databases and four plant proteomes (A. thaliana, M. truncatula, O. sativa, and P. trichocarpa), and analyzed using various domain and gene modeling tools. A total of 41,260 GSR assemblies and singletons were annotated, of which 19,786 have unique GenBank accession numbers. Within the GSR dataset, 29% of the sequences were annotated using the Arabidopsis Gene Ontology (GO) with the largest categories of assigned function being catalytic activity and metabolic processes, groups that include the majority of cellular enzymes and components of amino acid, carbohydrate and lipid metabolism. A total of 5,888 GSRs had homology to genes encoding transcription factors (TFs) and transcription associated factors (TAFs) representing about 5% of the total annotated sequences in the dataset. Sixty-two (62) of the 64 well-characterized plant transcription factor (TF) gene families are represented in the cowpea GSRs, and these families are of similar size and phylogenetic organization to those characterized in other plants. The cowpea GSRs also provides a rich source of genes involved in photoperiodic control, symbiosis, and defense-related responses. Comparisons to available databases revealed that about 74% of cowpea ESTs and 70% of all legume ESTs were represented in the GSR dataset. As approximately 12% of all GSRs contain an identifiable simple-sequence repeat, the dataset is a powerful resource for the design of microsatellite markers.
The availability of extensive publicly available genomic data for cowpea, a non-model legume with significant importance in the developing world, represents a significant step forward in legume research. Not only does the gene space sequence enable the detailed analysis of gene structure, gene family organization and phylogenetic relationships within cowpea, but it also facilitates the characterization of syntenic relationships with other cultivated and model legumes, and will contribute to determining patterns of chromosomal evolution in the Leguminosae. The micro and macrosyntenic relationships detected between cowpea and other cultivated and model legumes should simplify the identification of informative markers for marker-assisted trait selection and map-based gene isolation necessary for cowpea improvement.
Sireviruses are an ancient genus of the Copia superfamily of LTR retrotransposons, and the only one that has exclusively proliferated within plant genomes. Based on experimental data and phylogenetic analyses, Sireviruses have successfully infiltrated many branches of the plant kingdom, extensively colonizing the genomes of grass species. Notably, it was recently shown that they have been a major force in the make-up and evolution of the maize genome, where they currently occupy ~21% of the nuclear content and ~90% of the Copia population. It is highly likely, therefore, that their life dynamics have been fundamental in the genome composition and organization of a plethora of plant hosts. To assist studies into their impact on plant genome evolution and also facilitate accurate identification and annotation of transposable elements in sequencing projects, we developed MASiVEdb (Mapping and Analysis of SireVirus Elements Database), a collective and systematic resource of Sireviruses in plants.
Taking advantage of the increasing availability of plant genomic sequences, and using an updated version of MASiVE, an algorithm specifically designed to identify Sireviruses based on their highly conserved genome structure, we populated MASiVEdb (http://bat.infspire.org/databases/masivedb/) with data on 16,243 intact Sireviruses (total length >158Mb) discovered in 11 fully-sequenced plant genomes. MASiVEdb is unlike any other transposable element database, providing a multitude of highly curated and detailed information on a specific genus across its hosts, such as complete set of coordinates, insertion age, and an analytical breakdown of the structure and gene complement of each element. All data are readily available through basic and advanced query interfaces, batch retrieval, and downloadable files. A purpose-built system is also offered for detecting and visualizing similarity between user sequences and Sireviruses, as well as for coding domain discovery and phylogenetic analysis.
MASiVEdb is currently the most comprehensive directory of Sireviruses, and as such complements other efforts in cataloguing plant transposable elements and elucidating their role in host genome evolution. Such insights will gradually deepen, as we plan to further improve MASiVEdb by phylogenetically mapping Sireviruses into families, by including data on fragments and solo LTRs, and by incorporating elements from newly-released genomes.