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

Genomics assisted mapping of earliness in pea (Pisum sativum L.)

BACKGROUND

Garden pea (Pisum sativum L.), is a temperate crop belonging to the Leguminosae family. Early maturing pea varieties complete their growth cycle in ∼80-90 days and fits very well within the crop rotation of rice, wheat, and maize, thereby providing an extra source of income to the farmers. Identification of genes associated with the earliness is very important for developing early maturing pea varieties.

METHODS AND RESULTS

In the present study we investigated the genetics of earliness and identified the putative genomic regions associated with the earliness in F2 population derived from a cross between early-maturing (Matar Ageta-10) and late-maturing (Punjab-89) pea varieties using BSA-Seq approach. Genetic analysis revealed that earliness follows a monogenic recessive inheritance pattern. Two extreme phenotypic pools were constructed by identifying ten extreme early and ten extreme late plants from the F2 population, and QTL-seq analysis was performed to obtain major genomic region of 6.5 Mb located at 418.46 Mb to 424.97 Mb on chromosome 7 and has been designated as PsE7. Further, a total of 907 SNPs were identified within this 6.5 Mb genomic region of which seven SNPs were validated through KASP markers. Among these, one marker namely PS423028253 showed association with the earliness trait at distance of 1.7 cM.

CONCLUSION

This novel genomic region along with KASP marker (PS423028253) identified in this study could be used for marker-assisted selection in pea breeding programs and will aid in the identification of the candidate genes in future studies.

Understanding the root of the problem for tackling pea root rot disease

Pea (Pisum sativum), a crop historically significant in the field of genetics, is regaining momentum in sustainable agriculture due to its high protein content and environmental benefits. However, its cultivation faces significant challenges from root rot, a complex disease caused by multiple soil-borne pathogens prevalent across most pea growing regions. This disease leads to substantial yield losses, further complicated by the dynamic interactions among pathogens, soil conditions, weather, and agricultural practices. Recent advancements in molecular diagnostics provide promising tools for the early and precise detection of these pathogens, which is critical for implementing effective disease management strategies. In this review, we explore how the availability of latest pea genomic resources and emerging technologies, such as CRISPR and cell-specific transcriptomics, will enable a deeper understanding of the molecular basis underlying host-pathogen interactions. We emphasize the need for a comprehensive approach that integrates genetic resistance, advanced diagnostics, cultural practices and the role of the soil microbiome in root rot. By leveraging these strategies, it is possible to develop pea varieties that can withstand root rot, ensuring the crop's resilience and its continued importance in global agriculture.

Epistasis and pleiotropy-induced variation for plant breeding

Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.

Genome-Wide Association Studies on Resistance to Pea Weevil: Identification of Novel Sources of Resistance and Associated Markers

Little resistance to the pea weevil insect pest (Bruchus pisorum) is available in pea (Pisum sativum) cultivars, highlighting the need to search for sources of resistance in Pisum germplasm and to decipher the genetic basis of resistance. To address this need, we screened the response to pea weevil in a Pisum germplasm collection (324 accession, previously genotyped) under field conditions over four environments. Significant variation for weevil seed infestation (SI) was identified, with resistance being frequent in P. fulvum, followed by P. sativum ssp. elatius, P. abyssinicum, and P. sativum ssp. humile. SI tended to be higher in accessions with lighter seed color. SI was also affected by environmental factors, being favored by high humidity during flowering and hampered by warm winter temperatures and high evapotranspiration during and after flowering. Merging the phenotypic and genotypic data allowed genome-wide association studies (GWAS) yielding 73 markers significantly associated with SI. Through the GWAS models, 23 candidate genes were found associated with weevil resistance, highlighting the interest of five genes located on chromosome 6. These included gene 127136761 encoding squalene epoxidase; gene 127091639 encoding a transcription factor MYB SRM1; gene 127097033 encoding a 60S ribosomal protein L14; gene 127092211, encoding a BolA-like family protein, which, interestingly, was located within QTL BpLD.I, earlier described as conferring resistance to weevil in pea; and gene 127096593 encoding a methyltransferase. These associated genes offer valuable potential for developing pea varieties resistant to Bruchus spp. and efficient utilization of genomic resources through marker-assisted selection (MAS).

Transcriptomic analysis identifies candidate genes for Aphanomyces root rot disease resistance in pea

BACKGROUND

Aphanomyces euteiches is a soil-borne oomycete that causes root rot in pea and other legume species. Symptoms of Aphanomyces root rot (ARR) include root discoloration and wilting, leading to significant yield losses in pea production. Resistance to ARR is known to be polygenic but the roles of single genes in the pea immune response are still poorly understood. This study uses transcriptomics to elucidate the immune response of two pea genotypes varying in their levels of resistance to A. euteiches.

RESULTS

In this study, we inoculated roots of the pea (P. sativum L.) genotypes 'Linnea' (susceptible) and 'PI180693' (resistant) with two different A. euteiches strains varying in levels of virulence. The roots were harvested at 6 h post-inoculation (hpi), 20 hpi and 48 hpi, followed by differential gene expression analysis. Our results showed a time- and genotype-dependent immune response towards A. euteiches infection, involving several WRKY and MYB-like transcription factors, along with genes associated with jasmonic acid (JA) and abscisic acid (ABA) signaling. By cross-referencing with genes segregating with partial resistance to ARR, we identified 39 candidate disease resistance genes at the later stage of infection. Among the genes solely upregulated in the resistant genotype 'PI180693', Psat7g091800.1 was polymorphic between the pea genotypes and encoded a Leucine-rich repeat receptor-like kinase reminiscent of the Arabidopsis thaliana FLAGELLIN-SENSITIVE 2 receptor.

CONCLUSIONS

This study provides new insights into the gene expression dynamics controlling the immune response of resistant and susceptible pea genotypes to A. euteiches infection. We present a set of 39 candidate disease resistance genes for ARR in pea, including the putative immune receptor Psat7g091800.1, for future functional validation.

A Hydroponic-Based Bioassay to Facilitate Plasmodiophora brassicae Phenotyping

Clubroot, caused by the obligate parasite Plasmodiophora brassicae, is one of the most devastating diseases affecting the canola/oilseed rape (Brassica napus) industry worldwide. Currently, the planting of clubroot-resistant (CR) cultivars is the most effective strategy used to restrict the spread and the economic losses linked to the disease. However, virulent P. brassicae isolates have been able to infect many of the currently available CR cultivars, and the options to manage the disease are becoming limited. Another challenge has been achieving consistency in evaluating host reactions to P. brassicae infection, with most bioassays conducted in soil and/or potting medium, which requires significant space and can be labor intensive. Visual scoring of clubroot symptom development can also be influenced by user bias. Here, we have developed a hydroponic bioassay using well-characterized P. brassicae single-spore isolates representative of clubroot virulence in Canada, as well as field isolates from three Canadian provinces in combination with canola inbred homozygous lines carrying resistance genetics representative of CR cultivars available to growers in Canada. To improve the efficiency and consistency of disease assessment, symptom severity scores were compared with clubroot evaluations based on the scanned root area. According to the results, this bioassay offers a reliable, less expensive, and reproducible option to evaluate P. brassicae virulence, as well as to identify which canola resistance profile(s) may be effective against particular isolates. This bioassay will contribute to the breeding of new CR canola cultivars and the identification of virulence genes in P. brassicae that could trigger resistance and that have been very elusive to this day.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Evaluation of pea genotype PI180693 partial resistance towards aphanomyces root rot in commercial pea breeding

The cultivation of vining pea (Pisum sativum) faces a major constraint with root rot diseases, caused by a complex of soil-borne pathogens including the oomycetes Aphanomyces euteiches and Phytophtora pisi. Disease resistant commercial varieties are lacking but the landrace PI180693 is used as a source of partial resistance in ongoing pea breeding programs. In this study, the level of resistance and their interaction with A. euteiches virulence levels of six new back-crossed pea breeding lines, deriving from the cross between the susceptible commercial cultivar Linnea and PI180693, were evaluated for their resistance towards aphanomyces root rot in growth chamber and green house tests. Resistance towards mixed infections by A. euteiches and P. pisi and commercial production traits were evaluated in field trials. In growth chamber trials, pathogen virulence levels had a significant effect on plant resistance, as resistance was more consistent against A. euteiches strains exhibiting high or intermediate virulence compared with lowly virulent strains. In fact, line Z1701-1 showed to be significantly more resistant than both parents when inoculated with a lowly virulent strain. In two separate field trials in 2020, all six breeding lines performed equally well as the resistant parent PI180693 at sites only containing A. euteiches, as there were no differences in disease index. In mixed infections, PI180693 exhibited significantly lower disease index scores than Linnea. However, breeding lines displayed higher disease index scores compared with PI180693, indicating higher susceptibility towards P. pisi. Data on seedling emergence from the same field trials suggested that PI180693 was particularly sensitive towards seed decay/damping off disease caused by P. pisi. Furthermore, the breeding lines performed equally well as Linnea in traits important for green pea production, again emphasizing the commercial potential. In summary, we show that the resistance from PI180693 interacts with virulence levels of the pathogen A. euteiches and is less effective towards root rot caused by P. pisi. Our results show the potential use of combining PI180693 partial resistance against aphanomyces root rot with commercially favorable breeding traits in commercial breeding programs.

Genetic Diversity and Population Structure of a Wide Pisum spp. Core Collection

Peas (Pisum sativum) are the fourth most cultivated pulses worldwide and a critical source of protein in animal feed and human food. Developing pea core collections improves our understanding of pea evolution and may ease the exploitation of their genetic diversity in breeding programs. We carefully selected a highly diverse pea core collection of 325 accessions and established their genetic diversity and population structure. DArTSeq genotyping provided 35,790 polymorphic DArTseq markers, of which 24,279 were SilicoDArT and 11,511 SNP markers. More than 90% of these markers mapped onto the pea reference genome, with an average of 2787 SilicoDArT and 1644 SNP markers per chromosome, and an average LD50 distance of 0.48 and 1.38 Mbp, respectively. The pea core collection clustered in three or six subpopulations depending on the pea subspecies. Many admixed accessions were also detected, confirming the frequent genetic exchange between populations. Our results support the classification of Pisum genus into two species, P. fulvum and P. sativum (including subsp. sativum, arvense, elatius, humile, jomardii and abyssinicum). In addition, the study showed that wild alleles were incorporated into the cultivated pea through the intermediate P. sativum subsp. jomardii and P. sativum subsp. arvense during pea domestication, which have important implications for breeding programs. The high genetic diversity found in the collection and the high marker coverage are also expected to improve trait discovery and the efficient implementation of advanced breeding approaches.

Pea Breeding for Resistance to Rhizospheric Pathogens

Pea (Pisum sativum L.) is a grain legume widely cultivated in temperate climates. It is important in the race for food security owing to its multipurpose low-input requirement and environmental promoting traits. Pea is key in nitrogen fixation, biodiversity preservation, and nutritional functions as food and feed. Unfortunately, like most crops, pea production is constrained by several pests and diseases, of which rhizosphere disease dwellers are the most critical due to their long-term persistence in the soil and difficulty to manage. Understanding the rhizosphere environment can improve host plant root microbial association to increase yield stability and facilitate improved crop performance through breeding. Thus, the use of various germplasm and genomic resources combined with scientific collaborative efforts has contributed to improving pea resistance/cultivation against rhizospheric diseases. This improvement has been achieved through robust phenotyping, genotyping, agronomic practices, and resistance breeding. Nonetheless, resistance to rhizospheric diseases is still limited, while biological and chemical-based control strategies are unrealistic and unfavourable to the environment, respectively. Hence, there is a need to consistently scout for host plant resistance to resolve these bottlenecks. Herein, in view of these challenges, we reflect on pea breeding for resistance to diseases caused by rhizospheric pathogens, including fusarium wilt, root rots, nematode complex, and parasitic broomrape. Here, we will attempt to appraise and harmonise historical and contemporary knowledge that contributes to pea resistance breeding for soilborne disease management and discuss the way forward.

Genome-wide association study and selection for field resistance to cassava root rot disease and productive traits

Cassava root rot disease is caused by a complex of soil-borne pathogens and has high economic impacts because it directly affects the tuberous roots, which are the main commercial product. This study aimed to evaluate cassava genotypes for resistance to root rot disease in a field with a previous history of high disease incidence. It also aimed to identify possible genomic regions associated with field resistance based on genome-wide association studies. A total of 148 genotypes from Embrapa Mandioca and Fruticultura were evaluated over two years, including improved materials and curated germplasms. Analysis of phenotypic data was conducted, as well as a genomic association analysis, based on the general linear model, mixed linear model, and fixed and random model circulating probability unification. The observed high disease index (ω) was directly correlated with genotype survival, affecting plant height, shoot yield, and fresh root yield. The genotypes were grouped into five clusters, which were classified according to level of root rot resistance (i.e., extremely susceptible, susceptible, moderately susceptible, moderately resistant, and resistant). The 10 genotypes with the best performance in the field were selected as potential progenitors for the development of segregating progenies. Estimates of genomic kinship between these genotypes ranged from -0.183 to 0.671. The genotypes BGM-1171 and BGM-1190 showed the lowest degree of kinship with the other selected sources of resistance. The genotypes BGM-0209, BGM-0398, and BGM-0659 showed negative kinship values with most elite varieties, while BGM-0659 presented negative kinship with all landraces. A genome-wide association analysis detected five significant single nucleotide polymorphisms related to defense mechanisms against biotic and abiotic stresses, with putative association with fresh root yield in soil infested with root rot pathogens. These findings can be utilized to develop molecular selection for root rot resistance in cassava.

Genomics Enabled Breeding Strategies for Major Biotic Stresses in Pea (Pisum sativum L.)

Pea (Pisum sativum L.) is one of the most important and productive cool season pulse crops grown throughout the world. Biotic stresses are the crucial constraints in harnessing the potential productivity of pea and warrant dedicated research and developmental efforts to utilize omics resources and advanced breeding techniques to assist rapid and timely development of high-yielding multiple stress-tolerant-resistant varieties. Recently, the pea researcher's community has made notable achievements in conventional and molecular breeding to accelerate its genetic gain. Several quantitative trait loci (QTLs) or markers associated with genes controlling resistance for fusarium wilt, fusarium root rot, powdery mildew, ascochyta blight, rust, common root rot, broomrape, pea enation, and pea seed borne mosaic virus are available for the marker-assisted breeding. The advanced genomic tools such as the availability of comprehensive genetic maps and linked reliable DNA markers hold great promise toward the introgression of resistance genes from different sources to speed up the genetic gain in pea. This review provides a brief account of the achievements made in the recent past regarding genetic and genomic resources' development, inheritance of genes controlling various biotic stress responses and genes controlling pathogenesis in disease causing organisms, genes/QTLs mapping, and transcriptomic and proteomic advances. Moreover, the emerging new breeding approaches such as transgenics, genome editing, genomic selection, epigenetic breeding, and speed breeding hold great promise to transform pea breeding. Overall, the judicious amalgamation of conventional and modern omics-enabled breeding strategies will augment the genetic gain and could hasten the development of biotic stress-resistant cultivars to sustain pea production under changing climate. The present review encompasses at one platform the research accomplishment made so far in pea improvement with respect to major biotic stresses and the way forward to enhance pea productivity through advanced genomic tools and technologies.

Unraveling the Genetic Basis of Key Agronomic Traits of Wrinkled Vining Pea (Pisum sativum L.) for Sustainable Production

Estimating the allelic variation and exploring the genetic basis of quantitatively inherited complex traits are the two foremost breeding scenarios for sustainable crop production. The current study utilized 188 wrinkled vining pea genotypes comprising historical varieties and breeding lines to evaluate the existing genetic diversity and to detect molecular markers associated with traits relevant to vining pea production, such as wrinkled vining pea yield (YTM100), plant height (PH), earliness (ERL), adult plant resistance to downy mildew (DM), pod length (PDL), numbers of pods per plant (PDP), number of peas per pod (PPD), and percent of small wrinkled vining peas (PSP). Marker-trait associations (MTAs) were conducted using 6902 quality single nucleotide polymorphism (SNP) markers generated from the diversity arrays technology sequencing (DArTseq) and Genotyping-by-sequencing (GBS) sequencing methods. The best linear unbiased prediction (BLUP) values were estimated from the two-decades-long (1999-2020) unbalanced phenotypic data sets recorded from two private breeding programs, the Findus and the Birds eye, now owned by Nomad Foods. Analysis of variance revealed a highly significant variation between genotypes and genotype-by-environment interactions for the ten traits. The genetic diversity and population structure analyses estimated an intermediate level of genetic variation with two optimal sub-groups within the current panel. A total of 48 significant (P < 0.0001) MTAs were identified for eight different traits, including five for wrinkled vining pea yield on chr2LG1, chr4LG4, chr7LG7, and scaffolds (two), and six for adult plant resistance to downy mildew on chr1LG6, chr3LG5 (two), chr6LG2, and chr7LG7 (two). We reported several novel MTAs for different crucial traits with agronomic importance in wrinkled vining pea production for the first time, and these candidate markers could be easily validated and integrated into the active breeding programs for marker-assisted selection.

An oomycete effector targets a plant RNA helicase involved in root development and defense

Oomycete plant pathogens secrete effector proteins to promote disease. The damaging soilborne legume pathogen Aphanomyces euteiches harbors a specific repertoire of Small Secreted Protein effectors (AeSSPs), but their biological functions remain unknown. Here we characterize AeSSP1256. The function of AeSSP1256 is investigated by physiological and molecular characterization of Medicago truncatula roots expressing the effector. A potential protein target of AeSSP1256 is identified by yeast-two hybrid, co-immunoprecipitation, and fluorescent resonance energy transfer-fluorescence lifetime imaging microscopy (FRET-FLIM) assays, as well as promoter studies and mutant characterization. AeSSP1256 impairs M. truncatula root development and promotes pathogen infection. The effector is localized to the nucleoli rim, triggers nucleoli enlargement and downregulates expression of M. truncatula ribosome-related genes. AeSSP1256 interacts with a functional nucleocytoplasmic plant RNA helicase (MtRH10). AeSSP1256 relocates MtRH10 to the perinucleolar space and hinders its binding to plant RNA. MtRH10 is associated with ribosome-related genes, root development and defense. This work reveals that an oomycete effector targets a plant RNA helicase, possibly to trigger nucleolar stress and thereby promote pathogen infection.

Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.

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.

Heritable Variation in Pea for Resistance Against a Root Rot Complex and Its Characterization by Amplicon Sequencing

Soil-borne pathogens cause severe root rot of pea (Pisum sativum L.) and are a major constraint to pea cultivation worldwide. Resistance against individual pathogen species is often ineffective in the field where multiple pathogens form a pea root rot complex (PRRC) and conjointly infect pea plants. On the other hand, various beneficial plant-microbe interactions are known that offer opportunities to strengthen plant health. To account for the whole rhizosphere microbiome in the assessment of root rot resistance in pea, an infested soil-based resistance screening assay was established. The infested soil originated from a field that showed severe pea root rot in the past. Initially, amplicon sequencing was employed to characterize the fungal microbiome of diseased pea roots grown in the infested soil. The amplicon sequencing evidenced a diverse fungal community in the roots including pea pathogens Fusarium oxysporum, F. solani, Didymella sp., and Rhizoctonia solani and antagonists such as Clonostachys rosea and several mycorrhizal species. The screening system allowed for a reproducible assessment of disease parameters among 261 pea cultivars, breeding lines, and landraces grown for 21 days under controlled conditions. A sterile soil control treatment was used to calculate relative shoot and root biomass in order to compare growth performance of pea lines with highly different growth morphologies. Broad sense heritability was calculated from linear mixed model estimated variance components for all traits. Emergence on the infested soil showed high (H 2 = 0.89), root rot index (H 2 = 0.43), and relative shoot dry weight (H 2 = 0.51) medium heritability. The resistance screening allowed for a reproducible distinction between PRRC susceptible and resistant pea lines. The combined assessment of root rot index and relative shoot dry weight allowed to identify resistant (low root rot index) and tolerant pea lines (low relative shoot dry weight at moderate to high root rot index). We conclude that relative shoot dry weight is a valuable trait to select disease tolerant pea lines. Subsequently, the resistance ranking was verified in an on-farm experiment with a subset of pea lines. We found a significant correlation (r s = 0.73, p = 0.03) between the controlled conditions and the resistance ranking in a field with high PRRC infestation. The screening system allows to predict PRRC resistance for a given field site and offers a tool for selection at the seedling stage in breeding nurseries. Using the complexity of the infested field soil, the screening system provides opportunities to study plant resistance in the light of diverse plant-microbe interactions occurring in the rhizosphere.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

It takes three to tango: the importance of microbes, host plant, and soil management to elucidate manipulation strategies for the plant microbiome

The world’s population is expected to grow to almost 10 billion by 2050, placing unprecedented demands on agriculture and natural resources. The risk in food security is also aggravated by climate change and land degradation, which compromise agricultural productivity. In recent years, our understanding of the role of microbial communities on ecosystem functioning, including plant-associated microbes, has advanced considerably. Yet, translating this knowledge into practical agricultural technologies is challenged by the intrinsic complexity of agroecosystems. Here, we review current strategies for plant microbiome manipulation, classifying them into three main pillars: (i) introducing and engineering microbiomes, (ii) breeding and engineering the host plant, and (iii) selecting agricultural practices that enhance resident soil and plant-associated microbial communities. In each of these areas, we analyze current trends in research, as well as research priorities and future perspectives.

Exploiting natural variation in root system architecture via genome-wide association studies

Root growth and development has become an important research topic for breeders and researchers based on a growing need to adapt plants to changing and more demanding environmental conditions worldwide. Over the last few years, genome-wide association studies (GWASs) became an important tool to identify the link between traits in the field and their genetic background. Here we give an overview of the current literature concerning GWASs performed on root system architecture (RSA) in plants. We summarize which root traits and approaches have been used for GWAS, mentioning their respective success rate towards a successful gene discovery. Furthermore, we zoom in on the current technical hurdles in root phenotyping and GWAS, and discuss future possibilities in this field of research.

Development of core-collections for Guizhou tea genetic resources and GWAS of leaf size using SNP developed by genotyping-by-sequencing

An accurate depiction of the genetic relationship, the development of core collection, and genome-wide association analysis (GWAS) are key for the effective exploitation and utilization of genetic resources. Here, genotyping-by-sequencing (GBS) was used to characterize 415 tea accessions mostly collected from the Guizhou region in China. A total of 30,282 high-quality SNPs was used to estimate the genetic relationships, develop core collections, and perform GWAS. We suggest 198 and 148 accessions to represent the core set and mini-core set, which consist of 47% and 37% of the whole collection, respectively, and contain 93–95% of the total SNPs. Furthermore, the frequencies of all alleles and genotypes in the whole set were very well retained in the core set and mini-core set. The 415 accessions were clustered into 14 groups and the core and the mini-core collections contain accessions from each group, species, cultivation status and growth habit. By analyzing the significant SNP markers associated with multiple traits, nine SNPs were found to be significantly associated with four leaf size traits, namely MLL, MLW, MLA and MLSI (P < 1.655E−06). This study characterized the genetic distance and relationship of tea collections, suggested the core collections, and established an efficient GWAS analysis of GBS result.

Dissecting the Genetic Architecture of Aphanomyces Root Rot Resistance in Lentil by QTL Mapping and Genome-Wide Association Study

Lentil (Lens culinaris Medikus) is an important source of protein for people in developing countries. Aphanomyces root rot (ARR) has emerged as one of the most devastating diseases affecting lentil production. In this study, we applied two complementary quantitative trait loci (QTL) analysis approaches to unravel the genetic architecture underlying this complex trait. A recombinant inbred line (RIL) population and an association mapping population were genotyped using genotyping by sequencing (GBS) to discover novel single nucleotide polymorphisms (SNPs). QTL mapping identified 19 QTL associated with ARR resistance, while association mapping detected 38 QTL and highlighted accumulation of favorable haplotypes in most of the resistant accessions. Seven QTL clusters were discovered on six chromosomes, and 15 putative genes were identified within the QTL clusters. To validate QTL mapping and genome-wide association study (GWAS) results, expression analysis of five selected genes was conducted on partially resistant and susceptible accessions. Three of the genes were differentially expressed at early stages of infection, two of which may be associated with ARR resistance. Our findings provide valuable insight into the genetic control of ARR, and genetic and genomic resources developed here can be used to accelerate development of lentil cultivars with high levels of partial resistance to ARR.

Genomics of Plant Disease Resistance in Legumes

The constant interactions between plants and pathogens in the environment and the resulting outcomes are of significant importance for agriculture and agricultural scientists. Disease resistance genes in plant cultivars can break down in the field due to the evolution of pathogens under high selection pressure. Thus, the protection of crop plants against pathogens is a continuous arms race. Like any other type of crop plant, legumes are susceptible to many pathogens. The dawn of the genomic era, in which high-throughput and cost-effective genomic tools have become available, has revolutionized our understanding of the complex interactions between legumes and pathogens. Genomic tools have enabled a global view of transcriptome changes during these interactions, from which several key players in both the resistant and susceptible interactions have been identified. This review summarizes some of the large-scale genomic studies that have clarified the host transcriptional changes during interactions between legumes and their plant pathogens while highlighting some of the molecular breeding tools that are available to introgress the traits into breeding programs. These studies provide valuable insights into the molecular basis of different levels of host defenses in resistant and susceptible interactions.

Advanced Imaging for Quantitative Evaluation of Aphanomyces Root Rot Resistance in Lentil

Aphanomyces root rot (ARR) is a soil-borne disease that results in severe yield losses in lentil. The development of resistant cultivars is one of the key strategies to control this pathogen. However, the evaluation of disease severity is limited to visual scores that can be subjective. This study utilized image-based phenotyping approaches to evaluate Aphanomyces euteiches resistance in lentil genotypes in greenhouse (351 genotypes from lentil single plant/LSP derived collection and 191 genotypes from recombinant inbred lines/RIL using digital Red-Green-Blue/RGB and hyperspectral imaging) and field (173 RIL genotypes using unmanned aerial system-based multispectral imaging) conditions. Moderate to strong correlations were observed between RGB, multispectral, and hyperspectral derived features extracted from lentil shoots/roots and visual scores. In general, root features extracted from RGB imaging were found to be strongly associated with disease severity. With only three root traits, elastic net regression model was able to predict disease severity across and within multiple datasets (R 2 = 0.45-0.73 and RMSE = 0.66-1.00). The selected features could represent visual disease scores. Moreover, we developed twelve normalized difference spectral indices (NDSIs) that were significantly correlated with disease scores: two NDSIs for lentil shoot section - computed from wavelengths of 1170, 1160, 1270, and 1280 nm (0.12 ≤ |r| ≤ 0.24, P < 0.05) and ten NDSIs for lentil root sections - computed from wavelengths in the range of 630-670, 700-840, and 1320-1530 nm (0.10 ≤ |r| ≤ 0.50, P < 0.05). Root-derived NDSIs were more accurate in predicting disease scores with an R 2 of 0.54 (RMSE = 0.86), especially when the model was trained and tested on LSP accessions, compared to R 2 of 0.25 (RMSE = 1.64) when LSP and RIL genotypes were used as train and test datasets, respectively. Importantly, NDSIs - computed from wavelengths of 700, 710, 730, and 790 nm - had strong positive correlations with disease scores (0.35 ≤r ≤ 0.50, P < 0.0001), which was confirmed in field phenotyping with similar correlations using vegetation index with red edge wavelength (normalized difference red edge, 0.36 ≤ |r| ≤ 0.57, P < 0.0001). The adopted image-based phenotyping approaches can help plant breeders to objectively quantify ARR resistance and reduce the subjectivity in selecting potential genotypes.

Confirmation of Fusarium root rot resistance QTL Fsp-Ps 2.1 of pea under controlled conditions

BACKGROUND

Dry pea production has increased substantially in North America over the last few decades. With this expansion, significant yield losses have been attributed to an escalation in Fusarium root rots in pea fields. Among the most significant rot rotting pathogenic fungal species, Fusarium solani fsp. pisi (Fsp) is one of the main causal agents of root rot of pea. High levels of partial resistance to Fsp has been identified in plant genetic resources. Genetic resistance offers one of the best solutions to control this root rotting fungus. A recombinant inbred population segregating for high levels of partial resistance, previously single nucleotide polymorphism (SNP) genotyped using genotyping-by-sequencing, was phenotyped for disease reaction in replicated and repeated greenhouse trials. Composite interval mapping was deployed to identify resistance-associated quantitative trait loci (QTL).

RESULTS

Three QTL were identified using three disease reaction criteria: root disease severity, ratios of diseased vs. healthy shoot heights and dry plant weights under controlled conditions using pure cultures of Fusarium solani fsp. pisi. One QTL Fsp-Ps 2.1 explains 44.4-53.4% of the variance with a narrow confidence interval of 1.2 cM. The second and third QTL Fsp-Ps3.2 and Fsp-Ps3.3 are closely linked and explain only 3.6-4.6% of the variance. All of the alleles are contributed by the resistant parent PI 180693.

CONCLUSION

With the confirmation of Fsp-Ps 2.1 now in two RIL populations, SNPs associated with this region make a good target for marker-assisted selection in pea breeding programs to obtain high levels of partial resistance to Fusarium root rot caused by Fusarium solani fsp. pisi.

Insights to plant-microbe interactions provide opportunities to improve resistance breeding against root diseases in grain legumes

Root and foot diseases severely impede grain legume cultivation worldwide. Breeding lines with resistance against individual pathogens exist, but these resistances are often overcome by the interaction of multiple pathogens in field situations. Novel tools allow to decipher plant-microbiome interactions in unprecedented detail and provide insights into resistance mechanisms that consider both simultaneous attacks of various pathogens and the interplay with beneficial microbes. Although it has become clear that plant-associated microbes play a key role in plant health, a systematic picture of how and to what extent plants can shape their own detrimental or beneficial microbiome remains to be drawn. There is increasing evidence for the existence of genetic variation in the regulation of plant-microbe interactions that can be exploited by plant breeders. We propose to consider the entire plant holobiont in resistance breeding strategies in order to unravel hidden parts of complex defence mechanisms. This review summarizes (a) the current knowledge of resistance against soil-borne pathogens in grain legumes, (b) evidence for genetic variation for rhizosphere-related traits, (c) the role of root exudation in microbe-mediated disease resistance and elaborates (d) how these traits can be incorporated in resistance breeding programmes.