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Marker-Assisted Selection for Neutral Detergent Fiber in Smooth Bromegrass


This article in CS

  1. Vol. 46 No. 1, p. 303-311
    Received: Feb 17, 2005

    * Corresponding author(s): mdcasler@wisc.edu
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  1. C. Stendala,
  2. M. D. Casler *b and
  3. G. Jungc
  1. a Dep. of Agronomy, Univ. of Wisconsin, Madison, WI 53706-1597
    b USDA-ARS, U.S. Dairy Forage Research Center, 1925 Linden Dr. West, Madison, WI 53706-1108
    c Dep. of Plant Pathology, Univ. of Wisconsin, Madison, WI 53706


Neutral detergent fiber (NDF) is the most effective and measurable predictor of animal intake. About 70% of the variation in animal production is attributed to differences in intake potential of livestock feed. Sixteen molecular markers associated with NDF in four divergently selected smooth bromegrass (Bromus inermis L.) populations were selected from a previous study for further examination for possible use in a marker-assisted selection (MAS) breeding program. The objectives of this experiment were to confirm the association of previously identified markers to NDF concentration in smooth bromegrass populations and to develop a marker-based selection index. Marker and NDF data were analyzed and marker indices were constructed using data from the current and previous studies. Index scores were used to rank genotypes and create selection differentials on the basis of phenotypic data. Marker frequencies calculated on a subpopulation basis between the previous and current studies were highly unrepeatable. Nevertheless, of the 14 groups of marker indices, seven of which accounted for pedigree structure, one marker index appears to provide the greatest potential for use in MAS to reduce NDF across all four populations of smooth bromegrass. Where pedigree structure is known, selections made using this index would lead to the largest expected response per year and eliminate the need to collect phenotypic data for as long as linkage relationships remain intact. Where pedigree structure is unknown, a general marker index may be used, or phenotypic data can be utilized along with a marker index. However, inclusion of phenotypic data would necessitate a cost–benefit analysis.

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