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操纵子的自然选择取决于基因组大小。

Natural selection for operons depends on genome size.

作者信息

Nuñez Pablo A, Romero Héctor, Farber Marisa D, Rocha Eduardo P C

机构信息

Instituto de Biotecnología, Instituto Nacional de Tecnología Agropecuaria (CICVyA-INTA), Buenos Aires, Argentina.

出版信息

Genome Biol Evol. 2013;5(11):2242-54. doi: 10.1093/gbe/evt174.

DOI:10.1093/gbe/evt174
PMID:24201372
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3845653/
Abstract

In prokaryotes, genome size is associated with metabolic versatility, regulatory complexity, effective population size, and horizontal transfer rates. We therefore analyzed the covariation of genome size and operon conservation to assess the evolutionary models of operon formation and maintenance. In agreement with previous results, intraoperonic pairs of essential and of highly expressed genes are more conserved. Interestingly, intraoperonic pairs of genes are also more conserved when they encode proteins at similar cell concentrations, suggesting a role of cotranscription in diminishing the cost of waste and shortfall in gene expression. Larger genomes have fewer and smaller operons that are also less conserved. Importantly, lower conservation in larger genomes was observed for all classes of operons in terms of gene expression, essentiality, and balanced protein concentration. We reached very similar conclusions in independent analyses of three major bacterial clades (α- and β-Proteobacteria and Firmicutes). Operon conservation is inversely correlated to the abundance of transcription factors in the genome when controlled for genome size. This suggests a negative association between the complexity of genetic networks and operon conservation. These results show that genome size and/or its proxies are key determinants of the intensity of natural selection for operon organization. Our data fit better the evolutionary models based on the advantage of coregulation than those based on genetic linkage or stochastic gene expression. We suggest that larger genomes with highly complex genetic networks and many transcription factors endure weaker selection for operons than smaller genomes with fewer alternative tools for genetic regulation.

摘要

在原核生物中,基因组大小与代谢多样性、调控复杂性、有效种群大小及水平转移率相关。因此,我们分析了基因组大小与操纵子保守性的协变关系,以评估操纵子形成和维持的进化模型。与先前结果一致,操纵子内必需基因对和高表达基因对更保守。有趣的是,当操纵子内基因对编码的蛋白质在细胞内浓度相似时,它们也更保守,这表明共转录在降低基因表达中的浪费成本和不足方面发挥了作用。较大的基因组具有更少、更小且保守性更低的操纵子。重要的是,就基因表达、必需性和平衡的蛋白质浓度而言,在较大基因组中观察到所有类型操纵子的保守性都较低。在对三个主要细菌类群(α-和β-变形菌门以及厚壁菌门)的独立分析中,我们得出了非常相似的结论。在控制基因组大小的情况下,操纵子保守性与基因组中转录因子的丰度呈负相关。这表明遗传网络的复杂性与操纵子保守性之间存在负相关。这些结果表明,基因组大小和/或其替代指标是操纵子组织自然选择强度的关键决定因素。我们的数据更符合基于共调控优势的进化模型而非基于遗传连锁或随机基因表达的模型。我们认为,与具有较少遗传调控替代工具的较小基因组相比,具有高度复杂遗传网络和许多转录因子的较大基因组对操纵子的选择较弱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/d58407778a25/evt174f6p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/66d0e5823d3b/evt174f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/2ebba6efa4ff/evt174f2p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/47218f4a3d28/evt174f3p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/2be486cd5058/evt174f4p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/baa878329e27/evt174f5p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/d58407778a25/evt174f6p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/66d0e5823d3b/evt174f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/2ebba6efa4ff/evt174f2p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/47218f4a3d28/evt174f3p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/2be486cd5058/evt174f4p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/baa878329e27/evt174f5p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2b8/3845653/d58407778a25/evt174f6p.jpg

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Brief Funct Genomics. 2012 Jul;11(4):291-9. doi: 10.1093/bfgp/els024. Epub 2012 Jun 28.
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ProOpDB: Prokaryotic Operon DataBase.ProOpDB:原核操纵子数据库。
Nucleic Acids Res. 2022 Feb 22;50(3):1673-1686. doi: 10.1093/nar/gkac004.
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Prediction and analysis of metagenomic operons via MetaRon: a pipeline for prediction of Metagenome and whole-genome opeRons.通过 MetaRon 预测和分析宏基因组操纵子:用于预测宏基因组和全基因组操纵子的管道。
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