Major QTLs for Resistance to Early and Late Leaf Spot Diseases Are Identified on Chromosomes 3 and 5 in Peanut (Arachis hypogaea)

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Genetic diversity, disease resistance, and environmental adaptation of Arachis duranensis L.: New insights from landscape genomics

The genetic diversity that exists in natural populations of Arachis duranensis, the wild diploid donor of the A subgenome of cultivated tetraploid peanut, has the potential to improve crop adaptability, resilience to major pests and diseases, and drought tolerance. Despite its potential value for peanut improvement, limited research has been focused on the association between allelic variation, environmental factors, and response to early (ELS) and late leaf spot (LLS) diseases. The present study implemented a landscape genomics approach to gain a better understanding of the genetic variability of A. duranensis represented in the ex-situ peanut germplasm collection maintained at the U.S. Department of Agriculture, which spans the entire geographic range of the species in its center of origin in South America. A set of 2810 single nucleotide polymorphism (SNP) markers allowed a high-resolution genome-wide characterization of natural populations. The analysis of population structure showed a complex pattern of genetic diversity with five putative groups. The incorporation of bioclimatic variables for genotype-environment associations, using the latent factor mixed model (LFMM2) method, provided insights into the genomic signatures of environmental adaptation, and led to the identification of SNP loci whose allele frequencies were correlated with elevation, temperature, and precipitation-related variables (q < 0.05). The LFMM2 analysis for ELS and LLS detected candidate SNPs and genomic regions on chromosomes A02, A03, A04, A06, and A08. These findings highlight the importance of the application of landscape genomics in ex situ collections of peanut and other crop wild relatives to effectively identify favorable alleles and germplasm for incorporation into breeding programs. We report new sources of A. duranensis germplasm harboring adaptive allelic variation, which have the potential to be utilized in introgression breeding for a single or multiple environmental factors, as well as for resistance to leaf spot diseases.

High-density bin-based genetic map reveals a 530-kb chromosome segment derived from wild peanut contributing to late leaf spot resistance

KEY MESSAGE

Twenty-eight QTLs for LLS disease resistance were identified using an amphidiploid constructed mapping population, a favorable 530-kb chromosome segment derived from wild species contributes to the LLS resistance. Late leaf spot (LLS) is one of the major foliar diseases of peanut, causing serious yield loss and affecting the quality of kernel and forage. Some wild Arachis species possess higher resistance to LLS as compared with cultivated peanut; however, ploidy level differences restrict utilization of wild species. In this study, a synthetic amphidiploid (Ipadur) of wild peanuts with high LLS resistance was used to cross with Tifrunner to construct TI population. In total, 200 recombinant inbred lines were collected for whole-genome resequencing. A high-density bin-based genetic linkage map was constructed, which includes 4,809 bin markers with an average inter-bin distance of 0.43 cM. The recombination across cultivated and wild species was unevenly distributed, providing a novel recombination landscape for cultivated-wild Arachis species. Using phenotyping data collected across three environments, 28 QTLs for LLS disease resistance were identified, explaining 4.35-20.42% of phenotypic variation. The major QTL located on chromosome 14, qLLS14.1, could be consistently detected in 2021 Jiyang and 2022 Henan with 20.42% and 12.12% PVE, respectively. A favorable 530-kb chromosome segment derived from Ipadur was identified in the region of qLLS14.1, in which 23 disease resistance proteins were located and six of them showed significant sequence variations between Tifrunner and Ipadur. Allelic variation analysis indicating the 530-kb segment of wild species might contribute to the disease resistance of LLS. These associate genomic regions and candidate resistance genes are of great significance for peanut breeding programs for bringing durable resistance through pyramiding such multiple LLS resistance loci into peanut cultivars.

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality.

Effects of microbial agent and microbial fertilizer input on soil microbial community structure and diversity in a peanut continuous cropping system

INTRODUCTION

The soil harbors a diverse array of microorganisms, and these are essential components of terrestrial ecosystems. The presence of microorganisms in the soil, particularly in the rhizosphere, is closely linked to plant growth and soil fertility.

OBJECTIVE

The primary objective of this study is to assess the potential advantages of integrating microbial inoculants with compound fertilizer in enhancing peanut yield.

METHODS

We utilized Illumina MiSeq high-throughput sequencing technology to conduct our investigation. The experimental design consists of four treatment groups: compound fertilizers (CF), compound fertilizers supplemented with microbial agents (CF + MA), compound fertilizers supplemented with microbial fertilizers (CF + MF), and compound fertilizers supplemented with both microbial agents and microbial fertilizers (CF + MM).

RESULTS

The experimental results demonstrated a significant increase in peanut yield upon application of CF + MA, CF + MF, and CF + MM treatments. During the blossom stage and pod-setting stage, the soil's catalase, urease, and acid phosphatase activities were significantly increased in the CF + MA, and CF + MM treatments compared to the CF treatment. The application of CF + MA resulted in an increase in bacterial richness in the rhizosphere soil of peanuts, as indicated by the sequencing results. The application of CF + MA, CF + MF, and CF + MM resulted in a reduction of fungal diversity. Proteobacteria, Actinobacteria, and Acidobacteria were the dominant bacterial phyla, while Ascomycota and Basidiomycota were the dominant phyla in the fungal component of the rhizosphere soil microbiome across all experimental treatments.

CONCLUSION

Microbial agents and fertilizers modify the peanut rhizosphere soil's microbial community structure, as per our findings. The abundance of potentially beneficial bacteria (Bradyrhizobium, Rhizobium, and Burkholderia) and fungi (Trichoderma and Cladophialophora) could increase, while pathogenic fungi (Penicillium and Fusarium) decreased, thereby significantly promoting plant growth and yield of peanut.

An Overview of Mapping Quantitative Trait Loci in Peanut (Arachis hypogaea L.)

Quantitative Trait Loci (QTL) mapping has been thoroughly used in peanut genetics and breeding in spite of the narrow genetic diversity and the segmental tetraploid nature of the cultivated species. QTL mapping is helpful for identifying the genomic regions that contribute to traits, for estimating the extent of variation and the genetic action (i.e., additive, dominant, or epistatic) underlying this variation, and for pinpointing genetic correlations between traits. The aim of this paper is to review the recently published studies on QTL mapping with a particular emphasis on mapping populations used as well as traits related to kernel quality. We found that several populations have been used for QTL mapping including interspecific populations developed from crosses between synthetic tetraploids and elite varieties. Those populations allowed the broadening of the genetic base of cultivated peanut and helped with the mapping of QTL and identifying beneficial wild alleles for economically important traits. Furthermore, only a few studies reported QTL related to kernel quality. The main quality traits for which QTL have been mapped include oil and protein content as well as fatty acid compositions. QTL for other agronomic traits have also been reported. Among the 1261 QTL reported in this review, and extracted from the most relevant studies on QTL mapping in peanut, 413 (~33%) were related to kernel quality showing the importance of quality in peanut genetics and breeding. Exploiting the QTL information could accelerate breeding to develop highly nutritious superior cultivars in the face of climate change.

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.

Marker-assisted introgression of wild chromosome segments conferring resistance to fungal foliar diseases into peanut (Arachis hypogaea L.)

INTRODUCTION

Fungal foliar diseases can severely affect the productivity of the peanut crop worldwide. Late leaf spot is the most frequent disease and a major problem of the crop in Brazil and many other tropical countries. Only partial resistance to fungal diseases has been found in cultivated peanut, but high resistances have been described on the secondary gene pool.

METHODS

To overcome the known compatibility barriers for the use of wild species in peanut breeding programs, we used an induced allotetraploid (Arachis stenosperma × A. magna)^4x, as a donor parent, in a successive backcrossing scheme with the high-yielding Brazilian cultivar IAC OL 4. We used microsatellite markers associated with late leaf spot and rust resistance for foreground selection and high-throughput SNP genotyping for background selection.

RESULTS

With these tools, we developed agronomically adapted lines with high cultivated genome recovery, high-yield potential, and wild chromosome segments from both A. stenosperma and A. magna conferring high resistance to late leaf spot and rust. These segments include the four previously identified as having QTLs (quantitative trait loci) for resistance to both diseases, which could be confirmed here, and at least four additional QTLs identified by using mapping populations on four generations.

DISCUSSION

The introgression germplasm developed here will extend the useful genetic diversity of the primary gene pool by providing novel wild resistance genes against these two destructive peanut diseases.

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 association mapping for LLS resistance in a MAGIC population of groundnut (Arachis hypogaea L.)

The identified 30 functional nucleotide polymorphisms or genic SNP markers would offer essential information for marker-assisted breeding in groundnut. A genome-wide association study (GWAS) on component traits of LLS resistance in an eight-way multiparent advance generation intercross (MAGIC) population of groundnut in the field and in a light chamber (controlled conditions) was performed via an Affymetrix 48 K single-nucleotide polymorphism (SNP) 'Axiom Arachis' array. Multiparental populations with high-density genotyping enable the detection of novel alleles. In total, five quantitative trait loci (QTLs) with marker - log10(p value) scores ranging from 4.25 to 13.77 for the incubation period (IP) and six QTLs with marker - log10(p value) scores ranging from 4.33 to 10.79 for the latent period (LP) were identified across the A- and B-subgenomes. A total of 62 markers‒trait associations (MTAs) were identified across the A- and B-subgenomes. Markers for LLS scores and the area under the disease progression curve (AUDPC) recorded for plants in the light chamber and under field conditions presented - log10 (p value) scores ranging from 4.22 to 27.30. The highest number of MTAs (six) was identified on chromosomes A05, B07 and B09. Out of a total of 73 MTAs, 37 and 36 MTAs were detected in subgenomes A and B, respectively. Taken together, these results suggest that both subgenomes have equal potential genomic regions contributing to LLS resistance. A total of 30 functional nucleotide polymorphisms or genic SNP markers were detected, among which eight genes were found to encode leucine-rich repeat (LRR) receptor-like protein kinases and putative disease resistance proteins. These important SNPs can be used in breeding programmes for the development of cultivars with improved disease resistance.

Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm

Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.

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.

De novo genes in Arachis hypogaea cv. Tifrunner: systematic identification, molecular evolution, and potential contributions to cultivated peanut

De novo genes are derived from non-coding sequences, and they can play essential roles in organisms. Cultivated peanut (Arachis hypogaea) is a major oil and protein crop derived from a cross between Arachis duranensis and Arachis ipaensis. However, few de novo genes have been documented in Arachis. Here, we identified 381 de novo genes in A. hypogaea cv. Tifrunner based on comparison with five closely related Arachis species. There are distinct differences in gene expression patterns and gene structures between conserved and de novo genes. The identified de novo genes originated from ancestral sequence regions associated with metabolic and biosynthetic processes, and they were subsequently integrated into existing regulatory networks. De novo paralogs and homoeologs were identified in A. hypogaea cv. Tifrunner. De novo paralogs and homoeologs with conserved expression have mismatching cis-acting elements under normal growth conditions. De novo genes potentially have pluripotent functions in responses to biotic stresses as well as in growth and development based on quantitative trait locus data. This work provides a foundation for future research examining gene birth processes and gene function in Arachis and related taxa.

Application of CRISPR/Cas9 System for Efficient Gene Editing in Peanut

Peanuts are an economically important crop cultivated worldwide. However, several limitations restrained its productivity, including biotic/abiotic stresses. CRISPR/Cas9-based gene-editing technology holds a promising approach to developing new crops with improved agronomic and nutritional traits. Its application has been successful in many important crops. However, the application of this technology in peanut research is limited, probably due to the lack of suitable constructs and protocols. In this study, two different constructs were generated to induce insertion/deletion mutations in the targeted gene for a loss of function study. The first construct harbors the regular gRNA scaffold, while the second construct has the extended scaffold plus terminator. The designed gRNA targeting the coding sequence of the FAD2 genes was cloned into both constructs, and their functionality and efficiency were validated using the hairy root transformation system. Both constructs displayed insertions and deletions as the types of edits. The construct harboring the extended plus gRNA terminator showed a higher editing efficiency than the regular scaffold for monoallelic and biallelic mutations. These two constructs can be used for gene editing in peanuts and could provide tools for improving peanut lines for the benefit of peanut breeders, farmers, and industry.

Identification of consistent QTL for time to maturation in Virginia-type Peanut (Arachis hypogaea L.)

BACKGROUND

Time-to-maturation (TTM) is an important trait contributing to adaptability, yield and quality in peanut (Arachis hypogaea L). Virginia market-type peanut belongs to the late-maturing A. hypogaea subspecies with considerable variation in TTM within this market type. Consequently, planting and harvesting schedule of peanut cultivars, including Virginia market-type, need to be optimized to maximize yield and grade. Little is known regarding the genetic control of TTM in peanut due to the challenge of phenotyping and limited DNA polymorphism. Here, we investigated the genetic control of TTM within the Virginia market-type peanut using a SNP-based high-density genetic map. A recombinant inbred line (RIL) population, derived from a cross between two Virginia-type cultivars 'Hanoch' and 'Harari' with contrasting TTM (12-15 days on multi-years observations), was phenotyped in the field for 2 years following a randomized complete block design. TTM was estimated by maturity index (MI). Other agronomic traits like harvest index (HI), branching habit (BH) and shelling percentage (SP) were recorded as well.

RESULTS

MI was highly segregated in the population, with 13.3-70.9% and 28.4-80.2% in years 2018 and 2019. The constructed genetic map included 1833 SNP markers distributed on 24 linkage groups, covering a total map distance of 1773.5 cM corresponding to 20 chromosomes on the tetraploid peanut genome with 1.6 cM mean distance between the adjacent markers. Thirty QTL were identified for all measured traits. Among the four QTL regions for MI, two consistent QTL regions (qMIA04a,b and qMIB03a,b) were identified on chromosomes A04 (118680323-125,599,371; 6.9Mbp) and B03 (2839591-4,674,238; 1.8Mbp), with LOD values of 5.33-6.45 and 5-5.35 which explained phenotypic variation of 9.9-11.9% and 9.3-9.9%, respectively. QTL for HI were found to share the same loci as MI on chromosomes B03, B05, and B06, demonstrating the possible pleiotropic effect of HI on TTM. Significant but smaller effects on MI were detected for BH, pod yield and SP.

CONCLUSIONS

This study identified consistent QTL regions conditioning TTM for Virginia market-type peanut. The information and materials generated here can be used to further develop molecular markers to select peanut idiotypes suitable for diverse growth environments.

Association of differentially expressed R-gene candidates with leaf spot resistance in peanut (Arachis hypogaea L.)

Early leaf spot (ELS) and late leaf spot (LLS) are major fungal diseases of peanut that can severely reduce yield and quality. Development of acceptable genetic resistance has been difficult due to a strong environmental component and many major and minor QTLs. Resistance genes (R-genes) are an important component of plant immune system and have been identified in peanut. Association of specific R-genes to leaf spot resistance will provide molecular targets for marker-assisted breeding strategies. In this study, advanced breeding lines from different pedigrees were evaluated for leaf spot resistance and 76 candidate R-genes expression study was applied to susceptible and resistant lines. Thirty-six R-genes were differentially expressed and significantly correlated with resistant lines, of which a majority are receptor like kinases (RLKs) and receptor like proteins (RLPs) that sense the presence of pathogen at the cell surface and initiate protection response. The largest group was receptor-like cytoplasmic kinases (RLCKs) VII that are involved in pattern-triggered kinase signaling resulting in the production reactive oxygen species (ROS). Four R-genes were homologous to TMV resistant protein N which has shown to confer resistance against tobacco mosaic virus (TMV). When mapped to peanut genomes, 36 R-genes were represented in most chromosomes except for A09 and B09. Low levels of gene-expression in resistant lines suggest expression is tightly controlled to balance the cost of R-gene expression to plant productively. Identification and association of R-genes involved in leaf spot resistance will facilitate genetic selection of leaf spot resistant lines with good agronomic traits.

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.

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.