ENHANCED LINKAGE MAPS FROM FAMILY-BASED GENETICS STUDIES

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 减数分裂连锁图谱是定位疾病基因的连锁和连锁不平衡研究的基础。尽管精确的图谱很重要，但现有的全基因组连锁图谱只使用了一小部分家系，因此对图谱距离的估计有很大的可信区间。不正确的标记顺序和图谱距离会对连锁分析产生深远的影响。使用按性别平均的地图而不是按性别划分的地图会使LOD得分偏高，从而显著增加假阳性率。由于跟踪许多假阳性结果的成本非常高，显然需要更精确和准确的性别特定基因图谱。除了利用基因数据进行连锁分析外，无法通过任何方法获得减数分裂图谱距离的准确估计。我们建议利用数以千计的先前进行过基因分型的个体，建立改进的、高度精确的性别特定连锁图谱。在过滤掉明显的亲缘关系和基因错误之后，我们将采用正确建模基因分型错误的方法。除了为科学界创建精确的图谱外，我们还建议使用这些基因数据来研究重组在不同种族之间的差异。NHLBI哺乳动物基因分型服务生成的基因类型正是制作更准确地图所需的数据类型。这些数据收集包含3,400多个家系，与用于构建当前全基因组连锁图谱的8个CEPH家族中包含的信息相比，信息量增加了100倍以上。我们的新地图将由MAP-O-MAT链接地图服务器公开提供。在未来，我们预计将扩大我们的研究范围，纳入其他基因分型中心的基因数据，如遗传病研究中心(CIDR)。目前图谱中存在的不准确可能会导致误导性的结果，这可能是令人失望的原因之一，即确定导致哮喘、心血管疾病、高血压、高胆固醇血症、糖尿病、肥胖和癌症等复杂疾病的基因少之又少。我们提议构建的更精确的地图将提高许多正在进行的和新的疾病研究的力量和价值。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Meiotic linkage maps are the foundation of both linkage and linkage disequilibrium studies for mapping disease genes. Despite the importance of precise maps, existing genome-wide linkage maps were built using only a small collection of pedigrees, and so have wide confidence intervals surrounding estimates of map distance. Incorrect marker order and map distances can have a profound effect on linkage analyses. Using a sex-averaged map instead of a sex-specific map biases the lod scores upward, markedly increasing the false positive rate. Since it is very costly to follow-up many false-positive results, there is a clear need for more precise and accurate sex-specific genetic maps. Accurate estimates of meiotic map distance cannot be obtained by any means other than by linkage analysis using genotype data. We propose to build improved highly-precise sex-specific linkage maps utilizing thousands of individuals who have previously been genotyped. After filtering out obvious relationship and genotype errors, we will incorporate methods that properly model for genotyping errors. In addition to creating precise maps for the scientific community, we also propose to use these genotype data to study how recombination may vary between ethnic groups. The genotypes generated by the NHLBI Mammalian Genotyping Service are precisely the type of data required to produce more accurate maps. These data collections contain over 3,400 pedigrees with more than a 100-fold increase in information compared to that contained in the 8 CEPH families that have been used to construct current genome-wide linkage maps. Our new maps will be made publicly available by the MAP-O-MAT linkage mapping server. In the future, we anticipate broadening our study to incorporate genotype data from additional genotyping centers such as the Center for Inherited Disease Research (CIDR). The inaccuracies present in current maps can contribute to misleading results, and may be one of the reasons that disappointingly few genes have been definitively identified that contribute to such complex diseases as asthma, cardiovascular disease, hypertension, hypercholesterolemia, diabetes, obesity, and cancer. The more precise maps that we propose to construct will improve the power and value of many ongoing and new disease studies.