Genotyping-by-sequencing based genetic mapping reveals large number of epistatic interactions for stem rot resistance in groundnut

Designing future peanut: the power of genomics-assisted breeding

KEY MESSAGE

Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.

Dissection of the Genetic Basis of Resistance to Stem Rot in Cultivated Peanuts (Arachis hypogaea L.) through Genome-Wide Association Study

Peanut (Arachis hypogaea) is an important oilseed and cash crop worldwide, contributing an important source of edible oil and protein for human nutrition. However, the incidence of stem rot disease caused by Athelia rolfsii poses a major challenge to peanut cultivation, resulting in significant yield losses. In this study, a panel of 202 peanut accessions was evaluated for their resistance to stem rot by inoculating plants in the field with A. rolfsii-infested oat grains in three environments. The mean disease index value of each environment for accessions in subsp. fasitigiate and subsp. hypogaea showed no significant difference. Accessions from southern China displayed the lowest disease index value compared to those from other ecological regions. We used whole-genome resequencing to analyze the genotypes of the accessions and to identify significant SNPs associated with stem rot resistance through genome-wide association study (GWAS). A total of 121 significant SNPs associated with stem rot resistance in peanut were identified, with phenotypic variation explained (PVE) ranging from 12.23% to 15.51%. A total of 27 candidate genes within 100 kb upstream and downstream of 23 significant SNPs were annotated, which have functions related to recognition, signal transduction, and defense response. These significant SNPs and candidate genes provide valuable information for further validation and molecular breeding to improve stem rot resistance in peanut.

Overexpression of peanut (Arachis hypogaea L.) AhGRFi gene enhanced root growth inhibition under exogenous NAA treatment in Arabidopsis thaliana

The 14-3-3 protein is a kind of evolutionary ubiquitous protein family highly conserved in eukaryotes. Initially, 14-3-3 proteins were reported in mammalian nervous tissues, but in the last decade, their role in various metabolic pathways in plants established the importance of 14-3-3 proteins. In the present study, a total of 22 14-3-3 genes, also called general regulatory factors (GRF), were identified in the peanut (Arachis hypogaea) genome, out of which 12 belonged to the ε group, whereas 10 of them belonged to the non- ε-group. Tissue-specific expression of identified 14-3-3 genes were studied using transcriptome analysis. The peanut AhGRFi gene was cloned and transformed into Arabidopsis thaliana. The investigation of subcellular localization indicated that AhGRFi is localized in the cytoplasm. Overexpression of the AhGRFi gene in transgenic Arabidopsis showed that under exogenous 1-naphthaleneacetic acid (NAA) treatment, root growth inhibition in transgenic plants was enhanced. Further analysis indicated that the expression of auxin-responsive genes IAA3, IAA7, IAA17, and SAUR-AC1 was upregulated and GH3.2 and GH3.3 were downregulated in transgenic plants, but the expression of GH3.2, GH3.3, and SAUR-AC1 showed opposite trends of change under NAA treatment. These results suggest that AhGRFi may be involved in auxin signaling during seedling root development. An in-depth study of the molecular mechanism of this process remains to be further explored.

Advances in omics research on peanut response to biotic stresses

Peanut growth, development, and eventual production are constrained by biotic and abiotic stresses resulting in serious economic losses. To understand the response and tolerance mechanism of peanut to biotic and abiotic stresses, high-throughput Omics approaches have been applied in peanut research. Integrated Omics approaches are essential for elucidating the temporal and spatial changes that occur in peanut facing different stresses. The integration of functional genomics with other Omics highlights the relationships between peanut genomes and phenotypes under specific stress conditions. In this review, we focus on research on peanut biotic stresses. Here we review the primary types of biotic stresses that threaten sustainable peanut production, the multi-Omics technologies for peanut research and breeding, and the recent advances in various peanut Omics under biotic stresses, including genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics and phenomics, for identification of biotic stress-related genes, proteins, metabolites and their networks as well as the development of potential traits. We also discuss the challenges, opportunities, and future directions for peanut Omics under biotic stresses, aiming sustainable food production. The Omics knowledge is instrumental for improving peanut tolerance to cope with various biotic stresses and for meeting the food demands of the exponentially growing global population.

Genetic mapping identifies genomic regions and candidate genes for seed weight and shelling percentage in groundnut

Seed size is not only a yield-related trait but also an important measure to determine the commercial value of groundnut in the international market. For instance, small size is preferred in oil production, whereas large-sized seeds are preferred in confectioneries. In order to identify the genomic regions associated with 100-seed weight (HSW) and shelling percentage (SHP), the recombinant inbred line (RIL) population (Chico × ICGV 02251) of 352 individuals was phenotyped for three seasons and genotyped with an Axiom_Arachis array containing 58K SNPs. A genetic map with 4199 SNP loci was constructed, spanning a map distance of 2708.36 cM. QTL analysis identified six QTLs for SHP, with three consistent QTLs on chromosomes A05, A08, and B10. Similarly, for HSW, seven QTLs located on chromosomes A01, A02, A04, A10, B05, B06, and B09 were identified. BIG SEED locus and spermidine synthase candidate genes associated with seed weight were identified in the QTL region on chromosome B09. Laccase, fibre protein, lipid transfer protein, senescence-associated protein, and disease-resistant NBS-LRR proteins were identified in the QTL regions associated with shelling percentage. The associated markers for major-effect QTLs for both traits successfully distinguished between the small- and large-seeded RILs. QTLs identified for HSW and SHP can be used for developing potential selectable markers to improve the cultivars with desired seed size and shelling percentage to meet the demands of confectionery industries.

Genome-wide identification of germin-like proteins in peanut (Arachis hypogea L.) and expression analysis under different abiotic stresses

Peanut is an important food and feed crop, providing oil and protein nutrients. Germins and germin-like proteins (GLPs) are ubiquitously present in plants playing numerous roles in defense, growth and development, and different signaling pathways. However, the GLP members have not been comprehensively studied in peanut at the genome-wide scale. We carried out a genome-wide identification of the GLP genes in peanut genome. GLP members were identified comprehensively, and gene structure, genomic positions, motifs/domains distribution patterns, and phylogenetic history were studied in detail. Promoter Cis-elements, gene duplication, collinearity, miRNAs, protein-protein interactions, and expression were determined. A total of 84 GLPs (AhGLPs ) were found in the genome of cultivated peanut. These GLP genes were clustered into six groups. Segmental duplication events played a key role in the evolution of AhGLPs, and purifying selection pressure was underlying the duplication process. Most AhGLPs possessed a well-maintained gene structure and motif organization within the same group. The promoter regions of AhGLPs contained several key cis-elements responsive to 'phytohormones', 'growth and development', defense, and 'light induction'. Seven microRNAs (miRNAs) from six families were found targeting 25 AhGLPs. Gene Ontology (GO) enrichment analysis showed that AhGLPs are highly enriched in nutrient reservoir activity, aleurone grain, external encapsulating structure, multicellular organismal reproductive process, and response to acid chemicals, indicating their important biological roles. AhGLP14, AhGLP38, AhGLP54, and AhGLP76 were expressed in most tissues, while AhGLP26, AhGLP29, and AhGLP62 showed abundant expression in the pericarp. AhGLP7, AhGLP20, and AhGLP21, etc., showed specifically high expression in embryo, while AhGLP12, AhGLP18, AhGLP40, AhGLP78, and AhGLP82 were highly expressed under different hormones, water, and temperature stress. The qRT-PCR results were in accordance with the transcriptome expression data. In short, these findings provided a foundation for future functional investigations on the AhGLPs for peanut breeding programs.

A first insight into the genetics of maturity trait in Runner × Virginia types peanut background

'Runner' and 'Virginia', the two main market types of Arachis hypogaea subspecies hypogaea, differ in several agricultural and industrial characteristics. One such trait is time to maturation (TTM), contributing to the specific environmental adaptability of each subspecies. However, little is known regarding TTM's genetic and molecular control in peanut in general, and particularly in the Runner/Virginia background. Here, a recombinant inbred line population, originating from a cross between an early-maturing Virginia and a late-maturing Runner type, was used to detect quantitative trait loci (QTL) for maturity. An Arachis SNP-array was used for genotyping, and a genetic map with 1425 SNP loci spanning 24 linkage groups was constructed. Six significant QTLs were identified for the maturity index (MI) trait on chromosomes A04, A08, B02 and B04. Two sets of stable QTLs in the same loci were identified, namely qMIA04a,b and qMIA08_2a,b with 11.5%, 8.1% and 7.3%, 8.2% of phenotypic variation explained respectively in two environments. Interestingly, one consistent QTL, qMIA04a,b, overlapped with the previously reported QTL in a Virginia × Virginia population having the same early-maturing parent ('Harari') in common. The information and materials generated here can promote informed targeting of peanut idiotypes by indirect marker-assisted selection.

Whole Genome Sequencing and Morphological Trait-Based Evaluation of UPOV Option 2 for DUS Testing in Rice

To evaluate the application potential of high-density SNPs in rice distinctness, uniformity, and stability (DUS) testing, we screened 37,929 SNP loci distributed on 12 rice chromosomes based on whole-genome resequencing of 122 rice accessions. These SNP loci were used to analyze the DUS testing of rice varieties based on the correlation between the molecular and phenotypic distances of varieties according to UPOV option 2. The results showed that statistical algorithms and the number of phenotypic traits and SNP loci all affected the correlation between the molecular and phenotypic distances of rice varieties. Relative to the other nine algorithms, the Jaccard similarity algorithm had the highest correlation of 0.6587. Both the number of SNPs and the number of phenotypes had a ceiling effect on the correlation between the molecular and phenotypic distances of varieties, and the ceiling effect of the number of SNP loci was more obvious. To overcome the correlation bottleneck, we used the genome-wide prediction method to predict 30 phenotypic traits and found that the prediction accuracy of some traits, such as the basal sheath anthocyanin color, glume length, and intensity of the green color of the leaf blade, was very low. In combination with group comparison analysis, we found that the key to overcoming the ceiling effect of correlation was to improve the resolution of traits with low predictive values. In addition, we also performed distinctness testing on rice varieties by using the molecular distance and phenotypic distance, and we found that there were large differences between the two methods, indicating that UPOV option 2 alone cannot replace the traditional phenotypic DUS testing. However, genotype and phenotype analysis together can increase the efficiency of DUS testing.

High-Density Genetic Variation Map Reveals Key Candidate Loci and Genes Associated With Important Agronomic Traits in Peanut

Peanut is one of the most important cash crops with high quality oil, high protein content, and many other nutritional elements, and grown globally. Cultivated peanut (Arachis hypogaea L.) is allotetraploid with a narrow genetic base, and its genetics and molecular mechanisms controlling the agronomic traits are poorly understood. Here, we report a comprehensive genome variation map based on the genotyping of a panel of 178 peanut cultivars using Axiom_Arachis2 SNP array, including 163 representative varieties of different provinces in China, and 15 cultivars from 9 other countries. According to principal component analysis (PCA) and phylogenetic analysis, the peanut varieties were divided into 7 groups, notable genetic divergences between the different areas were shaped by environment and domestication. Using genome-wide association study (GWAS) analysis, we identified several marker-trait associations (MTAs) and candidate genes potentially involved in regulating several agronomic traits of peanut, including one MTA related with hundred seed weight, one MTA related with total number of branches, and 14 MTAs related with pod shape. This study outlines the genetic basis of these peanut cultivars and provides 13,125 polymorphic SNP markers for further distinguishing and utility of these elite cultivars. In addition, the candidate loci and genes provide valuable information for further fine mapping of QTLs and improving the quality and yield of peanut using a genomic-assisted breeding method.

Characteristics of biological control and mechanisms of Pseudomonas chlororaphis zm-1 against peanut stem rot

Background

Peanut stem rot is a serious plant disease that causes great economic losses. At present, there are no effective measures to prevent or control the occurrence of this plant disease. Biological control is one of the most promising plant disease control measures. In this study, Pseudomonas chlororaphis subsp. aurantiaca strain zm-1, a bacterial strain with potential biocontrol properties isolated by our team from the rhizosphere soil of Anemarrhena asphodeloides, was studied to control this plant disease.

Methods

We prepared extracts of Pseudomonas chloroaphis zm-1 extracellular antibacterial compounds (PECEs), determined their antifungal activities by confrontation assay, and identified their components by UPLC-MS/MS. The gene knockout strains were constructed by homologous recombination, and the biocontrol efficacy of P. chlororaphis zm-1 and its mutant strains were evaluated by pot experiments under greenhouse conditions and plot experiments, respectively.

Results

P. chlororaphis zm-1 could produce extracellular antifungal substances and inhibit the growth of Sclerotium rolfsii, the main pathogenic fungus causing peanut stem rot. The components of PECEs identified by UPLC-MS/MS showed that three kinds of phenazine compounds, i.e., 1-hydroxyphenazine, phenazine-1-carboxylic acid (PCA), and the core phenazine, were the principal components. In particular, 1-hydroxyphenazine produced by P. chlororaphis zm-1 showed antifungal activities against S. rolfsii, but 2-hydroxyphenazine did not. This is quite different with the previously reported. The extracellular compounds of two mutant strains, ΔphzH and ΔphzE, was analysed and showed that ΔphzE did not produce any phenazine compounds, and ΔphzH no longer produced 1-hydroxyphenazine but could still produce PCA and phenazine. Furthermore, the antagonistic ability of ΔphzH declined, and that of ΔphzE was almost completely abolished. According to the results of pot experiments under greenhouse conditions, the biocontrol efficacy of ΔphzH dramatically declined to 47.21% compared with that of wild-type P. chlororaphis zm-1 (75.63%). Moreover, ΔphzE almost completely lost its ability to inhibit S. rolfsii (its biocontrol efficacy was reduced to 6.19%). The results of the larger plot experiments were also consistent with these results.

Conclusions

P. chlororaphis zm-1 has the potential to prevent and control peanut stem rot disease. Phenazines produced and secreted by P. chlororaphis zm-1 play a key role in the control of peanut stem rot caused by S. rolfsii. These findings provide a new idea for the effective prevention and treatment of peanut stem rot.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02420-x.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10-52% over the seasons. A common QTL region (46.7-50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1-18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.

Construction of ddRADseq-Based High-Density Genetic Map and Identification of Quantitative Trait Loci for Trans-resveratrol Content in Peanut Seeds

Resveratrol (trans-3,4',5-trihydroxystilbene) is a natural stilbene phytoalexin which is also found to be good for human health. Cultivated peanut (Arachis hypogaea L.), a worldwide important legume crop, is one of the few sources of human's dietary intake of resveratrol. Although the variations of resveratrol contents among peanut varieties were observed, the variations across environments and its underlying genetic basis were poorly investigated. In this study, the resveratrol content in seeds of a recombination inbred line (RIL) population (Zhonghua 6 × Xuhua 13, 186 progenies) were quantified by high performance liquid chromatography (HPLC) method across four environments. Genotypes, environments and genotype × environment interactions significantly influenced the resveratrol contents in the RIL population. A total of 8,114 high-quality single nucleotide polymorphisms (SNPs) were identified based on double-digest restriction-site-associated DNA sequencing (ddRADseq) reads. These SNPs were clustered into bins using a reference-based method, which facilitated the construction of high-density genetic map (2,183 loci with a total length of 2,063.55 cM) and the discovery of several chromosome translocations. Through composite interval mapping (CIM), nine additive quantitative trait loci (QTL) for resveratrol contents were identified on chromosomes A01, A07, A08, B04, B05, B06, B07, and B10 with 5.07-8.19% phenotypic variations explained (PVE). Putative genes within their confidential intervals might play roles in diverse primary and secondary metabolic processes. These results laid a foundation for the further genetic dissection of resveratrol content as well as the breeding and production of high-resveratrol peanuts.

Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut

A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

Identification of novel QTLs for late leaf spot resistance and validation of a major rust QTL in peanut (Arachis hypogaea L.)

Co-occurrence of two devastating foliar-fungal diseases of peanut, viz., late leaf spot (LLS), and rust may cause heavy yield loss besides adversely affecting the quality of kernel and fodder. This study reports the mapping of seven novel stress-related candidate EST-SSRs in a region having major QTLs for LLS and rust diseases using an F₂ mapping population (GJG17 × GPBD4) consisting of 328 individuals. The parental polymorphism using 1311 SSRs revealed 84 SSRs (6.4%) as polymorphic and of these 70 SSRs could be mapped on 14 linkage groups (LG). QTL analysis has identified a common QTL (LLS_QTL1/Rust_QTL) for LLS and rust diseases in the map interval of 1.41 cM on A03 chromosome, explaining 47.45% and 70.52% phenotypic variations, respectively. Another major QTL for LLS (LLS_QTL1), explaining a 29.06% phenotypic variation was also found on LG_A03. A major rust QTL has been validated which was found harboring R-gene and resistance-related genes having a role in inducing hypersensitive response (HR). Further, 23 linked SSRs including seven novel EST-SSRs were also validated in 177 diverse Indian groundnut genotypes. Twelve genotypes resistant to both LLS and rust were found carrying the common (rust and LLS) QTL region, LLS QTL region, and surrounding regions. These identified and validated candidate EST-SSR markers would be of great use for the peanut breeding groups working for the improvement of foliar-fungal disease resistance.

Unraveling the mechanisms of resistance to Sclerotium rolfsii in peanut (Arachis hypogaea L.) using comparative RNA-Seq analysis of resistant and susceptible genotypes

Stem rot, a devastating fungal disease of peanut, is caused by Sclerotium rolfsii. RNA-sequencing approaches have been used to unravel the mechanisms of resistance to stem rot in peanut over the course of fungal infection in resistant (NRCG-CS85) and susceptible (TG37A) genotypes under control conditions and during the course of infection. Out of about 290 million reads, nearly 251 million (92.22%) high-quality reads were obtained and aligned to the Arachis duranensis and Arachis ipaensis genomes with the average mapping of 78.91% and 78.61%, respectively. In total, about 48.6% of genes were commonly regulated, while approximately 21.8% and 29.6% of uniquely regulated genes from A. duranensis and A. ipaensis genomes, respectively, were identified. Several annotated transcripts, such as receptor-like kinases, jasmonic acid pathway enzymes, and transcription factors (TFs), including WRKY, Zinc finger protein, and C2-H2 zinc finger, showed higher expression in resistant genotypes upon infection. These transcripts have a known role in channelizing the downstream of pathogen perception. The higher expression of WRKY transcripts might have induced the systemic acquired resistance (SAR) by the activation of the jasmonic acid defense signaling pathway. Furthermore, a set of 30 transcripts involved in the defense mechanisms were validated with quantitative real-time PCR. This study suggested PAMP-triggered immunity as a probable mechanism of resistance, while the jasmonic acid signaling pathway was identified as a possible defense mechanism in peanut. The information generated is of immense importance in developing more effective ways to combat the stem rot disease in peanut.

Nested-association mapping (NAM)-based genetic dissection uncovers candidate genes for seed and pod weights in peanut (Arachis hypogaea)

Multiparental genetic mapping populations such as nested-association mapping (NAM) have great potential for investigating quantitative traits and associated genomic regions leading to rapid discovery of candidate genes and markers. To demonstrate the utility and power of this approach, two NAM populations, NAM_Tifrunner and NAM_Florida-07, were used for dissecting genetic control of 100-pod weight (PW) and 100-seed weight (SW) in peanut. Two high-density SNP-based genetic maps were constructed with 3341 loci and 2668 loci for NAM_Tifrunner and NAM_Florida-07, respectively. The quantitative trait locus (QTL) analysis identified 12 and 8 major effect QTLs for PW and SW, respectively, in NAM_Tifrunner, and 13 and 11 major effect QTLs for PW and SW, respectively, in NAM_Florida-07. Most of the QTLs associated with PW and SW were mapped on the chromosomes A05, A06, B05 and B06. A genomewide association study (GWAS) analysis identified 19 and 28 highly significant SNP-trait associations (STAs) in NAM_Tifrunner and 11 and 17 STAs in NAM_Florida-07 for PW and SW, respectively. These significant STAs were co-localized, suggesting that PW and SW are co-regulated by several candidate genes identified on chromosomes A05, A06, B05, and B06. This study demonstrates the utility of NAM population for genetic dissection of complex traits and performing high-resolution trait mapping in peanut.

Translational genomics for achieving higher genetic gains in groundnut

KEY MESSAGE

Groundnut has entered now in post-genome era enriched with optimum genomic and genetic resources to facilitate faster trait dissection, gene discovery and accelerated genetic improvement for developing climate-smart varieties. Cultivated groundnut or peanut (Arachis hypogaea), an allopolyploid oilseed crop with a large and complex genome, is one of the most nutritious food. This crop is grown in more than 100 countries, and the low productivity has remained the biggest challenge in the semiarid tropics. Recently, the groundnut research community has witnessed fast progress and achieved several key milestones in genomics research including genome sequence assemblies of wild diploid progenitors, wild tetraploid and both the subspecies of cultivated tetraploids, resequencing of diverse germplasm lines, genome-wide transcriptome atlas and cost-effective high and low-density genotyping assays. These genomic resources have enabled high-resolution trait mapping by using germplasm diversity panels and multi-parent genetic populations leading to precise gene discovery and diagnostic marker development. Furthermore, development and deployment of diagnostic markers have facilitated screening early generation populations as well as marker-assisted backcrossing breeding leading to development and commercialization of some molecular breeding products in groundnut. Several new genomics applications/technologies such as genomic selection, speed breeding, mid-density genotyping assay and genome editing are in pipeline. The integration of these new technologies hold great promise for developing climate-smart, high yielding and more nutritious groundnut varieties in the post-genome era.

Discovery of two novel and adjacent QTLs on chromosome B02 controlling resistance against bacterial wilt in peanut variety Zhonghua 6

Two novel and adjacent genomics and candidate genes for bacterial wilt resistance were identified on chromosome B02 in peanut variety Zhonghua 6 using both traditional QTL mapping and QTL-seq methods. Peanut (Arachis hypogaea) is an important oilseed crop worldwide. Utilization of genetic resistance is the most economic and effective approach to control bacterial wilt, one of the most devastating plant diseases, in peanut production. To accelerate the genetic improvement of bacterial wilt resistance (BWR) in peanut breeding programs, quantitative trait locus (QTL) mapping has been conducted for two resistant varieties. In this context, we deployed linkage mapping as well as sequencing-based mapping approach, QTL-seq, to identify genomic regions and candidate genes for BWR in another highly resistant variety Zhonghua 6. The recombination inbred line population (268 progenies) from the cross Xuhua 13 × Zhonghua 6 was used in BWR evaluation across five environments. QTL mapping using both SSR- and SNP-based genetic maps identified a stable QTL (qBWRB02-1) on chromosome B02 with 37.79-78.86% phenotypic variation explained (PVE) across five environments. The QTL-seq facilitated further dissection of qBWRB02-1 into two adjacent genomic regions, qBWRB02-1-1 (2.81-4.24 Mb) and qBWRB02-1-2 (6.54-8.75 Mb). Mapping of newly developed Kompetitive allele-specific PCR (KASP) markers on the genetic map confirmed their stable expressions across five environments. The effects of qBWRB02-1-1 (49.43-68.86% PVE) were much higher than qBWRB02-1-2 (3.96-6.48% PVE) and other previously reported QTLs. Nineteen putative candidate genes affected by 49 non-synonymous SNPs were identified for qBWRB02-1-1, and ten of them were predicted to code for disease resistance proteins. The major and stable QTL qBWRB02-1-1 and validated KASP markers could be deployed in genomics-assisted breeding (GAB) to develop improved peanut varieties with enhanced BWR.

Mapping quantitative trait loci (QTLs) and estimating the epistasis controlling stem rot resistance in cultivated peanut (Arachis hypogaea)

A total of 33 additive stem rot QTLs were identified in peanut genome with nine of them consistently detected in multiple years or locations. And 12 pairs of epistatic QTLs were firstly reported for peanut stem rot disease. Stem rot in peanut (Arachis hypogaea) is caused by the Sclerotium rolfsii and can result in great economic loss during production. In this study, a recombinant inbred line population from the cross between NC 3033 (stem rot resistant) and Tifrunner (stem rot susceptible) that consists of 156 lines was genotyped by using 58 K peanut single nucleotide polymorphism (SNP) array and phenotyped for stem rot resistance at multiple locations and in multiple years. A linkage map consisting of 1451 SNPs and 73 simple sequence repeat (SSR) markers was constructed. A total of 33 additive quantitative trait loci (QTLs) for stem rot resistance were detected, and six of them with phenotypic variance explained of over 10% (qSR.A01-2, qSR.A01-5, qSR.A05/B05-1, qSR.A05/B05-2, qSR.A07/B07-1 and qSR.B05-1) can be consistently detected in multiple years or locations. Besides, 12 pairs of QTLs with epistatic (additive × additive) interaction were identified. An additive QTL qSR.A01-2 also with an epistatic effect interacted with a novel locus qSR.B07_1-1 to affect the percentage of asymptomatic plants in a row. A total of 193 candidate genes within 38 stem rot QTLs intervals were annotated with functions of biotic stress resistance such as chitinase, ethylene-responsive transcription factors and pathogenesis-related proteins. The identified stem rot resistance QTLs, candidate genes, along with the associated SNP markers in this study, will benefit peanut molecular breeding programs for improving stem rot resistance.

Construction of a high-density genetic map and QTL mapping of leaf traits and plant growth in an interspecific F1 population of Catalpa bungei × Catalpa duclouxii Dode

BACKGROUND

Catalpa bungei is an important tree species used for timber in China and widely cultivated for economic and ornamental purposes. A high-density linkage map of C. bungei would be an efficient tool not only for identifying key quantitative trait loci (QTLs) that affect important traits, such as plant growth and leaf traits, but also for other genetic studies.

RESULTS

Restriction site-associated DNA sequencing (RAD-seq) was used to identify molecular markers and construct a genetic map. Approximately 280.77 Gb of clean data were obtained after sequencing, and in total, 25,614,295 single nucleotide polymorphisms (SNPs) and 2,871,647 insertions-deletions (InDels) were initially identified in the genomes of 200 individuals of a C. bungei (7080) × Catalpa duclouxii (16-PJ-3) F₁ population and their parents. Finally, 9072 SNP and 521 InDel markers that satisfied the requirements for constructing a genetic map were obtained. The integrated genetic map contained 9593 pleomorphic markers in 20 linkage groups and spanned 3151.63 cM, with an average distance between adjacent markers of 0.32 cM. Twenty QTLs for seven leaf traits and 13 QTLs for plant height at five successive time points were identified using our genetic map by inclusive composite interval mapping (ICIM). Q16-60 was identified as a QTL for five leaf traits, and three significant QTLs (Q9-1, Q18-66 and Q18-73) associated with plant growth were detected at least twice. Genome annotation suggested that a cyclin gene participates in leaf trait development, while the growth of C. bungei may be influenced by CDC48C and genes associated with phytohormone synthesis.

CONCLUSIONS

This is the first genetic map constructed in C. bungei and will be a useful tool for further genetic study, molecular marker-assisted breeding and genome assembly.