|Chen, Yiwu - MICHIGAN STATE UNIV.|
|Gu, Cuihua - MICHIGAN STATE UNIV.|
|Mensah, Clarice - MICHIGAN STATE UNIV.|
|Wang, Dechun - MICHIGAN STATE UNIV.|
Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 15, 2007
Publication Date: November 21, 2007
Citation: Chen, Y., Gu, C., Mensah, C., Nelson, R.L., Wang, D. 2007. SSR marker diversity of soybean aphid resistance sources in northern America. Crop Science. 50:1104-1111. Interpretive Summary: Soybean aphid is a recently introduce pest of soybean in the northern U.S. Aphids have caused significant yield losses and have necessitated the application of insecticides to protect the crop. Host plant resistance, a more economical and environmentally friendly means of control, has been identified in several lines from the USDA Soybean Germplasm Collection. We used DNA markers to determine the genetic relationships among these resistant lines. We found that the resistance sources were distributed among 3 different genetic groups. These data indicate that this lines are genetically different and may carry different genes for resistant. These results will be of most interest to soybean breeders and entomologist who are developing aphid resistant varieties.
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 resistance 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.