Predicting tissue-specific enhancers in the human genome
Predicting tissue-specific enhancers in the human genome
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DOI：
10.1101/gr.5972507
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发表时间：
2007-02-01
期刊：
影响因子：
7
通讯作者：
Ovcharenko, Ivan
中科院分区：
文献类型：
--
作者：
Pennacchio, Len A.;Loots, Gabriela G.;Ovcharenko, Ivan
确定转录调控信号如何在脊椎动物基因组中编码对于理解多细胞复杂性的起源至关重要;然而脊椎动物基因调控的遗传密码仍然知之甚少。为了阐明这一密码，我们协同结合全基因组基因表达谱分析、脊椎动物基因组比较和转录因子结合位点分析，以确定人类基因组中候选组织特异性增强子的序列特征。我们将这种策略应用于79种人体组织的基于微阵列的基因表达谱，并确定了7187个候选增强子，这些增强子定义了它们的侧翼基因表达，其中大多数位于已知启动子之外。我们交叉验证了这种方法从头预测组织特异性基因表达的能力，并在79种可用的人体组织中的57种中证实了其可靠性，增强子识别的平均精度为32%至63%，灵敏度为47%。我们使用这种方法识别的序列特征，成功地将组织特异性预测分配给人类基因组中类似于328，000个人-小鼠保守非编码元件。通过将这些全基因组预测与转基因小鼠体内验证的增强子数据集重叠，我们能够以28%的灵敏度和50%的精确度确认我们的结果。这些结果表明，互补的基因组数据集相结合的力量作为一个初始的计算进军到脊椎动物组织特异性基因调控的全局视图。
Determining how transcriptional regulatory signals are encoded in vertebrate genomes is essential for understanding the origins of multicellular complexity; yet the genetic code of vertebrate gene regulation remains poorly understood. In an attempt to elucidate this code, we synergistically combined genome-wide gene-expression profiling, vertebrate genome comparisons, and transcription factor binding-site analysis to define sequence signatures characteristic of candidate tissue-specific enhancers in the human genome. We applied this strategy to microarray-based gene expression profiles from 79 human tissues and identified 7187 candidate enhancers that defined their flanking gene expression, the majority of which were located outside of known promoters. We cross-validated this method for its ability to de novo predict tissue-specific gene expression and confirmed its reliability in 57 of the 79 available human tissues, with an average precision in enhancer recognition ranging from 32% to 63% and a sensitivity of 47%. We used the sequence signatures identified by this approach to successfully assign tissue-specific predictions to similar to 328,000 human-mouse conserved noncoding elements in the human genome. By overlapping these genome-wide predictions with a data set of enhancers validated in vivo, in transgenic mice, we were able to confirm our results with a 28% sensitivity and 50% precision. These results indicate the power of combining complementary genomic data sets as an initial computational foray into a global view of tissue-specific gene regulation in vertebrates.