4.5 Article

Meta-analysis of results from quantitative trait loci mapping studies on pig chromosome 4

期刊

ANIMAL GENETICS
卷 42, 期 3, 页码 280-292

出版社

WILEY
DOI: 10.1111/j.1365-2052.2010.02145.x

关键词

meta-analysis; pig; quantitative trait loci

资金

  1. Brazilian National Council of Research (CNPq)
  2. Minas Gerais State Research Foundation (Fapemig)
  3. European Commission [KBBE-211708]
  4. Capes/Brazilian Department of Education

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Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this study, we performed a meta-analysis of QTL on chromosome 4 in pig, using data from 25 separate experiments. First, a meta-analysis was performed for individual traits: average daily gain and backfat thickness. Second, a meta-analysis was performed for the QTL of three traits affecting loin yield: loin eye area, carcass length and loin meat weight. Third, 78 QTL were selected from 20 traits that could be assigned to one of three broad categories: carcass, fatness or growth traits. For each analysis, the number of identified meta-QTL was smaller than the number of initial QTL. The reduction in the number of QTL ranged from 71% to 86% compared to the total number before the meta-analysis. In addition, the meta-analysis reduced the QTL confidence intervals by as much as 85% compared to individual QTL estimates. The reduction in the confidence interval was greater when a large number of independent QTL was included in the meta-analysis. Meta-QTL related to growth and fatness were found in the same region as the FAT1 region. Results indicate that the meta-analysis is an efficient strategy to estimate the number and refine the positions of QTL when QTL estimates are available from multiple populations and experiments. This strategy can be used to better target further studies such as the selection of candidate genes related to trait variation.

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