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This article in CS

  1. Vol. 37 No. 3, p. 691-697
     
    Received: July 15, 1996
    Published: May, 1997


    * Corresponding author(s): mes12@cornell.edu
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doi:10.2135/cropsci1997.0011183X003700030001x

Direct Classification and Selection of Superior Alleles for Crop Improvement

  1. Mark E. Sorrells  and
  2. William A. Wilson
  1. Dep. of Plant Breeding and Biometry, Cornell Univ., Ithaca, NY 14853

Abstract

Abstract

The use of conventional breeding methods has resulted in consistent crop improvement within the cultivated gene pool by producing genotypes with new combinations of alleles that produce better phenotypes than either of the parents (transgressive segregation). Biotechnology has provided new methods to generate, identify, characterize, and manipulate genetic variation. Among these methods, marker assisted selection (MAS) with DNA markers has been applied in plant improvement programs. However, MAS is limited by the effort required to generate information about map location and breeding value of genes controlling important traits. Comparative genetic analysis across the domesticated grasses facilitates the identification and localization of gene sequences controlling specific traits of interest. The emerging databases of gene sequences will allow directed discovery of genes in higher plants and classification of alleles present within breeding germplasm. Identification of the genes controlling a trait and knowledge of their DNA sequence would facilitate classification of variation in the germplasm pool based on gene fingerprinting or characterization of variation in key DNA sequences. Classification of sequence variants at a targeted locus would substantially reduce the amount of work required to determine their relative breeding value and lead to the identification of superior alleles. Combining direct allele selection (DAS) with conventional selection, would allow more rapid and precise improvement of populations and breeding lines. Limitations of current technology can be minimized by transfer of genetic information across species, identification of highly variable genes, and focusing on the most important genes and traits for the species of interest.

Contribution from the Dep. of Plant Breeding and Biometry, Cornell Univ. Paper no. 831 of the Plant Breeding series. Research supported by Hatch project nos. 419 and 418 USDA Plant Genome National Research Initiative (USDA NRI Grant No. 94-37300-0324, subcontract number 92-G0161-Cornell of USDA NRI Grant No. 92-37300-7550) and The New York State Center for Advanced Technology in Biotechnology Program.

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