Identification and Validation of a New Source of Low Grain Cadmium Accumulation in Durum Wheat (Triticum Turgidum L. Subsp. Durum (Defs.))

Cadmium (Cd) is a toxic heavy metal with no known biological function. The maximum level of Cd concentration allowed in the international market for wheat grain is 0.2 mg kg-1. Higher Cd levels in durum wheat (Triticum turgidum L. var. durum Desf) may threaten its export. To develop new durum wheat cultivars low in Cd uptake and speed up the selection process in breeding programs, this study attempted to identify SNP(s) associated with a low Cd uptake in the durum experimental line D041735. D041735 was developed from a cross between hexaploid (Sumai 3) and durum wheat by NDSU breeding program and has consistently shown low grain Cd levels. Therefore, this study sought 1) to identify SNP marker(s) tightly linked to Cd uptake and genetic dissection of the grain Cd content in a recombinant inbred line mapping population derived from D041735 and Divide (a high Cd accumulator cultivar) using wheat 90k SNP chips and 2) to test for alleles from detected Cd-linked markers among three sources of low Cd accumulators, including Strongfield, Haurani, and D041735. The QTL analysis performed in this study identified only a single major QTL for Cd uptake on chromosome arm 5BL. The QTL was detected in a 0.3 cM interval flanked by SNP markers RAC875_c20785_1219 and Kukri_c66357_357. Validation results using these flanking markers initially suggested the existence of a different gene or allele for low Cd uptake in the D041735 line as a new source for the durum breeding program at NDSU. The BLAST analysis of these flanking markers suggested the Aluminum Induced Protein Like Protein and heavy metal transporter ATPase 3 as candidate genes for the major QTL. Allelism testing revealed that the identified QTL in this study is novel and not the previously mapped QTL Cdu1on 5BL. This study therefore confirmed that the D041735 experimental line is a novel source of low Cd uptake in durum wheat germplasms, where the major QTL is most likely introduced from hexaploid wheat

Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches

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

Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments

The genetic improvement of economically important production traits of dry bean (Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized Bean Abiotic Stress Evaluation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs. Includes Corrigendu

2015 NDSU Bean Breeding Program Genotyping Snapshot

The dataset consists of genotyping and common bacterial blight phenotyping information from genotypes within the NDSU Dry Bean Breeding Program. The Middle American data set consists of 713 genotypes and the Andean dataset consists of 139 genotypes. Both Middle American and Andean lines were phenotyped with common bacterial blight at both the unifoliate and trifoliate stages and the medians recorded. DNA was isolated from each line and sequenced using a single-end Illumina platform. Sequences were quality trimmed using SICKLE and then aligned to the Phaseolus vulgaris v2.1 reference sequence (DOE-JGI and USDA-NIFA, http://phytozome.jgi.doe.gov), indexed and sorted using BWA-MEMB and SAMtools. Read groups including library ID, platform and platform unit were added to each alignment within the BAM files using Picard (http://broadinstitute.github.io/picard/). Unifiedgenotyper from GATK3.6 (DePristo et al. 2011) was used to call variants with quality scores above 10. Quality scores between 10 and 30 were marked as low quality. Variants with a read depth of less than two were filtered using GATK3.6 variantfiltration and subsequently replaced as missing data. Low quality variants were removed via hard filtering when variants contained more than 25% missing data (50% in the MA SNP data set), more than one nucleotide, more than two alleles, or the minor allele was less than 5% in the Andean dataset(<1% in the MA SNP dataset). Genotypes with more than 90% missing data were removed. SNPs with less than 25% in the Andean dataset (50% in MA SNP dataset) of missing data were imputed in fastPHASE. The output file was converted to a hmp file for distribution. The dataset was used for identifying genomic regions associated with resistance to common bacterial blight in dry beans and can be mined for other SNPs of interest.USDA Agricultural Marketing Service grant 15-SCBGP-ND-002

Assessing the Effect of Phenotyping Scoring Systems and SNP Calling and Filtering Parameters on Detection of QTL Associated with Reaction of Brassica napus to Sclerotinia sclerotiorum

The polyploid nature of canola (Brassica napus) represents a challenge for the accurate identification of single-nucleotide polymorphisms (SNPs) and the detection of quantitative trait loci (QTL). In this study, combinations of eight phenotyping scoring systems and six SNP calling and filtering parameters were evaluated for their efficiency in detection of QTL associated with response to Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, in two doubled haploid canola mapping populations. Most QTL were detected in lesion length, relative areas under the disease progress curve (rAUDPC) for lesion length, and binomial-plant mortality data sets. Binomial data derived from lesion size were less efficient in QTL detection. Inclusion of additional phenotypic sets to the analysis increased the numbers of significant QTL by 2.3-fold; however, the continuous data sets were more efficient. Between two filtering parameters used to analyze genotyping-by-sequencing data, imputation of missing data increased QTL detection in one population with a high level of missing data but not in the other. Inclusion of segregation-distorted SNPs increased QTL detection but did not impact their R2 values significantly. In all, 12 of 16 detected QTL were on chromosomes A02 and C01, and the rest were on A07, A09, and C03. Marker A02-7594120, associated with a QTL on chromosome A02, was detected in both populations. Results of this study suggest that the impact of genotypic variant calling and filtering parameters may be population dependent while deriving additional phenotyping scoring systems such as rAUDPC datasets and mortality binary may improve QTL detection efficiency.[Graphic: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license

Using Breeding Populations With a Dual Purpose: Cultivar Development and Gene Mapping?A Case Study Using Resistance to Common Bacterial Blight in Dry Bean (Phaseolus vulgaris L.)

Dry bean (Phaseolus vulgaris L.) is an important worldwide legume crop with low to moderate levels of resistance to common bacterial blight (CBB) caused by Xanthomonas axonopodis pv. phaseoli. A total of 852 genotypes (cultivars, preliminary and advanced breeding lines) from the North Dakota State University dry bean breeding program were tested for their effectiveness as populations for genome-wide association studies (GWAS) to identify genomic regions associated with resistance to CBB, to exploit the associated markers for marker-assisted breeding (MAB), and to identify candidate genes. The genotypes were evaluated in a growth chamber for disease resistance at both the unifoliate and trifoliate stages. At the unifoliate stage, 35% of genotypes were resistant, while 25% of genotypes were resistant at the trifoliate stage. Libraries generated from each genotype were sequenced using the Illumina platform. After filtering for sequence quality, read depth, and minor allele frequency, 41,998 single-nucleotide polymorphisms (SNPs) and 30,285 SNPs were used in GWAS for the Middle American and Andean gene pools, respectively. One region near the distal end of Pv10 near the SAP6 molecular marker from the Andean gene pool explained 26.7?36.4% of the resistance variation. Three to seven regions from the Middle American gene pool contributed to 25.8?27.7% of the resistance, with the most significant peak also near the SAP6 marker. Six of the eight total regions associated with CBB resistance are likely the physical locations of quantitative trait loci identified from previous genetic studies. The two new locations associated with CBB resistance are located at Pv10:22.91?23.36 and Pv11:52.4. A lipoxgenase-1 ortholog on Pv10 emerged as a candidate gene for CBB resistance. The state of one SNP on Pv07 was associated with susceptibility. Its subsequent use in MAB would reduce the current number of lines in preliminary and advanced field yield trial by up to 14% and eliminate only susceptible genotypes. These results provide a foundational SNP data set, improve our understanding of CBB resistance in dry bean, and impact resource allocation within breeding programs as breeding populations may be used for dual purposes: cultivar development as well as genetic studies.The datasets presented in this study can be found in the NDSU repository at https://hdl.handle.net/10365/31610U.S. Department of Agriculture?s (USDA) Agricultural Marketing Service grant 15-SCBGP-ND-0026Northarvest Bean Growers Association and USDA-National Institute of Food and Agriculture (NIFA ? Hatch project ND01508, Hatch project ND02229, and Hatch multistate project ND01589

Dry Edible Bean White Mold MAGIC Population

A dry edible bean MAGIC population was generated to map genes for resistance to white mold and to produce inbred lines with improved white mold (WM) resistance combined with good agronomic performance for primarily the pinto bean market class. Eight founding parents were crossed to develop a modified MAGIC population. PT7-2 was intermated with Powderhorn (cross A). ID14-4 was intermated with CO16079 (cross B). La Paz was intermated with Lariat (cross C). USPT-WM_12 was intermated with El Dorado (cross D). Subsequently, F1 plants of each initial cross were intermated using a one-way funnel, F1 from cross A was mated with F1 from cross B and F1 from cross C was mated with F1 from cross D meaning that not every possible cross combination was conducted. The next cycle consisted of intermating F1 from the AxB cross with F1 from the CxD cross. For each cycle reciprocal crosses were conducted to offset potential maternal effects and maternal inheritance. After the final crosses, the F1 were planted to produce the F2 generation which then went through three rounds of single seed descent from F2 to F5. A total of 1,050 F2-derived F5 inbred lines were developed for this WM-MAGIC population. A total of 428 lines representing each of the crosses were assigned to the training population. The remaining lines were assigned to the validation population. The training population has been genotyped. Briefly, the DNA was isolated from each line and sequenced using a single-end Illumina platform. Sequences were quality trimmed using SICKLE and then aligned to the Phaseolus vulgaris v2.1 reference sequence (DOE-JGI and USDA-NIFA, http://phytozome.jgi.doe.gov) or the UI111 v1.0 reference sequence, indexed and sorted using BWA-MEMB and SAMtools. Read groups including library ID, platform and platform unit were added to each alignment within the BAM files using Picard. Unifiedgenotyper from GATK3.6 (DePristo et al. 2011) was used to call variants with quality scores above 10. Quality scores between 10 and 30 were marked as low quality. Variants with a read depth of less than two were filtered using GATK3.6 variantfiltration and subsequently replaced as missing data. Low quality variants were removed via hard filtering when variants contained more than 25% missing data, more than one nucleotide, or the minor allele was less than 1%. Genotypes with more than 90% missing data were removed. SNPs with missing data were imputed using fastPHASE. The output file was converted to a hmp file for distribution. Lines were phenotyped using the seedling straw test method proposed by Arkwazee and Myers (2017). The plants were scored four days after inoculation using the disease severity scale described in the protocol. Lines were considered resistant with values from 1 to 3, intermediate with a value of 4, and susceptible with values from 5 to 9. Adjusted means (least square means) were calculated using a linear mixed model in which genotypes were considered fixed effects and reps, blocks, and samples were considered random effects.Funding for this dataset was provided by USDA, Agricultural Research Service (USDA-ARS) through the National Sclerotinia Initiative, Agreement No. 58-3060-9-037 and Northarvest Bean Growers Association

Identification and Validation of a New Source of Low Grain Cadmium Accumulation in Durum Wheat

Cadmium (Cd) is a heavy metal that has no known biological function and is toxic for many living organisms. The maximum level of Cd concentration allowed in the international market for wheat grain is 0.2 mg kg−1. Because phenotyping for Cd uptake is expensive and time consuming, molecular markers associated with genes conferring low Cd uptake would expedite selection and lead to the development of durum cultivars with reduced Cd concentrations. Here, we identified single nucleotide polymorphisms (SNPs) associated with a novel low Cd uptake locus in the durum experimental line D041735, which has hexaploid common wheat in its pedigree. Genetic analysis revealed a single major QTL for Cd uptake on chromosome arm 5BL within a 0.3 cM interval flanked by SNP markers. Analysis of the intervening sequence revealed a gene with homology to an aluminum-induced protein as a candidate gene. Validation and allelism tests revealed that the low Cd uptake gene identified in this study is different from the closely linked Cdu1-B gene, which also resides on 5BL. This study therefore showed that the durum experimental line D041735 contains a novel low Cd uptake gene that was likely acquired from hexaploid wheat

Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments

The genetic improvement of economically important production traits of dry bean (Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized Bean Abiotic Stress Evaluation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs. Includes Corrigendu

Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments

The genetic improvement of economically important production traits of dry bean (Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized Bean Abiotic Stress Evaluation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs