Identification of quantitative trait loci for lodging and related agronomic traits in soybean (Glycine max [L.] Merr.).

BACKGROUND: Lodging, a crucial agronomic trait linked to soybean yield, poses a significant challenge in soybean production. Nevertheless, there has been less research on soybean lodging compared to other important agronomic traits, hindering progress in breeding high-yield soybeans. Our goals were to investigate lodging, pinpoint quantitative trait loci (QTL) linked to lodging, and forecast potential candidate genes linked to this trait. To achieve this, we employed a recombinant inbred line (RIL) population derived from a cross between Guizao 1 and B13 (GB) across various environments. RESULTS: The lodging score of the RIL population was found to be significantly positively correlated with flowering time, maturity time, plant height, number of main stem nodes, stem diameter, and internode length, with correlation coefficients ranging from 0.457 to 0.783. A total of 84 QTLs associated with soybean lodging and related traits were identified using the GB population. The contribution of phenotypic variance ranged from 1.26 to 66.87%, with LOD scores ranging from 2.52 to 69.22. Additionally, within these QTLs, a stable major QTL associated with lodging was newly discovered in the GB population. Out of the ten major QTLs associated with other related traits, nine of them were situated within the qLD-4-1 interval of the major lodging score locus, displaying phenotypic variations ranging from 12.10 to 66.87%. Specific alterations in gene expression were revealed through the analysis of resequencing data from the two parental lines, potentially indicating their significant roles in lodging. Subsequently, it was determined through qRT-PCR that four genes are likely to be the major genes controlling soybean lodging. CONCLUSIONS: This study's findings offer valuable insights into the genetic underpinnings of soybean lodging resistance traits. By comprehending the potential genetic factors associated with lodging, this research lays the groundwork for breeding high-yield soybeans with improved lodging resistance.

Dual domestications and origin of traits in grapevine evolution.

We elucidate grapevine evolution and domestication histories with 3525 cultivated and wild accessions worldwide. In the Pleistocene, harsh climate drove the separation of wild grape ecotypes caused by continuous habitat fragmentation. Then, domestication occurred concurrently about 11,000 years ago in Western Asia and the Caucasus to yield table and wine grapevines. The Western Asia domesticates dispersed into Europe with early farmers, introgressed with ancient wild western ecotypes, and subsequently diversified along human migration trails into muscat and unique western wine grape ancestries by the late Neolithic. Analyses of domestication traits also reveal new insights into selection for berry palatability, hermaphroditism, muscat flavor, and berry skin color. These data demonstrate the role of the grapevines in the early inception of agriculture across Eurasia.

Identification of quantitative trait loci (QTLs) and candidate genes of seed Iron and zinc content in soybean [Glycine max (L.) Merr.].

BACKGROUND: Deciphering the hereditary mechanism of seed iron (Fe) and zinc (Zn) content in soybean is important and sustainable to address the "hidden hunger" that presently affects approximately 2 billion people worldwide. Therefore, in order to detect genomic regions related to soybean seed Fe and Zn content, a recombinant inbred line (RIL) population with 248 lines was assessed in four environments to detect Quantitative Trait Loci (QTLs) related to soybean seed Fe and Zn content. RESULT: Wide variation was found in seed Fe and Zn content in four environments, and genotype, environment, and genotype × environment interactions had significant influences on both the seed Fe and Zn content. A positive correlation was observed between seed Fe content and seed Zn content, and broad-sense heritability (H2) of seed Fe and Zn content were 0.73 and 0.75, respectively. In this study, five QTLs for seed Fe content were detected with 4.57 - 32.71% of phenotypic variation explained (PVE) and logarithm of odds (LOD) scores ranging from 3.60 to 33.79. Five QTLs controlling the seed Zn content were detected, and they individually explained 3.35 to 26.48% of the phenotypic variation, with LOD scores ranging from 3.64 to 20.4. Meanwhile, 409,541 high-quality single-nucleotide variants (SNVs) and 85,102 InDels (except intergenic regions) between two bi-parental lines were identified by whole genome resequencing. A total of 12 candidate genes were reported in one major QTL for seed Fe content and two major QTLs for seed Zn content, with the help of RNA-Seq analysis, gene ontology (GO) enrichment, gene annotation, and bi-parental whole genome sequencing (WGS) data. CONCLUSIONS: Limited studies were performed about microelement of soybean, so these results may play an important role in the biofortification of Fe and Zn and accelerate the development of marker-assisted selection (MAS) for breeding soybeans fortified with iron and zinc.

Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments.

Introduction: The seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear. Methods: To understand the molecular genetic basis for the formation of soybean yield traits, the present study focused on QTLs mapping for seed size and weight traits in different environments and target genes mining. Results: A total of 85 QTLs associated with seed size and weight traits were identified using a recombinant inbred line (RIL) population developed from Guizao1×B13 (GB13). We also detected 18 environmentally stable QTLs. Of these, qSL-3-1 was a novel QTL with a stable main effect associated with seed length. It was detected in all environments, three of which explained more than 10% of phenotypic variance (PV), with a maximum of 15.91%. In addition, qSW-20-3 was a novel QTL with a stable main effect associated with seed width, which was identified in four environments. And the amount of phenotypic variance explained (PVE) varied from 9.22 to 21.93%. Five QTL clusters associated with both seed size and seed weight were summarized by QTL cluster identification. Fifteen candidate genes that may be involved in regulating soybean seed size and weight were also screened based on gene function annotation and GO enrichment analysis. Discussion: The results provide a biologically basic reference for understanding the formation of soybean seed size and weight traits.

Genome Assembly and Analyses of the Macrofungus Macrocybe gigantea.

Macrocybe gigantea (M. gigantea) is a macrofungus genus that contains a big number of fairly fleshy gilled mushrooms with white spores. This macrofungus produces diverse bioactive compounds, antioxidants, and water-soluble polysaccharides. However, the genomic resources of this species remain unknown. Here, we assembled the genome of M. gigantea (41.23 Mb) into 336 scaffolds with a N50 size of 374,455 bp and compared it with the genomes of eleven other macrofungi. Comparative genomics study confirmed that M. gigantea belonged to the Macrocybe genus, a stand-alone genus different from the Tricholoma genus. In addition, we found that glycosyl hydrolase family 28 (GH28) in M. gigantea shared conserved motifs that were significantly different from their counterparts in Tricholoma. The genomic resource uncovered by this study will enhance our understanding of fungi biology, especially the differences in their growth rates and energy metabolism.

QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map.

BACKGROUND: Different soybean (Glycine max L.) leaf chlorophyll-content traits are considered to be significantly linked to soybean yield. To map the quantitative trait loci (QTLs) of soybean leaf chlorophyll-content traits, an advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3) population was adopted to phenotypic data acquisitions for the target traits across six distinct environments (seasons and soybean growth stages). Moreover, the restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage map of the RIL population was utilized for QTL mapping by carrying out the composite interval mapping (CIM) approach. RESULTS: Correlation analyses showed that most traits were correlated with each other under specific chlorophyll assessing method and were regulated both by hereditary and environmental factors. In this study, 78 QTLs for soybean leaf chlorophyll-content traits were identified. Furthermore, 13 major QTLs and five important QTL hotspots were classified and highlighted from the detected QTLs. Finally, Glyma01g15506, Glyma02g08910, Glyma02g11110, Glyma07g15960, Glyma15g19670 and Glyma15g19810 were predicted from the genetic intervals of the major QTLs and important QTL hotspots. CONCLUSIONS: The detected QTLs and candidate genes may facilitate to gain a better understanding of the hereditary basis of soybean leaf chlorophyll-content traits and may be valuable to pave the way for the marker-assisted selection (MAS) breeding of the target traits.

Identification and Mapping of Stable QTLs for Seed Oil and Protein Content in Soybean [Glycine max (L.) Merr.].

This research aimed to identify stable quantitative trait loci (QTL) associated with oil and protein content in soybean. A population of 196 recombinant inbred lines (RILs) derived from Huachun 2 × Wayao was used to evaluate these target traits. A high-density genetic linkage map was constructed by using high-throughput genome-wide sequencing technology, which contained 3413 recombination bin markers and spanned 5400.4 cM with an average distance of 1.58 cM between markers. Eighteen stable QTLs controlling oil and protein content were detected. Among them, qOil-11-1 was identified for the first time as a novel QTL, while qOil-5-1, qPro-10-1, and qPro-14-1 were strong and stable QTLs with high log-likelihood (LOD) values. Sixteen differentially expressed genes (DEGs) within these four QTLs were shown to be highly expressed during seed development based on RNA sequencing (RNA-seq) data analysis. Our results may contribute toward gene mining and marker-assisted selection (MAS) for breeding a high-quality soybean in the future.

Fine mapping of a Phytophthora-resistance locus RpsGZ in soybean using genotyping-by-sequencing.

BACKGROUND: Phytophthora root rot (PRR) caused by Phytophthora sojae (P. sojae) is one of the most serious limitations to soybean production worldwide. The identification of resistance gene(s) and their incorporation into elite varieties is an effective approach for breeding to prevent soybean from being harmed by this disease. A valuable mapping population of 228 F8:11 recombinant inbred lines (RILs) derived from a cross of the resistant cultivar Guizao1 and the susceptible cultivar BRSMG68 and a high-density genetic linkage map with an average distance of 0.81 centimorgans (cM) between adjacent bin markers in this population were used to map and explore candidate gene(s). RESULTS: PRR resistance in Guizao1 was found to be controlled by a single Mendelian locus and was finely mapped to a 367.371-kb genomic region on chromosome 3 harbouring 19 genes, including 7 disease resistance (R)-like genes, in the reference Willliams 82 genome. Quantitative real-time PCR assays of possible candidate genes revealed that Glyma.03 g05300 was likely involved in PRR resistance. CONCLUSIONS: These findings from the fine mapping of a novel Rps locus will serve as a basis for the cloning and transfer of resistance genes in soybean and the breeding of P. sojae-resistant soybean cultivars through marker-assisted selection.

QTL mapping for aluminum tolerance in RIL population of soybean (Glycine max L.) by RAD sequencing.

Aluminum (Al3+) toxicity is a typical abiotic stress that severely limits crop production in acidic soils. In this study, an RIL (recombinant inbred line, F12) population derived from the cross of Zhonghuang 24 (ZH 24) and Huaxia 3 (HX 3) (160 lines) was tested using hydroponic cultivation. Relative root elongation (RRE) and apical Al3+ content (AAC) were evaluated for each line, and a significant negative correlation was detected between the two indicators. Based on a high-density genetic linkage map, the phenotypic data were used to identify quantitative trait loci (QTLs) associated with these traits. With composite interval mapping (CIM) of the linkage map, five QTLs that explained 39.65% of RRE and AAC variation were detected on chromosomes (Chrs) Gm04, Gm16, Gm17 and Gm19. Two new QTLs, qRRE_04 and qAAC_04, were located on the same region of bin93-bin94 on Chr Gm04, which explained 7.09% and 8.98% phenotypic variation, respectively. Furthermore, the results of the expression analysis of candidate genes in the five genetic regions of the QTLs showed that six genes (Glyma.04g218700, Glyma.04g212800, Glyma.04g213300, Glyma.04g217400, Glyma.04g216100 and Glyma.04g220600) exhibited significant differential expression between the Al3+ treatment and the control of two parents. The results of qRT-PCR analysis indicated that Glyma.04g218700 was upregulated by Al3+ treatment with the hundreds-fold increased expression level and may be a candidate gene with potential roles in the response to aluminum stress. Therefore, our efforts will enable future functional analysis of candidate genes and will contribute to the strategies for improvement of aluminum tolerance in soybean.

The genome assembly of asparagus bean, Vigna unguiculata ssp. sesquipedialis.

Asparagus bean (Vigna. unguiculata ssp. sesquipedialis), known for its very long and tender green pods, is an important vegetable crop broadly grown in the developing Asian countries. In this study, we reported a 632.8 Mb assembly (549.81 Mb non-N size) of asparagus bean based on the whole genome shotgun sequencing strategy. We also generated a linkage map for asparagus bean, which helped anchor 94.42% of the scaffolds into 11 pseudo-chromosomes. A total of 42,609 protein-coding genes and 3,579 non-protein-coding genes were predicted from the assembly. Taken together, these genomic resources of asparagus bean will help develop a pan-genome of V. unguiculata and facilitate the investigation of economically valuable traits in this species, so that the cultivation of this plant would help combat the protein and energy malnutrition in the developing world.

QTL fine-mapping of soybean (Glycine max L.) leaf type associated traits in two RILs populations.

BACKGROUND: The different leaf type associated traits of soybean (Glycine max L.) including leaf area, leaf length, leaf width, leaf shape and petiole length are considered to be associated with seed yield. In order to identify quantitative trait loci (QTLs) affecting leaf type traits, two advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3; GB, Guizao 1 × Brazil 13) populations were introduced to score phenotypic values in plants across nine different environments (years, seasons, locations and soybean growth stages). Two restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage maps with an average distance of 1.00 centimorgan (cM) between adjacent bin markers were utilized for QTL fine mapping. RESULTS: Correlation analysis showed that most of the traits were correlated with each other and regulated both by hereditary and environmental factors. A total of 190 QTLs were identified for leaf type associated traits in the two populations, of which 14 loci were found to be environmentally stable. Moreover, these detected QTLs were categorized into 34 QTL hotspots, and four important QTL hotspots with phenotypic variance ranging from 3.89-23.13% were highlighted. Furthermore, Glyma04g05840, Glyma19g37820, Glyma14g07140 and Glyma19g39340 were predicted in the intervals of the stable loci and important QTL hotspots for leaf type traits by adopting Gene Ontology (GO) enrichment analysis. CONCLUSIONS: Our findings of the QTLs and the putative genes will be beneficial to gain new insights into the genetic basis for soybean leaf type traits and may further accelerate the breeding process for reasonable leaf type soybean.

Genetic mapping of powdery mildew resistance genes in soybean by high-throughput genome-wide sequencing.

KEY MESSAGE: The Mendelian locus conferring resistance to powdery mildew in soybean was precisely mapped using a combination of phenotypic screening, genetic analyses, and high-throughput genome-wide sequencing. Powdery mildew (PMD), caused by the fungus Microsphaera diffusa Cooke & Peck, leads to considerable yield losses in soybean [Glycine max (L.) Merr.] under favourable environmental conditions and can be controlled by identifying germplasm resources with resistance genes. In this study, resistance to M. diffusa among resistant varieties B3, Fudou234, and B13 is mapped as a single Mendelian locus using three mapping populations derived from crossing susceptible with resistant cultivars. The position of the PMD resistance locus in B3 is located between simple sequence repeat (SSR) markers GMES6959 and Satt_393 on chromosome 16, at genetic distances of 7.1 cM and 4.6 cM, respectively. To more finely map the PMD resistance gene, a high-density genetic map was constructed using 248 F8 recombinant inbred lines derived from a cross of Guizao1 × B13. The final map includes 3748 bins and is 3031.9 cM in length, with an average distance of 0.81 cM between adjacent markers. This genotypic analysis resulted in the precise delineation of the B13 PMD resistance locus to a 188.06-kb genomic region on chromosome 16 that harbours 28 genes, including 17 disease resistance (R)-like genes in the reference Williams 82 genome. Quantitative real-time PCR assays of possible candidate genes revealed differences in the expression levels of 9 R-like genes between the resistant and susceptible parents. These results provide useful information for marker-assisted breeding and gene cloning for PMD resistance.

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

BACKGROUND: Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. RESULTS: A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. CONCLUSIONS: This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

Acid phosphatase gene GmHAD1 linked to low phosphorus tolerance in soybean, through fine mapping.

KEY MESSAGE: Map-based cloning identified GmHAD1, a gene which encodes a HAD-like acid phosphatase, associated with soybean tolerance to low phosphorus stress. Phosphorus (P) deficiency in soils is a major limiting factor for crop growth worldwide. Plants may adapt to low phosphorus (LP) conditions via changes to root morphology, including the number, length, orientation, and branching of the principal root classes. To elucidate the genetic mechanisms for LP tolerance in soybean, quantitative trait loci (QTL) related to root morphology responses to LP were identified via hydroponic experiments. In total, we identified 14 major loci associated with these traits in a RIL population. The log-likelihood scores ranged from 2.81 to 7.43, explaining 4.23-13.98% of phenotypic variance. A major locus on chromosome 08, named qP8-2, was co-localized with an important P efficiency QTL (qPE8), containing phosphatase genes GmACP1 and GmACP2. Another major locus on chromosome 10 named qP10-2 explained 4.80-13.98% of the total phenotypic variance in root morphology. The qP10-2 contains GmHAD1, a gene which encodes an acid phosphatase. In the transgenic soybean hairy roots, GmHAD1 overexpression increased P efficiency by 8.4-16.5% relative to the control. Transgenic Arabidopsis plants had higher biomass than wild-type plants across both short- and long-term P reduction. These results suggest that GmHAD1, an acid phosphatase gene, improved the utilization of organic phosphate by soybean and Arabidopsis plants.

Improving Nelumbo nucifera genome assemblies using high-resolution genetic maps and BioNano genome mapping reveals ancient chromosome rearrangements.

Genetic and physical maps are powerful tools to anchor fragmented draft genome assemblies generated from next-generation sequencing. Currently, two draft assemblies of Nelumbo nucifera, the genomes of 'China Antique' and 'Chinese Tai-zi', have been released. However, there is presently no information on how the sequences are assembled into chromosomes in N. nucifera. The lack of physical maps and inadequate resolution of available genetic maps hindered the assembly of N. nucifera chromosomes. Here, a linkage map of N. nucifera containing 2371 bin markers [217 577 single nucleotide polymorphisms (SNPs)] was constructed using restriction-site associated DNA sequencing data of 181 F2 individuals and validated by adding 197 simple sequence repeat (SSR) markers. Additionally, a BioNano optical map covering 86.20% of the 'Chinese Tai-zi' genome was constructed. The draft assembly of 'Chinese Tai-zi' was improved based on the BioNano optical map, showing an increase of the scaffold N50 from 0.989 to 1.48 Mb. Using a combination of multiple maps, 97.9% of the scaffolds in the 'Chinese Tai-zi' draft assembly and 97.6% of the scaffolds in the 'China Antique' draft assembly were anchored into pseudo-chromosomes, and the centromere regions along the pseudo-chromosomes were identified. An evolutionary scenario was proposed to reach the modern N. nucifera karyotype from the seven ancestral eudicot chromosomes. The present study provides the highest-resolution linkage map, the optical map and chromosome level genome assemblies for N. nucifera, which are valuable for the breeding and cultivation of N. nucifera and future studies of comparative and evolutionary genomics in angiosperms.

Fine-mapping of QTLs for individual and total isoflavone content in soybean (Glycine max L.) using a high-density genetic map.

KEY MESSAGE: Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively. Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F7:8-10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171-39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37-59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection.

A High Density Genetic Map Derived from RAD Sequencing and Its Application in QTL Analysis of Yield-Related Traits in Vigna unguiculata.

Cowpea [Vigna unguiculata (L.) Walp.] is an annual legume of economic importance and widely grown in the semi-arid tropics. However, high-density genetic maps of cowpea are still lacking. Here, we identified 34,868 SNPs (single nucleotide polymorphisms) that were distributed in the cowpea genome based on the RAD sequencing (restriction-site associated DNA sequencing) technique using a population of 170 individuals (two cowpea parents and 168 F2:3 progenies). Of these, 17,996 reliable SNPs were allotted to 11 consensus linkage groups (LGs). The length of the genetic map was 1,194.25 cM in total with a mean distance of 0.066 cM/SNP marker locus. Using this map and the F2:3 population, combined with the CIM (composite interval mapping) method, eleven quantitative trait loci (QTL) of yield-related trait were detected on seven LGs (LG4, 5, 6, 7, 9, 10, and 11) in cowpea. These QTL explained 0.05-17.32% of the total phenotypic variation. Among these, four QTL were for pod length, four QTL for thousand-grain weight (TGW), two QTL for grain number per pod, and one QTL for carpopodium length. Our results will provide a foundation for understanding genes related to grain yield in the cowpea and genus Vigna.

An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding.

KEY MESSAGE: The innovative RTM-GWAS procedure provides a relatively thorough detection of QTL and their multiple alleles for germplasm population characterization, gene network identification, and genomic selection strategy innovation in plant breeding. The previous genome-wide association studies (GWAS) have been concentrated on finding a handful of major quantitative trait loci (QTL), but plant breeders are interested in revealing the whole-genome QTL-allele constitution in breeding materials/germplasm (in which tremendous historical allelic variation has been accumulated) for genome-wide improvement. To match this requirement, two innovations were suggested for GWAS: first grouping tightly linked sequential SNPs into linkage disequilibrium blocks (SNPLDBs) to form markers with multi-allelic haplotypes, and second utilizing two-stage association analysis for QTL identification, where the markers were preselected by single-locus model followed by multi-locus multi-allele model stepwise regression. Our proposed GWAS procedure is characterized as a novel restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS, https://github.com/njau-sri/rtm-gwas ). The Chinese soybean germplasm population (CSGP) composed of 1024 accessions with 36,952 SNPLDBs (generated from 145,558 SNPs, with reduced linkage disequilibrium decay distance) was used to demonstrate the power and efficiency of RTM-GWAS. Using the CSGP marker information, simulation studies demonstrated that RTM-GWAS achieved the highest QTL detection power and efficiency compared with the previous procedures, especially under large sample size and high trait heritability conditions. A relatively thorough detection of QTL with their multiple alleles was achieved by RTM-GWAS compared with the linear mixed model method on 100-seed weight in CSGP. A QTL-allele matrix (402 alleles of 139 QTL × 1024 accessions) was established as a compact form of the population genetic constitution. The 100-seed weight QTL-allele matrix was used for genetic characterization, candidate gene prediction, and genomic selection for optimal crosses in the germplasm population.

Construction of high-density genetic map and QTL mapping of yield-related and two quality traits in soybean RILs population by RAD-sequencing.

BACKGROUND: One of the overarching goals of soybean breeding is to develop lines that combine increased yield with improved quality characteristics. High-density-marker QTL mapping can serve as an effective strategy to identify novel genomic information to facilitate crop improvement. In this study, we genotyped a recombinant inbred line (RIL) population (Zhonghuang 24 × Huaxia 3) using a restriction-site associated DNA sequencing (RAD-seq) approach. A high-density soybean genetic map was constructed and used to identify several QTLs that were shown to influence six yield-related and two quality traits. RESULTS: A total of 47,472 single-nucleotide polymorphisms (SNPs) were detected for the RILs that were integrated into 2639 recombination bin units, with an average distance of 1.00 cM between adjacent markers. Forty seven QTLs for yield-related traits and 13 QTLs for grain quality traits were found to be distributed on 16 chromosomes in the 2 year studies. Among them, 18 QTLs were stable, and were identified in both analyses. Twenty six QTLs were identified for the first time, with a single QTL (qNN19a) in a 56 kb region explaining 32.56% of phenotypic variation, and an additional 10 of these were novel, stable QTLs. Moreover, 8 QTL hotpots on four different chromosomes were identified for the correlated traits. CONCLUSIONS: With RAD-sequencing, some novel QTLs and important QTL clusters for both yield-related and quality traits were identified based on a new, high-density bin linkage map. Three predicted genes were selected as candidates that likely have a direct or indirect influence on both yield and quality in soybean. Our findings will be helpful for understanding common genetic control mechanisms of co-localized traits and to select cultivars for further analysis to predictably modulate soybean yield and quality simultaneously.