Genetic analysis of segregating recessive variation

项目摘要/摘要 大多数群体都含有大量的低频隐性等位基因，很少见 暴露为纯合子，为理解的努力创造了巨大的统计挑战 他们的影响。这个问题需要一个实验上易于处理的隔离模型。 隐性变异。模型应该包括稀有等位基因转移到更容易处理的 频率、完全测序的基因组和高度可复制的二倍体基因型 在纯合性的位置和程度上有所不同。这份提案回答了这一问题 通过解剖有害隐性变异的遗传基础来呼吁在一个样本 从线虫自然种群中提取的基因组。29、有义务 异交线虫与两性实验室模式C密切相关。 优雅女装。这些线虫在基因研究方面与线虫有共同的特殊优点， 包括基因组紧凑、世代时间短、繁殖力高和 用于冷冻保存。与线虫不同的是，这一物种拥有大量的 分离隐性变异。这项提案的目标包括创建一个 有害隐性等位基因的永久作图资源、表型 一系列纯合子的生殖适合度，并构建预测性 将纯合子的表型效应与特定分子联系起来的模型 分离等位基因的特征。 低频隐性等位基因的更精确的分子特征将是 在从序列定义的变异中推断遗传风险方面具有巨大的价值。会是 在个体表型预测方面特别有价值，这是遗传研究的关键目标 医药。

Project Summary/Abstract Most populations harbor enormous numbers of low-frequency recessive alleles, rarely exposed as homozygotes, creating great statistical challenges for efforts to understand their effects. The problem calls for an experimentally tractable model of segregating recessive variation. The model should include rare alleles shifted to more tractable frequencies, completely sequenced genomes, and highly replicable diploid genotypes that vary in the location and extent of their homozygosity. This proposal answers that call by dissecting the genetic basis of deleterious recessive variation in a sample of genomes extracted from a natural population of Caenorhabditis sp. 29, obligate outcrossing nematodes closely related to the hermaphroditic laboratory model C. elegans. These nematodes share with C. elegans exceptional virtues for genetic study, including a compact genome, a short generation time, high fecundity, and the capacity for cryopreservation. Unlike C. elegans, this species harbors a substantial load of segregating recessive variation. The aims of this proposal involve the creation of a permanent resource for mapping the deleterious recessive alleles, the phenotyping of reproductive fitness across a range of homozygosities, and the construction of predictive models that connect the phenotypic effects of homozygosity to specific molecular features of the segregating alleles. A more precise molecular characterization of low-frequency recessive alleles will be of great value in inferring genetic risk from sequence-defined variants. It will be particularly valuable in individual phenotypic prediction, a key goal for genetic medicine.