In silico analysis of transcription factor repertoire and prediction of stress responsive transcription factors in soybean

Functional genomics of soybean for improvement of productivity in adverse conditions

Global soybean production is frequently impacted by various stresses, including both abiotic and biotic stresses. To develop soybean plants with enhanced tolerance to different stressors, functional genomics of soybean and a comprehensive understanding of available biotechnological resources and approaches are essential. In this review, we will discuss recent advances in soybean functional genomics which provide unprecedented opportunities to understand global patterns of gene expression, gene regulatory networks, various physiological, biochemical, and metabolic pathways as well as their association with the development of specific phenotypes. Soybean functional genomics, therefore, will ultimately enable us to develop new soybean varieties with improved productivity under adverse conditions by genetic engineering.

Genome-wide analysis of two-component systems and prediction of stress-responsive two-component system members in soybean

In plants, the two-component systems (TCSs) play important roles in regulating diverse biological processes, including responses to environmental stress stimuli. Within the soybean genome, the TCSs consist of at least 21 histidine kinases, 13 authentic and pseudo-phosphotransfers and 18 type-A, 15 type-B, 3 type-C and 11 pseudo-response regulator proteins. Structural and phylogenetic analyses of soybean TCS members with their Arabidopsis and rice counterparts revealed similar architecture of their TCSs. We identified a large number of closely homologous soybean TCS genes, which likely resulted from genome duplication. Additionally, we analysed tissue-specific expression profiles of those TCS genes, whose data are available from public resources. To predict the putative regulatory functions of soybean TCS members, with special emphasis on stress-responsive functions, we performed comparative analyses from all the TCS members of soybean, Arabidopsis and rice and coupled these data with annotations of known abiotic stress-responsive cis-elements in the promoter region of each soybean TCS gene. Our study provides insights into the architecture and a solid foundation for further functional characterization of soybean TCS elements. In addition, we provide a new resource for studying the conservation and divergence among the TCSs within plant species and/or between plants and other organisms.

Genomics and bioinformatics resources for crop improvement

Recent remarkable innovations in platforms for omics-based research and application development provide crucial resources to promote research in model and applied plant species. A combinatorial approach using multiple omics platforms and integration of their outcomes is now an effective strategy for clarifying molecular systems integral to improving plant productivity. Furthermore, promotion of comparative genomics among model and applied plants allows us to grasp the biological properties of each species and to accelerate gene discovery and functional analyses of genes. Bioinformatics platforms and their associated databases are also essential for the effective design of approaches making the best use of genomic resources, including resource integration. We review recent advances in research platforms and resources in plant omics together with related databases and advances in technology.

Identification and prediction of abiotic stress responsive transcription factors involved in abiotic stress signaling in soybean

Abiotic stresses such as extreme temperature, drought, high salinity, cold and waterlogging often result in significant losses to the yields of economically important crops such as soybean (Glycine max L.). Transcription factors (TFs) which bind to DNA through specific cis-regulatory sequences either activate or repress gene transcription have been reported to act as control switches in stress signaling. Recent completion of the soybean genomic sequence has open wide opportunities for large-scale identification and annotations of regulatory TFs in soybean for functional studies. Within the soybean genome, we identified 5,035 TF models which grouped into 61 families. Detailed annotations of soybean TF genes can be accessed at SoybeanTFDB (soybeantfdb.psc.riken.jp). Moreover, we have reported a new idea of high throughput prediction and selection of abiotic stress responsive TFs based on the existence of known stress responsive cis-element(s) located in the promoter regions of respective TFs and GO annotations. We, therefore, have provided a basic platform for the genome-wide analysis of regulatory mechanisms underlying abiotic stress responses and a reliable tool for prediction and selection of stress responsive TFs for further functional studies and genetic engineering.

LegumeTFDB: an integrative database of Glycine max, Lotus japonicus and Medicago truncatula transcription factors

We have established a database named LegumeTFDB to provide access to transcription factor (TF) repertoires of three major legume species: soybean (Glycine max), Lotus japonicus and Medicago truncatula. LegumeTFDB integrates unique information for each TF gene and family, including sequence features, gene promoters, domain alignments, gene ontology (GO) assignment and sequence comparison data derived from comparative analysis with TFs found within legumes, in Arabidopsis, rice and poplar as well as with proteins in NCBI nr and UniProt. We also analyzed the promoter regions for all of the TFs to identify all types of cis-motifs provided by the PLACE database. Additionally, we supply hyperlinks to make available expression data of 2411 soybean TF genes. LegumeTFDB provides an important user-friendly public resource for comparative genomics and understanding of transcriptional regulation in agriculturally important legumes.

AVAILABILITY

http://legumetfdb.psc.riken.jp/.

SUPPLEMENTARY INFORMATION

Supplementary data available at Bioinformatics online.