|Clarice, Mensah - MICHIGAN STATE UNIVERSITY|
|Dechun, Wang - MICHIGAN STATE UNIVERSITY|
Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: November 1, 2007
Publication Date: November 7, 2007
Citation: Chen, C.Y., Gu, C., Clarice, M., Dechun, W., Nelson, R.L. 2007. SSR marker diversity of soybean aphid resistance sources in North America. ASA-CSSA-SSSA Annual Meeting Abstracts. Interpretive Summary: none required.
Technical Abstract: The soybean aphid (Aphis glycines Matsumura) has become a major pest of soybean in North America since 2000. Seven aphid resistance sources, PI 71506, Dowling (PI 548663), Jackson (PI 548657), PI 567541B, PI 567598B, PI 567543C, and PI 567597C, ranging in maturity from maturity group (MG) III to VIII have been identified. Prior knowledge of genetic relationships among these sources and their ancestral parents will help breeders to facilitate the development of new cultivars with different resistant genes. The objective of this research was to examine the genetic relationships among these resistant sources. Sixty one lines including all aphid resistant lines were tested with 86 simple sequence repeat (SSR) markers from 20 linkage groups. Nonhierarchical (VARCLUS) and hierarchical (Ward's) clustering and multidimensional scaling (MDS) were used to determine relationships among the 61 lines. Analysis of molecular variance (AMOVA) was used to estimate the components of variance among clusters and among individuals within clusters. Two hundred and sixty two alleles of the 86 SSR loci were detected with a mean polymorphism information content (PIC) value of 0.36. The 61 lines were grouped into four clusters by both clustering methods and the MDS results consistently corresponded to the assigned clusters. The seven resistant sources were clustered into three different groups corresponding to their geographical origin and known pedigree information indicating genetic differences among these sources. The largest variation was found among individuals within different clusters by AMOVA.