Research Article

Evaluation of insertion-deletion markers suitable for genetic diversity studies and marker-trait correlation analyses in cultivated peanut (Arachis hypogaea L.)

Published: August 12, 2016
Genet. Mol. Res. 15(3): gmr8207 DOI: 10.4238/gmr.15038207

Abstract

Peanut is one of the most important oil crops worldwide. We used insertion-deletion (InDel) markers to assess the genetic diversity and population structure in cultivated peanut. Fifty-four accessions from North China were genotyped using 48 InDel markers. The markers amplified 61 polymorphic loci with 1 to 8 alleles and an average of 2.6 alleles per marker. The polymorphism information content values ranged from 0.0364 to 0.9030, with an average of 0.5038. Population structure and neighbor-joining (NJ) tree analyses suggested that all accessions could be divided into four clusters (A1-A4), using the NJ method. Likewise, four subpopulations (G1-G4) were identified using STRUCTURE analysis. A principal component analysis was also used and results concordant with the other analysis methods were found. A multi-linear stepwise regression analysis revealed that 13 InDel markers correlated with five measured agronomical traits. Our results will provide important information for future peanut molecular breeding and genetic research.

Peanut is one of the most important oil crops worldwide. We used insertion-deletion (InDel) markers to assess the genetic diversity and population structure in cultivated peanut. Fifty-four accessions from North China were genotyped using 48 InDel markers. The markers amplified 61 polymorphic loci with 1 to 8 alleles and an average of 2.6 alleles per marker. The polymorphism information content values ranged from 0.0364 to 0.9030, with an average of 0.5038. Population structure and neighbor-joining (NJ) tree analyses suggested that all accessions could be divided into four clusters (A1-A4), using the NJ method. Likewise, four subpopulations (G1-G4) were identified using STRUCTURE analysis. A principal component analysis was also used and results concordant with the other analysis methods were found. A multi-linear stepwise regression analysis revealed that 13 InDel markers correlated with five measured agronomical traits. Our results will provide important information for future peanut molecular breeding and genetic research.