Boitard Simon, Abdallah Jihad, de Rochambeau Hubert, Cierco-Ayrolles Christine, Mangin Brigitte
Unité de Biométrie et Intelligence Artificielle, Institut National de la Recherche Agronomique, BP 52627, 31326 Castanet-Tolosan Cedex, France.
BMC Genomics. 2006 Mar 16;7:54. doi: 10.1186/1471-2164-7-54.
For many years gene mapping studies have been performed through linkage analyses based on pedigree data. Recently, linkage disequilibrium methods based on unrelated individuals have been advocated as powerful tools to refine estimates of gene location. Many strategies have been proposed to deal with simply inherited disease traits. However, locating quantitative trait loci is statistically more challenging and considerable research is needed to provide robust and computationally efficient methods.
Under a three-locus Wright-Fisher model, we derived approximate expressions for the expected haplotype frequencies in a population. We considered haplotypes comprising one trait locus and two flanking markers. Using these theoretical expressions, we built a likelihood-maximization method, called HAPim, for estimating the location of a quantitative trait locus. For each postulated position, the method only requires information from the two flanking markers. Over a wide range of simulation scenarios it was found to be more accurate than a two-marker composite likelihood method. It also performed as well as identity by descent methods, whilst being valuable in a wider range of populations.
Our method makes efficient use of marker information, and can be valuable for fine mapping purposes. Its performance is increased if multiallelic markers are available. Several improvements can be developed to account for more complex evolution scenarios or provide robust confidence intervals for the location estimates.
多年来,基因定位研究一直通过基于家系数据的连锁分析来进行。最近,基于无关个体的连锁不平衡方法被倡导为细化基因位置估计的强大工具。已经提出了许多策略来处理简单遗传的疾病性状。然而,定位数量性状基因座在统计学上更具挑战性,需要大量研究来提供强大且计算高效的方法。
在一个三位点的赖特 - 费希尔模型下,我们推导了群体中预期单倍型频率的近似表达式。我们考虑了包含一个性状基因座和两个侧翼标记的单倍型。利用这些理论表达式,我们构建了一种称为HAPim的似然最大化方法,用于估计数量性状基因座的位置。对于每个假定位置,该方法仅需要来自两个侧翼标记的信息。在广泛的模拟场景中,发现它比双标记复合似然方法更准确。它的表现也与基于同源性的方法相当,同时在更广泛的群体中具有价值。
我们的方法有效利用了标记信息,对于精细定位目的可能很有价值。如果有多等位基因标记可用,其性能会提高。可以进行一些改进以考虑更复杂的进化场景或为位置估计提供稳健的置信区间。