Genomic editing of intronic enhancers unveils their role in fine-tuning tissue-specific gene expression in Arabidopsis thaliana.

Enhancers located in introns are abundant and play a major role in the regulation of gene expression in mammalian species. By contrast, the functions of intronic enhancers in plants have largely been unexplored and only a handful of plant intronic enhancers have been reported. We performed a genome-wide prediction of intronic enhancers in Arabidopsis thaliana using open chromatin signatures based on DNase I sequencing. We identified 941 candidate intronic enhancers associated with 806 genes in seedling tissue and 1,271 intronic enhancers associated with 1,069 genes in floral tissue. We validated the function of 15 of 21 (71%) of the predicted intronic enhancers in transgenic assays using a reporter gene. We also created deletion lines of three intronic enhancers associated with two different genes using CRISPR/Cas. Deletion of these enhancers, which span key transcription factor binding sites, did not abolish gene expression but caused varying levels of transcriptional repression of their cognate genes. Remarkably, the transcriptional repression of the deletion lines occurred at specific developmental stages and resulted in distinct phenotypic effects on plant morphology and development. Clearly, these three intronic enhancers are important in fine-tuning tissue- and development-specific expression of their cognate genes.

GmPLP1 negatively regulates soybean resistance to high light stress by modulating photosynthetic capacity and reactive oxygen species accumulation in a blue light-dependent manner.

High light stress is an important factor limiting crop yield. Light receptors play an important role in the response to high light stress, but their mechanisms are still poorly understood. Here, we found that the abundance of GmPLP1, a positive blue light receptor protein, was significantly inhibited by high light stress and mainly responded to high blue light. GmPLP1 RNA-interference soybean lines exhibited higher light energy utilization ability and less light damage and reactive oxygen species (ROS) accumulation in leaves under high light stress, while the phenotype of GmPLP1:GmPLP1-Flag overexpression soybean showed the opposite characteristics. Then, we identified a protein-protein interaction between GmPLP1 and GmVTC2, and the intensity of this interaction was primarily affected by sensing the intensity of blue light. More importantly, overexpression of GmVTC2b improved soybean tolerance to high light stress by enhancing the ROS scavenging capability through increasing the biosynthesis of ascorbic acid. This regulation was significantly enhanced after interfering with a GmPLP1-interference fragment in GmVTC2b-ox soybean leaves, but was weakened when GmPLP1 was transiently overexpressed. These findings demonstrate that GmPLP1 regulates the photosynthetic capacity and ROS accumulation of soybean to adapt to changes in light intensity by sensing blue light. In summary, this study discovered a new mechanism through which GmPLP1 participates in high light stress in soybean, which has great significance for improving soybean yield and the adaptability of soybean to high light.

Genome-wide association analysis of resistance to frogeye leaf spot China race 7 in soybean based on high-throughput sequencing.

KEY MESSAGE: FLS is a disease that causes severe yield reduction in soybean. In this study, four genes (Glyma.16G176800, Glyma.16G177300, Glyma.16G177400 and Glyma.16G182300) were tentatively confirmed to play an important role in the resistance of soybean to FLS race 7. Frogeye leaf spot (FLS) causes severe yield loss in soybean and has been found in several countries worldwide. Therefore, it is necessary to select and utilize FLS-resistant varieties for the management of FLS. In the present study, 335 representative soybean materials were assessed for partial resistance to FLS race 7. Quantitative trait nucleotide (QTN) and FLS race 7 candidate genes were identified using genome-wide association analysis (GWAS) based on a site-specific amplified fragment sequencing (SLAF-seq) approach. A total of 23,156 single-nucleotide polymorphisms (SNPs) were used to evaluate the level of linkage disequilibrium with a minor allele frequency ≥ 5 and deletion data < 3%. These SNPs covered about 947.01 MBP, nearly 86.09% of the entire soybean genome. In addition, a compressed mixed linear model was utilized to identify association signals for partial resistance to FLS race 7. A total of 15 QTNs associated with resistance were found to be novel for FLS race 7 resistance. A total of 217 candidate genes located in the 200-kb genomic region of these peak SNPs were identified. Based on gene association analysis, qRT-PCR, haplotype analysis and virus-induced gene silencing (VIGS) systems were used to further verify candidate genes Glyma.16G176800, Glyma.16G177300, Glyma.16G177400 and Glyma.16G182300. This indicates that these four candidate genes may participate in FLS race 7 resistance responses.

Genetic dissection of soybean partial resistance to sclerotinia stem rot through genome wide association study and high throughout single nucleotide polymorphisms.

Sclerotinia stem rot (SSR) is a disease of soybean [Glycine max (L.) Merr] that causes severe yield losses. We studied 185 representative soybean accessions to evaluate partial SSR resistance and sequenced these by the specific-locus amplified fragment sequencing method. In total, 22,048 single-nucleotide polymorphisms (SNPs), with minor allele frequencies (MAF) ≥5% and missing data <3%, were developed and applied to genome-wide association study of SSR responsiveness and assess linkage disequilibrium (LD) level for candidate gene selection. We identified 18 association signals related to SSR partial resistance. Among them, six overlapped the regions of previous quantitative trait loci, and twelve were novel. We identified 243 candidate genes located in the 200 kb genomic region of these peak SNPs. Based on quantitative real-time polymerase chain reaction and haplotype analysis, Glyma.03G196000 and Glyma.20G095100, encoding pentatricopeptide repeat proteins, might be important factors in the resistance response of soybean to SSR.

GmLecRlk, a Lectin Receptor-like Protein Kinase, Contributes to Salt Stress Tolerance by Regulating Salt-Responsive Genes in Soybean.

Soybean [Glycine max (L.) Merr.] is an important oil crop that provides valuable resources for human consumption, animal feed, and biofuel. Through the transcriptome analysis in our previous study, GmLecRlk (Glyma.07G005700) was identified as a salt-responsive candidate gene in soybean. In this study, qRT-PCR analysis showed that the GmLecRlk gene expression level was significantly induced by salt stress and highly expressed in soybean roots. The pCAMBIA3300-GmLecRlk construct was generated and introduced into the soybean genome by Agrobacterium rhizogenes. Compared with the wild type (WT), GmLecRlk overexpressing (GmLecRlk-ox) soybean lines had significantly enhanced fresh weight, proline (Pro) content, and catalase (CAT) activity, and reduced malondialdehyde (MDA) and H2O2 content under salt stress. These results show that GmLecRlk gene enhanced ROS scavenging ability in response to salt stress in soybean. Meanwhile, we demonstrated that GmLecRlk gene also conferred soybean salt tolerance when it was overexpressed alone in soybean hairy root. Furthermore, the combination of RNA-seq and qRT-PCR analysis was used to determine that GmLecRlk improves the salt tolerance of soybean by upregulating GmERF3, GmbHLH30, and GmDREB2 and downregulating GmGH3.6, GmPUB8, and GmLAMP1. Our research reveals a new mechanism of salt resistance in soybean, which exposes a novel avenue for the cultivation of salt-resistant varieties.

A Nuclear Factor Y-B Transcription Factor, GmNFYB17, Regulates Resistance to Drought Stress in Soybean.

Soybean is sensitive to drought stress, and increasing tolerance to drought stresses is an important target for improving the performance of soybean in the field. The genetic mechanisms underlying soybean's drought tolerance remain largely unknown. Via a genome-wide association study (GWAS) combined with linkage analysis, we identified 11 single-nucleotide polymorphisms (SNPs) and 22 quantitative trait locus (QTLs) that are significantly associated with soybean drought tolerance. One of these loci, namely qGI10-1, was co-located by GWAS and linkage mapping. The two intervals of qGI10-1 were differentiated between wild and cultivated soybean. A nuclear factor Y transcription factor, GmNFYB17, was located in one of the differentiated regions of qGI10-1 and thus selected as a candidate gene for further analyses. The analysis of 29 homologous genes of GmNFYB17 in soybean showed that most of the genes from this family were involved in drought stress. The over-expression of GmNFYB17 in soybean enhanced drought resistance and yield accumulation. The transgenic plants grew better than control under limited water conditions and showed a lower degree of leaf damage and MDA content but higher RWC, SOD activity and proline content compared with control. Moreover, the transgenic plants showed a fast-growing root system, especially regarding a higher root-top ratio and more branching roots and lateral roots. The better agronomic traits of yield were also found in GmNFYB17 transgenic plants. Thus, the GmNFYB17 gene was proven to positively regulate drought stress resistance and modulate root growth in soybean. These results provide important insights into the molecular mechanisms underlying drought tolerance in soybean.

Identification of a candidate gene associated with isoflavone content in soybean seeds using genome-wide association and linkage mapping.

Isoflavone, a secondary metabolite produced by Glycine max (L.) Merr. (soybean), is valuable for human and plant health. The genetic architecture of soybean isoflavone content remains unclear, however, despite several mapping studies. We generated genomic data for 200 soybean cultivars and 150 recombinant inbred lines (RILs) to localize putative loci associated with soybean seed isoflavone content. Using a genome-wide association study (GWAS), we identified 87 single-nucleotide polymorphisms (SNPs) that were significantly associated with isoflavone concentration. Using linkage mapping, we identified 37 quantitative trait loci (QTLs) underlying the content of four isoflavones found in the RILs. A major locus on chromosome 8 (qISO8-1) was co-located by both the GWAS and linkage mapping. qISO8-1 was fine mapped to a 99.5-kb region, flanked by SSR_08_1651 and SSR_08_1656, in a BC2 F5 population. GmMPK1, encoding a mitogen-activated protein kinase, was identified as the causal gene in qISO8-1, and two natural GmMPK1 polymorphisms were significantly associated with isoflavone content. Overexpression of GmMPK1 in soybean hairy roots resulted in increased isoflavone concentrations. Overexpressing GmMPK1 in transgenic soybeans had greater resistance to Phytophthora root rot, suggesting that GmMPK1 might increase soybean resistance to biotic stress by influencing isoflavone content. Our results not only increase our understanding of the genetic architecture of soybean seed isoflavone content, but also provide a framework for the future marker-assisted breeding of high isoflavone content in soybean cultivars.

GmST1, which encodes a sulfotransferase, confers resistance to soybean mosaic virus strains G2 and G3.

Soybean mosaic virus (SMV) is one of the most widespread and devastating viral diseases worldwide. The genetic architecture of qualitative resistance to SMV in soybean remains unclear. Here, the Rsvg2 locus was identified as underlying soybean resistance to SMV by genome-wide association and linkage analyses. Fine mapping results showed that soybean resistance to SMV strains G2 and G3 was controlled by a single dominant gene, GmST1, on chromosome 13, encoding a sulfotransferase (SOT). A key variation at position 506 in the coding region of GmST1 associated with the structure of the encoded SOT and changed SOT activity levels between RSVG2-S and RSVG2-R alleles. In RSVG2-S allele carrier "Hefeng25", the overexpression of GmST1 carrying the RSVG2-R allele from the SMV-resistant line "Dongnong93-046" conferred resistance to SMV strains G2 and G3. Compared to Hefeng25, the accumulation of SMV was decreased in transgenic plants carrying the RSVG2-R allele. SMV infection differentiated both the accumulation of jasmonates and expression patterns of genes involved in jasmonic acid (JA) signalling, biosynthesis and catabolism in RSVG2-R and RSVG2-S allele carriers. This characterization of GmST1 suggests a new scenario explaining soybean resistance to SMV.

Identification of glutathione transferase gene associated with partial resistance to Sclerotinia stem rot of soybean using genome-wide association and linkage mapping.

KEY MESSAGE: Association and linkage mapping techniques were used to identify and verify single nucleotide polymorphisms (SNPs) associated with Sclerotinia sclerotiorum resistance. A novel resistant gene, GmGST , was cloned and shown to be involved in soybean resistance to SSR. Sclerotinia stem rot (SSR), caused by the fungus Sclerotinia sclerotiorum, is one of the most devastating diseases in soybean (Glycine max (Linn.) Merr.) However, the genetic architecture underlying soybean resistance to SSR is poorly understood, despite several mapping and gene mining studies. In the present study, the identification of quantitative trait loci (QTLs) involved in the resistance to S. sclerotiorum was conducted in two segregating populations: an association population that consisted of 261 diverse soybean germplasms, and the MH population, derived from a cross between a partially resistant cultivar (Maple arrow) and a susceptible cultivar (Hefeng25). Three and five genomic regions affecting resistance were detected by genome-wide association study to control the lesion length of stems (LLS) and the death rate of seedling (DRS), respectively. Four QTLs were detected to underlie LLS, and one QTL controlled DRS after SSR infection. A major locus on chromosome (Chr.) 13 (qDRS13-1), which affected both DRS and LLS, was detected in both the natural population and the MH population. GmGST, encoding a glutathione S-transferase, was cloned as a candidate gene in qDRS13-1. GmGST was upregulated by the induction of the partially resistant cultivar Maple arrow. Transgenic experiments showed that the overexpression of GmGST in soybean increased resistance to S. sclerotiorum and the content of soluble pigment in stems of soybean. The results increase our understanding of the genetic architecture of soybean resistance to SSR and provide a framework for the future marker-assisted breeding of resistant soybean cultivars.

Genome-wide association mapping for seed protein and oil contents using a large panel of soybean accessions.

Soybean is globally cultivated primarily for its protein and oil. The protein and oil contents of the seeds are quantitatively inherited traits determined by the interaction of numerous genes. In order to gain a better understanding of the molecular foundation of soybean protein and oil content for the marker-assisted selection (MAS) of high quality traits, a population of 185 soybean germplasms was evaluated to identify the quantitative trait loci (QTLs) associated with the seed protein and oil contents. Using specific length amplified fragment sequencing (SLAF-seq) technology, a total of 12,072 single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) ≥ 0.05 were detected across the 20 chromosomes (Chr), with a marker density of 78.7 kbp. A total of 31 SNPs located on 12 of the 20 soybean chromosomes were correlated with seed protein and oil content. Of the 31 SNPs that were associated with the two target traits, 31 beneficial alleles were identified. Two SNP markers, namely rs15774585 and rs15783346 on Chr 07, were determined to be related to seed oil content both in 2015 and 2016. Three SNP markers, rs53140888 on Chr 01, rs19485676 on Chr 13, and rs24787338 on Chr 20 were correlated with seed protein content both in 2015 and 2016. These beneficial alleles may potentially contribute towards the MAS of favorable soybean protein and oil characteristics.

Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill].

BACKGROUND: The hundred seed weight (HSW) is one of the yield components of soybean [Glycine max (L.) Merrill] and is especially critical for various soybean food types. In this study, a representative sample consisting of 185 accessions was selected from Northeast China and analysed in three tested environments to determine the quantitative trait nucleotide (QTN) of HSW through a genome-wide association study (GWAS). RESULT: A total of 24,180 single nucleotide polymorphisms (SNPs) with minor allele frequencies greater than 0.2 and missing data less than 3% were utilized to estimate linkage disequilibrium (LD) levels in the tested association panel. Thirty-four association signals were identified as associated with HSW via GWAS. Among them, nineteen QTNs were novel, and another fifteen QTNs were overlapped or located near the genomic regions of known HSW QTL. A total of 237 genes, derived from 31 QTNs and located near peak SNPs from the three tested environments in 2015 and 2016, were considered candidate genes, were related to plant growth regulation, hormone metabolism, cell, RNA, protein metabolism, development, starch accumulation, secondary metabolism, signalling, and the TCA cycle, some of which have been found to participate in the regulation of HSW. A total of 106 SNPs from 16 candidate genes were significantly associated with HSW in soybean. CONCLUSIONS: The identified loci with beneficial alleles and candidate genes might be valuable for the molecular network and MAS of HSW.

Genome-wide association and transcriptional studies reveal novel genes for unsaturated fatty acid synthesis in a panel of soybean accessions.

BACKGROUND: The nutritional value of soybean oil is largely influenced by the proportions of unsaturated fatty acids (FAs), including oleic acid (OA, 18:1), linoleic acid (LLA, 18:2), and linolenic acid (LNA, 18:3). Genome-wide association (GWAS) studies along with gene expression studies in soybean [Glycine max (L.) Merr.] were leveraged to dissect the genetics of unsaturated FAs. RESULTS: A association panel of 194 diverse soybean accessions were phenotyped in 2013, 2014 and 2015 to identify Single Nucleotide Polymorphisms (SNPs) associated with OA, LLA, and LNA content, and determine putative candidate genes responsible for regulating unsaturated FAs composition. 149 SNPs that represented 73 genomic regions were found to be associated with the unsaturated FA contents in soybean seeds according to the results of GWAS. Twelve novel genes were predicted to be involved in unsaturated FA synthesis in soybean. The relationship between expression pattern of the candidate genes and the accumulation of unsaturated FAs revealed that multiple genes might be involved in unsaturated FAs regulation simultaneously but work in very different ways: Glyma.07G046200 and Glyma.20G245500 promote the OA accumulation in soybean seed in all the tested accessions; Glyma.13G68600 and Glyma.16G200200 promote the OA accumulation only in high OA germplasms; Glyma.07G151300 promotes OA accumulation in higher OA germplasms and suppresses that in lower OA germplasms; Glyma.16G003500 has the effect of increasing LLA accumulation in higher LA germplasms; Glyma.07G254500 suppresses the accumulation of LNA in lower OA germplasms; Glyma.14G194300 might be involved in the accumulation of LNA content in lower LNA germplasms. CONCLUSIONS: The beneficial alleles and candidate genes identified might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying unsaturated fatty acid of soybean.

Identification of genetic loci and candidate genes related to soybean flowering through genome wide association study.

BACKGROUND: As a photoperiod-sensitive and self-pollinated species, the growth periods traits play important roles in the adaptability and yield of soybean. To examine the genetic architecture of soybean growth periods, we performed a genome-wide association study (GWAS) using a panel of 278 soybean accessions and 34,710 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) higher than 0.04 detected by the specific-locus amplified fragment sequencing (SLAF-seq) with a 6.14-fold average sequencing depth. GWAS was conducted by a compressed mixed linear model (CMLM) involving in both relative kinship and population structure. RESULTS: GWAS revealed that 37 significant SNP peaks associated with soybean flowering time or other growth periods related traits including full bloom, beginning pod, full pod, beginning seed, and full seed in two or more environments at -log10(P) > 3.75 or -log10(P) > 4.44 were distributed on 14 chromosomes, including chromosome 1, 2, 3, 5, 6, 9, 11, 12, 13, 14, 15, 17, 18, 19. Fourteen SNPs were novel loci and 23 SNPs were located within known QTLs or 75 kb near the known SNPs. Five candidate genes (Glyma.05G101800, Glyma.11G140100, Glyma.11G142900, Glyma.19G099700, Glyma.19G100900) in a 90 kb genomic region of each side of four significant SNPs (Gm5_27111367, Gm11_10629613, Gm11_10950924, Gm19_34768458) based on the average LD decay were homologs of Arabidopsis flowering time genes of AT5G48385.1, AT3G46510.1, AT5G59780.3, AT1G28050.1, and AT3G26790.1. These genes encoding FRI (FRIGIDA), PUB13 (plant U-box 13), MYB59, CONSTANS, and FUS3 proteins respectively might play important roles in controlling soybean growth periods. CONCLUSIONS: This study identified putative SNP markers associated with soybean growth period traits, which could be used for the marker-assisted selection of soybean growth period traits. Furthermore, the possible candidate genes involved in the control of soybean flowering time were predicted.

Genome-wide association study of inflorescence length of cultivated soybean based on the high-throughout single-nucleotide markers.

As an important and complex trait, inflorescence length (IL) of soybean [Glycine max (L.) Merr.] significantly affected seed yields. Therefore, elucidating molecular basis of inflorescence architecture, especially for IL, was important for improving soybean yield potentials. Longer IL meaned to have more pod and seed in soybean. Hence, increasing IL and improving yield are targets for soybean breeding. In this study, a association panel, comprising 283 diverse samples, was used to dissect the genetic basis of IL based on genome-wide association analysis (GWAS) and haplotype analysis. GWAS and haplotype analysis were conducted through high-throughout single-nucleotide polymorphisms (SNP) developed by SLAF-seq methodology. A total of 39, 057 SNPs (minor allele frequency ≥ 0.2 and missing data ≤ 10%) were utilized to evaluate linkage disequilibrium (LD) level in the tested association panel. A total of 30 association signals were identified to be associated with IL via GWAS. Among them, 13 SNPs were novel, and another 17 SNPs were overlapped or located near the linked regions of known quantitative trait nucleotide (QTN) with soybean seed yield or yield component. The functional genes, located in the 200-kb genomic region of each peak SNP, were considered as candidate genes, such as the cell division/ elongation, specific enzymes, and signaling or transport of specific proteins. These genes have been reported to participant in the regulation of IL. Ten typical long-IL lines and ten typical short-IL lines were re-sequencing, and then, six SNPs from five genes were obtained based on candidate gene-based association. In addition, 42 haplotypes were defined based on haplotype analysis. Of them, 11 haplotypes were found to regulate long IL (> 14 mm) in soybean. The identified 30 QTN with beneficial alleles and their candidate genes might be valuable for dissecting the molecular mechanisms of IL and further improving the yield potential of soybean.

Loci and candidate genes in soybean that confer resistance to Fusarium graminearum.

KEY MESSAGE: Association analysis techniques were used to identify and verify twelve single nucleotide polymorphisms (SNPs) associated with Fusarium graminearum resistance. Two novel candidate genes were obtained. Fusarium graminearum causes seed and root rot and seedling damping-off of soybean, leading to severe yield loss. Presently, the genetic basis of resistance to F. graminearum is elucidated in only four soybean accessions, which is not sufficient for resistance improvement. The objective of the present study was to identify the genome-wide genetic architecture of resistance to F. graminearum in landraces and cultivated soybeans based on a growth room evaluation. The resistance levels of 314 diverse accessions were tested, and 22,888 single nucleotide polymorphisms (SNPs) with a minor allele frequency of > 0.05 were developed using the specific-locus amplified fragment sequencing (SLAF-seq) approach. Twelve SNPs were identified as associated with F. graminearum resistance, and these SNPs were located at 12 genomic regions on eight chromosomes (Chr.) and could explain 5.53-14.71% of the observed phenotypic variation. One SNP, rs9479021, located on Chr.6, overlapped with qRfg_Gm06, the known QTL for resistance to F. graminearum. The other SNPs were novel and associated with resistance to F. graminearum. Nine novel candidate genes were predicted to contribute to resistance to F. graminearum according to the haplotype and transcript abundance analysis of the candidate genes. The identified markers and resistant cultivars are valuable for the improvement of resistance to F. graminearum.

Loci and candidate genes conferring resistance to soybean cyst nematode HG type 2.5.7.

BACKGROUND: Soybean (Glycine max L. Merr.) cyst nematode (SCN, Heterodera glycines I,) is a major pest of soybean worldwide. The most effective strategy to control this pest involves the use of resistant cultivars. The aim of the present study was to investigate the genome-wide genetic architecture of resistance to SCN HG Type 2.5.7 (race 1) in landrace and elite cultivated soybeans. RESULTS: A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. CONCLUSIONS: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.

Identification of quantitative trait loci underlying seed protein content of soybean including main, epistatic, and QTL × environment effects in different regions of Northeast China.

The objective here was to identify QTL underlying soybean protein content (PC), and to evaluate the additive and epistatic effects of the QTLs. A mapping population, consisting of 129 recombinant inbred lines (RILs), was created by crossing 'Dongnong 46' and 'L-100'. Phenotypic data of the parents and RILs were collected for 4 years in three locations of Heilongjiang Province of China. A total of 213 SSR markers were used to construct a genetic linkage map. Eight QTLs, located on seven chromosomes (Chr), were identified to be associated with PC among the 10 tested environments. Of the seven QTLs, five QTLs, qPR-2 (Satt710, on Chr9), qPR-3 (Sat_122, on Chr12), qPR-5 (Satt543, on Chr17), qPR-7 (Satt163, on Chr18), and qPR-8 (Satt614, on Chr20), were detected in six, seven, seven, six, and seven environments, respectively, implying relatively stable QTLs. qPR-3 could explain 3.33%-11.26% of the phenotypic variation across eight tested environments. qPR-5 and qPR-8 explained 3.64%-10.1% and 11.86%-18.40% of the phenotypic variation, respectively, across seven tested environments. Eight QTLs associated with PC exhibited additive and (or) additive × environment interaction effects. The results showed that environment-independent QTLs often had higher additive effects. Moreover, five epistatic pairwise QTLs were identified in the 10 environments.

Loci and candidate gene identification for resistance to Sclerotinia sclerotiorum in soybean (Glycine max L. Merr.) via association and linkage maps.

Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM-resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of 'Maple Arrow' (partial resistant to SWM) and 'Hefeng 25' (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole-genome encompassing approach and 25 179 single-nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome-wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.

Domestication footprints anchor genomic regions of agronomic importance in soybeans.

Present-day soybeans consist of elite cultivars and landraces (Glycine max, fully domesticated (FD)), annual wild type (Glycine soja, nondomesticated (ND)), and semi-wild type (semi-domesticated (SD)). FD soybean originated in China, although the details of its domestication history remain obscure. More than 500 diverse soybean accessions were sequenced using specific-locus amplified fragment sequencing (SLAF-seq) to address fundamental questions regarding soybean domestication. In total, 64,141 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) > 0.05 were found among the 512 tested accessions. The results indicated that the SD group is not a hybrid between the FD and ND groups. The initial domestication region was pinpointed to central China (demarcated by the Great Wall to the north and the Qinling Mountains to the south). A total of 800 highly differentiated genetic regions and > 140 selective sweeps were identified, and these were three- and twofold more likely, respectively, to encompass a known quantitative trait locus (QTL) than the rest of the soybean genome. Forty-three potential quantitative trait nucleotides (QTNs; including 15 distinct traits) were identified by genome-wide association mapping. The results of the present study should be beneficial for soybean improvement and provide insight into the genetic architecture of traits of agronomic importance.

Genetic characteristics of soybean resistance to HG type 0 and HG type 1.2.3.5.7 of the cyst nematode analyzed by genome-wide association mapping.

BACKGROUND: Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most fatal pests of soybean (Glycine max (L.) Merr.) worldwide and causes huge loss of soybean yield each year. Multiple sources of resistance are urgently needed for effective management of SCN via the development of resistant cultivars. The aim of the present study was to investigate the genetic architecture of resistance to SCN HG Type 0 (race 3) and HG Type 1.2.3.5.7 (race 4) in landraces and released elite soybean cultivars mostly from China. RESULTS: A total of 440 diverse soybean landraces and elite cultivars were screened for resistance to SCN HG Type 0 and HG Type 1.2.3.5.7. Exactly 131 new sources of SCN resistance were identified. Lines were genotyped by SNP markers detected by the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 36,976 SNPs were identified with minor allele frequencies (MAF) > 4% that were present in 97% of all the genotypes. Genome-wide association mapping showed that a total of 19 association signals were significantly related to the resistance for the two HG Types. Of the 19 association signals, eight signals overlapped with reported QTL including Rhg1 and Rhg4 genes. Another eight were located in the linked regions encompassing known QTL. Three QTL were found that were not previously reported. The average value of female index (FI) of soybean accessions with resistant alleles was significantly lower than those with susceptible alleles for each peak SNP. Disease resistance proteins with leucine rich regions, cytochrome P450s, protein kinases, zinc finger domain proteins, RING domain proteins, MYB and WRKY transcription activation families were identified. Such proteins may participate in the resistant reaction to SCN and were frequently found in the tightly linked genomic regions of the peak SNPs. CONCLUSIONS: GWAS extended understanding of the genetic architecture of SCN resistance in multiple genetic backgrounds. Nineteen association signals were obtained for the resistance to the two Hg Types of SCN. The multiple beneficial alleles from resistant germplasm sources will be useful for the breeding of cultivars with improved resistance to SCN. Analysis of genes near association signals may facilitate the recognition of the causal gene(s) underlying SCN resistances.