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蛋白质分子功能的系统发育基因组学推断

Phylogenomic inference of protein molecular function.

作者信息

Krishnamurthy Nandini, Sjölander Kimmen

机构信息

University of California, Berkeley, California, USA.

出版信息

Curr Protoc Bioinformatics. 2005 Oct;Chapter 6:Unit 6.9. doi: 10.1002/0471250953.bi0609s11.

Abstract

With the explosion in sequence data, accurate prediction of protein function has become a vital task in prioritizing experimental investigation. While computationally efficient methods for homology-based function prediction have been developed to make this approach feasible in high-throughput mode, it is not without its dangers. Biological processes such as gene duplication, domain shuffling, and speciation produce families of related genes whose gene products can have vastly different molecular functions. Standard sequence-comparison approaches may not discriminate effectively among these candidate homologs, leading to errors in database annotations. In this unit, we describe phylogenomic approaches to reduce the error rate in function prediction. Phylogenomic inference of protein molecular function consists of a series of subtasks. Once a cluster of homologs is identified, a multiple sequence alignment and phylogenetic tree are constructed. Finally, the phylogenetic tree is overlaid with experimental data culled for the members of the family, and changes in biochemical function can be traced along the evolutionary tree.

摘要

随着序列数据的激增,准确预测蛋白质功能已成为确定实验研究优先级的一项至关重要的任务。虽然已经开发出计算效率高的基于同源性的功能预测方法,以使这种方法在高通量模式下可行,但它并非没有风险。诸如基因复制、结构域改组和物种形成等生物学过程会产生相关基因家族,其基因产物可能具有截然不同的分子功能。标准的序列比较方法可能无法有效区分这些候选同源物,从而导致数据库注释错误。在本单元中,我们描述了系统发育基因组学方法,以降低功能预测中的错误率。蛋白质分子功能的系统发育基因组学推断包括一系列子任务。一旦确定了同源物簇,就构建多序列比对和系统发育树。最后,将为该家族成员挑选的实验数据覆盖在系统发育树上,并且可以沿着进化树追踪生化功能的变化。

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