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GWAS Discovery Of Candidate Genes for Yield-Related Traits in Peanut and Support from Earlier QTL Mapping Studies

Wang, Juan (författare)
Shandong Peanut Research Institute
Yan, Caixia (författare)
Shandong Peanut Research Institute
Li, Yuan (författare)
Lund University,Lunds universitet,Beräkningsbiologi och biologisk fysik - Har omorganiserats,Institutionen för astronomi och teoretisk fysik - Har omorganiserats,Naturvetenskapliga fakulteten,Computational Biology and Biological Physics - Has been reorganised,Department of Astronomy and Theoretical Physics - Has been reorganised,Faculty of Science
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Li, Chunjuan (författare)
Shandong Peanut Research Institute
Zhao, Xiaobo (författare)
Shandong Peanut Research Institute
Yuan, Cuiling (författare)
Shandong Peanut Research Institute
Sun, Quanxi (författare)
Shandong Peanut Research Institute
Shan, Shihua (författare)
Shandong Peanut Research Institute
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 (creator_code:org_t)
2019-10-12
2019
Engelska.
Ingår i: Genes. - : MDPI AG. - 2073-4425. ; 10:10
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Peanut (Arachishypogaea 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.

Ämnesord

LANTBRUKSVETENSKAPER  -- Bioteknologi med applikationer på växter och djur -- Genetik och förädling inom lantbruksvetenskap (hsv//swe)
AGRICULTURAL SCIENCES  -- Agricultural Biotechnology -- Genetics and Breeding in Agricultural Sciences (hsv//eng)

Nyckelord

co-localization
GBS-GWAS
peanut
QTLs

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art (ämneskategori)
ref (ämneskategori)

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