Genetic Dissection of Diverse Seed Coat Patterns in Cowpea through a Comprehensive GWAS Approach.

This study investigates the genetic determinants of seed coat color and pattern variations in cowpea (Vigna unguiculata), employing a genome-wide association approach. Analyzing a mapping panel of 296 cowpea varieties with 110,000 single nucleotide polymorphisms (SNPs), we focused on eight unique coat patterns: (1) Red and (2) Cream seed; (3) White and (4) Brown/Tan seed coat; (5) Pink, (6) Black, (7) Browneye and (8) Red/Brown Holstein. Across six GWAS models (GLM, SRM, MLM, MLMM, FarmCPU from GAPIT3, and TASSEL5), 13 significant SNP markers were identified and led to the discovery of 23 candidate genes. Among these, four specific genes may play a direct role in determining seed coat pigment. These findings lay a foundational basis for future breeding programs aimed at creating cowpea varieties aligned with consumer preferences and market requirements.

Genetic Architecture of Salt Tolerance in Cowpea (Vigna unguiculata (L.) Walp.) at Seedling Stage Using a Whole Genome Resequencing Approach.

Cowpea (Vigna unguiculata (L.) Walp.) is a diploid legume crop used for human consumption, feed for livestock, and cover crops. Earlier reports have shown that salinity has been a growing threat to cowpea cultivation. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify SNP markers and to investigate candidate genes for salt tolerance in cowpea. A total of 331 cowpea genotypes were evaluated for salt tolerance by supplying a solution of 200 mM NaCl in our previous work. The cowpea panel was genotyped using a whole genome resequencing approach, generating 14,465,516 SNPs. Moreover, 5,884,299 SNPs were used after SNP filtering. GWAS was conducted on a total of 296 cowpea genotypes that have high-quality SNPs. BLINK was used for conducting GWAS. Results showed (1) a strong GWAS peak on an 890-bk region of chromosome 2 for leaf SPAD chlorophyll under salt stress in cowpea and harboring a significant cluster of nicotinamide adenine dinucleotide (NAD) dependent epimerase/dehydratase genes such as Vigun02g128900.1, Vigun02g129000.1, Vigun02g129100.1, Vigun02g129200.1, and Vigun02g129500.1; (2) two GWAS peaks associated with relative tolerance index for chlorophyll were identified on chromosomes 1 and 2. The peak on chromosome 1 was defined by a cluster of 10 significant SNPs mapped on a 5 kb region and was located in the vicinity of Vigun01g086000.1, encoding for a GATA transcription factor. The GWAS peak on chromosome 2 was defined by a cluster of 53 significant SNPs and mapped on a 68 bk region of chromosome 2, and (3) the highest GWAS peak was identified on chromosome 3, and this locus was associated with leaf score injury. This peak was within the structure of a potassium channel gene (Vigun03g144700.1). To the best of our knowledge, this is one the earliest reports on the salt tolerance study of cowpea using whole genome resequencing data.

Genome-Wide Association Study and Genomic Prediction of Fusarium Wilt Resistance in Common Bean Core Collection.

The common bean (Phaseolus vulgaris L.) is a globally cultivated leguminous crop. Fusarium wilt (FW), caused by Fusarium oxysporum f. sp. phaseoli (Fop), is a significant disease leading to substantial yield loss in common beans. Disease-resistant cultivars are recommended to counteract this. The objective of this investigation was to identify single nucleotide polymorphism (SNP) markers associated with FW resistance and to pinpoint potential resistant common bean accessions within a core collection, utilizing a panel of 157 accessions through the Genome-wide association study (GWAS) approach with TASSEL 5 and GAPIT 3. Phenotypes for Fop race 1 and race 4 were matched with genotypic data from 4740 SNPs of BARCBean6K_3 Infinium Bea Chips. After ranking the 157-accession panel and revealing 21 Fusarium wilt-resistant accessions, the GWAS pinpointed 16 SNPs on chromosomes Pv04, Pv05, Pv07, Pv8, and Pv09 linked to Fop race 1 resistance, 23 SNPs on chromosomes Pv03, Pv04, Pv05, Pv07, Pv09, Pv10, and Pv11 associated with Fop race 4 resistance, and 7 SNPs on chromosomes Pv04 and Pv09 correlated with both Fop race 1 and race 4 resistances. Furthermore, within a 30 kb flanking region of these associated SNPs, a total of 17 candidate genes were identified. Some of these genes were annotated as classical disease resistance protein/enzymes, including NB-ARC domain proteins, Leucine-rich repeat protein kinase family proteins, zinc finger family proteins, P-loopcontaining nucleoside triphosphate hydrolase superfamily, etc. Genomic prediction (GP) accuracy for Fop race resistances ranged from 0.26 to 0.55. This study advanced common bean genetic enhancement through marker-assisted selection (MAS) and genomic selection (GS) strategies, paving the way for improved Fop resistance.

A Genome-Wide Association Study Reveals Region Associated with Seed Protein Content in Cowpea.

Cowpea (Vigna unguiculata L. Walp., 2n = 2x = 22) is a protein-rich crop that complements staple cereals for humans and serves as fodder for livestock. It is widely grown in Africa and other developing countries as the primary source of protein in the diet; therefore, it is necessary to identify the protein-related loci to improve cowpea breeding. In the current study, we conducted a genome-wide association study (GWAS) on 161 cowpea accessions (151 USDA germplasm plus 10 Arkansas breeding lines) with a wide range of seed protein contents (21.8~28.9%) with 110,155 high-quality whole-genome single-nucleotide polymorphisms (SNPs) to identify markers associated with protein content, then performed genomic prediction (GP) for future breeding. A total of seven significant SNP markers were identified using five GWAS models (single-marker regression (SMR), the general linear model (GLM), Mixed Linear Model (MLM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), which are located at the same locus on chromosome 8 for seed protein content. This locus was associated with the gene Vigun08g039200, which was annotated as the protein of the thioredoxin superfamily, playing a critical function for protein content increase and nutritional quality improvement. In this study, a genomic prediction (GP) approach was employed to assess the accuracy of predicting seed protein content in cowpea. The GP was conducted using cross-prediction with five models, namely ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL), applied to seven random whole genome marker sets with different densities (10 k, 5 k, 2 k, 1 k, 500, 200, and 7), as well as significant markers identified through GWAS. The accuracies of the GP varied between 42.9% and 52.1% across the seven SNPs considered, depending on the model used. These findings not only have the potential to expedite the breeding cycle through early prediction of individual performance prior to phenotyping, but also offer practical implications for cowpea breeding programs striving to enhance seed protein content and nutritional quality.

A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean.

Soybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to identify the markers associated with SBR resistance by 30,314 high quality single nucleotide polymorphism (SNPs). Then five genomic selection (GS) models, including Ridge regression best linear unbiased predictor (rrBLUP), Genomic best linear unbiased predictor (gBLUP), Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), Random Forest (RF), and Support vector machines (SVM), were used to predict breeding values of SBR resistance using whole genome SNP sets and GWAS-based marker sets. Four SNPs, namely Gm18_57,223,391 (LOD = 2.69), Gm16_29,491,946 (LOD = 3.86), Gm06_45,035,185 (LOD = 4.74), and Gm18_51,994,200 (LOD = 3.60), were located near the reported P. pachyrhizi R genes, Rpp1, Rpp2, Rpp3, and Rpp4, respectively. Other significant SNPs, including Gm02_7,235,181 (LOD = 7.91), Gm02_7234594 (LOD = 7.61), Gm03_38,913,029 (LOD = 6.85), Gm04_46,003,059 (LOD = 6.03), Gm09_1,951,644 (LOD = 10.07), Gm10_39,142,024 (LOD = 7.12), Gm12_28,136,735 (LOD = 7.03), Gm13_16,350,701(LOD = 5.63), Gm14_6,185,611 (LOD = 5.51), and Gm19_44,734,953 (LOD = 6.02), were associated with abundant disease resistance genes, such as Glyma.02G084100, Glyma.03G175300, Glyma.04g189500, Glyma.09G023800, Glyma.12G160400, Glyma.13G064500, Glyma.14g073300, and Glyma.19G190200. The annotations of these genes included but not limited to: LRR class gene, cytochrome 450, cell wall structure, RCC1, NAC, ABC transporter, F-box domain, etc. The GWAS based markers showed more accuracies in genomic prediction than the whole genome SNPs, and Bayesian LASSO model was the ideal model in SBR resistance prediction with 44.5% ~ 60.4% accuracies. This study aids breeders in predicting selection accuracy of complex traits such as disease resistance and can shorten the soybean breeding cycle by the identified markers.

A Genome-Wide Association Study and Genomic Prediction for Fiber and Sucrose Contents in a Mapping Population of LCP 85-384 Sugarcane.

Sugarcane (Saccharum spp. hybrids) is an economically important crop for both sugar and biofuel industries. Fiber and sucrose contents are the two most critical quantitative traits in sugarcane breeding that require multiple-year and multiple-location evaluations. Marker-assisted selection (MAS) could significantly reduce the time and cost of developing new sugarcane varieties. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify DNA markers associated with fiber and sucrose contents and to perform genomic prediction (GP) for the two traits. Fiber and sucrose data were collected from 237 self-pollinated progenies of LCP 85-384, the most popular Louisiana sugarcane cultivar from 1999 to 2007. The GWAS was performed using 1310 polymorphic DNA marker alleles with three models of TASSEL 5, single marker regression (SMR), general linear model (GLM) and mixed linear model (MLM), and the fixed and random model circulating probability unification (FarmCPU) of R package. The results showed that 13 and 9 markers were associated with fiber and sucrose contents, respectively. The GP was performed by cross-prediction with five models, ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB) and Bayesian least absolute shrinkage and selection operator (BL). The accuracy of GP varied from 55.8% to 58.9% for fiber content and 54.6% to 57.2% for sucrose content. Upon validation, these markers can be applied in MAS and genomic selection (GS) to select superior sugarcane with good fiber and high sucrose contents.

Genome-wide association study and genomic prediction of white rust resistance in USDA GRIN spinach germplasm.

White rust, caused by Albugo occidentalis, is one of the major yield-limiting diseases of spinach (Spinacia oleracea) in some major commercial production areas, particularly in southern Texas in the United States. The use of host resistance is the most economical and environment-friendly approach to managing white rust in spinach production. The objectives of this study were to conduct a genome-wide associating study (GWAS), to identify single nucleotide polymorphism (SNP) markers associated with white rust resistance in spinach, and to perform genomic prediction (GP) to estimate the prediction accuracy (PA). A GWAS panel of 346 USDA (US Dept. of Agriculture) germplasm accessions was phenotyped for white rust resistance under field conditions and GWAS was performed using 13 235 whole-genome resequencing (WGR) generated SNPs. Nine SNPs, chr2_53 049 132, chr3_58 479 501, chr3_95 114 909, chr4_9 176 069, chr4_17 807 168, chr4_83 938 338, chr4_87 601 768, chr6_1 877 096, and chr6_31 287 118, located on chromosomes 2, 3, 4, and 6 were associated with white rust resistance in this GWAS panel. Four scenarios were tested for PA using Pearson's correlation coefficient (r) between the genomic estimation breeding value (GEBV) and the observed values: (1) different ratios between the training set and testing set (fold), (2) different GP models, (3) different SNP numbers in three different SNP sets, and (4) the use of GWAS-derived significant SNP markers. The results indicated that a 2- to 10-fold difference in the various GP models had similar, although not identical, averaged r values in each SNP set; using GWAS-derived significant SNP markers would increase PA with a high r-value up to 0.84. The SNP markers and the high PA can provide valuable information for breeders to improve spinach by marker-assisted selection (MAS) and genomic selection (GS).

Genome-Wide Association Study and Genomic Prediction for Bacterial Wilt Resistance in Common Bean (Phaseolus vulgaris) Core Collection.

Common bean (Phaseolus vulgaris) is one of the major legume crops cultivated worldwide. Bacterial wilt (BW) of common bean (Curtobacterium flaccumfaciens pv. flaccumfaciens), being a seed-borne disease, has been a challenge in common bean producing regions. A genome-wide association study (GWAS) was conducted to identify SNP markers associated with BW resistance in the USDA common bean core collection. A total of 168 accessions were evaluated for resistance against three different isolates of BW. Our study identified a total of 14 single nucleotide polymorphism (SNP) markers associated with the resistance to BW isolates 528, 557, and 597 using mixed linear models (MLMs) in BLINK, FarmCPU, GAPIT, and TASSEL 5. These SNPs were located on chromosomes Phaseolus vulgaris [Pv]02, Pv04, Pv08, and Pv09 for isolate 528; Pv07, Pv10, and Pv11 for isolate 557; and Pv04, Pv08, and Pv10 for isolate 597. The genomic prediction accuracy was assessed by utilizing seven GP models with 1) all the 4,568 SNPs and 2) the 14 SNP markers. The overall prediction accuracy (PA) ranged from 0.30 to 0.56 for resistance against the three BW isolates. A total of 14 candidate genes were discovered for BW resistance located on chromosomes Pv02, Pv04, Pv07, Pv08, and Pv09. This study revealed vital information for developing genetic resistance against the BW pathogen in common bean. Accordingly, the identified SNP markers and candidate genes can be utilized in common bean molecular breeding programs to develop novel resistant cultivars.

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.

Genome-Wide Association Study and Genomic Prediction for Soybean Cyst Nematode Resistance in USDA Common Bean (Phaseolus vulgaris) Core Collection.

Soybean cyst nematode (SCN, Heterodera glycines) has become the major yield-limiting biological factor in soybean production. Common bean is also a good host of SCN, and its production is challenged by this emerging pest in many regions such as the upper Midwest USA. The use of host genetic resistance has been the most effective and environmentally friendly method to manage SCN. The objectives of this study were to evaluate the SCN resistance in the USDA common bean core collection and conduct a genome-wide association study (GWAS) of single nucleotide polymorphism (SNP) markers with SCN resistance. A total of 315 accessions of the USDA common bean core collection were evaluated for resistance to SCN HG Type 0 (race 6). The common bean core set was genotyped with the BARCBean6K_3 Infinium BeadChips, consisting of 4,654 SNPs. Results showed that 15 accessions were resistant to SCN with a Female Index (FI) at 4.8 to 9.4, and 62 accessions were moderately resistant (10 < FI < 30) to HG Type 0. The association study showed that 11 SNP markers, located on chromosomes Pv04, 07, 09, and 11, were strongly associated with resistance to HG Type 0. GWAS was also conducted for resistance to HG Type 2.5.7 and HG Type 1.2.3.5.6.7 based on the public dataset (N = 276), consisting of a diverse set of common bean accessions genotyped with the BARCBean6K_3 chip. Six SNPs associated with HG Type 2.5.7 resistance on Pv 01, 02, 03, and 07, and 12 SNPs with HG Type 1.2.3.5.6.7 resistance on Pv 01, 03, 06, 07, 09, 10, and 11 were detected. The accuracy of genomic prediction (GP) was 0.36 to 0.49 for resistance to the three SCN HG types, indicating that genomic selection (GS) of SCN resistance is feasible. This study provides basic information for developing SCN-resistant common bean cultivars, using the USDA core germ plasm accessions. The SNP markers can be used in molecular breeding in common beans through marker-assisted selection (MAS) and GS.

Physicochemical characterizations of starches isolated from Tetrastigma hemsleyanum Diels et Gilg.

Physicochemical characteristics of starch isolated from Tetrastigma hemsleyanum Diels et Gilg (T. hemsleyanum) tuber root of 4 different origins were firstly analyzed in this study. The starch granules of T. hemsleyanum tuber root were oval or globular, showed unimodal distribution with average size of 21.66-28.79 µm. T. hemsleyanum starch had typical B-type diffraction pattern. T. hemsleyanum root was rich in starch, and apparent amylose content ranged from 39.82% to 47.67%. The amylopectin chain profiles showed that over 50% of the total detectable chains had degree of polymerization (DP) with 13-24. T. hemsleyanum tuber root had high RS content, which reached up to 61.44% in flour and 68.81% in isolated starch. After cooking, the RS content decreased, but was still high up to 7.52% in flour and 9.93% in isolated starch. The peak gelatinization temperature of T. hemsleyanum starch ranged from 68.12 to 74.42 °C. The peak viscosity of T. hemsleyanum flour and starch ranged from 778 to 1258 cP and 1577 to 2009 cP respectively. The results indicate that T. hemsleyanum is a potential source for novel starch with high resistant starch and provide some guides for comprehensive utilization of T. hemsleyanum starch in food and pharmaceuticals industry.

Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20.

Sweet potato [Ipomoea batatas (L.) Lam.] (2n = 6x = 90) is an economic important autopolyploid species and its varieties differ regarding storage root skin and flesh colors. Two sweet potato genetic lines, Sushu8 (with red skin) and its mutant Zhengshu20, which produced different colored storage roots, were used in this study. The total flavonoid, carotenoid, and anthocyanin contents of the two lines were analyzed and revealed that anthocyanin was primarily responsible for the skin color difference. In addition, the early storage root expanding stage was the key period for anthocyanin accumulation in Sushu8. A total of 24 samples, including the skins of the fibrous root and the storage root at the early and middle expanding stages as well as the flesh of the storage root at the middle expanding stage, were analyzed based on differentially expressed genes identified by transcriptome sequencing and a weighted gene co-expression network analysis. Two gene modules highly related with the regulation of sweet potato skin color through stress responses as well as starch synthesis and glucose metabolism were identified. Furthermore, the WRKY75 transcription factor gene, fructose-bisphosphate aldolase 2 gene, and other DEGs highly related to the regulation of anthocyanin metabolism were enriched in the brown and green modules.

Genetic Diversity and Population Structure of Cowpea (Vigna unguiculata L. Walp).

The genetic diversity of cowpea was analyzed, and the population structure was estimated in a diverse set of 768 cultivated cowpea genotypes from the USDA GRIN cowpea collection, originally collected from 56 countries. Genotyping by sequencing was used to discover single nucleotide polymorphism (SNP) in cowpea and the identified SNP alleles were used to estimate the level of genetic diversity, population structure, and phylogenetic relationships. The aim of this study was to detect the gene pool structure of cowpea and to determine its relationship between different regions and countries. Based on the model-based ancestry analysis, the phylogenetic tree, and the principal component analysis, three well-differentiated genetic populations were postulated from 768 worldwide cowpea genotypes. According to the phylogenetic analyses between each individual, region, and country, we may trace the accession from off-original, back to the two candidate original areas (West and East of Africa) to predict the migration and domestication history during the cowpea dispersal and development. To our knowledge, this is the first report of the analysis of the genetic variation and relationship between globally cultivated cowpea genotypes. The results will help curators, researchers, and breeders to understand, utilize, conserve, and manage the collection for more efficient contribution to international cowpea research.