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Analysis of genetic diversity and population structure of peanut cultivars and breeding lines from China, India and the US using simple sequence repeat markers
Author(s) -
Wang Hui,
Khera Pawan,
Huang Bingyan,
Yuan Mei,
Katam Ramesh,
Zhuang Weijian,
HarrisShultz Karen,
Moore Kim M.,
Culbreath Albert K.,
Zhang Xinyou,
Varshney Rajeev K.,
Xie Lianhui,
Guo Baozhu
Publication year - 2016
Publication title -
journal of integrative plant biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.734
H-Index - 83
eISSN - 1744-7909
pISSN - 1672-9072
DOI - 10.1111/jipb.12380
Subject(s) - genetic diversity , dendrogram , biology , cultivar , allele , microsatellite , population , genetic distance , locus (genetics) , genetic structure , breeding program , plant breeding , microbiology and biotechnology , molecular breeding , genetics , genetic variation , botany , gene , demography , sociology
Cultivated peanut is grown worldwide as rich‐source of oil and protein. A broad genetic base is needed for cultivar improvement. The objectives of this study were to develop highly informative simple sequence repeat (SSR) markers and to assess the genetic diversity and population structure of peanut cultivars and breeding lines from different breeding programs in China, India and the US. A total of 111 SSR markers were selected for this study, resulting in a total of 472 alleles. The mean values of gene diversity and polymorphic information content (PIC) were 0.480 and 0.429, respectively. Country‐wise analysis revealed that alleles per locus in three countries were similar. The mean gene diversity in the US, China and India was 0.363, 0.489 and 0.47 with an average PIC of 0.323, 0.43 and 0.412, respectively. Genetic analysis using the STRUCTURE divided these peanut lines into two populations (P1, P2), which was consistent with the dendrogram based on genetic distance (G1, G2) and the clustering of principal component analysis. The groupings were related to peanut market types and the geographic origin with a few admixtures. The results could be used by breeding programs to assess the genetic diversity of breeding materials to broaden the genetic base and for molecular genetics studies.