Abstract
Peanut (Arachis hypogaea L.) is one of the most important oil crops worldwide, and its yet increasing market demand may be met by genetic improvement of yield related traits, which may be facilitated by a good understanding of the underlying genetic base of these traits. Here, we have carried out a genome-wide association study (GWAS) with the aim to identify genomic regions and the candidate genes within these regions that may be involved in determining the phenotypic variation at seven yield-related traits in peanut. For the GWAS analyses, 195 peanut accessions were phenotyped and/or genotyped; the latter was done using a genotyping-by-sequencing approach, which produced a total of 13,435 high-quality single nucleotide polymorphisms (SNPs). Analyses of these SNPs show that the analyzed peanut accessions can be approximately grouped into two big groups that, to some extent, agree with the botanical classification of peanut at the subspecies level. By taking this genetic structure as well as the relationships between the analyzed accessions into consideration, our GWAS analyses have identified 93 non-overlapping peak SNPs that are significantly associated with four of the studied traits. Gene annotation of the genome regions surrounding these peak SNPs have found a total of 311 unique candidate genes. Among the 93 yield-related-trait-associated SNP peaks, 12 are found to be co-localized with the quantitative trait loci (QTLs) that were identified by earlier related QTL mapping studies, and these 12 SNP peaks are only related to three traits and are almost all located on chromosomes Arahy.05 and Arahy.16. Gene annotation of these 12 co-localized SNP peaks have found 36 candidates genes, and a close examination of these candidate genes found one very interesting gene (arahy.RI9HIF), the rice homolog of which produces a protein that has been shown to improve rice yield when over-expressed. Further tests of the arahy.RI9HIF gene, as well as other candidate genes especially those within the more confident co-localized genomic regions, may hold the potential for significantly improving peanut yield.
Highlights
As one important source of edible oil, the cultivated peanut (Arachis hypogaea L.) has been planted in more than 100 countries (FAOSTAT; http://faostat.fao.org) [1], including China, which has become the largest producer and exporter of peanut in the world [2]
Understanding the genetic base of yield-related traits is the most important prerequisite for peanut genetic improvement and such understanding has been greatly advanced, especially through approaches that search for quantitative trait loci (QTL)
Analysis has some significant advantages over traditional QTL mapping; for example, the much greater historical recombination and genetic diversity that are usually embedded within the studied plant lines for the former significantly increase the mapping resolution of this time-efficient method and make it rather easy for minor effect genes to be detected [11]
Summary
As one important source of edible oil, the cultivated peanut (Arachis hypogaea L.) has been planted in more than 100 countries (FAOSTAT; http://faostat.fao.org) [1], including China, which has become the largest producer and exporter of peanut in the world [2]. There is still a huge market demand for peanut, which may be resolved with genetic improvement of yield-related traits [3,4]. Understanding the genetic base of yield-related traits is the most important prerequisite for peanut genetic improvement and such understanding has been greatly advanced, especially through approaches that search for quantitative trait loci (QTL). GWAS analysis has some significant advantages over traditional QTL mapping; for example, the much greater historical recombination and genetic diversity that are usually embedded within the studied plant lines for the former significantly increase the mapping resolution of this time-efficient method and make it rather easy for minor effect genes to be detected [11]
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