The Plant Genome (Jul 2013)

Structural and Temporal Variation in Genetic Diversity of European Spring Two-Row Barley Cultivars and Association Mapping of Quantitative Traits

  • Alessandro Tondelli,
  • Xin Xu,
  • Marc Moragues,
  • Rajiv Sharma,
  • Florian Schnaithmann,
  • Christina Ingvardsen,
  • Outi Manninen,
  • Jordi Comadran,
  • Joanne Russell,
  • Robbie Waugh,
  • Alan H. Schulman,
  • Klaus Pillen,
  • Søren K. Rasmussen,
  • Benjamin Kilian,
  • Luigi Cattivelli,
  • William T. B. Thomas,
  • Andrew J. Flavell

DOI
https://doi.org/10.3835/plantgenome2013.03.0007
Journal volume & issue
Vol. 6, no. 2

Abstract

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Two hundred sixteen barley ( L.) cultivars were selected to represent the diversity and history of European spring two-row barley breeding and to search for alleles controlling agronomic traits by association genetics. The germplasm was genotyped with 7864 gene-based single nucleotide polymorphism markers and corresponding field trial trait data relating to growth and straw strength were obtained at multiple European sites. Analysis of the marker data by statistical population genetics approaches revealed two important trends in the genetic diversity of European two-row spring barley, namely, i) directional selection for approximately 14% of total genetic variation of the population in the last approximately 50 yr and ii) highly uneven genomic distribution of genetic diversity. Association analysis of the phenotypic and genotypic data identified multiple loci affecting the traits investigated, some of which co-map with selected regions. Collectively, these data show that the genetic makeup of European two-row spring barley is evolving under breeder selection, with signs of extinction of diversity in some genomic regions, suggesting that “breeding the best with the best” is leading towards fixation of some breeder targets. Nevertheless, modern germplasm also retains many regions of high diversity, suggesting that site-specific genetic approaches for allele identification and crop improvement such as association genetics are likely to be successful.