Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality.
This is the first report on association analysis of salt tolerance and identification of SNP markers associated with salt tolerance in cowpea. Cowpea (Vigna unguiculata (L.) Walp) is one of the most important cultivated legumes in Africa. The worldwide annual production in cowpea dry seed is 5.4 million metric tons. However, cowpea is unfavorably affected by salinity stress at germination and seedling stages, which is exacerbated by the effects of climate change. The lack of knowledge on the genetic underlying salt tolerance in cowpea limits the establishment of a breeding strategy for developing salt-tolerant cowpea cultivars. The objectives of this study were to conduct association mapping for salt tolerance at germination and seedling stages and to identify SNP markers associated with salt tolerance in cowpea. We analyzed the salt tolerance index of 116 and 155 cowpea accessions at germination and seedling stages, respectively. A total of 1049 SNPs postulated from genotyping-by-sequencing were used for association analysis. Population structure was inferred using Structure 2.3.4; K optimal was determined using Structure Harvester. TASSEL 5, GAPIT, and FarmCPU involving three models such as single marker regression, general linear model, and mixed linear model were used for the association study. Substantial variation in salt tolerance index for germination rate, plant height reduction, fresh and dry shoot biomass reduction, foliar leaf injury, and inhibition of the first trifoliate leaf was observed. The cowpea accessions were structured into two subpopulations. Three SNPs, Scaffold87490_622, Scaffold87490_630, and C35017374_128 were highly associated with salt tolerance at germination stage. Seven SNPs, Scaffold93827_270, Scaffold68489_600, Scaffold87490_633, Scaffold87490_640, Scaffold82042_3387, C35069468_1916, and Scaffold93942_1089 were found to be associated with salt tolerance at seedling stage. The SNP markers were consistent across the three models and could be used as a tool to select salt-tolerant lines for breeding improved cowpea tolerance to salinity.
Cowpea is a nutrient-dense legume that significantly contributes to the population’s diet in sub-Saharan Africa and other regions of the world. Improving cowpea cultivars to be more resilient to abiotic stress such as drought would be of great importance. The use of a multi-parent advanced generation intercross (MAGIC) population has been shown to be efficient in increasing the frequency of rare alleles that could be associated with important agricultural traits. In addition, drought tolerance index has been reported to be a reliable parameter for assessing crop tolerance to water-deficit conditions. Therefore, the objectives of this study were to evaluate the drought tolerance index for plant growth habit, plant maturity, flowering time, 100-seed weight, and grain yield in a MAGIC cowpea population, to conduct genome-wide association study (GWAS) and identify single nucleotide polymorphism (SNP) markers associated with the drought tolerance indices, to investigate the potential relationship existing between the significant loci associated with the drought tolerance indices, and to conduct genomic selection (GS). These analyses were performed using the existing phenotypic and genotypic data published for the MAGIC population which consisted of 305 F8 recombinant inbred lines (RILs) developed at University of California, Riverside. The results indicated that: (1) large variation in drought tolerance indices existed among the cowpea genotypes, (2) a total of 14, 18, 5, 5, and 35 SNPs were associated with plant growth habit change due to drought stress, and drought tolerance indices for maturity, flowering time, 100-seed weight, and grain yield, respectively, (3) the network-guided approach revealed clear interactions between the loci associated with the drought tolerance traits, and (4) the GS accuracy varied from low to moderate. These results could be applied to improve drought tolerance in cowpea through marker-assisted selection (MAS) and genomic selection (GS). To the best of our knowledge, this is the first report on marker loci associated with drought tolerance indices in cowpea.
BackgroundSoybean cyst nematode (SCN), Heterodera glycines Ichinohe, has been one of the most devastating pathogens affecting soybean production. In the United States alone, SCN damage accounted for more than $1 billion loss annually. With a narrow genetic background of the currently available SCN-resistant commercial cultivars, high risk of resistance breakdown can occur. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify QTL, SNP markers, and candidate genes associated with soybean leaf chlorophyll content tolerance to SCN infection, and to carry out a genomic selection (GS) study for the chlorophyll content tolerance.ResultsA total of 172 soybean genotypes were evaluated for the effect of SCN HG Type 1.2.3.5.6.7 (race 4) on soybean leaf chlorophyll. The soybean lines were genotyped using a total of 4089 filtered and high-quality SNPs. Results showed that (1) a large variation in SCN tolerance based on leaf chlorophyll content indices (CCI); (2) a total of 22, 14, and 16 SNPs associated with CCI of non-SCN-infected plants, SCN-infected plants, and reduction of CCI SCN, respectively; (3) a new locus of chlorophyll content tolerance to SCN mapped on chromosome 3; (4) candidate genes encoding for Leucine-rich repeat protein, plant hormone signaling molecules, and biomolecule transporters; and (5) an average GS accuracy ranging from 0.31 to 0.46 with all SNPs and varying from 0.55 to 0.76 when GWAS-derived SNP markers were used across five models. This study demonstrated the potential of using genome-wide selection to breed chlorophyll-content-tolerant soybean for managing SCN.ConclusionsIn this study, soybean accessions with higher CCI under SCN infestation, and molecular markers associated with chlorophyll content related to SCN were identified. In addition, a total of 15 candidate genes associated with chlorophyll content tolerance to SCN in soybean were also identified. These candidate genes will lead to a better understanding of the molecular mechanisms that control chlorophyll content tolerance to SCN in soybean. Genomic selection analysis of chlorophyll content tolerance to SCN showed that using significant SNPs obtained from GWAS could provide better GS accuracy.
Spinach (Spinacia oleracea L., 2n = 2x = 12) is an economically important vegetable crop worldwide and one of the healthiest vegetables due to its high concentrations of nutrients and minerals. The objective of this research was to conduct genetic diversity and population structure analysis of a collection of world-wide spinach genotypes using single nucleotide polymorphisms (SNPs) markers. Genotyping by sequencing (GBS) was used to discover SNPs in spinach genotypes. Three sets of spinach genotypes were used: 1) 268 USDA GRIN spinach germplasm accessions originally collected from 30 countries; 2) 45 commercial spinach F1 hybrids from three countries; and 3) 30 US Arkansas spinach cultivars/breeding lines. The results from this study indicated that there was genetic diversity among the 343 spinach genotypes tested. Furthermore, the genetic background in improved commercial F1 hybrids and in Arkansas cultivars/lines had a different structured populations from the USDA germplasm. In addition, the genetic diversity and population structures were associated with geographic origin and germplasm from the US Arkansas breeding program had a unique genetic background. These data could provide genetic diversity information and the molecular markers for selecting parents in spinach breeding programs.
Soybean cyst nematode (SCN), Heterodera glycines Ichinohe, is one of the most devastating pathogens affecting soybean production in the U.S. and worldwide. The use of SCNresistant soybean cultivars is one of the most affordable strategies to cope with SCN infestation. Because of the limited sources of SCN resistance and changes in SCN virulence phenotypes, host resistance in current cultivars has increasingly been overcome by the pathogen. Host tolerance has been recognized as an additional tool to manage the SCN. The objectives of this study were to conduct a genome-wide association study (GWAS), to identify single nucleotide polymorphism (SNP) markers, and to perform a genomic selection (GS) study for SCN tolerance in soybean based on reduction in biomass. A total of 234 soybean genotypes (lines) were evaluated for their tolerance to SCN in greenhouse using four replicates. The tolerance index (TI = 100 × Biomass of a line in SCN infested / Biomass of the line without SCN) was used as phenotypic data of SCN tolerance. GWAS was conducted using a total of 3,782 high quality SNPs. GS was performed based upon the whole set of SNPs and the GWASderived SNPs, respectively. Results showed that (1) a large variation in soybean TI to SCN infection among the soybean genotypes was identified; (2) a total of 35, 21, and 6 SNPs were found to be associated with SCN tolerance using the models SMR, GLM (PCA), and MLM (PCA+K) with 6 SNPs overlapping between models; (3) GS accuracy was SNP set-, model-, and training population size-dependent; and (4) genes around Glyma.
BackgroundSpinach is a useful source of dietary vitamins and mineral elements. Breeding new spinach cultivars with high nutritional value is one of the main goals in spinach breeding programs worldwide, and identification of single nucleotide polymorphism (SNP) markers for mineral element concentrations is necessary to support spinach molecular breeding. The purpose of this study was to conduct a genome-wide association study (GWAS) and to identify SNP markers associated with mineral elements in the USDA-GRIN spinach germplasm collection.ResultsA total of 14 mineral elements: boron (B), calcium (Ca), cobalt (Co), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn), molybdenum (Mo), sodium (Na), nickel (Ni), phosphorus (P), sulfur (S), and zinc (Zn) were evaluated in 292 spinach accessions originally collected from 29 countries. Significant genetic variations were found among the tested genotypes as evidenced by the 2 to 42 times difference in mineral concentrations. A total of 2402 SNPs identified from genotyping by sequencing (GBS) approach were used for genetic diversity and GWAS. Six statistical methods were used for association analysis. Forty-five SNP markers were identified to be strongly associated with the concentrations of 13 mineral elements. Only two weakly associated SNP markers were associated with K concentration. Co-localized SNPs for different elemental concentrations were discovered in this research. Three SNP markers, AYZV02017731_40, AYZV02094133_57, and AYZV02281036_185 were identified to be associated with concentrations of four mineral components, Co, Mn, S, and Zn. There is a high validating correlation coefficient with r > 0.7 among concentrations of the four elements. Thirty-one spinach accessions, which rank in the top three highest concentrations in each of the 14 mineral elements, were identified as potential parents for spinach breeding programs in the future.ConclusionsThe 45 SNP markers strongly associated with the concentrations of the 13 mineral elements: B, Ca, Co, Cu, Fe, Mg, Mn, Mo, Na, Ni, P, S, and Zn could be used in breeding programs to improve the nutritional quality of spinach through marker-assisted selection (MAS). The 31 spinach accessions with high concentrations of one to several mineral elements can be used as potential parents for spinach breeding programs. Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4297-y) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.