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选择性剪接是真核生物基因调控的基本调节机制之一,与各种类型的生理和病理活动相关.癌症相关基因的不正常剪接可能与多种癌症的发生发展有关.作为选择性剪接进化的主体,选择性剪接外显子展示了其在不同物种中多样的进化功能.本文系统整理了2 989个癌症相关基因的各项功能,通过比较基因组学的分析方法总结了癌症相关基因的选择性剪接外显子的功能和进化关系,建立了癌症相关基因选择性剪接进化数据库(ASeeDB数据库).ASeeDB包含癌症相关基因外显子区域的进化保守性、结构域预测、Ka/Ks值、以及基因、转录本、外显子区域3个层次的表达量统计等信息,结合这些信息用户可以方便的检索有研究意义的基因或者外显子.外显子区域蛋白质结构域的预测可以帮助了解其可能的功能,而外显子是否存在选择性剪接又可以推及包含该外显子的转录本是否具有相似的功能以及推测剪接是否会对蛋白质功能发生影响.数据库提供的物种间的序列比对可以帮助用户发现没有注释的外显子区域或者是保留的失去功能的外显子.相比于基因层面的Ka/Ks,数据库提供的外显子层面的Ka/Ks对于发现适应性进化事件具有更高的敏感性,可以更加方便地预示基因中未知功能的区域.
Alternative splicing is one of the basic regulatory mechanisms of gene regulation in eukaryotes, and is associated with various types of physiological and pathological activities.Extension of cancer-associated genes may be related to the development of a variety of cancers.As an alternative splicing The main body, alternative splicing of exons shows its diverse evolutionary functions in different species.This article systematically sorted out the functions of 2 989 cancer-related genes and compared the selectivity of cancer-related genes by comparative genomics analysis Splicing exons function and evolutionary relationships, the establishment of a cancer-related gene alternative splicing evolution database (ASeeDB database) .ASeeDB contains cancer-related genes in exon evolutionary conservation, domain prediction, Ka / Ks value, as well as genes , Transcripts, and expression levels of three levels of exon regions, etc. Based on these information, users can conveniently search for genes or exons of interest.Prediction of exonic domain protein domains may help to understand its possible Function, and whether the presence of exons in alternative splicing in turn can infer whether the exon containing transcripts have Like functions and speculation about whether the splicing will have an effect on the function of the protein.The sequence alignment provided by the database to help users find unnoticeled exon regions or conserved deletions of exons compared to the gene level Ka / Ks, the database provides exon-level Ka / Ks for the discovery of adaptive evolution events have a higher sensitivity, it is more convenient to predict the unknown function of the region.