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

Genetic analysis and fine mapping reveal that AhRt3, which encodes an anthocyanin reductase, is responsible for red testa in cultivated peanuts

KEY MESSAGE

AhRt3, which governs the red testa of peanut, was narrowed down to a 125.30 kb region, and one gene encoding anthocyanin reductase was identified as the putative candidate gene. Testa color is a special characteristic of peanuts (Arachis hypogaea L.), and those with dark testa have been focused on recent years owing to their high-anthocyanin content and increased antioxidant nutritional value. However, the genetic mechanisms underlying this trait remain limited. To identify the gene responsible for the red testa color in peanuts, an F2 population was constructed by crossing YH91 (pink testa) with JHT1 (red testa). Genetic analysis revealed that the red testa was controlled by a single dominant gene named AhRt3 (Arachis hypogaea Red Testa 3). Through bulked segregant analysis sequencing, AhRt3 was preliminarily mapped to the chromosome Arahy.03 and subsequently narrowed to a 125.30 kb genomic region containing 12 potential candidate genes. RNA-seq analysis revealed that 4,880 genes were differentially expressed in the seed testa, with only the candidate gene Arahy.W8TDEC exhibiting higher expression levels in JHT1 than in YH91. Additionally, sequence variation, functional annotation, and expression profiling confirmed that Arahy.W8TDEC, which encodes an anthocyanin reductase, may be a candidate gene for AhRt3. The structural variation involving an inversion between the sixth exon and the 3'UTR of Arahy.W8TDEC resulted in altered amino acids closely associated with the red testa phenotype in peanuts. In conclusion, this study highlights the role of a novel gene in regulating red testa and contributes valuable insights into the genetic basis of seed testa in peanuts.

PSC1, a basic/helix-loop-helix transcription factor controlling the purplish-red testa trait in peanut

Seed color is a key agronomic trait in crops such as peanut, where it is a vital indicator of both nutritional and commercial value. In recent years, peanuts with darker seed coats have gained market attention due to their high anthocyanin content. Here, we used bulk segregant analysis to identify the gene associated with the purplish-red coat trait and identified a novel gene encoding a basic/helix-loop-helix transcription factor, PURPLE RED SEED COAT1 (PSC1), which regulates the accumulation of anthocyanins in the seed coat. Specifically, we found that a 35-bp insertion in the PSC1 promoter increased the abundance of PSC1 mRNA. Transcriptomic and metabolomic analyses indicated that the purplish-red color of the seed coat was the result of decreased expression of anthocyanidin reductase (ANR), leading to increased accumulation of delphinidin, cyanidin, and pelargonidin derivatives. Further analysis revealed that PSC1 interacts with AhMYB7 to form a complex that specifically binds to the ANR promoter to suppress its expression, resulting in increased anthocyanin accumulation. Moreover, overexpression of PSC1 increased anthocyanin content in Arabidopsis thaliana and peanut callus. Our study reveals a new gene that controls seed coat color by regulating anthocyanin metabolism and provides a valuable genetic resource for breeding peanuts with a purplish-red seed coat.

Integrated eQTL mapping approach reveals genomic regions regulating candidate genes of the E8-r3 locus in soybean

Deciphering the gene regulatory networks of critical quantitative trait loci associated with early maturity provides information for breeders to unlock soybean's (Glycine max (L.) Merr.) northern potential and expand its cultivation range. The E8-r3 locus is a genomic region regulating the number of days to maturity under constant short-day photoperiodic conditions in two early-maturing soybean populations (QS15524F2:F3 and QS15544RIL) belonging to maturity groups MG00 and MG000. In this study, we developed a combinatorial expression quantitative trait loci mapping approach using three algorithms (ICIM, IM, and GCIM) to identify the regions that regulate three candidate genes of the E8-r3 locus (Glyma.04G167900/GmLHCA4a, Glyma.04G166300/GmPRR1a, and Glyma.04G159300/GmMDE04). Using this approach, a total of 2,218 trans (2,061 genes)/7 cis (7 genes) and 4,073 trans (2,842 genes)/3,083 cis (2,418 genes) interactions were mapped in the QS15524F2:F3 and QS15544RIL populations, respectively. From these interactions, we successfully identified two hotspots (F2_GM15:49,385,092-49,442,237 and F2_GM18:1,434,182-1,935,386) and three minor regions (RIL_GM04:17,227,512-20,251,662, RIL_GM04:31,408,946-31,525,671 and RIL_GM13:37,289,785-38,620,690) regulating the candidate genes of E8-r3 and several of their homologs. Based on co-expression network and single nucleotide variant analyses, we identified ALTERED PHLOEM DEVELOPMENT (Glyma.15G263700) and DOMAIN-CONTAINING PROTEIN 21 (Glyma.18G025600) as the best candidates for the F2_GM15:49,385,092-49,442,237 and F2_GM18:1,434,182-1,935,386 hotspots. These findings demonstrate that a few key regions are involved in the regulation of the E8-r3 candidates GmLHCA4a, GmPRR1a, and GmMDE04.

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.

Alterations in Growth Habit to Channel End-of-Season Perennial Reserves towards Increased Yield and Reduced Regrowth after Defoliation in Upland Cotton (Gossypium hirsutum L.)

Cotton (Gossypium spp.) is the primary source of natural textile fiber in the U.S. and a major crop in the Southeastern U.S. Despite constant efforts to increase the cotton fiber yield, the yield gain has stagnated. Therefore, we undertook a novel approach to improve the cotton fiber yield by altering its growth habit from perennial to annual. In this effort, we identified genotypes with high-expression alleles of five floral induction and meristem identity genes (FT, SOC1, FUL, LFY, and AP1) from an Upland cotton mini-core collection and crossed them in various combinations to develop cotton lines with annual growth habit, optimal flowering time, and enhanced productivity. To facilitate the characterization of genotypes with the desired combinations of stacked alleles, we identified molecular markers associated with the gene expression traits via genome-wide association analysis using a 63 K SNP Array. Over 14,500 SNPs showed polymorphism and were used for association analysis. A total of 396 markers showed associations with expression traits. Of these 396 markers, 159 were mapped to genes, 50 to untranslated regions, and 187 to random genomic regions. Biased genomic distribution of associated markers was observed where more trait-associated markers mapped to the cotton D sub-genome. Many quantitative trait loci coincided at specific genomic regions. This observation has implications as these traits could be bred together. The analysis also allowed the identification of candidate regulators of the expression patterns of these floral induction and meristem identity genes whose functions will be validated.

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.

Integrated metabolomic and transcriptomic analysis reveal the effect of mechanical stress on sugar metabolism in tea leaves (Camellia sinensis) post-harvest

Sugar metabolites not only act as the key compounds in tea plant response to stress but are also critical for tea quality formation during the post-harvest processing of tea leaves. However, the mechanisms by which sugar metabolites in post-harvest tea leaves respond to mechanical stress are unclear. In this study, we aimed to investigate the effects of mechanical stress on saccharide metabolites and related post-harvest tea genes. Withered (C15) and mechanically-stressed (V15) for 15 min Oolong tea leaves were used for metabolome and transcriptome sequencing analyses. We identified a total of 19 sugar metabolites, most of which increased in C15 and V15. A total of 69 genes related to sugar metabolism were identified using transcriptome analysis, most of which were down-regulated in C15 and V15. To further understand the relationship between the down-regulated genes and sugar metabolites, we analyzed the sucrose and starch, galactose, and glycolysis metabolic pathways, and found that several key genes of invertase (INV), α-amylase (AMY), β-amylase (BMY), aldose 1-epimerase (AEP), and α-galactosidase (AGAL) were down-regulated. This inhibited the hydrolysis of sugars and might have contributed to the enrichment of galactose and D-mannose in V15. Additionally, galactinol synthase (Gols), raffinose synthase (RS), hexokinase (HXK), 6-phosphofructokinase 1 (PFK-1), and pyruvate kinase (PK) genes were significantly upregulated in V15, promoting the accumulation of D-fructose-6-phosphate (D-Fru-6P), D-glucose-6-phosphate (D-glu-6P), and D-glucose. Transcriptome and metabolome association analysis showed that the glycolysis pathway was enhanced and the hydrolysis rate of sugars related to hemicellulose synthesis slowed in response to mechanical stress. In this study, we explored the role of sugar in the response of post-harvest tea leaves to mechanical stress by analyzing differences in the expression of sugar metabolites and related genes. Our results improve the understanding of post-harvest tea's resistance to mechanical stress and the associated mechanism of sugar metabolism. The resulting treatment may be used to control the quality of Oolong tea.

Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus

BACKGROUND

Regulation of gene expression plays an essential role in controlling the phenotypes of plants. Brassica napus (B. napus) is an important source for the vegetable oil in the world, and the seed oil content is an important trait of B. napus.

RESULTS

We perform a comprehensive analysis of the transcriptional variability in the seeds of B. napus at two developmental stages, 20 and 40 days after flowering (DAF). We detect 53,759 and 53,550 independent expression quantitative trait loci (eQTLs) for 79,605 and 76,713 expressed genes at 20 and 40 DAF, respectively. Among them, the local eQTLs are mapped to the adjacent genes more frequently. The adjacent gene pairs are regulated by local eQTLs with the same open chromatin state and show a stronger mode of expression piggybacking. Inter-subgenomic analysis indicates that there is a feedback regulation for the homoeologous gene pairs to maintain partial expression dosage. We also identify 141 eQTL hotspots and find that hotspot87-88 co-localizes with a QTL for the seed oil content. To further resolve the regulatory network of this eQTL hotspot, we construct the XGBoost model using 856 RNA-seq datasets and the Basenji model using 59 ATAC-seq datasets. Using these two models, we predict the mechanisms affecting the seed oil content regulated by hotspot87-88 and experimentally validate that the transcription factors, NAC13 and SCL31, positively regulate the seed oil content.

CONCLUSIONS

We comprehensively characterize the gene regulatory features in the seeds of B. napus and reveal the gene networks regulating the seed oil content of B. napus.

Targeted metabolome analysis reveals accumulation of metabolites in testa of four peanut germplasms

Cultivated peanut (Arachis hypogaea L.) is an important source of edible oil and protein. Peanut testa (seed coat) provides protection for seeds and serves as a carrier for diversity metabolites necessary for human health. There is significant diversity available for testa color in peanut germplasms. However, the kinds and type of metabolites in peanut testa has not been comprehensively investigated. In this study, we performed metabolite profiling using UPLC-MS/MS for four peanut germplasm lines with different testa colors, including pink, purple, red, and white. A total of 85 metabolites were identified in four peanuts. Comparative metabolomics analysis identified 78 differentially accumulated metabolites (DAMs). Some metabolites showed significant correlation with other metabolites. For instance, proanthocyanidins were positively correlated with cyanidin 3-O-rutinoside and malvin, and negatively correlated with pelargonidin-3-glucoside. We observed that the total proanthocyanidins are most abundant in pink peanut variety WH10. The red testa accumulated more isoflavones, flavonols and anthocyanidins compared with that in pink testa. These results provided valuable information about differential accumulation of metabolites in testa with different color, which are helpful for further investigation of the molecular mechanism underlying biosynthesis and accumulation of these metabolites in peanut.

BSA‑seq and genetic mapping reveals AhRt2 as a candidate gene responsible for red testa of peanut

The candidate recessive gene AhRt2 responsible for red testa of peanut was identified through combined BSA-seq and linkage mapping approaches. The testa color of peanuts (Arachis hypogaea L.) is an important trait, and those with red testa are particularly popular owing to the high-anthocyanin content. However, the identification of genes underlying the regulation of the red testa trait in peanut are rarely reported. In order to fine map red testa gene, two F_2:4 populations were constructed through the cross of YZ9102 (pink testa) with ZH12 (red testa) and ZH2 (red testa). Genetic analysis indicated that red testa was controlled by a single recessive gene named as AhRt2 (Red testa gene 2). Using BSA-seq approach, AhRt2 was preliminary identified on chromosome 12, which was further mapped to a 530-kb interval using 220 recombinant lines through linkage mapping. Furthermore, functional annotation, expression profiling, and the analyses of sequence variation confirmed that the anthocyanin reductase namely (Arahy.IK60LM) was the most likely candidate gene for AhRt2. It was found that a SNP in the third exon of AhRt2 altered the encoding amino acids, and was associated with red testa in peanut. In addition, a closely linked molecular marker linked with red testa trait in peanut was also developed for future studies. Our results provide valuable insight into the molecular mechanism underlying peanut testa color and present significant diagnostic marker resources for marker-assisted selected breeding in peanut.

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.

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.

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.

Genetic dissection of rhizome yield-related traits in Nelumbo nucifera through genetic linkage map construction and QTL mapping

Lotus (Nelumbo nucifera) is a perennial aquatic plant with great value in ornamentation, nutrition, and medicine. Being a storage organ, lotus rhizome is not only used for vegetative reproduction, but also as a popular vegetable in Southeast Asia. Rhizome development, especially enlargement, largely determines its yield and hence becomes one of the major concerns in rhizome lotus breeding and cultivation. To obtain the genetic characteristic of this trait, and discover markers or genes associated with this trait, an F₂ population was generated by crossing between temperate and tropical cultivars with contrasting rhizome enlargement. Based on this F₂ population and Genotyping-by-Sequencing (GBS) technique, a genetic map was constructed with 1475 bin markers containing 12,113 SNP markers. Six traits associated with rhizome yield were observed over 3 years. Quantitative trait locus (QTL) mapping analysis identified 22 QTLs that are associated with at least one of these traits, among which 9 were linked with 3 different intervals. Comparison of the genes located in these three intervals with our previous transcriptomic data showed that light and phytohormone signaling might contribute to the development and enlargement of lotus rhizome. The QTLs obtained here could also be used for marker-assisted breeding of rhizome lotus.

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.

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.