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Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms.

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 gene-based 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.

International audience; The French government has supported as part of its "Investments for the Future" program a 9-year research project, PeaMUST, devoted to pea and to a lesser extent, faba bean improvement. Focusing on the main causes of yield irregularity that limit pea and faba bean cultivation, an integrated approach, including molecular exploitation of the pea genome sequence, was applied to identify and incorporate favorable alleles and allele combinations in prebreeding material.

International audience; Plant-plant associations, notably cereal-legume intercropping, have been proposed in agroecology to better value resources and thus reduce the use of chemical inputs in agriculture. Wheat-pea intercropping allows to decreasing the use of nitrogen fertilization through ecological processes such as niche complementarity and facilitation. Rhizosphere microbial communities may account for these processes, since they play a major role in biogeochemical cycles and impact plant nutrition. Still, knowledge on the effect of intecropping on the rhizosphere microbiota remains scarce. Especially, it is an open question whether rhizosphere microbial communities in cereal-legume intercropping are the sum or not of the microbiota of each plant species cultivated in sole cropping. In the present study, we assessed the impact of wheat and pea in IC on the diversity and structure of their respective rhizosphere microbiota. For this purpose, several cultivars of wheat and pea were cultivated in sole and intercropping. Roots of wheat and pea were collected separately in intercropping for microbiota analyses to allow deciphering the effect of IC on the bacterial community of each plant species/cultivar tested. Our data confirmed the well-known specificity of the rhizosphere effect and further stress the differentiation of bacterial communities between pea genotypes (Hr and hr). As regards the intercropping effect, diversity and structure of the rhizosphere microbiota were comparable to sole cropping. However, a specific co-occurrence pattern in each crop rhizosphere due to intercropping was revealed through network analysis. Bacterial co-occurrence network of wheat rhizosphere in IC was dominated by OTUs belonging to Alphaproteobacteria, Bacteroidetes and Gammaproteobacteria. We also evidenced a common network found in both rhizosphere under IC, indicating the interaction between the plant species; this common network was dominated by Acidobacteria, Alphaproteobacteria, and Bacteroidetes, with three OTUs belonging to Acidobacteria, Betaproteobacteria and Chloroflexi that were identified as keystone taxa. These findings indicate more complex rhizosphere bacterial networks in intercropping. Possible implications of these conclusions are discussed in relation with the functioning of rhizosphere microbiota in intercropping accounting for its beneficial effects.

Genome-wide association study (GWAS) was conducted to identify loci associated with agronomic (days to flowering, days to maturity, plant height, seed yield and seed weight), seed morphology (shape and dimpling), and seed quality (protein, starch, and fiber concentrations) traits of field pea (Pisum sativum L.). A collection of 135 pea accessions from 23 different breeding programs in Africa (Ethiopia), Asia (India), Australia, Europe (Belarus, Czech Republic, Denmark, France, Lithuania, Netherlands, Russia, Sweden, Ukraine and United Kingdom), and North America (Canada and USA), was used for the GWAS. The accessions were genotyped using genotyping-by-sequencing (GBS). After filtering for a minimum read depth of five, and minor allele frequency of 0.05, 16,877 high quality SNPs were selected to determine marker-trait associations (MTA). The LD decay (LD1/2max,90) across the chromosomes varied from 20 to 80 kb. Population structure analysis grouped the accessions into nine subpopulations. The accessions were evaluated in multi-year, multi-location trials in Olomouc (Czech Republic), Fargo, North Dakota (USA), and Rosthern and Sutherland, Saskatchewan (Canada) from 2013 to 2017. Each trait was phenotyped in at least five location-years. MTAs that were consistent across multiple trials were identified. Chr5LG3_566189651 and Chr5LG3_572899434 for plant height, Chr2LG1_409403647 for lodging resistance, Chr1LG6_57305683 and Chr1LG6_366513463 for grain yield, Chr1LG6_176606388, Chr2LG1_457185, Chr3LG5_234519042 and Chr7LG7_8229439 for seed starch concentration, and Chr3LG5_194530376 for seed protein concentration were identified from different locations and years. This research identified SNP markers associated with important traits in pea that have potential for marker-assisted selection towards rapid cultivar improvement.

International audience; Pea (Pisum sativum L.) is an important source of dietary proteins. Nutrient recycling from leaves contributes to the accumulation of seed proteins and is a pivotal determinant of protein yields in this grain legume. The aim of this study was to unveil the transcriptional regulations occurring in pea leaves before the sharp decrease in chlorophyll breakdown. As a prelude to this study, a time-series analysis of N-15 translocation at the whole plant level was performed, which indicated that nitrogen recycling among organs was highly dynamic during this period and varied depending on nitrate availability. Leaves collected on vegetative and reproductive nodes were further analyzed by transcriptomics. The data revealed extensive transcriptome changes in leaves of reproductive nodes during early seed development (from flowering to 14 days after flowering), including an up-regulation of genes encoding transporters, and particularly of sulfate that might sustain sulfur metabolism in leaves of the reproductive part. This developmental period was also characterized by a down-regulation of cell wall-associated genes in leaves of both reproductive and vegetative nodes, reflecting a shift in cell wall structure. Later on, 27 days after flowering, genes potentially switching the metabolism of leaves toward senescence were pinpointed, some of which are related to ribosomal RNA processing, autophagy, or transport systems. Transcription factors differentially regulated in leaves between stages were identified and a gene co-expression network pointed out some of them as potential regulators of the above-mentioned biological processes. The same approach was conducted in Medicago truncatula to identify shared regulations with this wild legume species. Altogether the results give a global view of transcriptional events in leaves of legumes at early reproductive stages and provide a valuable resource of candidate genes that could be targeted by reverse genetics to improve nutrient remobilization and/or delay catabolic processes leading to senescence.

Whole genome profiling (WGP) is a sequence-based physical mapping technology and uses sequence tags generated by next generation sequencing for construction of bacterial artificial chromosome (BAC) contigs of complex genomes. The physical map provides a framework for assembly of genome sequence and information for localization of genes that are difficult to find through positional cloning. To address the challenges of accurate assembly of the pea genome (~4.2 GB of which approximately 85% is repetitive sequences), we have adopted the WGP technology for assembly of a pea BAC library. Multi-dimensional pooling of 295,680 BAC clones and sequencing the ends of restriction fragments of pooled DNA generated 1,814 million high quality reads, of which 825 million were deconvolutable to 1.11 million unique WGP sequence tags. These WGP tags were used to assemble 220,013 BACs into contigs. Assembly of the BAC clones using the modified Fingerprinted Contigs (FPC) program has resulted in 13,040 contigs, consisting of 213,719 BACs, and 6,294 singleton BACs. The average contig size is 0.33 Mbp and the N50 contig size is 0.62 Mbp. WGPTM technology has proved to provide a robust physical map of the pea genome, which would have been difficult to assemble using traditional restriction digestion based methods. This sequence-based physical map will be useful to assemble the genome sequence of pea. Additionally, the 1.1 million WGP tags will support efficient assignment of sequence scaffolds to the BAC clones, and thus an efficient sequencing of BAC pools with targeted genome regions of interest.

International audience; Pea forms symbiotic nodules with Rhizobium leguminosarum sv. viciae (Rlv). In the field, pea roots can be exposed to multiple compatible Rlv strains. Little is known about the mechanisms underlying the competitiveness for nodulation of Rlv strains and the ability of pea to choose between diverse compatible Rlv strains. The variability of pea-Rlv partner choice was investigated by co-inoculation with a mixture of five diverse Rlv strains of a 104-pea collection representative of the variability encountered in the genus Pisum. The nitrogen fixation efficiency conferred by each strain was determined in additional mono-inoculation experiments on a subset of 18 pea lines displaying contrasted Rlv choice. Differences in Rlv choice were observed within the pea collection according to their genetic or geographical diversities. The competitiveness for nodulation of a given pea-Rlv association evaluated in the multi-inoculated experiment was poorly correlated with its nitrogen fixation efficiency determined in mono-inoculation. Both plant and bacterial genetic determinants contribute to pea-Rlv partner choice. No evidence was found for co-selection of competitiveness for nodulation and nitrogen fixation efficiency. Plant and inoculant for an improved symbiotic association in the field must be selected not only on nitrogen fixation efficiency but also for competitiveness for nodulation.

Desgroux, Aurore;Baudais, Valentin N;Aubert, Veronique;Le Roy, Gwenola;de Larambergue, Henri;Miteul, Henri;Aubert, Gregoire;Boutet, Gilles;Duc, Gerard;Baranger, Alain;Burstin, Judith;Manzanares-Dauleux, Maria;Pilet-Nayel, Marie-Laure;Bourion, Virginie;Journal Article;Switzerland;Front Plant Sci. 2018 Jan 5;8:2195. doi: 10.3389/fpls.2017.02195. eCollection 2017.; International audience; 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.

LEAM, a late embryogenesis abundant protein, and HSP22, a small heat shock protein, were shown to accumulate in the mitochondria during pea (Pisum sativum L.) seed development, where they are expected to contribute to desiccation tolerance. Here, their expression was examined in seeds of 89 pea genotypes by Western blot analysis. All genotypes expressed LEAM and HSP22 in similar amounts. In contrast with HSP22, LEAM displayed different isoforms according to apparent molecular mass. Each of the 89 genotypes harboured a single LEAM isoform. Genomic and RT-PCR analysis revealed four LEAM genes differing by a small variable indel in the coding region. These variations were consistent with the apparent molecular mass of each isoform. Indels, which occurred in repeated domains, did not alter the main properties of LEAM. Structural modelling indicated that the class A α-helix structure, which allows interactions with the mitochondrial inner membrane in the dry state, was preserved in all isoforms, suggesting functionality is maintained. The overall results point out the essential character of LEAM and HSP22 in pea seeds. LEAM variability is discussed in terms of pea breeding history as well as LEA gene evolution mechanisms.

AGAP : équipe GE2pop; Improving nutritional seed quality is an important challenge in grain legume breeding. However, the genes controlling the differential accumulation of globulins, which are major contributors to seed nutritional value in legumes, remain largely unknown. We combined a search for protein quantity loci with genome-wide association studies on the abundance of 7S and 11S globulins in seeds of the model legume species Medicago truncatula. Identified genomic regions and genes carrying polymorphisms linked to globulin variations were then cross-compared with pea (Pisum sativum), leading to the identification of candidate genes for the regulation of globulin abundance in this crop. Key candidates identified include genes involved in transcription, chromatin remodeling, post-translational modifications, transport and targeting of proteins to storage vacuoles. Inference of a gene coexpression network of 12 candidate transcription factors and globulin genes revealed the transcription factor ABA-insensitive 5 (ABI5) as a highly connected hub. Characterization of loss-of-function abi5 mutants in pea uncovered a role for ABI5 in controlling the relative abundance of vicilin, a sulfur-poor 7S globulin, in pea seeds. This demonstrates the feasibility of using genome-wide association studies in M. truncatula to reveal genes that can be modulated to improve seed nutritional value.

International audience; Avoidance mechanisms and intrinsic resistance are complementary strategies to improve winter frost tolerance and yield potential in field pea. The development of the winter pea crop represents a major challenge to expand plant protein production in temperate areas. Breeding winter cultivars requires the combination of freezing tolerance as well as high seed productivity and quality. In this context, we investigated the genetic determinism of winter frost tolerance and assessed its genetic relationship with yield and developmental traits. Using a newly identified source of frost resistance, we developed a population of recombinant inbred lines and evaluated it in six environments in Dijon and Clermont-Ferrand between 2005 and 2010. We developed a genetic map comprising 679 markers distributed over seven linkage groups and covering 947.1 cM. One hundred sixty-one quantitative trait loci (QTL) explaining 9-71 % of the phenotypic variation were detected across the six environments for all traits measured. Two clusters of QTL mapped on the linkage groups III and one cluster on LGVI reveal the genetic links between phenology, morphology, yield-related traits and frost tolerance in winter pea. QTL clusters on LGIII highlighted major developmental gene loci (Hr and Le) and the QTL cluster on LGVI explained up to 71 % of the winter frost damage variation. This suggests that a specific architecture and flowering ideotype defines frost tolerance in winter pea. However, two consistent frost tolerance QTL on LGV were independent of phenology and morphology traits, showing that different protective mechanisms are involved in frost tolerance. Finally, these results suggest that frost tolerance can be bred independently to seed productivity and quality.

BAPGEAPSISUPDAT; The molecular pathways responsible for the flowering response to photoperiod have been extensively studied in Arabidopsis thaliana and cereals but remain poorly understood in other major plant groups. Here, we describe a dominant mutant at the LATE BLOOMER2 (LATE2) locus in pea (Pisum sativum) that is late-flowering with a reduced response to photoperiod. LATE2 acts downstream of light signaling and the circadian clock to control expression of the main photoperiod-regulated FT gene, FTb2, implying that it plays a primary role in photoperiod measurement. Mapping identified the CYCLING DOF FACTOR gene CDFc1 as a strong candidate for LATE2, and the late2-1D mutant was found to carry a missense mutation in CDFc1 that impairs its capacity to bind to the blue-light photoreceptor FKF1 in yeast two-hybrid assays and delays flowering in Arabidopsis when overexpressed. Arabidopsis CDF genes are important negative regulators of CONSTANS (CO) transcription, but we found no effect of LATE2 on the transcription of pea CO-LIKE genes, nor on genes in any other families previously implicated in the activation of FT in Arabidopsis. Our results reveal an important component of the pea photoperiod response pathway and support the view that regulation of FTb2 expression by photoperiod occurs via a CO-independent mechanism.

Background The continuing increase in size and quality of the “short reads” raw data is a significant help for the quality of the assembly obtained through various bioinformatics tools. However, building a reference genome sequence for most plant species remains a significant challenge due to the large number of repeated sequences which are problematic for a whole-genome quality de novo assembly. Furthermore, for most SNP identification approaches in plant genetics and breeding, only the “Gene-space” regions including the promoter, exon and intron sequences are considered. Results We developed the iPea protocol to produce a de novo Gene-space assembly by reconstructing, in an iterative way, the non-coding sequence flanking the Unigene cDNA sequence through addition of next-generation DNA-seq data. The approach was elaborated with the large diploid genome of pea (Pisumsativum L.), rich in repetitive sequences. The final Gene-space assembly included 35,400 contigs (97 Mb), covering 88 % of the 40,227 contigs (53.1 Mb) of the PsCam_low-copy Unigen set. Its accuracy was validated by the results of the built GenoPea 13.2 K SNP Array. Conclusion The iPEA protocol allows the reconstruction of a Gene-space based from RNA-Seq and DNA-seq data with limited computing resources. Electronic supplementary material The online version of this article (doi:10.1186/s13104-016-1903-z) contains supplementary material, which is available to authorized users.

Background Genome-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. Methods A 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. Results GWA 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. Conclusion This study provides valuable markers, marker haplotypes and germplasm lines to increase levels of partial resistance to A. euteiches in pea breeding. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2429-4) contains supplementary material, which is available to authorized users.

Pea is the most widely cultivated grain legume crop in Europe. In the French research project PeaMUST, a large public and private sector partnership has been set up to undertake complementary strategies towards the development of high and stable yielding cultivars. These different strategies will contribute to the definition of a pea ideotype based on both a priori and a posteriori approaches. On the one hand, genomic selection will identify interesting genotypes which may display new phenotypic ideotypes. On the other hand, marker-assisted selection will enable cumulating resistance for a given or different stresses to reach more durably stable phenotypes. Moreover, mutations identified in candidate genes controlling aerial and root architecture will be tested for their effects on stress tolerance.

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; Pea (Pisum sativum L.) is the most cultivated European pulse crop and the pea seeds mainly serve as a protein source for monogastric animals. Because the seed protein composition impacts on seed nutritional value, we aimed at identifying the determinants of its variability. This paper presents the first pea mature seed proteome reference map, which includes 156 identified proteins (http://www.inra.fr/legumbase/peaseedmap/). This map provides a fine dissection of the pea seed storage protein composition revealing a large diversity of storage proteins resulting both from gene diversity and post-translational processing. It gives new insights into the pea storage protein processing (especially 7S globulins) as a possible adaptation towards progressive mobilization of the proteins during germination. The nonstorage seed proteome revealed the presence of proteins involved in seed defense together with proteins preparing germination. The plasticity of the seed proteome was revealed for seeds produced in three successive years of cultivation, and 30% of the spots were affected by environmental variations. This work pinpoints seed proteins most affected by environment, highlighting new targets to stabilize storage protein composition that should be further analyzed.

International audience; 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.

Background Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. Results A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. Conclusion The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being developed will most probably allow for a more efficient selection in this species. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1266-1) contains supplementary material, which is available to authorized users.

International audience; 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 Q(2) 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.

Next-generation sequencing technologies allow an almost exhaustive survey of the transcriptome, even in species with no available genome sequence. To produce a Unigene set representing most of the expressed genes of pea, 20 cDNA libraries produced from various plant tissues harvested at various developmental stages from plants grown under contrasting nitrogen conditions were sequenced. Around one billion reads and 100 Gb of sequence were de novo assembled. Following several steps of redundancy reduction, 46 099 contigs with N50 length of 1667 nt were identified. These constitute the 'Caméor' Unigene set. The high depth of sequencing allowed identification of rare transcripts and detected expression for approximately 80% of contigs in each library. The Unigene set is now available online (http://bios.dijon.inra.fr/FATAL/cgi/pscam.cgi), allowing (i) searches for pea orthologs of candidate genes based on gene sequences from other species, or based on annotation, (ii) determination of transcript expression patterns using various metrics, (iii) identification of uncharacterized genes with interesting patterns of expression, and (iv) comparison of gene ontology pathways between tissues. This resource has allowed identification of the pea orthologs of major nodulation genes characterized in recent years in model species, as a major step towards deciphering unresolved pea nodulation phenotypes. In addition to a remarkable conservation of the early transcriptome nodulation apparatus between pea and Medicago truncatula, some specific features were highlighted. The resource provides a reference for the pea exome, and will facilitate transcriptome and proteome approaches as well as SNP discovery in pea.

International audience; 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.

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; The identification of the molecular polymorphisms giving rise to phenotypic trait variability—both quantitative and qualitative—is a major goal of the present agronomic research. Various approaches such as positional cloning or transposon tagging, as well as the candidate gene strategy have been used to discover the genes underlying this variation in plants. The construction of functional maps, i.e. composed of genes of known function, is an important component of the candidate gene approach. In the present paper we report the development of 63 single nucleotide polymorphism markers and 15 single-stranded conformation polymorphism markers for genes encoding enzymes mainly involved in primary metabolism, and their genetic mapping on a composite map using two pea recombinant inbred line populations. The complete genetic map covers 1,458 cM and comprises 363 loci, including a total of 111 gene-anchored markers: 77 gene-anchored markers described in this study, 7 microsatellites located in gene sequences, 16 flowering time genes, the Tri gene, 5 morphological markers, and 5 other genes. The mean spacing between adjacent markers is 4 cM and 90% of the markers are closer than 10 cM to their neighbours. We also report the genetic mapping of 21 of these genes in Medicago truncatula and add 41 new links between the pea and M. truncatula maps. We discuss the use of this new composite functional map for future candidate gene approaches in pea.

International audience; This paper aims at providing reliable and cost effective genotyping conditions, level of polymorphism in a range of genotypes and map position of newly developed microsatellite markers in order to promote broad application of these markers as a common set for genetic studies in pea. Optimal PCR conditions were determined for 340 microsatellite markers based on amplification in eight genotypes. Levels of polymorphism were determined for 309 of these markers. Compared to data obtained for other species, levels of polymorphism detected in a panel of eight genotypes were high with a mean number of 3.8 alleles per polymorphic locus and an average PIC value of 0.62, indicating that pea represents a rather polymorphic autogamous species. One of our main objectives was to locate a maximum number of microsatellite markers on the pea genetic map. Data obtained from three different crosses were used to build a composite genetic map of 1,430 cM (Haldane) comprising 239 microsatellite markers. These include 216 anonymous SSRs developed from enriched genomic libraries and 13 SSRs located in genes. The markers are quite evenly distributed throughout the seven linkage groups of the map, with 85% of intervals between the adjacent SSR markers being smaller than 10 cM. There was a good conservation of marker order and linkage group assignment across the three populations. In conclusion,we hope this report will promote wide application of these markers and will allow information obtained by different laboratories worldwide in diverse fields of pea genetics, such as QTL mapping studies and genetic resource surveys, to be easily aligned.

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; The fluxes of (1) exogenous nitrogen (N) assimilation and (2) remobilization of endogenous N from vegetative plant compartments were measured by 15N labeling during the seed-filling period in pea (Pisum sativum L. cv Caméor), to better understand the mechanism of N remobilization. While the majority (86%) of exogenous N was allocated to the vegetative organs before the beginning of seed filling, this fraction decreased to 45% at the onset of seed filling, the remainder being directed to seeds. Nitrogen remobilization from vegetative parts contributed to 71% of the total N in mature seeds borne on the first two nodes (first stratum). The contribution of remobilized N to total seed N varied, with the highest proportion at the beginning of filling; it was independent of the developmental stage of each stratum of seeds, suggesting that remobilized N forms a unique pool, managed at the whole-plant level and supplied to all filling seeds whatever their position on the plant. Once seed filling starts, N is remobilized from all vegetative organs: 30% of the total N accumulated in seeds was remobilized from leaves, 20% from pod walls, 11% from roots, and 10% from stems. The rate of N remobilization was maximal when seeds of all the different strata were filling, consistent with regulation according to the N demand of seeds. At later stages of seed filling, the rate of remobilization decreases and may become controlled by the amount of residual N in vegetative tissues.

A proteomic approach was used to analyze protein changes during nitrogen mobilization (N mobilization) from leaves to filling seeds in pea (Pisum sativum). First, proteome reference maps were established for mature leaves and stems. They displayed around 190 Coomassie Blue-stained spots with pIs from 4 to 7. A total of 130 spots were identified by mass spectrometry as corresponding to 80 different proteins implicated in a variety of cellular functions. Although the leaf proteome map contained more abundant spots, corresponding to proteins involved in energy/carbon metabolism, than the stem map, their comparison revealed a highly similar protein profile. Second, the leaf proteome map was used to analyze quantitative variations in leaf proteins during N mobilization. Forty percent of the spots showed significant changes in their relative abundance in the total protein extract. The results confirmed the importance of Rubisco as a source of mobilizable nitrogen, and suggested that in pea leaves the rate of degradation of Rubisco may vary throughout N mobilization. Correlated with the loss of Rubisco was an increase in relative abundance of chloroplastic protease regulatory subunits. Concomitantly, the relative abundance of some proteins related to the photosynthetic apparatus (Rubisco activase, Rubisco-binding proteins) and of several chaperones increased. A role for these proteins in the maintenance of a Rubisco activation state and in the PSII repair during the intense proteolytic activity within the chloroplasts was proposed. Finally, two 14-3-3-like proteins, with a potential regulatory role, displayed differential expression patterns during the massive remobilization of nitrogen.

Key message Gene-based SNPs were identified and mapped in pea using five recombinant inbred line populations segregating for traits of agronomic importance. Abstract Pea (Pisum sativum L.) is one of the world’s oldest domesticated crops and has been a model system in plant biology and genetics since the work of Gregor Mendel. Pea is the second most widely grown pulse crop in the world following common bean. The importance of pea as a food crop is growing due to its combination of moderate protein concentration, slowly digestible starch, high dietary fiber concentration, and its richness in micronutrients; however, pea has lagged behind other major crops in harnessing recent advances in molecular biology, genomics and bioinformatics, partly due to its large genome size with a large proportion of repetitive sequence, and to the relatively limited investment in research in this crop globally. The objective of this research was the development of a genome-wide transcriptome-based pea single-nucleotide polymorphism (SNP) marker platform using next-generation sequencing technology. A total of 1,536 polymorphic SNP loci selected from over 20,000 non-redundant SNPs identified using deep transcriptome sequencing of eight diverse Pisum accessions were used for genotyping in five RIL populations using an Illumina GoldenGate assay. The first high-density pea SNP map defining all seven linkage groups was generated by integrating with previously published anchor markers. Syntenic relationships of this map with the model legume Medicago truncatula and lentil (Lens culinaris Medik.) maps were established. The genic SNP map establishes a foundation for future molecular breeding efforts by enabling both the identification and tracking of introgression of genomic regions harbouring QTLs related to agronomic and seed quality traits. Electronic supplementary material The online version of this article (doi:10.1007/s00122-014-2375-y) contains supplementary material, which is available to authorized users.

International audience; Pea has a complex genome of 4.3 Gb for which only limited genomic resources are available to date. Although SNP markers are now highly valuable for research and modern breeding, only a few are described and used in pea for genetic diversity and linkage analysis.[br/] We developed a large resource by cDNA sequencing of 8 genotypes representative of modern breeding material using the Roche 454 technology, combining both long reads (400 bp) and high coverage (3.8 million reads, reaching a total of 1,369 megabases). Sequencing data were assembled and generated a 68 K unigene set, from which 41 K were annotated from their best blast hit against the model species Medicago truncatula. Annotated contigs showed an even distribution along M. truncatula pseudochromosomes, suggesting a good representation of the pea genome. 10 K pea contigs were found to be polymorphic among the genetic material surveyed, corresponding to 35 K SNPs.We validated a subset of 1538 SNPs through the GoldenGate assay, proving their ability to structure a diversity panel of breeding germplasm. Among them, 1340 were genetically mapped and used to build a new consensus map comprising a total of 2070 markers. Based on blast analysis, we could establish 1252 bridges between our pea consensus map and the pseudochromosomes of M. truncatula, which provides new insight on synteny between the two species.[br/] Our approach created significant new resources in pea, i.e. the most comprehensive genetic map to date tightly linked to the model species M. truncatula and a large SNP resource for both academic research and breeding.

Pisum sativum sequences were retrieved from Genbank/EMBL data-bases and searched for all possible dinucleotide and trinucleotide tandem repeats, One-hundred and seventy-one simple sequence repeats (SSRs) were found among 663 sequences. The different dinucleotide or trinucleotide motifs occurred at varying frequencies, CT/AG was the most frequent dinucleotide, and TCT/AGA the most frequent trinucleotide. Forty-three microsatellite markers were generated from these sequences and used to assess the genetic variability among 12 pea genotypes. Thirty-one were polymorphic among the genotypes and the average number of variants per marker was 3.6 when considering only polymorphic markers. Overall, the number of variants for a given SSR marker was correlated with the length of the SSR but some 12-bp long SSRs showed the same degree of polymorphism as longer ones. The groupings resulting from the SSR genotyping among the 12 genotypes gave an interesting insight into the possible origin of one recent cultivar. Database-derived SSR markers are highly variable. They can provide useful information on the genetic diversity among P. sativum cultivated types.

Plant cell elongation depends on the physical properties of the primary cell wall. Because xyloglucan endotransglycosylases (XETs) are enzymes that mediate cleavage and rejoining of the beta(1-4)-XG backbone of primary cell wall, they are potentially involved in cell elongation. In this paper, the growth of the barley coleoptile was related to the expression patterns of two genes from this family (hvEXT, hvXEB) in experiments where coleoptile elongation varied according to light/dark treatments in order to assess the potential role of these genes in cell elongation. In dark-grown and light-grown coleoptiles, growth rate variations were associated with altered levels of expression of hvEXT and hvXEB: they were higher in dark-grown than in light-grown seedlings, and decreased after 5 d in darkness, and after 4 d in continuous light. In 4-d-old seedlings, coleoptile elongation decreased significantly 4 h after the onset of a continuous white- light irradiation, and hvXEB and hvEXT mRNA levels decreased, respectively, 2 h and 4 h after the onset of white-light irradiation. Moreover, the distribution of hvXEB and hvEXT along the coleoptiles of 4-d-old dark-grown seedlings were different. Altogether, these results suggest a complex pattern of temporal and positional expression for the different genes of the XET-related family.

Methods that could predict F 1 maize (Zea mays L.) hybrid performance with some accuracy prior to field evaluation are of particular interest. This study was conducted to evaluate the efficencies of the conventional additive model based on the general combining ability (GCA) as a control and of three different predictions of the specific combining ability (SCA). The first approach was based on the hypothesis that the degree of SCA expressed by a single-cross is related to the marker distance between its parental lines. The second approach was based on a factorial regression model of interaction, where markers were used by means of principal component analysis to generate covariates for SCA. The third approach was adapted from the best linear unbiased prediction (BLUP) of SCA, where covariances between hybrid SCAs were estimated with marker date Efficiencies were evaluated by means of a cross-validation procedure for silage performance of a 21 by 21 half-diallel population among maize inbreds. This procedure was applied to (i) all hybrids and (ii) hybrids between unrelated parents only. In situation (i), introducing a distance term in the model accounted for up to 73.6% of the variation in the hybrid performance observed, whereas the corresponding efficiency of the GCA model was 63.4%. The introduction of a distance term did not modify prediction efficiency in situation (ii) whereas the use of the factorial regression model or the BLUP approach led to moderate improvements. These results suggested that efficient approaches can be proposed to predict hybrid silage yield and that prediction of SCA is mostly justified in situations where coancestry among inbreds is unknown or only suspected.

18 pages; International audience

Chapter 10; International audience

Here, we report a subtilase gene (SBT1.1) specifically expressed in the endosperm of Medicago truncatula and Pisum sativum seeds during development, which is located at a chromosomal position coinciding with a seed weight quantitative trait locus (QTL). Association studies between SBT1.1 polymorphisms and seed weights in ecotype collections provided further evidence for linkage disequilibrium between the SBT1.1 locus and a seed weight locus. To investigate the possible contribution of SBT1.1 to the control of seed weight, a search for TILLING (Targeting Induced Local Lesions in Genomes) mutants was performed. An inspection of seed phenotype revealed a decreased weight and area of the sbt1.1 mutant seeds, thus inferring a role of SBT1.1 in the control of seed size in the forage and grain legume species. Microscopic analyses of the embryo, representing the major part of the seed, revealed a reduced number of cells in the MtP330S mutant, but no significant variation in cell size. SBT1.1 is therefore most likely to be involved in the control of cotyledon cell number, rather than cell expansion, during seed development. This raises the hypothesis of a role of SBT1.1 in the regulation of seed size by providing molecules that can act as signals to control cell division within the embryo.

[i]Medicago truncatula[/i] is used as a model plant for exploring the genetic and molecular determinants of nitrogen (N) nutrition in legumes. In this study, our aim was to detect quantitative trait loci (QTL) controlling plant N nutrition using a simple framework of carbon/N plant functioning stemming from crop physiology. This framework was based on efficiency variables which delineated the plant's efficiency to take up and process carbon and N resources. A recombinant inbred line population (LR4) was grown in a glasshouse experiment under two contrasting nitrate concentrations. At low nitrate, symbiotic N-2 fixation was the main N source for plant growth and a QTL with a large effect located on linkage group (LG) 8 affected all the traits. Significantly, efficiency variables were necessary both to precisely localize a second QTL on LG5 and to detect a third QTL involved in epistatic interactions on LG2. At high nitrate, nitrate assimilation was the main N source and a larger number of QTL with weaker effects were identified compared to low nitrate. Only two QTL were common to both nitrate treatments: a QTL of belowground biomass located at the bottom of LG3 and another one on LG6 related to three different variables (leaf area, specific N uptake and aboveground:belowground biomass ratio). Possible functions of several candidate genes underlying QTL of efficiency variables could be proposed. Altogether, our results provided new insights into the genetic control of N nutrition in M. truncatula. For instance, a novel result for [i]M. truncatula[/i] was identification of two epistatic interactions in controlling plant N-2 fixation. As such this study showed the value of a simple conceptual framework based on efficiency variables for studying genetic determinants of complex traits and particularly epistatic interactions

In most centres of crop domestication, legumes and cereals have been domesticated together (Gepts, 2004). Associated with cereals, legumes constitute the main component of traditional dishes throughout the world, where maize and beans, rice and lentils, barley and peas, wheat and chickpeas are eaten together. Legumes are consumed in many forms: seedling and young leaves are eaten in salads, fresh immature pods and seeds provide a green vegetable, and dry seeds are cooked in various dishes. However, researches have been mainly devoted to the dry seeds. Legume seeds provide an exceptionally varied nutrient profile, including proteins, fibres, vitamins and minerals (Mitchell et al. 2009). Nitrogen that is used by the young seedling during germination is stored in the seed in the form of storage proteins. Seeds contain from 16% to 50% of protein and provide one third of all dietary protein nitrogen (Graham and Vance, 2003). Anticipating the increasing demand for protein food sources, the Protein Advisory Group of the United Nations has identified the improvement of legumes as a critically important area of research

To identify genes involved in phenotypic traits, translational genomics from highly characterized model plants to poorly characterized crop plants provides a valuable source of markers to saturate a zone of interest as well as functionally characterized candidate genes. In this paper, an integrated view of the pea genetic map was developed. A series of gene markers were mapped and their best reciprocal homologs were identified on M. truncatula, L. japonicus, soybean, and poplar pseudomolecules. Based on the syntenic relationships uncovered between pea and M. truncatula, 5460 pea Unigenes were tentatively placed on the consensus map. A new bioinformatics tool, http://www.thelegumeportal.net/pea_mtr_translational_toolkit, was developed that allows, for any gene sequence, to search its putative position on the pea consensus map and hence to search for candidate genes among neighboring Unigenes. As an example, a promising candidate gene for the hypernodulation mutation nod3 in pea was proposed based on the map position of the likely homolog of Pub1, a M. truncatula gene involved in nodulation regulation. A broader view of pea genome evolution was obtained by revealing syntenic relationships between pea and sequenced genomes. Blocks of synteny were identified which gave new insights into the evolution of chromosome structure in Papillionoids and Eudicots. The power of the translational genomics approach was underlined.

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility.

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; Pea (Pisum sativum L.) is the third most important grain legume worldwide, and the increasing demand for protein-rich raw material has led to a great interest in this crop as a protein source. Seed yield and protein content in crops are strongly determined by nitrogen (N) nutrition, which in legumes relies on two complementary pathways: absorption by roots of soil mineral nitrogen, and fixation in nodules of atmospheric dinitrogen through the plant-Rhizobium symbiosis. This study assessed the potential of naturally occurring genetic variability of nodulated root structure and functioning traits to improve N nutrition in pea. Glasshouse and field experiments were performed on seven pea genotypes and on the 'Cameor' x 'Ballet' population of recombinant inbred lines selected on the basis of parental contrast for root and nodule traits. Significant variation was observed for most traits, which were obtained from non-destructive kinetic measurements of nodulated root and shoot in pouches, root and shoot image analysis, (15)N quantification, or seed yield and protein content determination. A significant positive relationship was found between nodule establishment and root system growth, both among the seven genotypes and the RIL population. Moreover, several quantitative trait loci for root or nodule traits and seed N accumulation were mapped in similar locations, highlighting the possibility of breeding new pea cultivars with increased root system size, sustained nodule number, and improved N nutrition. The impact on both root or nodule traits and N nutrition of the genomic regions of the major developmental genes Le and Af was also underlined.

International audience; Legume seeds are an important source of food and feed, and have been principally studied with a view to optimizing the composition of reserve substances starch, oligosaccharides, oil, and protein. The availability of genome and transcribed genome sequences for the legume model species Medicago truncatula and Lotus japonicus has stimulated the application of the -omics technologies to understanding legume seed development in these and closely related crop species. The -omics techniques that we shall consider here are transcriptomics, proteomics, metabolomics, and ionomics (Fig. 1). Transcriptomics and proteomics methodologies attempt to describe the global complement of transcripts and proteins, respectively, of an organism, and utilize directly primary genomic sequence or expressed sequence tag information as reference. In contrast, metabolomics analyses determine organic metabolite constitution, and ionomics the inorganic ion contents of the organism. They are thus distinct but complementary sources of information about different levels of the phenome. The full exploitation of -omics depends on the establishment of interactive databases that facilitate connecting these different sources of information obtained without any a priori knowledge (Dondrup et al., 2009; Truncatulix: http://lily.cebitec.uni-bielefeld. de/truncatulix/app; Henckel et al., 2009; Legoo:http://www.legoo.org/). This backbone of technology is being applied to legume seeds in a number of ways: to dissect gene expression at different levels of detail (whole seed, component tissues, organelles, etc.), to study different physiological phenomena such as the different phases of seed development, maturation and germination, or biotic and abiotic stresses, and to evaluate the effects of specific mutations on phenotypes.

International audience; Eight pea genotypes characterized for their major protein fractions were used to investigate the effect of seed protein composition variability on protein digestibility in poultry. These genotypes of various pea types, were also variable in other seed components. They showed variations in their carbohydrate (insoluble fibre compounds, soluble fibre, soluble carbohydrates) and trypsin inhibitor (TI) contents. To exclude the effect of tannins and of particle size, the seeds were dehulled and micro-ground. They were incorporated as the only protein source in isoproteinaceous diets with similar metabolisable energy content and fed to cecectomized chickens. The average amino acid digestibility (apparent and true) and endogenous amino acid excretion were related with pea diet characteristics (protein composition, carbohydrate composition and TI activity). This allowed to precise which of the diet characteristics affect protein digestibility and endogenous excretion. Average apparent digestibility of amino acids was negatively correlated with insoluble fibre components (R=-0.71 to -0.72; p

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; An understanding of the genetic determinism of frost tolerance is a prerequisite for the development of frost tolerant cultivars for cold northern areas. In legumes, it is not known to which extent vernalization requirement or photoperiod responsiveness are necessary for the development of frost tolerance. In pea (Pisum sativum L.) however, the flowering locus Hr is suspected to influence winter frost tolerance by delaying floral initiation until after the main winter freezing periods have passed. The objective of this study was to dissect the genetic determinism of frost tolerance in pea by QTL analysis and to assess the genetic linkage between winter frost tolerance and the Hr locus. A population of 164 recombinant inbred lines (RILs), derived from the cross Champagne x Terese was evaluated both in the greenhouse and in field conditions to characterize the photoperiod response from which the allele at the Hr locus was inferred. In addition, the population was also assessed for winter frost tolerance in 11 field conditions. Six QTL were detected, among which three were consistent among the different experimental conditions, confirming an oligogenic determinism of frost tolerance in pea. The Hr locus was found to be the peak marker for the highest explanatory QTL of this study. This result supports the hypothesis of the prominent part played by the photoperiod responsiveness in the determinism of frost tolerance for this species. The consistency of three QTL makes these positions interesting targets for marker-assisted selection.

UTILLdb is a database of phenotypic and sequence information on mutant genes from a reference Pisum sativum EMS-mutant population., The systematic characterization of gene functions in species recalcitrant to Agrobacterium-based transformation, like Pisum sativum, remains a challenge. To develop a high throughput forward and reverse genetics tool in pea, we have constructed a reference ethylmethane sulfonate mutant population and developed a database, UTILLdb, that contains phenotypic as well as sequence information on mutant genes. UTILLdb can be searched online for TILLING alleles, through the BLAST tool, or for phenotypic information about mutants by keywords.

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699; International audience; Increasing pea (Pisum sativum) seed nutritional value and particularly seed protein content, while maintaining yield, is an important challenge for further development of this crop. Seed protein content and yield are complex and unstable traits, integrating all the processes occurring during the plant life cycle. During filling, seeds are the main sink to which assimilates are preferentially allocated at the expense of vegetative organs. Nitrogen seed demand is satisfied partly by nitrogen acquired by the roots, but also by nitrogen remobilized from vegetative organs. In this study, we evaluated the respective roles of nitrogen source capacity and sink strength in the genetic variability of seed protein content and yield. We showed in eight genotypes of diverse origins that both the maximal rate of nitrogen accumulation in the seeds and nitrogen source capacity varied among genotypes. Then, to identify the genetic factors responsible for seed protein content and yield variation, we searched for quantitative trait loci (QTL) for seed traits and for indicators of sink strength and source nitrogen capacity. We detected 261 QTL across five environments for all traits measured. Most QTL for seed and plant traits mapped in clusters, raising the possibility of common underlying processes and candidate genes. In most environments, the genes Le and Afila, which control internode length and the switch between leaflets and tendrils, respectively, determined plant nitrogen status. Depending on the environment, these genes were linked to QTL of seed protein content and yield, suggesting that source-sink adjustments depend on growing conditions

A collection of 148 Pisum accessions, mostly from Western Europe, and including both primitive germplasm and cultivated types, was structured using 121 protein- and PCR-based markers. This molecular marker-based classification allowed us to trace back major lineages of pea breeding in Western Europe over the last decades, and to follow the main breeding objectives: increase of seed weight, introduction of the afila foliage type and white flowers, and improvement of frost tolerance for winter-sown peas. The classification was largely consistent with the available pedigree data, and clearly resolved the different main varietal types according to their end-uses (fodder, food and feed peas) from exotic types and wild forms. Fodder types were further separated into two sub-groups. Feed peas, corresponding to either spring-sown or winter-sown types, were also separated, with two apparently different gene pools for winter-sown peas. The garden pea group was the most difficult to structure, probably due to a continuum in breeding of feed peas from garden types. The classification also stressed the paradox between the narrowness of the genetic basis of recent cultivars and the very large diversity available within P. sativum. A sub-collection of 43 accessions representing 96% of the whole allelic variability is proposed as a starting point for the construction of a core collection.

We utilized a proteomic approach to investigate seed development in Medicago truncatula, cv Jemalong, line J5 at specific stages of seed filling corresponding to the acquisition of germination capacity and protein deposition. One hundred twenty proteins differing in kinetics of appearance were subjected to matrix-assisted laser desorption ionization time of flight mass spectrometry. These analyses provided peptide mass fingerprint data that identified 84 of them. Some of these proteins had previously been shown to accumulate during seed development in legumes (e.g. legumins, vicilins, convicilins, and lipoxygenases), confirming the validity of M. truncatula as a model for analysis of legume seed filling. The study also revealed proteins presumably involved in cell division during embryogenesis (β-tubulin and annexin). Their abundance decreased before the accumulation of the major storage protein families, which itself occurs in a specific temporal order: vicilins (14 d after pollination [DAP]), legumins (16 DAP), and convicilins (18 DAP). Furthermore, the study showed an accumulation of enzymes of carbon metabolism (e.g. sucrose synthase, starch synthase) and of proteins involved in embryonic photosynthesis (e.g. chlorophyll a/b binding), which may play a role in providing cofactors for protein/lipid synthesis or for CO2 refixation during seed filling. Correlated with the reserve deposition phase was the accumulation of proteins associated with cell expansion (actin 7 and reversibly glycosylated polypeptide) and of components of the precursor accumulating vesicles, which give rise to a trypsin inhibitor on maturation. Finally, we revealed a differential accumulation of enzymes involved in methionine metabolism (S-adenosyl-methionine synthetase and S-adenosylhomo-cysteine hydrolase) and propose a role for these enzymes in the transition from a highly active to a quiescent state during seed development.

Numerous studies have aimed at assessing the relationships between (i) distances computed from phenotypic data, (ii) distances computed from marker data and (iii) heterosis, for pairs of individuals or populations. The conflicting results obtained illustrate that these relationships are far from simple. In this paper, we investigate the effect on these relationships of (i) the polygenic inheritance of phenotypic traits and (ii) the structure of linkage disequilibrium between genetic markers and the loci involved in the variation of quantitative traits (QTLs). Both theoretical and experimental results showed that the relationship between marker distances and phenotypic distances computed from quantitative traits displays a triangular shape: low marker distances are systematically associated with low phenotypic distances, whereas high marker distances correspond to either low or high phenotypic distances. Because of this property, the linear coefficient of correlation between both distances decreases as the number of QTLs involved in the variation of the traits considered for phenotypic distance computation increases. Similar properties are expected for the relationship between heterosis and phenotypic distances.

Background Single Nucleotide Polymorphisms (SNPs) can be used as genetic markers for applications such as genetic diversity studies or genetic mapping. New technologies now allow genotyping hundreds to thousands of SNPs in a single reaction. In order to evaluate the potential of these technologies in pea, we selected a custom 384-SNP set using SNPs discovered in Pisum through the resequencing of gene fragments in different genotypes and by compiling genomic sequence data present in databases. We then designed an Illumina GoldenGate assay to genotype both a Pisum germplasm collection and a genetic mapping population with the SNP set. Results We obtained clear allelic data for more than 92% of the SNPs (356 out of 384). Interestingly, the technique was successful for all the genotypes present in the germplasm collection, including those from species or subspecies different from the P. sativum ssp sativum used to generate sequences. By genotyping the mapping population with the SNP set, we obtained a genetic map and map positions for 37 new gene markers. Conclusion Our results show that the Illumina GoldenGate assay can be used successfully for high-throughput SNP genotyping of diverse germplasm in pea. This genotyping approach will simplify genotyping procedures for association mapping or diversity studies purposes and open new perspectives in legume genomics.