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

Deciphering of Genomic Loci Associated with Alkaline Tolerance in Soybean [Glycine max (L.) Merr.] by Genome-Wide Association Study

Alkaline stress is one of the major abiotic constraints that limits plant growth and development. However, the genetic basis underlying alkaline tolerance in soybean [Glycine max (L.) Merr.] remains largely unexplored. In this study, an integrated genomic analysis approach was employed to elucidate the genetic architecture of alkaline tolerance in a diverse panel of 326 soybean cultivars. Through association mapping, we detected 28 single nucleotide polymorphisms (SNPs) significantly associated with alkaline tolerance. By examining the genomic distances around these significant SNPs, five genomic regions were characterized as stable quantitative trait loci (QTLs), which were designated as qAT1, qAT4, qAT14, qAT18, and qAT20. These QTLs are reported here for the first time in soybean. Seventeen putative candidate genes were identified within the physical intervals of these QTLs. Haplotype analysis indicated that four of these candidate genes exhibited significant allele variation associated with alkaline tolerance-related traits, and the haplotype alleles for these four genes varied in number from two to four. The findings of this study may have important implications for soybean breeding programs aimed at enhancing alkaline tolerance.

GWAS analysis revealed genomic loci and candidate genes associated with the 100-seed weight in high-latitude-adapted soybean germplasm

KEY MESSAGE

In the present study, we identified 22 significant SNPs, eight stable QTLs and 17 potential candidate genes associated with 100-seed weight in soybean. Soybean is an economically important crop that is rich in seed oil and protein. The 100-seed weight (HSW) is a crucial yield contributing trait. This trait exhibits complex inheritance regulated by many genes and is highly sensitive to environmental factors. In this study, an integrated strategy of association mapping, QTL analysis, candidate gene and haplotype analysis was utilized to elucidate the complex genetic architecture of HSW in a panel of diverse soybean cultivars. Our study revealed 22 SNPs significantly associated with HSW through association mapping using five GWAS models across multiple environments plus a combined environment. By considering the detection of SNPs in multiple environments and GWAS models, the genomic regions of eight consistent SNPs within the ± 213.5 kb were depicted as stable QTLs. Among the eight QTLs, four, viz. qGW1.1, qGW1.2, qGW9 and qGW16, are reported here for the first time, and the other four, viz. qGW4, qGW8, qGW17 and qGW19, have been reported in previous studies. Thirty-two genes were detected as putative candidates within physical intervals of eight QTLs by in silico analysis. Twelve genes (out of total 32) showed significant differential expression patterns among the soybean accessions with contrasting HSW. Moreover, different haplotype alleles of 10 candidate genes are associated with different phenotypes of HSW. The outcome of the current investigation can be used in soybean breeding programs for producing cultivars with higher yields.

Deciphering the genetic basis of salinity tolerance in a diverse panel of cultivated and wild soybean accessions by genome-wide association mapping

KEY MESSAGE

In a genome-wide association study involving 269 cultivated and wild soybean accessions, potential salt tolerance donors were identified along with significant markers and candidate genes, such as GmKUP6 and GmWRKY33. Salt stress remains a significant challenge in agricultural systems, notably impacting soybean productivity worldwide. A comprehensive genome-wide association study (GWAS) was conducted to elucidate the genetic underpinnings of salt tolerance and identify novel source of salt tolerance among soybean genotypes. A diverse panel comprising 269 wild and cultivated soybean accessions was subjected to saline stress under controlled greenhouse conditions. Phenotypic data revealed that salt tolerance of soybean germplasm accessions was heavily compromised by the accumulation of sodium and chloride, as indicated by highly significant positive correlations of leaf scorching score with leaf sodium/chloride content. The GWAS analysis, leveraging a dataset of 32,832 SNPs, unveiled 32 significant marker-trait associations (MTAs) across seven traits associated with salt tolerance. These markers explained a substantial portion of the phenotypic variation, ranging from 14 to 52%. Notably, 11 markers surpassed Bonferroni's correction threshold, exhibiting highly significant associations with the respective traits. Gene Ontology enrichment analysis conducted within a 100 Kb range of the identified MTAs highlighted candidate genes such as potassium transporter 6 (GmKUP6), cation hydrogen exchanger (GmCHX15), and GmWRKY33. Expression levels of GmKUP6 and GmWRKY33 significantly varied between salt-tolerant and salt-susceptible soybean accessions under salt stress. The genetic markers and candidate genes identified in this study hold promise for developing soybean varieties resilient to salinity stress, thereby mitigating its adverse effects.

Genome-wide association study provides new insight into the underlying mechanism of drought tolerance during seed germination stage in soybean

Drought is one of the major environmental issues that reduce crop yield. Seed germination is a crucial stage of plant development in all crop plants, including soybean. In soybean breeding, information about genetic mechanism of drought tolerance has great importance. However, at germination stage, there is relatively little knowledge on the genetic basis of soybean drought resistance. The objective of this work was to find the quantitative trait nucleotides (QTNs) linked to drought tolerance related three traits using a genome-wide association study (GWAS), viz., germination rate (GR), root length (RL), and whole seedling length (WSL), using germplasm population of 240 soybean PIs with 34,817 SNPs genotype data having MAF > 0.05. It was observed that heritability (H2) for GR, WSL, and RL across both environments (2020, and 2019) were high in the range of 0.76-0.99, showing that genetic factors play a vital role in drought tolerance as compared to environmental factors. A number of 23 and 27 QTNs were found to be linked to three traits using MLM and mrMLM, respectively. Three significant QTNs, qGR8-1, qWSL13-1, and qRL-8, were identified using both MLM and mrMLM methods among these QTNs. QTN8, located on chromosome 8 was consistently linked to two traits (GR and RL). The area (± 100 Kb) associated with this QTN was screened for drought tolerance based on gene annotation. Fifteen candidate genes were found by this screening. Based on the expression data, four candidate genes i.e. Glyma08g156800, Glyma08g160000, Glyma08g162700, and Glyma13g249600 were found to be linked to drought tolerance regulation in soybean. Hence, the current study provides evidence to understand the genetic constitution of drought tolerance during the germination stage and identified QTNs or genes could be utilized in molecular breeding to enhance the yield under drought stress.

QTL Detection of Salt Tolerance at Soybean Seedling Stage Based on Genome-Wide Association Analysis and Linkage Analysis

The utilization of saline land is a global challenge, and cultivating salt-tolerant soybean varieties is beneficial for improving the efficiency of saline land utilization. Exploring the genetic basis of salt-tolerant soybean varieties and developing salt-tolerant molecular markers can effectively promote the process of soybean salt-tolerant breeding. In the study, the membership function method was used to evaluate seven traits related to salt tolerance and comprehensive salt tolerance at the soybean seedling stage; genome-wide association analysis (GWAS) was performed in a natural population containing 200 soybean materials; and linkage analysis was performed in 112 recombinant inbred lines (RIL) population to detect quantitative trait loci (QTLs) of salt tolerance. In the GWAS, 147 SNPs were mapped, explaining 5.28-17.16% of phenotypic variation. In the linkage analysis, 10 QTLs were identified, which could explain 6.9-16.16% of phenotypic variation. And it was found that there were two co-located regions between the natural population and the RIL population, containing seven candidate genes of salt tolerance in soybean. In addition, one colocalization interval was found to contain qZJS-15-1, rs47665107, and rs4793412, all of which could explain more than 10% of phenotypic variation rates, making it suitable for molecular marker development. The physical positions of rs47665107 and rs47934112 were included in qZJS-15-1. Therefore, a KASP marker was designed and developed using Chr. 15:47907445, which was closely linked to the qZJS-15-1. This marker could accurately and clearly cluster the materials of salt-tolerant genotypes in the heterozygous population tested. The QTLs and KASP markers found in the study provide a theoretical and technical basis for accelerating the salt-tolerant breeding of soybean.

Residual networks without pooling layers improve the accuracy of genomic predictions

KEY MESSAGE

Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous algorithms. With the decrease in DNA sequencing costs and the development of deep learning, phenotype prediction accuracy by genomic selection (GS) continues to improve. Residual networks, a widely validated deep learning technique, are introduced to deep learning for GS. Since each locus has a different weighted impact on the phenotype, strided convolutions are more suitable for GS problems than pooling layers. Through the above technological innovations, we propose a GS deep learning algorithm, residual neural network for genomic selection (ResGS). ResGS is the first neural network to reach 35 layers in GS. In 15 cases from four public data, the prediction accuracy of ResGS is higher than that of ridge-regression best linear unbiased prediction, support vector regression, random forest, gradient boosting regressor, and deep neural network genomic prediction in most cases. ResGS performs well in dealing with gene-environment interaction. Phenotypes from other environments are imported into ResGS along with genetic data. The prediction results are much better than just providing genetic data as input, which demonstrates the effectiveness of GS multi-modal learning. Standard deviation is recommended as an auxiliary GS evaluation metric, which could improve the distribution of predicted results. Deep learning for GS, such as ResGS, is becoming more accurate in phenotype prediction.

GWAS and WGCNA Analysis Uncover Candidate Genes Associated with Oil Content in Soybean

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content.

Identification of QTNs, QTN-by-environment interactions, and their candidate genes for salt tolerance related traits in soybean

BACKGROUND

Salt stress significantly reduces soybean yield. To improve salt tolerance in soybean, it is important to mine the genes associated with salt tolerance traits.

RESULTS

Salt tolerance traits of 286 soybean accessions were measured four times between 2009 and 2015. The results were associated with 740,754 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and QTN-by-environment interactions (QEIs) using three-variance-component multi-locus random-SNP-effect mixed linear model (3VmrMLM). As a result, eight salt tolerance genes (GmCHX1, GsPRX9, Gm5PTase8, GmWRKY, GmCHX20a, GmNHX1, GmSK1, and GmLEA2-1) near 179 significant and 79 suggested QTNs and two salt tolerance genes (GmWRKY49 and GmSK1) near 45 significant and 14 suggested QEIs were associated with salt tolerance index traits in previous studies. Six candidate genes and three gene-by-environment interactions (GEIs) were predicted to be associated with these index traits. Analysis of four salt tolerance related traits under control and salt treatments revealed six genes associated with salt tolerance (GmHDA13, GmPHO1, GmERF5, GmNAC06, GmbZIP132, and GmHsp90s) around 166 QEIs were verified in previous studies. Five candidate GEIs were confirmed to be associated with salt stress by at least one haplotype analysis. The elite molecular modules of seven candidate genes with selection signs were extracted from wild soybean, and these genes could be applied to soybean molecular breeding. Two of these genes, Glyma06g04840 and Glyma07g18150, were confirmed by qRT-PCR and are expected to be key players in responding to salt stress.

CONCLUSIONS

Around the QTNs and QEIs identified in this study, 16 known genes, 6 candidate genes, and 8 candidate GEIs were found to be associated with soybean salt tolerance, of which Glyma07g18150 was further confirmed by qRT-PCR.

Salt Tolerance in Soybeans: Focus on Screening Methods and Genetics

Salinity greatly affects the production of soybeans in arid and semi-arid lands around the world. The responses of soybeans to salt stress at germination, emergence, and other seedling stages have been evaluated in multitudes of studies over the past decades. Considerable salt-tolerant accessions have been identified. The association between salt tolerance responses during early and later growth stages may not be as significant as expected. Genetic analysis has confirmed that salt tolerance is distinctly tied to specific soybean developmental stages. Our understanding of salt tolerance mechanisms in soybeans is increasing due to the identification of key salt tolerance genes. In this review, we focus on the methods of soybean salt tolerance screening, progress in forward genetics, potential mechanisms involved in salt tolerance, and the importance of translating laboratory findings into field experiments via marker-assisted pyramiding or genetic engineering approaches, and ultimately developing salt-tolerant soybean varieties that produce high and stable yields. Progress has been made in the past decades, and new technologies will help mine novel salt tolerance genes and translate the mechanism of salt tolerance into new varieties via effective routes.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

Genome-wide association and RNA-seq analyses reveal a potential gene related to linolenic acid in soybean seeds

Linolenic acid (LA) has poor oxidative stability since it is a polyunsaturated fatty acid. Soybean oil has a high LA content and thus has poor oxidative stability. To identify candidate genes that affect the linolenic acid (LA) content in soybean seeds, a genome-wide association study (GWAS) was performed with 1,060 soybean cultivars collected in China between 2019-2021 and which LA content was measured using matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS). A candidate gene, GmWRI14, encoding an APETALA2 (AP2)-type transcription factor, was detected by GWAS in cultivars from all three study years. Multiple sequence alignments showed that GmWRI14 belongs to the plant WRI1 family. The fatty acid contents of different soybean lines were evaluated in transgenic lines with a copy of GmWRI14, control lines without GmWRI14, and the gmwri14 mutant. MALDI-TOF IMS revealed that GmWRI14 transgenic soybeans had a lower LA content with a significant effect on seed size and shape, whereas gmwri14 mutants had a higher LA content. compared to control. The RNA-seq results showed that GmWRI14 suppresses GmFAD3s (GmFAD3B and GmFAD3C) and GmbZIP54 expression in soybean seeds, leading to decreased LA content. Based on the RNA-seq data, yeast one-hybrid (Y1H) and qRT-PCR were performed to confirm the transcriptional regulation of FAD3s by GmWRI14. Our results suggest that FAD3 is indirectly regulated by GmWRI14, representing a new molecular mechanism of fatty acid biosynthesis, in which GmWRI14 regulates LA content in soybean seeds.

A novel method for irrigating plants, tracking water use, and imposing water deficits in controlled environments

The study of genomic control of drought tolerance in crops requires techniques to impose well defined and consistent levels of drought stress and efficiently measure single-plant water use for hundreds of experimental units over timescales of several months. Traditional gravimetric methods are extremely labor intensive or require expensive technology, and are subject to other errors. This study demonstrates a low-cost, passive, bottom-watered system that is easily scaled for high-throughput phenotyping. The soil water content in the pots is controlled by altering the water table height in an underlying wicking bed via a float valve. The resulting soil moisture profile is then maintained passively as water withdrawn by the plant is replaced by upward movement of water from the wicking bed, which is fed from a reservoir via the float valve. The single-plant water use can be directly measured over time intervals from one to several days by observing the water level in the reservoir. Using this method, four different drought stress levels were induced in pots containing soybean (Glycine max (L.) Merr.), producing four statistically distinct groups for shoot dry weight and seed yield, as well as clear treatment effects for other relevant parameters, including root:shoot dry weight ratio, pod number, cumulative water use, and water use efficiency. This system has a broad range of applications, and should increase feasibility of high-throughput phenotyping efforts for plant drought tolerance traits.

Genome-wide analysis of cold imbibition stress in soybean, Glycine max

In Canada, the length of the frost-free season necessitates planting crops as early as possible to ensure that the plants have enough time to reach full maturity before they are harvested. Early planting carries inherent risks of cold water imbibition (specifically less than 4°C) affecting seed germination. A marker dataset developed for a previously identified Canadian soybean GWAS panel was leveraged to investigate the effect of cold water imbibition on germination. Seed from a panel of 137 soybean elite cultivars, grown in the field at Ottawa, ON, over three years, were placed on filter paper in petri dishes and allowed to imbibe water for 16 hours at either 4°C or 20°C prior to being transferred to a constant 20°C. Observations on seed germination, defined as the presence of a 1 cm radicle, were done from day two to seven. A three-parameter exponential rise to a maximum equation (3PERM) was fitted to estimate germination, time to the one-half maximum germination, and germination uniformity for each cultivar. Genotype-by-sequencing was used to identify SNPs in 137 soybean lines, and using genome-wide association studies (GWAS - rMVP R package, with GLM, MLM, and FarmCPU as methods), haplotype block analysis, and assumed linkage blocks of ±100 kbp, a threshold for significance was established using the qvalue package in R, and five significant SNPs were identified on chromosomes 1, 3, 4, 6, and 13 for maximum germination after cold water imbibition. Percent of phenotypic variance explained (PVE) and allele substitution effect (ASE) eliminated two of the five candidate SNPs, leaving three QTL regions on chromosomes 3, 6, and 13 (Chr3-3419152, Chr6-5098454, and Chr13-29649544). Based on the gene ontology (GO) enrichment analysis, 14 candidate genes whose function is predicted to include germination and cold tolerance related pathways were identified as candidate genes. The identified QTLs can be used to select future soybean cultivars tolerant to cold water imbibition and mitigate risks associated with early soybean planting.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Genome-wide association study of drought tolerance traits in sugar beet germplasms at the seedling stage

Introduction: Sugar beets are an important crop for global sugar production. Intense drought and the increasing lack of water resources pose a great threat to sugar beet cultivation. It is a priority to investigate favourable germplasms and functional genes to improve the breeding of drought tolerant plants. Methods: Thus, in this study, 328 sugar beet germplasms were used in a genome-wide association study (GWAS) to identify single nucleotide polymorphism (SNP) markers and candidate genes associated with drought tolerance. Results: The results showed that under drought stress (9% PEG-6000), there were 11 significantly associated loci on chromosomes 2, 3, 5, 7, and 9 from the 108946 SNPs filtered using a mixed linear model (MLM). Genome-wide association analysis combined with qRT-PCR identified 13 genes that were significantly differentially expressed in drought-tolerant extreme materials. Discussion: These candidate genes mainly exhibited functions such as regulating sugar metabolism, maintaining internal environmental stability and participating in photosystem repair. This study provides valuable information for exploring the molecular mechanisms of drought tolerance and improvement in sugar beet.

Insights into the Transcriptomics of Crop Wild Relatives to Unravel the Salinity Stress Adaptive Mechanisms

The narrow genomic diversity of modern cultivars is a major bottleneck for enhancing the crop's salinity stress tolerance. The close relatives of modern cultivated plants, crop wild relatives (CWRs), can be a promising and sustainable resource to broaden the diversity of crops. Advances in transcriptomic technologies have revealed the untapped genetic diversity of CWRs that represents a practical gene pool for improving the plant's adaptability to salt stress. Thus, the present study emphasizes the transcriptomics of CWRs for salinity stress tolerance. In this review, the impacts of salt stress on the plant's physiological processes and development are overviewed, and the transcription factors (TFs) regulation of salinity stress tolerance is investigated. In addition to the molecular regulation, a brief discussion on the phytomorphological adaptation of plants under saline environments is provided. The study further highlights the availability and use of transcriptomic resources of CWR and their contribution to pangenome construction. Moreover, the utilization of CWRs' genetic resources in the molecular breeding of crops for salinity stress tolerance is explored. Several studies have shown that cytoplasmic components such as calcium and kinases, and ion transporter genes such as Salt Overly Sensitive 1 (SOS1) and High-affinity Potassium Transporters (HKTs) are involved in the signaling of salt stress, and in mediating the distribution of excess Na⁺ ions within the plant cells. Recent comparative analyses of transcriptomic profiling through RNA sequencing (RNA-Seq) between the crops and their wild relatives have unraveled several TFs, stress-responsive genes, and regulatory proteins for generating salinity stress tolerance. This review specifies that the use of CWRs transcriptomics in combination with modern breeding experimental approaches such as genomic editing, de novo domestication, and speed breeding can accelerate the CWRs utilization in the breeding programs for enhancing the crop's adaptability to saline conditions. The transcriptomic approaches optimize the crop genomes with the accumulation of favorable alleles that will be indispensable for designing salt-resilient crops.

Genomic Dynamics and Functional Insights under Salt Stress in Gossypium hirsutum L

The changing climate is intensifying salt stress globally. Salt stress is a menace to cotton crop quality and yield. The seedling, germination, and emergence phases are more prone to the effects of salt stress than other stages. Higher levels of salt can lead to delayed flowering, a reduced number of fruiting positions, shedding of fruits, decreased boll weight, and yellowing of fiber, all of which have an adverse effect on the yield and quality of the seed cotton. However, sensitivity toward salt stress is dependent on the salt type, cotton growth phase, and genotype. As the threat of salt stress continues to grow, it is crucial to gain a comprehensive understanding of the mechanisms underlying salt tolerance in plants and to identify potential avenues for enhancing the salt tolerance of cotton. The emergence of marker-assisted selection, in conjunction with next-generation sequencing technologies, has streamlined cotton breeding efforts. This review begins by providing an overview of the causes of salt stress in cotton, as well as the underlying theory of salt tolerance. Subsequently, it summarizes the breeding methods that utilize marker-assisted selection, genomic selection, and techniques for identifying elite salt-tolerant markers in wild species or mutated materials. Finally, novel cotton breeding possibilities based on the approaches stated above are presented and debated.

Identification of hub genes regulating isoflavone accumulation in soybean seeds via GWAS and WGCNA approaches

INTRODUCTION

Isoflavones are the secondary metabolites synthesized by the phenylpropanoid biosynthesis pathway in soybean that benefits human and plant health.

METHODS

In this study, we have profiled seed isoflavone content by HPLC in 1551 soybean accessions grown in Beijing and Hainan for two consecutive years (2017 and 2018) and in Anhui for one year (2017).

RESULTS

A broad range of phenotypic variations was observed for individual and total isoflavone (TIF) content. The TIF content ranged from 677.25 to 5823.29 µg g^-1 in the soybean natural population. Using a genome-wide association study (GWAS) based on 6,149,599 single nucleotide polymorphisms (SNPs), we identified 11,704 SNPs significantly associated with isoflavone contents; 75% of them were located within previously reported QTL regions for isoflavone. Two significant regions on chromosomes 5 and 11 were associated with TIF and malonylglycitin across more than 3 environments. Furthermore, the WGCNA identified eight key modules: black, blue, brown, green, magenta, pink, purple, and turquoise. Of the eight co-expressed modules, brown (r = 0.68***), magenta (r = 0.64***), and green (r = 0.51**) showed a significant positive association with TIF, as well as with individual isoflavone contents. By combining the gene significance, functional annotation, and enrichment analysis information, four hub genes Glyma.11G108100, Glyma.11G107100, Glyma.11G106900, and Glyma.11G109100 encoding, basic-leucine zipper (bZIP) transcription factor, MYB4 transcription factor, early responsive to dehydration, and PLATZ transcription factor respectively were identified in brown and green modules. The allelic variation in Glyma.11G108100 significantly influenced individual and TIF accumulation.

DISCUSSION

The present study demonstrated that the GWAS approach, combined with WGCNA, could efficiently identify isoflavone candidate genes in the natural soybean population.

A genome-wide association study identifies novel players in Na and Fe homeostasis in Arabidopsis thaliana under alkaline-salinity stress

In nature, multiple stress factors occur simultaneously. The screening of natural diversity panels and subsequent Genome-Wide Association Studies (GWAS) is a powerful approach to identify genetic components of various stress responses. Here, the nutritional status variation of a set of 270 natural accessions of Arabidopsis thaliana grown on a natural saline-carbonated soil is evaluated. We report significant natural variation on leaf Na (LNa) and Fe (LFe) concentrations in the studied accessions. Allelic variation in the NINJA and YUC8 genes is associated with LNa diversity, and variation in the ALA3 is associated with LFe diversity. The allelic variation detected in these three genes leads to changes in their mRNA expression and correlates with plant differential growth performance when plants are exposed to alkaline salinity treatment under hydroponic conditions. We propose that YUC8 and NINJA expression patters regulate auxin and jasmonic signaling pathways affecting plant tolerance to alkaline salinity. Finally, we describe an impairment in growth and leaf Fe acquisition associated with differences in root expression of ALA3, encoding a phospholipid translocase active in plasma membrane and the trans Golgi network which directly interacts with proteins essential for the trafficking of PIN auxin transporters, reinforcing the role of phytohormonal processes in regulating ion homeostasis under alkaline salinity.

Identification of Drought-Tolerance Genes in the Germination Stage of Soybean

Drought stress influences the vigor of plant seeds and inhibits seed germination, making it one of the primary environmental factors adversely affecting food security. The seed germination stage is critical to ensuring the growth and productivity of soybeans in soils prone to drought conditions. We here examined the genetic diversity and drought-tolerance phenotypes of 410 accessions of a germplasm diversity panel for soybean and conducted quantitative genetics analyses to identify loci associated with drought tolerance of seed germination. We uncovered significant differences among the diverse genotypes for four growth indices and five drought-tolerance indices, which revealed abundant variation among genotypes, upon drought stress, and for genotype × treatment effects. We also used 158,327 SNP markers and performed GWAS for the drought-related traits. Our data met the conditions (PCA + K) for using a mixed linear model in TASSEL, and we thus identified 26 SNPs associated with drought tolerance indices for germination stage distributed across 10 chromosomes. Nine SNP sites, including, for example, Gm20_34956219 and Gm20_36902659, were associated with two or more phenotypic indices, and there were nine SNP markers located in or adjacent to (within 500 kb) previously reported drought tolerance QTLs. These SNPs led to our identification of 41 candidate genes related to drought tolerance in the germination stage. The results of our study contribute to a deeper understanding of the genetic mechanisms underlying drought tolerance in soybeans at the germination stage, thereby providing a molecular basis for identifying useful soybean germplasm for breeding new drought-tolerant varieties.

Identification of genomic regions associated with soybean responses to off-target dicamba exposure

The widespread adoption of genetically modified (GM) dicamba-tolerant (DT) soybean was followed by numerous reports of off-target dicamba damage and yield losses across most soybean-producing states. In this study, a subset of the USDA Soybean Germplasm Collection consisting of 382 genetically diverse soybean accessions originating from 15 countries was used to identify genomic regions associated with soybean response to off-target dicamba exposure. Accessions were genotyped with the SoySNP50K BeadChip and visually screened for damage in environments with prolonged exposure to off-target dicamba. Two models were implemented to detect significant marker-trait associations: the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) and a model that allows the inclusion of population structure in interaction with the environment (G×E) to account for variable patterns of genotype responses in different environments. Most accessions (84%) showed a moderate response, either moderately tolerant or moderately susceptible, with approximately 8% showing tolerance and susceptibility. No differences in off-target dicamba damage were observed across maturity groups and centers of origin. Both models identified significant associations in regions of chromosomes 10 and 19. The BLINK model identified additional significant marker-trait associations on chromosomes 11, 14, and 18, while the G×E model identified another significant marker-trait association on chromosome 15. The significant SNPs identified by both models are located within candidate genes possessing annotated functions involving different phases of herbicide detoxification in plants. These results entertain the possibility of developing non-GM soybean cultivars with improved tolerance to off-target dicamba exposure and potentially other synthetic auxin herbicides. Identification of genetic sources of tolerance and genomic regions conferring higher tolerance to off-target dicamba may sustain and improve the production of other non-DT herbicide soybean production systems, including the growing niche markets of organic and conventional soybean.

Molecular Tools and Their Applications in Developing Salt-Tolerant Soybean (Glycine max L.) Cultivars

Abiotic stresses are one of the significant threats to soybean (Glycine max L.) growth and yields worldwide. Soybean has a crucial role in the global food supply chain and food security and contributes the main protein share compared to other crops. Hence, there is a vast scientific saddle on soybean researchers to develop tolerant genotypes to meet the growing need of food for the huge population. A large portion of cultivated land is damaged by salinity stress, and the situation worsens yearly. In past years, many attempts have increased soybean resilience to salinity stress. Different molecular techniques such as quantitative trait loci mapping (QTL), genetic engineering, transcriptome, transcription factor analysis (TFs), CRISPR/Cas9, as well as other conventional methods are used for the breeding of salt-tolerant cultivars of soybean to safeguard its yield under changing environments. These powerful genetic tools ensure sustainable soybean yields, preserving genetic variability for future use. Only a few reports about a detailed overview of soybean salinity tolerance have been published. Therefore, this review focuses on a detailed overview of several molecular techniques for soybean salinity tolerance and draws a future research direction. Thus, the updated review will provide complete guidelines for researchers working on the genetic mechanism of salinity tolerance in soybean.

Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

Identifying the genetic components underlying yield-related traits in soybean is crucial for improving its production and productivity. Here, 211 soybean genotypes were evaluated across six environments for four yield-related traits, including seed yield per plant (SYP), number of pods per plant number of seeds per plant and 100-seed weight (HSW). Genome-wide association study (GWAS) and genomic prediction (GP) analyses were performed using 12,617 single nucleotide polymorphism markers from NJAU 355K SoySNP Array. A total of 57 SNPs were significantly associated with four traits across six environments and a combined environment using five Genome-wide association study models. Out of these, six significant SNPs were consistently identified in more than three environments using multiple GWAS models. The genomic regions (±670 kb) flanking these six consistent SNPs were considered stable QTL regions. Gene annotation and in silico expression analysis revealed 15 putative genes underlying the stable QTLs that might regulate soybean yield. Haplotype analysis using six significant SNPs revealed various allelic combinations regulating diverse phenotypes for the studied traits. Furthermore, the GP analysis revealed that accurate breeding values for the studied soybean traits is attainable at an earlier generation. Our study paved the way for increasing soybean yield performance within a short breeding cycle.

Genome-Wide Association Study of Salt Tolerance at the Seed Germination Stage in Flax (Linum usitatissimum L.)

Soil salinization seriously affects the growth and distribution of flax. However, there is little information about the salt tolerance of flax. In this study, the salt tolerance of 200 diverse flax accessions during the germination stage was evaluated, and then the Genome-wide Association Study (GWAS) was carried out based on the relative germination rate (RGR), relative shoot length (RSL) and relative root length (RRL), whereby quantitative trait loci (QTLs) related to salt tolerance were identified. The results showed that oil flax had a better salt tolerance than fiber flax. A total of 902 single nucleotide polymorphisms (SNPs) were identified on 15 chromosomes. These SNPs were integrated into 64 QTLs, explaining 14.48 to 29.38% (R²) of the phenotypic variation. In addition, 268 candidate genes were screened by combining previous transcriptome data and homologous gene annotation. Among them, Lus10033213 is a single-point SNP repeat mapping gene, which encodes a Glutathione S-transferase (GST). This study is the first to use GWAS to excavate genes related to salt tolerance during the germination stage of flax. The results of this study provide important information for studying the genetic mechanism of salt tolerance of flax, and also provide the possibility to improve the salt tolerance of flax.

Genetic architecture of salt tolerance in a Multi-Parent Advanced Generation Inter-Cross (MAGIC) cowpea population

Background

Previous reports have shown that soil salinity is a growing threat to cowpea production, and thus the need for breeding salt-tolerant cowpea cultivars. A total of 234 Multi-Parent Advanced Generation Inter-Cross (MAGIC) lines along with their 8 founders were evaluated for salt tolerance under greenhouse conditions. The objectives of this study were to evaluate salt tolerance in a multi-parent advanced generation inter-cross (MAGIC) cowpea population, to identify single nucleotide polymorphism (SNP) markers associated with salt tolerance, and to assess the accuracy of genomic selection (GS) in predicting salt tolerance, and to explore possible epistatic interactions affecting salt tolerance in cowpea. Phenotyping was validated through the use of salt-tolerant and salt-susceptible controls that were previously reported. Genome-wide association study (GWAS) was conducted using a total of 32,047 filtered SNPs. The epistatic interaction analysis was conducted using the PLINK platform.

Results

Results indicated that: (1) large variation in traits evaluated for salt tolerance was identified among the MAGIC lines, (2) a total of 7, 2, 18, 18, 3, 2, 5, 1, and 23 were associated with number of dead plants, salt injury score, leaf SPAD chlorophyll under salt treatment, relative tolerance index for leaf SPAD chlorophyll, fresh leaf biomass under salt treatment, relative tolerance index for fresh leaf biomass, relative tolerance index for fresh stem biomass, relative tolerance index for the total above-ground fresh biomass, and relative tolerance index for plant height, respectively, with overlapping SNP markers between traits, (3) candidate genes encoding for proteins involved in ion transport such as Na+/Ca2+ K+ independent exchanger and H+/oligopeptide symporter were identified, and (4) epistatic interactions were identified.

Conclusions

These results will have direct applications in breeding programs aiming at improving salt tolerance in cowpea through marker-assisted selection. To the best of our knowledge, this study was one of the earliest reports using a MAGIC population to investigate the genetic architecture of salt tolerance in cowpea.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08332-y.

Genome-Wide Association Study Identifies Candidate Genes Related to the Linoleic Acid Content in Soybean Seeds

Soybean (Glycine max (L.) Merrill) oil is a complex mixture of five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic). The high content of linoleic acid (LA) contributes to the oil having poor oxidative stability. Therefore, soybean seed with a lower LA content is desirable. To investigate the genetic architecture of LA, we performed a genome-wide association study (GWAS) using 510 soybean cultivars collected from China. The phenotypic identification results showed that the content of LA varied from 36.22% to 72.18%. The GWAS analysis showed that there were 37 genes related to oleic acid content, with a contribution rate of 7%. The candidate gene Glyma.04G116500.1 (GmWRI14) on chromosome 4 was detected in three consecutive years. The GmWRI14 showed a negative correlation with the LA content and the correlation coefficient was -0.912. To test whether GmWRI14 can lead to a lower LA content in soybean, we introduced GmWRI14 into the soybean genome. Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS) showed that the overexpression of GmWRI14 leads to a lower LA content in soybean seeds. Meanwhile, RNA-seq verified that GmWRI14-overexpressed soybean lines showed a lower accumulation of GmFAD2-1A and GmFAD2-1B than control lines. Our results indicate that the down-regulation of the FAD2 gene triggered by the transcription factor GmWRI14 is the underlying mechanism reducing the LA level of seed. Our results provide novel insights into the genetic architecture of LA and pinpoint potential candidate genes for further in-depth studies.

Novel QTL identification and candidate gene analysis for enhancing salt tolerance in soybean (Glycine max (L.) Merr.)

Soybean, a glycophyte that is sensitive to salt stress, is greatly affected by salinity at all growth stages. A mapping population derived from a cross between a salt-sensitive Korean cultivar, Cheongja 3, and a salt-tolerant landrace, IT162669, was used to identify quantitative trait loci (QTLs) conferring salt tolerance in soybean. Following treatment with 120 mM NaCl for 2 weeks, phenotypic traits representing physiological damage, leaf Na+ content, and K+/Na+ ratio were characterized. Among the QTLs mapped on a high-density genetic map harboring 2,630 single nucleotide polymorphism markers, we found two novel major loci, qST6, on chromosome 6, and qST10, on chromosome 10, which controlled traits related to ion toxicity and physiology in response to salinity, respectively. These loci were distinct from the previously known salt tolerance allele on chromosome 3. Other QTLs associated with abiotic stress overlapped with the genomic regions of qST6 and qST10, or with their paralogous regions. Based on the functional annotation and parental expression differences, we identified eight putative candidate genes, two in qST6 and six in qST10, which included a phosphoenolpyruvate carboxylase and an ethylene response factor. This study provides additional genetic resources to breed soybean cultivars with enhanced salt tolerance.

Identification of a Novel Salt Tolerance-Related Locus in Wild Soybean (Glycine soja Sieb. & Zucc.)

Salinity is an important abiotic stress factor that affects growth and yield of soybean. NY36-87 is a wild soybean germplasm with high salt tolerance. In this study, two F_2:3 mapping populations derived from NY36-87 and two salt-sensitive soybean cultivars, Zhonghuang39 and Peking, were used to map salt tolerance-related genes. The two populations segregated as 1 (tolerant):2 (heterozygous):1 (sensitive), indicating a Mendelian segregation model. Using simple sequence repeat (SSR) markers together with the bulked segregant analysis (BSA) mapping strategy, we mapped a salt tolerance locus on chromosome 03 in F_2:3 population Zhonghuang39×NY36-87 to a 98-kb interval, in which the known gene GmSALT3 co-segregated with the salt tolerance locus. In the F_2:3 population of Peking×NY36-87, the dominant salt tolerance-associated gene was detected and mapped on chromosome 18. We named this gene GmSALT18 and fine mapped it to a 241-kb region. Time course analysis and a grafting experiment confirmed that Peking accumulated more Na⁺ in the shoot via a root-based mechanism. These findings reveal that the tolerant wild soybean line NY36-87 contains salt tolerance-related genes GmSALT3 and GmSALT18, providing genetic material and a novel locus for breeding salt-tolerant soybean.

Selection of the Salt Tolerance Gene GmSALT3 During Six Decades of Soybean Breeding in China

Salt tolerance is an important trait that affects the growth and yield of plants growing in saline environments. The salt tolerance gene GmSALT3 was cloned from the Chinese soybean cultivar Tiefeng 8, and its variation evaluated in Chinese wild soybeans and landraces. However, the potential role of GmSALT3 in cultivation, and its genetic variation throughout the history of Chinese soybean breeding, remains unknown. Here we identified five haplotypes of GmSALT3 in 279 Chinese soybean landraces using a whole genome resequencing dataset. Additionally, we developed five PCR-based functional markers: three indels and two cleaved amplified polymorphic sequences (CAPS) markers. A total of 706 Chinese soybean cultivars (released 1956-2012), and 536 modern Chinese breeding lines, were genotyped with these markers. The Chinese landraces exhibited relatively high frequencies of the haplotypes H1, H4, and H5. H1 was the predominant haplotype in both the northern region (NR) and Huanghuai region (HHR), and H5 and H4 were the major haplotypes present within the southern region (SR). In the 706 cultivars, H1, H2, and H5 were the common haplotypes, while H3 and H4 were poorly represented. Historically, H1 gradually decreased in frequency in the NR but increased in the HHR; while the salt-sensitive haplotype, H2, increased in frequency in the NR during six decades of soybean breeding. In the 536 modern breeding lines, H2 has become the most common haplotype in the NR, while H1 has remained the highest frequency haplotype in the HHR, and H5 and H1 were highest in the SR. Frequency changes resulting in geographically favored haplotypes indicates that strong selection has occurred over six decades of soybean breeding. Our molecular markers could precisely identify salt tolerant (98.9%) and sensitive (100%) accessions and could accurately trace the salt tolerance gene in soybean pedigrees. Our study, therefore, not only identified effective molecular markers for use in soybean, but also demonstrated how these markers can distinguish GmSALT3 alleles in targeted breeding strategies for specific ecoregions.

A review of biotechnological approaches towards crop improvement in African yam bean (Sphenostylis stenocarpa Hochst. Ex A. Rich.)

Globally, climate change is a major factor that contributes significantly to food and nutrition insecurity, limiting crop yield and availability. Although efforts are being made to curb food insecurity, millions of people still suffer from malnutrition. For the United Nations (UN) Sustainable Development Goal of Food Security to be achieved, diverse cropping systems must be developed instead of relying mainly on a few staple crops. Many orphan legumes have untapped potential that can be of significance for developing improved cultivars with enhanced tolerance to changing climatic conditions. One typical example of such an orphan crop is Sphenostylis stenocarpa Hochst. Ex A. Rich. Harms, popularly known as African yam bean (AYB). The crop is an underutilised tropical legume that is climate-resilient and has excellent potential for smallholder agriculture in sub-Saharan Africa (SSA). Studies on AYB have featured morphological characterisation, assessment of genetic diversity using various molecular markers, and the development of tissue culture protocols for rapidly multiplying propagules. However, these have not translated into varietal development, and low yields remain a challenge. The application of suitable biotechnologies to improve AYB is imperative for increased yield, sustainable utilisation and conservation. This review discusses biotechnological strategies with prospective applications for AYB improvement. The potential risks of these strategies are also highlighted.

Meta-GWAS for quantitative trait loci identification in soybean

We report a meta-Genome Wide Association Study involving 73 published studies in soybean [Glycine max L. (Merr.)] covering 17,556 unique accessions, with improved statistical power for robust detection of loci associated with a broad range of traits. De novo GWAS and meta-analysis were conducted for composition traits including fatty acid and amino acid composition traits, disease resistance traits, and agronomic traits including seed yield, plant height, stem lodging, seed weight, seed mottling, seed quality, flowering timing, and pod shattering. To examine differences in detectability and test statistical power between single- and multi-environment GWAS, comparison of meta-GWAS results to those from the constituent experiments were performed. Using meta-GWAS analysis and the analysis of individual studies, we report 483 peaks at 393 unique loci. Using stringent criteria to detect significant marker-trait associations, 59 candidate genes were identified, including 17 agronomic traits loci, 19 for seed-related traits, and 33 for disease reaction traits. This study identified potentially valuable candidate genes that affect multiple traits. The success in narrowing down the genomic region for some loci through overlapping mapping results of multiple studies is a promising avenue for community-based studies and plant breeding applications.

Application of Genomics to Understand Salt Tolerance in Lentil

Soil salinity is a major abiotic stress, limiting lentil productivity worldwide. Understanding the genetic basis of salt tolerance is vital to develop tolerant varieties. A diversity panel consisting of 276 lentil accessions was screened in a previous study through traditional and image-based approaches to quantify growth under salt stress. Genotyping was performed using two contrasting methods, targeted (tGBS) and transcriptome (GBS-t) genotyping-by-sequencing, to evaluate the most appropriate methodology. tGBS revealed the highest number of single-base variants (SNPs) (c. 56,349), and markers were more evenly distributed across the genome compared to GBS-t. A genome-wide association study (GWAS) was conducted using a mixed linear model. Significant marker-trait associations were observed on Chromosome 2 as well as Chromosome 4, and a range of candidate genes was identified from the reference genome, the most plausible being potassium transporters, which are known to be involved in salt tolerance in related species. Detailed mineral composition performed on salt-treated and control plant tissues revealed the salt tolerance mechanism in lentil, in which tolerant accessions do not transport Na⁺ ions around the plant instead localize within the root tissues. The pedigree analysis identified two parental accessions that could have been the key sources of tolerance in this dataset.

Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS

Background

The number of panicles per plant, number of grains per panicle, and 1000-grain weight are important factors contributing to the grain yield per plant in rice. The Rice Diversity Panel 1 (RDP1) contains a total of 421 purified, homozygous rice accessions representing diverse genetic variations within O. sativa. The release of High-Density Rice Array (HDRA, 700 k SNPs) dataset provides a new opportunity to discover the genetic variants of panicle architectures in rice.

Results

In this report, a new method genome-phenome wide association study (GPWAS) was performed with 391 individuals and 27 traits derived from RDP1 to scan the relationship between the genes and multi-traits. A total of 1985 gene models were linked to phenomic variation with a p-value cutoff of 4.49E-18. Besides, 406 accessions derived from RDP1 with 411,066 SNPs were used to identify QTLs associated with the total spikelets number per panicle (TSNP), grain number per panicle (GNP), empty grain number per panicle (EGNP), primary branch number (PBN), panicle length (PL), and panicle number per plant (PN) by GLM, MLM, FarmCPU, and BLINK models for genome-wide association study (GWAS) analyses. A total of 18, 21, 18, 17, 15, and 17 QTLs were identified tightly linked with TSNP, GNP, EGNP, PBN, PL, and PN, respectively. Then, a total of 23 candidate genes were mapped simultaneously using both GWAS and GPWAS methods, composed of 6, 4, 5, 4, and 4 for TSNP, GNP, EGNP, PBN, and PL. Notably, one overlapped gene (Os01g0140100) were further investigated based on the haplotype and gene expression profile, indicating this gene might regulate the TSNP or panicle architecture in rice.

Conclusions

Nearly 30 % (30/106) QTLs co-located with the previous published genes or QTLs, indicating the power of GWAS. Besides, GPWAS is a new method to discover the relationship between genes and traits, especially the pleiotropy genes. Through comparing the results from GWAS and GPWAS, we identified 23 candidate genes related to panicle architectures in rice. This comprehensive study provides new insights into the genetic basis controlling panicle architectures in rice, which lays a foundation in rice improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07391-x.

Genome-Wide Association Study of Root and Shoot Related Traits in Spring Soybean (Glycine max L.) at Seedling Stages Using SLAF-Seq

Root systems can display variable genetic architectures leading to nutrient foraging or improving abiotic stress tolerance. Breeding for new soybean varieties with efficient root systems has tremendous potential in enhancing resource use efficiency and plant adaptation for challenging climates. In this study, root related traits were analyzed in a panel of 260 spring soybean with genome-wide association study (GWAS). Genotyping was done with specific locus amplified fragment sequencing (SLAF-seq), and five GWAS models (GLM, MLM, CMLM, FaST-LMM, and EMMAX) were used for analysis. A total of 179,960 highly consistent SNP markers distributed over the entire genome with an inter-marker distance of 2.36 kb was used for GWAS analysis. Overall, 27 significant SNPs with a phenotypic contribution ranging from 20 to 72% and distributed on chromosomes 2, 6, 8, 9, 13, 16 and 18 were identified and two of them were found to be associated with multiple root-related traits. Based on the linkage disequilibrium (LD) distance of 9.5 kb for the different chromosomes, 11 root and shoot regulating genes were detected based on LD region of a maximum 55-bp and phenotypic contribution greater than 22%. Expression analysis revealed an association between expression levels of those genes and the degree of root branching number. The current study provides new insights into the genetic architecture of soybean roots, and the underlying SNPs/genes could be critical for future breeding of high-efficient root system in soybean.

Genome-Wide Association Analysis Coupled With Transcriptome Analysis Reveals Candidate Genes Related to Salt Stress in Alfalfa (Medicago sativa L.)

Salt stress is the main abiotic factor affecting alfalfa yield and quality. However, knowledge of the genetic basis of the salt stress response in alfalfa is still limited. Here, a genome-wide association study (GWAS) involving 875,023 single-nucleotide polymorphisms (SNPs) was conducted on 220 alfalfa varieties under both normal and salt-stress conditions. Phenotypic analysis showed that breeding status and geographical origin play important roles in the alfalfa salt stress response. For germination ability under salt stress, a total of 15 significant SNPs explaining 9%-14% of the phenotypic variation were identified. For tolerance to salt stress in the seedling stage, a total of 18 significant SNPs explaining 12%-23% of the phenotypic variation were identified. Transcriptome analysis revealed 2,097 and 812 differentially expressed genes (DEGs) that were upregulated and 2,445 and 928 DEGs that were downregulated in the leaves and roots, respectively, under salt stress. Among these DEGs, many encoding transcription factors (TFs) were found, including MYB-, CBF-, NAC-, and bZIP-encoding genes. Combining the results of our GWAS analysis and transcriptome analysis, we identified a total of eight candidate genes (five candidate genes for tolerance to salt stress and three candidate genes for germination ability under salt stress). Two SNPs located within the upstream region of MsAUX28, which encodes an auxin response protein, were significantly associated with tolerance to salt stress. The two significant SNPs within the upstream region of MsAUX28 existed as three different haplotypes in this panel. Hap 1 (G/G, A/A) was under selection in the alfalfa domestication and improvement process.

Soybean BARCSoySNP6K: An assay for soybean genetics and breeding research

The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000-2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.

Identification of Genes Conferring Plant Salt Tolerance using GWAS: Current Success and Perspectives

An understanding of the molecular mechanisms that underlie plant salt tolerance is important for both economic and scientific interests. Genome-wide association study (GWAS) is a promising approach to pinpoint genes that confer plant salt tolerance. With the advancement of supporting technology and methodology, GWAS has enabled the discovery of genes that play central roles in regulating plant salt tolerance in the past decade. Here, I highlight recent successful GWAS work in unveiling the molecular factors underlying plant salt tolerance and discuss the concerns and opportunities in conducting such experiments. It is anticipated that GWAS will be increasingly successful in the identification of key genes that are useful for crop improvement.

Genome-Wide Association Analyses Reveal Genomic Regions Controlling Canopy Wilting in Soybean

Drought stress causes the greatest soybean [Glycine max (L.) Merr.] yield losses among the abiotic stresses in rain-fed U.S. growing areas. Because less than 10% of U.S. soybean hectares are irrigated, combating this stress requires soybean plants which possess physiological mechanisms to tolerate drought for a period of time. Phenotyping for these mechanisms is challenging, and the genetic architecture for these traits is poorly understood. A morphological trait, slow or delayed canopy wilting, has been observed in a few exotic plant introductions (PIs), and may lead to yield improvement in drought stressed fields. In this study, we visually scored wilting during stress for a panel of 162 genetically diverse maturity group VI-VIII soybean lines genotyped with the SoySNP50K iSelect BeadChip. Field evaluation of canopy wilting was conducted under rain-fed conditions at two locations (Athens, GA and Salina, KS) in 2015 and 2016. Substantial variation in canopy wilting was observed among the genotypes. Using a genome-wide association mapping approach, 45 unique SNPs that tagged 44 loci were associated with canopy wilting in at least one environment with one region identified in a single environment and data from across all environments. Several new soybean accessions were identified with canopy wilting superior to those of check genotypes. The germplasm and genomic regions identified can be used to better understand the slow canopy wilting trait and be incorporated into elite germplasm to improve drought tolerance in soybean.

The Soybean Gene J Contributes to Salt Stress Tolerance by Up-Regulating Salt-Responsive Genes

Soybean [Glycine max (L.) Merr.] is an important crop for oil and protein resources worldwide, and its farming is impacted by increasing soil salinity levels. In Arabidopsis the gene EARLY FLOWERING 3 (ELF3), increased salt tolerance by suppressing salt stress response pathways. J is the ortholog of AtELF3 in soybean, and loss-of-function J-alleles greatly prolong soybean maturity and enhance grain yield. The exact role of J in abiotic stress response in soybean, however, remains unclear. In this study, we showed that J expression was induced by NaCl treatment and that the J protein was located in the nucleus. Compared to NIL-J, tolerance to NaCl was significantly lower in the NIL-j mutant. We also demonstrated that overexpression of J increased NaCl tolerance in transgenic soybean hairy roots. J positively regulated expression of downstream salt stress response genes, including GmWRKY12, GmWRKY27, GmWRKY54, GmNAC, and GmSIN1. Our study disclosed a mechanism in soybean for regulation of the salt stress response. Manipulation of these genes should facilitate improvements in salt tolerance in soybean.

Unraveling the genetic architecture for carbon and nitrogen related traits and leaf hydraulic conductance in soybean using genome-wide association analyses

BACKGROUND

Drought stress is a major limiting factor of soybean [Glycine max (L.) Merr.] production around the world. Soybean plants can ameliorate this stress with improved water-saving, sustained N2 fixation during water deficits, and/or limited leaf hydraulic conductance. In this study, carbon isotope composition (δ13C), which can relate to variation in water-saving capability, was measured. Additionally, nitrogen isotope composition (δ15N) and nitrogen concentration that relate to nitrogen fixation were evaluated. Decrease in transpiration rate (DTR) of de-rooted soybean shoots in a silver nitrate (AgNO3) solution compared to deionized water under high vapor pressure deficit (VPD) conditions was used as a surrogate measurement for limited leaf hydraulic conductance. A panel of over 200 genetically diverse soybean accessions genotyped with the SoySNP50K iSelect BeadChips was evaluated for the carbon and nitrogen related traits in two field environments (Athens, GA in 2015 and 2016) and for transpiration response to AgNO3 in a growth chamber. A multiple loci linear mixed model was implemented in FarmCPU to perform genome-wide association analyses for these traits.

RESULTS

Thirty two, 23, 26, and nine loci for δ13C, δ15N, nitrogen concentration, and transpiration response to AgNO3, respectively, were significantly associated with these traits. Candidate genes that relate to drought stress tolerance enhancement or response were identified near certain loci that could be targets for improving and understanding these traits. Soybean accessions with favorable breeding values were also identified. Low correlations were observed between many of the traits and the genetic loci associated with each trait were largely unique, indicating that these drought tolerance related traits are governed by different genetic loci.

CONCLUSIONS

The genomic regions and germplasm identified in this study can be used by breeders to understand the genetic architecture for these traits and to improve soybean drought tolerance. Phenotyping resources needed, trait heritability, and relationship to the target environment should be considered before deciding which of these traits to ultimately employ in a specific breeding program. Potential marker-assisted selection efforts could focus on loci which explain the greatest amount of phenotypic variation for each trait, but may be challenging due to the quantitative nature of these traits.

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.

Genome-wide association analysis of salinity responsive traits in Medicago truncatula

Salinity stress is an important cause of crop yield loss in many parts of the world. Here, we performed genome-wide association studies of salinity-stress responsive traits in 132 HapMap genotypes of the model legume Medicago truncatula. Plants grown in soil were subjected to a step-wise increase in NaCl concentration, from 0 through 0.5% and 1.0% to 1.5%, and the following traits were measured: vigor, shoot biomass, shoot water content, leaf chlorophyll content, leaf size, and leaf and root concentrations of proline and major ions (Na+ , Cl- , K+ , Ca2+ , etc.). Genome-wide association studies were carried out using 2.5 million single nucleotide polymorphisms, and 12 genomic regions associated with at least four traits each were identified. Transcript-level analysis of the top eight candidate genes in five extreme genotypes revealed association between salinity tolerance and transcript-level changes for seven of the genes, encoding a vacuolar H+ -ATPase, two transcription factors, two proteins involved in vesicle trafficking, one peroxidase, and a protein of unknown function. Earlier functional studies on putative orthologues of two of the top eight genes (a vacuolar H+ -ATPase and a peroxidase) demonstrated their involvement in plant salinity tolerance.

Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping

BACKGROUND

Salinity is an abiotic stress that negatively affects soybean [Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900, on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC).

RESULTS

For both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset.

CONCLUSIONS

A region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs.

Salinity stress response and 'omics' approaches for improving salinity stress tolerance in major grain legumes

Sustaining yield gains of grain legume crops under growing salt-stressed conditions demands a thorough understanding of plant salinity response and more efficient breeding techniques that effectively integrate modern omics knowledge. Grain legume crops are important to global food security being an affordable source of dietary protein and essential mineral nutrients to human population, especially in the developing countries. The global productivity of grain legume crops is severely challenged by the salinity stress particularly in the face of changing climates coupled with injudicious use of irrigation water and improper agricultural land management. Plants adapt to sustain under salinity-challenged conditions through evoking complex molecular mechanisms. Elucidating the underlying complex mechanisms remains pivotal to our knowledge about plant salinity response. Improving salinity tolerance of plants demand enriching cultivated gene pool of grain legume crops through capitalizing on 'adaptive traits' that contribute to salinity stress tolerance. Here, we review the current progress in understanding the genetic makeup of salinity tolerance and highlight the role of germplasm resources and omics advances in improving salt tolerance of grain legumes. In parallel, scope of next generation phenotyping platforms that efficiently bridge the phenotyping-genotyping gap and latest research advances including epigenetics is also discussed in context to salt stress tolerance. Breeding salt-tolerant cultivars of grain legumes will require an integrated "omics-assisted" approach enabling accelerated improvement of salt-tolerance traits in crop breeding programs.

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.

Salt stress under the scalpel - dissecting the genetics of salt tolerance

Salt stress limits the productivity of crops grown under saline conditions, leading to substantial losses of yield in saline soils and under brackish and saline irrigation. Salt tolerant crops could alleviate these losses while both increasing irrigation opportunities and reducing agricultural demands on dwindling freshwater resources. However, despite significant efforts, progress towards this goal has been limited, largely because of the genetic complexity of salt tolerance for agronomically important yield-related traits. Consequently, the focus is shifting to the study of traits that contribute to overall tolerance, thus breaking down salt tolerance into components that are more genetically tractable. Greater consideration of the plasticity of salt tolerance mechanisms throughout development and across environmental conditions furthers this dissection. The demand for more sophisticated and comprehensive methodologies is being met by parallel advances in high-throughput phenotyping and sequencing technologies that are enabling the multivariate characterisation of vast germplasm resources. Alongside steady improvements in statistical genetics models, forward genetics approaches for elucidating salt tolerance mechanisms are gaining momentum. Subsequent quantitative trait locus and gene validation has also become more accessible, most recently through advanced techniques in molecular biology and genomic analysis, facilitating the translation of findings to the field. Besides fuelling the improvement of established crop species, this progress also facilitates the domestication of naturally salt tolerant orphan crops. Taken together, these advances herald a promising era of discovery for research into the genetics of salt tolerance in plants.

A cation diffusion facilitator, GmCDF1, negatively regulates salt tolerance in soybean

Salt stress is one of the major abiotic factors that affect the metabolism, growth and development of plants, and soybean [Glycine max (L.) Merr.] germination is sensitive to salt stress. Thus, to ensure the successful establishment and productivity of soybeans in saline soil, the genetic mechanisms of salt tolerance at the soybean germination stage need to be explored. In this study, a population of 184 recombinant inbred lines (RILs) was utilized to map quantitative trait loci (QTLs) related to salt tolerance. A major QTL related to salt tolerance at the soybean germination stage named qST-8 was closely linked with the marker Sat_162 and detected on chromosome 8. Interestingly, a genome-wide association study (GWAS) identified several single nucleotide polymorphisms (SNPs) significantly associated with salt tolerance in the same genetic region on chromosome 8. Resequencing, bioinformatics and gene expression analyses were implemented to identify the candidate gene Glyma.08g102000, which belongs to the cation diffusion facilitator (CDF) family and was named GmCDF1. Overexpression and RNA interference of GmCDF1 in soybean hairy roots resulted in increased sensitivity and tolerance to salt stress, respectively. This report provides the first demonstration that GmCDF1 negatively regulates salt tolerance by maintaining K+-Na+ homeostasis in soybean. In addition, GmCDF1 affected the expression of two ion homeostasis-associated genes, salt overly sensitive 1 (GmSOS1) and Na+/H+ exchanger 1 (GmNHX1), in transgenic hairy roots. Moreover, a haplotype analysis detected ten haplotypes of GmCDF1 in 31 soybean genotypes. A candidate-gene association analysis showed that two SNPs in GmCDF1 were significantly associated with salt tolerance and that Hap1 was more sensitive to salt stress than Hap2. The results demonstrated that the expression level of GmCDF1 was negatively correlated with salt tolerance in the 31 soybean accessions (r = -0.56, P < 0.01). Taken together, these results not only indicate that GmCDF1 plays a negative role in soybean salt tolerance but also help elucidate the molecular mechanisms of salt tolerance and accelerate the breeding of salt-tolerant soybean.

A Case of Need: Linking Traits to Genebank Accessions

Genebanks are responsible for collecting, maintaining, characterizing, documenting, and distributing plant genetic resources for research, education, and breeding purposes. The rationale for requests of plant materials varies highly from areas of anthropology, social science, small-holder farmers, the commercial sector, rehabilitation of degraded systems, all the way to crop improvement and basic research. Matching "the right" accessions to a particular request is not always a straightforward process especially when genetic resource collections are large and the user does not already know which accession or even which species they want to study. Some requestors have limited knowledge of the crop; therefore, they do not know where to begin and thus, initiate the search by consultation with crop curators to help direct their request to the most suitable germplasm. One way to enhance the use of genebank material and aid in the selection of genetic resources is to have thoroughly cataloged agronomic, biochemical, genomic, and other traits linked to genebank accessions. In general, traits of importance to most users include genotypes that thrive under various biotic and abiotic stresses, morphological traits (color, shape, size of fruits), plant architecture, disease resistance, nutrient content, yield, and crop specific quality traits. In this review, we discuss methods for linking traits to genebank accessions, examples of linked traits, and some of the complexities involved, while reinforcing why it is critical to have well characterized accessions with clear trait data publicly available.

GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.

GWAS Uncovers Differential Genetic Bases for Drought and Salt Tolerances in Sesame at the Germination Stage

Sesame has great potential as an industrial crop but its production is challenged by drought and salt stresses. To unravel the genetic variants leading to salinity and drought tolerances at the germination stage, genome-wide association studies of stress tolerance indexes related to NaCl-salt and polyethylene glycol-drought induced stresses were performed with a diversity panel of 490 sesame accessions. An extensive variation was observed for drought and salt responses in the population and most of the accessions were moderately tolerant to both stresses. A total of 132 and 120 significant Single Nucleotide Polymorphisms (SNPs) resolved to nine and 15 Quantitative trait loci (QTLs) were detected for drought and salt stresses, respectively. Only two common QTLs for drought and salt responses were found located on linkage groups 5 and 7, respectively. This indicates that the genetic bases for drought and salt responses in sesame are different. A total of 13 and 27 potential candidate genes were uncovered for drought and salt tolerance indexes, respectively, encoding transcription factors, antioxidative enzymes, osmoprotectants and involved in hormonal biosynthesis, signal transduction or ion sequestration. The identified SNPs and potential candidate genes represent valuable resources for future functional characterization towards the enhancement of sesame cultivars for drought and salt tolerances.