Problems in Population Genetics

索耶0107420 研究人员研究了利用比对的DNA或蛋白质序列中包含的信息来估计选择支持或反对特定遗传位点新突变的平均遗传变异率的方法。 如果估计的选择量是显著负的，这表明该区域是不稳定的选择，并可能具有重要的生物功能。 如果估计的平均选择量是正的，那么这个区域的新变异就更受欢迎，这在某些免疫系统基因中很常见。 模型，允许随机变化的数量选择网站也被认为是。 所研究的方法在计算上易于实现，并且很容易获得显著性水平，但是假设多态位点之间的统计独立性，而不是更常见的紧密连锁假设。 研究表明，在许多情况下，短片段基因的转换和重组比点突变的发生率更高，因此紧密联系并不总是一个合理的假设。 模拟进行测试的假设，小到中等数量的基因转换和重组是足以保证站点之间足够的独立性，使建议的估计willhave理想的统计特性。 该模型应用于公共数据库中的比对序列。 它们也被应用到人类SNP数据集，其中站点独立性的假设更清晰。 生物学的最新进展已经提供了大量关于人类基因组和其他物种基因组的数据。 用于理解这些数据的重要性，特别是个人之间数据差异的重要性的工具已经落后。 一个问题是，在特定的基因位点（或DNA片段）上的新的遗传变异是否在过去的平均水平上受到青睐，是否使它们的拥有者变得不那么健康，或者是否对具有这些DNA变异的个体的命运产生了本质上相同的影响。 提出了一种简单的计算方法来确定这三种情况中的哪一种适用于特定的遗传位点。这些测试是基于该位点上几个个体的DNA中变异位点的构型。 这个测试的结果可以提供关于这段DNA功能的信息。 它们也可以提供关于一个特定基因是如何受到进化影响的信息。来自相关生物物种的信息可以提供进一步的信息。 所提出的方法的困难在于，它们假设遗传位点的不同部分是近似独立地进化的。 对于某些遗传数据（例如，SNP的“单核苷酸多态性”数据），这通常可以假设。 测试了所提出的方法对非SNP数据的独立性假设的敏感性。

Sawyer0107420 The investigator studies ways to estimate the average amountof selection for or against new mutations at a particular geneticlocus using information contained in aligned DNA or proteinsequences. If the estimated amount of selection is significantlynegative, this is an indication that the region is understabilizing selection and may have an important biologicalfunction. If the estimated average amount of selection ispositive, then new variants in this region are favored, as iscommon for some immune system genes. Models that allow randomvariation of the amounts of selection over sites are alsoconsidered. The methods studied are computationally easy to carryout and have easily obtained significance levels, but assumestatistical independence between polymorphic sites instead of themore usual assumption of tight linkage. Studies have shown inmany cases that short-segment gene conversion and recombinationact at a greater rate than point mutation, so that tight linkageis not always a reasonable assumption. Simulations are carriedout to test the assumption that small to moderate amounts of geneconversion and recombination are sufficient to guarantee enoughindependence between sites so that the proposed estimators willhave desirable statistical properties. The models are applied toaligned sequences from public databases. They are also applied tohuman SNP datasets, for which the assumption of sitewiseindependence is clearer. Recent advances in biology have made a vast amount of dataavailable about the human genome and about the genomes of otherspecies. Tools for understanding the significance of this data,and in particular the significance of variation in this databetween individuals, have lagged behind. One question is whethernew genetic variants at a particular genetic locus (or segment ofDNA) have been favored on the average in the past, have renderedtheir owners less fit, or have had essentially the same effect onthe fate of individuals with those DNA variants. Tests areproposed that give a computationally easy way of determiningwhich of these three cases applies at a particular genetic locus.These tests are based on the configurations of variant sites inDNA from several individuals at that locus. The results of thistest can give information about the function of this stretch ofDNA. They can also give information about how a particular geneis affected by or is currently being affected by evolution.Information from related biological species can give furtherinformation. The difficulty of the proposed methods is that theyassume that different portions of the genetic locus are evolvingapproximately independently. For some genetic data (for example,SNP for "single-nucleotide polymorphism" data) this can generallybe assumed. The sensitivity of the proposed methods to thisindependence assumption for non-SNP data is tested.