Iron deficiency chlorosis (IDC) is a yield limiting problem in soybean (Glycine max (L.) Merr) production regions with calcareous soils. Genome-wide association study (GWAS) was performed using a ...high density SNP map to discover significant markers, QTL and candidate genes associated with IDC trait variation. A stepwise regression model included eight markers after considering LD between markers, and identified seven major effect QTL on seven chromosomes. Twelve candidate genes known to be associated with iron metabolism mapped near these QTL supporting the polygenic nature of IDC. A non-synonymous substitution with the highest significance in a major QTL region suggests soybean orthologs of FRE1 on Gm03 is a major gene responsible for trait variation. NAS3, a gene that encodes the enzyme nicotianamine synthase which synthesizes the iron chelator nicotianamine also maps to the same QTL region. Disease resistant genes also map to the major QTL, supporting the hypothesis that pathogens compete with the plant for Fe and increase iron deficiency. The markers and the allelic combinations identified here can be further used for marker assisted selection.
Determinacy is an agronomically important trait associated with the domestication in soybean (Glycine max). Most soybean cultivars are classifiable into indeterminate and determinate growth habit, ...whereas Glycine soja, the wild progenitor of soybean, is indeterminate. Indeterminate (Dt1/Dt1) and determinate (dt1/dt1) genotypes, when mated, produce progeny that segregate in a monogenic pattern. Here, we show evidence that Dt1 is a homolog (designated as GmTfl1) of Arabidopsis terminal flower 1 (TFL1), a regulatory gene encoding a signaling protein of shoot meristems. The transition from indeterminate to determinate phenotypes in soybean is associated with independent human selections of four distinct single-nucleotide substitutions in the GmTfl1 gene, each of which led to a single amino acid change. Genetic diversity of a minicore collection of Chinese soybean landraces assessed by simple sequence repeat (SSR) markers and allelic variation at the GmTfl1 locus suggest that human selection for determinacy took place at early stages of landrace radiation. The GmTfl1 allele introduced into a determinate-type (tfl1/tfl1) Arabidopsis mutants fully restored the wild-type (TFL1/TFL1) phenotype, but the Gmtfl1 allele in tfl1/tfl1 mutants did not result in apparent phenotypic change. These observations indicate that GmTfl1 complements the functions of TFL1 in ARABIDOPSIS: However, the GmTfl1 homeolog, despite its more recent divergence from GmTfl1 than from Arabidopsis TFL1, appears to be sub- or neo-functionalized, as revealed by the differential expression of the two genes at multiple plant developmental stages and by allelic analysis at both loci.
The presence of seed color in common bean (Phaseolus vulgaris) requires the dominantacting P (pigment) gene, and white seed is a recessive phenotype in all domesticated races of the species. P was ...classically associated with seed size, thus describing it as the first genetic marker for a quantitative trait. The molecular structure of P was characterized to understand the selection of white seeds during bean diversification and the relationship of P to seed weight.
P was identified by homology searches, a genome-wide association study (GWAS) and gene remodeling, and confirmed by gene silencing. Allelic variation was assessed by a combination of resequencing and marker development, and the relationship between P and seed weight was assessed by a GWAS study.
P is a member of clade B of subclass IIIf of plant basic helix–loop–helix (bHLH) proteins. Ten race-specific P alleles conditioned the white seed phenotype, and each causative mutation affected at least one bHLH domain required for color expression. GWAS analysis confirmed the classic association of P with seed weight.
In common bean, white seeds are the result of convergent evolution and, among plant species, orthologous convergence on a single transcription factor gene was observed.
Understanding syntentic relationship between two species is critical to assessing the potential for comparative genomic analysis. Common bean (Phaseolus vulgaris L.) and soybean (Glycine max L.), the ...two most important members of the Phaseoleae legumes, appear to have a diploid and polyploidy recent past, respectively. Determining the syntentic relationship between these two species will allow researchers to leverage not only genomic resources but also genetic data for important agronomic traits to improve both of these species.
Genetically-positioned transcript loci of common bean were mapped relative to the recent soybean 1.01 pseudochromosome assembly. In nearly every case, each common bean locus mapped to two loci in soybean, a result consistent with the duplicate polyploidy history of soybean. Blocks of synteny averaging 32 cM in common bean and 4.9 Mb in soybean were observed for all 11 common bean linkage groups, and these blocks mapped to all 20 soybean pseudochromosomes. The median physical-to-genetic distance ratio in common bean (based on soybean physical distances) was approximately 120 kb/cM. approximately 15,000 common bean sequences (primarily EST contigs and EST singletons) were electronically positioned onto the common bean map using the shared syntentic blocks as references points.
The collected evidence from this mapping strongly supports the duplicate history of soybean. It further provides evidence that the soybean genome was fractionated and reassembled at some point following the duplication event. These well mapped syntentic relationships between common bean and soybean will enable researchers to target specific genomic regions to discover genes or loci that affect phenotypic expression in both species.
Common bean (Phaseolus vulgaris L.) breeding programs aim to improve both agronomic and seed characteristics traits. However, the genetic architecture of the many traits that affect common bean ...production are not completely understood. Genome‐wide association studies (GWAS) provide an experimental approach to identify genomic regions where important candidate genes are located. A panel of 280 modern bean genotypes from race Mesoamerica, referred to as the Middle American Diversity Panel (MDP), were grown in four US locations, and a GWAS using >150,000 single‐nucleotide polymorphisms (SNPs) (minor allele frequency MAF ≥ 5%) was conducted for six agronomic traits. The degree of inter‐ and intrachromosomal linkage disequilibrium (LD) was estimated after accounting for population structure and relatedness. The LD varied between chromosomes for the entire MDP and among race Mesoamerica and Durango–Jalisco genotypes within the panel. The LD patterns reflected the breeding history of common bean. Genome‐wide association studies led to the discovery of new and known genomic regions affecting the agronomic traits at the entire population, race, and location levels. We observed strong colocalized signals in a narrow genomic interval for three interrelated traits: growth habit, lodging, and canopy height. Overall, this study detected ∼30 candidate genes based on a priori and candidate gene search strategies centered on the 100‐kb region surrounding a significant SNP. These results provide a framework from which further research can begin to understand the actual genes controlling important agronomic production traits in common bean.
White mold (WM) is a major disease in common bean (
Phaseolus vulgaris
L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.2, one of the nine ...meta-QTL with a major effect on WM tolerance, explains up to 35% of the phenotypic variation and was previously mapped to a large genomic interval on Pv02. Our objective was to narrow the interval of this QTL using combined approach of classic QTL mapping and QTL-based bulk segregant analysis (BSA), and confirming those results with Khufu
de novo
QTL-seq. The phenotypic and genotypic data from two RIL populations, ‘Raven’/I9365-31 (R31) and ‘AN–37’/PS02–029C–20 (Z0726-9), were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing. The QTL physical interval was determined by considering overlapping interval of the identified QTL or peak region in both populations by three independent QTL mapping analyses. Our findings revealed that meta-QTL WM2.2 consists of three regions, WM2.2a (4.27-5.76 Mb; euchromatic), WM 2.2b (12.19 to 17.61 Mb; heterochromatic), and WM2.2c (23.01-25.74 Mb; heterochromatic) found in both populations. Gene models encoding for gibberellin 2-oxidase 8, pentatricopeptide repeat, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein (Phvul.002G09200) and LRR domain containing family proteins are potential candidate genes associated with WM2.2b resistance. Nine gene models encoding disease resistance protein pathogenesis-related thaumatin superfamily protein and disease resistance-responsive (dirigent-like protein) family protein etc found within the WM2.2c QTL interval are putative candidate genes. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b and WM2.2c regions trigger physiological resistance based on putative candidate genes.
Dry bean (Phaseolus vulgaris L.) production in many regions is threatened by white mold (WM) Sclerotinia sclerotiorum (Lib.) de Bary. Seed yield losses can be up to 100% under conditions favorable ...for the pathogen. The low heritability, polygenic inheritance, and cumbersome screening protocols make it difficult to breed for improved genetic resistance. Some progress in understanding genetic resistance and germplasm improvement has been accomplished, but cultivars with high levels of resistance are yet to be released. A WM multiparent advanced generation inter‐cross (MAGIC) population (n = 1060) was developed to facilitate mapping and breeding efforts. A seedling straw test screening method provided a quick assay to phenotype the population for response to WM isolate 1980. Nineteen MAGIC lines were identified with improved resistance. For genome‐wide association studies (GWAS), the data was transformed into three phenotypic distributions—quantitative, polynomial, and binomial—and coupled with ∼52,000 single‐nucleotide polymorphisms (SNPs). The three phenotypic distributions identified 30 significant genomic intervals −log10 (P value) ≥ 3.0. However, across distributions, four new genomic regions as well as two regions previously reported were found to be associated with resistance. Cumulative R2 values were 57% for binomial distribution using 13 genomic intervals, 41% for polynomial using eight intervals, and 40% for quantitative using 11 intervals. New resistant germplasm as well as new genomic regions associated with resistance are now available for further investigation.
Core Ideas
A MAGIC population was developed to facilitate mapping and pyramiding of QTL related to white mold resistance.
New genomic regions associated with white mold resistance are reported while some known regions are confirmed.
Pinto and great northern beans with improved resistance to white mold were identified.
Disease‐related candidate genes for white mold resistance were identified.
Climate change models predict temporal and spatial shifts in precipitation resulting in more frequent incidents of flooding, particularly in regions with poor soil drainage. In these flooding ...conditions, crop losses are inevitable due to exposure of plants to hypoxia and the spread of root rot diseases. Improving the tolerance of bean cultivars to flooding is crucial to minimize crop losses. In this experiment, we evaluated the phenotypic responses of 277 genotypes from the Andean Diversity Panel to flooding at germination and seedling stages. A randomized complete block design, with a split plot arrangement, was employed for phenotyping germination rate, total weight, shoot weight, root weight, hypocotyl length, SPAD index, adventitious root rate, and survival score. A subset of genotypes (
= 20) were further evaluated under field conditions to assess correlations between field and greenhouse data and to identify the most tolerant genotypes. A genome-wide association study (GWAS) was performed using ~203 K SNP markers to understand the genetic architecture of flooding tolerance in this panel. Survival scores between field and greenhouse data were significantly correlated (
= 0.55,
= 0.01). Subsequently, a subset of the most tolerant and susceptible genotypes were evaluated under pathogenic
spp. pressure. This experiment revealed a potential link between flooding tolerance and
spp. resistance. Several tolerant genotypes were identified that could be used as donor parents in breeding pipelines, especially ADP-429 and ADP-604. Based on the population structure analysis, a subpopulation consisting of 20 genotypes from the Middle American gene pool was detected that also possessed the highest root weight, hypocotyl length, and adventitious root development under flooding conditions. Genomic regions associated with flooding tolerance were identified including a region on Pv08/3.2 Mb, which is associated with germination rate and resides in vicinity of
, a central gene involved in response of plants to hypoxia. Furthermore, a QTL at Pv07/4.7 Mb was detected that controls survival score of seedlings under flooding conditions. The association of these QTL with the survivability traits including germination rate and survival score, indicates that these loci can be used in marker-assisted selection breeding to improve flooding tolerance in the Andean germplasm.
Genetic resistance is the primary means for control of
(BGYMV) in common bean (
). Breeding for resistance is difficult because of sporadic and uneven infection across field nurseries. We sought to ...facilitate breeding for BGYMV resistance by improving marker-assisted selection (MAS) for the recessive
gene and identifying and developing MAS for quantitative trait loci (QTL) conditioning resistance. Genetic linkage mapping in two recombinant inbred line populations and genome-wide association study (GWAS) in a large breeding population and two diversity panels revealed a candidate gene for
and three QTL BGY4.1, BGY7.1, and BGY8.1 on independent chromosomes. A mutation (5 bp deletion) in a NAC (No Apical Meristem) domain transcriptional regulator superfamily protein gene
on chromosome Pv03 corresponded with the recessive
resistance allele. The five bp deletion in exon 2 starting at 20 bp (Pv03: 2,601,582) is expected to cause a stop codon at codon 23 (Pv03: 2,601,625), disrupting further translation of the gene. A T
-shift assay marker named PvNAC1 was developed to track
. PvNAC1 corresponded with
across ∼1,000 lines which trace
back to a single landrace "Garrapato" from Mexico. BGY8.1 has no effect on its own but exhibited a major effect when combined with
. BGY4.1 and BGY7.1 acted additively, and they enhanced the level of resistance when combined with
. T
-shift assay markers were generated for MAS of the QTL, but their effectiveness requires further validation.
Snap beans are a significant source of micronutrients in the human diet. Among the micronutrients present in snap beans are phenolic compounds with known beneficial effects on human health, ...potentially via their metabolism by the gut-associated microbiome. The genetic pathways leading to the production of phenolics in snap bean pods remain uncertain. In this study, we quantified the level of total phenolic content (TPC) in the Bean Coordinated Agriculture Program (CAP) snap bean diversity panel of 149 accessions. The panel was characterized spectrophotometrically for phenolic content with a Folin-Ciocalteu colorimetric assay. Flower, seed and pod color were also quantified, as red, purple, yellow and brown colors are associated with anthocyanins and flavonols in common bean. Genotyping was performed through an Illumina Infinium Genechip BARCBEAN6K_3 single nucleotide polymorphism (SNP) array. Genome-Wide Association Studies (GWAS) analysis identified 11 quantitative trait nucleotides (QTN) associated with TPC. An SNP was identified for TPC on Pv07 located near the
gene, which is a major switch in the flavonoid biosynthetic pathway. Candidate genes were identified for seven of the 11 TPC QTN. Five regulatory genes were identified and represent novel sources of variation for exploitation in developing snap beans with higher phenolic levels for greater health benefits to the consumer.
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