Accurate Quantification of Functional Analogy among Close Homologs

Correctly evaluating functional similarities among homologous proteins is necessary for accurate transfer of experimental knowledge from one organism to another, and is of particular importance for the development of animal models of human disease. While the fact that sequence similarity implies functional similarity is a fundamental paradigm of molecular biology, sequence comparison does not directly assess the extent to which two proteins participate in the same biological processes, and has limited utility for analyzing families with several parologous members. Nevertheless, we show that it is possible to provide a cross-organism functional similarity measure in an unbiased way through the exclusive use of high-throughput gene-expression data. Our methodology is based on probabilistic cross-species mapping of functionally analogous proteins based on Bayesian integrative analysis of gene expression compendia. We demonstrate that even among closely related genes, our method is able to predict functionally analogous homolog pairs better than relying on sequence comparison alone. We also demonstrate that the landscape of functional similarity is often complex and that definitive “functional orthologs” do not always exist. Even in these cases, our method and the online interface we provide are designed to allow detailed exploration of sources of inferred functional similarity that can be evaluated by the user.精准评估同源蛋白（homologous proteins）间的功能相似性，是实现实验知识在不同生物体间准确迁移的必要前提，对于人类疾病动物模型的开发亦具有重要意义。尽管序列相似性意味着功能相似性是分子生物学的核心范式之一，但序列比对无法直接衡量两种蛋白质参与相同生物学过程的程度，且在分析包含多个旁系同源（paralogous）成员的基因家族时效用有限。尽管如此，本研究证明，仅通过高通量基因表达数据，即可以无偏倚的方式构建跨生物体的功能相似性度量方法。我们的方法基于对基因表达汇编（gene expression compendia）的贝叶斯整合分析，实现功能类似蛋白的跨物种概率映射。研究表明，即便在亲缘关系较近的基因中，本方法也能够比单纯依赖序列比对更精准地预测功能类似的同源蛋白对。本研究同时证实，功能相似性的分布往往较为复杂，绝对意义上的"功能直系同源（functional orthologs）"蛋白并非始终存在。即便在这类场景中，我们的方法与所提供的在线交互界面，仍可支持用户对推断出的功能相似性来源进行细致探索与评估。