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ARS Home » Midwest Area » Urbana, Illinois » Soybean/maize Germplasm, Pathology, and Genetics Research » Research » Publications at this Location » Publication #84227
Title: IDENTIFICATION OF A CORE SET OF RANDOM PRIMERS TO EVALUATE GENETIC DIVERSITY IN SOYBEAN

Author
item Thompson, Jeffrey
item Nelson, Randall

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/4/1997
Publication Date: N/A
Citation: N/A

Interpretive Summary: Characterizing organisms by comparing differences at the DNA level is a powerful new tool for plant breeders and geneticists. One procedure, Random Amplified Polymorphic DNA (RAPD), uses random strings of DNA bases called primers to match the DNA in the soybean. Some of these primers are much better than others in detecting differences among soybean lines. The objective of this research was to select a small number of primers that can be used to establish relationships between exotic germplasm and the current U.S. genetic base. Data collected from 125 primers were used to establish relationships among 17 major ancestors of U.S. varieties and 18 exotic soybean lines. Analysis of the data allowed the selection of the most important primers in determining those relationships. We found that the data from only 35 primers could successfully define the relationships among the tested lines. This small number of highly informative primers will make it economically feasible for soybean breeders and geneticists to characterize large numbers of soybean germplasm lines.

Technical Abstract: Almost a limitless number of random primers are available to generate random amplified polymorphic DNA (RAPD) markers. However, not all random primers are equally informative. The focus of this research was to identify a small set of RAPD primers that can adequately describe the relationships among major North American soybean [Glycine max (L.) Merr.] ancestors and selected plant introductions (PIs). A data set of 281 RAPD markers collected on 35 ancestors and PIs were screened for reproducibility and levels of diversity. Principal components analysis was employed to identify RAPD markers associated with the largest sources of variation. Hierarchical and non-hierarchical cluster analyses were used to depict the relationships among the 35 genotypes. There were 120 RAPD markers from 64 random primers that were highly reproducible and had diversity scores greater than or equal to 0.30. Principal components analysis revealed that eight components explained 60% of the total variation. Step-wise removal of data from individual primers revealed that data from only 35 primers was critical to the analysis. The product-moment correlation of pairwise distances estimated from the complete RAPD marker data set and this core data set was 0.86 (P<0.0001). Results from cluster analysis confirmed that this set of primers accurately displays the relationships among the 35 genotypes. These primers will be useful for estimating relationships between exotic accessions and the current N.A. genetic base.