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Background Soybean [Glycine max (L.) Merrill] is one of the most important legumes cultivated worldwide, and Brazil is one of the main producers of this crop. Since the sequencing of its reference genome, interest in structural and allelic variations of cultivated and wild soybean germplasm has grown. To investigate the genetics of the Brazilian soybean germplasm, we selected soybean cultivars based on the year of commercialization, geographical region and maturity group and resequenced their genomes. Results We resequenced the genomes of 28 Brazilian soybean cultivars with an average genome coverage of 14.8X. A total of 5,835,185 single nucleotide polymorphisms (SNPs) and 1,329,844 InDels were identified across the 20 soybean chromosomes, with 541,762 SNPs, 98,922 InDels and 1,093 CNVs that were exclusive to the 28 Brazilian cultivars. In addition, 668 allelic variations of 327 genes were shared among all of the Brazilian cultivars, including genes related to DNA-dependent transcription-elongation, photosynthesis, ATP synthesis-coupled electron transport, cellular respiration, and precursors of metabolite generation and energy. A very homogeneous structure was also observed for the Brazilian soybean germplasm, and we observed 41 regions putatively influenced by positive selection. Finally, we detected 3,880 regions with copy-number variations (CNVs) that could help to explain the divergence among the accessions evaluated. Conclusions The large number of allelic and structural variations identified in this study can be used in marker-assisted selection programs to detect unique SNPs for cultivar fingerprinting. The results presented here suggest that despite the diversification of modern Brazilian cultivars, the soybean germplasm remains very narrow because of the large number of genome regions that exhibit low diversity. These results emphasize the need to introduce new alleles to increase the genetic diversity of the Brazilian germplasm. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2431-x) contains supplementary material, which is available to authorized users.

Background Soybean is a major crop that provides an important source of protein and oil to humans and animals, but its production can be dramatically decreased by the occurrence of drought stress. Soybeans can survive drought stress if there is a robust and deep root system at the early vegetative growth stage. However, little is known about the genome-wide molecular mechanisms contributing to soybean root system architecture. This study was performed to gain knowledge on transcriptome changes and related molecular mechanisms contributing to soybean root development under water limited conditions. Results The soybean Williams 82 genotype was subjected to very mild stress (VMS), mild stress (MS) and severe stress (SS) conditions, as well as recovery from the severe stress after re-watering (SR). In total, 6,609 genes in the roots showed differential expression patterns in response to different water-deficit stress levels. Genes involved in hormone (Auxin/Ethylene), carbohydrate, and cell wall-related metabolism (XTH/lipid/flavonoids/lignin) pathways were differentially regulated in the soybean root system. Several transcription factors (TFs) regulating root growth and responses under varying water-deficit conditions were identified and the expression patterns of six TFs were found to be common across the stress levels. Further analysis on the whole plant level led to the finding of tissue-specific or water-deficit levels specific regulation of transcription factors. Analysis of the over-represented motif of different gene groups revealed several new cis-elements associated with different levels of water deficit. The expression patterns of 18 genes were confirmed byquantitative reverse transcription polymerase chain reaction method and demonstrated the accuracy and effectiveness of RNA-Seq. Conclusions The primary root specific transcriptome in soybean can enable a better understanding of the root response to water deficit conditions. The genes detected in root tissues that were associated with key hormones, carbohydrates, and cell wall-related metabolism could play a vital role in achieving drought tolerance and could be promising candidates for future functional characterization. TFs involved in the soybean root and at the whole plant level could be used for future network analysis between TFs and cis-elements. All of these findings will be helpful in elucidating the molecular mechanisms associated with water stress responses in soybean roots. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2378-y) contains supplementary material, which is available to authorized users.

Background The plant phytohormone auxin controls many aspects of plant growth and development, which largely depends on its uneven distribution in plant tissues. Transmembrane proteins of the PIN family are auxin efflux facilitators. They play a key role in polar auxin transport and are associated with auxin asymmetrical distribution in plants. PIN genes have been characterized in several plant species, while comprehensive analysis of this gene family in soybean has not been reported yet. Results In this study, twenty-three members of the PIN gene family were identified in the soybean genome through homology searches. Analysis of chromosome distribution and phylogenetic relationships of the soybean PIN genes indicated nine pairs of duplicated genes and a legume specific subfamily. Organ/tissue expression patterns and promoter activity assays of the soybean PINs suggested redundant functions for most duplicated genes and complementary and tissue-specific functions during development for non-duplicated genes. The soybean PIN genes were differentially regulated by various abiotic stresses and phytohormone stimuli, implying crosstalk between auxin and abiotic stress signaling pathways. This was further supported by the altered auxin distribution under these conditions as revealed by DR5::GUS transgenic soybean hairy root. Our data indicates that GmPIN9, a legume-specific PIN gene, which was responsive to several abiotic stresses, might play a role in auxin re-distribution in soybean root under abiotic stress conditions. Conclusions This study provided the first comprehensive analysis of the soybean PIN gene family. Information on phylogenetic relationships, gene structure, protein profiles and expression profiles of the soybean PIN genes in different tissues and under various abiotic stress treatments helps to identity candidates with potential roles in specific developmental processes and/or environmental stress conditions. Our study advances our understanding of plant responses to abiotic stresses and serves as a basis for uncovering the biological role of PIN genes in soybean development and adaption to adverse environments. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2149-1) contains supplementary material, which is available to authorized users.

Background Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most devastating pathogen of soybean. Many gene expression profiling studies have been conducted to investigate the responses of soybean to the infection by this pathogen using primarily the first-generation soybean genome array that covered approximately 37,500 soybean transcripts. However, no study has been reported yet using the second-generation Affymetrix soybean whole-genome transcript array (Soybean WT array) that represents approximately 66,000 predicted soybean transcripts. Results In the present work, the gene expression profiles of two soybean plant introductions (PIs) PI 437654 and PI 567516C (both resistant to multiple SCN HG Types) and cultivar Magellan (susceptible to SCN) were compared in the presence or absence of the SCN inoculum at 3 and 8 days post-inoculation using the Soybean WT array. Data analysis revealed that the two resistant soybean lines showed distinctive gene expression profiles from each other and from Magellan not only in response to the SCN inoculation, but also in the absence of SCN. Overall, 1,413 genes and many pathways were revealed to be differentially regulated. Among them, 297 genes were constitutively regulated in the two resistant lines (compared with Magellan) and 1,146 genes were responsive to the SCN inoculation in the three lines, with 30 genes regulated both constitutively and by SCN. In addition to the findings similar to those in the published work, many genes involved in ethylene, protein degradation, and phenylpropanoid pathways were also revealed differentially regulated in the present study. GC-rich elements (e.g., GCATGC) were found over-represented in the promoter regions of certain groups of genes. These have not been observed before, and could be new defense-responsive regulatory elements. Conclusions Different soybean lines showed different gene expression profiles in the presence and absence of the SCN inoculum. Both inducible and constitutive gene expression may contribute to resistance to multiple SCN HG Types in the resistant soybean PI lines. Ethylene, protein degradation, and phenylpropanoid pathways, as well as many other pathways reported previously, may play important roles in mediating the soybean-SCN interactions. The revealed genes, pathways, and promoter elements can be further explored to regulate or engineer soybean for resistance to SCN. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1316-8) contains supplementary material, which is available to authorized users.

Background Root system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja. Results Wild and cultivated soybean both contributed alleles towards significant additive large effect QTLs on chromosome 6 and 7 for a longer total root length and root distribution, respectively. Epistatic effect QTLs were also identified for taproot length, average diameter, and root distribution. These root traits will influence the water and nutrient uptake in soybean. Two cell division-related genes (D type cyclin and auxin efflux carrier protein) with insertion/deletion variations might contribute to the shorter root phenotypes observed in G. soja compared with cultivated soybean. Based on the location of the QTLs and sequence information from a second G. soja accession, three genes (slow anion channel associated 1 like, Auxin responsive NEDD8-activating complex and peroxidase), each with a non-synonymous single nucleotide polymorphism mutation were identified, which may also contribute to changes in root architecture in the cultivated soybean. In addition, Apoptosis inhibitor 5-like on chromosome 7 and slow anion channel associated 1-like on chromosome 15 had epistatic interactions for taproot length QTLs in soybean. Conclusion Rare alleles from a G. soja accession are expected to enhance our understanding of the genetic components involved in root architecture traits, and could be combined to improve root system and drought adaptation in soybean. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1334-6) contains supplementary material, which is available to authorized users.

Background Bi-parental mapping populations have been commonly utilized to identify and characterize quantitative trait loci (QTL) controlling resistance to soybean cyst nematode (SCN, Heterodera glycines Ichinohe). Although this approach successfully mapped a large number of SCN resistance QTL, it captures only limited allelic diversity that exists in parental lines, and it also has limitations for genomic resolution. In this study, a genome-wide association study (GWAS) was performed using a diverse set of 553 soybean plant introductions (PIs) belonging to maturity groups from III to V to detect QTL/genes associated with SCN resistance to HG Type 0. Results Over 45,000 single nucleotide polymorphism (SNP) markers generated by the SoySNP50K iSelect BeadChip (http//www.soybase.org) were utilized for analysis. GWAS identified 14 loci distributed over different chromosomes comprising 60 SNPs significantly associated with SCN resistance. Results also confirmed six QTL that were previously mapped using bi-parental populations, including the rhg1 and Rhg4 loci. GWAS identified eight novel QTL, including QTL on chromosome 10, which we have previously mapped by using a bi-parental population. In addition to the known loci for four simple traits, such as seed coat color, flower color, pubescence color, and stem growth habit, two traits, like lodging and pod shattering, having moderately complex inheritance have been confirmed with great precision by GWAS. Conclusions The study showed that GWAS can be employed as an effective strategy for identifying complex traits in soybean and for narrowing GWAS-defined genomic regions, which facilitates positional cloning of the causal gene(s). Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1811-y) contains supplementary material, which is available to authorized users.

Background SWEET (MtN3_saliva) domain proteins, a recently identified group of efflux transporters, play an indispensable role in sugar efflux, phloem loading, plant-pathogen interaction and reproductive tissue development. The SWEET gene family is predominantly studied in Arabidopsis and members of the family are being investigated in rice. To date, no transcriptome or genomics analysis of soybean SWEET genes has been reported. Results In the present investigation, we explored the evolutionary aspect of the SWEET gene family in diverse plant species including primitive single cell algae to angiosperms with a major emphasis on Glycine max. Evolutionary features showed expansion and duplication of the SWEET gene family in land plants. Homology searches with BLAST tools and Hidden Markov Model-directed sequence alignments identified 52 SWEET genes that were mapped to 15 chromosomes in the soybean genome as tandem duplication events. Soybean SWEET (GmSWEET) genes showed a wide range of expression profiles in different tissues and developmental stages. Analysis of public transcriptome data and expression profiling using quantitative real time PCR (qRT-PCR) showed that a majority of the GmSWEET genes were confined to reproductive tissue development. Several natural genetic variants (non-synonymous SNPs, premature stop codons and haplotype) were identified in the GmSWEET genes using whole genome re-sequencing data analysis of 106 soybean genotypes. A significant association was observed between SNP-haplogroup and seed sucrose content in three gene clusters on chromosome 6. Conclusion Present investigation utilized comparative genomics, transcriptome profiling and whole genome re-sequencing approaches and provided a systematic description of soybean SWEET genes and identified putative candidates with probable roles in the reproductive tissue development. Gene expression profiling at different developmental stages and genomic variation data will aid as an important resource for the soybean research community and can be extremely valuable for understanding sink unloading and enhancing carbohydrate delivery to developing seeds for improving yield. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1730-y) contains supplementary material, which is available to authorized users.

Background Whole genome sequencing provides the most comprehensive collection of an organism’s genetic information. The availability of complete genome sequences is expected to dramatically deliver a high impact on biology. However, to achieve this impact in the area of crop improvement, significant efforts are still required on functional genomics, including the areas of gene annotation, cloning, expression profiling, and functional validation. Results Here we report our efforts in generating the first transcription factor (TF) open reading frame (ORF)eome resource associated with drought resistance in soybean (Glycine max), a major oil/protein crop grown worldwide. This study provides a highly annotated soybean TF-ORFeome associated with drought resistance. It contains information from experimentally verified protein-coding sequences (CDS), expression profiling under several abiotic stresses (drought, salinity, dehydration and ABA), and computationally predicted protein subcellular localization and cis-regulatory elements (CREs) analysis. All the information is available to plant researchers through a freely accessible and user-friendly database, Soybean Knowledge Base (SoyKB). Conclusions The soybean TF-ORFeome provides a valuable public resource for functional genomics studies, especially in the area of plant abiotic stresses. It will accelerate findings in the areas of abiotic stresses and lead to the generation of crops with enhanced resistance to multiple stresses. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1743-6) contains supplementary material, which is available to authorized users.

Background Glycine max is an economically important crop and many different varieties of soybean exist around the world. The first draft sequences and gene models of G. max (domesticated soybean) as well as G. soja (wild soybean), both became available in 2010. This opened the door for comprehensive comparative genomics studies between the two varieties. Results We have further analysed the sequences and identified the 425 genes that are unique to G. max and unavailable in G. soja. We further studied the genes with significant number of non-synonymous SNPs in their upstream regions. 12 genes involved in seed development, 3 in oil and 6 in protein concentration are unique to G. max. A significant number of unique genes are seen to overlap with the QTL regions of the three traits including seed, oil and protein. We have also developed a graphical chromosome visualizer as part of the Soybean Knowledge Base (SoyKB) tools for molecular breeding, which was used in the analysis and visualization of overlapping QTL regions for multiple traits with the deletions and SNPs in G. soja. Conclusions The comparisons between genome sequences of G. max and G. soja show significant differences between the genomic compositions of the two. The differences also highlight the phenotypic differences between the two in terms of seed development, oil and protein traits. These significant results have been integrated into the SoyKB resource and are publicly available for users to browse at http://soykb.org/GSoja.

Background Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for soybean translational genomics. SoyKB is designed to handle the management and integration of soybean genomics, transcriptomics, proteomics and metabolomics data along with annotation of gene function and biological pathway. It contains information on four entities, namely genes, microRNAs, metabolites and single nucleotide polymorphisms (SNPs). Methods SoyKB has many useful tools such as Affymetrix probe ID search, gene family search, multiple gene/metabolite search supporting co-expression analysis, and protein 3D structure viewer as well as download and upload capacity for experimental data and annotations. It has four tiers of registration, which control different levels of access to public and private data. It allows users of certain levels to share their expertise by adding comments to the data. It has a user-friendly web interface together with genome browser and pathway viewer, which display data in an intuitive manner to the soybean researchers, producers and consumers. Conclusions SoyKB addresses the increasing need of the soybean research community to have a one-stop-shop functional and translational omics web resource for information retrieval and analysis in a user-friendly way. SoyKB can be publicly accessed at http://soykb.org/.

Background With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific mapping populations is essential for fine-mapping and map-based cloning of economically important genes. Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation existing between any diverse genotypes that are usually used for QTL mapping studies. The massively parallel sequencing technologies (Roche GS/454, Illumina GA/Solexa, and ABI/SOLiD), have been widely applied to identify genome-wide sequence variations. However, it is still remains unclear whether sequence data at a low sequencing depth are enough to detect the variations existing in any QTL regions of interest in a crop genome, and how to prepare sequencing samples for a complex genome such as soybean. Therefore, with the aims of identifying SNP markers in a cost effective way for fine-mapping several QTL regions, and testing the validation rate of the putative SNPs predicted with Solexa short sequence reads at a low sequencing depth, we evaluated a pooled DNA fragment reduced representation library and SNP detection methods applied to short read sequences generated by Solexa high-throughput sequencing technology. Results A total of 39,022 putative SNPs were identified by the Illumina/Solexa sequencing system using a reduced representation DNA library of two parental lines of a mapping population. The validation rates of these putative SNPs predicted with low and high stringency were 72% and 85%, respectively. One hundred sixty four SNP markers resulted from the validation of putative SNPs and have been selectively chosen to target a known QTL, thereby increasing the marker density of the targeted region to one marker per 42 K bp. Conclusions We have demonstrated how to quickly identify large numbers of SNPs for fine mapping of QTL regions by applying massively parallel sequencing combined with genome complexity reduction techniques. This SNP discovery approach is more efficient for targeting multiple QTL regions in a same genetic population, which can be applied to other crops.

Background Integrated genetic and physical maps are extremely valuable for genomic studies and as important references for assembling whole genome shotgun sequences. Screening of a BAC library using molecular markers is an indispensable procedure for integration of both physical and genetic maps of a genome. Molecular markers provide anchor points for integration of genetic and physical maps and also validate BAC contigs assembled based solely on BAC fingerprints. We employed a six-dimensional BAC pooling strategy and an in silico approach to anchor molecular markers onto the soybean physical map. Results A total of 1,470 markers (580 SSRs and 890 STSs) were anchored by PCR on a subset of a Williams 82 Bst Y I BAC library pooled into 208 pools in six dimensions. This resulted in 7,463 clones (~1× genome equivalent) associated with 1470 markers, of which the majority of clones (6,157, 82.5%) were anchored by one marker and 1106 (17.5%) individual clones contained two or more markers. This contributed to 1184 contigs having anchor points through this 6-D pool screening effort. In parallel, the 21,700 soybean Unigene set from NCBI was used to perform in silico mapping on 80,700 Williams 82 BAC end sequences (BES). This in silico analysis yielded 9,835 positive results anchored by 4152 unigenes that contributed to 1305 contigs and 1624 singletons. Among the 1305 contigs, 305 have not been previously anchored by PCR. Therefore, 1489 (78.8%) of 1893 contigs are anchored with molecular markers. These results are being integrated with BAC fingerprints to assemble the BAC contigs. Ultimately, these efforts will lead to an integrated physical and genetic map resource. Conclusion We demonstrated that the six-dimensional soybean BAC pools can be efficiently used to anchor markers to soybean BACs despite the complexity of the soybean genome. In addition to anchoring markers, the 6-D pooling method was also effective for targeting BAC clones for investigating gene families and duplicated regions in the genome, as well as for extending physical map contigs.