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

Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments

Chickpea, renowned for its exceptional nutritional value, stands as a crucial crop, serving as a dietary staple in various parts of the world. However, its productivity faces a significant challenge in the form of drought stress. This challenge highlights the urgent need to find genetic markers linked to drought tolerance for effective breeding programs. The primary objective of this study is to identify genetic markers associated with drought tolerance to facilitate effective breeding programs. To address this, we cultivated 185 chickpea accessions in two distinct locations in Lebanon over a two-year period, subjecting them to both irrigated and rain-fed environments. We assessed 11 drought-linked traits, including morphology, growth, yield, and tolerance score. SNP genotyping revealed 1344 variable SNP markers distributed across the chickpea genome. Genetic diversity across populations originating from diverse geographic locations was unveiled by the PCA, clustering, and structure analysis indicating that these genotypes have descend from five or four distinct ancestors. A genome-wide association study (GWAS) revealed several marker trait associations (MTAs) associated with the traits evaluated. Within the rainfed conditions, 11 significant markers were identified, each associated with distinct chickpea traits. Another set of 11 markers exhibited associations in both rainfed and irrigated environments, reflecting shared genetic determinants across these conditions for the same trait. The analysis of linkage disequilibrium (LD) highlighted two genomic regions with notably strong LD, suggesting significant interconnections among several investigated traits. This was further investigated by the correlation between major markers associated with these traits. Gene annotation of the identified markers has unveiled insights into 28 potential genes that play a role in influencing various chickpea drought-linked traits. These traits encompass crucial aspects such as blooming organ development, plant growth, seed weight, starch metabolism, drought regulation, and height index. Among the identified genes are CPN60-2, hsp70, GDSL(GELP), AHL16, NAT3, FAB1B, bZIP, and GL21. These genes collectively contribute to the multifaceted response of chickpea plants to drought stress. Our identified genetic factors exert their influence in both irrigated and rainfed environments, emphasizing their importance in shaping chickpea characteristics.

Genetic Diversity Assessment of Spanish and Some Endangered Tunisian Pea (Pisum sativum L.) Accessions Based on Microsatellite Markers (SSRs)

In the current investigation, 28 accessions of Spanish and Tunisian peas were characterized by eight SSR polymorphic markers to assess their genetic diversity. Many methods have been applied to evaluate these relationships including diversity indices, analysis of molecular variance, cluster analysis, and population structure. The means of diversity indices, the polymorphism information content (PIC), the allelic richness, and the Shannon information index were 0.51, 3.87, and 0.9, respectively. These results revealed a large polymorphism (84.15 %) which produced a higher degree of genetic distance amongst the accessions. The unweighted pair group approach with arithmetic mean divided the collection of these accessions into three major genetic clusters. Therefore, this article has clearly demonstrated the usefulness of the SSR markers that can significantly contribute to the management and conservation of pea germplasm in these countries, as well as to future reproduction.

Vignette of Vigna domestication: From archives to genomics

The genus Vigna comprises fast-growing, diploid legumes, cultivated in tropical and subtropical parts of the world. It comprises more than 200 species among which Vigna angularis, Vigna radiata, Vigna mungo, Vigna aconitifolia, Vigna umbellata, Vigna unguiculata, and Vigna vexillata are of enormous agronomic importance. Human selection along with natural variability within these species encompasses a vital source for developing new varieties. The present review convokes the early domestication history of Vigna species based on archeological pieces of evidence and domestication-related traits (DRTs) together with genetics of domestication. Traces of early domestication of Vigna have been evidenced to spread across several temperate and tropical regions of Africa, Eastern Asia, and few parts of Europe. Several DRTs of Vigna species, such as pod shattering, pod and seed size, dormancy, seed coat, seed color, maturity, and pod dehiscence, can clearly differentiate wild species from their domesticates. With the advancement in next-generation high-throughput sequencing techniques, exploration of genetic variability using recently released reference genomes along with de novo sequencing of Vigna species have provided a framework to perform genome-wide association and functional studies to figure out different genes related to DRTs. In this review, genes and quantitative trait loci (QTLs) related to DRTs of different Vigna species have also been summarized. Information provided in this review will enhance the in-depth understanding of the selective pressures that causes crop domestication along with nature of evolutionary selection made in unexplored Vigna species. Furthermore, correlated archeological and domestication-related genetic evidence will facilitate Vigna species to be considered as suitable model plants.

Low-Cost Platform for Multiplexed Electrochemical Melting Curve Analysis

Detection and identification of single nucleotide polymorphisms (SNPs) have garnered increasing interest in the past decade, finding potential application in detection of antibiotic resistance, advanced forensic science, as well as clinical diagnostics and prognostics, moving toward the realization of personalized medicine. Many different techniques have been developed for genotyping SNPs, and ideally these techniques should be rapid, easy-to-use, cost-effective, flexible, scalable, easily automated, and requiring minimal end-user intervention. While high-resolution melting curve analysis has been widely used for the detection of SNPs, fluorescence detection does not meet many of the desired requirements, and electrochemical detection is an attractive alternative due to its high sensitivity, simplicity, cost-effectiveness, and compatibility with microfabrication. Herein, we describe the multiplexed electrochemical melting curve analysis of duplex surfaces tethered to electrodes of an array. In this approach, thiolated probes designed to hybridize to a DNA sequence containing the SNP to be interrogated are immobilized on gold electrodes. Asymmetric PCR using a ferrocene-labeled forward primer is used to generate this single-stranded redox-labeled PCR amplicon. Following hybridization with the probe immobilized on the electrode surface, the electrode array is exposed to a controlled ramping of temperature, with concomitant constant washing of the electrode array surface while simultaneously carrying out voltammetric measurements. The optimum position of the site complementary to the SNP site in the immobilized probe to achieve maximum differentiation in melting temperature between wild-type and single base mismatch, thus facilitating allelic discrimination, was determined and applied to the detection of a cardiomyopathy associated SNP.

Genomics Associated Interventions for Heat Stress Tolerance in Cool Season Adapted Grain Legumes

Cool season grain legumes occupy an important place among the agricultural crops and essentially provide multiple benefits including food supply, nutrition security, soil fertility improvement and revenue for farmers all over the world. However, owing to climate change, the average temperature is steadily rising, which negatively affects crop performance and limits their yield. Terminal heat stress that mainly occurred during grain development phases severely harms grain quality and weight in legumes adapted to the cool season, such as lentils, faba beans, chickpeas, field peas, etc. Although, traditional breeding approaches with advanced screening procedures have been employed to identify heat tolerant legume cultivars. Unfortunately, traditional breeding pipelines alone are no longer enough to meet global demands. Genomics-assisted interventions including new-generation sequencing technologies and genotyping platforms have facilitated the development of high-resolution molecular maps, QTL/gene discovery and marker-assisted introgression, thereby improving the efficiency in legumes breeding to develop stress-resilient varieties. Based on the current scenario, we attempted to review the intervention of genomics to decipher different components of tolerance to heat stress and future possibilities of using newly developed genomics-based interventions in cool season adapted grain legumes.

Identification of Root Rot Resistance QTLs in Pea Using Fusarium solani f. sp. pisi-Responsive Differentially Expressed Genes

Pisum sativum (pea) yields in the United States have declined significantly over the last decades, predominantly due to susceptibility to root rot diseases. One of the main causal agents of root rot is the fungus Fusarium solani f. sp. pisi (Fsp), leading to yield losses ranging from 15 to 60%. Determining and subsequently incorporating the genetic basis for resistance in new cultivars offers one of the best solutions to control this pathogen; however, no green-seeded pea cultivars with complete resistance to Fsp have been identified. To date, only partial levels of resistance to Fsp has been identified among pea genotypes. SNPs mined from Fsp-responsive differentially expressed genes (DEGs) identified in a preceding study were utilized to identify QTLs associated with Fsp resistance using composite interval mapping in two recombinant inbred line (RIL) populations segregating for partial root rot resistance. A total of 769 DEGs with single nucleotide polymorphisms (SNPs) were identified, and the putative SNPs were evaluated for being polymorphic across four partially resistant and four susceptible P. sativum genotypes. The SNPs with validated polymorphisms were used to screen two RIL populations using two phenotypic criteria: root disease severity and plant height. One QTL, WB.Fsp-Ps 5.1 that mapped to chromosome 5 explained 14.8% of the variance with a confidence interval of 10.4 cM. The other four QTLs located on chromosomes 2, 3, and 5, explained 5.3-8.1% of the variance. The use of SNPs derived from Fsp-responsive DEGs for QTL mapping proved to be an efficient way to identify molecular markers associated with Fsp resistance in pea. These QTLs are potential candidates for marker-assisted selection and gene pyramiding to obtain high levels of partial resistance in pea cultivars to combat root rot caused by Fsp.

Omics resources and omics-enabled approaches for achieving high productivity and improved quality in pea (Pisum sativum L.)

Pea (Pisum sativum L.), a cool-season legume crop grown in more than 85 countries, is the second most important grain legume and one of the major green vegetables in the world. While pea was historically studied as the genetic model leading to the discovery of the laws of genetics, pea research has lagged behind that of other major legumes in the genomics era, due to its large and complex genome. The evolving climate change and growing population have posed grand challenges to the objective of feeding the world, making it essential to invest research efforts to develop multi-omics resources and advanced breeding tools to support fast and continuous development of improved pea varieties. Recently, the pea researchers have achieved key milestones in omics and molecular breeding. The present review provides an overview of the recent important progress including the development of genetic resource databases, high-throughput genotyping assays, reference genome, genes/QTLs responsible for important traits, transcriptomic, proteomic, and phenomic atlases of various tissues under different conditions. These multi-faceted resources have enabled the successful implementation of various markers for monitoring early-generation populations as in marker-assisted backcrossing breeding programs. The emerging new breeding approaches such as CRISPR, speed breeding, and genomic selection are starting to change the paradigm of pea breeding. Collectively, the rich omics resources and omics-enable breeding approaches will enhance genetic gain in pea breeding and accelerate the release of novel pea varieties to meet the elevating demands on productivity and quality.

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.

Population Structure and Genetic Diversity in Korean Cowpea Germplasm Based on SNP Markers

Cowpea is one of the most essential legume crops providing inexpensive dietary protein and nutrients. The aim of this study was to understand the genetic diversity and population structure of global and Korean cowpea germplasms. A total of 384 cowpea accessions from 21 countries were genotyped with the Cowpea iSelect Consortium Array containing 51,128 single-nucleotide polymorphisms (SNPs). After SNP filtering, a genetic diversity study was carried out using 35,116 SNPs within 376 cowpea accessions, including 229 Korean accessions. Based on structure and principal component analysis, a total of 376 global accessions were divided into four major populations. Accessions in group 1 were from Asia and Europe, those in groups 2 and 4 were from Korea, and those in group 3 were from West Africa. In addition, 229 Korean accessions were divided into three major populations (Q1, Jeonra province; Q2, Gangwon province; Q3, a mixture of provinces). Additionally, the neighbor-joining tree indicated similar results. Further genetic diversity analysis within the global and Korean population groups indicated low heterozygosity, a low polymorphism information content, and a high inbreeding coefficient in the Korean cowpea accessions. The population structure analysis will provide useful knowledge to support the genetic potential of the cowpea breeding program, especially in Korea.

Allele-specific PCR with a novel data processing method based on difference value for single nucleotide polymorphism genotyping of ALDH2 gene

Single nucleotide polymorphism (SNP) analysis based on allele-specific polymerase chain reaction (AS-PCR) is a relatively effective and economical method compared with other genotyping technologies such as DNA sequencing, DNA hybridization and isothermal amplification strategies. But AS-PCR is limited by its labor-intensive optimization of reaction parameters and time-consuming result assessment. In this study, we put forward a novel idea of data processing to address this problem. SNP analysis was accomplished by AS-PCR with endpoint electrochemical detection. For each sample, two separate reactions were run simultaneously with two sets of allele-specific primers (wild-type primers for W system and mutant primers for M system). We measured their redox current signals on screen-printed electrodes once AS-PCR finished and calculated the difference value of current signals between two systems to determine the genotyping result. Based on the difference value of fluorescent signals, real-time fluorescent PCR was used to study reaction parameters in AS-PCR. With screened parameters, we obtained the genotyping results within 50 min. 36 hair-root samples from volunteers were analyzed by our method and their genotypes of ALDH2 gene (encoding aldehyde dehydrogenase 2) were totally identical with data from commercialized sequencing. Our work first employed difference value between two reaction systems to differentiate allele and provided a novel idea of data processing in AS-PCR method. It is able to promote the quick analysis of SNP in the fields of health monitor, disease precaution, and personalized diagnosis and treatment.

SYMMETRIC PETALS 1 Encodes an ALOG Domain Protein that Controls Floral Organ Internal Asymmetry in Pea (Pisum sativum L.)

In contrast to typical radially symmetrical flowers, zygomorphic flowers, such as those produced by pea (Pisum sativum L.), have bilateral symmetry, manifesting dorsoventral (DV) and organ internal (IN) asymmetry. However, the molecular mechanism controlling IN asymmetry remains largely unclear. Here, we used a comparative mapping approach to clone SYMMETRIC PETALS 1 (SYP1), which encodes a key regulator of floral organ internal asymmetry. Phylogenetic analysis showed that SYP1 is an ortholog of Arabidopsis thaliana LIGHT-DEPENDENT SHORT HYPOCOTYL 3 (LSH3), an ALOG (Arabidopsis LSH1 and Oryza G1) family transcription factor. Genetic analysis and physical interaction assays showed that COCHLEATA (COCH, Arabidopsis BLADE-ON-PETIOLE ortholog), a known regulator of compound leaf and nodule identity in pea, is involved in organ internal asymmetry and interacts with SYP1. COCH and SYP1 had similar expression patterns and COCH and SYP1 target to the nucleus. Furthermore, our results suggested that COCH represses the 26S proteasome-mediated degradation of SYP1 and regulates its abundance. Our study suggested that the COCH-SYP1 module plays a pivotal role in floral organ internal asymmetry development in legumes.

Identification of potential candidate genes controlling pea aphid tolerance in a Pisum fulvum high-density integrated DArTseq SNP-based genetic map

BACKGROUND

Pea (Pisum sativum) is one of the most important temperate grain legumes in the world, and its production is severely constrained by the pea aphid (Acyrthosiphon pisum). Wild relatives, such as P. fulvum, are valuable sources of allelic diversity to improve the genetic resistance of cultivated pea species against A. pisum attack. To unravel the genetic control underlying resistance to the pea aphid attack, a quantitative trait loci (QTL) analysis was performed using the previously developed high density integrated genetic linkage map originated from an intraspecific recombinant inbred line (RIL) population (P. fulvum: IFPI3260 × IFPI3251).

RESULTS

We accurately evaluated specific resistance responses to pea aphid that allowed the identification, for the first time, of genomic regions that control plant damage and aphid reproduction. Eight QTLs associated with tolerance to pea aphid were identified in LGs I, II, III, IV and V, which individually explained from 17.0% to 51.2% of the phenotypic variation depending on the trait scored, and as a whole from 17.0% to 88.6%. The high density integrated genetic linkage map also allowed the identification of potential candidate genes co-located with the QTLs identified.

CONCLUSIONS

Our work shows how the survival of P. fulvum after the pea aphid attack depends on the triggering of a multi-component protection strategy that implies a quantitative tolerance. The genomic regions associated with the tolerance responses of P. fulvum during A. pisum infestation have provided six potential candidate genes that could be useful in marker-assisted selection (MAS) and genomic assisted breeding (GAB) after functional validation in the future. © 2019 Society of Chemical Industry.

Identification of quantitative trait loci (QTL) controlling resistance to pea weevil (Bruchus pisorum) in a high-density integrated DArTseq SNP-based genetic map of pea

Pea weevil (Bruchus pisorum) is a damaging insect pest affecting pea (Pisum sativum) production worldwide. No resistant cultivars are available, although some levels of incomplete resistance have been identified in Pisum germplasm. To decipher the genetic control underlying the resistance previously identify in P. sativum ssp. syriacum, a recombinant inbred line (RIL F8:9) population was developed. The RIL was genotyped through Diversity Arrays Technology PL's DArTseq platform and screened under field conditions for weevil seed infestation and larval development along 5 environments. A newly integrated genetic linkage map was generated with a subset of 6,540 markers, assembled into seven linkage groups, equivalent to the number of haploid pea chromosomes. An accumulated distance of 2,503 cM was covered with an average density of 2.61 markers cM-1. The linkage map allowed the identification of three QTLs associated to reduced seed infestation along LGs I, II and IV. In addition, a QTL for reduced larval development was also identified in LGIV. Expression of these QTLs varied with the environment, being particularly interesting QTL BpSI.III that was detected in most of the environments studied. This high-saturated pea genetic map has also allowed the identification of seven potential candidate genes co-located with QTLs for marker-assisted selection, providing an opportunity for breeders to generate effective and sustainable strategies for weevil control.

Neutralized chimeric DNA probe for the improvement of GC-rich RNA detection specificity on the nanowire field-effect transistor

Silicon nanowire (SiNW) field-effect transistors (FETs) is a powerful tool in genetic molecule analysis because of their high sensitivity, short detection time, and label-free detection. In nucleic acid detection, GC-rich nucleic acid sequences form self- and cross-dimers and stem-loop structures, which can easily obtain data containing signals from nonspecific DNA binding. The features of GC-rich nucleic acid sequences cause inaccuracies in nucleic acid detection and hinder the development of precision medicine. To improve the inaccurate detection results, we used phosphate-methylated (neutral) nucleotides to synthesize the neutralized chimeric DNA oligomer probe. The probe fragment originated from a primer for the detection of hepatitis C virus (HCV) genotype 3b, and single-mismatched and perfect-matched targets were designed for single nucleotide polymorphisms (SNP) detection on the SiNW FET device. Experimental results revealed that the HCV-3b chimeric neutralized DNA (nDNA) probe exhibited better performance for SNP discrimination in 10 mM bis-tris propane buffer at 25 °C than a regular DNA probe. The SNP discrimination of the nDNA probe could be further improved at 40 °C on the FET device. Consequently, the neutralized chimeric DNA probe could successfully distinguish SNP in the detection of GC-rich target sequences under optimal operating conditions on the SiNW FET device.

ZNA probe immobilized single-use electrodes for impedimetric detection of nucleic acid hybridization related to single nucleotide mutation

The development of a low-cost and disposable biosensing technologies has received a great interest of healthcare for the sensitive and reliable detection of single nucleotide mutation related to single nucleotide polymorphisms (SNPs). In the present study, an impedimetric biosensing platform based on zip nucleic acids (ZNA) was developed for the sensitive detection of Factor V Leiden (FV Leiden) mutation. After optimization of experimental parameters, the sequence selective hybridization between ZNA probe and target related to FV Leiden mutation was evaluated via electrochemical impedance spectroscopy technique (EIS) by measuring changes at the charge transfer resistance, R_ct. Sensitive and selective impedimetric analysis was performed using carbon nanofiber (CNF) modified screen printed electrodes (SPE) and multi-channel screen printed array of electrodes (MULTIx8 CNF-SPE) resulting in a relatively shorter time in comparison to conventional methods. The selectivity of ZNA probe to mutation-free DNA sequences was also investigated. The applicability of single-use ZNA biosensor was also tested in synthetic PCR samples containing a single base mutation.

Enzymatic Litmus Test for Selective Colorimetric Detection of C-C Single Nucleotide Polymorphisms

A paper based litmus test has been developed using modulation of urease enzyme activity for detection of C-C mismatch single nucleotide polymorphisms (SNPs) by the naked eye. Urease is first inactivated with silver ions and printed onto paper microzones. Addition of DNA containing C-C mismatches reactivates urease via binding of Ag(I), allowing restoration of urease activity, hydrolysis of urea to produce ammonia, and an increase in pH, which is monitored colorimetrically using a pH indicator with a limit of detection of 11 nM DNA in 40 min. The assay system is easy to use, portable, and stable for at least 30 days at ambient temperature. To assess the versatility and practical application of the paper sensor, we used it to identify a G > C transversion present in human genomic DNA from a ductal carcinoma cell line, a mutation commonly found in breast cancer. We believe this new assay system has the potential to be a low-cost method for rapidly identifying DNA with the C-C mismatch SNP as a means of cancer screening in resource-limited areas.

Genetic Mapping of the Incompatibility Locus in Olive and Development of a Linked Sequence-Tagged Site Marker

The genetic control of self-incompatibility (SI) has been recently disclosed in olive. Inter-varietal crossing confirmed the presence of only two incompatibility groups (G1 and G2), suggesting a simple Mendelian inheritance of the trait. A double digest restriction associated DNA (ddRAD) sequencing of a biparental population segregating for incompatibility groups has been performed and high-density linkage maps were constructed in order to map the SI locus and identify gene candidates and linked markers. The progeny consisted of a full-sib family of 229 individuals derived from the cross 'Leccino' (G1) × 'Dolce Agogia' (G2) varieties, segregating 1:1 (G1:G2), in accordance with a diallelic self-incompatibility (DSI) model. A total of 16,743 single nucleotide polymorphisms was identified, 7,006 in the female parent 'Leccino' and 9,737 in the male parent 'Dolce Agogia.' Each parental map consisted of 23 linkage groups and showed an unusual large size (5,680 cM in 'Leccino' and 3,538 cM in 'Dolce Agogia'). Recombination was decreased across all linkage groups in pollen mother cells of 'Dolce Agogia,' the parent with higher heterozygosity, compared to megaspore mother cells of 'Leccino,' in a context of a species that showed exceptionally high recombination rates. A subset of 109 adult plants was assigned to either incompatibility group by a stigma test and the diallelic self-incompatibility (DSI) locus was mapped to an interval of 5.4 cM on linkage group 18. This region spanned a size of approximately 300 Kb in the olive genome assembly. We developed a sequence-tagged site marker in the DSI locus and identified five haplotypes in 57 cultivars with known incompatibility group assignment. A combination of two single-nucleotide polymorphisms (SNPs) was sufficient to predict G1 or G2 phenotypes in olive cultivars, enabling early marker-assisted selection of compatible genotypes and allowing for a rapid screening of inter-compatibility among cultivars in order to guarantee effective fertilization and increase olive production. The construction of high-density linkage maps has led to the development of the first functional marker in olive and provided positional candidate genes in the SI locus.

Magnetic beads assay based on Zip nucleic acid for electrochemical detection of Factor V Leiden mutation

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation among people. Development of reliable methods for the detection of SNP is crucial in aspects of molecular diagnosis and personalized medicine. In our study, a genomagnetic assay in combination with zip nucleic acid (ZNA) for electrochemical detection of SNP related to Factor V Leiden mutation. For the first time in the literature, a new generation nucleic acid; ZNA was applied herein for electrochemical monitoring of nucleic acid hybridization. Streptavidin coated magnetic beads (MBs) were used for preparation of samples containing ZNA-DNA hybrid and accordingly, the guanine signal was measured as a response of hybridization related to Factor V Leiden mutation by carbon nanofibers (CNF) modified screen printed electrodes (SPE) and multi-channel screen printed array of electrodes (CNF-MULTI SPEx8). The detection limit (DL) was found to be 3.79 μg/mL (376 nM) and, 11.63 μg/mL (1.624 μM), respectively by CNF-SPE and CNF-MULTI SPEx8. The selectivity of ZNA probe to mutation-free DNA sequences was also investigated in contrast to DNA probe. The applicability of ZNA based magnetic beads assay to sequence selective hybridization related to Factor V Leiden was also tested in synthetic PCR samples.

Analysis of Genetic Variation and Enhancement of Salt Tolerance in French Pea (Pisum Sativum L.)

Pisum sativum L. (field pea) is a crop of a high nutritional value and seed oil content. The characterization of pea germplasm is important to improve yield and quality. This study aimed at using fatty acid profiling and amplified fragment length polymorphism (AFLP) markers to evaluate the variation and relationships of 25 accessions of French pea. It also aimed to conduct a marker-trait associations analysis using the crude oil content as the target trait for this analysis, and to investigate whether 5-aminolevulinic acid (ALA) could enhance salt tolerance in the pea germplasm. The percentage of crude oil of the 25 pea genotypes varied from 2.6 to 3.5%, with a mean of 3.04%. Major fatty acids in all of the accessions were linoleic acid. Moreover, the 12 AFLP markers used were polymorphic. The cluster analysis based on fatty acids data or AFLP data divided the 25 pea germplasm into two main clusters. The gene diversity of the AFLP markers varied from 0.21 to 0.58, with a mean of 0.41. Polymorphic information content (PIC) of pea germplasm varied from 0.184 to 0.416 with a mean of 0.321, and their expected heterozygosity (He) varied from 0.212 to 0.477 with a mean of 0.362. The AFLP results revealed that the Nain Ordinaire cultivar has the highest level of genetic variability, whereas Elatius 3 has the lowest level. Three AFLP markers (E-AAC/M-CAA, E-AAC/M-CAC, and E-ACA/M-CAG) were significantly associated with the crude oil content trait. The response of the Nain Ordinaire and Elatius 3 cultivars to high salinity stress was studied. High salinity (150 mM NaCl) slightly reduced the photosynthetic pigments contents in Nain Ordinaire leaves at a non-significant level, however, the pigments contents in the Elatius 3 leaves were significantly reduced by high salinity. Antioxidant enzymes (APX-ascorbate peroxidase; CAT-catalase; and POD-peroxidase) activities were significantly induced in the Nain Ordinaire cultivar, but non-significantly induced in Elatius 3 by high salinity. Priming the salt-stressed Nain Ordinaire and Elatius 3 plants with ALA significantly enhanced the pigments biosynthesis, antioxidant enzymes activities, and stress-related genes expression, as compared to the plants stressed with salt alone. In conclusion, this study is amongst the first investigations that conducted marker-trait associations in pea, and revealed a sort of correlation between the diversity level and salt tolerance.

Development and Applications of a High Throughput Genotyping Tool for Polyploid Crops: Single Nucleotide Polymorphism (SNP) Array

Polypoid species play significant roles in agriculture and food production. Many crop species are polyploid, such as potato, wheat, strawberry, and sugarcane. Genotyping has been a daunting task for genetic studies of polyploid crops, which lags far behind the diploid crop species. Single nucleotide polymorphism (SNP) array is considered to be one of, high-throughput, relatively cost-efficient and automated genotyping approaches. However, there are significant challenges for SNP identification in complex, polyploid genomes, which has seriously slowed SNP discovery and array development in polyploid species. Ploidy is a significant factor impacting SNP qualities and validation rates of SNP markers in SNP arrays, which has been proven to be a very important tool for genetic studies and molecular breeding. In this review, we (1) discussed the pros and cons of SNP array in general for high throughput genotyping, (2) presented the challenges of and solutions to SNP calling in polyploid species, (3) summarized the SNP selection criteria and considerations of SNP array design for polyploid species, (4) illustrated SNP array applications in several different polyploid crop species, then (5) discussed challenges, available software, and their accuracy comparisons for genotype calling based on SNP array data in polyploids, and finally (6) provided a series of SNP array design and genotype calling recommendations. This review presents a complete overview of SNP array development and applications in polypoid crops, which will benefit the research in molecular breeding and genetics of crops with complex genomes.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

A High-Density Integrated DArTseq SNP-Based Genetic Map of Pisum fulvum and Identification of QTLs Controlling Rust Resistance

Pisum fulvum, a wild relative of pea is an important source of allelic diversity to improve the genetic resistance of cultivated species against fungal diseases of economic importance like the pea rust caused by Uromyces pisi. To unravel the genetic control underlying resistance to this fungal disease, a recombinant inbred line (RIL) population was generated from a cross between two P. fulvum accessions, IFPI3260 and IFPI3251, and genotyped using Diversity Arrays Technology. A total of 9,569 high-quality DArT-Seq and 8,514 SNPs markers were generated. Finally, a total of 12,058 markers were assembled into seven linkage groups, equivalent to the number of haploid chromosomes of P. fulvum and P. sativum. The newly constructed integrated genetic linkage map of P. fulvum covered an accumulated distance of 1,877.45 cM, an average density of 1.19 markers cM^-1 and an average distance between adjacent markers of 1.85 cM. The composite interval mapping revealed three QTLs distributed over two linkage groups that were associated with the percentage of rust disease severity (DS%). QTLs UpDSII and UpDSIV were located in the LGs II and IV respectively and were consistently identified both in adult plants over 3 years at the field (Córdoba, Spain) and in seedling plants under controlled conditions. Whenever they were detected, their contribution to the total phenotypic variance varied between 19.8 and 29.2. A third QTL (UpDSIV.2) was also located in the LGIVand was environmentally specific as was only detected for DS % in seedlings under controlled conditions. It accounted more than 14% of the phenotypic variation studied. Taking together the data obtained in the study, it could be concluded that the expression of resistance to fungal diseases in P. fulvum originates from the resistant parent IFPI3260.

High-Throughput RNA-Seq Data Analysis of the Single Nucleotide Polymorphisms (SNPs) and Zygomorphic Flower Development in Pea (Pisum sativum L.)

Pea (Pisum sativum L.) is a model plant that has been used in classical genetics and organ development studies. However, its large and complex genome has hindered research investigations in pea. Here, we generated transcriptomes from different tissues or organs of three pea accessions using next-generation sequencing to assess single nucleotide polymorphisms (SNPs), and further investigated petal differentially expressed genes to elucidate the mechanisms regulating floral zygomorphy. Eighteen samples were sequenced, which yielded a total of 617 million clean reads, and de novo assembly resulted in 87,137 unigenes. A total of 9044 high-quality SNPs were obtained among the three accessions, and a consensus map was constructed. We further discovered several dorsoventral asymmetrically expressed genes that were confirmed by qRT-PCR among different petals, including previously reported three CYC-like proliferating cell factor (TCP) genes. One MADS-box gene was highly expressed in dorsal petals, and several MYB factors were predominantly expressed among dorsal, lateral, and/or ventral petals, together with a ventrally expressed TCP gene. In sum, our comprehensive database complements the existing resources for comparative genetic mapping and facilitates future investigations in legume zygomorphic flower development.

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.

Molecular diversity of sunflower populations maintained as genetic resources is affected by multiplication processes and breeding for major traits

SNP genotyping of 114 cultivated sunflower populations showed that the multiplication process and the main traits selected during breeding of sunflower cultivars drove molecular diversity of the populations. The molecular diversity in a set of 114 cultivated sunflower populations was studied by single-nucleotide polymorphism genotyping. These populations were chosen as representative of the 400 entries in the INRA collection received or developed between 1962 and 2011 and made up of land races, open-pollinated varieties, and breeding pools. Mean allele number varied from 1.07 to 1.90. Intra-population variability was slightly reduced according to the number of multiplications since entry but some entries were probably largely homozygous when received. A principal component analysis was used to study inter-population variability. The first 3 axes accounted for 17% of total intra-population variability. The first axis was significantly correlated with seed oil content, more closely than just the distinction between oil and confectionary types. The second axis was related to the presence or absence of restorer genes and the third axis to flowering date and possibly to adaptation to different climates. Our results provide arguments highlighting the effect of the maintenance process on the within population genetic variability as well as on the impact of breeding for major agronomic traits on the between population variability of the collection. Propositions are made to improve sunflower population maintenance procedures to keep maximum genetic variability for future breeding.

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.

Genetic Diversity and Population Structure of Cowpea (Vigna unguiculata L. Walp)

The genetic diversity of cowpea was analyzed, and the population structure was estimated in a diverse set of 768 cultivated cowpea genotypes from the USDA GRIN cowpea collection, originally collected from 56 countries. Genotyping by sequencing was used to discover single nucleotide polymorphism (SNP) in cowpea and the identified SNP alleles were used to estimate the level of genetic diversity, population structure, and phylogenetic relationships. The aim of this study was to detect the gene pool structure of cowpea and to determine its relationship between different regions and countries. Based on the model-based ancestry analysis, the phylogenetic tree, and the principal component analysis, three well-differentiated genetic populations were postulated from 768 worldwide cowpea genotypes. According to the phylogenetic analyses between each individual, region, and country, we may trace the accession from off-original, back to the two candidate original areas (West and East of Africa) to predict the migration and domestication history during the cowpea dispersal and development. To our knowledge, this is the first report of the analysis of the genetic variation and relationship between globally cultivated cowpea genotypes. The results will help curators, researchers, and breeders to understand, utilize, conserve, and manage the collection for more efficient contribution to international cowpea research.

Ascochyta blight disease of pea (Pisum sativum L.): defence-related candidate genes associated with QTL regions and identification of epistatic QTL

KEY MESSAGE

Advances have been made in our understanding of Ascochyta blight resistance genetics through mapping candidate genes associated with QTL regions and demonstrating the importance of epistatic interactions in determining resistance. Ascochyta blight disease of pea (Pisum sativum L.) is economically significant with worldwide distribution. The causal pathogens are Didymella pinodes, Phoma medicaginis var pinodella and, in South Australia, P. koolunga. This study aimed to identify candidate genes that map to quantitative trait loci (QTL) for Ascochyta blight field disease resistance and to explore the role of epistatic interactions. Candidate genes associated with QTL were identified beginning with 101 defence-related genes from the published literature. Synteny between pea and Medicago truncatula was used to narrow down the candidates for mapping. Fourteen pea candidate sequences were mapped in two QTL mapping populations, A26 × Rovar and A88 × Rovar. QTL peaks, or the intervals containing QTL peaks, for the Asc2.1, Asc4.2, Asc4.3 and Asc7.1 QTL were defined by four of these candidate genes, while another three candidate genes occurred within 1.0 LOD confidence intervals. Epistasis involving QTL × background marker and background marker × background marker interactions contributed to the disease response phenotypes observed in the two mapping populations. For each population, five pairwise interactions exceeded the 5% false discovery rate threshold. Two candidate genes were involved in significant pairwise interactions. Markers in three genomic regions were involved in two or more epistatic interactions. Therefore, this study has identified pea defence-related sequences that are candidates for resistance determination, and that may be useful for marker-assisted selection. The demonstration of epistasis informs breeders that the architecture of this complex quantitative resistance includes epistatic interactions with non-additive effects.

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

BACKGROUND

Progress in genetics and breeding in pea still suffers from the limited availability of molecular resources. SNP markers that can be identified through affordable sequencing processes, without the need for prior genome reduction or a reference genome to assemble sequencing data would allow the discovery and genetic mapping of thousands of molecular markers. Such an approach could significantly speed up genetic studies and marker assisted breeding for non-model species.

RESULTS

A total of 419,024 SNPs were discovered using HiSeq whole genome sequencing of four pea lines, followed by direct identification of SNP markers without assembly using the discoSnp tool. Subsequent filtering led to the identification of 131,850 highly designable SNPs, polymorphic between at least two of the four pea lines. A subset of 64,754 SNPs was called and genotyped by short read sequencing on a subpopulation of 48 RILs from the cross 'Baccara' x 'PI180693'. This data was used to construct a WGGBS-derived pea genetic map comprising 64,263 markers. This map is collinear with previous pea consensus maps and therefore with the Medicago truncatula genome. Sequencing of four additional pea lines showed that 33 % to 64 % of the mapped SNPs, depending on the pairs of lines considered, are polymorphic and can therefore be useful in other crosses. The subsequent genotyping of a subset of 1000 SNPs, chosen for their mapping positions using a KASP™ assay, showed that almost all generated SNPs are highly designable and that most (95 %) deliver highly qualitative genotyping results. Using rather low sequencing coverages in SNP discovery and in SNP inferring did not hinder the identification of hundreds of thousands of high quality SNPs.

CONCLUSIONS

The development and optimization of appropriate tools in SNP discovery and genetic mapping have allowed us to make available a massive new genomic resource in pea. It will be useful for both fine mapping within chosen QTL confidence intervals and marker assisted breeding for important traits in pea improvement.

A SNP-based consensus genetic map for synteny-based trait targeting in faba bean (Vicia faba L.)

Faba bean (Vicia faba L.) is a globally important nitrogen-fixing legume, which is widely grown in a diverse range of environments. In this work, we mine and validate a set of 845 SNPs from the aligned transcriptomes of two contrasting inbred lines. Each V. faba SNP is assigned by BLAST analysis to a single Medicago orthologue. This set of syntenically anchored polymorphisms were then validated as individual KASP assays, classified according to their informativeness and performance on a panel of 37 inbred lines, and the best performing 757 markers used to genotype six mapping populations. The six resulting linkage maps were merged into a single consensus map on which 687 SNPs were placed on six linkage groups, each presumed to correspond to one of the six V. faba chromosomes. This sequence-based consensus map was used to explore synteny with the most closely related crop species, lentil and the most closely related fully sequenced genome, Medicago. Large tracts of uninterrupted colinearity were found between faba bean and Medicago, making it relatively straightforward to predict gene content and order in mapped genetic interval. As a demonstration of this, we mapped a flower colour gene to a 2-cM interval of Vf chromosome 2 which was highly colinear with Mt3. The obvious candidate gene from 78 gene models in the collinear Medicago chromosome segment was the previously characterized MtWD40-1 gene controlling anthocyanin production in Medicago and resequencing of the Vf orthologue showed a putative causative deletion of the entire 5' end of the gene.

High-Throughput Sequencing Reveals Single Nucleotide Variants in Longer-Kernel Bread Wheat

The transcriptomes of bread wheat Yunong 201 and its ethyl methanesulfonate derivative Yunong 3114 were obtained by next-sequencing technology. Single nucleotide variants (SNVs) in the wheat strains were explored and compared. A total of 5907 and 6287 non-synonymous SNVs were acquired for Yunong 201 and 3114, respectively. A total of 4021 genes with SNVs were obtained. The genes that underwent non-synonymous SNVs were significantly involved in ATP binding, protein phosphorylation, and cellular protein metabolic process. The heat map analysis also indicated that most of these mutant genes were significantly differentially expressed at different developmental stages. The SNVs in these genes possibly contribute to the longer kernel length of Yunong 3114. Our data provide useful information on wheat transcriptome for future studies on wheat functional genomics. This study could also help in illustrating the gene functions of the non-synonymous SNVs of Yunong 201 and 3114.

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.

ConPADE: genome assembly ploidy estimation from next-generation sequencing data

As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace. With well-established methodologies, larger and more complex genomes are being tackled, including polyploid plant genomes. Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions. Unfortunately, such collapse is often not ideal, as keeping contigs separate can lead both to improved assembly and also insights about how haplotypes influence phenotype. Here, we describe a first step in avoiding inappropriate collapse during assembly. In particular, we describe ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, we report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. We also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low. We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

Diploid organisms, such as human beings, have two “copies” of each chromosome, whereas polyploid organisms have multiple “copies” (we use quotes to stress that the “copies” are not identical). A key difference between diploid and polyploid organisms is that the “copies” tend to be less similar in polyploid organisms. This difference leads to important differences in the process of de novo genome assembly from short fragments of DNA. In particular, when assembling polyploid organisms, contigs corresponding to different copies of the chromosomes can be quite different, and merging them leads to loss of information. Thus, it is important to maintain distinct contigs, even though they correspond to copies of the same chromosomal region. An important step in doing so is to determine how many truly distinct copies of a chromosomal region are found in a single contig. For example, if there are 12 copies of a particular chromosome, the possible number of distinct copies could be anywhere from 1 to 12. We call this task “contig ploidy estimation”, and present a method for accomplishing it. This set of methods is useful for the de novo assembly of complex, polyploid genomes such as sugarcane, switchgrass, and wheat.

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.

Assessment of genetic variation within a global collection of lentil (Lens culinaris Medik.) cultivars and landraces using SNP markers

Background

Lentil is a self-pollinated annual diploid (2n = 2× = 14) crop with a restricted history of genetic improvement through breeding, particularly when compared to cereal crops. This limited breeding has probably contributed to the narrow genetic base of local cultivars, and a corresponding potential to continue yield increases and stability. Therefore, knowledge of genetic variation and relationships between populations is important for understanding of available genetic variability and its potential for use in breeding programs. Single nucleotide polymorphism (SNP) markers provide a method for rapid automated genotyping and subsequent data analysis over large numbers of samples, allowing assessment of genetic relationships between genotypes.

Results

In order to investigate levels of genetic diversity within lentil germplasm, 505 cultivars and landraces were genotyped with 384 genome-wide distributed SNP markers, of which 266 (69.2%) obtained successful amplification and detected polymorphisms. Gene diversity and PIC values varied between 0.108-0.5 and 0.102-0.375, with averages of 0.419 and 0.328, respectively. On the basis of clarity and interest to lentil breeders, the genetic structure of the germplasm collection was analysed separately for cultivars and landraces. A neighbour-joining (NJ) dendrogram was constructed for commercial cultivars, in which lentil cultivars were sorted into three major groups (G-I, G-II and G-III). These results were further supported by principal coordinate analysis (PCoA) and STRUCTURE, from which three clear clusters were defined based on differences in geographical location. In the case of landraces, a weak correlation between geographical origin and genetic relationships was observed. The landraces from the Mediterranean region, predominantly Greece and Turkey, revealed very high levels of genetic diversity.

Conclusions

Lentil cultivars revealed clear clustering based on geographical origin, but much more limited correlation between geographic origin and genetic diversity was observed for landraces. These results suggest that selection of divergent parental genotypes for breeding should be made actively on the basis of systematic assessment of genetic distance between genotypes, rather than passively based on geographical distance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0150-3) contains supplementary material, which is available to authorized users.

Genetic mapping of legume orthologs reveals high conservation of synteny between lentil species and the sequenced genomes of Medicago and chickpea

Lentil (Lens culinaris Medik.) is a global food crop with increasing importance for food security in south Asia and other regions. Lens ervoides, a wild relative of cultivated lentil, is an important source of agronomic trait variation. Lens is a member of the galegoid clade of the Papilionoideae family, which includes other important dietary legumes such as chickpea (Cicer arietinum) and pea (Pisum sativum), and the sequenced model legume Medicago truncatula. Understanding the genetic structure of Lens spp. in relation to more fully sequenced legumes would allow leveraging of genomic resources. A set of 1107 TOG-based amplicons were identified in L. ervoides and a subset thereof used to design SNP markers for mapping. A map of L. ervoides consisting of 377 SNP markers spread across seven linkage groups was developed using a GoldenGate genotyping array and single SNP marker assays. Comparison with maps of M. truncatula and L. culinaris documented considerable shared synteny and led to the identification of a few major translocations and a major inversion that distinguish Lens from M. truncatula, as well as a translocation that distinguishes L. culinaris from L. ervoides. The identification of chromosome-level differences among Lens spp. will aid in the understanding of introgression of genes from L. ervoides into cultivated L. culinaris, furthering genetic research and breeding applications in lentil.

Genetic diversity and population structure among pea (Pisum sativum L.) cultivars as revealed by simple sequence repeat and novel genic markers

Field pea (Pisum sativum L.) is an important cool season legume crop widely grown around the world. This research provides a basis for selection of pea germplasm across geographical regions in current and future breeding and genetic mapping efforts for pea improvement. Eleven novel genic markers were developed from pea expressed sequence tag (EST) sequences having significant similarity with gene calls from Medicago truncatula spanning at least one intron. In this study, 96 cultivars widely grown or used in breeding programs in the USA and Canada were analyzed for genetic diversity using 31 microsatellite or simple sequence repeat (SSR) and 11 novel EST-derived genic markers. The polymorphic information content varied from 0.01-0.56 among SSR markers and 0.04-0.43 among genic markers. The results showed that SSR and EST-derived genic markers displayed one or more highly reproducible, multi-allelic, and easy to score loci ranging from 200 to 700 bp in size. Genetic diversity was assessed through unweighted neighbor-joining method, and 96 varieties were grouped into three main clusters based on the dissimilarity matrix. Four subpopulations were determined through STRUCTURE analysis with no significant geographic separation of the subpopulations. The findings of the present study can be used to select diverse genotypes to be used as parents of crosses aimed for breeding improved pea cultivars.

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.

Diversity in 113 cowpea [Vigna unguiculata (L) Walp] accessions assessed with 458 SNP markers

Single Nucleotide Polymorphism (SNP) markers were used in characterization of 113 cowpea accessions comprising of 108 from Ghana and 5 from abroad. Leaf tissues from plants cultivated at the University of Ghana were genotyped at KBioscience in the United Kingdom. Data was generated for 477 SNPs, out of which 458 revealed polymorphism. The results were used to analyze genetic dissimilarity among the accessions using Darwin 5 software. The markers discriminated among all of the cowpea accessions and the dissimilarity values which ranged from 0.006 to 0.63 were used for factorial plot. Unexpected high levels of heterozygosity were observed on some of the accessions. Accessions known to be closely related clustered together in a dendrogram drawn with WPGMA method. A maximum length sub-tree which comprised of 48 core accessions was constructed. The software package structure was used to separate accessions into three groups, and the programme correctly identified varieties that were known hybrids. The hybrids were those accessions with numerous heterozygous loci. The structure plot showed closely related accessions with similar genome patterns. The SNP markers were more efficient in discriminating among the cowpea germplasm than morphological, seed protein polymorphism and simple sequence repeat studies reported earlier on the same collection.

Identification of quantitative trait loci and candidate genes for specific cellular resistance responses against Didymella pinodes in pea

KEY MESSAGE

Phenotyping of specific cellular resistance responses and improvement of previous genetic map allowed the identification of novel genomic regions controlling cellular mechanisms involved in pea resistance to ascochyta blight and provided candidate genes suitable for MAS. Didymella pinodes, causing ascochyta blight, is a major pathogen of the pea crop and is responsible for serious damage and yield losses. Resistance is inherited polygenically and several quantitative trait loci (QTLs) have been already identified. However, the position of these QTLs should be further refined to identify molecular markers more closely linked to the resistance genes. In previous works, resistance was scored visually estimating the final disease symptoms; in this study, we have conducted a more precise phenotyping of resistance evaluating specific cellular resistance responses at the histological level to perform a more accurate QTL analysis. In addition, P665 × Messire genetic map used to identify the QTLs was improved by adding 117 SNP markers located in genes. This combined approach has allowed the identification, for the first time, of genomic regions controlling cellular mechanisms directly involved in pea resistance to ascochyta blight. Furthermore, the inclusion of the gene-based SNP markers has allowed the identification of candidate genes co-located with QTLs and has provided robust markers for marker-assisted selection.

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.

Genomics-assisted breeding in four major pulse crops of developing countries: present status and prospects

KEY MESSAGE

Given recent advances in pulse molecular biology, genomics-driven breeding has emerged as a promising approach to address the issues of limited genetic gain and low productivity in various pulse crops. The global population is continuously increasing and is expected to reach nine billion by 2050. This huge population pressure will lead to severe shortage of food, natural resources and arable land. Such an alarming situation is most likely to arise in developing countries due to increase in the proportion of people suffering from protein and micronutrient malnutrition. Pulses being a primary and affordable source of proteins and minerals play a key role in alleviating the protein calorie malnutrition, micronutrient deficiencies and other undernourishment-related issues. Additionally, pulses are a vital source of livelihood generation for millions of resource-poor farmers practising agriculture in the semi-arid and sub-tropical regions. Limited success achieved through conventional breeding so far in most of the pulse crops will not be enough to feed the ever increasing population. In this context, genomics-assisted breeding (GAB) holds promise in enhancing the genetic gains. Though pulses have long been considered as orphan crops, recent advances in the area of pulse genomics are noteworthy, e.g. discovery of genome-wide genetic markers, high-throughput genotyping and sequencing platforms, high-density genetic linkage/QTL maps and, more importantly, the availability of whole-genome sequence. With genome sequence in hand, there is a great scope to apply genome-wide methods for trait mapping using association studies and to choose desirable genotypes via genomic selection. It is anticipated that GAB will speed up the progress of genetic improvement of pulses, leading to the rapid development of cultivars with higher yield, enhanced stress tolerance and wider adaptability.

Genetic diversity and demographic history of Cajanus spp. illustrated from genome-wide SNPs

Understanding genetic structure of Cajanus spp. is essential for achieving genetic improvement by quantitative trait loci (QTL) mapping or association studies and use of selected markers through genomic assisted breeding and genomic selection. After developing a comprehensive set of 1,616 single nucleotide polymorphism (SNPs) and their conversion into cost effective KASPar assays for pigeonpea (Cajanus cajan), we studied levels of genetic variability both within and between diverse set of Cajanus lines including 56 breeding lines, 21 landraces and 107 accessions from 18 wild species. These results revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, 75.8% of successful SNP assays revealed polymorphism, and more than 95% of these assays could be successfully transferred to related wild species. To show regional patterns of variation, we used STRUCTURE and Analysis of Molecular Variance (AMOVA) to partition variance among hierarchical sets of landraces and wild species at either the continental scale or within India. STRUCTURE separated most of the domesticated germplasm from wild ecotypes, and separates Australian and Asian wild species as has been found previously. Among Indian regions and states within regions, we found 36% of the variation between regions, and 64% within landraces or wilds within states. The highest level of polymorphism in wild relatives and landraces was found in Madhya Pradesh and Andhra Pradesh provinces of India representing the centre of origin and domestication of pigeonpea respectively.

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.

Grapevine powdery mildew resistance and susceptibility loci identified on a high-resolution SNP map

Improved efficacy and durability of powdery mildew resistance can be enhanced via knowledge of the genetics of resistance and susceptibility coupled with the development of high-resolution maps to facilitate the stacking of multiple resistance genes and other desirable traits. We studied the inheritance of powdery mildew (Erysiphe necator) resistance and susceptibility of wild Vitis rupestris B38 and cultivated V. vinifera 'Chardonnay', finding evidence for quantitative variation. Molecular markers were identified using genotyping-by-sequencing, resulting in 16,833 single nucleotide polymorphisms (SNPs) based on alignment to the V. vinifera 'PN40024' reference genome sequence. With an average density of 36 SNPs/Mbp and uniform coverage of the genome, this 17K set was used to identify 11 SNPs on chromosome 7 associated with a resistance locus from V. rupestris B38 and ten SNPs on chromosome 9 associated with a locus for susceptibility from 'Chardonnay' using single marker association and linkage disequilibrium analysis. Linkage maps for V. rupestris B38 (1,146 SNPs) and 'Chardonnay' (1,215 SNPs) were constructed and used to corroborate the 'Chardonnay' locus named Sen1 (Susceptibility to Erysiphe necator 1), providing the first insight into the genetics of susceptibility to powdery mildew from V. vinifera. The identification of markers associated with a susceptibility locus in a V. vinifera background can be used for negative selection among breeding progenies. This work improves our understanding of the nature of powdery mildew resistance in V. rupestris B38 and 'Chardonnay', while applying next-generation sequencing tools to advance grapevine genomics and breeding.