High-Density Genetic Variation Map Reveals Key Candidate Loci and Genes Associated With Important Agronomic Traits in Peanut

Using cross-country datasets for association mapping in Arachis hypogaea L

Groundnut (Arachis hypogaea L.) is one of the most important climate-resilient oil crops in sub-Saharan Africa. There is a significant yield gap for groundnut in Africa because of poor soil fertility, low agricultural inputs, biotic and abiotic stresses. Cross-country evaluations of promising breeding lines can facilitate the varietal development process. The objective of our study was to characterize popular test environments in Uganda (Serere and Nakabango) and Malawi (Chitala and Chitedze) and identify genotypes with stable superior yields for potential future release. Phenotypic data were generated for 192 breeding lines for yield-related traits, while genotypic data were generated using skim-sequencing. We observed significant variation (p < 0.001; p < 0.01; p < 0.05) across genotypes for all yield-related traits: days to flowering (DTF), pod yield (PY), shelling percentage, 100-seed weight, and grain yield within and across locations. Nakabango, Chitedze, and Serere were clustered as one mega-environment with the top five most stable genotypes being ICGV-SM 01709, ICGV-SM 15575, ICGV-SM 90704, ICGV-SM 15576, and ICGV-SM 03710, all Virginia types. Population structure analysis clustered the genotypes in three distinct groups based on market classes. Eight and four marker-trait associations (MTAs) were recorded for DTF and PY, respectively. One of the MTAs for DTF was co-localized within an uncharacterized protein on chromosome 13, while another one (TRv2Chr.11_3476885) was consistent across the two countries. Future studies will need to further characterize the candidate genes as well as confirm the stability of superior genotypes across seasons before recommending them for release.

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

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

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Identification of QTLs associated with very-long chain fatty acid (VLCFA) content via linkage mapping and BSA-seq in peanut

KEY MESSAGE

Three major QTLs qA01, qB04.1 and qB05 for VLCFA content and their corresponding allele-specific markers will benefit peanut low VLCFA breeding, and a candidate gene Arahy.IF1JV3 was predicted. Peanut is a globally significant oilseed crop worldwide, and contains a high content (20%) of saturated fatty acid (SFA) in its seeds. As high level SFA intake in human dietary may increase the cardiovascular disease risk, reducing the SFA content in peanut is crucial for improving its nutritional quality. Half of the SFAs in peanut are very long-chain fatty acids (VLCFA), so reducing the VLCFA content is a feasible strategy to decrease the total SFA content. Luoaowan with extremely low VLCFA (4.80%) was crossed with Jihua16 (8.00%) to construct an F2:4 population. Three major QTLs including qA01, qB04.1 and qB05 for VLCFA content were detected with 4.43 ~ 14.32% phenotypic variation explained through linkage mapping. Meanwhile, three genomic regions on chromosomes B03, B04 and B05 were identified via BSA-seq approach. Two co-localized intervals on chromosomes B04 (100.10 ~ 103.97 Mb) and B05 (6.39 ~ 10.90 Mb) were identified. With markers developed based on SNP/InDel variations in qA01 between the two parents, the remaining interval was refined to 103.58 ~ 111.14 Mb. A candidate gene Arahy.IF1JV3 encoding a β-ketoacyl-CoA synthase was found in qA01, and its expression level in Luoaowan was significantly lower than that in Jihua16. Allele-specific markers targeting qA01, qB04.1 and qB05 were developed and validated in F4 population, and an elite line with high oleic, low VLCFA (5.05%) and low SFA (11.48%) contents was selected. This study initially revealed the genetic mechanism of VLCFA content, built a marker-assisted selection system for low VLCFA breeding, and provided an effective method to decrease the SFA content in peanut.

Mapping Quantitative Trait Loci (QTLs) for Hundred-Pod and Hundred-Seed Weight under Seven Environments in a Recombinant Inbred Line Population of Cultivated Peanut (Arachis hypogaea L.)

The cultivated peanut (Arachis hypogaea L.) is a significant oil and cash crop globally. Hundred-pod and -seed weight are important components for peanut yield. To unravel the genetic basis of hundred-pod weight (HPW) and hundred-seed weight (HSW), in the current study, a recombinant inbred line (RIL) population with 188 individuals was developed from a cross between JH5 (JH5, large pod and seed weight) and M130 (small pod and seed weight), and was utilized to identify QTLs for HPW and HSW. An integrated genetic linkage map was constructed by using SSR, AhTE, SRAP, TRAP and SNP markers. This map consisted of 3130 genetic markers, which were assigned to 20 chromosomes, and covered 1998.95 cM with an average distance 0.64 cM. On this basis, 31 QTLs for HPW and HSW were located on seven chromosomes, with each QTL accounting for 3.7-10.8% of phenotypic variance explained (PVE). Among these, seven QTLs were detected under multiple environments, and two major QTLs were found on B04 and B08. Notably, a QTL hotspot on chromosome A08 contained seven QTLs over a 2.74 cM genetic interval with an 0.36 Mb physical map, including 18 candidate genes. Of these, Arahy.D52S1Z, Arahy.IBM9RL, Arahy.W18Y25, Arahy.CPLC2W and Arahy.14EF4H might play a role in modulating peanut pod and seed weight. These findings could facilitate further research into the genetic mechanisms influencing pod and seed weight in cultivated peanut.

Estimates of Genomic Heritability and the Marker-Derived Gene for Re(Production) Traits in Xinggao Sheep

Xinggao sheep are a breed of Chinese domestic sheep that are adapted to the extremely cold climatic features of the Hinggan League in China. The economically vital reproductive trait of ewes (litter size, LS) and productive traits of lambs (birth weight, BWT; weaning weight, WWT; and average daily gain, ADG) are expressed in females and later in life after most of the selection decisions have been made. This study estimated the genetic parameters for four traits to explore the genetic mechanisms underlying the variation, and we performed genome-wide association study (GWAS) tests on a small sample size to identify novel marker trait associations (MTAs) associated with prolificacy and growth. We detected two suggestive significant single-nucleotide polymorphisms (SNPs) associated with LS and eight significant SNPs for BWT, WWT, and ADG. These candidate loci and genes also provide valuable information for further fine-mapping of QTLs and improvement of reproductive and productive traits in sheep.