Defining Functional Genic Regions in the Human Genome through Integration of Biochemical, Evolutionary, and Genetic Evidence
Defining Functional Genic Regions in the Human Genome through Integration of Biochemical, Evolutionary, and Genetic Evidence
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DOI：
10.1093/molbev/msx101
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发表时间：
2017-07
影响因子：
10.7
通讯作者：
Z. Tsai;J. P. Lloyd;Shin-Han Shiu
中科院分区：
文献类型：
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作者：
Z. Tsai;J. P. Lloyd;Shin-Han Shiu
人类基因组由大量具有广泛生物化学活性但功能未知的DNA组成。特别地，已经确定转录活性不限于已知基因。然而，这种基因间转录是否代表具有功能意义或噪音的活性正在争论中，突出了对定义功能基因组区域的有效方法的需要。此外，这些发现提出了一个问题，即基因组区域是否可以仅仅基于生物化学活性的存在而被定义为功能性的，而不考虑进化（保守）和遗传（突变的影响）证据。在这里，建立了整合遗传、进化和生化证据的计算模型，为人类蛋白质编码和RNA基因提供了可靠的预测。重要的是，除了序列保守性，生物化学特征允许在强纯化选择下用表型证据准确预测基因序列，这表明它们可以用作选择的替代措施。此外，18.5%的注释的非编码RNA表现出更高程度的相似性表型基因，因此，可能是功能性的。然而，64.5%的非编码RNA似乎属于它们自己的序列类别，剩下的17%更类似于假基因和随机基因间序列，可能代表噪音转录。
The human genome is dominated by large tracts of DNA with extensive biochemical activity but no known function. In particular, it is well established that transcriptional activities are not restricted to known genes. However, whether this intergenic transcription represents activity with functional significance or noise is under debate, highlighting the need for an effective method of defining functional genomic regions. Moreover, these discoveries raise the question whether genomic regions can be defined as functional based solely on the presence of biochemical activities, without considering evolutionary (conservation) and genetic (effects of mutations) evidence. Here, computational models integrating genetic, evolutionary, and biochemical evidence are established that provide reliable predictions of human protein-coding and RNA genes. Importantly, in addition to sequence conservation, biochemical features allow accurate predictions of genic sequences with phenotypic evidence under strong purifying selection, suggesting that they can be used as an alternative measure of selection. Moreover, 18.5% of annotated noncoding RNAs exhibit higher degrees of similarity to phenotype genes and, thus, are likely functional. However, 64.5% of noncoding RNAs appear to belong to a sequence class of their own, and the remaining 17% are more similar to pseudogenes and random intergenic sequences that may represent noisy transcription.