Microarrays and beyond: What potential do current and future genomics tools have for breeders?

ABSTRACT One of the most exciting tools from genomics is the ability to obtain a whole-genome snapshot of gene expression. This is typically called a microarray analysis, because probes for the genes of interest, which can run into the thousands, are spotted in a very small array on a glass slide or some other substrate. The resulting array is often called a gene chip, or simply a chip, in the case of short oligo arrays, or slides in the case of cDNA or long oligo arrays. Microarrays offer the awesome potential of simultaneously examining the level of expression, where expression is intended to measure the standing amount of mRNA, for all of the genes in a genome. Given this potential, it is not surprising that microarrays have attracted a great deal of attention from animal geneticists and breeders. The purpose of this review is to provide a brief, yet critical, overview of some of the potential uses of such whole-genome expression studies in applied animal breeding and to speculate about what additional forthcoming tools might be of use.

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© 2004, by the American Society of Animal Science. All rights reserved.

J. Anim. Sci. 2004. 82(E. Suppl.):E292-E299

Implications

Modern molecular biology and genomics have certainly forever changed the face of biology, and animal breeding is no exception. It is imperative, however, to not simply rush blindly forward with the implementation of new technologies but rather to critically assess which tools are likely to be of significant benefit for improving breeding. The lessons from the initial heady days of quantitative trait loci mapping are quite informative, namely that although the promise of these approaches is extremely exciting, their application is very often more problematic than initially envisioned. The use of expression arrays and the potential future use of information on gene networks should heed these lessons. Selection based solely on phenotypic information still performs favorably, and any movement toward a more genomics-based approach for any particular selection problem should first consider a serious cost-benefit analysis.