Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons
- PMID: 15471812
- DOI: 10.2527/2004.8213_supplE313x
Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons
Abstract
During the past few decades, advances in molecular genetics have led to the identification of multiple genes or genetic markers associated with genes that affect traits of interest in livestock, including genes for single-gene traits and QTL or genomic regions that affect quantitative traits. This has provided opportunities to enhance response to selection, in particular for traits that are difficult to improve by conventional selection (low heritability or traits for which measurement of phenotype is difficult, expensive, only possible late in life, or not possible on selection candidates). Examples of genetic tests that are available to or used in industry programs are documented and classified into causative mutations (direct markers), linked markers in population-wide linkage disequilibrium with the QTL (LD markers), and linked markers in population-wide equilibrium with the QTL (LE markers). In general, although molecular genetic information has been used in industry programs for several decades and is growing, the extent of use has not lived up to initial expectations. Most applications to date have been integrated in existing programs on an ad hoc basis. Direct markers are preferred for effective implementation of marker-assisted selection, followed by LD and LE markers, the latter requiring within-family analysis and selection. Ease of application and potential for extra-genetic gain is greatest for direct markers, followed by LD markers, but is antagonistic to ease of detection, which is greatest for LE markers. Although the success of these applications is difficult to assess, several have been hampered by logistical requirements, which are substantial, in particular for LE markers. Opportunities for the use of molecular information exist, but their successful implementation requires a comprehensive integrated strategy that is closely aligned with business goals. The current attitude toward marker-assisted selection is therefore one of cautious optimism.
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