Genome-wide approaches delineate the additive, epistatic, and pleiotropic nature of variants controlling fatty acid composition in peanut (Arachis hypogaea L.)

Epistasis and pleiotropy-induced variation for plant breeding

Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.

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.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Genome-wide association studies reveal novel loci for resistance to groundnut rosette disease in the African core groundnut collection

We identified markers associated with GRD resistance after screening an Africa-wide core collection across three seasons in Uganda Groundnut is cultivated in several African countries where it is a major source of food, feed and income. One of the major constraints to groundnut production in Africa is groundnut rosette disease (GRD), which is caused by a complex of three agents: groundnut rosette assistor luteovirus, groundnut rosette umbravirus and its satellite RNA. Despite several years of breeding for GRD resistance, the genetics of the disease is not fully understood. The objective of the current study was to use the African core collection to establish the level of genetic variation in their response to GRD, and to map genomic regions responsible for the observed resistance. The African groundnut core genotypes were screened across two GRD hotspot locations in Uganda (Nakabango and Serere) for 3 seasons. The Area Under Disease Progress Curve combined with 7523 high quality SNPs were analyzed to establish marker-trait associations (MTAs). Genome-Wide Association Studies based on Enriched Compressed Mixed Linear Model detected 32 MTAs at Nakabango: 21 on chromosome A04, 10 on B04 and 1 on B08. Two of the significant markers were localised on the exons of a putative TIR-NBS-LRR disease resistance gene on chromosome A04. Our results suggest the likely involvement of major genes in the resistance to GRD but will need to be further validated with more comprehensive phenotypic and genotypic datasets. The markers identified in the current study will be developed into routine assays and validated for future genomics-assisted selection for GRD resistance in groundnut.

Understanding variation in oleic acid content of high-oleic virginia-type peanut

Contamination at the FAD2B locus due to inadequate screening protocols is the primary cause of sporadic, insufficient oleic acid content in Virginia-type peanut. The high oleic trait in peanut is conditioned by loss-of-function mutations in a pair of homeologous enzymes and is well known to improve the shelf life of peanut products. As such, the trait is given high priority in current and future cultivars by the North Carolina State University peanut breeding program. For unknown reasons, high oleic cultivars and breeding lines intermittently failed to meet self-imposed thresholds for oleic acid content in internal testing. To determine why, a manual seed chipper, crude DNA isolation protocol, genotyping assays for both mutations, and a web-based SNP calling application were developed. The primary cause was determined to be contamination with normal oleic seeds resulting from inadequate screening protocols. In order to correct the problem, a faster screening method was acquired to accommodate a higher oleic acid threshold. Additionally, results showed the mutation in one homeolog is fixed in the program, dig date had no significant effect on oleic acid content, and minor modifiers segregating within the program explained 6% of the variation in oleic acid content.