A proximity-based method to identify genomic regions correlated with a continuously varying environmental variable.
A proximity-based method to identify genomic regions correlated with a continuously varying environmental variable.
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DOI：
10.4137/ebo.s10211
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Gasparini M
中科院分区：
文献类型：
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作者：
Di Gaetano C;Matullo G;Piazza A;Ursino M;Gasparini M
人类基因组中显示空间模式并与不同环境决定因素极端相关的标记的知识对于理解影响我们物种生物进化的因素发挥着重要作用。我们使用来自人类基因组多样性面板 (HGDP-CEPH -CEPH) 数据集的超过 50 万个单核苷酸多态性 (SNP) 的基因型数据，并计算了绝对纬度与每个 SNP 的两个等位基因频率之一之间的 Spearman 相关性。我们选择了相关系数位于分布尾部上部 1% 内的 SNP。然后，我们使用重要变异之间的接近度标准来关注在基因组的一部分上显示连续信号的 DNA 区域。根据外部信息和基因组注释，我们证明大多数信号最强的区域也具有生物学相关性。我们相信，与现有文献相比，这种邻近性要求为我们的新方法增加了优势，突出了与体型或形状、人类身高、头发颜色和精神分裂症相关的几个基因（例如 DTNB、DOT1L、TPCN2、RELN、MSRA、NRG3）。我们的方法通常可以应用于多态性频率和连续变化的环境变量之间关联的任何测量。
Knowledge of markers in the human genome which show spatial patterns and display extreme correlation with different environmental determinants play an important role in understanding the factors which affect the biological evolution of our species. We used the genotype data of more than half a million single nucleotide polymorphisms (SNPs) from the data set Human Genome Diversity Panel (HGDP-CEPH -CEPH) and we calculated Spearman’s correlation between absolute latitude and one of the two allele frequencies of each SNP. We selected SNPs with a correlation coefficient within the upper 1% tail of the distribution. We then used a criterion of proximity between significant variants to focus on DNA regions showing a continuous signal over a portion of the genome. Based on external information and genome annotations, we demonstrated that most regions with the strongest signals also have biological relevance. We believe this proximity requirement adds an edge to our novel method compared to the existing literature, highlighting several genes (for example DTNB, DOT1L, TPCN2, RELN, MSRA, NRG3) related to body size or shape, human height, hair color, and schizophrenia. Our approach can be applied generally to any measure of association between polymorphic frequencies and continuously varying environmental variables.