Enhanced linkage maps from family-based genetics studies

描述(由申请人提供)： 减数分裂连锁图谱是连锁和连锁的基础 疾病基因图谱的不平衡研究。尽管重要的是 精确的图谱，现有的全基因组连锁图谱只用了一小部分 家系的集合，因此周围有很大的可信区间 地图距离的估计。标记顺序和地图距离可能不正确 对连锁分析产生了深远的影响。使用按性别平均的地图而不是 特定性别的地图使LOD得分上升，显著增加了错误 阳性率。由于跟踪许多假阳性是非常昂贵的 结果，显然需要更精确和准确的性别区分 基因图谱。无法获得减数分裂图谱距离的准确估计 除了通过使用基因数据的连锁分析以外的任何手段。我们建议 利用数千份改良的高度精确的性别特定连锁图谱 之前已经进行过基因分型的个体。过滤掉后 明显的关系和基因错误，我们将结合 为基因分型错误建立适当的模型。除了创建精确的地图之外 对于科学界，我们还建议使用这些基因数据来 研究重组在不同种族群体之间的差异。基因分型 由NHLBI哺乳动物基因分型服务产生的正是 制作更准确的地图所需的数据。这些数据集合包含 超过3,400个家系，信息量增加了100倍以上 相比于8个CEPH家族中包含的 构建当前的全基因组连锁图谱。我们的新地图将会制作 和我们研究中的基因数据将通过以下方式获得 MAP-0-MAT联动映射服务器。在未来，我们预计将扩大 我们的研究纳入了来自其他基因分型中心的基因数据，如 作为遗传病研究中心(CIDR)。存在的不准确之处 在当前地图中，可能会导致误导性的结果，并且可能是 令人失望的是，几乎没有基因被确定为 导致哮喘、心血管疾病等复杂疾病， 高血压、高胆固醇血症、糖尿病、肥胖和癌症。越多 我们建议构建的精确地图将提高 许多正在进行的和新的疾病研究。

DESCRIPTION (provided by applicant): 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 1 00-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 and the genotype data from our study will be accessible by the MAP-0-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.