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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. [ABSTRACT FROM AUTHOR]

Background: Aflatoxin contamination caused by Aspergillus fungi has been a serious factor affecting food safety of peanut (Arachis hypogaea L.) because aflatoxins are highly harmful for human and animal health. As three mechanisms of resistance to aflatoxin in peanut including shell infection resistance, seed infection resistance and aflatoxin production resistance exist among naturally evolved germplasm stocks, it is highly crucial to pyramid these three resistances for promoting peanut industry development and protecting consumers' health. However, less research effort has been made yet to investigate the differentiation and genetic relationship among the three resistances in diversified peanut germplasm collections. Results: In this study, the Chinese peanut mini-mini core collection selected from a large basic collection was systematically evaluated for the three resistances against A. flavus for the first time. The research revealed a wide variation among the diversified peanut accessions for all the three resistances. Totally, 14 resistant accessions were identified, including three with shell infection resistance, seven with seed infection resistance and five with aflatoxin production resistance. A special accession, Zh.h1312, was identified with both seed infection and aflatoxin production resistance. Among the five botanic types of A. hypogaea, the var. vulgaris (Spanish type) belonging to subspecies fastigiata is the only one which possessed all the three resistances. There was no close correlation between shell infection resistance and other two resistances, while there was a significant positive correlation between seed infection and toxin production resistance. All the three resistances had a significant negative correlation with pod or seed size. A total of 16 SNPs/InDels associated with the three resistances were identified through genome-wide association study (GWAS). Through comparative analysis, Zh.h1312 with seed infection resistance and aflatoxin production resistance was also revealed to possess all the resistance alleles of associated loci for seed infection index and aflatoxin content. Conclusions: This study provided the first comprehensive understanding of differentiation of aflatoxin resistance in diversified peanut germplasm collection, and would further contribute to the genetic enhancement for resistance to aflatoxin contamination. [ABSTRACT FROM AUTHOR]

Resveratrol, a polyphenolic compound, is related with stress resistance or tolerance in plants and highly beneficial to human health. Peanut (Arachis hypogaea L.) is not only an important oilseed crop worldwide but also a key source of resveratrol from dietary food. In this study, a peanut recombinant inbred line (RIL) population consisting of 166 lines derived from a cross combination with a high resveratrol variety ICGV86699 and a normal resveratrol variety Zhonghua 5 as parents was assessed for resveratrol content across three environments. Broad phenotypic variation of resveratrol content ranging from 76.75 to 1617.00 µg/kg was observed among the RILs. From phenotyping resveratrol content and other traits, three elite lines (QT079, QT135, and QT141) were identified with resveratrol level as high as ICGV86699 while their seeds weights were around 1.5 times of ICGV8669. Nine additive QTLs with phenotypic variation explained (PVE) ranging from 6.66 to 11.33% were detected for resveratrol contnet, among which, qRESA05.3 with 7.88–10.91% PVE was repeatedly detected. Furthermore, an InDel marker (InDel-A05-8,713,397) based on qRESA05.3 could be detected in both the RILs and selected diverse peanut germplasm accessions possessing "aa" genotype, and the average resveratrol content of these "aa" accessions was significantly higher than that in the genotypes possessing "AA". The favorable allele was found to raise the resveratrol content by 292.15 ± 32.05 µg/kg in the diverse germplasm panel. This is the first report of stable marker for peanut resveratrol, which would be helpful for further fine-mapping the locus and developing marker-assisted selection strategy for high resveratrol peanut. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Peanut is one of major sources for vegetable oil. Improving oil content is an important goal for peanut breeding programs. Major loci with linked markers for oil content could facilitate rapid development of high-oil varieties through marker-assisted breeding. To identify major loci underlying the oil content, we conducted the QTL analysis based on the high-dense genetic map, using RIL population derived from Zhonghua10 and ICG12625. A total of 18 additive QTLs, including two major and stable QTLs (qOCB06 and qOCB10.1), were identified in three environments. Besides, 26 pairs of QTLs with epistatic (additive × additive) interaction were mapped on 17 linkage groups. qOCB06 with up to 22.59% of the phenotypic variations was located in a 0.6-Mb interval of B06. qOCB10.1 on B10 explained 9.18–12.55% of the phenotypic variations. The additive effect of two QTLs ranged from 0.70 to 1.13% oil content in different environments. Favorable alleles of the two loci were from male and female parent, respectively. Pyramiding the two favorable alleles in the RIL population could increase "2.66 ± 0.48%" oil content across multiple environments. The marker Ai06B29452 and AGGS2133-1 linked to qOCB06 and qOCB10.1, respectively, were validated to be associated with oil content in peanut germplasms with diverse phenotypes. These markers were valuable in marker-assisted selection and pyramiding breeding for improving oil content in peanut. Major and stable QTLs with linked markers in the present study provided resources to discovery candidate genes in the future and to guide marker-assisted selection for improving oil content in peanut. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Key message: 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. [ABSTRACT FROM AUTHOR]

Resveratrol, a stilbene phytoalexin in plants, is believed to benefit human health. In this study, an optimized enzyme‐assisted method was developed to extract the total content of trans‐resveratrol (free or combined with glucose) in peanut seeds, followed by detection using high‐performance liquid chromatography. The extraction process was optimized by Box–Behnken design and response surface methodology. The optimized enzyme concentration, digestion time, pH, and temperature were 3.02 g/L, 57.06 min, 5.88, and 51.05°C, respectively. Validation tests indicated that the experimental yield of trans‐resveratrol was 0.183 ± 0.007 µg/g with a relative standard deviation of 3.87% (n = 5) under the optimal condition, which was closely agreed with the predicted value (0.182 µg/g). The recoveries obtained from the spiked samples were varied from 89.4 to 103.9%. Therefore, this study will provide a useful method for quantification of total trans‐resveratrol in peanut seeds. [ABSTRACT FROM AUTHOR]

Summary: The transcriptome connects genome to the gene function and ultimate phenome in biology. So far, transcriptomic approach was not used in peanut for performing trait mapping in bi‐parental populations. In this research, we sequenced the whole transcriptome in immature seeds in a peanut recombinant inbred line (RIL) population and explored thoroughly the landscape of transcriptomic variations and its genetic basis. The comprehensive analysis identified total 49 691 genes in RIL population, of which 92 genes followed a paramutation‐like expression pattern. Expression quantitative trait locus (eQTL) analysis identified 1207 local eQTLs and 15 837 distant eQTLs contributing to the whole‐genome transcriptomic variation in peanut. There were 94 eQTL hot spot regions detected across the genome with the dominance of distant eQTL. By integrating transcriptomic profile and annotation analyses, we unveiled a putative candidate gene and developed a linked marker InDel02 underlying a major QTL responsible for purple testa colour in peanut. Our result provided a first understanding of genetic basis of whole‐genome transcriptomic variation in peanut and illustrates the potential of the transcriptome‐aid approach in dissecting important traits in non‐model plants. [ABSTRACT FROM AUTHOR]

Key message: ddRAD-seq-based high-density genetic map comprising 2595 loci identified a major and consensus QTL with a linked marker in a 0.8-Mb physical interval for oil content in peanut. Enhancing oil content is an important breeding objective in peanut. High-resolution mapping of quantitative trait loci (QTLs) with linked markers could facilitate marker-assisted selection in breeding for target traits. In the present study, a recombined inbred line population (Xuhua 13 × Zhonghua 6) was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing (ddRAD-seq). The resulting high-density genetic map contained 2595 loci, and spanned a length of 2465.62 cM, with an average distance of 0.95 cM/locus. Seven QTLs for oil content were identified on five linkage groups, including the major and stable QTL qOCA08.1 on chromosome A08 with 10.14–27.19% phenotypic variation explained. The physical interval of qOCA08.1 was further delimited to a ~ 0.8-Mb genomic region where two genes affecting oil synthesis had been annotated. The marker SNPOCA08 was developed targeting the SNP loci associated with oil content and validated in peanut cultivars with diverse oil contents. The major and stable QTL identified in the present study could be further dissected for gene discovery. Furthermore, the tightly linked marker for oil content would be useful in marker-assisted breeding in peanut. [ABSTRACT FROM AUTHOR]

Summary: Bacterial wilt, caused by Ralstonia solanacearum, is a devastating disease affecting over 350 plant species. A few peanut cultivars were found to possess stable and durable bacterial wilt resistance (BWR). Genomics‐assisted breeding can accelerate the process of developing resistant cultivars by using diagnostic markers. Here, we deployed sequencing‐based trait mapping approach, QTL‐seq, to discover genomic regions, candidate genes and diagnostic markers for BWR in a recombination inbred line population (195 progenies) of peanut. The QTL‐seq analysis identified one candidate genomic region on chromosome B02 significantly associated with BWR. Mapping of newly developed single nucleotide polymorphism (SNP) markers narrowed down the region to 2.07 Mb and confirmed its major effects and stable expressions across three environments. This candidate genomic region had 49 nonsynonymous SNPs affecting 19 putative candidate genes including seven putative resistance genes (R‐genes). Two diagnostic markers were successfully validated in diverse breeding lines and cultivars and could be deployed in genomics‐assisted breeding of varieties with enhanced BWR. [ABSTRACT FROM AUTHOR]

Summary: Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non‐synonymous effects or in UTRs were identified in these regions for SP. Cost‐effective KASP (Kompetitive Allele‐Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties. [ABSTRACT FROM AUTHOR]

The genetic architecture determinants of yield traits in peanut ( Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut. [ABSTRACT FROM AUTHOR]

Key message: SSR-based QTL mapping provides useful information for map-based cloning of major QTLs and can be used to improve the agronomic and quality traits in cultivated peanut by marker-assisted selection. Abstract: Cultivated peanut ( Arachis hypogaea L.) is an allotetraploid species (AABB, 2 n = 4× = 40), valued for its edible oil and digestible protein. Linkage mapping has been successfully conducted for most crops, and it has been applied to detect the quantitative trait loci (QTLs) of biotic and abiotic traits in peanut. However, the genetic basis of agronomic and quality-related traits remains unclear. In this study, high levels of phenotypic variation, broad-sense heritability and significant correlations were observed for agronomic and quality-related traits in an F population. A genetic linkage map was constructed for cultivated peanut containing 470 simple sequence repeat (SSR) loci, with a total length of 1877.3 cM and average distance of 4.0 cM between flanking markers. For 10 agronomic traits, 24 QTLs were identified and each QTL explained 1.69-18.70 % of the phenotypic variance. For 8 quality-related traits, 12 QTLs were identified that explained 1.72-20.20 % of the phenotypic variance. Several QTLs for multiple traits were overlapped, reflecting the phenotypic correlation between these traits. The majority of QTLs exhibited obvious dominance or over-dominance effects on agronomic and quality traits, highlighting the importance of heterosis for breeding. A comparative analysis revealed genomic duplication and arrangement of peanut genome, which aids the assembly of scaffolds in genomic sequencing of Arachis hypogaea. Our QTL analysis results enabled us to clearly understand the genetic base of agronomic and quality traits in cultivated peanut, further accelerating the progress of map-based cloning of major QTLs and marker-assisted selection in future breeding. [ABSTRACT FROM AUTHOR]

Sucrose content is a crucial indicator of quality and flavor in peanut seed, and there is a lack of clarity on the molecular basis of sucrose metabolism in peanut seed. In this context, we performed a comprehensive comparative transcriptome study on the samples collected at seven seed development stages between a high-sucrose content variety (ICG 12625) and a low-sucrose content variety (Zhonghua 10). The transcriptome analysis identified a total of 8334 genes exhibiting significantly different abundances between the high- and low-sucrose varieties. We identified 28 differentially expressed genes (DEGs) involved in sucrose metabolism in peanut and 12 of these encoded sugars will eventually be exported transporters (SWEETs). The remaining 16 genes encoded enzymes, such as cell wall invertase (CWIN), vacuolar invertase (VIN), cytoplasmic invertase (CIN), cytosolic fructose-bisphosphate aldolase (FBA), cytosolic fructose-1,6-bisphosphate phosphatase (FBP), sucrose synthase (SUS), cytosolic phosphoglucose isomerase (PGI), hexokinase (HK), and sucrose-phosphate phosphatase (SPP). The weighted gene co-expression network analysis (WGCNA) identified seven genes encoding key enzymes (CIN, FBA, FBP, HK, and SPP), three SWEET genes, and 90 transcription factors (TFs) showing a high correlation with sucrose content. Furthermore, upon validation, six of these genes were successfully verified as exhibiting higher expression in high-sucrose recombinant inbred lines (RILs). Our study suggested the key roles of the high expression of SWEETs and enzymes in sucrose synthesis making the genotype ICG 12625 sucrose-rich. This study also provided insights into the molecular basis of sucrose metabolism during seed development and facilitated exploring key candidate genes and molecular breeding for sucrose content in peanuts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Aflatoxin contamination caused by Aspergillus flavus is a major constraint to peanut industry worldwide due to its toxicological effects to human and animals. Developing peanut varieties with resistance to seed infection and/or aflatoxin accumulation is the most effective and economic strategy for reducing aflatoxin risk in food chain. Breeding for resistance to aflatoxin in peanut is a challenging task for breeders because the genetic basis is still poorly understood. To identify the quantitative trait loci (QTLs) for resistance to aflatoxin contamination in peanut, a recombinant inbred line (RIL) population was developed from crossing Zhonghua 10 (susceptible) with ICG 12625 (resistant). The percent seed infection index (PSII), the contents of aflatoxin B1 (AFB1) and aflatoxin B2 (AFB2) of RILs were evaluated by a laboratory kernel inoculation assay. Results: Two QTLs were identified for PSII including one major QTL with 11.32–13.00% phenotypic variance explained (PVE). A total of 12 QTLs for aflatoxin accumulation were detected by unconditional analysis, and four of them (qAFB1A07 and qAFB1B06.1 for AFB1, qAFB2A07 and qAFB2B06 for AFB2) exhibited major and stable effects across multiple environments with 9.32–21.02% PVE. Furthermore, not only qAFB1A07 and qAFB2A07 were co-localized in the same genetic interval on LG A07, but qAFB1B06.1 was also co-localized with qAFB2B06 on LG B06. Conditional QTL mapping also confirmed that there was a strong interaction between resistance to AFB1 and AFB2 accumulation. Genotyping of RILs revealed that qAFB1A07 and qAFB1B06.1 interacted additively to improve the resistance to both AFB1 and AFB2 accumulation. Additionally, validation of the two markers was performed in diversified germplasm collection and four accessions with resistance to aflatoxin accumulation were identified. Conclusions: Single major QTL for resistance to PSII and two important co-localized intervals associated with major QTLs for resistance to AFB1 and AFB2. Combination of these intervals could improve the resistance to aflatoxin accumulation in peanut. SSR markers linked to these intervals were identified and validated. The identified QTLs and associated markers exhibit potential to be applied in improvement of resistance to aflatoxin contamination. [ABSTRACT FROM AUTHOR]

[Display omitted] • A major QTL for aflatoxin production resistance was identified in a 1.98 Mbp genomic region by both NGS-based QTL-seq approach and genetic linkage analysis. • A gene namely AhAftr1 , annotated as "NB-LRRs protein gene" with structural variation (SV) in the LRRs domain between parental lines was identified by fine-mapping using a secondary segregation mapping population. • Transgenic experiments confirmed that the SV of AhAftr1 confers aflatoxin production resistance. • RNA-Seq and differential gene expression analysis indicated that AhAftr1 might be involved in disease resistance via the ETI pathway. • Thirty-six lines were identified from a special panel of germplasm accessions and breeding lines by using AFTR.Del.A07, which was developed based on the SV, and their aflatoxin content were decreased by over 77.67% compared to the susceptible control Zhonghua12. 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. 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. 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. 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. Our findings would provide insights of aflatoxin production resistance mechanisms and laid meaningful foundation for further breeding programs. [ABSTRACT FROM AUTHOR]

Peanut is an important source of edible vegetable oils worldwide. Saturated fatty acid content is a key factor that affects the quality of peanut oil; thus, reducing its content is a key objective in peanut breeding. In this study, we constructed a dense genetic map of recombinant inbred line (RIL) population (Zhonghua 10 × ICG 12625) with 1443 SSR loci, covering a total length of 2279.10 cM. Using phenotypic data from three environments, we have identified 59 additive QTLs including eight stable ones and nine epistatic QTLs for various fatty acids. Combination of conditional and unconditional QTL analyses further revealed that there was a high genetic correlation between stearic acid and very long-chain saturated fatty acids. In addition, four QTL clusters (CLB04-1, CLB04-2, CLB04-3, and CLB06) harboring major and stable QTLs for saturated fatty acids were identified, which explained 10.77–36.73%, 35.10–41.89%, 10.79–39.18%, and 4.85–20.32% phenotypic variations, respectively. The physical interval of four QTL clusters was located at pseudomolecule B04 and B06 of Arachis ipaensis, containing putative genes that encode enzymes and transcription factors involved in fatty acid biosynthesis pathways. This study comprehensively analyzed the genetic components that controlled saturated fatty acid profiles and identified four QTL clusters containing stable QTLs with large effects. Our results could provide a platform for further gene discovery and guide the development of markers for genome-wide assisted selection of varieties with desired components of saturated fatty acids. [ABSTRACT FROM AUTHOR]