Identification of QTLs associated with seed protein concentration in two diverse recombinant inbred line populations of pea

Improving the seed protein concentration (SPC) of pea (Pisum sativum L.) has turned into an important breeding objective because of the consumer demand for plant-based protein and demand from protein fractionation industries. To support the marker-assisted selection (MAS) of SPC towards accelerated breeding of improved cultivars, we have explored two diverse recombinant inbred line (RIL) populations to identify the quantitative trait loci (QTLs) associated with SPC. The two RIL populations, MP 1918 × P0540-91 (PR-30) and Ballet × Cameor (PR-31), were derived from crosses between moderate SPC × high SPC accessions. A total of 166 and 159 RILs of PR-30 and PR-31, respectively, were genotyped using an Axiom® 90K SNP array and 13.2K SNP arrays, respectively. The RILs were phenotyped in replicated trials in two and three locations of Saskatchewan, Canada in 2020 and 2021, respectively, for agronomic assessment and SPC. Using composite interval mapping, we identified three QTLs associated with SPC in PR-30 and five QTLs in PR-31, with the LOD value ranging from 3.0 to 11.0. A majority of these QTLs were unique to these populations compared to the previously known QTLs for SPC. The QTL SPC-Ps-5.1 overlapped with the earlier reported SPC associated QTL PC-QTL-3. Three QTLs, SPC-Ps-4.2, SPC-Ps-5.1, and SPC-Ps-7.2 with LOD scores of 7.2, 7.9, and 11.3, and which explained 14.5%, 11.6%, and 11.3% of the phenotypic variance, respectively, can be used for marker-assisted breeding to increase SPC in peas. Eight QTLs associated with the grain yield were identified with LOD scores ranging from 3.1 to 8.2. Two sets of QTLs, SPC-Ps-2.1 and GY-Ps-2.1, and SPC-Ps-5.1 and GY-Ps-5.3, shared the QTL/peak regions. Each set of QTLs contributed to either SPC or grain yield depending on which parent the QTL region is derived from, thus confirming that breeding for SPC should take into consideration the effects on grain yield.

Recombinant inbred lines derived from wide crosses in Pisum

Genomic resources are becoming available for Pisum but to link these to phenotypic diversity requires well marked populations segregating for relevant traits. Here we describe two such resources. Two recombinant inbred populations, derived from wide crosses in Pisum are described. One high resolution mapping population involves cv Caméor, for which the first pea whole genome assembly was obtained, crossed to JI0281, a basally divergent P. sativum sativum landrace from Ethiopia. The other is an inter sub-specific cross between P. s. sativum and the independently domesticated P. s. abyssinicum. The corresponding genetic maps provide information on chromosome level sequence assemblies and identify structural differences between the genomes of these two Pisum subspecies. In order to visualise chromosomal translocations that distinguish the mapping parents, we created a simplified version of Threadmapper to optimise it for interactive 3-dimensional display of multiple linkage groups. The genetic mapping of traits affecting seed coat roughness and colour, plant height, axil ring pigmentation, leaflet number and leaflet indentation enabled the definition of their corresponding genomic regions. The consequence of structural rearrangement for trait analysis is illustrated by leaf serration. These analyses pave the way for identification of the underlying genes and illustrate the utility of these publicly available resources. Segregating inbred populations derived from wide crosses in Pisum, together with the associated marker data, are made publicly available for trait dissection. Genetic analysis of these populations is informative about chromosome scale assemblies, structural diversity in the pea genome and has been useful for the fine mapping of several discrete and quantitative traits.

Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case on grain legumes

While the continuing decline in genotyping and sequencing costs has largely benefited plant research, some key species for meeting the challenges of agriculture remain mostly understudied. As a result, heterogeneous datasets for different traits are available for a significant number of these species. As gene structures and functions are to some extent conserved through evolution, comparative genomics can be used to transfer available knowledge from one species to another. However, such a translational research approach is complex due to the multiplicity of data sources and the non-harmonized description of the data. Here, we provide two pipelines, referred to as structural and functional pipelines, to create a framework for a NoSQL graph-database (Neo4j) to integrate and query heterogeneous data from multiple species. We call this framework Orthology-driven knowledge base framework for translational research (Ortho_KB). The structural pipeline builds bridges across species based on orthology. The functional pipeline integrates biological information, including QTL, and RNA-sequencing datasets, and uses the backbone from the structural pipeline to connect orthologs in the database. Queries can be written using the Neo4j Cypher language and can, for instance, lead to identify genes controlling a common trait across species. To explore the possibilities offered by such a framework, we populated Ortho_KB to obtain OrthoLegKB, an instance dedicated to legumes. The proposed model was evaluated by studying the conservation of a flowering-promoting gene. Through a series of queries, we have demonstrated that our knowledge graph base provides an intuitive and powerful platform to support research and development programmes.

Assembly of the 81.6 Mb centromere of pea chromosome 6 elucidates the structure and evolution of metapolycentric chromosomes

Centromeres in the legume genera Pisum and Lathyrus exhibit unique morphological characteristics, including extended primary constrictions and multiple separate domains of centromeric chromatin. These so-called metapolycentromeres resemble an intermediate form between monocentric and holocentric types, and therefore provide a great opportunity for studying the transitions between different types of centromere organizations. However, because of the exceedingly large and highly repetitive nature of metapolycentromeres, highly contiguous assemblies needed for these studies are lacking. Here, we report on the assembly and analysis of a 177.6 Mb region of pea (Pisum sativum) chromosome 6, including the 81.6 Mb centromere region (CEN6) and adjacent chromosome arms. Genes, DNA methylation profiles, and most of the repeats were uniformly distributed within the centromere, and their densities in CEN6 and chromosome arms were similar. The exception was an accumulation of satellite DNA in CEN6, where it formed multiple arrays up to 2 Mb in length. Centromeric chromatin, characterized by the presence of the CENH3 protein, was predominantly associated with arrays of three different satellite repeats; however, five other satellites present in CEN6 lacked CENH3. The presence of CENH3 chromatin was found to determine the spatial distribution of the respective satellites during the cell cycle. Finally, oligo-FISH painting experiments, performed using probes specifically designed to label the genomic regions corresponding to CEN6 in Pisum, Lathyrus, and Vicia species, revealed that metapolycentromeres evolved via the expansion of centromeric chromatin into neighboring chromosomal regions and the accumulation of novel satellite repeats. However, in some of these species, centromere evolution also involved chromosomal translocations and centromere repositioning.

A QTL approach in faba bean highlights the conservation of genetic control of frost tolerance among legume species

Frost is a major abiotic stress of winter type faba beans (Vica faba L.) and has adverse effects on crop yield. Climate change, far from reducing the incidence of frost events, is making these phenomena more and more common, severe, and prolonged. Despite the important interaction that the environment has in the tolerance of faba bean to frost, this trait seems to have good levels of heritability. Several QTLs for frost tolerance have already been reported, however, a more robust identification is needed to more precisely identify the genomic regions involved in faba bean tolerance to sub-zero temperatures. Several pea (Pisum sativum L.) and barrel medic (Medicago truncatula L.) frost tolerance QTLs appear to be conserved between these two species, furthering the hypothesis that the genetic control of frost tolerance in legume species might be more generally conserved. In this work, the QTL mapping in two faba bean recombinant inbred line (RIL) populations connected by a common winter-type parent has led to the identification of five genomic regions involved in the control of frost tolerance on linkage groups I, III, IV, and V. Among them, a major and robust QTL of great interest for marker-assisted selection was identified on the lower part of the long-arm of LGI. The synteny between the faba bean frost tolerance QTLs and those previously identified in other legume species such as barrel medic, pea or soybean highlighted at least partial conservation of the genetic control of frost tolerance among different faba bean genetic pools and legume species. Four novel RILs showing high and stable levels of tolerance and the ability to recover from freezing temperatures by accumulating frost tolerance QTLs are now available for breeding programs.

MtEFD and MtEFD2: Two transcription factors with distinct neofunctionalization in symbiotic nodule development

Rhizobium-legume nitrogen-fixing symbiosis involves the formation of a specific organ, the root nodule, which provides bacteria with the proper cellular environment for atmospheric nitrogen fixation. Coordinated differentiation of plant and bacterial cells is an essential step of nodule development, for which few transcriptional regulators have been characterized. Medicago truncatula ETHYLENE RESPONSE FACTOR REQUIRED FOR NODULE DIFFERENTIATION (MtEFD) encodes an APETALA2/ETHYLENE RESPONSIVE FACTOR (ERF) transcription factor, the mutation of which leads to both hypernodulation and severe defects in nodule development. MtEFD positively controls a negative regulator of cytokinin signaling, the RESPONSE REGULATOR 4 (MtRR4) gene. Here we showed that that the Mtefd-1 mutation affects both plant and bacterial endoreduplication in nodules, as well as the expression of hundreds of genes in young and mature nodules, upstream of known regulators of symbiotic differentiation. MtRR4 expressed with the MtEFD promoter complemented Mtefd-1 hypernodulation but not the nodule differentiation phenotype. Unexpectedly, a nonlegume homolog of MtEFD, AtERF003 in Arabidopsis (Arabidopsis thaliana), could efficiently complement both phenotypes of Mtefd-1, in contrast to the MtEFD paralog MtEFD2 expressed in the root and nodule meristematic zone. A domain swap experiment showed that MtEFD2 differs from MtEFD by its C-terminal fraction outside the DNA binding domain. Furthermore, clustered regularly interspaced short palindromic repeats-CRISPR associated protein 9 (CRISPR-Cas9) mutagenesis of MtEFD2 led to a reduction in the number of nodules formed in Mtefd-1, with downregulation of a set of genes, including notably NUCLEAR FACTOR-YA1 (MtNF-YA1) and MtNF-YB16, which are essential for nodule meristem establishment. We, therefore, conclude that nitrogen-fixing symbiosis recruited two proteins originally expressed in roots, MtEFD and MtEFD2, with distinct functions and neofunctionalization processes for each of them.

A major-effect genetic locus, ApRVII, controlling resistance against both adapted and non-adapted aphid biotypes in pea

KEY MESSAGE

A genome-wide association study for pea resistance against a pea-adapted biotype and a non-adapted biotype of the aphid, Acyrthosiphon pisum, identified a genomic region conferring resistance to both biotypes. In a context of reduced insecticide use, the development of cultivars resistant to insect pests is crucial for an integrated pest management. Pea (Pisum sativum) is a crop of major importance among cultivated legumes, for the supply of dietary proteins and nitrogen in low-input cropping systems. However, yields of the pea crop have become unstable due to plant parasites. The pea aphid (Acyrthosiphon pisum) is an insect pest species forming a complex of biotypes, each one adapted to feed on one or a few related legume species. This study aimed to identify resistance to A. pisum and the underlying genetic determinism by examining a collection of 240 pea genotypes. The collection was screened against a pea-adapted biotype and a non-adapted biotype of A. pisum to characterize their resistant phenotype. Partial resistance was observed in some pea genotypes exposed to the pea-adapted biotype. Many pea genotypes were completely resistant to non-adapted biotype, but some exhibited partial susceptibility. A genome-wide association study, using pea exome-capture sequencing data, enabled the identification of the major-effect quantitative trait locus ApRVII on the chromosome 7. ApRVII includes linkage disequilibrium blocks significantly associated with resistance to one or both of the two aphid biotypes studied. Finally, we identified candidate genes underlying ApRVII that are potentially involved in plant-aphid interactions and marker haplotypes linked with aphid resistance. This study sets the ground for the functional characterization of molecular pathways involved in pea defence to the aphids but also is a step forward for breeding aphid-resistant cultivars.

Rhizosphere Bacterial Networks, but Not Diversity, Are Impacted by Pea-Wheat Intercropping

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.

Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea

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.

Genome-wide association study identifies favorable SNP alleles and candidate genes for frost tolerance in pea

BACKGROUND

Frost is a limiting abiotic stress for the winter pea crop (Pisum sativum L.) and identifying the genetic determinants of frost tolerance is a major issue to breed varieties for cold northern areas. Quantitative trait loci (QTLs) have previously been detected from bi-parental mapping populations, giving an overview of the genome regions governing this trait. The recent development of high-throughput genotyping tools for pea brings the opportunity to undertake genetic association studies in order to capture a higher allelic diversity within large collections of genetic resources as well as to refine the localization of the causal polymorphisms thanks to the high marker density. In this study, a genome-wide association study (GWAS) was performed using a set of 365 pea accessions. Phenotyping was carried out by scoring frost damages in the field and in controlled conditions. The association mapping collection was also genotyped using an Illumina Infinium® BeadChip, which allowed to collect data for 11,366 single nucleotide polymorphism (SNP) markers.

RESULTS

GWAS identified 62 SNPs significantly associated with frost tolerance and distributed over six of the seven pea linkage groups (LGs). These results confirmed 3 QTLs that were already mapped in multiple environments on LG III, V and VI with bi-parental populations. They also allowed to identify one locus, on LG II, which has not been detected yet and two loci, on LGs I and VII, which have formerly been detected in only one environment. Fifty candidate genes corresponding to annotated significant SNPs, or SNPs in strong linkage disequilibrium with the formers, were found to underlie the frost damage (FD)-related loci detected by GWAS. Additionally, the analyses allowed to define favorable haplotypes of markers for the FD-related loci and their corresponding accessions within the association mapping collection.

CONCLUSIONS

This study led to identify FD-related loci as well as corresponding favorable haplotypes of markers and representative pea accessions that might to be used in winter pea breeding programs. Among the candidate genes highlighted at the identified FD-related loci, the results also encourage further attention to the presence of C-repeat Binding Factors (CBF) as potential genetic determinants of the frost tolerance locus on LG VI.

Genome-Wide Association Mapping for Agronomic and Seed Quality Traits of Field Pea (Pisum sativum L.)

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 (LD_1/2max,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.

A reference genome for pea provides insight into legume genome evolution

We report the first annotated chromosome-level reference genome assembly for pea, Gregor Mendel's original genetic model. Phylogenetics and paleogenomics show genomic rearrangements across legumes and suggest a major role for repetitive elements in pea genome evolution. Compared to other sequenced Leguminosae genomes, the pea genome shows intense gene dynamics, most likely associated with genome size expansion when the Fabeae diverged from its sister tribes. During Pisum evolution, translocation and transposition differentially occurred across lineages. This reference sequence will accelerate our understanding of the molecular basis of agronomically important traits and support crop improvement.

Transcriptional Reprogramming of Pea Leaves at Early Reproductive Stages

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 ¹⁵N 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.

Development of a Sequence-Based Reference Physical Map of Pea (Pisum sativum L.)

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. WGP^TM 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.

Co-inoculation of a Pea Core-Collection with Diverse Rhizobial Strains Shows Competitiveness for Nodulation and Efficiency of Nitrogen Fixation Are Distinct traits in the Interaction

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.

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.

Patterns of Genetic Structure and Linkage Disequilibrium in a Large Collection of Pea Germplasm

Pea (Pisum sativum, L.) is a major pulse crop used both for animal and human alimentation. Owing to its association with nitrogen-fixing bacteria, it is also a valuable component for low-input cropping systems. To evaluate the genetic diversity and the scale of linkage disequilibrium (LD) decay in pea, we genotyped a collection of 917 accessions, gathering elite cultivars, landraces, and wild relatives using an array of ∼13,000 single nucleotide polymorphisms (SNP). Genetic diversity is broadly distributed across three groups corresponding to wild/landraces peas, winter types, and spring types. At a finer subdivision level, genetic groups relate to local breeding programs and type usage. LD decreases steeply as genetic distance increases. When considering subsets of the data, LD values can be higher, even if the steep decay remains. We looked for genomic regions exhibiting high level of differentiation between wild/landraces, winter, and spring pea, respectively. Two regions on linkage groups 5 and 6 containing 33 SNPs exhibit stronger differentiation between winter and spring peas than would be expected under neutrality. Interestingly, QTL for resistance to cold acclimation and frost resistance have been identified previously in the same regions.

Genome-wide association studies with proteomics data reveal genes important for synthesis, transport and packaging of globulins in legume seeds

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.

EARLY FLOWERING3 Redundancy Fine-Tunes Photoperiod Sensitivity

Three pea (Pisum sativum) loci controlling photoperiod sensitivity, HIGH RESPONSE (HR), DIE NEUTRALIS (DNE), and STERILE NODES (SN), have recently been shown to correspond to orthologs of Arabidopsis (Arabidopsis thaliana) circadian clock genes EARLY FLOWERING3 (ELF3), ELF4, and LUX ARRHYTHMO, respectively. A fourth pea locus, PHOTOPERIOD (PPD), also contributes to the photoperiod response in a similar manner to SN and DNE, and recessive ppd mutants on a spring-flowering hr mutant background show early, photoperiod-insensitive flowering. However, the molecular identity of PPD has so far remained elusive. Here, we show that the PPD locus also has a role in maintenance of diurnal and circadian gene expression rhythms and identify PPD as an ELF3 co-ortholog, termed ELF3b Genetic interactions between pea ELF3 genes suggest that loss of PPD function does not affect flowering time in the presence of functional HR, whereas PPD can compensate only partially for the lack of HR These results provide an illustration of how gene duplication and divergence can generate potential for the emergence of more subtle variations in phenotype that may be adaptively significant.

Identification of LATE BLOOMER2 as a CYCLING DOF FACTOR Homolog Reveals Conserved and Divergent Features of the Flowering Response to Photoperiod in Pea

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.

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

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.

De novo construction of a "Gene-space" for diploid plant genome rich in repetitive sequences by an iterative Process of Extraction and Assembly of NGS reads (iPEA protocol) with limited computing resources

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 (Pisum sativum 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.

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 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.

Full-length de novo assembly of RNA-seq data in pea (Pisum sativum L.) provides a gene expression atlas and gives insights into root nodulation in this species

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.

Variability within a pea core collection of LEAM and HSP22, two mitochondrial seed proteins involved in stress tolerance

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.

Genetic diversity and trait genomic prediction in a pea diversity panel

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.

Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy

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.

Gene-based SNP discovery and genetic mapping in pea

KEY MESSAGE

Gene-based SNPs were identified and mapped in pea using five recombinant inbred line populations segregating for traits of agronomic importance. 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.

QTL analysis of frost damage in pea suggests different mechanisms involved in frost tolerance

KEY MESSAGE

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.

Transcriptome sequencing for high throughput SNP development and genetic mapping in Pea

BACKGROUND

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.

RESULTS

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.

CONCLUSIONS

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.

A role for an endosperm-localized subtilase in the control of seed size in legumes

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.

Genetic diversity in European Pisum germplasm collections

The distinctness of, and overlap between, pea genotypes held in several Pisum germplasm collections has been used to determine their relatedness and to test previous ideas about the genetic diversity of Pisum. Our characterisation of genetic diversity among 4,538 Pisum accessions held in 7 European Genebanks has identified sources of novel genetic variation, and both reinforces and refines previous interpretations of the overall structure of genetic diversity in Pisum. Molecular marker analysis was based upon the presence/absence of polymorphism of retrotransposon insertions scored by a high-throughput microarray and SSAP approaches. We conclude that the diversity of Pisum constitutes a broad continuum, with graded differentiation into sub-populations which display various degrees of distinctness. The most distinct genetic groups correspond to the named taxa while the cultivars and landraces of Pisum sativum can be divided into two broad types, one of which is strongly enriched for modern cultivars. The addition of germplasm sets from six European Genebanks, chosen to represent high diversity, to a single collection previously studied with these markers resulted in modest additions to the overall diversity observed, suggesting that the great majority of the total genetic diversity collected for the Pisum genus has now been described. Two interesting sources of novel genetic variation have been identified. Finally, we have proposed reference sets of core accessions with a range of sample sizes to represent Pisum diversity for the future study and exploitation by researchers and breeders.

Using a physiological framework for improving the detection of quantitative trait loci related to nitrogen nutrition in Medicago truncatula

Medicago truncatula 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 M. truncatula 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.

Translational Genomics in Legumes Allowed Placing In Silico 5460 Unigenes on the Pea Functional Map and Identified Candidate Genes in Pisum sativum L

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.

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition

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.

Highly-multiplexed SNP genotyping for genetic mapping and germplasm diversity studies in pea

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.

Genetic dissection of nitrogen nutrition in pea through a QTL approach of root, nodule, and shoot variability

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.

Dissecting the proteome of pea mature seeds reveals the phenotypic plasticity of seed protein composition

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.

Reserve accumulation in legume seeds

The accumulation of seed reserves is the result of distinct processes occurring in parallel in the main seed compartments of either maternal (seed coats) or zygotic (embryo, endosperm) origin. With the development of legume genomic resources, recent advances have been made toward understanding the metabolic control of seed filling and the regulatory network underlying reserve accumulation. Genetic variability for seed composition has been studied along with the environmental factors influencing reserve accumulation. Nutrient availability and sink strength were both found to be limiting for reserve accumulation. Genes and/or QTL controlling seed protein content and sulfur-amino acid levels have been identified. These new findings will support our attempts to engineer legume seed composition for added end user value.

The flowering locus Hr colocalizes with a major QTL affecting winter frost tolerance in Pisum sativum L

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, a Pisum sativum in silico forward and reverse genetics tool

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.

Developmental genes have pleiotropic effects on plant morphology and source capacity, eventually impacting on seed protein content and productivity in pea

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.

Functional mapping in pea, as an aid to the candidate gene selection and for investigating synteny with the model legume Medicago truncatula

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.

Microsatellite marker polymorphism and mapping in pea (Pisum sativum L.)

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.