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

KEY MESSAGE: 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.

Comprehensive evaluation of Chinese peanut mini-mini core collection and QTL mapping for aflatoxin resistance.

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.

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

KEY MESSAGE: 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.

Key Regulators of Sucrose Metabolism Identified through Comprehensive Comparative Transcriptome Analysis in Peanuts.

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.

Genome-wide expression quantitative trait locus analysis in a recombinant inbred line population for trait dissection in peanut.

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.

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.).

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.

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

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.

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.

Optimization of extraction of total trans-resveratrol from peanut seeds and its determination by HPLC.

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.

Discovery of genomic regions and candidate genes controlling shelling percentage using QTL-seq approach in cultivated peanut (Arachis hypogaea L.).

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.

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

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.

Identification of genomic regions and diagnostic markers for resistance to aflatoxin contamination in peanut (Arachis hypogaea L.).

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.

Chromosomes A07 and A05 associated with stable and major QTLs for pod weight and size in cultivated peanut (Arachis hypogaea L.).

KEY MESSAGE: Co-localized intervals and candidate genes were identified for major and stable QTLs controlling pod weight and size on chromosomes A07 and A05 in an RIL population across four environments. Cultivated peanut (Arachis hypogaea L.) is an important legume crops grown in > 100 countries. Hundred-pod weight (HPW) is an important yield trait in peanut, but its underlying genetic mechanism was not well studied. In this study, a mapping population (Xuhua 13 × Zhonghua 6) with 187 recombinant inbred lines (RILs) was developed to map quantitative trait loci (QTLs) for HPW together with pod length (PL) and pod width (PW) by both unconditional and conditional QTL analyses. A genetic map covering 1756.48 cM was constructed with 817 markers. Additive effects, epistatic interactions, and genotype-by-environment interactions were analyzed using the phenotyping data generated across four environments. Twelve additive QTLs were identified on chromosomes A05, A07, and A08 by unconditional analysis, and five of them (qPLA07, qPLA05.1, qPWA07, qHPWA07.1, and qHPWA05.2) showed major and stable expressions in all environments. Conditional QTL mapping found that PL had stronger influences on HPW than PW. Notably, qHPWA07.1, qPLA07, and qPWA07 that explained 17.93-43.63% of the phenotypic variations of the three traits were co-localized in a 5 cM interval (1.48 Mb in physical map) on chromosome A07 with 147 candidate genes related to catalytic activity and metabolic process. In addition, qHPWA05.2 and qPLA05.1 were co-localized with minor QTL qPWA05.2 to a 1.3 cM genetic interval (280 kb in physical map) on chromosome A05 with 12 candidate genes. This study provides a comprehensive characterization of the genetic components controlling pod weight and size as well as candidate QTLs and genes for improving pod yield in future peanut breeding.

Co-localization of major quantitative trait loci for pod size and weight to a 3.7 cM interval on chromosome A05 in cultivated peanut (Arachis hypogaea L.).

BACKGROUND: Cultivated peanut (Arachis hypogaea L.), an important source of edible oil and protein, is widely grown in tropical and subtropical areas of the world. Genetic improvement of yield-related traits is essential for improving yield potential of new peanut varieties. Genomics-assisted breeding (GAB) can accelerate the process of genetic improvement but requires linked markers for the traits of interest. In this context, we developed a recombinant inbred line (RIL) mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 individuals and used to map quantitative trait loci (QTLs) associated with three important pod features, namely pod length, pod width and hundred-pod weight. RESULTS: QTL analysis using the phenotyping data generated across four environments in two locations and genotyping data on 743 mapped loci identified 15 QTLs for pod length, 11 QTLs for pod width and 16 QTLs for hundred-pod weight. The phenotypic variation explained (PVE) ranged from 3.68 to 27.84%. Thirteen QTLs were consistently detected in at least two environments and three QTLs (qPLA05.7, qPLA09.3 and qHPWA05.6) were detected in all four environments indicating their consistent and stable expression. Three major QTLs, detected in at least three environments, were found to be co-localized to a 3.7 cM interval on chromosome A05, and they were qPLA05.7 for pod length (16.89-27.84% PVE), qPWA05.5 for pod width (13.73-14.12% PVE), and qHPWA05.6 for hundred-pod weight (13.75-26.82% PVE). This 3.7 cM linkage interval corresponds to ~2.47 Mb genomic region of the pseudomolecule A05 of A. duranensis, including 114 annotated genes related to catalytic activity and metabolic process. CONCLUSIONS: This study identified three major consistent and stable QTLs for pod size and weight which were co-localized in a 3.7 cM interval on chromosome A05. These QTL regions not only offer further investigation for gene discovery and development of functional markers but also provide opportunity for deployment of these QTLs in GAB for improving yield in peanut.

Development of SSR markers and identification of major quantitative trait loci controlling shelling percentage in cultivated peanut (Arachis hypogaea L.).

KEY MESSAGE: A total of 204,439 SSR markers were developed in diploid genomes, and 25 QTLs for shelling percentage were identified in a RIL population across 4 years including five consistent QTLs. Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing edible oil and protein for human nutrition. Genome sequences of its diploid ancestors, Arachis duranensis and A. ipaensis, were reported, but their SSRs have not been well exploited and utilized hitherto. Shelling percentage is an important economic trait and its improvement has been one of the major objectives in peanut breeding programs. In this study, the genome sequences of A. duranensis and A. ipaensis were used to develop SSR markers, and a mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 recombinant inbred lines was used to map QTLs controlling shelling percentage. The numbers of newly developed SSR markers were 84,383 and 120,056 in the A. duranensis and A. ipaensis genomes, respectively. Genotyping of the mapping population was conducted with both newly developed and previously reported markers. QTL analysis using the phenotyping data generated in Wuhan across four consecutive years and genotyping data of 830 mapped loci identified 25 QTLs with 4.46-17.01% of phenotypic variance explained in the four environments. Meta-analysis revealed five consistent QTLs that could be detected in at least two environments. Notably, the consistent QTL cqSPA09 was detected in all four environments and explained 10.47-17.01% of the phenotypic variance. The segregation in the progeny of a residual heterozygous line confirmed that the cpSPA09 locus had additive effect in increasing shelling percentage. These consistent and major QTL regions provide opportunity not only for further gene discovery, but also for the development of functional markers for breeding.

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.

Genetic mapping of AhVt1, a novel genetic locus that confers the variegated testa color in cultivated peanut (Arachis hypogaea L.) and its utilization for marker-assisted selection.

Introduction: Peanut (Arachis hypogaea L.) is an important cash crop worldwide. Compared with the ordinary peanut with pure pink testa, peanut with variegated testa color has attractive appearance and a higher market value. In addition, the variegated testa represents a distinct regulation pattern of anthocyanin accumulation in integument cells. Methods: In order to identify the genetic locus underlying variegated testa color in peanut, two populations were constructed from the crosses between Fuhua 8 (pure-pink testa) and Wucai (red on white variegated testa), Quanhonghua 1 (pure-red testa) and Wucai, respectively. Genetic analysis and bulked sergeant analysis sequencing were applied to detect and identify the genetic locus for variegated testa color. Marker-assisted selection was used to develop new variegated testa peanut lines. Results: As a result, all the seeds harvested from the F1 individuals of both populations showed the variegated testa type with white trace. Genetic analysis revealed that the pigmentation of colored region in red on white variegated testa was controlled by a previous reported gene AhRt1, while the formation of white region (un-pigmented region) in variegated testa was controlled by another single genetic locus. This locus, named as AhVt1 (Arachis hypogaea Variegated Testa 1), was preliminary mapped on chromosome 08 through bulked sergeant analysis sequencing. Using a secondary mapping population derived from the cross between Fuhua 8 and Wucai, AhVt1 was further mapped to a 1.89-Mb genomic interval by linkage analysis, and several potential genes associated with the uneven distribution of anthocyanin, such as MADS-box, MYB, and Chalcone synthase-like protein, were harbored in the region. Moreover, the molecular markers closely linked to the AhVt1 were developed, and the new variegated testa peanut lines were obtained with the help of marker-assisted selection. Conclusion: Our findings will accelerate the breeding program for developing new peanut varieties with "colorful" testa colors and laid a foundation for map-based cloning of gene responsible for variegated testa.

Identification and Pyramiding Major QTL Loci for Simultaneously Enhancing Aflatoxin Resistance and Yield Components in Peanut.

Peanut is susceptible to Aspergillus flavus infection, and the consequent aflatoxin contamination has been recognized as an important risk factor affecting food safety and industry development. Planting peanut varieties with resistance to aflatoxin contamination is regarded as an ideal approach to decrease the risk in food safety, but most of the available resistant varieties have not been extensively used in production because of their low yield potential mostly due to possessing small pods and seeds. Hence, it is highly necessary to integrate resistance to aflatoxin and large seed weight. In this study, an RIL population derived from a cross between Zhonghua 16 with high yield and J 11 with resistance to infection of A. flavus and aflatoxin production, was used to identify quantitative trait locus (QTL) for aflatoxin production (AP) resistance and hundred-seed weight (HSW). From combined analysis using a high-density genetic linkage map constructed, 11 QTLs for AP resistance with 4.61-11.42% phenotypic variation explanation (PVE) and six QTLs for HSW with 3.20-28.48% PVE were identified, including three major QTLs for AP resistance (qAFTA05.1, qAFTB05.2 and qAFTB06.3) and three for HSW (qHSWA05, qHSWA08 and qHSWB06). In addition, qAFTA05.1, qAFTB06.3, qHSWA05, qHSWA08 and qHSWB06 were detected in multiple environments. The aflatoxin contents under artificial inoculation were decreased by 34.77-47.67% in those segregated lines harboring qAFTA05.1, qAFTB05.2 and qAFTB06.3, while the HSWs were increased by 47.56-49.46 g in other lines harboring qHSWA05, qHSWA08 and qHSWB06. Conditional QTL mapping indicated that HSW and percent seed infection index (PSII) had no significant influence on aflatoxin content. Interestingly, the QT 1059 simultaneously harboring alleles of aflatoxin content including qAFTA05.1 and qAFTB05.2, alleles of PSII including qPSIIB03.1, qPSIIB03.2, and qPSIIB10 and alleles of HSW including qHSWA05, qHSWB06, qHSWA08 had better resistance to A. flavus infection and to toxin production and higher yield potential compared with the two parents of the RIL. The above identified major loci for AP resistance and HWS would be helpful for marker-assisted selection in peanut breeding.

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.

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.