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Abstract The APETALA2/ETHYLENE RESPONSIVE FACTOR (AP2/ERF) gene family plays vital roles in plants, serving as a key regulator in responses to abiotic stresses. Despite its significance, a comprehensive understanding of this family in lettuce remains incomplete. In this study, we performed a genome-wide search for the AP2/ERF family in lettuce and identified a total of 224 members. The duplication patterns provided evidence that both tandem and segmental duplications contributed to the expansion of this family. Ka/Ks ratio analysis demonstrated that, following duplication events, the genes have been subjected to purifying selection pressure, leading to selective constraints on their protein sequence. This selective pressure provides a dosage benefit against stresses in plants. Additionally, a transcriptome analysis indicated that some duplicated genes gained novel functions, emphasizing the contribution of both dosage effect and functional divergence to the family functionalities. Furthermore, an orthologous relationship study showed that 60% of genes descended from a common ancestor of Rosid and Asterid lineages, 28% from the Asterid ancestor, and 12% evolved in the lettuce lineage, suggesting lineage-specific roles in adaptive evolution. These results provide valuable insights into the evolutionary mechanisms of the AP2/ERF gene family in lettuce, with implications for enhancing abiotic stress tolerance, ultimately contributing to the genetic improvement of lettuce crop production.

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.

Genomic selection (GS) is a marker-based selection method used to improve the genetic gain of quantitative traits in plant breeding. A large number of breeding datasets are available in the soybean database, and the application of these public datasets in GS will improve breeding efficiency and reduce time and cost. However, the most important problem to be solved is how to improve the ability of across-population prediction. The objectives of this study were to perform genomic prediction (GP) and estimate the prediction ability (PA) for seed oil and protein contents in soybean using available public datasets to predict breeding populations in current, ongoing breeding programs. In this study, six public datasets of USDA GRIN soybean germplasm accessions with available phenotypic data of seed oil and protein contents from different experimental populations and their genotypic data of single-nucleotide polymorphisms (SNPs) were used to perform GP and to predict a bi-parent-derived breeding population in our experiment. The average PA was 0.55 and 0.50 for seed oil and protein contents within the bi-parents population according to the within-population prediction; and 0.45 for oil and 0.39 for protein content when the six USDA populations were combined and employed as training sets to predict the bi-parent-derived population. The results showed that four USDA-cultivated populations can be used as a training set individually or combined to predict oil and protein contents in GS when using 800 or more USDA germplasm accessions as a training set. The smaller the genetic distance between training population and testing population, the higher the PA. The PA increased as the population size increased. In across-population prediction, no significant difference was observed in PA for oil and protein content among different models. The PA increased as the SNP number increased until a marker set consisted of 10,000 SNPs. This study provides reasonable suggestions and methods for breeders to utilize public datasets for GS. It will aid breeders in developing GS-assisted breeding strategies to develop elite soybean cultivars with high oil and protein contents.

The tomato is one of the most important vegetable crops grown worldwide. Tomato brown rugose fruit virus (ToBRFV), a seed-borne tobamovirus, poses a serious threat to tomato production due to its ability to break the resistant genes (Tm-1, Tm-2, Tm-22) in tomatoes. The objective of this work was to identify new resistant source(s) of tomato germplasm against ToBRFV. To achieve this aim, a total of 476 accessions from 12 Solanum species were tested with the ToBRFV US isolate for their resistance and susceptibility. As a result, a total of 44 asymptomatic accessions were identified as resistant/tolerant, including thirty-one accessions of S. pimpinellifolium, one accession of S. corneliomulleri, four accessions of S. habrochaites, three accessions of S. peruvianum, and five accessions of S. subsection lycopersicon hybrid. Further analyses using serological tests identified four highly resistant S. pimpinellifolium lines, PI 390713, PI 390714, PI 390716, and PI 390717. The inheritance of resistance in the selected lines was verified in the next generation and confirmed using RT-qPCR. To our knowledge, this is a first report of high resistance to ToBRFV in S. pimpinellifolium. These new genetic resources will expand the genetic pool available for breeders to develop new resistant cultivars of tomato against ToBRFV.

Bacterial wilt (BW), caused by Ralstonia solanacearum, is one of the devastating diseases in tomatoes (Solanum lycopersicum L.). The use of resistant cultivars and breeding for genetic resistance is the most effective, economical, and environmentally friendly management strategy for this disease. It is necessary to screen diverse germplasm and cultivated genotypes to identify resistant resources and to develop resistant cultivars in tomatoes to combat the changing pathogen isolates. This study evaluated 40 United States Department of Agriculture (USDA) tomato accessions for their BW resistance to the R. solanacearum isolate P822 under greenhouse conditions. The tomato plants were inoculated and visually assessed to observe their symptoms, and the disease severity was scored on a scale of 0 to 4 (0 = no leaf wilted, 1 = 25% of leaves wilted, 2 = 50% leaves wilted, 3 = 75% of leaves wilted, and 4 = 100% leaves wilted). Five accessions (PI 645370, PI 647306, PI 600993, PI 355110, and PI 270210) were observed as BW resistance, with PI 645370 showing the greatest resistance. The broad-sense heritability for BW resistance was estimated as 59.9% and 42.8% based on a 0–4 scale of disease incidence and the disease severity index, respectively. Two distinct clusters (sub-populations) were detected among 39 of the 40 accessions. The five identified BW-resistant accessions were distributed in both clusters, suggesting a likely difference in the genetic base among the five resistance accessions. The resistant accessions will contribute significantly to the tomato breeding program to develop new cultivars with BW resistance.

Drought, a crucial abiotic stressor, markedly reduces the growth and yield of tomato crops (Solanum lycopersicum L.). Consequently, adopting drought-resistant cultivars and implementing breeding programs to enhance drought tolerance have emerged as enduring solutions to alleviate the adverse effects of drought in various tomato cultivation regions. In this study, 68 United States Department of Agriculture (USDA) tomato accessions were assessed in a controlled greenhouse experiment, encompassing both water deficit treatment and a control group subjected to standard watering conditions. The experiment was arranged in a randomized complete block design with three replications. The results of this study pinpointed four accessions, PI 365956, PI 584456, PI 390510, and PI 370091, as drought-tolerant accessions. Additionally, high broad-sense heritability was revealed for leaf wilting, leaf rolling, and SPAD chlorophyll content (total leaf chlorophyll). Furthermore, positive correlations were found among parameters associated with leaf wilting, leaf rolling, and SPAD chlorophyll content. The findings offer valuable insights for tomato breeding initiatives, especially those focused on enhancing drought tolerance in elite cultivars. Future studies will expand the evaluation to include a larger pool of tomato accessions and conduct a genome-wide association study to identify single nucleotide polymorphism (SNP) markers for molecular breeding in tomatoes.

Abstract Efficient partitioning of above and below-ground biomass in response to nitrogen (N) is critical to the productivity of plants under sub-optimal conditions. It is particularly essential in vegetable crops like spinach with shallow root systems, a short growth cycle, and poor nitrogen use efficiency. In this study, we conducted a genome-wide association study (GWAS) to explore N-induced changes using spinach accessions with diverse genetic backgrounds. We evaluated phenotypic variations as percent changes in the shoot and root biomass in response to N using 201 spinach accessions grown in randomized complete blocks design in a soilless media under a controlled environment. A GWAS was performed for the percent changes in the shoot and root biomass in response to N in the 201 spinach accessions using 60,940 whole-genome resequencing generated SNPs. Three SNP markers, chr4_28292655, chr6_1531056, and chr6_37966006 on chromosomes 4 and 6, were significantly associated with %change in root weight, and two SNP markers, chr2_18480277 and chr4_47598760 on chromosomes 2 and 4, were significantly associated with % change shoot weight. The outcome of this study established a foundation for genetic studies needed to improve the partitioning of total biomass and provided a resource to identify molecular markers to enhance N uptake via marker-assisted selection or genomic selection in spinach breeding programs.

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

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.

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.

Abstract Large amounts of nitrogen fertilizers applied during lettuce (Lactuca sativa L.) production are lost due to leaching or volatilization, causing severe environmental pollution and increased costs of production. Developing lettuce varieties with high nitrogen use efficiency (NUE) is the eco-friendly solution to reduce nitrogen pollution. Hence, in-depth knowledge of nitrogen metabolism and assimilation genes and their regulation is critical for developing high NUE varieties. In this study, we performed comparative transcriptomic analysis of the cultivated lettuce (L. sativa L.) and its wild progenitor (L. serriola) under high and low nitrogen conditions. A total of 2,704 differentially expressed genes were identified. Key enriched biological processes included photosynthesis, oxidation–reduction process, chlorophyll biosynthetic process, and cell redox homeostasis. The transcription factors (TFs) belonging to the ethylene responsive factor family and basic helix-loop-helix family were among the top differentially expressed TFs. Using weighted gene co-expression network analysis we constructed nine co-expression modules. Among these, two modules were further investigated because of their significant association with total nitrogen content and photosynthetic efficiency of photosystem II. Three highly correlated clusters were identified which included hub genes for nitrogen metabolism, secondary metabolites, and carbon assimilation, and were regulated by cluster specific TFs. We found that the expression of nitrogen transportation and assimilation genes varied significantly between the two lettuce species thereby providing the opportunity of introgressing wild alleles into the cultivated germplasm for developing lettuce cultivars with more efficient use of nitrogen.

Powdered crab and lobster shells (crustacean meal) obtained from fisheries are used as soil amendments to promote plant health and defense. In this study, a commercial crustacean meal amendment used to promote the health of lettuce, tomato, and other crop plants was applied to roots of lettuce and tomato seedlings. Gene expression profiling of the treated roots was assessed by RNA sequencing (RNA-seq) at 24 h after application relative to a 0 h time point. The RNA-seq analyses revealed upregulation of different types of genes in both tomato and lettuce roots at 24 h. Gene ontology analyses revealed increased expression of genes associated with oxidoreductases/metal ion binding in tomato roots at 24 h, while there was predominantly increased expression of genes associated with cell wall organization, lyases, and hydrolases in lettuce roots at 24 h. The types of defense-related genes expressed were also markedly different. In tomato roots, the most highly induced gene (log2 fold change 13.84, P ≤ 0.001) encoded a defense-associated miraculin-like protein, but transcripts of a similar gene were not induced in lettuce roots. Interestingly, phenylpropanoid pathway genes relating to cell wall biogenesis and lignification were significantly upregulated in both lettuce and tomato roots, suggesting that strengthening of plant cell walls is a common response to crustacean meal application. This research provides insight into gene expression patterns in the roots of lettuce and tomato in response to crustacean meal, improving our understanding of how this amendment could aid in plant health. [Graphic: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022.

Abstract 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.

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.

Ashy stem blight (ASB), caused by the fungus Macrophomina phaseolina (Tassi) Goidanich is an important disease of the common bean (Phaseolus vulgaris L.). It is important to identify quantitative trait loci (QTL) for ASB resistance and introgress into susceptible cultivars of the common bean. The objective of this research was to identify QTL and single nucleotide polymorphism (SNP) markers associated with ASB resistance in recombinant inbred lines (RIL) derived from a cross between BAT 477 and NY6020-4 common bean. One hundred and twenty-six F6:7 RIL were phenotyped for ASB in the greenhouse. Disease severity was scored on a scale of 1–9. Genotyping was performed using whole genome resequencing with 2x common bean genome size coverage, and over six million SNPs were obtained. After being filtered, 72,017 SNPs distributed on 11 chromosomes were used to conduct the genome-wide association study (GWAS) and QTL mapping. A novel QTL region of ~4.28 Mbp from 35,546,329 bp to 39,826,434 bp on chromosome Pv03 was identified for ASB resistance. The two SNPs, Chr03_39824257 and Chr03_39824268 located at 39,824,257 bp and 39,824,268 bp on Pv03, respectively, were identified as the strongest markers associated with ASB resistance. The gene Phvul.003G175900 (drought sensitive, WD repeat-containing protein 76) located at 39,822,021 – 39,824,655 bp on Pv03 was recognized as one candidate for ASB resistance in the RIL, and the gene contained the two SNP markers. QTL and SNP markers may be used to select plants and lines for ASB resistance through marker-assisted selection (MAS) in common bean breeding.

Spinach (Spinacia oleracea) is a popular leafy vegetable crop and commercial production is centered in California and Arizona in the US. The oomycete Peronospora effusa causes the most important disease in spinach, downy mildew. A total of nineteen races of P. effusa are known, with more than 15 documented in the last three decades, and the regular emergence of new races is continually overcoming the genetic resistance to the pathogen. This study aimed to finely map the downy mildew resistance locus RPF3 in spinach, identify single nucleotide polymorphism (SNP) markers associated with the resistance, refine the candidate genes responsible for the resistance, and evaluate the prediction performance using multiple machine learning genomic prediction (GP) methods. Segregating progeny population developed from a cross of resistant cultivar Whale and susceptible cultivar Viroflay to race 5 of P. effusa was inoculated under greenhouse conditions to determine downy mildew disease response across the panel. The progeny panel and the parents were resequenced at low coverage (1x) to identify genome wide SNP markers. Association analysis was performed using disease response phenotype data and SNP markers in TASSEL, GAPIT, and GENESIS programs and mapped the race 5 resistance loci (RPF3) to 1.25 and 2.73 Mb of Monoe-Viroflay chromosome 3 with the associated SNP in the 1.25 Mb region was 0.9 Kb from the NBS-LRR gene SOV3g001250. The RPF3 locus in the 1.22-1.23 Mb region of Sp75 chromosome 3 is 2.41-3.65 Kb from the gene Spo12821 annotated as NBS-LRR disease resistance protein. This study extended our understanding of the genetic basis of downy mildew resistance in spinach cultivar Whale and mapped the RPF3 resistance loci close to the NBS-LRR gene providing a target to pursue functional validation. Three SNP markers efficiently selected resistance based on multiple genomic selection (GS) models. The results from this study have added new genomic resources, generated an informed basis of the RPF3 locus resistant to spinach downy mildew pathogen, and developed markers and prediction methods to select resistant lines.

Abstract Background Downy mildew, the most devastating disease of spinach (Spinacia oleracea L.), is caused by the oomycete Peronospora effusa [=P. farinosa f. sp. spinaciae]. The P. effusa shows race specificities to the resistant host and comprises 19 reported races and many novel isolates. Sixteen new P. effusa races were identified during the past three decades, and the new pathogen races are continually overcoming the genetic resistances used in commercial cultivars. A spinach breeding population derived from the cross between cultivars Whale and Lazio was inoculated with P. effusa race 16 in an environment-controlled facility; disease response was recorded and genotyped using genotyping by sequencing (GBS). The main objective of this study was to identify resistance-associated single nucleotide polymorphism (SNP) markers from the cultivar Whale against the P. effusa race 16. Results Association analysis conducted using GBS markers identified six significant SNPs (S3_658,306, S3_692697, S3_1050601, S3_1227787, S3_1227802, S3_1231197). The downy mildew resistance locus from cultivar Whale was mapped to a 0.57 Mb region on chromosome 3, including four disease resistance candidate genes (Spo12736, Spo12784, Spo12908, and Spo12821) within 2.69–11.28 Kb of the peak SNP. Conclusions Genomewide association analysis approach was used to map the P. effusa race 16 resistance loci and identify associated SNP markers and the candidate genes. The results from this study could be valuable in understanding the genetic basis of downy mildew resistance, and the SNP marker will be useful in spinach breeding to select resistant lines.

Abstract The availability of well-assembled genome sequences and reduced sequencing costs have enabled the resequencing of many additional accessions in several crops, thus facilitating the rapid discovery and development of simple sequence repeat (SSR) markers. Although the genome sequence of inbred spinach line Sp75 is available, previous efforts have resulted in a limited number of useful SSR markers. Identification of additional polymorphic SSR markers will support genetics and breeding research in spinach. This study aimed to use the available genomic resources to mine and catalog a large number of polymorphic SSR markers. A search for SSR loci on six chromosome sequences of spinach line Sp75 using GMATA identified a total of 42,155 loci with repeat motifs of two to six nucleotides in the Sp75 reference genome. Whole-genome sequences (30x) of additional 21 accessions were aligned against the chromosome sequences of the reference genome and in silico genotyped using the HipSTR program by comparing and counting repeat numbers variation across the SSR loci among the accessions. The HipSTR program generated SSR genotype data were filtered for monomorphic and high missing loci, and a final set of the 5986 polymorphic SSR loci were identified. The polymorphic SSR loci were present at a density of 12.9 SSRs/Mb and were physically mapped. Out of 36 randomly selected SSR loci for validation, two failed to amplify, while the remaining were all polymorphic in a set of 48 spinach accessions from 34 countries. Genetic diversity analysis performed using the SSRs allele score data on the 48 spinach accessions showed three main population groups. This strategy to mine and develop polymorphic SSR markers by a comparative analysis of the genome sequences of multiple accessions and computational genotyping of the candidate SSR loci eliminates the need for laborious experimental screening. Our approach increased the efficiency of discovering a large set of novel polymorphic SSR markers, as demonstrated in this report.

Soybean is a primary meal protein for human consumption, poultry, and livestock feed. In this study, quantitative trait locus (QTL) controlling protein content was explored via genome-wide association studies (GWAS) and linkage mapping approaches based on 284 soybean accessions and 180 recombinant inbred lines (RILs), respectively, which were evaluated for protein content for 4 years. A total of 22 single nucleotide polymorphisms (SNPs) associated with protein content were detected using mixed linear model (MLM) and general linear model (GLM) methods in Tassel and 5 QTLs using Bayesian interval mapping (IM), single-trait multiple interval mapping (SMIM), single-trait composite interval mapping maximum likelihood estimation (SMLE), and single marker regression (SMR) models in Q-Gene and IciMapping. Major QTLs were detected on chromosomes 6 and 20 in both populations. The new QTL genomic region on chromosome 6 (Chr6_18844283–19315351) included 7 candidate genes and the Hap.XAA at the Chr6_19172961 position was associated with high protein content. Genomic selection (GS) of protein content was performed using Bayesian Lasso (BL) and ridge regression best linear unbiased prediction (rrBULP) based on all the SNPs and the SNPs significantly associated with protein content resulted from GWAS. The results showed that BL and rrBLUP performed similarly; GS accuracy was dependent on the SNP set and training population size. GS efficiency was higher for the SNPs derived from GWAS than random SNPs and reached a plateau when the number of markers was >2,000. The SNP markers identified in this study and other information were essential in establishing an efficient marker-assisted selection (MAS) and GS pipelines for improving soybean protein content.

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.

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.

Cowpea [Vigna unguiculate (L.) Walp.] is not only a healthy, nutritious, and versatile leguminous crop; it also has a relatively high adaptation to drought. Research has shown that cowpea lines have a high tolerance to drought, and many of them can survive more than 40 days under scorching and dry conditions. The cowpea (Southern pea) breeding program at the University of Arkansas has been active for more than 50 years and has produced more than 1000 advanced breeding lines. The purpose of this study was to evaluate the drought-tolerant ability in Arkansas cowpea lines and use the drought-tolerant lines in cowpea production or as parents in cowpea breeding. A total of 36 University of Arkansas breeding lines were used to screen drought tolerance at the seedling stage in this study. The experiment was conducted in the greenhouse using a randomized complete block design (RCBD) with two replicates, organized in a split-plot manner, where the drought treatment (drought and nondrought stress) as the main plot and the cowpea genotypes as the subplot. Drought stress was applied for 4 weeks, and three drought-tolerant–related traits were collected and analyzed. Results showed that cowpea breeding lines: ‘17-61’, ‘17-86’, ‘Early Scarlet’, and ‘ARBlackeye #1’ were found to be drought tolerant.

Abstract Background Soybean 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. Results A 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. Conclusions In 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.

Increased environmental fluctuations because of climate change have been forecasted in many agricultural regions to increase the frequency, intensity, and duration of drought episodes, which threaten the sustainability of future crop production. Although cowpeas are drought-tolerant, recent evidence shows that soil water stress in the early stages of vegetative growth significantly impairs crop growth and development, with detrimental impacts on yields. Diversity in cowpeas has been extensively genotyped and sequenced to enhance drought stress tolerance based on genetic diversity, population structure, and phylogenetic relationships. Hence, this study was conducted to evaluate whether cowpea genotypes with contrasting drought-tolerant status respond differently to varying moisture stress under a controlled environment. Three cowpea genotypes, including Arkansas Blackeye #1 (ARB), Top Pick Cream (TPC), and 17–111 were subjected to 28 days of three volumetric water content (VWC) treatments, which comprised of 0.270, 0.203, and 0.135 m3m−3, identified respectively as well-watered (WW), intermediate drought (ID), and drought-stressed (DS) conditions. After 28 days of VWC treatment (DAT), it was observed that the seedlings of all cowpea genotypes survived, showing different characteristics of the DS effect. The results showed that plant height (PH), leaf area (LA) and number (LN), fresh (FM) and total dry mass (TDM) of cowpea genotypes were significantly decreased under DS compared to WW and ID. Furthermore, cowpea genotypes subjected to DS showed significant reductions in their rate of photosynthesis (Pn) at 14 DAT when compared to 28 DAT. Thus, suggesting cowpeas tend to adapt to DS with time. Similar results were obtained for stomatal conductance (gs), intercellular CO2 concentration (Ci), and transpiration rate (E). However, the water use efficiency (WUE) increases linearly under DS. DS also resulted in the decline of chlorophyll fluorescence parameters except non-photochemical quenching (qN) which increased with decreasing VWC treatments. Overall, the ARB was observed to have significantly highest Pn, gs, E, Ci, LA, PH, Jmax, and Vcmax at DS, ID, and WW when compared to TPC and 17–111 cowpea genotypes, indicating its tolerance to DS. Cowpea breeders may use the contrasting drought-tolerant genotypes and identified morpho-physiological features to develop new genotypes that could tolerate DS during the vegetative stage in future climates.

Predictive modeling (PM) is a useful tool in selecting from a large number of target variables. Given the large quantities of data types generated from unmanned aerial system (UAS) platforms, uncovering the most appropriate candidate UAS data–based phenotype (UASDP) with a strong relationship to target crop traits may be a challenge with the traditional regression models. We hypothesized that by employing machine learning modeling techniques, the contributions of multiple vegetative indices as predictors of biomass and water-use could be defined and ranked. The objective of this study was to apply predictive machine techniques in determining the phase of spinach growth and UASDP variables that best predict yield and water-use efficiency. UASDPs were derived using red-green-blue and multi-spectral sensors mounted on a UAS platform flown weekly on 10 spinach genotypes under well-watered and partial water deficit conditions. Candidate UASDPs including mean and maximum plant height, canopy cover and volume, excess greenness index (ExG), chlorophyll red-edge (ChlRE), normalized difference vegetation index (NDVI) and normalized difference red-edge (NDRE) were generated. UASDPs were used to predict above-ground biomass-based fresh yield, biological dry yield, and field water-use efficiency (WUEf). This study highlights the use of bootstrap forest partitioning, and partition rank fraction as methods for selecting among many UASDPs as predictors of WUEf and yield. We also used a weighted geometric mean to integrate various model performance metrics to further refine the UASDPs rankings. UASDPs from mid to late growth stages were better predictors of yield and WUEf than UASDPs from earlier periods. Canopy volume, NDRE and ExG were the best predictors overall and were useful for distinguishing varieties, particularly in water-stress conditions. We expect that the approaches detailed here will improve reliability of discriminating the importance of UAS-acquired data types thereby improving UAS data-processing efficiency.

Genotype-by-sequencing (GBS) was used to explore the genetic diversity and structure of Spinacia turkestanica, and the selective sweeps involved in domestication of cultivated spinach, S. oleracea, from S. turkestanica. A total 7,065 single nucleotide polymorphisms (SNPs) generated for 16 Spinacia oleracea and 76 S. turkestanica accessions placed the S. oleracea accessions in one group, Q1, and the 76 S. turkestanica accessions, which originated from Central Asia, in two distinct groups, Q2 and Q3. The Q2 group shared greater genetic identity with the S. oleracea accessions, Q1, than the Q3 S. turkestanica group. Likewise, the S. oleracea Q1 group had a smaller Fst (0.008) with the Q2 group than with the Q3 group (Fst = 0.012), and a greater gene flow (Nm = 30.13) with the Q2 group than with the Q3 group (Nm = 21.83). The Q2 accessions originated primarily from Uzbekistan while the Q3 accessions originated mostly from Tajikistan. The Zarafshan Mountain Range appears to have served as a physical barrier that largely separated members of the Q2 and Q3 groups of S. turkestanica. Accessions with admixtures of Q2 and Q3 were collected primarily from lower elevations at the southern end of the Zarafshan Mountain Range in Uzbekistan. Selective sweep regions identified at 32, 49, and 52 Mb on chromosomes 1, 2, and 3, respectively, appear to have played a vital role in the domestication of S. oleracea as they are correlated with important domestication traits, including day length sensitivity for bolting (flowering). High XP-CLR scores at the 52 Mb genomic region of chromosome three suggest that a selective sweep at this region was responsible for early differentiation of S. turkestanica into two groups in Central Asia.

Abstract Genetic diversity is an important resource in crop breeding to improve cultivars with desirable traits. Selective breeding can lead to a reduction of genetic diversity. However, our understanding on this subject remains limited in lettuce (Lactuca sativa L.). Genotyping‐by‐sequencing (GBS) can provide a reduced version of the genome as a cost‐effective method to identify genetic variants across the genome. We genotyped a diverse set of 441 lettuce accessions using the GBS method. Phylogenetic and population genetic analyses indicated substantial genetic divergence among four horticultural types of lettuce: butterhead, crisphead, leaf, and romaine. Genetic‐diversity estimates between and within the four types indicated that the crisphead type was the most differentiated from other types, whereas its population was the most homogenous with the slowest linkage disequilibrium (LD) decay among the four types. These results suggested that crisphead lettuces had relatively less genetic variation across the genome as well as low gene flow from other types. We identified putative selective sweep regions that showed low genetic variation in the crisphead type. Genome‐wide association study (GWAS) and quantitative trait loci (QTL) analyses provided evidence that these genomic regions were, in part, associated with delayed bolting, implicating the positive selection of delayed bolting in reducing variation. Our findings enhance the current understanding of genetic diversity and the impacts of selective breeding on patterning genetic variation in lettuce.

Waterlogging is an important environmental stress limiting the productivity of crops worldwide. Cowpea (Vigna unguiculata L.) is particularly sensitive to waterlogging stress during the reproductive stage, with a consequent decline in pod formation and yield. However, little is known about the critical processes underlying cowpea’s responses to waterlogging during the reproductive stage. Thus, we investigated the key parameters influencing carbon fixation, including stomatal conductance (gs), intercellular CO2 concentration, chlorophyll content, and chlorophyll fluorescence, of two cowpea genotypes with contrasting waterlogging tolerance. These closely related genotypes have starkly contrasting responses to waterlogging during and after 7 days of waterlogging stress (DOW). In the intolerant genotype (‘EpicSelect.4’), waterlogging resulted in a gradual loss of pigment and decreased photosynthetic capacity as a consequent decline in shoot biomass. On the other hand, the waterlogging-tolerant genotype (‘UCR 369’) maintained CO2 assimilation rate (A), stomatal conductance (gs), biomass, and chlorophyll content until 5 DOW. Moreover, there was a highly specific downregulation of the mesophyll conductance (gm), maximum rate of Rubisco (Vcmax), and photosynthetic electron transport rate (Jmax) as non-stomatal limiting factors decreasing A in EpicSelect.4. Exposure of EpicSelect.4 to 2 DOW resulted in the loss of PSII photochemistry by downregulating the PSII quantum yield (Fv/Fm), photochemical efficiency (ΦPSII), and photochemical quenching (qP). In contrast, we found no substantial change in the photosynthesis and chlorophyll fluorescence of UCR 369 in the first 5 DOW. Instead, UCR 369 maintained biomass accumulation, chlorophyll content, and Rubisco activity, enabling the genotype to maintain nutrient absorption and photosynthesis during the early period of waterlogging. However, compared to the control, both cowpea genotypes could not fully recover their photosynthetic capacity after 7 DOW, with a more significant decline in EpicSelect.4. Overall, our findings suggest that the tolerant UCR 369 genotype maintains higher photosynthesis under waterlogging stress attributable to higher photochemical efficiency, Rubisco activity, and less stomatal restriction. After recovery, the incomplete recovery of A can be attributed to the reduced gs caused by severe waterlogging damage in both genotypes. Thus, promoting the rapid recovery of stomata from waterlogging stress may be crucial for the complete restoration of carbon fixation in cowpeas during the reproductive stage.

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.

This review summarizes the history and current state of the known genetic basis for soybean resistance to Soybean mosaic virus (SMV), and examines how the integration of molecular markers has been utilized in breeding for crop improvement. SVM causes yield loss and seed quality reduction in soybean based on the SMV strain and the host genotype. Understanding the molecular underpinnings of SMV–soybean interactions and the genes conferring resistance to SMV has been a focus of intense research interest for decades. Soybean reactions are classified into three main responses: resistant, necrotic, or susceptible. Significant progress has been achieved that has greatly increased the understanding of soybean germplasm diversity, differential reactions to SMV strains, genotype–strain interactions, genes/alleles conferring specific reactions, and interactions among resistance genes and alleles. Many studies that aimed to uncover the physical position of resistance genes have been published in recent decades, collectively proposing different candidate genes. The studies on SMV resistance loci revealed that the resistance genes are mainly distributed on three chromosomes. Resistance has been pyramided in various combinations for durable resistance to SMV strains. The causative genes are still elusive despite early successes in identifying resistance alleles in soybean; however, a gene at the Rsv4 locus has been well validated.

The effects of soilless substrate-based versus soil cultivation on overall fruit quality and yield in tomato (Solanum lycopersicum) were studied using the tomato cv. Zhonghua Lvbao. Experiments for tomato soilless cultivation were carried out under greenhouse conditions. Plant growth, fruit quality and yield, and physiologic traits were observed. RNA-seq and RT-PCR, as well as metabolomic analyses were performed to examine the expressed genes and metabolites under soilless substrate cultivation. The results showed that the plant height, stem diameter, and chlorophyll contents of tomato under substrate-based cultivation were increased by 37.3%, 19.8%, and 15.3%, respectively, compared with soil cultivation system. Leaf photosynthetic and transpiration rates, stomatal conductance, and root vitality of tomato, under substrate-based cultivation, increased by 29.0%, 21.2%, 43.9%, and 84.5%, respectively, compared with soil cultivation. The yield reached 7177.5 kg/667 m2, and the relative yield increased by 10.1%, compared with soil cultivation. The contents of total soluble sugar, soluble solids, and vitamin C increased by 35.7%, 19.7%, and 18.2%, respectively, higher than those of soil cultivation in tomato fruits, while nitrate content and titratable acid decreased by 29.4% and 11.8%, respectively. Therefore, substrate-based-cultivation can increase production and improve tomato fruit quality and taste. We examined the expressed genes and metabolites to explore the molecular mechanism of plant growth and overall fruit quality improvement in substrate-based cultivation. A total of 476 differentially expressed genes were identified by transcriptomes profiling, of which 321 and 155 were significantly up- and down-regulated, respectively. The results of metabolomics analysis showed that 441 metabolites were detected, where 24 and 36 metabolites were up- and down-regulated, respectively. By combining analyses of transcriptomic and metabolic groups, genes and metabolites related to the fruit quality were mainly concentrated in the vitamin B6/ascorbic acid/aldonic acidmetabolism, and glycerophospholipid metabolic pathways. Therefore, substrate-based cultivation can elevate vitamin and soluble sugar contents and the expression of fruit flavor related genes, which lays an initial background for exploring the mechanism of substrate-based cultivation, in order to improve the quality of tomato in the future.

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

Downy mildew, caused by the oomycete Peronospora effusa, is the most economically important disease on spinach. Fourteen new races of P. effusa have been identified in the last three decades. The frequent emergence of new races of P. effusa continually overcome the genetic resistance to the pathogen. The objectives of this research were to more clearly map the downy mildew resistance locus RPF1 in spinach, to identify single nucleotide polymorphism (SNP) markers associated with the resistance, and to refine the candidate genes responsible for the resistance. Progeny from populations generated from crosses of cultivars resistant (due to RPF1) to race 13 of P. effusa (Swan, T-Bird, Squirrel, and Tonga) with race 13 susceptible cultivars (Whale and Polka) were inoculated and the downy mildew disease response determined. Association analysis was performed in TASSEL, GAPIT, PLINK, and GENESIS programs using SNP markers identified from genotyping by sequencing (GBS). Association analysis mapped the race 13 resistance loci (RPF1) to positions 0.39, 0.69, 0.94-0.98, and 1.2 Mb of chromosome 3. The associated SNPs were within 1–7 kb of the disease resistance genes Spo12784, Spo12719, Spo12905, and Spo12821, and 11–18 Kb from Spo12903. This study extended our understanding of the genetic basis of downy mildew resistance in spinach and provided the most promising candidate genes Spo12784 and Spo12903 near the RPF1 locus, to pursue functional validation. The SNP markers may be used to select for the resistant lines to improve genetic resistance against the downy mildew pathogen and in developing durably resistant cultivars.

Sugarcane (Saccharum spp. hybrids) is one of the most important commercial crops for sugar, ethanol, and other byproducts production; therefore, it is of great significance to carry out genetic research. Assessing the genetic population structure and diversity plays a vital role in managing genetic resources and gene mapping. In this study, we assessed the genetic diversity and population structure among 196 Saccharum accessions, including 34 S. officinarum, 69 S. spontaneum, 17 S. robustum, 25 S. barberi, 13 S. sinense, 2 S. edule, and 36 Saccharum spp. hybrids. A total of 624 polymorphic SSR alleles were amplified by PCR with 22 pairs of fluorescence-labeled highly polymorphic SSR primers and identified on a capillary electrophoresis (CE) detection system including 109 new alleles. Three approaches (model-based clustering, principal component analysis, and phylogenetic analysis) were conducted for population structure and genetic diversity analyses. The results showed that the 196 accessions could be grouped into either three (Q) or eight (q) sub-populations. Phylogenetic analysis indicated that most accessions from each species merged. The species S. barberi and S. sinense formed one group. The species S. robustum, S. barberi, S. spontaneum, S. edule, and sugarcane hybrids merged into the second group. The S. officinarum accessions formed the third group located between the other two groups. Two-way chi-square tests derived a total of 24 species-specific or species-associated SSR alleles, including four alleles each for S. officinarum, S. spontaneum, S. barberi, and S. sinense, five alleles for S. robustum. and three alleles for Saccharum spp. hybrids. These species-specific or species-associated SSR alleles will have a wide application value in sugarcane breeding and species identification. The overall results provide useful information for future genetic study of the Saccharum genus and efficient utilization of sugarcane germplasm resources in sugarcane breeding.

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 SCN-resistant 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 GWAS-derived 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.06G134900, Glyma.15G097500.1, Glyma.15G100900.3, Glyma.15G105400, Glyma.15G107200, and Glyma.19G121200.1 (Table 4). Glyma.06G134900, Glyma.15G097500.1, Glyma.15G100900.3, Glyma.15G105400, and Glyma.19G121200.1 are best candidates. To the best of our knowledge, this is the first report highlighting SNP markers associated with tolerance index based on biomass reduction under SCN infestation in soybean. This research opens a new approach to use SCN tolerance in soybean breeding and the SNP markers will provide a tool for breeders to select for SCN tolerance.

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.

Abstract Background Spinach 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. Results A 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. Conclusions The 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.

Olive (Olea europaea L.) is a very important edible oil crop and has been cultivated for about 4,000 years in the Mediterranean area. Due to its nutritional and economic importance, researches on germplasm characterization received extensive attention. In this study, using the genotyping-by-sequencing (GBS) technology, we carried out genetic diversity analysis on 57 olive cultivars with different geographical origins. In total, 73,482 high-quality single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) > 5%, call rate > 50%, and heterozygosity rate < 10% were obtained at the whole genome level. Genetic structure and phylogenetic analysis showed that the 57 olive cultivars could be classified into two groups (Group I and Group II). No clear geographical distributions of cultivars were observed generally between the two groups. The average nucleotide diversities (π) specific for Group I and Group II were 0.317 and 0.305. The fixation index (FST) between Group I and Group II was 0.033. In Group II, cultivars could be further divided into two subgroups (Group IIa and Group IIb), which seem to be associated with their fruit sizes. The five Chinese-bred cultivars were all clustered in Group II, showing a closer genetic relationship with those from the central Mediterranean region and limited genetic background. It is therefore necessary for Chinese olive breeding programs to incorporate other genetic basis by utilizing germplasm from the other regions particularly from the east Mediterranean region as breeding parents. The results showed that GBS is an effective marker choice for cultivar characterization and genetic diversity analysis in olive and will help us better understand the genetic backgrounds of the crop.

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.

Zao5241 is an elite soybean [Glycine max (L.) Merr.] line and backbone parent. In this study, we employed iTRAQ to analyze the proteomes and protein expression profiles of Zao5241 during leaf development. We identified 1,245 proteins in all experiments, of which only 45 had been previously annotated. Among overlapping proteins between three biological replicates, 598 proteins with 2 unique peptides identified were reliably quantified. The protein datasets were classified into 36 GO functional terms, and the photosynthesis term was most significantly enriched. A total of 113 proteins were defined as being differentially expressed during leaf development; 41 proteins were found to be differently expressed between two and four week old leaves, and 84 proteins were found to be differently expressed between two and six week old leaves, respectively. Cluster analysis of the data revealed dynamic proteomes. Proteins annotated as electron carrier activity were greatly enriched in the peak expression profiles, and photosynthesis proteins were negatively modulated along the whole time course. This dataset will serve as the foundation for a systems biology approach to understanding photosynthetic development.

Phytophthora sojae, an oomycete pathogen of soybean, causes stem and root rot, resulting in annual economic loss up to $2 billion worldwide. Varieties with P. sojae resistance are environmental friendly to effectively reduce disease damages. In order to improve the resistance of P. sojae and broaden the genetic diversity in Southern soybean cultivars and germplasm in the U.S., we established a P. sojae resistance gene pool that has high genetic diversity, and explored genomic regions underlying the host resistance to P. sojae races 1, 3, 7, 17 and 25. A soybean germplasm panel from maturity groups (MGs) IV and V including 189 accessions originated from 10 countries were used in this study. The panel had a high genetic diversity compared to the 6,749 accessions from MGs IV and V in USDA Soybean Germplasm Collection. Based on disease evaluation dataset of these accessions inoculated with P. sojae races 1, 3, 7, 17 and 25, which are publically available, five accessions in this panel were resistant to all races. Genome-wide association analysis identified a total of 32 significant SNPs, which were clustered in resistance-associated genomic regions, among those, ss715619920 was only 3kb away from the gene Glyma.14g087500, a subtilisin protease. Gene expression analysis showed that the gene was down-regulated more than 4 fold (log2 fold > 2.2) in response to P. sojae infection. The identified molecular markers and genomic regions that are associated with the disease resistance in this gene pool will greatly assist the U.S. Southern soybean breeders in developing elite varieties with broad genetic background and P. sojae resistance.

Peronospora effusa is an obligate pathogen that causes downy mildew on spinach and is considered the most economically important disease of spinach. The objective of the current research was to assess genetic diversity of known historical races and isolates collected in 2014 from production fields in Yuma, Arizona and Salinas Valley, California. Candidate neutral single nucleotide polymorphisms (SNPs) were identified by comparing sequence data from reference isolates of known races of the pathogen collected in 2009 and 2010. Genotypes were assessed using targeted sequencing on genomic DNA extracted directly from infected plant tissue. Genotyping 26 historical and 167 contemporary samples at 46 SNP loci revealed 82 unique multi-locus genotypes. The unique genotypes clustered into five groups and the majority of isolates collected in 2014 were genetically closely related, regardless of source location. The historical samples, representing several races, showed greater genetic differentiation. Overall, the SNP data indicate much of the genotypic variation found within fields was produced during asexual development, whereas overall genetic diversity may be influenced by sexual recombination on broader geographical and temporal scales.

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.