Marie-Laure Pilet-Nayel

Partial resistance of Medicago truncatula to Aphanomyces euteiches is associated with protection of the root stele and is controlled by a major QTL rich in proteasome-related genes.

A pathosystem between Aphanomyces euteiches, the causal agent of pea root rot disease, and the model legume Medicago truncatula was developed to gain insights into mechanisms involved in resistance to this oomycete. The F83005.5 French accession and the A17-Jemalong reference line, susceptible and partially resistant, respectively, to A. euteiches, were selected for further cytological and genetic analyses. Microscopy analyses of thin root sections revealed that a major difference between the two inoculated lines occurred in the root stele, which remained pathogen free in A17. Striking features were observed in A17 roots only, including i) frequent pericycle cell divisions, ii) lignin deposition around the pericycle, and iii) accumulation of soluble phenolic compounds. Genetic analysis of resistance was performed on an F7 population of 139 recombinant inbred lines and identified a major quantitative trait locus (QTL) near the top of chromosome 3. A second study, with near-isogenic line responses to A. euteiches confirmed the role of this QTL in expression of resistance. Fine-mapping allowed the identification of a 135-kb sequenced genomic DNA region rich in proteasome-related genes. Most of these genes were shown to be induced only in inoculated A17. Novel mechanisms possibly involved in the observed partial resistance are proposed.

SNP discovery and genetic mapping using genotyping by sequencing of whole genome genomic DNA from a pea RIL population

BackgroundProgress in genetics and breeding in pea still suffers from the limited availability of molecular resources. SNP markers that can be identified through affordable sequencing processes, without the need for prior genome reduction or a reference genome to assemble sequencing data would allow the discovery and genetic mapping of thousands of molecular markers. Such an approach could significantly speed up genetic studies and marker assisted breeding for non-model species.ResultsA total of 419,024 SNPs were discovered using HiSeq whole genome sequencing of four pea lines, followed by direct identification of SNP markers without assembly using the discoSnp tool. Subsequent filtering led to the identification of 131,850 highly designable SNPs, polymorphic between at least two of the four pea lines.A subset of 64,754 SNPs was called and genotyped by short read sequencing on a subpopulation of 48 RILs from the cross ‘Baccara’ x ‘PI180693’. This data was used to construct a WGGBS-derived pea genetic map comprising 64,263 markers. This map is collinear with previous pea consensus maps and therefore with the Medicago truncatula genome. Sequencing of four additional pea lines showed that 33 % to 64 % of the mapped SNPs, depending on the pairs of lines considered, are polymorphic and can therefore be useful in other crosses.The subsequent genotyping of a subset of 1000 SNPs, chosen for their mapping positions using a KASP™ assay, showed that almost all generated SNPs are highly designable and that most (95 %) deliver highly qualitative genotyping results. Using rather low sequencing coverages in SNP discovery and in SNP inferring did not hinder the identification of hundreds of thousands of high quality SNPs.ConclusionsThe development and optimization of appropriate tools in SNP discovery and genetic mapping have allowed us to make available a massive new genomic resource in pea. It will be useful for both fine mapping within chosen QTL confidence intervals and marker assisted breeding for important traits in pea improvement.

Development of two major resources for pea genomics: the GenoPea 13.2K SNP Array and a high‐density, high‐resolution consensus genetic map

Single 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.

Genomic Tools in Pea Breeding Programs: Status and Perspectives

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 Mendels 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.

Genome-wide association mapping of partial resistance to Aphanomyces euteiches in pea

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.

Quantitative Resistance to Plant Pathogens in Pyramiding Strategies for Durable Crop Protection

Quantitative resistance has gained interest in plant breeding for pathogen control in low-input cropping systems. Although quantitative resistance frequently has only a partial effect and is difficult to select, it is considered more durable than major resistance (R) genes. With the exponential development of molecular markers over the past 20 years, resistance QTL have been more accurately detected and better integrated into breeding strategies for resistant varieties with increased potential for durability. This review summarizes current knowledge on the genetic inheritance, molecular basis, and durability of quantitative resistance. Based on this knowledge, we discuss how strategies that combine major R genes and QTL in crops can maintain the effectiveness of plant resistance to pathogens. Combining resistance QTL with complementary modes of action appears to be an interesting strategy for breeding effective and potentially durable resistance. Combining quantitative resistance with major R genes has proven to be a valuable approach for extending the effectiveness of major genes. In the plant genomics era, improved tools and methods are becoming available to better integrate quantitative resistance into breeding strategies. Nevertheless, optimal combinations of resistance loci will still have to be identified to preserve resistance effectiveness over time for durable crop protection.

Bean pod mottle virus: a new powerful tool for functional genomics studies in Pisum sativum.

Summary Pea (Pisum sativum L.) is an important legume worldwide. The importance of pea in arable rotations and nutritional value for both human and animal consumption have fostered sustained production and different studies to improve agronomic traits of interest. Moreover, complete sequencing of the pea genome is currently underway and will lead to the identification of a large number of genes potentially associated with important agronomic traits. Because stable genetic transformation is laborious for pea, virus‐induced gene silencing (VIGS) appears as a powerful alternative technology for determining the function of unknown genes. In this work, we present a rapid and efficient viral inoculation method using DNA infectious plasmids of Bean pod mottle virus (BPMV)‐derived VIGS vector. Six pea genotypes with important genes controlling biotic and/or abiotic stresses were found susceptible to BPMV carrying a GFP reporter gene and showed fluorescence in both shoots and roots. In a second step, we investigated 37 additional pea genotypes and found that 30 were susceptible to BPMV and only 7 were resistant. The capacity of BPMV to induce silencing of endogenes was investigated in the most susceptible genotype using two visual reporter genes: PsPDS and PsKORRIGAN1 (PsKOR1) encoding PHYTOENE DESATURASE and a 1,4‐β‐D‐glucanase, respectively. The features of the ‘one‐step’ BPMV‐derived VIGS vector include (i) the ease of rub‐inoculation, without any need for biolistic or agro‐inoculation procedures, (ii) simple cost‐effective procedure and (iii) noninterference of viral symptoms with silencing. These features make BPMV the most adapted VIGS vector in pea to make low‐ to high‐throughput VIGS studies.

Comparative Genome-Wide-Association Mapping Identifies Common Loci Controlling Root System Architecture and Resistance to Aphanomyces euteiches in Pea

Combining plant genetic resistance with architectural traits that are unfavorable to disease development is a promising strategy for reducing epidemics. However, few studies have identified root system architecture (RSA) traits with the potential to limit root disease development. Pea is a major cultivated legume worldwide and has a wide level of natural genetic variability for plant architecture. The root pathogen Aphanomyces euteiches is a major limiting factor of pea crop yield. This study aimed to increase the knowledge on the diversity of loci and candidate genes controlling RSA traits in pea and identify RSA genetic loci associated with resistance to A. euteiches which could be combined with resistance QTL in breeding. A comparative genome wide association (GWA) study of plant architecture and resistance to A. euteiches was conducted at the young plant stage in a collection of 266 pea lines contrasted for both traits. The collection was genotyped using 14,157 SNP markers from recent pea genomic resources. It was phenotyped for ten root, shoot and overall plant architecture traits, as well as three disease resistance traits in controlled conditions, using image analysis. We identified a total of 75 short-size genomic intervals significantly associated with plant architecture and overlapping with 46 previously detected QTL. The major consistent intervals included plant shoot architecture or flowering genes (PsLE, PsTFL1) with putative pleiotropic effects on root architecture. A total of 11 genomic intervals were significantly associated with resistance to A. euteiches confirming several consistent previously identified major QTL. One significant SNP, mapped to the major QTL Ae-Ps7.6, was associated with both resistance and RSA traits. At this marker, the resistance-enhancing allele was associated with an increased total root projected area, in accordance with the correlation observed between resistance and larger root systems in the collection. Seven additional intervals associated with plant architecture overlapped with GWA intervals previously identified for resistance to A. euteiches. This study provides innovative results about genetic interdependency of root disease resistance and RSA inheritance. It identifies pea lines, QTL, closely-linked markers and candidate genes for marker-assisted-selection of RSA loci to reduce Aphanomyces root rot severity in future pea varieties.