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Although seed and pod traits are important for peanut breeding, little is known about the inheritance of these traits. A recombinant inbred line (RIL) population of 156 lines from a cross of Tifrunner x NC 3033 was genotyped with the Axiom_Arachis1 SNP array and SSRs to generate a genetic map composed of 1524 markers in 29 linkage groups (LG). The genetic positions of markers were compared with their physical positions on the peanut genome to confirm the validity of the linkage map and explore the distribution of recombination and potential chromosomal rearrangements. This linkage map was then used to identify Quantitative Trait Loci (QTL) for seed and pod traits that were phenotyped over three consecutive years for the purpose of developing trait-associated markers for breeding. Forty-nine QTL were identified in 14 LG for seed size index, kernel percentage, seed weight, pod weight, single-kernel, double-kernel, pod area and pod density. Twenty QTL demonstrated phenotypic variance explained (PVE) greater than 10% and eight more than 20%. Of note, seven of the eight major QTL for pod area, pod weight and seed weight (PVE >20% variance) were attributed to NC 3033 and located in a single linkage group, LG B06_1. In contrast, the most consistent QTL for kernel percentage were located on A07/B07 and derived from Tifrunner.

Blanchability is an often overlooked, but important trait for peanut breeding. The process of blanching, removing the skin, is an important step in the processing of raw nuts for manufacturing. Under strong genetic control and requiring considerable effort to phenotype, blanchability is conducive for marker-assisted selection. We used QTL sequencing (QTL-seq) to identify two QTLs related to blanchability using previously phenotyped breeding populations. To validate the QTLs, we show that two markers can select for significantly increased blanchability in an independent recombinant inbred line (RIL) population. Two wild introgressions from Arachis cardenasii conferring strong disease resistance were segregated in the population and were found to negatively impact blanchability. Finally, we show that by utilizing highly accurate sequence analysis pipelines, low coverage sequencing can be used to genotype whole populations with increased power and precision. This study highlights the potential to mine breeding data to identify and develop useful markers for genetic improvement programs, and provide powerful tools for breeding for processing and quality traits.

Next Generation sequencing was a step change for molecular genetics and genomics. Illumina sequencing in particular still provides substantial value to animal and plant genomics. A simple yet powerful technique, referred to as QTL sequencing (QTL-seq) is susceptible to high levels of noise due to ambiguity of alignment of short reads in complex regions of the genome. This noise is particularly high when working with polyploid and/or outcrossing crop species, which impairs the efficacy of QTL-seq in identifying functional variation. By filtering loci based on the optimal alignment of short reads, we have developed a pipeline, named Khufu, that substantially improves the accuracy of QTL-seq analysis in complex genomes, allowing de novo variant discovery directly from bulk sequence. We first demonstrate the pipeline by identifying and validating loci contributing to blanching percentage in peanut using lines from multiple related populations. Using other published datasets in peanut, Brassica rapa, Hordeum volgare, Lactua satvia, and Felis catus, we demonstrate that Khufu produces more accurate results straight from bulk sequence. Khufu works across species, genome ploidy level, and data types. In cases where identified QTL were fine mapped, the fine mapped region corresponds to the top of the peak identified by Khufu. The accuracy of Khufu allows the analysis of population sequencing at very low coverage (

A total of 33 additive stem rot QTLs were identified in peanut genome with nine of them consistently detected in multiple years or locations. And 12 pairs of epistatic QTLs were firstly reported for peanut stem rot disease. Stem rot in peanut (Arachis hypogaea) is caused by the Sclerotium rolfsii and can result in great economic loss during production. In this study, a recombinant inbred line population from the cross between NC 3033 (stem rot resistant) and Tifrunner (stem rot susceptible) that consists of 156 lines was genotyped by using 58 K peanut single nucleotide polymorphism (SNP) array and phenotyped for stem rot resistance at multiple locations and in multiple years. A linkage map consisting of 1451 SNPs and 73 simple sequence repeat (SSR) markers was constructed. A total of 33 additive quantitative trait loci (QTLs) for stem rot resistance were detected, and six of them with phenotypic variance explained of over 10% (qSR.A01-2, qSR.A01-5, qSR.A05/B05-1, qSR.A05/B05-2, qSR.A07/B07-1 and qSR.B05-1) can be consistently detected in multiple years or locations. Besides, 12 pairs of QTLs with epistatic (additive × additive) interaction were identified. An additive QTL qSR.A01-2 also with an epistatic effect interacted with a novel locus qSR.B07_1-1 to affect the percentage of asymptomatic plants in a row. A total of 193 candidate genes within 38 stem rot QTLs intervals were annotated with functions of biotic stress resistance such as chitinase, ethylene-responsive transcription factors and pathogenesis-related proteins. The identified stem rot resistance QTLs, candidate genes, along with the associated SNP markers in this study, will benefit peanut molecular breeding programs for improving stem rot resistance.

Common beans are an important food legume faced with a series of abiotic stresses the most severe of which is drought. The crop is interesting as a model for the analysis of gene phylogenies due to its domestication process, race structure, and origins in a group of wild common beans found along the South American Andes and the region of Mesoamerica. Meanwhile, the DREB2 transcription factors have been implicated in controlling non-ABA dependent responses to drought stress. With this in mind our objective was to study in depth the genetic diversity for two DREB2 genes as possible candidates for association with drought tolerance through a gene phylogenetic analysis. In this genetic diversity assessment, we analyzed nucleotide diversity at the two candidate genes Dreb2A and Dreb2B, in partial core collections of 104 wild and 297 cultivated common beans with a total of 401 common bean genotypes from world-wide germplasm analyzed. Our wild population sample covered a range of semi-mesic to very dry habitats, while our cultivated samples presented a wide spectrum of low to high drought tolerance. Both genes showed very different patterns of nucleotide variation. Dreb2B exhibited very low nucleotide diversity relative to neutral reference loci previously surveyed in these populations. This suggests that strong purifying selection has been acting on this gene. In contrast, Dreb2A exhibited higher levels of nucleotide diversity, which is indicative of adaptive selection and population expansion. These patterns were more distinct in wild compared to cultivated common beans. These approximations suggested the importance of Dreb2 genes in the context of drought tolerance, and constitute the first steps towards an association study between genetic polymorphism of this gene family and variation in drought tolerance traits. We discuss the utility of allele mining in the DREB gene family for the discovery of new drought tolerance traits from wild common bean.

Common bean architecture is in part determined by the determinacy gene fin which can affect yield potential and adaptation to various environments and has many known effects in temperate regions. Tropical adaptation, meanwhile, requires adaptation to rainy and dry seasons where heat and drought stress are major problems. The goal of this research was to determine the effect of the fin gene on plants grown under heat, drought and non-stress conditions in the tropics and to identify quantitative trait loci (QTL) for architectural, phenological and yield traits related to fin in an inter-genepool population derived from a cross between an indeterminate Mesoamerican genotype with erect architecture (A55) and a determinate Andean genotype with heat tolerance (G122). The population was evaluated in four experiments conducted in a tropical location across two rainy seasons and across dry season drought stress and dry season irrigated treatments. A total of 71 SSR loci and 245 AFLP, RAPD, seed protein or phenotypic markers were integrated together into a genetic map with a total distance of 982.8 cM. A total of 36 QTL were identified based on the evaluation of six phenotypic variables differentiating the parents. The A55 parent was high yielding under all conditions; while G122 was confirmed to be resistant to high temperatures, but not to drought. Some QTL for yield were associated with erect growth alleles inherited from the indeterminate parent and were located on linkage group b01 near the fin locus while other QTL for seed weight were found across the genome.

Microsatellite markers or simple sequence repeat (SSR) loci are useful for diversity characterization and genetic–physical mapping. Different in silico microsatellite search methods have been developed for mining bacterial artifi cial chromosome (BAC) end sequences for SSRs. The overall goal of this study was genome characterization based on SSRs in 89,017 BAC end sequences (BESs) from the G19833 common bean ( Phaseolus vulgaris L.) library. Another objective was to identify new SSR taking into account three tandem motif identifi cation programs (Automated Microsatellite Marker Development [AMMD], Tandem Repeats Finder [TRF], and SSRLocator [SSRL]). Among the microsatellite search engines, SSRL identifi ed the highest number of SSRs; however, when primer design was attempted, the number dropped due to poor primer design regions. Automated Microsatellite Marker Development software identifi ed many SSRs with valuable AT/TA or AG/TC motifs, while TRF found fewer SSRs and produced no primers. A subgroup of 323 AT-rich, di-, and trinucleotide SSRs were selected from the AMMD results and used in a parental survey with DOR364 and G19833, of which 75 could be mapped in the corresponding population; these represented 4052 BAC clones. Together with 92 previously mapped BES- and 114 non-BES-derived markers, a total of 280 SSRs were included in the polymerase chain reaction (PCR)-based map, integrating a total of 8232 BAC clones in 162 contigs from the physical map.

Background The abscisic acid (ABA) pathway plays an important role in the plants’ reaction to drought stress and ABA-stress response (Asr) genes are important in controlling this process. In this sense, we accessed nucleotide diversity at two candidate genes for drought tolerance (Asr1 and Asr2), involved in an ABA signaling pathway, in the reference collection of cultivated common bean (Phaseolus vulgaris L.) and a core collection of wild common bean accessions. Results Our wild population samples covered a range of mesic (semi-arid) to very dry (desert) habitats, while our cultivated samples presented a wide spectrum of drought tolerance. Both genes showed very different patterns of nucleotide variation. Asr1 exhibited very low nucleotide diversity relative to the neutral reference loci that were previously surveyed in these populations. This suggests that strong purifying selection has been acting on this gene. In contrast, Asr2 exhibited higher levels of nucleotide diversity, which is indicative of adaptive selection. These patterns were more notable in wild beans than in cultivated common beans indicting that natural selection has played a role over long time periods compared to farmer selection since domestication. Conclusions Together these results suggested the importance of Asr1 in the context of drought tolerance, and constitute the first steps towards an association study between genetic polymorphism of this gene family and variation in drought tolerance traits. Furthermore, one of our major successes was to find that wild common bean is a reservoir of genetic variation and selection signatures at Asr genes, which may be useful for breeding drought tolerance in cultivated common bean.

Background Common bean (Phaseolus vulgaris L.) is the most important legume for direct human consumption and the goal of this study was to integrate a recently constructed physical map for the species with a microsatellite based genetic map using a BAC library from the genotype G19833 and the recombinant inbred line population DOR364 × G19833. Results We searched for simple sequence repeats (SSRs) in the 89,017 BAC-end sequences (BES) from the physical map and genetically mapped any polymorphic BES-SSRs onto the genetic map. Among the BES it was possible to identify 623 contig-linked SSRs, most of which were highly AT-rich. A subgroup of 230 di-nucleotide and tri-nucleotide based SSR primer pairs from these BACs was tested on the mapping parents with 176 single copy loci and 114 found to be polymorphic markers. Of these, 99 were successfully integrated into the genetic map. The 99 linkages between the genetic and physical maps corresponded to an equal number of contigs containing a total of 5,055 BAC clones. Conclusions Class II microsatellites were more common in the BES than longer class I microsatellites. Both types of markers proved to be valuable for linking BAC clones to the genetic map and were successfully placed across all 11 linkage groups. The integration of common bean physical and genetic maps is an important part of comparative genome analysis and a prelude to positional cloning of agronomically important genes for this crop.

Late leaf spot (LLS; Cercosporidium personatum) is a major fungal disease of cultivated peanut (Arachis hypogaea). A recombinant inbred line population segregating for quantitative field resistance was used to identify quantitative trait loci (QTL) using QTL-seq. High rates of false positive SNP calls using established methods in this allotetraploid crop obscured significant QTLs. To resolve this problem, robust parental SNPs were first identified using polyploid-specific SNP identification pipelines, leading to discovery of significant QTLs for LLS resistance. These QTLs were confirmed over 4 years of field data. Selection with markers linked to these QTLs resulted in a significant increase in resistance, showing that these markers can be immediately applied in breeding programs. This study demonstrates that QTL-seq can be used to rapidly identify QTLs controlling highly quantitative traits in polyploid crops with complex genomes. Markers identified can then be deployed in breeding programs, increasing the efficiency of selection using molecular tools. Key Message: Field resistance to late leaf spot is a quantitative trait controlled by many QTLs. Using polyploid-specific methods, QTL-seq is faster and more cost effective than QTL mapping.

Background Among abiotic stresses, drought is the most common reducer of crop yields. The slow-wilting soybean genotype PI 416937 is somewhat robust to water deficit and has been used previously to map the trait in a bi-parental population. Since drought stress response is a complex biological process, whole genome transcriptome analysis was performed to obtain a deeper understanding of the drought response in soybean. Results Contrasting data from PI 416937 and the cultivar ‘Benning’, we developed a classification system to identify genes that were either responding to water-deficit in both genotypes or that had a genotype x environment (GxE) response. In spite of very different wilting phenotypes, 90% of classifiable genes had either constant expression in both genotypes (33%) or very similar response profiles (E genes, 57%). By further classifying E genes based on expression profiles, we were able to discern the functional specificity of transcriptional responses at particular stages of water-deficit, noting both the well-known reduction in photosynthesis genes as well as the less understood up-regulation of the protein transport pathway. Two percent of classifiable genes had a well-defined GxE response, many of which are located within slow-wilting QTLs. We consider these strong candidates for possible causal genes underlying PI 416937’s unique drought avoidance strategy. Conclusions There is a general and functionally significant transcriptional response to water deficit that involves not only known pathways, such as down-regulation of photosynthesis, but also up-regulation of protein transport and chromatin remodeling. Genes that show a genotypic difference are more likely to show an environmental response than genes that are constant between genotypes. In this study, at least five genes that clearly exhibited a genotype x environment response fell within known QTL and are very good candidates for further research into slow-wilting. Electronic supplementary material The online version of this article (doi:10.1186/s12870-015-0422-8) contains supplementary material, which is available to authorized users.