Problems in Population Genetics

Sawyer0107420研究人员研究如何使用比对的DNA或蛋白质序列中包含的信息来估计在特定基因位点上支持或反对新突变的平均选择数量。如果估计的选择数量显著为负，这表明该区域选择不稳定，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种就会受到青睐，这在一些免疫系统基因中很常见。还考虑了允许选择地点的数量随机变化的模型。所研究的方法在计算上很容易实现，并且很容易获得显著水平，但假设多态位点之间是统计上的独立，而不是通常的紧密连锁的假设。研究表明，在许多情况下，短片段基因转化和重组的速度比点突变更快，因此紧密联系并不总是一个合理的假设。进行了模拟，以检验这样的假设，即少量到中等数量的基因转换和重组足以保证站点之间足够的独立性，从而使所提出的估计器具有理想的统计特性。这些模型被应用于公共数据库中的比对序列。它们也适用于人类SNP数据集，对于这些数据集，站点独立性的假设更加明确。生物学的最新进展使有关人类基因组和其他物种基因组的大量数据变得可用。理解这些数据的重要性的工具，特别是这个数据库在个人之间的差异的重要性，已经落后。一个问题是，特定遗传位点(或DNA片段)上的新遗传变异是否在过去平均而言受到了青睐，让它们的所有者变得不那么合适，或者对拥有这些DNA变异的个体的命运产生了基本上相同的影响。测试被提出，给出了一种计算简单的方法来确定这三种情况中的哪一种适用于特定的遗传基因位点。这些测试基于该基因座上几个个体的DNA变异位点的配置。这项测试的结果可以提供关于这段DNA的功能的信息。它们还可以提供关于特定基因如何受到进化影响或当前正在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基因座的不同部分是近似独立地进化的。对于一些遗传数据(例如，“单核苷酸多态”数据的SNP)，这通常可以被假定。对于非SNP数据，检验了所提方法对这种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.