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相似性回归可预测转录因子序列特异性进化
作者:小柯机器人 发布时间:2019/7/10 16:17:51

加拿大多伦多大学Timothy R. Hughes团队取得了一项研究成果,他们发现相似性回归可预测转录因子序列特异性进化。该成果发表于2019年6月出版的国际学术期刊《Nature Genetics》上。

在本研究中,该团队描述了相似性回归,一种显著改进了的预测基序的方法,并用它来更新和扩展Cis-BP数据库。研究发现,相似性回归固有地量化了TF基序的进化,并且表明先前认为人类和果蝇之间基序近乎完全保守的说法是夸大的,两个物种之间几乎一半的基序不存在于另一个中,这很大程度上缘于C2H2锌指蛋白的广泛分散。研究人员得出结论,DNA结合基序的多样化是普遍存在的,并提供了一种新的工具和更新的资源来研究真核生物间TF的多样性及基因调控。

据悉,转录因子 (TF) 的结合特异性(基序)对于基因调控的分析是必须的。准确预测TF基序至关重要,因为分析所有已测序的真核基因组中的所有TF是不可行的。关于相关物种之间的基序多样化程度长期存在争议,部分缘于基序预测方法的不确定性。

附:英文原文

Title: Similarity regression predicts evolution of transcription factor sequence specificity

Author: Samuel A. Lambert, Ally W. H. Yang, Alexander Sasse, Gwendolyn Cowley, Mihai Albu, Mark X. Caddick, Quaid D. Morris, Matthew T. Weirauch, Timothy R. Hughes

Issue&Volume: Volume 51 Issue 6, June 2019

Abstract: Transcription factor (TF) binding specificities (motifs) are essential for the analysis of gene regulation. Accurate prediction of TF motifs is critical, because it is infeasible to assay all TFs in all sequenced eukaryotic genomes. There is ongoing controversy regarding the degree of motif diversification among related species that is, in part, because of uncertainty in motif prediction methods. Here we describe similarity regression, a significantly improved method for predicting motifs, which we use to update and expand the Cis-BP database. Similarity regression inherently quantifies TF motif evolution, and shows that previous claims of near-complete conservation of motifs between human and Drosophila are inflated, with nearly half of the motifs in each species absent from the other, largely due to extensive divergence in C2H2 zinc finger proteins. We conclude that diversification in DNA-binding motifs is pervasive, and present a new tool and updated resource to study TF diversity and gene regulation across eukaryotes.

DOI: 10.1038/s41588-019-0411-1

Source:https://www.nature.com/articles/s41588-019-0411-1

期刊信息

Nature Genetics:《自然—遗传学》,创刊于1992年。隶属于施普林格·自然出版集团,最新IF:25.455
官方网址:https://www.nature.com/ng/
投稿链接:https://mts-ng.nature.com/cgi-bin/main.plex