4.5 Article

Exploring and Exploiting Genetic Variation from Unadapted Sorghum Germplasm in a Breeding Program

Journal

CROP SCIENCE
Volume 51, Issue 4, Pages 1444-1457

Publisher

WILEY
DOI: 10.2135/cropsci2010.06.0326

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Funding

  1. Queensland Government
  2. Grains Research and Development Corporation (GRDC)

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Loss of genetic diversity in elite breeding populations is often identified as a potential impediment to future genetic gain. The use of diverse unadapted germplasm in breeding has been suggested as one way of combating this problem but often proves impractical, due to the poor performance of progeny produced by crosses between adapted and unadapted parent lines. This study evaluates the effectiveness of a breeding method aimed at utilizing unadapted sorghum [Sorghum bicolor (L.) Moench] germplasm. The method involves producing large BC 1 F 1 populations, using a single elite line as the recurrent parent, and then selecting the resulting progeny for key adaptive traits (e.g., height and flowering time). Populations of 30 to 90 BC 1 F 4 lines derived from 56 unadapted parents were then evaluated in hybrid combination in 21 trials over a 4-yr period. The unadapted sources included lines with geographic or racial diversity, phenotypic diversity for key traits, elite lines from breeding programs in other countries, and cross-compatible wild species. Despite strong selection for acceptable height and maturity, considerable genetic variation for grain yield was retained in the populations, with molecular marker analysis indicating an average of 22% of the genome being retained in each line as compared with a theoretical 25% in the absence of selection. In all cases progeny were identified in each population that performed significantly better than the recurrent parent hybrid for grain yield, and in some cases specific adaptation of particular populations was observed. The method we used proved to be an effective way to introduce new alleles from unadapted sorghum germplasm into elite breeding material. The potential of the populations as a resource for nested association mapping to elucidate the architecture of complex traits is discussed.

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