Meta‐analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining

As soybean seed fatty acid content is valued in food, animal feed and some industrial applications, plant breeders continually aim to improve seed fatty acid constituent value. This study analysed 163 original quantitative trait loci (QTLs) related to soybean fatty acid content from databases and references and revealed 43 consensus QTLs. Meta‐analysis using BioMercator ver.2.1 indicated that these were located across 16 linkage groups (LGs) excluding LG D1a, LG C1, LG M and LG H. Moreover, the overview method was used to optimize these QTLs based on statistical analysis. Some valid QTL regions were narrowed down to 0.5 Mb and mapped on the same LGs as the meta‐analysis result. Furthermore, the functions of all genes located in these consensus QTL intervals were predicted and eight candidate genes were identified. KEGG pathway analysis indicated that Glyma.13G127900 and Glyma.18G232000 were involved in the fatty acid synthesis metabolic (pathway ID ko00071, ko00062, ko01040). These results lay a foundation for fine mapping of QTLs related to fatty acid content and marker‐assisted breeding in soybean.     

Genome‐wide association analysis reveals flowering‐related genes regulating rachis length in rice

Rachis length is correlated with panicle size in rice. Unveiling the genetic basis of rachis length is important for understanding the genetic regulation of panicle size. In this study, we performed a genomewide association study of rachis length using 529 rice accessions from two environments. In total, 20 loci were identified for rachis length and distributed across the 12 chromosomes except for chromosomes 2 and 5. Thirteen of the 20 loci were not linked to the cloned panicle size genes. Six flowering‐related genes, including the CCT domain‐containing genes Ghd7, Ghd7.1, Hd1, OsCCT1 and OsCO3 as well as Ehd1, were associated with rachis length in this study. These findings suggest that the network of these flowering‐related genes probably participates in the regulation of rachis length and thus affects panicle length and yield. Interestingly, haplotype analysis showed that OsCCT1 is a putative candidate gene which plays a key role in the variation of rachis length. Together, the genetic loci identified in this study could be used for rice breeding by marker‐assisted selection to improve grain yield.     

Soybean plant height QTL mapping and meta‐analysis for mining candidate genes

Plant height is closely related to seed yield of soybean. The goal of this study was to identify important loci affecting soybean plant height using meta‐analysis based on a reference physical map. Plant height related to QTLs was mapped across eight years with a RIL population by WinQTLCart v2.5. 182 QTLs related to plant height of soybean from database and our research were collected, and each QTL was projected onto the soybean physical map by software BioMercator v2.1. The confidence interval of meta‐QTL ranged from 0.09 to 5.07 Mb, and the mean phenotypic variance ranged from 4.9% to 73.0%. Furthermore, 4,259 candidate genes were located in these consensus QTLs, and 40 of them were involved in the plant growth and stem elongation and annotated as plant hormone signal transduction (pathway ID ko04075) in KEGG pathway. These results would lay a foundation for fine mapping of QTLs/genes related to plant height and marker‐assisted selection for breeding in soybean.     

Genome‐wide association studies in elite varieties of German winter barley using single‐marker and haplotype‐based methods

Genome‐wide association studies (GWAS) became a widely used method to map qualitative and quantitative traits in plants. We compared existing single‐marker and haplotype‐based methods for GWAS with a focus on barley. Based on German winter barley cultivars, four different single‐marker and haplotype‐based methods were tested for their power to detect significant associations in a large genome with a limited number of markers. We identified significant associations for yield and quality‐related traits using the iSelect array with 3886 mapped single nucleotide polymorphism (SNP) markers in a structured population consisting of 109 genotypes. Genome simulations with different numbers of genotypes, marker densities and marker effects were used to compare different GWAS methods. Results of simulations revealed a higher power in detecting significant associations for haplotype‐ than for single‐marker approaches, but showed a higher false discovery rate for SNP detection, due to lack of correction for population structure. Our simulations revealed that a population size of about 500 individuals is required to detect QTLs explaining a small trait variance (<10%).     

Identification and validation of number of pod ‐ and seed ‐ related traits QTLs in soybean

Traits related to the number of pods and seeds are important yield factors on soybean. The relationships between phenotype and quantitative trait loci (QTLs) of these traits may reveal the mechanisms underlying productivity. Our study objectives were to analyse phenotypic correlations, detect stable QTLs and identify candidate genes useful for marker‐assisted selection. Phenotypic analyses revealed that NThSP (number of three‐seeded pods) was positively correlated with NPPP (number of pods per plant) and SNPP (number of seeds per plant). Seventy‐five QTLs were identified based on the mean phenotypic data for at least 2 years. We detected two to 15 and one to three significant QTLs identified at the same location, respectively. Six consensus QTLs associated with at least two NPS‐related (number of pods and seeds related) traits were identified. Two of these were verified in another population. The QTLs for NPPP, SNPP and NThSP formed a consensus QTL cluster on GM02. Another 27 QTLs also formed clusters in five regions. Fifteen candidate genes were mined and discussed. The results will provide more information to soybean breeding.     

Identification and confirmation of quantitative trait loci for stachyose content in soybean seed

Stachyose is an unfavorable sugar in soybean meal that causes flatulence for non‐ruminant animals. Understanding the genetic control of stachyose in soybean will facilitate the modification of stachyose content at the molecular level. The objective of this study was to identify quantitative trait loci (QTL) associated with seed stachyose content using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. A normal stachyose cultivar, ‘Osage’, was crossed with a low stachyose line, V99‐5089, to develop a QTL mapping population. Two parents were screened with 33 SSR and 37 SNP markers randomly distributed on chromosome 10, and 20 SSR and 19 SNP markers surrounding a previously reported stachyose QTL region on chromosome 11. Of these, 5 SSR and 16 SNP markers were used to screen the F_3:4 lines derived from ‘Osage’ x V99‐5089. Seed samples from F_3:5 and F_3:6 lines were analyzed for stachyose content using high‐performance liquid chromatography (HPLC). Composite interval mapping analysis indicated that two stachyose QTL were mapped to chromosome 10 and 11, explaining 11% and 79% of phenotypic variation for stachyose content, respectively. The SSR/SNP markers linked to stachyose QTL could be used in breeding soybean lines with desired stachyose contents. Chi‐square tests further indicated that these two QTL probably represent two independent genes for stachyose content. Therefore, a major QTL was confirmed on chromosome 11 and a novel QTL was found on chromosome 10 for stachyose content.     

Identification of soybean genes related to fatty acid content based on a soybean genome collinearity analysis

Seed fatty acid content is an important consideration for soybean produced for food, feed, and industrial applications. In this study, MCScanX was used to analyze the entire soybean genome to generate a collinearity block, which was then used to assess the collinearity among the soybean fatty acid quantitative trait loci (QTL) in the SoyBase database. The hub‐QTLs located in the Gm06, Gm07, and Gm10 segments were identified. The Kyoto Encyclopedia of Genes and Genomes and gene ontology databases were used to analyze the genes in hub‐QTL regions, resulting in the identification of 17 candidate genes related to soybean fatty acid content. Two lines with different fatty acid contents and a recurrent parent were selected from a chromosome segment substitution line library for a subsequent quantitative real‐time polymerase chain reaction (qRT‐PCR) assay to verify the candidate gene expression patterns. Four genes were related to the total soybean fatty acid content, while three genes were related to the content of specific fatty acid types. The results of this study may be relevant for the fine mapping of soybean fatty acid QTLs/genes.     

Mapping and analysis of QTLs related to seed length and seed width in Glycine max

Both seed length and seed width are important traits for soybean yield. In the present study, 89 Quantitative trait loci (QTLs) of seed length and 65 QTLs of seed width were collected from published papers and our study. QTLs in this study were evaluated by the soymap2, then totally 23 consensus QTLs were located on 17 linkage groups (LGs) through the meta‐analysis. The minimum confidence interval was 0.28 cM and the mean phenotypic variance (R²) was ranged from 5.33% to 23.36%. To optimize these QTLs based on statistic analysis, overview method was further used to narrow down CI, the number of QTLs was narrowed down to 84. Furthermore, 2,750 candidate genes were screened from the consensus QTL intervals by informatics, a total of 37 genes were found to be associated with seed size. All results could lay a foundation for MAS (Molecular Assisted Selection) and gene cloning.     

Genomewide association analysis of salt tolerance in soybean [Glycine max (L.) Merr.]

Salinity is a common abiotic stress causing soybean [Glycine max (L.) Merr.] yield loss worldwide. The use of tolerant cultivars is an effective and economic approach to coping with this stress. Towards this, research is needed to identify salt‐tolerant germplasm and better understand the genetic and molecular basis of salt tolerance in soybean. The objectives of this study were to identify salt‐tolerant genotypes, to search for single‐nucleotide polymorphisms (SNPs) and QTLs associated with salt tolerance. A total of 192 diverse soybean lines and cultivars were screened for salt tolerance in the glasshouse based on visual leaf scorch scores after 15–18 days of 120 mM NaCl stress. These genotypes were further genotyped using the SoySNP50K iSelect BeadChip. Genomewide association mapping showed that 62 SNP markers representing six genomic regions on chromosomes (Chr.) 2, 3, 5, 6, 8 and 18, respectively, were significantly associated with salt tolerance (p < 0.001). A total of 52 SNP markers on Chr. 3 are mapped at or near the major salt tolerance QTL previously identified in S‐100 (Lee et al., 2014). Three SNPs on Chr. 18 map near the salt tolerance QTL previously identified in Nannong1138‐2 (Chen, Cui, Fu, Gai, & Yu, 2008). The other significant SNPs represent four putative minor QTLs for salt tolerance, newly identified in this study. The results above lay the foundation for fine mapping, cloning and molecular breeding for soybean salt tolerance.     

Quantitative trait locus analysis for soybean (Glycine max) seed protein and oil concentrations using selected breeding populations

Soybean seed protein and oil concentrations are important traits that directly affect the quality of soyfoods. Many studies and breeding programmes have been conducted to find major quantitative trait loci (QTL) that regulate protein and oil concentrations and to develop soybean cultivars with high protein and/or oil content. The purpose of this study was to identify these QTL using a selected breeding population. The population was tested in field conditions over a period of 3 years. Seed protein and oil concentrations were measured each year. Single‐nucleotide polymorphisms (SNPs) were used to construct genetic map using a 180K SoyaSNP array, which identified 1,570 SNPs. We identified 12 QTL for seed protein, 11 for seed oil concentration and four for both traits. Among these, 17 QTL were closely mapped to previously reported QTL, whereas ten sites were novel. Several QTL were detected across at least two experimental years. These loci are good candidate QTL for optimal seed protein and oil concentrations. Our results demonstrate that favourable target QTL can be successfully identified using selected breeding populations.     

Identification of QTLs for growth period traits in soybean using association analysis and linkage mapping

The growth period traits of soybean (Glycine max L. Merr.) are quantitatively inherited and crucial for its adaptation to different environments. Association analysis and linkage mapping were used to identify the quantitative trait loci (QTLs) for days to flowering (DF), days from flowering to maturity (DFM) and days to maturity (DM). Considering the effect of sowing date, the phenotypes were evaluated in three or four sowing‐date‐experiments in each year. A total of 96 associations, involving 19 SSRs corresponding to DF, DFM and/or DM, were identified by association mapping. Six, eight and two QTLs were observed relating to DF, DFM and DM by linkage mapping, respectively, and some QTLs were shared by DF, DFM and DM. Four SSRs (Satt150, Satt489, Satt172 and Sat_312) were found to be related to the growth period traits using the two mapping methods. In summary, association analysis and linkage mapping can complement and verify results from both methods to identify QTLs in soybean, and these findings may be useful in facilitating the selection of growth period–related traits via marker‐assisted selection.     

Effects of divergent selection for seed protein content in high‐protein vs. food‐grade populations of early maturity soybean

Due to the growing need for vegetable protein in Central European agriculture, there is interest in producing food‐grade soybeans, which are higher in seed protein and sucrose content and have a larger seed size than conventional soybeans. As protein content of conventional soybean is often below 400 g/kg, either high‐protein or food‐grade donors were crossed with adapted genotypes in order to increase their protein level. After divergent selection for protein content, lines were evaluated for seed quality characters across three environments in Austria. The objectives of this research were to determine the roles of genetic background and the selection for protein content on food‐grade soybean traits. While seed protein content of adapted parents was between 395 and 420 g/kg, its range was from 410 to 490 g/kg for the high‐protein and from 390 to 450 g/kg for the food‐grade lines, respectively. However, food‐grade populations were superior in seed size and sucrose content and revealed different correlation patterns between quality traits as compared to high‐protein populations, which demonstrates their usefulness for developing soybeans with improved quality.     

Effects of high oleic acid soybean on seed yield,protein and oil contents,and seed germination revealed by near‐isogeneic lines

Typical soybean oil is composed of palmitic, stearic, oleic, linoleic and linolenic acids. High oleic acid content in soybean seed is a key compositional trait that improves oxidative stability and increases oil functionality and shelf life. Using a marker‐assisted selection method, near‐isogenic lines (NILs) of G00‐3213 for the high oleic trait were developed and yield tested. These NILs have various combinations of FAD2‐1A and FAD2‐1B alleles that were derived from the same backcrossing populations. The results indicated that G00‐3213 NILs with both homozygous mutant FAD2‐1A and FAD2‐1B alleles produced an average of 788 g/kg oleic acid content. The results also demonstrated that possessing these mutant alleles did not cause a yield reduction. Furthermore, seed germination tests across 12 temperatures (12.8–32.0°C) showed that modified seed composition for oleic acid in general did not have a major impact on seed germination. However, there was a possible reduction in seed germination vigour when high oleic seeds are planted in cold soil. The mutant FAD2‐1A and FAD2‐1B alleles did not hinder either seed or plant development.     

单粒花生主要脂肪酸含量近红外预测模型的建立及其应用

脂肪酸组成是影响花生营养价值和货架寿命的主要因素,高油酸花生以其营养保健价值高、化学稳定性好、耐储藏等特点,深受广大消费者和花生加工企业的喜爱。因此,培育高油酸品种是花生育种的重要目标,建立快速、高效、准确检测花生中主要脂肪酸含量的无损方法是加快花生脂肪酸改良和高油酸品种选育进程的重要技术保障。本研究利用近红外光谱技术建立了可以非破坏性地快速检测单粒花生中油酸、亚油酸、棕榈酸含量的数学模型,其中油酸模型的决定系数(R2)为0.907,均方差为3.463;亚油酸模型的决定系数为0.918,均方差为2.824;棕榈酸模型的决定系数为0.824,均方差为0.782。使用100粒花生验证该模型的准确性,结果油酸、亚油酸和棕榈酸的近红外预测值与化学值的相关系数分别为0.88、0.90和0.71,表明此模型可以准确地预测单粒花生中这3种脂肪酸的含量。本研究借助该模型建立了一种不依赖分子标记的快速、高效选育高油酸花生的方法,并成功应用于高油酸花生育种,选育出高油酸花生品种中花215。     

A SNP genetic linkage map based on the ‘Hamilton’ by ‘Spencer’ recombinant inbred line population identified QTL for seed isoflavone contents in soybean

Soybean is one of the most important crops worldwide for its protein and oil as well as the health beneficial phytoestrogens or isoflavone. This study reports a relatively dense single nucleotide polymorphism (SNP)‐based genetic map based on ‘Hamilton’ by ‘Spencer’ recombinant inbred line population and quantitative trait loci (QTL) for seed isoflavone contents. The genetic map is composed of 1502 SNP markers and covers about 1423.72 cM of the soybean genome. Two QTL for seed isoflavone contents have been identified in this population. One major QTL that controlled both daidzein (qDZ1) and total isoflavone contents (qTI1) was found on LG C2 (Chr 6). And a second QTL for glycitein content (qGT1) was identified on the LG G (Chr 18). These two QTL in addition to others identified in soybean could be used in soybean breeding to optimize isoflavone content. This newly assembled soybean linkage map is a useful tool to identify and map QTL for important agronomic traits and enhance the identification of the genes involved in these traits.