Mapping resistance to Sclerotinia white mold in two pinto bean recombinant inbred line populations.

White mold, caused by the fungus Sclerotinia sclerotiorum (Lib.) de Bary, is a devastating disease affecting common bean (Phaseolus vulgaris L.) production worldwide.

Agile Genetics: Single gene resolution without the fuss.

Gene discovery reveals new biology, expands the utility of marker-assisted selection, and enables targeted mutagenesis. Still, such discoveries can take over a decade. We present a general strategy, "Agile Genetics," that uses nested, structured populations to overcome common limits on gene resolution.

Aspergillus flavus pangenome (AflaPan) uncovers novel aflatoxin and secondary metabolite associated gene clusters.

Background: Aspergillus flavus is an important agricultural and food safety threat due to its production of carcinogenic aflatoxins. It has high level of genetic diversity that is adapted to various environments. Recently, we reported two reference genomes of A.

Integrating de novo QTL-seq and linkage mapping to identify quantitative trait loci conditioning physiological resistance and avoidance to white mold disease in dry bean.

White mold (WM), caused by the ubiquitous fungus Sclerotinia sclerotiorum, is a devastating disease that limits production and quality of dry bean globally. In the present study, classic linkage mapping combined with QTL-seq were employed in two recombinant inbred line (RIL) populations, "Montrose"/I9365-25 (M25) and "Raven"/I9365-31 (R31), with the initial goal of fine-mapping QTL WM5.4 and WM7.

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

White mold (WM) is a major disease in common bean ( L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.

Two New Reference Genomes Reveal a Large Insertion Potentially Contributing to Isolate Stress Tolerance and Aflatoxin Production.

Efforts in genome sequencing in the genus have led to the development of quality reference genomes for several important species including , , and However, less progress has been made for As part of the effort of the USDA-ARS Annual Aflatoxin Workshop Fungal Genome Project, the isolate NRRL3357 was sequenced and resulted in a scaffold-level genome released in 2005. Our goal has been biologically driven, focusing on two areas: isolate variation in aflatoxin production and drought stress exacerbating aflatoxin production by Therefore, we developed two reference pseudomolecule genome assemblies derived from chromosome arms for two isolates: AF13, a MAT1-2, highly stress tolerant, and highly aflatoxigenic isolate; and NRRL3357, a MAT1-1, less stress tolerant, and moderate aflatoxin producer in comparison to AF13. Here, we report these two reference-grade assemblies for these isolates through a combination of PacBio long-read sequencing and optical mapping, and coupled them with comparative, functional, and phylogenetic analyses.

The genome sequence of segmental allotetraploid peanut Arachis hypogaea.

Like many other crops, the cultivated peanut (Arachis hypogaea L.) is of hybrid origin and has a polyploid genome that contains essentially complete sets of chromosomes from two ancestral species. Here we report the genome sequence of peanut and show that after its polyploid origin, the genome has evolved through mobile-element activity, deletions and by the flow of genetic information between corresponding ancestral chromosomes (that is, homeologous recombination).

Machine Learning as an Effective Method for Identifying True Single Nucleotide Polymorphisms in Polyploid Plants.

Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid species is difficult. Peanut ( L.

Crossword: A data-driven simulation language for the design of genetic-mapping experiments and breeding strategies.

Quantitative genetic simulations can save time and resources by optimizing the logistics of an experiment. Current tools are difficult to use by those unfamiliar with programming, and these tools rarely address the actual genetic structure of the population under study. Here, we introduce crossword, which utilizes the widely available re-sequencing and genomics data to create more realistic simulations and to reduce user burden.

Haplotype-Based Genotyping in Polyploids.

Accurate identification of polymorphisms from sequence data is crucial to unlocking the potential of high throughput sequencing for genomics. Single nucleotide polymorphisms (SNPs) are difficult to accurately identify in polyploid crops due to the duplicative nature of polyploid genomes leading to low confidence in the true alignment of short reads. Implementing a haplotype-based method in contrasting subgenome-specific sequences leads to higher accuracy of SNP identification in polyploids.

Insight into Genes Regulating Postharvest Aflatoxin Contamination of Tetraploid Peanut from Transcriptional Profiling.

Postharvest aflatoxin contamination is a challenging issue that affects peanut quality. Aflatoxin is produced by fungi belonging to the Aspergilli group, and is known as an acutely toxic, carcinogenic, and immune-suppressing class of mycotoxins. Evidence for several host genetic factors that may impact aflatoxin contamination has been reported, , genes for lipoxygenase (PnLOX1 and PnLOX2/PnLOX3 that showed either positive or negative regulation with infection), reactive oxygen species, and WRKY (highly associated with or differentially expressed upon infection of maize with ); however, their roles remain unclear.

Genotypic Regulation of Aflatoxin Accumulation but Not Aspergillus Fungal Growth upon Post-Harvest Infection of Peanut (Arachis hypogaea L.) Seeds.

Aflatoxin contamination is a major economic and food safety concern for the peanut industry that largely could be mitigated by genetic resistance. To screen peanut for aflatoxin resistance, ten genotypes were infected with a green fluorescent protein (GFP)-expressing strain. Percentages of fungal infected area and fungal GFP signal intensity were documented by visual ratings every 8 h for 72 h after inoculation.