Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials
Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials
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DOI：
10.1142/9789813235533_0049
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发表时间：
2018
影响因子：
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通讯作者：
Travis S. Johnson;Sihong Li;Jonathan Kho;Kun Huang;Yan Zhang
中科院分区：
文献类型：
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作者：
Travis S. Johnson;Sihong Li;Jonathan Kho;Kun Huang;Yan Zhang
假基因是基因的化石亲属。假基因长期以来被认为是“垃圾DNA”，因为它们不编码正常组织中的蛋白质。虽然大多数人类假基因不具有明显的功能，但约20%的假基因具有转录活性。有证据表明，一些假基因具有lncRNA的功能，并作为基因表达的调节因子。此外，假基因甚至可以在某些情况下被“重新激活”，例如癌症启动。一些假基因在特定的癌症类型中被转录，并且一些甚至被翻译成蛋白质，如在几种癌细胞系中观察到的。这些都表明假基因在基因组中可能具有功能作用或潜力。研究假基因与其对应基因之间的关系有助于揭示假基因的进化路径，并将假基因与功能潜能联系起来。在本研究中，我们发展了一种新的方法，结合图形分析，序列比对和功能分析来评估假基因-基因的关系，并将其应用于人类基因同源物和假基因。我们从原始的3，281个基因家族（13.56%）中产生了445个假基因（PGG）家族。其中438个（98.4%PGG，总共13.3%）是非平凡的（包含一个以上的假基因）。每个PGG家族包含多个基因和假基因，具有高度的序列相似性。对于每个家庭，我们生成一个序列比对网络和系统发育树概括的进化路径。我们发现了支持人类嗅觉家族（包括基因和假基因）进化历史的证据，这也支持了我们分析方法的有效性。接下来，我们评估这些网络的基因本体，从中我们确定丰富的功能，这些假基因基因家族和推断功能的影响，假基因参与的网络。这证明了我们的PGG网络数据库在疾病背景下的假基因功能研究中的应用。
Pseudogenes are fossil relatives of genes. Pseudogenes have long been thought of as "junk DNAs", since they do not code proteins in normal tissues. Although most of the human pseudogenes do not have noticeable functions, ∼20% of them exhibit transcriptional activity. There has been evidence showing that some pseudogenes adopted functions as lncRNAs and work as regulators of gene expression. Furthermore, pseudogenes can even be "reactivated" in some conditions, such as cancer initiation. Some pseudogenes are transcribed in specific cancer types, and some are even translated into proteins as observed in several cancer cell lines. All the above have shown that pseudogenes could have functional roles or potentials in the genome. Evaluating the relationships between pseudogenes and their gene counterparts could help us reveal the evolutionary path of pseudogenes and associate pseudogenes with functional potentials. It also provides an insight into the regulatory networks involving pseudogenes with transcriptional and even translational activities.In this study, we develop a novel approach integrating graph analysis, sequence alignment and functional analysis to evaluate pseudogene-gene relationships, and apply it to human gene homologs and pseudogenes. We generated a comprehensive set of 445 pseudogene-gene (PGG) families from the original 3,281 gene families (13.56%). Of these 438 (98.4% PGG, 13.3% total) were non-trivial (containing more than one pseudogene). Each PGG family contains multiple genes and pseudogenes with high sequence similarity. For each family, we generate a sequence alignment network and phylogenetic trees recapitulating the evolutionary paths. We find evidence supporting the evolution history of olfactory family (both genes and pseudogenes) in human, which also supports the validity of our analysis method. Next, we evaluate these networks in respect to the gene ontology from which we identify functions enriched in these pseudogene-gene families and infer functional impact of pseudogenes involved in the networks. This demonstrates the application of our PGG network database in the study of pseudogene function in disease context.