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

The pea branching RMS2 gene encodes the PsAFB4/5 auxin receptor and is involved in an auxin-strigolactone regulation loop

Strigolactones (SLs) are well known for their role in repressing shoot branching. In pea, increased transcript levels of SL biosynthesis genes are observed in stems of highly branched SL deficient (ramosus1 (rms1) and rms5) and SL response (rms3 and rms4) mutants indicative of negative feedback control. In contrast, the highly branched rms2 mutant has reduced transcript levels of SL biosynthesis genes. Grafting studies and hormone quantification led to a model where RMS2 mediates a shoot-to-root feedback signal that regulates both SL biosynthesis gene transcript levels and xylem sap levels of cytokinin exported from roots. Here we cloned RMS2 using synteny with Medicago truncatula and demonstrated that it encodes a putative auxin receptor of the AFB4/5 clade. Phenotypes similar to rms2 were found in Arabidopsis afb4/5 mutants, including increased shoot branching, low expression of SL biosynthesis genes and high auxin levels in stems. Moreover, afb4/5 and rms2 display a specific resistance to the herbicide picloram. Yeast-two-hybrid experiments supported the hypothesis that the RMS2 protein functions as an auxin receptor. SL root feeding using hydroponics repressed auxin levels in stems and down-regulated transcript levels of auxin biosynthesis genes within one hour. This auxin down-regulation was also observed in plants treated with the polar auxin transport inhibitor NPA. Together these data suggest a homeostatic feedback loop in which auxin up-regulates SL synthesis in an RMS2-dependent manner and SL down-regulates auxin synthesis in an RMS3 and RMS4-dependent manner.

Pea Marker Database (PMD) - A new online database combining known pea (Pisum sativum L.) gene-based markers

Pea (Pisum sativum L.) is the oldest model object of plant genetics and one of the most agriculturally important legumes in the world. Since the pea genome has not been sequenced yet, identification of genes responsible for mutant phenotypes or desirable agricultural traits is usually performed via genetic mapping followed by candidate gene search. Such mapping is best carried out using gene-based molecular markers, as it opens the possibility for exploiting genome synteny between pea and its close relative Medicago truncatula Gaertn., possessing sequenced and annotated genome. In the last 5 years, a large number of pea gene-based molecular markers have been designed and mapped owing to the rapid evolution of "next-generation sequencing" technologies. However, the access to the complete set of markers designed worldwide is limited because the data are not uniformed and therefore hard to use. The Pea Marker Database was designed to combine the information about pea markers in a form of user-friendly and practical online tool. Version 1 (PMD1) comprises information about 2484 genic markers, including their locations in linkage groups, the sequences of corresponding pea transcripts and the names of related genes in M. truncatula. Version 2 (PMD2) is an updated version comprising 15944 pea markers in the same format with several advanced features. To test the performance of the PMD, fine mapping of pea symbiotic genes Sym13 and Sym27 in linkage groups VII and V, respectively, was carried out. The results of mapping allowed us to propose the Sen1 gene (a homologue of SEN1 gene of Lotus japonicus (Regel) K. Larsen) as the best candidate gene for Sym13, and to narrow the list of possible candidate genes for Sym27 to ten, thus proving PMD to be useful for pea gene mapping and cloning. All information contained in PMD1 and PMD2 is available at www.peamarker.arriam.ru.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

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.

Genotyping-by-Sequencing and Its Exploitation for Forage and Cool-Season Grain Legume Breeding

Genotyping-by-Sequencing (GBS) may drastically reduce genotyping costs compared with single nucleotide polymorphism (SNP) array platforms. However, it may require optimization for specific crops to maximize the number of available markers. Exploiting GBS-generated markers may require optimization, too (e.g., to cope with missing data). This study aimed (i) to compare elements of GBS protocols on legume species that differ for genome size, ploidy, and breeding system, and (ii) to show successful applications and challenges of GBS data on legume species. Preliminary work on alfalfa and Medicago truncatula suggested the greater interest of ApeKI over PstI:MspI DNA digestion. We compared KAPA and NEB Taq polymerases in combination with primer extensions that were progressively more selective on restriction sites, and found greater number of polymorphic SNP loci in pea, white lupin and diploid alfalfa when adopting KAPA with a non-selective primer. This protocol displayed a slight advantage also for tetraploid alfalfa (where SNP calling requires higher read depth). KAPA offered the further advantage of more uniform amplification than NEB over fragment sizes and GC contents. The number of GBS-generated polymorphic markers exceeded 6,500 in two tetraploid alfalfa reference populations and a world collection of lupin genotypes, and 2,000 in different sets of pea or lupin recombinant inbred lines. The predictive ability of GBS-based genomic selection was influenced by the genotype missing data threshold and imputation, as well as by the genomic selection model, with the best model depending on traits and data sets. We devised a simple method for comparing phenotypic vs. genomic selection in terms of predicted yield gain per year for same evaluation costs, whose application to preliminary data for alfalfa and pea in a hypothetical selection scenario for each crop indicated a distinct advantage of genomic selection.

Genome-wide SNP identification, linkage map construction and QTL mapping for seed mineral concentrations and contents in pea (Pisum sativum L.)

BACKGROUND

Marker-assisted breeding is now routinely used in major crops to facilitate more efficient cultivar improvement. This has been significantly enabled by the use of next-generation sequencing technology to identify loci and markers associated with traits of interest. While rich in a range of nutritional components, such as protein, mineral nutrients, carbohydrates and several vitamins, pea (Pisum sativum L.), one of the oldest domesticated crops in the world, remains behind many other crops in the availability of genomic and genetic resources. To further improve mineral nutrient levels in pea seeds requires the development of genome-wide tools. The objectives of this research were to develop these tools by: identifying genome-wide single nucleotide polymorphisms (SNPs) using genotyping by sequencing (GBS); constructing a high-density linkage map and comparative maps with other legumes, and identifying quantitative trait loci (QTL) for levels of boron, calcium, iron, potassium, magnesium, manganese, molybdenum, phosphorous, sulfur, and zinc in the seed, as well as for seed weight.

RESULTS

In this study, 1609 high quality SNPs were found to be polymorphic between 'Kiflica' and 'Aragorn', two parents of an F6-derived recombinant inbred line (RIL) population. Mapping 1683 markers including 75 previously published markers and 1608 SNPs developed from the present study generated a linkage map of size 1310.1 cM. Comparative mapping with other legumes demonstrated that the highest level of synteny was observed between pea and the genome of Medicago truncatula. QTL analysis of the RIL population across two locations revealed at least one QTL for each of the mineral nutrient traits. In total, 46 seed mineral concentration QTLs, 37 seed mineral content QTLs, and 6 seed weight QTLs were discovered. The QTLs explained from 2.4% to 43.3% of the phenotypic variance.

CONCLUSION

The genome-wide SNPs and the genetic linkage map developed in this study permitted QTL identification for pea seed mineral nutrients that will serve as important resources to enable marker-assisted selection (MAS) for nutritional quality traits in pea breeding programs.

A Combined Comparative Transcriptomic, Metabolomic, and Anatomical Analyses of Two Key Domestication Traits: Pod Dehiscence and Seed Dormancy in Pea (Pisum sp.)

The origin of the agriculture was one of the turning points in human history, and a central part of this was the evolution of new plant forms, domesticated crops. Seed dispersal and germination are two key traits which have been selected to facilitate cultivation and harvesting of crops. The objective of this study was to analyze anatomical structure of seed coat and pod, identify metabolic compounds associated with water-impermeable seed coat and differentially expressed genes involved in pea seed dormancy and pod dehiscence. Comparative anatomical, metabolomics, and transcriptomic analyses were carried out on wild dormant, dehiscent Pisum elatius (JI64, VIR320) and cultivated, indehiscent Pisum sativum non-dormant (JI92, Cameor) and recombinant inbred lines (RILs). Considerable differences were found in texture of testa surface, length of macrosclereids, and seed coat thickness. Histochemical and biochemical analyses indicated genotype related variation in composition and heterogeneity of seed coat cell walls within macrosclereids. Liquid chromatography-electrospray ionization/mass spectrometry and Laser desorption/ionization-mass spectrometry of separated seed coats revealed significantly higher contents of proanthocyanidins (dimer and trimer of gallocatechin), quercetin, and myricetin rhamnosides and hydroxylated fatty acids in dormant compared to non-dormant genotypes. Bulk Segregant Analysis coupled to high throughput RNA sequencing resulted in identification of 770 and 148 differentially expressed genes between dormant and non-dormant seeds or dehiscent and indehiscent pods, respectively. The expression of 14 selected dormancy-related genes was studied by qRT-PCR. Of these, expression pattern of four genes: porin (MACE-S082), peroxisomal membrane PEX14-like protein (MACE-S108), 4-coumarate CoA ligase (MACE-S131), and UDP-glucosyl transferase (MACE-S139) was in agreement in all four genotypes with Massive analysis of cDNA Ends (MACE) data. In case of pod dehiscence, the analysis of two candidate genes (SHATTERING and SHATTERPROOF) and three out of 20 MACE identified genes (MACE-P004, MACE-P013, MACE-P015) showed down-expression in dorsal and ventral pod suture of indehiscent genotypes. Moreover, MACE-P015, the homolog of peptidoglycan-binding domain or proline-rich extensin-like protein mapped correctly to predicted Dpo1 locus on PsLGIII. This integrated analysis of the seed coat in wild and cultivated pea provides new insight as well as raises new questions associated with domestication and seed dormancy and pod dehiscence.

Gene Classification and Mining of Molecular Markers Useful in Red Clover (Trifolium pratense) Breeding

Red clover (Trifolium pratense) is an important forage plant worldwide. This study was directed to broadening current knowledge of red clover's coding regions and enhancing its utilization in practice by specific reanalysis of previously published assembly. A total of 42,996 genes were characterized using Illumina paired-end sequencing after manual revision of Blast2GO annotation. Genes were classified into metabolic and biosynthetic pathways in response to biological processes, with 7,517 genes being assigned to specific pathways. Moreover, 17,727 enzymatic nodes in all pathways were described. We identified 6,749 potential microsatellite loci in red clover coding sequences, and we characterized 4,005 potential simple sequence repeat (SSR) markers as generating polymerase chain reaction products preferentially within 100-350 bp. Marker density of 1 SSR marker per 12.39 kbp was achieved. Aligning reads against predicted coding sequences resulted in the identification of 343,027 single nucleotide polymorphism (SNP) markers, providing marker density of one SNP marker per 144.6 bp. Altogether, 95 SSRs in coding sequences were analyzed for 50 red clover varieties and a collection of 22 highly polymorphic SSRs with pooled polymorphism information content >0.9 was generated, thus obtaining primer pairs for application to diversity studies in T. pratense. A set of 8,623 genome-wide distributed SNPs was developed and used for polymorphism evaluation in individual plants. The polymorphic information content ranged from 0 to 0.375. Temperature switch PCR was successfully used in single-marker SNP genotyping for targeted coding sequences and for heterozygosity or homozygosity confirmation in validated five loci. Predicted large sets of SSRs and SNPs throughout the genome are key to rapidly implementing genome-based breeding approaches, for identifying genes underlying key traits, and for genome-wide association studies. Detailed knowledge of genetic relationships among breeding material can also be useful for breeders in planning crosses or for plant variety protection. Single-marker assays are useful for diagnostic applications.

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.

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.