Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines

Salt is a severe abiotic stress causing soybean yield loss in saline soils and irrigated fields. Marker-assisted selection (MAS) is a powerful genomic tool for improving the efficiency of breeding salt-tolerant soybean varieties. The objectives of this study were to uncover novel single-nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs) associated with salt tolerance and to confirm the previously identified genomic regions and SNPs for salt tolerance. A total of 283 diverse soybean plant introductions (PIs) were screened for salt tolerance in the greenhouse based on leaf chloride concentrations and leaf chlorophyll concentrations after 12–18 days of 120-mM NaCl treatment. A total of 33,009 SNPs across 283 genotypes from the Illumina Infinium SoySNP50K BeadChip database were employed in the association analysis with leaf chloride concentrations and leaf chlorophyll concentrations. Genome-wide association mapping showed that 45 SNPs representing nine genomic regions on chromosomes (Chr.) 2, 3, 7, 8, 10, 13, 14, 16, and 20 were significantly associated with both leaf chloride concentrations and leaf chlorophyll concentrations in 2014, 2015, and combined years. A total of 31 SNPs on Chr. 3 were mapped at or near the previously reported major salt tolerance QTL. The significant SNP on Chr. 2 was also in proximity to the previously reported SNP for salt tolerance. The other significant SNPs represent seven putative novel QTLs for salt tolerance. The significant SNP markers on Chr. 2, 3, 14, 16, and 20, which were identified in both general linear model and mixed linear model, were highly recommended for MAS in breeding salt-tolerant soybean varieties.     

RFLP analysis of soybean seed protein and oil content

Summary The objectives of this study were to present an expanded soybean RFLP map and to identify quantitative trait loci (QTL) in soybean [Glycine max (L.) Merr.] for seed protein and oil content. The study population was formed from a cross between a G. max experimental line (A81-356022) and a G. soja Sieb. and Zucc. plant introduction (PI 468916). A total of 252 markers was mapped in the population, forming 31 linkage groups. Protein and oil content were measured on seed harvested from a replicated trial of 60 F₂-derived lines in the F₃ generation (F₂₃ lines). Each F₂₃ line was genotyped with 243 RFLP, five isozyme, one storage protein, and three morphological markers. Significant (P<0.01) associations were found between the segregation of markers and seed protein and oil content. Segregation of individual markers explained up to 43% of the total variation for specific traits. All G. max alleles at significant loci for oil content were associated with greater oil content than G. soja alleles. All G. soja alleles at significant loci for protein content were associated with greater protein content than G. max alleles.     

In silico single nucleotide polymorphism discovery and application to marker-assisted selection in soybean

The general approach to discovering single nucleotide polymorphisms (SNPs) requires locus-specific PCR amplification. To enhance the efficiency of SNP discovery in soybean, we used in silico analysis prior to re-sequencing as it is both rapid and inexpensive. In silico analysis was performed to detect putative SNPs in expressed sequence tag (EST) contigs assembled using publicly available ESTs from 18 different soybean genotypes. SNP validation by direct sequencing of six soybean cultivars and a wild soybean genotype was performed with PCR primers designed from EST contigs aligned with at least 5 out of 18 soybean genotypes. The efficiency of SNP discovery among the confirmation genotypes was 81.2%. Furthermore, the efficiency of SNP discovery between Pureunkong and Jinpumkong 2 genotypes was 47.4%, a great improvement on our previous finding based on direct sequencing (22.3%). Using SNPs between Pureunkong and Jinpumkong 2 in EST contigs, which were linked to target traits, we were able to genotype 90 recombinant inbred lines by high-resolution melting (HRM) analysis. These SNPs were mapped onto the expected locations near quantitative trait loci for water-logging tolerance and seed pectin concentration. Thus, our protocol for HRM analysis can be applied successfully not only to genetic diversity studies, but also to marker-assisted selection (MAS). Our study suggests that a combination of in silico analysis and HRM can reduce the cost and labor involved in developing SNP markers and genotyping SNPs. The markers developed in this study can also easily be applied to MAS if the markers are associated with the target traits.     

A study of the possible association between adenosine A2A receptor gene polymorphisms and attention‐deficit hyperactivity disorder traits

The adenosine A_2A receptor (ADORA2A) is linked to the dopamine neurotransmitter system and is also implicated in the regulation of alertness, suggesting a potential association with attention‐deficit hyperactivity disorder (ADHD) traits. Furthermore, animal studies suggest that the ADORA2A may influence ADHD‐like behavior. For that reason, the ADORA2A gene emerges as a promising candidate for studying the etiology of ADHD traits. The aim of this study was to examine the relationship between ADORA2A gene polymorphisms and ADHD traits in a large population‐based sample. This study was based on the Child and Adolescent Twin Study in Sweden (CATSS), and included 1747 twins. Attention‐deficit hyperactivity disorder traits were assessed through parental reports, and samples of DNA were collected. Associations between six single nucleotide polymorphisms (SNPs) and ADHD traits were examined, and results suggested a nominal association between ADHD traits and three of these SNPs: rs3761422, rs5751876 and rs35320474. For one of the SNPs, rs35320474, results remained significant after correction for multiple comparisons. These results indicate the possibility that the ADORA2A gene may be involved in ADHD traits. However, more studies replicating the present results are warranted before this association can be confirmed .     

Selection for high seed oil content in soybean families derived from plants regenerated from protoplasts and tissue cultures

Recurrent selection for high seed oil content was carried out with 2,008 progeny of 28 plants regenerated via embryogenesis, 95 via organogenesis and 25 from protoplasts via organogenesis from five different soybean cultivars. Two lines derived from plants regenerated from the cultivar Jack with small increases in seed oil content emerged after three selection cycles in the field but in both cases the protein content was decreased and the seed yield of one of the lines was also decreased. Apparently somaclonal variation for seed oil content can arise, but on the basis of the decreases in protein and yield found in this study, this small change is not useful for soybean improvement. Received: 22 July 2000 / Accepted: 28 July 2000     

Genomic consequences of selection and genome-wide association mapping in soybean

Background

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits.

Results

To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified.

Conclusions

These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1872-y) contains supplementary material, which is available to authorized users.     

Genetic diversity and association mapping in a collection of selected Chinese soybean accessions based on SSR marker analysis

For broadening the narrow genetic base of modern soybean cultivars, 159 accessions were selected from the Chinese soybean collection which contained at least one of seven important agronomic traits: resistance to soybean cyst nematode (SCN) or soybean mosaic virus (SMV), tolerance to salt, cold, or drought, high seed oil content or high protein content. Genetic diversity evaluation using 55 microsatellite loci distributed across the genome indicated that a large amount of genetic diversity (0.806) and allelic variation (781) were conserved in this selected set, which captured 65.6% of the alleles present in Chinese soybean collection (1,863 accessions). On average, 9.4 rare alleles (frequency <5%) per locus were present, which were highly informative. Using model-based Bayesian clustering in STRUCTURE we distinguished four main clusters and a set of accessions with admixed ancestry. The four clusters reflected different geographic regions of origin of the accessions. Since the clusters were also clearly different with respect to the seven agronomic traits, the inferred population structure was introduced when association analysis was conducted. A total of 21 SSR markers on 16 chromosomes were identified as significantly (P < 0.01) associated with high oil content (6), high protein content (1), drought tolerance (5), SCN resistance (6) and SMV resistance (3). Twelve of these markers were located in or near previously identified quantitative trait loci (QTL). The results for both genetic relationship and trait-related markers will be useful for effective conservation and utilization of soybean germplasm.     

Three‐dimensional genetic networks among seed oil‐related traits,metabolites and genes reveal the genetic foundations of oil synthesis in soybean

Although the biochemical and genetic basis of lipid metabolism is clear in Arabidopsis, there is limited information concerning the relevant genes in Glycine max (soybean). To address this issue, we constructed three‐dimensional genetic networks using six seed oil‐related traits, 52 lipid metabolism‐related metabolites and 54 294 SNPs in 286 soybean accessions in total. As a result, 284 and 279 candidate genes were found to be significantly associated with seed oil‐related traits and metabolites by phenotypic and metabolic genome‐wide association studies and multi‐omics analyses, respectively. Using minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) analyses, six seed oil‐related traits were found to be significantly related to 31 metabolites. Among the above candidate genes, 36 genes were found to be associated with oil synthesis (27 genes), amino acid synthesis (four genes) and the tricarboxylic acid (TCA) cycle (five genes), and four genes (GmFATB1a, GmPDAT, GmPLDα1 and GmDAGAT1) are already known to be related to oil synthesis. Using this information, 133 three‐dimensional genetic networks were constructed, 24 of which are known, e.g. pyruvate–GmPDAT–GmFATA2–oil content. Using these networks, GmPDAT, GmAGT and GmACP4 reveal the genetic relationships between pyruvate and the three major nutrients, and GmPDAT, GmZF351 and GmPgs1 reveal the genetic relationships between amino acids and seed oil content. In addition, GmCds1, along with average temperature in July and the rainfall from June to September, influence seed oil content across years. This study provides a new approach for the construction of three‐dimensional genetic networks and reveals new information for soybean seed oil improvement and the identification of gene function.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Genome‐wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China

Bread wheat is a leading cereal crop worldwide. Limited amount of superior allele loci restricted the progress of molecular improvement in wheat breeding. Here, we revealed new allelic variation distribution for 13 yield‐related traits in series of genome‐wide association studies (GWAS) using the wheat 90K genotyping assay, characterized in 163 bread wheat cultivars. Agronomic traits were investigated in 14 environments at three locations over 3 years. After filtering SNP data sets, GWAS using 20 689 high‐quality SNPs associated 1769 significant loci that explained, on average, ~20% of the phenotypic variation, both detected already reported loci and new promising genomic regions. Of these, repetitive and pleiotropic SNPs on chromosomes 6AS, 6AL, 6BS, 5BL and 7AS were significantly linked to thousand kernel weight, for example BS00021705_51 on 6BS and wsnp_Ex_c32624_41252144 on 6AS, with phenotypic variation explained (PVE) of ~24%, consistently identified in 12 and 13 of the 14 environments, respectively. Kernel length‐related SNPs were mainly identified on chromosomes 7BS, 6AS, 5AL and 5BL. Plant height‐related SNPs on chromosomes 4DS, 6DL, 2DS and 1BL were, respectively, identified in more than 11 environments, with averaged PVE of ~55%. Four SNPs were confirmed to be important genetic loci in two RIL populations. Based on repetivity and PVE, a total of 41 SNP loci possibly played the key role in modulating yield‐related traits of the cultivars surveyed. Distribution of superior alleles at the 41 SNP loci indicated that superior alleles were getting popular with time and modern cultivars had integrated many superior alleles, especially for peduncle length‐ and plant height‐related superior alleles. However, there were still 19 SNP loci showing less than percentages of 50% in modern cultivars, suggesting they should be paid more attention to improve yield‐related traits of cultivars in the Yellow and Huai wheat region. This study could provide useful information for dissection of yield‐related traits and valuable genetic loci for marker‐assisted selection in Chinese wheat breeding programme.     

大豆种子蛋白和油脂含量调控的研究进展

作为重要的粮油饲兼用作物,大豆为世界膳食提供高达约71%的蛋白质和29%的油脂。随着人口不断增长和大豆消费需求的不断提高,在有限的耕地面积和单产条件下,大豆品质的遗传改良则更具重要意义。该文综述了大豆种子蛋白和油脂含量两个重要品质性状调控的研究进展,总结了调控大豆蛋白和油脂合成的关键酶和转录因子及因子间的相互作用,并根据蛋白和油脂合成代谢调控途径中关键酶和转录因子作用机制,绘制了大豆蛋白和油脂合成代谢的分子调控网络。此外,该文还讨论了当前大豆种子蛋白油脂含量调控研究存在的瓶颈及对策,以期为大豆种子品质的遗传改良和高产品种培育提供参考。     

Restriction fragment length polymorphism analysis of somatic hybrids between Lycopersicon esculentum and irradiated L. peruvianum: evidence for limited donor genome elimination and extensive chromosome rearrangements

Summary The genome composition of asymmetric somatic hybrids, obtained by fusion of leaf protoplasts fromLycopersicon esculentum and gamma-irradiated leaf protoplasts fromL. peruvianum, was characterised by Southern blot analysis using 29 restriction fragment length polymorphism markers. Eight low dose hybrids and seven high dose hybrids (irradiation dose 50 Gray and 300 Gray, respectively) were analysed. By densitometric scanning of the autoradiographs, the number of alleles for each locus of the component species was established. In general, elimination of alleles from the irradiatedL. peruvianum donor genome was limited and ranged from 17%–69%. ThreeL. peruvianum loci, located on chromosomes 2, 4 and 7, were present in all asymmetric hybrids, suggesting linkage to the regeneration capacity trait which was used in selecting them. The loss of donor genome was dose-dependent. Low dose hybrids contained more alleles, loci and complete chromosomes fromL. peruvianum than high dose hybrids, whereas the high dose hybrids contained more incomplete chromosomes. In most hybrids someL. esculentum alleles were lost. The possible implications of these results for the use of asymmetric hybrids in plant breeding are discussed.     

Identification of loci governing eight agronomic traits using a GBS‐GWAS approach and validation by QTL mapping in soya bean

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome‐wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping‐by‐sequencing (GBS) approach was used to provide dense genome‐wide marker coverage (>47 000 SNPs) for a panel of 304 short‐season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.     

Dissection of the genetic architecture of three seed‐quality traits and consequences for breeding in Brassica napus

Genome‐wide association studies (GWASs) combining high‐throughput genome resequencing and phenotyping can accelerate the dissection of genetic architecture and identification of genes for plant complex traits. In this study, we developed a rapeseed genomic variation map consisting of 4 542 011 SNPs and 628 666 INDELs. GWAS was performed for three seed‐quality traits, including erucic acid content (EAC), glucosinolate content (GSC) and seed oil content (SOC) using 3.82 million polymorphisms in an association panel. Six, 49 and 17 loci were detected to be associated with EAC, GSC and SOC in multiple environments, respectively. The mean total contribution of these loci in each environment was 94.1% for EAC and 87.9% for GSC, notably higher than that for SOC (40.1%). A high correlation was observed between phenotypic variance and number of favourable alleles for associated loci, which will contribute to breeding improvement by pyramiding these loci. Furthermore, candidate genes were detected underlying associated loci, based on functional polymorphisms in gene regions where sequence variation was found to correlate with phenotypic variation. Our approach was validated by detection of well‐characterized FAE1 genes at each of two major loci for EAC on chromosomes A8 and C3, along with MYB28 genes at each of three major loci for GSC on chromosomes A9, C2 and C9. Four novel candidate genes were detected by correlation between GSC and SOC and observed sequence variation, respectively. This study provides insights into the genetic architecture of three seed‐quality traits, which would be useful for genetic improvement of B. napus.     

新收集大豆种质资源主要品质鉴定与评价

对"十五"期间新收集、保存入国家种质资源库的841份大豆种质资源的蛋白质、脂肪两个主要品质性状进行了鉴定评价.结果表明,蛋白质、脂肪含量均近似正态分布,最大频度分别出现在41.01%～ 42.00%含量范围和20.01%～21.00%含量范围.与以前收集、保存的种质资源相比,新收集种质资源的蛋白质含量呈下降趋势,而脂肪含量和蛋脂总量呈上升趋势.不同类型种质资源的品质性状比较结果表明,地方品种的蛋白质总体水平明显高于育种材料、引进种质和选育品种3种类型,引进种质的脂肪、蛋脂总量的总体水平明显高于其他3种类型.国内种质资源高蛋白质大豆占有率高于引进种质资源;引进种质资源高脂肪、高蛋白兼高油的大豆占有率高于国内种质资源.     

Genome‐wide association mapping for female fertility traits in Danish and Swedish Holstein cattle

A genome‐wide association study was conducted using a mixed model analysis for QTL for fertility traits in Danish and Swedish Holstein cattle. The analysis incorporated 2,531 progeny tested bulls, and a total of 36 387 SNP markers on 29 bovine autosomes were used. Eleven fertility traits were analyzed for SNP association. Furthermore, mixed model analysis was used for association analyses where a polygenic effect was fitted as a random effect, and genotypes at single SNPs were successively included as a fixed effect in the model. The Bonferroni correction for multiple testing was applied to adjust the significance threshold. Seventy‐four SNP‐trait combinations showed chromosome‐wide significance, and five of these were significant genome‐wide. Twenty‐four QTL regions on 14 chromosomes were detected. Strong evidence for the presence of QTL that affect fertility traits were observed on chromosomes 3, 5, 10, 13, 19, 20, and 24. The QTL intervals were generally smaller than those described in earlier linkage studies. The identification of fertility trait‐associated SNPs and mapping of the corresponding QTL in small chromosomal regions reported here will facilitate searches for candidate genes and candidate polymorphisms.     

Identification of favorable SNP alleles and candidate genes responsible for inflorescence-related traits via GWAS in chrysanthemum

Key message

81 SNPs were identified for three inflorescence-related traits, in which 15 were highly favorable. Two dCAPS markers were developed for future MAS breeding, and six candidate genes were predicted.

Abstract

Chrysanthemum is a leading ornamental species worldwide and demonstrates a wealth of morphological variation. Knowledge about the genetic basis of its phenotypic variation for key horticultural traits can contribute to its effective management and genetic improvement. In this study, we conducted a genome-wide association study (GWAS) based on two years of phenotype data and a set of 92,617 single nucleotide polymorphisms (SNPs) using a panel of 107 diverse cut chrysanthemums to dissect the genetic control of three inflorescence-related traits. A total of 81 SNPs were significantly associated with the three inflorescence-related traits (capitulum diameter, number of ray florets and flowering time) in at least one environment, with an individual allele explaining 22.72–38.67% of the phenotypic variation. Fifteen highly favorable alleles were identified for the three target traits by computing the phenotypic effect values for the stable associations detected in 2 year-long trials at each locus. Dosage pyramiding effects of the highly favorable SNP alleles and significant linear correlations between highly favorable allele numbers and corresponding phenotypic performance were observed. Two highly favorable SNP alleles correlating to flowering time and capitulum diameter were converted to derived cleaved amplified polymorphic sequence (dCAPS) markers to facilitate future breeding. Finally, six putative candidate genes were identified that contribute to flowering time and capitulum diameter. These results serve as a foundation for analyzing the genetic mechanisms underlying important horticultural traits and provide valuable insights into molecular marker-assisted selection (MAS) in chrysanthemum breeding programs.