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 疾病基因定位的不平衡研究。尽管重要的是 精确的地图，现有的全基因组连锁图是用一个小的 家系的集合，因此具有宽的置信区间， 地图距离的估计。错误的标记顺序和标测图距离可能导致 对连锁分析产生了深远的影响。使用性别平均图而不是 性别特异性图谱使LOD值偏高， 阳性率由于对许多假阳性进行后续检查的成本很高， 结果，显然需要更精确和准确的性别特异性 基因图谱减数分裂图距离的精确估计无法获得 通过除使用基因型数据的连锁分析之外的任何手段。我们提出 利用上千个基因组构建高精确度的性别特异性连锁图谱， 已经被基因分型的个体。过滤掉 明显的关系和基因型错误，我们将纳入的方法， 对基因分型错误进行适当建模。除了绘制精确的地图 对于科学界，我们还建议使用这些基因型数据， 研究不同种族之间的重组可能会有什么不同。基因型 NHLBI哺乳动物基因分型服务产生的正是这种类型的 制作更精确的地图所需的数据。这些数据集包含 超过3,400个家系，信息量增加了100倍以上 与8个CEPH家族中所包含的相比， 构建当前的全基因组连锁图谱。我们的新地图将由 我们的研究的基因型数据将通过以下方式获得： MAP-0-MAT链接映射服务器。在未来，我们预计扩大 我们的研究纳入了来自其他基因分型中心的基因型数据， 遗传疾病研究中心（CIDR）存在的不准确性 在当前的地图可以有助于误导的结果，并可能是其中之一， 令人沮丧的是，很少有基因被明确确定， 会导致哮喘、心血管疾病等复杂疾病 高血压、高胆固醇血症、糖尿病、肥胖症和癌症。越 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.