ENHANCED LINKAGE MAPS FROM FAMILY-BASED GENETICS STUDIES

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目及 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 减数分裂连锁图谱是进行疾病基因定位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仅使用一小部分谱系来构建，因此图谱距离的估计具有较宽的置信区间。不正确的标记顺序和图距会对连锁分析产生深远的影响。使用性别平均图而不是性别特异性图会使lod值偏高，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，因此显然需要更精确和准确的性别特异性遗传图谱。除了利用基因型数据进行连锁分析外，不可能通过任何手段获得减数分裂图距的准确估计。我们建议建立改进的高度精确的性别特异性连锁图谱，利用成千上万的个人谁以前已经基因分型。在过滤掉明显的关系和基因型错误后，我们将采用适当的方法对基因分型错误进行建模。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型数据来研究重组如何在种族之间变化。NHLBI哺乳动物基因分型服务生成的基因型正是生成更准确图谱所需的数据类型。这些数据集包含超过3，400个系谱，与用于构建当前全基因组连锁图谱的8个CEPH家族中所包含的信息相比，信息增加了100倍以上。我们的新地图将由MAP-O-MAT连锁映射服务器公开提供。在未来，我们预计将扩大我们的研究，纳入其他基因分型中心，如遗传疾病研究中心（CIDR）的基因型数据。当前图谱中的不准确性可能导致误导性结果，并且可能是令人不安的原因之一，即很少有基因被明确鉴定出导致哮喘、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。我们建议构建的更精确的地图将提高许多正在进行的新疾病研究的能力和价值。

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.