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United States Department of Agriculture

Agricultural Research Service

Title: Evaluation of Genetic Diversity and Genome-Wide Linkage Disequilibrium Amoung Us Wheat (Triticum Aetivum L.) Germplasm Representing Different Market Classes

Authors
item Chao, Shiaoman
item Zhang, Wenjun - UNIV OF CALIFORNIA-DAVIS
item Dubcovsky, Jorge - UNIV OF CALIFORNIA-DAVIS
item Sorrells, Mark - CORNELL UNIVERSITY

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 2, 2007
Publication Date: June 1, 2007
Citation: Chao, S., Zhang, W., Dubcovsky, J., Sorrells, M. 2007. Evaluation of genetic diversity and genome-wide linkage disequilibrium amoung U.S. wheat (Triticum aetivum L.) germplasm representing different market classes. Crop Science. 47:1018-1030.

Interpretive Summary: In this study we genotyped about 1,600 wheat molecular DNA markers, known as SSR markers, on a set of 43 US wheat elite cultivars and breeding lines selected from across the country representing seven US market classes. Out of these 1,600 SSR markers, we focused on a subset of 242 markers, because their precise locations on wheat chromosomes have previously been determined. We then attempted to use the marker profile data generated based on these 242 markers to answer two questions. First, how much genetic diversity is present among the 43 wheat samples that we analyzed? To breed new wheat varieties, wheat breeders generally prefer to cross lines with diverse genetic backgrounds, so they have a better chance to select lines among the progeny that will perform better than the old varieties. Therefore, the results from the genetic diversity analysis will help breeders to make decisions on what parental lines could be used to initiate a new breeding cycle. Our analysis showed that there is a high level of genetic diversity among the samples we analyzed. Although there was a low level of cross-breeding between spring and winter lines during the breeding history for some of the winter samples we analyzed, generally there is little genetic similarity shared between the spring wheat and the winter wheat. Our analysis further indicated that the genetic diversity detected corresponded well to major geographic regions of wheat production in the US. For example, all the winter wheat lines we analyzed (28 of them) were separated into two genetically distinctive groups adapted to wheat production regions east and west of the Mississippi river. This suggests that the genetic diversity existing among these US wheat lines was influenced largely by regional adaptation rather than by wheat market class. In other words, breeders tend to use the lines grown within the same production region for breeding new varieties, so that the resulting new varieties will adapt better in that region. The second question we wanted to address was: How much resolution can we achieve by using this population of 43 lines to tag agronomic traits with markers through the use of a linkage disequilibrium (LD) mechanism. LD is a non-random association between any two adjacent DNA markers, or a marker and a trait adjacent to each other within a population under study. The main concept behind LD is that the closer the DNA marker is to the trait of interest, the less likely that genetic exchange will break the association, thus increasing the chance that the marker and trait will stay together on the same chromosome, even after many generations of breeding cycles. Using the LD mechanism, one can potentially use any breeding populations to tag agronomic traits with closely associated DNA markers, also known as association mapping. However, the patterns of LD can be affected by many factors in nature, such as the mating system, the recombination (or genetic exchange) rate, population history, and directional selection. Previous studies have indicated that LD is population dependent. Therefore, we performed analysis to better understand the patterns of LD among the sample collection used in this study. Our results indicated that most of the LD regions observed were encompassed by two adjacent markers with less than 10% chance of breaking their close association (ie. the markers were at a genetic distance of 10cM apart). This suggested that if any agronomic traits were located in between the two adjacent markers at these regions, it would be likely to find an association between the trait and its adjacent markers, thus tagging the trait with these markers. Therefore, a resolution of well below 10cM would be generally possible when placing traits on wheat chromosomes using this set of wheat lines. However, we want to caution the wheat community, who intend to use the association

Technical Abstract: Genetic diversity and genome-wide linkage disequilibrium (LD) were investigated among forty-three US wheat (Triticum aestivum L.) elite cultivars and breeding lines representing seven US wheat market classes using 242 wheat genomic simple sequence repeat (SSR) markers distributed throughout the wheat genome. Genetic diversity among these lines was examined using genetic distance-based and model-based clustering methods, and analysis of molecular variance. Four populations were identified from the model-based analysis, which partitioned each of the spring and winter populations into two subpopulations, corresponding largely to major geographic regions of wheat production in the US. This suggests that the genetic diversity existing among these US wheat germplasm was influenced more by regional adaptation than by market class, and that the individuals clustered in the same model-based population likely shared related ancestral lines in their breeding history. For this germplasm collection, genome-wide LD estimates were generally less than 1cM for the genetically linked loci pairs. This may result from the population stratification and small sample size that reduced statistical power. Most of the LD regions observed were between loci less than 10cM apart. However, the distribution of LD was not uniform based on linkage distance and was independent of marker density. Consequently, LD is likely to vary widely among wheat populations.

Last Modified: 10/24/2014
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