High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~ 0.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

Genome-wide association analysis in peanut accessions uncovers the genetic basis regulating oil and fatty acid variation

BACKGROUND

The cultivated peanut, Arachis hypogaea L., is a critical oil and food crop worldwide. Improving seed oil quality in peanut has long been an aim of breeders. However, our knowledge of the genetic basis of selecting for seed nutritional traits is limited. Based on AhFAD2A and AhFAD2B, scientists have now developed higher oleic acid (80-84%) in peanut. Decoding the genetic makeup behind natural variation in kernel oil and fatty acid concentrations is crucial for molecular breeding-based nutrient quantity and quality manipulation.

RESULTS

Herein, we recognized 87 quantitative trait loci (QTLs) in 45 genomic regions for the concentrations of oil, oleic acid, and linoleic acid, as well as the oleic acid to linoleic acid (O/L) ratio via a genome-wide association study (GWAS) involving 499 peanut accessions. Eight QTLs explained more than 15% of the phenotypic variation in peanut accessions. Among the 45 potential genes significantly related to the four traits, only three genes displayed annotation to the fatty acid pathway. Furthermore, on the basis of pleiotropism or linkage data belonging to the identified singular QTLs, we generated a trait-locus axis to better elucidate the genetic background behind the observed oil and fatty acid concentration association. Expression analysis indicated that arahy.AV6GAN and arahy.NNA8KD have higher expressions in the seeds.

CONCLUSION

This natural population consisting of 499 peanut accessions combined with high-density SNPs will provide a better choice for identifying peanut QTLs/genes in the future. Together, our results provide strong evidence for the genetic mechanism behind oil biosynthesis in peanut, facilitating future advances in multiple fatty acid component generation via pyramiding of desirable QTLs.

High-resolution genetic and physical mapping reveals a peanut spotted wilt disease resistance locus, PSWDR-1, to Tomato spotted wilt virus (TSWV), within a recombination cold-spot on chromosome A01

BACKGROUND

Peanut (Arachis hypogaea L.) is a vital global crop, frequently threatened by both abiotic and biotic stresses. Among the most damaging biotic stresses is Tomato spotted wilt virus (TSWV), which causes peanut spotted wilt disease resulting in significant yield loss. Developing TSWV-resistant cultivars is crucial to new cultivar release. Previous studies have used a subset of the "S" recombinant inbred line (RIL) population derived from SunOleic 97R and NC94022 and identified quantitative trait loci (QTLs) for resistance to TSWV. These studies utilized different genotyping techniques and found large consistent genomic regions on chromosome A01. The objective of this study was to fine map the QTL and identify candidate genes using the entire population of 352 RILs and high-density, high-quality peanut SNP arrays.

RESULTS

We used both versions of the peanut SNP arrays with five years of disease ratings, and successfully mapped the long-sought peanut spotted wilt disease resistance locus, PSWDR-1. QTL analyses identified two major QTLs, explaining 41.43% and 43.69% of the phenotypic variance within 3.6 cM and 0.28 cM intervals using the peanut Axiom_Arachis-v1 and Axiom_Arachis-v2 SNP arrays, respectively, on chromosome A01. These QTLs corresponded to 295 kb and 235 kb physical intervals. The unique overlap region of these two QTLs was 488 kb. A comparison of the genetic linkage map with the reference genome revealed a 1.3 Mb recombination "cold spot" (11.325-12.646 Mb) with only two recombination events of RIL-S1 and RIL-S17, which displayed contrasting phenotypes. Sequencing of these two recombinants confirmed the cold spot with only five SNPs detected within this region.

CONCLUSIONS

This study successfully identified a peanut spotted wilt disease resistance locus, PSWDR-1, on chromosome A01 within a recombination "cold spot". The PSWDR-1 locus contains three candidate genes, a TIR-NBS-LRR gene (Arahy.1PK53M), a glutamate receptor-like gene (Arahy.RI1BYW), and an MLO-like protein (Arahy.FX71XI). These findings provide a foundation for future functional studies to validate the roles of these candidate genes in resistance and application in breeding TSWV-resistant peanut cultivars.

Replacing rice straw with peanut vine and Broussonetia papyrifera silage in beef cattle feed reduced the use of soybean meal

The present study investigated whether replacing dietary rice straw with peanut vine (PEV) and Broussonetia papyrifera silage (BPS) reduces the use of soybean meal and explored its effects on the growth performance, blood biochemical indicators, serum metabolomics, and meat quality of fattening bulls. Forty-five Simmental crossbred bulls (initial body weight = 484.29 ± 8.49 kg) were randomly allotted into three dietary treatment groups (n = 15): (1) CON, 5% rice straw (DM basis); (2) PEV, 5% peanut vine (DM basis); and (3) BPS, 5% B. papyrifera silage (DM basis). The remaining roughage for all three treatment groups was supplemented with 25% corn silage (DM basis). The experiment lasted for 123 d, with the first 14 d serving as an adaptive period. Throughout the experiment, dietary BPS decreased the average daily dry matter intake (P < 0.001) and feed cost (P < 0.001). Serum metabolomics analysis showed that PEV affected the phenylalanine, tyrosine, and tryptophan biosynthesis pathways (P = 0.021) and lysine degradation pathway (P = 0.042), whereas BPS affected the phenylalanine, tyrosine and tryptophan biosynthesis pathways (P = 0.004), lysine degradation pathway (P = 0.012), and serotonergic synapse pathway (P < 0.001). Regarding meat quality, the redness (P = 0.025) and hue angle values (P < 0.001) of the longissimus dorsi muscle were lower in the BPS group than in the CON and PEV groups. The yellowness of the longissimus dorsi muscle was lower in the BPS group than in the PEV group (P = 0.024), and the shear force was lower in the PEV group than in the BPS group (P = 0.014). However, lysine content in beef was higher in the BPS group than in the CON group (P = 0.005). In conclusion, replacing rice straw with PEV and BPS reduced the use of soybean meal but had no adverse effects on growth performance. BPS affected the amino acid metabolism of bulls, thus decreasing feed intake and increasing the lysine content in meat. The PEV group showed better meat quality than the BPS group.

Identification of a New Major Oil Content QTL Overlapped with FAD2B in Cultivated Peanut (Arachis hypogaea L.)

High oil content in peanut seeds is a key breeding objective for peanut (Arachis hypogaea L.) quality improvement. In order to explore the genetic basis of oil content in peanuts, a recombinant inbred line (RIL) population consisting of 256 lines was phenotyped across six environments. Continuous distribution and transgressive segregation for both oil content and oleic acid content were demonstrated across all environments. Quantitative trait locus (QTL) analysis yielded 15 additive QTLs explaining 4.34 to 23.10% of phenotypic variations. A novel stable and major QTL region conditioning oil content (qOCB09.1) was mapped to chromosome B09, spanning a 1.99 Mb genomic region with 153 putative genes, including the oleic acid gene FAD2B, which may influence the oil content. Candidate genes were identified and diagnostic markers for this region were developed for further investigation. Additionally, 18 pairs of epistatic interactions involving 35 loci were identified to affect the oil content, explaining 1.25 to 1.84% of phenotypic variations. These findings provide valuable insights for further map-based cloning of favorable alleles for oil content in peanuts.

Chloroplast and whole-genome sequencing shed light on the evolutionary history and phenotypic diversification of peanuts

Cultivated peanut (Arachis hypogaea L.) is a widely grown oilseed crop worldwide; however, the events leading to its origin and diversification are not fully understood. Here by combining chloroplast and whole-genome sequence data from a large germplasm collection, we show that the two subspecies of A. hypogaea (hypogaea and fastigiata) likely arose from distinct allopolyploidization and domestication events. Peanut genetic clusters were then differentiated in relation to dissemination routes and breeding efforts. A combination of linkage mapping and genome-wide association studies allowed us to characterize genes and genomic regions related to main peanut morpho-agronomic traits, namely flowering pattern, inner tegument color, growth habit, pod/seed weight and oil content. Together, our findings shed light on the evolutionary history and phenotypic diversification of peanuts and might be of broad interest to plant breeders.

Identification of a Major QTL for Seed Protein Content in Cultivated Peanut (Arachis hypogaea L.) Using QTL-Seq

Peanut (Arachis hypogaea L.) is a great plant protein source for human diet since it has high protein content in the kernel. Therefore, seed protein content (SPC) is considered a major agronomic and quality trait in peanut breeding. However, few genetic loci underlying SPC have been identified in peanuts, and the underlying regulatory mechanisms remain unknown, limiting the effectiveness of breeding for high-SPC peanut varieties. In this study, a major QTL (qSPCB10.1) controlling peanut SPC was identified within a 2.3 Mb interval in chromosome B10 by QTL-seq using a recombinant inbred line population derived from parental lines with high and low SPCs, respectively. Sequence comparison, transcriptomic analysis, and annotation analysis of the qSPCB10.1 locus were performed. Six differentially expressed genes with sequence variations between two parents were identified as candidate genes underlying qSPCB10.1. Further locus interaction analysis revealed that qSPCB10.1 could not affect the seed oil accumulation unless qOCA08.1XH13 was present, a high seed oil content (SOC) allele for a major QTL underlying SOC. In summary, our study provides a basis for future investigation of the genetic basis of seed protein accumulation and facilitates marker-assisted selection for developing high-SPC peanut genotypes.

Identification of a major QTL underlying sugar content in peanut kernels based on the RIL mapping population

High sugar content in peanut seeds is one of the major breeding objectives for peanut flavor improvement. In order to explore the genetic control of sugar accumulation in peanut kernels, we constructed a recombinant inbred line population of 256 F2:6-7 lines derived from the Luhua11 × 06B16 cross. A high-resolution genetic map was constructed with 3692 bin markers through whole genome re-sequencing. The total map distance was 981.65 cM and the average bin marker distance was 0.27cM. A major stable QTL region (qSCB09/qSSCB09) was identified on linkage group (LG) B09 associated with both sucrose content (SC) and soluble sugar content (SSC) explaining 21.51-33.58% phenotypic variations. This major QTL region was consistently detected in three environments and mapped within a physical interval of 1.56 Mb on chromosome B09, and six candidate genes were identified. These results provide valuable information for further map-based cloning of favorable allele for sugar content in peanut.

Omics-driven advances in the understanding of regulatory landscape of peanut seed development

Peanuts (Arachis hypogaea) are an essential oilseed crop known for their unique developmental process, characterized by aerial flowering followed by subterranean fruit development. This crop is polyploid, consisting of A and B subgenomes, which complicates its genetic analysis. The advent and progression of omics technologies-encompassing genomics, transcriptomics, proteomics, epigenomics, and metabolomics-have significantly advanced our understanding of peanut biology, particularly in the context of seed development and the regulation of seed-associated traits. Following the completion of the peanut reference genome, research has utilized omics data to elucidate the quantitative trait loci (QTL) associated with seed weight, oil content, protein content, fatty acid composition, sucrose content, and seed coat color as well as the regulatory mechanisms governing seed development. This review aims to summarize the advancements in peanut seed development regulation and trait analysis based on reference genome-guided omics studies. It provides an overview of the significant progress made in understanding the molecular basis of peanut seed development, offering insights into the complex genetic and epigenetic mechanisms that influence key agronomic traits. These studies highlight the significance of omics data in profoundly elucidating the regulatory mechanisms of peanut seed development. Furthermore, they lay a foundational basis for future research on trait-related functional genes, highlighting the pivotal role of comprehensive genomic analysis in advancing our understanding of plant biology.

Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.)

BACKGROUND

This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS).

RESULTS

The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64-32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis.

CONCLUSIONS

Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.

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.

Global Transcriptome and Co-Expression Network Analyses Revealed Hub Genes Controlling Seed Size/Weight and/or Oil Content in Peanut

Cultivated peanut (Arachis hypogaea L.) is an important economic and oilseed crop worldwide, providing high-quality edible oil and high protein content. Seed size/weight and oil content are two important determinants of yield and quality in peanut breeding. To identify key regulators controlling these two traits, two peanut cultivars with contrasting phenotypes were compared to each other, one having a larger seed size and higher oil content (Zhonghua16, ZH16 for short), while the second cultivar had smaller-sized seeds and lower oil content (Zhonghua6, ZH6). Whole transcriptome analyses were performed on these two cultivars at four stages of seed development. The results showed that ~40% of the expressed genes were stage-specific in each cultivar during seed development, especially at the early stage of development. In addition, we identified a total of 5356 differentially expressed genes (DEGs) between ZH16 and ZH6 across four development stages. Weighted gene co-expression network analysis (WGCNA) based on DEGs revealed multiple hub genes with potential roles in seed size/weight and/or oil content. These hub genes were mainly involved in transcription factors (TFs), phytohormones, the ubiquitin-proteasome pathway, and fatty acid synthesis. Overall, the candidate genes and co-expression networks detected in this study could be a valuable resource for genetic breeding to improve seed yield and quality traits in 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.

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 quantitative trait loci and development of diagnostic markers for growth habit traits in peanut (Arachis hypogaea L.)

KEY MESSAGE

QTLs for growth habit are identified on Arahy.15 and Arahy.06 in peanut, and diagnostic markers are developed and validated for further use in marker-assisted breeding. Peanut is a unique legume crop because its pods develop and mature underground. The pegs derive from flowers following pollination, then reach the ground and develop into pods in the soil. Pod number per plant is influenced by peanut growth habit (GH) that has been categorized into four types, including erect, bunch, spreading and prostrate. Restricting pod development at the plant base, as would be the case for peanut plants with upright lateral branches, would decrease pod yield. On the other hand, GH characterized by spreading lateral branches on the ground would facilitate pod formation on the nodes, thereby increasing yield potential. We describe herein an investigation into the GH traits of 521 peanut recombinant inbred lines grown in three distinct environments. Quantitative trait loci (QTLs) for GH were identified on linkage group (LG) 15 between 203.1 and 204.2 cM and on LG 16 from 139.1 to 139.3 cM. Analysis of resequencing data in the identified QTL regions revealed that single nucleotide polymorphism (SNP) or insertion and/or deletion (INDEL) at Arahy15.156854742, Arahy15.156931574, Arahy15.156976352 and Arahy06.111973258 may affect the functions of their respective candidate genes, Arahy.QV02Z8, Arahy.509QUQ, Arahy.ATH5WE and Arahy.SC7TJM. These SNPs and INDELs in relation to peanut GH were further developed for KASP genotyping and tested on a panel of 77 peanut accessions with distinct GH features. This study validates four diagnostic markers that may be used to distinguish erect/bunch peanuts from spreading/prostrate peanuts, thereby facilitating marker-assisted selection for GH traits in peanut breeding.

Genetic analysis and exploration of major effect QTLs underlying oil content in peanut

KEY MESSAGE

AhyHOF1, likely encoding a WRI1 transcription factor, plays critical roles in peanut oil synthesis. Although increasing the oil content of peanut to meet growing demand has long been a primary aim of breeding programs worldwide, the mining of genetic resources to achieve this objective has obviously lagged behind that of other oil crops. In the present study, we developed an advanced recombinant inbred line population containing 192 F9:11 families derived from parents JH5 and KX01-6. We then constructed a high-resolution genetic map covering 3,706.382 cM, with an average length of 185.32 cM per linkage group, using 2840 polymorphic SNPs. Two stable QTLs, qCOA08_1 and qCOA08_2 having the highest contributions to genetic variation (16.1% and 20.7%, respectively), were simultaneously detected in multiple environments and closely mapped within physical intervals of approximately 2.9 Mb and 1.7 Mb, respectively, on chromosome A08. In addition, combined analysis of whole-genome and transcriptome resequencing data uncovered a strong candidate gene encoding a WRI1 transcription factor and differentially expressed between the two parents. This gene, designated as High Oil Favorable gene 1 in Arachis hypogaea (AhyHOF1), was hypothesized to play roles in oil accumulation. Examination of near-inbred lines of #AhyHOF1/#Ahyhof1 provided further evidence that AhyHOF1 increases oil content, mainly by affecting the contents of several fatty acids. Taken together, our results provide valuable information for cloning the favorable allele for oil content in peanut. In addition, the closely linked polymorphic SNP markers within qCOA08_1 and qCOA08_2 loci may be useful for accelerating marker-assisted selection breeding of peanut.

A Phylogenetic and Morphological Evolution Study of Ribes L. in China Using RAD-Seq

Ribes L. belongs to the Grossulariaceae family and has important edible, medicinal, ornamental, and landscaping values. Taxonomic classification within this genus is difficult due to its large variety of species, wide distribution, large morphological variations, and presence of two complex taxonomic groups with bisexual or unisexual flowers. Our study aims to clarify the phylogenetic relationships of Ribes L. taxa in China, and further, to provide a reference for a revised global classification of it. The phylogenetic analysis of 52 Ribes L. samples from 30 species was constructed based on restriction site-associated DNA sequencing and single nucleotide polymorphisms. Afterward, two important taxonomic characters were selected for ancestral state reconstruction over the molecular phylogeny. The results showed that the 52 samples could be divided into six branches, i.e., six subgenera, which caused some controversy regarding the morphological classification of Ribes L. in China. The molecular phylogeny supported the separation of subg. Coreosma from subg. Ribesia and subg. Hemibotrya from subg. Berisia and validated the rationale for recognizing subg. Grossularia as an independent subgenus, the rationality of which was further verified by the reconstruction of ancestor traits. Gene flow among Ribes L. was identified and further confirmed our results.

Gene expression and DNA methylation altering lead to the high oil content in wild allotetraploid peanut (A. monticola)

INTRODUCTION

The wild allotetraploid peanut Arachis monticola contains a higher oil content than the cultivated allotetraploid Arachis hypogaea. Besides the fact that increasing oil content is the most important peanut breeding objective, a proper understanding of its molecular mechanism controlling oil accumulation is still lacking.

METHODS

We investigated this aspect by performing comparative transcriptomics from developing seeds between three wild and five cultivated peanut varieties.

RESULTS

The analyses not only showed species-specific grouping transcriptional profiles but also detected two gene clusters with divergent expression patterns between two species enriched in lipid metabolism. Further analysis revealed that expression alteration of lipid metabolic genes with co-expressed transcription factors in wild peanut led to enhanced activity of oil biogenesis and retarded the rate of lipid degradation. In addition, bisulfite sequencing was conducted to characterize the variation of DNA methylation between wild allotetraploid (245, WH 10025) and cultivated allotetraploid (Z16, Zhh 7720) genotypes. CG and CHG context methylation was found to antagonistically correlate with gene expression during seed development. Differentially methylated region analysis and transgenic assay further illustrated that variations of DNA methylation between wild and cultivated peanuts could affect the oil content via altering the expression of peroxisomal acyl transporter protein (Araip.H6S1B).

DISCUSSION

From the results, we deduced that DNA methylation may negatively regulate lipid metabolic genes and transcription factors to subtly affect oil accumulation divergence between wild and cultivated peanuts. Our work provided the first glimpse on the regulatory mechanism of gene expression altering for oil accumulation in wild peanut and gene resources for future breeding applications.

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.

Fine-mapping and gene candidate analysis for AhRt1, a major dominant locus responsible for testa color in cultivated peanut

AhRt1 controlling red testa color in peanut was fine-mapped to an interval of 580 kb on chromosome A03, and one gene encoding bHLH transcriptional factor was identified as the putative candidate gene. Peanut with red testa has higher nutritional and economic value than the traditional pink testa varieties. Identification of genes controlling red testa color will accelerate the breeding program and facilitate uncovering the genetic mechanism. In this study, in order to identify gene underlying the red testa color in peanut, a F₂ population derived from a cross between a pink testa peanut variety "Fuhua 8" and a red testa variety "Quanhonghua 1" was constructed. The genetic analysis for the F₂ population revealed that the red testa color was controlled by one single dominant locus. This locus, named as AhRt1 (Arachis hypogaea Red Testa 1), was preliminary identified in chromosome A03 by BSA-sequencing analysis. Using a segregation mapping population, AhRt1 was fine-mapped to a 580-kb genomic region by substitution mapping strategy. Gene candidate analysis suggested that one predicted gene encoding bHLH transcriptional factor may be the possible candidate gene for AhRt1. A diagnostic marker closely linked to candidate gene has been developed for validating the fine-mapping result in different populations and peanut germplasm. Our findings will benefit the breeding program for developing new varieties with red testa color and laid foundation for map-based cloning gene responsible for red testa in peanut.

High-Density Genetic Linkage Map Construction Using Whole-Genome Resequencing for Mapping QTLs of Resistance to Aspergillus flavus Infection in Peanut

The cultivated peanut (Arachis hypogaea L.), which is rich in edible oil and protein, is widely planted around the world as an oil and cash crop. However, aflatoxin contamination seriously affects the quality safety of peanuts, hindering the development of the peanut industry and threatening the health of consumers. Breeding peanut varieties with resistance to Aspergillus flavus infection is important for the control of aflatoxin contamination, and understanding the genetic basis of resistance is vital to its genetic enhancement. In this study, we reported the quantitative trait locus (QTL) mapping of resistance to A. flavus infection of a well-known resistant variety, J11. A mapping population consisting of 200 recombinant inbred lines (RILs) was constructed by crossing a susceptible variety, Zhonghua 16, with J11. Through whole-genome resequencing, a genetic linkage map was constructed with 2,802 recombination bins and an average inter-bin distance of 0.58 cM. Combined with phenotypic data of an infection index in 4 consecutive years, six novel resistant QTLs with 5.03-10.87% phenotypic variances explained (PVE) were identified on chromosomes A05, A08, B01, B03, and B10. The favorable alleles of five QTLs were from J11, while that of one QTL was from Zhonghua 16. The combination of these favorable alleles significantly improved resistance to A. flavus infection. These results could contribute greatly to the understanding of the genetic basis of A. flavus resistance and could be meaningful in the improvement of further resistance in peanuts.

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.

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

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

Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping

Background

Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers.

Results

An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90–9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program.

Conclusion

This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties.

Translational genomics for achieving higher genetic gains in groundnut

KEY MESSAGE

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

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

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

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.