Ron M, Weller J I
Institute of Animal Sciences, ARO, The Volcani Center, Bet Dagan 50250, Israel.
Anim Genet. 2007 Oct;38(5):429-39. doi: 10.1111/j.1365-2052.2007.01640.x. Epub 2007 Aug 14.
Many quantitative trait loci (QTL) affecting economic traits in livestock have now been identified. However, the confidence interval (CI) of individual QTL as determined by linkage analysis often spans tens of map units, containing hundreds of genes. Linkage disequilibrium (LD) mapping can reduce the CI to individual map units, but this reduced interval will still contain tens of genes. Methods suitable for model animals to find and validate specific quantitative trait nucleotides (QTN) underlying the QTL cannot be easily applied to livestock species because of their long generation intervals, the cost of maintaining each animal and the difficulty of producing transgenics or 'knock-outs'. Considering these limitations, we review successful approaches for identifying QTN in livestock and outline a schematic strategy for QTN determination and verification. In addition to linkage and LD mapping, the methods include positional cloning, selection of candidate genes, DNA sequencing and statistical analyses. Concordance determination and functional assays are the critical tests for validation of a QTN; we provide a generalized formula for the probability of concordance by chance. Three genes that meet the burden of proof for QTN identification--DGAT1 in cattle, IGF2 in swine and GDF8 in sheep--are discussed in detail. The genetic and economic ramifications of identified QTN and the horizon for selection and introgression are also considered.
目前已鉴定出许多影响家畜经济性状的数量性状基因座(QTL)。然而,通过连锁分析确定的单个QTL的置信区间(CI)通常跨越数十个图谱单位,包含数百个基因。连锁不平衡(LD)作图可将CI缩小至单个图谱单位,但这个缩小后的区间仍将包含数十个基因。由于家畜世代间隔长、饲养每头动物成本高以及生产转基因或“基因敲除”动物困难,适用于模式动物寻找和验证QTL潜在特定数量性状核苷酸(QTN)的方法不易应用于家畜物种。考虑到这些局限性,我们综述了在家畜中鉴定QTN的成功方法,并概述了QTN确定和验证的示意图策略。除了连锁和LD作图外,这些方法还包括定位克隆、候选基因选择、DNA测序和统计分析。一致性测定和功能分析是验证QTN的关键测试;我们提供了一个关于偶然一致性概率的通用公式。详细讨论了三个符合QTN鉴定证据标准的基因——牛的DGAT1、猪的IGF2和绵羊的GDF8。还考虑了已鉴定QTN的遗传和经济影响以及选择和导入的前景。