SUMMARYSingle nucleotide polymorphism (SNP) arrays represent important genotyping tools for innovative strategies in both basic research and applied breeding. Pea is an important food, feed and sustainable crop with a large (about 4.45 Gbp) but not yet available genome sequence. In the present study, 12 pea recombinant inbred line populations were genotyped using the newly developed GenoPea 13.2K SNP Array. Individual and consensus genetic maps were built providing insights into the structure and organization of the pea genome. Largely collinear genetic maps of 3918-8503 SNPs were obtained from all mapping populations, and only two of these exhibited putative chromosomal rearrangement signatures. Similar distortion patterns in different populations were noted. A total of 12 802 transcript-derived SNP markers placed on a 15 079-marker high-density, high-resolution consensus map allowed the identification of ohnologue-rich regions within the pea genome and the localization of local duplicates. Dense syntenic networks with sequenced legume genomes were further established, paving the way for the identification of the molecular bases of important agronomic traits segregating in the mapping populations. The information gained on the structure and organization of the genome from this research will undoubtedly contribute to the understanding of the evolution of the pea genome and to its assembly. The GenoPea 13.2K SNP Array and individual and consensus genetic maps are valuable genomic tools for plant scientists to strengthen pea as a model for genetics and physiology and enhance breeding.

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BackgroundGenome-wide association (GWA) mapping has recently emerged as a valuable approach for refining the genetic basis of polygenic resistance to plant diseases, which are increasingly used in integrated strategies for durable crop protection. Aphanomyces euteiches is a soil-borne pathogen of pea and other legumes worldwide, which causes yield-damaging root rot. Linkage mapping studies reported quantitative trait loci (QTL) controlling resistance to A. euteiches in pea. However the confidence intervals (CIs) of these QTL remained large and were often linked to undesirable alleles, which limited their application in breeding. The aim of this study was to use a GWA approach to validate and refine CIs of the previously reported Aphanomyces resistance QTL, as well as identify new resistance loci.MethodsA pea-Aphanomyces collection of 175 pea lines, enriched in germplasm derived from previously studied resistant sources, was evaluated for resistance to A. euteiches in field infested nurseries in nine environments and with two strains in climatic chambers. The collection was genotyped using 13,204 SNPs from the recently developed GenoPea Infinium® BeadChip.ResultsGWA analysis detected a total of 52 QTL of small size-intervals associated with resistance to A. euteiches, using the recently developed Multi-Locus Mixed Model. The analysis validated six of the seven previously reported main Aphanomyces resistance QTL and detected novel resistance loci. It also provided marker haplotypes at 14 consistent QTL regions associated with increased resistance and highlighted accumulation of favourable haplotypes in the most resistant lines. Previous linkages between resistance alleles and undesired late-flowering alleles for dry pea breeding were mostly confirmed, but the linkage between loci controlling resistance and coloured flowers was broken due to the high resolution of the analysis. A high proportion of the putative candidate genes underlying resistance loci encoded stress-related proteins and others suggested that the QTL are involved in diverse functions.ConclusionThis study provides valuable markers, marker haplotypes and germplasm lines to increase levels of partial resistance to A. euteiches in pea breeding.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2429-4) contains supplementary material, which is available to authorized users.

Pea is an important food and feed crop and a valuable component of low-input farming systems. Improving resistance to biotic and abiotic stresses is a major breeding target to enhance yield potential and regularity. Genomic selection (GS) has lately emerged as a promising technique to increase the accuracy and gain of marker-based selection. It uses genome-wide molecular marker data to predict the breeding values of candidate lines to selection. A collection of 339 genetic resource accessions (CRB339) was subjected to high-density genotyping using the GenoPea 13.2K SNP Array. Genomic prediction accuracy was evaluated for thousand seed weight (TSW), the number of seeds per plant (NSeed), and the date of flowering (BegFlo). Mean cross-environment prediction accuracies reached 0.83 for TSW, 0.68 for NSeed, and 0.65 for BegFlo. For each trait, the statistical method, the marker density, and/or the training population size and composition used for prediction were varied to investigate their effects on prediction accuracy: the effect was large for the size and composition of the training population but limited for the statistical method and marker density. Maximizing the relatedness between individuals in the training and test sets, through the CDmean-based method, significantly improved prediction accuracies. A cross-population cross-validation experiment was further conducted using the CRB339 collection as a training population set and nine recombinant inbred lines populations as test set. Prediction quality was high with mean Q2 of 0.44 for TSW and 0.59 for BegFlo. Results are discussed in the light of current efforts to develop GS strategies in pea.

Pea (Pisum sativum L.) is an annual cool-season legume and one of the oldest domesticated crops. Dry pea seeds contain 22–25% protein, complex starch and fiber constituents, and a rich array of vitamins, minerals, and phytochemicals which make them a valuable source for human consumption and livestock feed. Dry pea ranks third to common bean and chickpea as the most widely grown pulse in the world with more than 11 million tons produced in 2013. Pea breeding has achieved great success since the time of Mendel's experiments in the mid-1800s. However, several traits still require significant improvement for better yield stability in a larger growing area. Key breeding objectives in pea include improving biotic and abiotic stress resistance and enhancing yield components and seed quality. Taking advantage of the diversity present in the pea genepool, many mapping populations have been constructed in the last decades and efforts have been deployed to identify loci involved in the control of target traits and further introgress them into elite breeding materials. Pea now benefits from next-generation sequencing and high-throughput genotyping technologies that are paving the way for genome-wide association studies and genomic selection approaches. This review covers the significant development and deployment of genomic tools for pea breeding in recent years. Future prospects are discussed especially in light of current progress toward deciphering the pea genome.

faba bean (Vicia faba L.) is a pulse crop of high nutritional value and high importance for sustainable agriculture and soil protection. With the objective of identifying gene-based Snps, transcriptome sequencing was performed in order to reduce faba bean genome complexity. A set of 1,819 genebased Snp markers polymorphic in three recombinant line populations was selected to enable the construction of a high-density consensus genetic map encompassing 1,728 markers well distributed in six linkage groups and spanning 1,547.71 cM with an average inter-marker distance of 0.89 cM. orthology-based comparison of the faba bean consensus map with legume genome assemblies highlighted synteny patterns that partly reflected the phylogenetic relationships among species. Solid blocks of macrosynteny were observed between faba bean and the most closely-related sequenced legume species such as pea, barrel medic or chickpea. Numerous blocks could also be identified in more divergent species such as common bean or cowpea. the genetic tools developed in this work can be used in association mapping, genetic diversity, linkage disequilibrium or comparative genomics and provide a backbone for map-based cloning. This will make the identification of candidate genes of interest more efficient and will accelerate marker-assisted selection (MAS) and genomic-assisted breeding (GAB) in faba bean.Legume crops serve as a source of food and feed. They also play an important role in sustainable agriculture because of their ability to improve soil fertility by fixing atmospheric nitrogen and increasing crop yield when used in crop rotation with cereals or intercropping 1 . In particular, faba bean (Vicia faba L.; Vf) is a primary ingredient of daily meals in both developing and industrialized countries due to its high content in proteins, carbohydrates, dietary fibers and micronutrients 2,3 . It is the most yielding pulse crop after field pea. However, its yield is still about half that of wheat, indicating that great breeding efforts are still needed 4 . Faba bean yield is greatly affected by environmental conditions, especially extreme temperatures, drought and acidity 5,6 . In addition, diseases such as chocolate spot (Botrytis fabae S. or B. cinerea P.) or ascochyta blight (Ascochyta fabae S.), viruses such as faba bean necrotic viruses, parasitic weeds of Orobanche genus and pests such as leaf weevil (Sitona lineatus L.), aphids (Aphis fabae S., A. craccivora K., Acyrthosiphon pisum H., Myzus persicae S.) or seed weevils (Bruchus rufimanus B.) considerably reduce its yield and affect the commercialization of the grains 5,7 . Other factors limiting the production of faba bean include the overproduction of flowers resulting in a variable fertilization

Increasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia faba L.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13 Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the improvement of sustainable protein production across the Mediterranean, subtropical and northern temperate agroecological zones.

BackgroundFreezing provokes severe yield losses to different fall-sown annual legumes. Understanding the molecular bases of freezing tolerance is of great interest for breeding programs. Medicago truncatula Gaertn. is an annual temperate forage legume that has been chosen as a model species for agronomically and economically important legume crops. The present study aimed to identify positional candidate genes for a major freezing tolerance quantitative trait locus that was previously mapped to M. truncatula chromosome 6 (Mt-FTQTL6) using the LR3 population derived from a cross between the freezing-tolerant accession F83005-5 and the freezing-sensitive accession DZA045-5.ResultsThe confidence interval of Mt-FTQTL6 was narrowed down to the region comprised between markers MTIC153 and NT6054 using recombinant F7 and F8 lines. A bacterial-artificial chromosome (BAC) clone contig map was constructed in an attempt to close the residual assembly gap existing therein. Twenty positional candidate genes including twelve C-repeat binding factor (CBF)/dehydration-responsive element binding factor 1 (DREB1) genes were identified from BAC-derived sequences and whole-genome shotgun sequences (WGS). CBF/DREB1 genes are organized in a tandem array within an approximately 296-Kb region. Eleven CBF/DREB1 genes were isolated and sequenced from F83005-5 and DZA045-5 which revealed high polymorphism among these accessions. Unique features characterizing CBF/DREB1 genes from M. truncatula, such as alternative splicing and large tandem duplication, are elucidated for the first time.ConclusionsOverall, twenty genes were identified as potential candidates to explain Mt-FTQTL6 effect. Their future functional characterization will uncover the gene(s) involved in freezing tolerance difference observed between F83005-5 and DZA045-5. Knowledge transfer for breeding improvement of crop legumes is expected. Furthermore, CBF/DREB1 related data will certainly have a large impact on research studies targeting this group of transcriptional activators in M. truncatula and other legume species.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-14-814) contains supplementary material, which is available to authorized users.