Next-generation sequencing identified genomic region and diagnostic markers for resistance to bacterial wilt on chromosome B02 in peanut (Arachis hypogaea L.)

Identification and application of a candidate gene AhAftr1 for aflatoxin production resistance in peanut seed (Arachis hypogaea L.)

INTRODUCTION

Peanut is susceptible to infection of Aspergillus fungi and conducive to aflatoxin contamination, hence developing aflatoxin-resistant variety is highly meaningful. Identifying functional genes or loci conferring aflatoxin resistance and molecular diagnostic marker are crucial for peanut breeding.

OBJECTIVES

This work aims to (1) identify candidate gene for aflatoxin production resistance, (2) reveal the related resistance mechanism, and (3) develop diagnostic marker for resistance breeding program.

METHODS

Resistance to aflatoxin production in a recombined inbred line (RIL) population derived from a high-yielding variety Xuhua13 crossed with an aflatoxin-resistant genotype Zhonghua 6 was evaluated under artificial inoculation for three consecutive years. Both genetic linkage analysis and QTL-seq were conducted for QTL mapping. The candidate gene was further fine-mapped using a secondary segregation mapping population and validated by transgenic experiments. RNA-Seq analysis among resistant and susceptible RILs was used to reveal the resistance pathway for the candidate genes.

RESULTS

The major effect QTL qAFTRA07.1 for aflatoxin production resistance was mapped to a 1.98 Mbp interval. A gene, AhAftr1 (Arachis hypogaea Aflatoxin resistance 1), was detected structure variation (SV) in leucine rich repeat (LRR) domain of its production, and involved in disease resistance response through the effector-triggered immunity (ETI) pathway. Transgenic plants with overexpression of AhAftr1(ZH6) exhibited 57.3% aflatoxin reduction compared to that of AhAftr1(XH13). A molecular diagnostic marker AFTR.Del.A07 was developed based on the SV. Thirty-six lines, with aflatoxin content decrease by over 77.67% compared to the susceptible control Zhonghua12 (ZH12), were identified from a panel of peanut germplasm accessions and breeding lines through using AFTR.Del.A07.

CONCLUSION

Our findings would provide insights of aflatoxin production resistance mechanisms and laid meaningful foundation for further breeding programs.

Fine mapping and identification of a Fusarium wilt resistance gene FwS1 in pea

KEY MESSAGE

A Fusarium wilt resistance gene FwS1 on pea chromosome 6 was identified and mapped to a 91.4 kb region by a comprehensive genomic-based approach, and the gene Psat6g003960 harboring NB-ARC domain was identified as the putative candidate gene. Pea Fusarium wilt, incited by Fusarium oxysporum f. sp. pisi (Fop), has always been a devastating disease that causes severe yield losses and economic damage in pea-growing regions worldwide. The utilization of pea cultivars carrying resistance gene is the most efficient approach for managing this disease. In order to finely map resistance gene, F2 populations were established through the cross between Shijiadacaiwan 1 (resistant) and Y4 (susceptible). The resistance genetic analysis indicated that the Fop resistance in Shijiadacaiwan 1 was governed by a single dominant gene, named FwS1. Based on the bulked segregant analysis sequencing analyses, the gene FwS1 was initially detected on chromosome 6 (i.e., linking group II, chr6LG2), and subsequent linkage mapping with 589 F2 individuals fine-mapped the gene FwS1 into a 91.4 kb region. The further functional annotation and haplotype analysis confirmed that the gene Psat6g003960, characterized by a NB-ARC (nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4) domain, was considered as the most promising candidate gene. The encoding amino acids were altered by a "T/C" single-nucleotide polymorphism (SNP) in the first exon of the Psat6g003960, and based on this SNP locus, the molecular marker A016180 was determined to be a diagnostic marker for FwS1 by validating its specificity in both pea accessions and genetic populations with different genetic backgrounds. The FwS1 with diagnostic KASP marker A016180 could facilitate marker-assisted selection in resistance pea breeding in pea. In addition, a comparison of the candidate gene Psat6g003960 in 74SN3B and SJ1 revealed the same sequences. This finding indicated that 74SN3B carried the candidate gene for FwS1, suggesting that FwS1 and Fwf may be closely linked or an identical resistant gene against Fusarium wilt.

Identification of candidate genes associated with peanut pod length by combined analysis of QTL-seq and RNA-seq

Pod length (PL) is one of the major traits determining pod size and yield of peanut. Discovering the quantitative trait loci (QTL) and identifying candidate genes associated with PL are essential for breeding high-yield peanut. In this study, quantitative trait loci sequencing (QTL-seq) was performed using the F2 population constructed by a short-pod variety Tifrunner (Tif) and a long-pod line Lps, and a 0.77 Mb genomic region on chromosome 07 was identified as the candidate region for PL. Then, the candidate region was narrowed to a 265.93 kb region by traditional QTL approach. RNA-seq analysis showed that there were four differentially expressed genes (DEGs) in the candidate region, among which Arahy.PF2L6F (AhCDC48) and Arahy.P4LK2T (AhTAA1) were speculated to be PL-related candidate genes. These results were informative for the elucidation of the underlying regulatory mechanism in peanut pod length and would facilitate further identification of valuable target genes.

Transcriptome sequencing and expression analysis in peanut reveal the potential mechanism response to Ralstonia solanacearum infection

BACKGROUND

Bacterial wilt caused by Ralstonia solanacearum severely affects peanut (Arachis hypogaea L.) yields. The breeding of resistant cultivars is an efficient means of controlling plant diseases. Therefore, identification of resistance genes effective against bacterial wilt is a matter of urgency. The lack of a reference genome for a resistant genotype severely hinders the process of identification of resistance genes in peanut. In addition, limited information is available on disease resistance-related pathways in peanut.

RESULTS

Full-length transcriptome data were used to generate wilt-resistant and -susceptible transcript pools. In total, 253,869 transcripts were retained to form a reference transcriptome for RNA-sequencing data analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes revealed the plant-pathogen interaction pathway to be the main resistance-related pathway for peanut to prevent bacterial invasion and calcium plays an important role in this pathway. Glutathione metabolism was enriched in wilt-susceptible genotypes, which would promote glutathione synthesis in the early stages of pathogen invasion. Based on our previous quantitative trait locus (QTL) mapping results, the genes arahy.V6I7WA and arahy.MXY2PU, which encode nucleotide-binding site-leucine-rich repeat receptor proteins, were indicated to be associated with resistance to bacterial wilt.

CONCLUSIONS

This study identified several pathways associated with resistance to bacterial wilt and identified candidate genes for bacterial wilt resistance in a major QTL region. These findings lay a foundation for investigation of the mechanism of resistance to bacterial wilt in peanut.

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.

A genomic variation map provides insights into peanut diversity in China and associations with 28 agronomic traits

Peanut (Arachis hypogaea L.) is an important allotetraploid oil and food legume crop. China is one of the world's largest peanut producers and consumers. However, genomic variations underlying the migration and divergence of peanuts in China remain unclear. Here we reported a genome-wide variation map based on the resequencing of 390 peanut accessions, suggesting that peanuts might have been introduced into southern and northern China separately, forming two cultivation centers. Selective sweep analysis highlights asymmetric selection between the two subgenomes during peanut improvement. A classical pedigree from South China offers a context for the examination of the impact of artificial selection on peanut genome. Genome-wide association studies identified 22,309 significant associations with 28 agronomic traits, including candidate genes for plant architecture and oil biosynthesis. Our findings shed light on peanut migration and diversity in China and provide valuable genomic resources for peanut improvement.

Genetic mapping identified major main-effect and three co-localized quantitative trait loci controlling high iron and zinc content in groundnut

Malnutrition is a major challenge globally, and groundnut is a highly nutritious self-pollinated legume crop blessed with ample genomic resources, including the routine deployment of genomic-assisted breeding. This study aimed to identify genomic regions and candidate genes for high iron (Fe) and zinc (Zn) content, utilizing a biparental mapping population (ICGV 00440 × ICGV 06040;). Genetic mapping and quantitative trait locus (QTL) analysis (474 mapped single-nucleotide polymorphism loci; 1536.33 cM) using 2 seasons of phenotypic data together with genotypic data identified 5 major main-effect QTLs for Fe content. These QTLs exhibited log-of-odds (LOD) scores ranging from 6.5 to 7.4, explaining phenotypic variation (PVE) ranging from 22% (qFe-Ah01) to 30.0% (qFe-Ah14). Likewise, four major main effect QTLs were identified for Zn content, with LOD score ranging from 4.4 to 6.8 and PVE ranging from 21.8% (qZn-Ah01) to 32.8% (qZn-Ah08). Interestingly, three co-localized major and main effect QTLs (qFe-Ah01, qZn-Ah03, and qFe-Ah11) were identified for both Fe and Zn contents. These genomic regions harbored key candidate genes, including zinc/iron permease transporter, bZIP transcription factor, and vacuolar iron transporter which likely play pivotal roles in the accumulation of Fe and Zn contents in seeds. The findings of this study hold potential for fine mapping and diagnostic marker development for high Fe and Zn contents in groundnut.

Whole-genome sequencing based discovery of candidate genes and diagnostic markers for seed weight in groundnut

Seed weight in groundnut (Arachis hypogaea L.) has direct impact on yield as well as market price because of preference for bold seeds by consumers and industry, thereby making seed-size improvement as one of the most important objectives of groundnut breeding programs globally. Marker-based early generation selection can accelerate the process of breeding for developing large-seeded varieties. In this context, we deployed the quantitative trait locus-sequencing (QTL-seq) approach on a biparental mapping population (Chico × ICGV 02251) to identify candidate genes and develop markers for seed weight in groundnut. A total of 289.4-389.4 million reads sequencing data were generated from three libraries (ICGV 02251 and two extreme bulks) achieving 93.9-95.1% genome coverage and 8.34-9.29× average read depth. The analysis of sequencing data using QTL-seq pipeline identified five genomic regions (three on chromosome B06 and one each on chromosomes B08 and B09) for seed weight. Detailed analysis of above associated genomic regions detected 182 single-nucleotide polymorphisms (SNPs) in genic and intergenic regions, and 11 of these SNPs were nonsynonymous in the genomic regions of 10 candidate genes including Ulp proteases and BIG SEED locus genes. Kompetitive allele specific polymerase chain reaction (KASP) markers for 14 SNPs were developed, and four of these markers (snpAH0031, snpAH0033, snpAH0037, and snpAH0038) were successfully validated for deployment in breeding for large-seeded groundnut varieties.

Fine mapping of qAHPS07 and functional studies of AhRUVBL2 controlling pod size in peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.) is an important oil and cash crop. Pod size is one of the major traits determining yield and commodity characteristic of peanut. Fine mapping of quantitative trait locus (QTL) and identification of candidate genes associated with pod size are essential for genetic improvement and molecular breeding of peanut varieties. In this study, a major QTL related to pod size, qAHPS07, was fine mapped to a 36.46 kb interval on chromosome A07 using F2 , recombinant inbred line (RIL) and secondary F2 populations. qAHPS07 explained 38.6%, 23.35%, 37.48%, 25.94% of the phenotypic variation for single pod weight (SPW), pod length (PL), pod width (PW) and pod shell thickness (PST), respectively. Whole genome resequencing and gene expression analysis revealed that a RuvB-like 2 protein coding gene AhRUVBL2 was the most likely candidate for qAHPS07. Overexpression of AhRUVBL2 in Arabidopsis led to larger seeds and plants than the wild type. AhRUVBL2-silenced peanut seedlings represented small leaves and shorter main stems. Three haplotypes were identified according to three SNPs in the promoter of AhRUVBL2 among 119 peanut accessions. Among them, SPW, PW and PST of accessions carrying Hap_ATT represent 17.6%, 11.2% and 26.3% higher than those carrying Hap_GAC，respectively. In addition, a functional marker of AhRUVBL2 was developed. Taken together, our study identified a key functional gene of peanut pod size, which provides new insights into peanut pod size regulation mechanism and offers practicable markers for the genetic improvement of pod size-related traits in peanut breeding.

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.

Fine mapping of a QTL and identification of candidate genes associated with cold tolerance during germination in peanut (Arachis hypogaea L.) on chromosome B09 using whole genome re-sequencing

Low temperatures significantly affect the growth and yield of peanuts. Temperatures lower than 12 °C are generally detrimental for the germination of peanuts. To date, there has been no report on precise information on the quantitative trait loci (QTL) for cold tolerance during the germination in peanuts. In this study, we developed a recombinant inbred line (RIL) population comprising 807 RILs by tolerant and sensitive parents. Phenotypic frequencies of germination rate low-temperature conditions among RIL population showed normally distributed in five environments. Then, we constructed a high density SNP-based genetic linkage map through whole genome re-sequencing (WGRS) technique and identified a major quantitative trait locus (QTL), qRGRB09, on chromosome B09. The cold tolerance-related QTLs were repeatedly detected in all five environments, and the genetic distance was 6.01 cM (46.74 cM - 61.75 cM) after taking a union set. To further confirm that qRGRB09 was located on chromosome B09, we developed Kompetitive Allele Specific PCR (KASP) markers for the corresponding QTL regions. A regional QTL mapping analysis, which was conducted after taking the intersection of QTL intervals of all environments into account, confirmed that qRGRB09 was between the KASP markers, G22096 and G220967 (chrB09:155637831-155854093), and this region was 216.26 kb in size, wherein a total of 15 annotated genes were detected. This study illustrates the relevance of WGRS-based genetic maps for QTL mapping and KASP genotyping that facilitated QTL fine mapping of peanuts. The results of our study also provided useful information on the genetic architecture underlying cold tolerance during germination in peanuts, which in turn may be useful for those engaged in molecular studies as well as crop improvement in the cold-stressed environment.

Identification of a stable major sucrose-related QTL and diagnostic marker for flavor improvement in peanut

An InDel marker closely linked with a major and stable quantitative trait locus (QTL) on chromosome A08, qSUCA08.2, controlling sucrose content will benefit peanut flavor improvement. Sucrose is the main soluble sugar in mature peanut kernel, and its content is a key determinant of flavor. However, the genetic basis of sucrose content in peanut remains poorly understood, which limits the progress of flavor improvement. In the present study, two genomic regions (qSUCA08a and qSUCB06a) for sucrose content on chromosomes A08 and B06 were identified by QTL-seq in a RIL population derived from a cross between Zhonghua 10 and ICG 12625. In the interval of qSUCB06a, QTL qSUCB06.2 was detected through QTL mapping in a single environment. The qSUCA08a was further dissected into 3 adjacent genomic regions using linkage analysis including a major QTL qSUCA08.2 explaining 5.43-17.84% phenotypic variation across five environments. A 61-bp insertion at position 35,099,320 in the higher sucrose parent ICG 12625 was found in qSUCA08.2. An InDel marker SUC.InDel.A08 based on the insertion/deletion polymorphism was developed and validated within a natural population containing 172 peanut cultivars in two environments. The mean sucrose content of 93 cultivars with ICG 12625 allele was significantly higher than that of 79 cultivars with Zhonghua 10 allele. The qSUCA08.2 corresponding to a 2.11 Mb interval harbored 110 genes. Among these genes, a total of 19 genes were considered as candidate genes including 5 non-synonymous mutation genes and 14 differentially expressed genes during seed development. These results provide new insights into the genetic basis of sucrose regulation in peanut and benefit the breeding program for developing new varieties with excellent flavor.

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.

Silicon Application for the Modulation of Rhizosphere Soil Bacterial Community Structures and Metabolite Profiles in Peanut under Ralstonia solanacearum Inoculation

Silicon (Si) has been shown to promote peanut growth and yield, but whether Si can enhance the resistance against peanut bacterial wilt (PBW) caused by Ralstonia solanacearum, identified as a soil-borne pathogen, is still unclear. A question regarding whether Si enhances the resistance of PBW is still unclear. Here, an in vitro R. solanacearum inoculation experiment was conducted to study the effects of Si application on the disease severity and phenotype of peanuts, as well as the microbial ecology of the rhizosphere. Results revealed that Si treatment significantly reduced the disease rate, with a decrement PBW severity of 37.50% as compared to non-Si treatment. The soil available Si (ASi) significantly increased by 13.62-44.87%, and catalase activity improved by 3.01-3.10%, which displayed obvious discrimination between non-Si and Si treatments. Furthermore, the rhizosphere soil bacterial community structures and metabolite profiles dramatically changed under Si treatment. Three significantly changed bacterial taxa were observed, which showed significant abundance under Si treatment, whereas the genus Ralstonia genus was significantly suppressed by Si. Similarly, nine differential metabolites were identified to involve into unsaturated fatty acids via a biosynthesis pathway. Significant correlations were also displayed between soil physiochemical properties and enzymes, the bacterial community, and the differential metabolites by pairwise comparisons. Overall, this study reports that Si application mediated the evolution of soil physicochemical properties, the bacterial community, and metabolite profiles in the soil rhizosphere, which significantly affects the colonization of the Ralstonia genus and provides a new theoretical basis for Si application in PBW prevention.

Transcriptome and metabolome response of eggplant against Ralstonia solanacearum infection

Bacterial wilt is a soil-borne disease that represents ubiquitous threat to Solanaceae crops. The whole-root transcriptomes and metabolomes of bacterial wilt-resistant eggplant were studied to understand the response of eggplant to bacterial wilt. A total of 2,896 differentially expressed genes and 63 differences in metabolites were identified after inoculation with Ralstonia solanacearum. Further analysis showed that the biosynthesis pathways for phytohormones, phenylpropanoids, and flavonoids were altered in eggplant after inoculation with R. solanacearum. The results of metabolomes also showed that phytohormones played a key role in eggplant response to bacterial wilt. Integrated analyses of the transcriptomic and metabolic datasets indicated that jasmonic acid (JA) content and gene involved in the JA signaling pathway increased in response to bacterial wilt. These findings remarkably improve our understanding of the mechanisms of induced defense response in eggplant and will provide insights intothe development of disease-resistant varieties of eggplant.

Whole genome resequencing identifies candidate genes and allelic diagnostic markers for resistance to Ralstonia solanacearum infection in cultivated peanut (Arachis hypogaea L.)

Bacterial wilt disease (BWD), caused by Ralstonia solanacearum is a major challenge for peanut production in China and significantly affects global peanut field productivity. It is imperative to identify genetic loci and putative genes controlling resistance to R. solanacearum (RRS). Therefore, a sequencing-based trait mapping approach termed "QTL-seq" was applied to a recombination inbred line population of 581 individuals from the cross of Yueyou 92 (resistant) and Xinhuixiaoli (susceptible). A total of 381,642 homozygous single nucleotide polymorphisms (SNPs) and 98,918 InDels were identified through whole genome resequencing of resistant and susceptible parents for RRS. Using QTL-seq analysis, a candidate genomic region comprising of 7.2 Mb (1.8-9.0 Mb) was identified on chromosome 12 which was found to be significantly associated with RRS based on combined Euclidean Distance (ED) and SNP-index methods. This candidate genomic region had 180 nonsynonymous SNPs and 14 InDels that affected 75 and 11 putative candidate genes, respectively. Finally, eight nucleotide binding site leucine rich repeat (NBS-LRR) putative resistant genes were identified as the important candidate genes with high confidence. Two diagnostic SNP markers were validated and revealed high phenotypic variation in the different resistant and susceptible RIL lines. These findings advocate the expediency of the QTL-seq approach for precise and rapid identification of candidate genomic regions, and the development of diagnostic markers that are applicable in breeding disease-resistant peanut varieties.

Genetic dissection of fatty acid components in the Chinese peanut (Arachis hypogaea L.) mini-core collection under multi-environments

Peanut (Arachis hypogaea L.) is an important source of edible oil and protein for human nutrition. The quality of peanut seed oil is mainly determined by the composition of fatty acids, especially the contents of oleic acid and linoleic acid. Improving the composition of fatty acids in the seed oil is one of the main objectives for peanut breeding globally. To uncover the genetic basis of fatty acids and broaden the genetic variation in future peanut breeding programs, this study used genome-wide association studies (GWAS) to identify loci associated with target traits and developed diagnostic marker. The contents of eight fatty acid components of the Chinese peanut mini-core collection were measured under four environments. Using the phenotypic information and over one hundred thousand single nucleotide polymorphisms (SNPs), GWAS were conducted to investigate the genetics basis of fatty acids under multi-environments. Overall, 75 SNPs were identified significant trait associations with fatty acid components. Nineteen associations were repeatedly identified in multiple environments, and 13 loci were co-associated with two or three traits. Three stable major associated loci were identified, including two loci for oleic acid and linoleic acid on chromosome A09 [mean phenotypic variation explained (PVE): 38.5%, 10.35%] and one for stearic acid on B06 (mean PVE: 23%). According to functional annotations, 21 putative candidate genes related to fatty acid biosynthesis were found underlying the three associations. The allelic effect of SNP A09-114690064 showed that the base variation was highly correlated with the phenotypic variation of oleic acid and linoleic acid contents, and a cost-effective Kompetitive allele-Specific PCR (KASP) diagnostic marker was developed. Furthermore, the SNP A09-114690064 was found to change the cis-element CAAT (-) in the promoter of ahFAD2A to YACT (+), leading dozens of times higher expression level. The enhancer-like activity of ahFAD2A promoter was identified that was valuable for enriching the regulation mechanism of ahFAD2A. This study improved our understanding on the genetic architecture of fatty acid components in peanut, and the new effective diagnostic marker would be useful for marker-assisted selection of high-oleic peanut breeding.

Comparative transcriptome analysis revealed molecular mechanisms of peanut leaves responding to Ralstonia solanacearum and its type III secretion system mutant

Bacterial wilt caused by Ralstonia solanacearum is a serious soil-borne disease that limits peanut production and quality, but the molecular mechanisms of the peanut response to R. solanacearum remain unclear. In this study, we reported the first work analyzing the transcriptomic changes of the resistant and susceptible peanut leaves infected with R. solanacearum HA4-1 and its type III secretion system mutant strains by the cutting leaf method at different timepoints (0, 24, 36, and 72 h post inoculation). A total of 125,978 differentially expressed genes (DEGs) were identified and subsequently classified into six groups to analyze, including resistance-response genes, susceptibility-response genes, PAMPs induced resistance-response genes, PAMPs induced susceptibility-response genes, T3Es induced resistance-response genes, and T3Es induced susceptibility-response genes. KEGG enrichment analyses of these DEGs showed that plant-pathogen interaction, plant hormone signal transduction, and MAPK signaling pathway were the outstanding pathways. Further analysis revealed that CMLs/CDPKs-WRKY module, MEKK1-MKK2-MPK3 cascade, and auxin signaling played important roles in the peanut response to R. solanacearum. Upon R. solanacearum infection (RSI), three early molecular events were possibly induced in peanuts, including Ca²⁺ activating CMLs/CDPKs-WRKY module to regulate the expression of resistance/susceptibility-related genes, auxin signaling was induced by AUX/IAA-ARF module to activate auxin-responsive genes that contribute to susceptibility, and MEKK1-MKK2-MPK3-WRKYs was activated by phosphorylation to induce the expression of resistance/susceptibility-related genes. Our research provides new ideas and abundant data resources to elucidate the molecular mechanism of the peanut response to R. solanacearum and to further improve the bacterial wilt resistance of peanuts.

The GmSNAP11 Contributes to Resistance to Soybean Cyst Nematode Race 4 in Glycine max

Soybean cyst nematode (SCN) has devastating effects on soybean production, making it crucial to identify genes conferring SCN resistance. Here we employed next-generation sequencing-based bulked segregant analysis (BSA) to discover genomic regions, candidate genes, and diagnostic markers for resistance to SCN race 4 (SCN4) in soybean. Phenotypic analysis revealed highly significant differences among the reactions of 145 recombinant inbred lines (RILs) to SCN4. In combination with euclidean distance (ED) and Δsingle-nucleotide polymorphism (SNP)-index analyses, we identified a genomic region on Gm11 (designated as rhg1-paralog) associated with SCN4 resistance. Overexpression and RNA interference analyzes of the two candidate genes identified in this region (GmPLAC8 and GmSNAP11) revealed that only GmSNAP11 significantly contributes to SCN4 resistance. We developed a diagnostic marker for GmSNAP11. Using this marker, together with previously developed markers for SCN-resistant loci, rhg1 and Rhg4, we evaluated the relationship between genotypes and SCN4 resistance in 145 RILs and 30 soybean accessions. The results showed that all the SCN4-resistant lines harbored all the three loci, however, some lines harboring the three loci were still susceptible to SCN4. This suggests that these three loci are necessary for the resistance to SCN4, but they alone cannot confer full resistance. The GmSNAP11 and the diagnostic markers developed could be used in genomic-assisted breeding to develop soybean varieties with increased resistance to SCN4.

Detection of a major QTL and development of KASP markers for seed weight by combining QTL-seq, QTL-mapping and RNA-seq in peanut

Combining QTL-seq, QTL-mapping and RNA-seq identified a major QTL and candidate genes, which contributed to the development of KASP markers and understanding of molecular mechanisms associated with seed weight in peanut. Seed weight, as an important component of seed yield, is a significant target of peanut breeding. However, relatively little is known about the quantitative trait loci (QTLs) and candidate genes associated with seed weight in peanut. In this study, three major QTLs on chromosomes A05, B02, and B06 were determined by applying the QTL-seq approach in a recombinant inbred line (RIL) population. Based on conventional QTL-mapping, these three QTL regions were successfully narrowed down through newly developed single nucleotide polymorphism (SNP) and simple sequence repeat markers. Among these three QTL regions, qSWB06.3 exhibited stable expression, contributing mainly to phenotypic variance across environments. Furthermore, differentially expressed genes (DEGs) were identified at the three seed developmental stages between the two parents of the RIL population. It was found that the DEGs were widely distributed in the ubiquitin-proteasome pathway, the serine/threonine-protein pathway, signal transduction of hormones and transcription factors. Notably, DEGs at the early stage were mostly involved in regulating cell division, whereas DEGs at the middle and late stages were primarily involved in cell expansion during seed development. The expression patterns of candidate genes related to seed weight in qSWB06.3 were investigated using quantitative real-time PCR. In addition, the allelic diversity of qSWB06.3 was investigated in peanut germplasm accessions. The marker Ah011475 has higher efficiency for discriminating accessions with different seed weights, and it would be useful as a diagnostic marker in marker-assisted breeding. This study provided insights into the genetic and molecular mechanisms of seed weight in peanut.

QTL identification, fine mapping, and marker development for breeding peanut (Arachis hypogaea L.) resistant to bacterial wilt

A major QTL, qBWA12, was fine mapped to a 216.68 kb physical region, and A12.4097252 was identified as a useful KASP marker for breeding peanut varieties resistant to bacterial wilt. Bacterial wilt, caused by Ralstonia solanacearum, is a major disease detrimental to peanut production in China. Breeding disease-resistant peanut varieties is the most economical and effective way to prevent the disease and yield loss. Fine mapping the QTLs for bacterial wilt resistance is critical for the marker-assisted breeding of disease-resistant varieties. A recombinant inbred population comprising 521 lines was used to construct a high-density genetic linkage map and to identify QTLs for bacterial wilt resistance following restriction-site-associated DNA sequencing. The genetic map, which included 5120 SNP markers, covered a length of 3179 cM with an average marker distance of 0.6 cM. Four QTLs for bacterial wilt resistance were mapped on four chromosomes. One major QTL, qBWA12, with LOD score of 32.8-66.0 and PVE of 31.2-44.8%, was stably detected in all four development stages investigated over the 3 trial years. Additionally, qBWA12 spanned a 2.7 cM region, corresponding to approximately 0.4 Mb and was fine mapped to a 216.7 kb region by applying KASP markers that were polymorphic between the two parents based on whole-genome resequencing data. In a large collection of breeding and germplasm lines, it was proved that KASP marker A12.4097252 can be applied for the marker-assisted breeding to develop peanut varieties resistant to bacterial wilt. Of the 19 candidate genes in the region covered by qBWA12, nine NBS-LRR genes should be further investigated regarding their potential contribution to the resistance of peanut against bacterial wilt.

Complete Genome Sequence Analysis of Ralstonia solanacearum Strain PeaFJ1 Provides Insights Into Its Strong Virulence in Peanut Plants

The bacterial wilt of peanut (Arachis hypogaea L.) caused by Ralstonia solanacearum is a devastating soil-borne disease that seriously restricted the world peanut production. However, the molecular mechanism of R. solanacearum–peanut interaction remains largely unknown. We found that R. solanacearum HA4-1 and PeaFJ1 isolated from peanut plants showed different pathogenicity by inoculating more than 110 cultivated peanuts. Phylogenetic tree analysis demonstrated that HA4-1 and PeaFJ1 both belonged to phylotype I and sequevar 14M, which indicates a high degree of genomic homology between them. Genomic sequencing and comparative genomic analysis of PeaFJ1 revealed 153 strain-specific genes compared with HA4-1. The PeaFJ1 strain-specific genes consisted of diverse virulence-related genes including LysR-type transcriptional regulators, two-component system-related genes, and genes contributing to motility and adhesion. In addition, the repertoire of the type III effectors of PeaFJ1 was bioinformatically compared with that of HA4-1 to find the candidate effectors responsible for their different virulences. There are 79 effectors in the PeaFJ1 genome, only 4 of which are different effectors compared with HA4-1, including RipS4, RipBB, RipBS, and RS_T3E_Hyp6. Based on the virulence profiles of the two strains against peanuts, we speculated that RipS4 and RipBB are candidate virulence effectors in PeaFJ1 while RipBS and RS_T3E_Hyp6 are avirulence effectors in HA4-1. In general, our research greatly reduced the scope of virulence-related genes and made it easier to find out the candidates that caused the difference in pathogenicity between the two strains. These results will help to reveal the molecular mechanism of peanut–R. solanacearum interaction and develop targeted control strategies in the future.

QTL-Seq Analysis for Identification of Resistance Loci to Bacterial Canker in Tomato

Bacterial canker caused by Clavibacter michiganensis (Cm) is one of the most economically important vascular diseases causing unilateral leaf wilting, stem canker, a bird's-eye lesion on fruit, and whole plant wilting in tomato. There is no commercially available cultivar with bacterial canker resistance, and genomics-assisted breeding can accelerate the development of cultivars with enhanced resistance. Solanum lycopersicum "Hawaii 7998" was found to show bacterial canker resistance. A Quantitative trait loci (QTL)-seq was performed to identify the resistance loci using 909 F₂ individuals derived from a cross between S. lycopersicum "E6203" (susceptible) and "Hawaii 7998," and a genomic region (37.24-41.15 Mb) associated with bacterial canker resistance on chromosome 6 (Rcm6) was found. To dissect the Rcm6 region, 12 markers were developed and several markers were associated with the resistance phenotypes. Among the markers, the Rcm6-9 genotype completely matched with the phenotype in the 47 cultivars. To further validate the Rcm6 as a resistance locus and the Rcm6-9 efficiency, subsequent analysis using F₂ and F₃ progenies was conducted. The progeny individuals with homozygous resistance allele at the Rcm6-9 showed significantly lower disease severity than those possessing homozygous susceptibility alleles. Genomes of five susceptible and two resistant cultivars were analyzed and previously known R-genes were selected to find candidate genes for Rcm6. Nucleotide-binding leucine-rich repeat, receptor-like kinase, and receptor-like protein were identified to have putative functional mutations and show differential expression upon the Cm infection. The DNA markers and candidate genes will facilitate marker-assisted breeding and provide genetic insight of bacterial canker resistance in tomato.

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Plant diseases are responsible for substantial crop losses each year and affect food security and agricultural sustainability. The improvement of crop resistance to pathogens through breeding represents an environmentally sound method for managing disease and minimizing these losses. The challenge is to breed varieties with a stable and broad-spectrum resistance. Different approaches, from markers to recent genomic and 'post-genomic era' technologies, will be reviewed in order to contribute to a better understanding of the complexity of host-pathogen interactions and genes, including those with small phenotypic effects and mechanisms that underlie resistance. An efficient combination of these approaches is herein proposed as the basis to develop a successful breeding strategy to obtain resistant crop varieties that yield higher in increasing disease scenarios.

Dissection of the Genetic Basis of Yield-Related Traits in the Chinese Peanut Mini-Core Collection Through Genome-Wide Association Studies

Peanut is an important legume crop worldwide. To uncover the genetic basis of yield features and assist breeding in the future, we conducted genome-wide association studies (GWAS) for six yield-related traits of the Chinese peanut mini-core collection. The seed (pod) size and weight of the population were investigated under four different environments, and these traits showed highly positive correlations in pairwise combinations. We sequenced the Chinese peanut mini-core collection using genotyping-by-sequencing approach and identified 105,814 high-quality single-nucleotide polymorphisms (SNPs). The population structure analysis showed essentially subspecies patterns in groups and obvious geographical distribution patterns in subgroups. A total of 79 significantly associated loci (P < 4.73 × 10^-7) were detected for the six yield-related traits through GWAS. Of these, 31 associations were consistently detected in multiple environments, and 15 loci were commonly detected to be associated with multiple traits. Two major loci located on chromosomal pseudomolecules A06 and A02 showed pleiotropic effects on yield-related traits, explaining ∼20% phenotypic variations across environments. The two genomic regions were found 46 putative candidate genes based on gene annotation and expression profile. The diagnostic marker for the yield-related traits from non-synonymous SNP (Aradu-A06-107901527) was successfully validated, achieving a high correlation between nucleotide polymorphism and phenotypic variation. This study provided insights into the genetic basis of yield-related traits in peanut and verified one diagnostic marker to facilitate marker-assisted selection for developing high-yield peanut varieties.

Complete genome sequence analysis of the peanut pathogen Ralstonia solanacearum strain Rs-P.362200

BACKGROUND

Bacterial wilt caused by Ralstonia solanacearum species complex is an important soil-borne disease worldwide that affects more than 450 plant species, including peanut, leading to great yield and quality losses. However, there are no effective measures to control bacterial wilt. The reason is the lack of research on the pathogenic mechanism of bacterial wilt.

RESULTS

Here, we report the complete genome of a toxic Ralstonia solanacearum species complex strain, Rs-P.362200, a peanut pathogen, with a total genome size of 5.86 Mb, encoding 5056 genes and the average G + C content of 67%. Among the coding genes, 75 type III effector proteins and 12 pseudogenes were predicted. Phylogenetic analysis of 41 strains including Rs-P.362200 shows that genetic distance mainly depended on geographic origins then phylotypes and host species, which associated with the complexity of the strain. The distribution and numbers of effectors and other virulence factors changed among different strains. Comparative genomic analysis showed that 29 families of 113 genes were unique to this strain compared with the other four pathogenic strains. Through the analysis of specific genes, two homologous genes (gene ID: 2_657 and 3_83), encoding virulence protein (such as RipP1) may be associated with the host range of the Rs-P.362200 strain. It was found that the bacteria contained 30 pathogenicity islands and 6 prophages containing 378 genes, 7 effectors and 363 genes, 8 effectors, respectively, which may be related to the mechanism of horizontal gene transfer and pathogenicity evaluation. Although the hosts of HA4-1 and Rs-P.362200 strains are the same, they have specific genes to their own genomes. The number of genomic islands and prophages in HA4-1 genome is more than that in Rs-P.36220, indicating a rapid change of the bacterial wilt pathogens.

CONCLUSION

The complete genome sequence analysis of peanut bacterial wilt pathogen enhanced the information of R. solanacearum genome. This research lays a theoretical foundation for future research on the interaction between Ralstonia solanacearum and 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.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Whole-genome resequencing-based QTL-seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human-made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy-to-use genetic markers enables early-generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL-seq approach for identification of key genomic regions and candidate genes. Whole-genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta-SNP index and identified a total of 10,759 genomewide high-confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes-RING-H2 finger protein and zeaxanthin epoxidase-were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL-seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut.

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.

Identification of Two Novel Peanut Genotypes Resistant to Aflatoxin Production and Their SNP Markers Associated with Resistance

Aflatoxin B₁ (AFB₁) and aflatoxin B₂ (AFB₂) are the most common aflatoxins produced by Aspergillus flavus in peanuts, with high carcinogenicity and teratogenicity. Identification of DNA markers associated with resistance to aflatoxin production is likely to offer breeders efficient tools to develop resistant cultivars through molecular breeding. In this study, seeds of 99 accessions of a Chinese peanut mini-mini core collection were investigated for their reaction to aflatoxin production by a laboratory kernel inoculation assay. Two resistant accessions (Zh.h0551 and Zh.h2150) were identified, with their aflatoxin content being 8.11%-18.90% of the susceptible control. The 99 peanut accessions were also genotyped by restriction site-associated DNA sequencing (RAD-Seq) for a genome-wide association study (GWAS). A total of 60 SNP (single nucleotide polymorphism) markers associated with aflatoxin production were detected, and they explained 16.87%-31.70% of phenotypic variation (PVE), with SNP02686 and SNP19994 possessing 31.70% and 28.91% PVE, respectively. Aflatoxin contents of accessions with "AG" (existed in Zh.h0551 and Zh.h2150) and "GG" genotypes of either SNP19994 or SNP02686 were significantly lower than that of "AA" genotypes in the mean value of a three-year assay. The resistant accessions and molecular markers identified in this study are likely to be helpful for deployment in aflatoxin resistance breeding in peanuts.

Evolutionary balance between LRR domain loss and young NBS-LRR genes production governs disease resistance in Arachis hypogaea cv. Tifrunner

BACKGROUND

Cultivated peanut (Arachis hypogaea L.) is an important oil and protein crop, but it has low disease resistance; therefore, it is important to reveal the number, sequence features, function, and evolution of genes that confer resistance. Nucleotide-binding site-leucine-rich repeats (NBS-LRRs) are resistance genes that are involved in response to various pathogens.

RESULTS

We identified 713 full-length NBS-LRRs in A. hypogaea cv. Tifrunner. Genetic exchange events occurred on NBS-LRRs in A. hypogaea cv. Tifrunner, which were detected in the same subgenomes and also found in different subgenomes. Relaxed selection acted on NBS-LRR proteins and LRR domains in A. hypogaea cv. Tifrunner. Using quantitative trait loci (QTL), we found that NBS-LRRs were involved in response to late leaf spot, tomato spotted wilt virus, and bacterial wilt in A. duranensis (2 NBS-LRRs), A. ipaensis (39 NBS-LRRs), and A. hypogaea cv. Tifrunner (113 NBS-LRRs). In A. hypogaea cv. Tifrunner, 113 NBS-LRRs were classified as 75 young and 38 old NBS-LRRs, indicating that young NBS-LRRs were involved in response to disease after tetraploidization. However, compared to A. duranensis and A. ipaensis, fewer LRR domains were found in A. hypogaea cv. Tifrunner NBS-LRR proteins, partly explaining the lower disease resistance of the cultivated peanut.

CONCLUSIONS

Although relaxed selection acted on NBS-LRR proteins and LRR domains, LRR domains were preferentially lost in A. hypogaea cv. Tifrunner compared to A. duranensis and A. ipaensis. The QTL results suggested that young NBS-LRRs were important for resistance against diseases in A. hypogaea cv. Tifrunner. Our results provid insight into the greater susceptibility of A. hypogaea cv. Tifrunner to disease compared to A. duranensis and A. ipaensis.