Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Transcriptomic and phylogenetic analysis of a bacterial cell cycle reveals strong associations between gene co-expression and evolution


ABSTRACT: We used deep RNA sequencing to obtain high coverage RNA-Seq data of five C. crescentus cell cycle stages, each with three biological replicates. We found that 1,586 genes (over a third of the genome) display significant differential expression between stages. This gene list, which contains many genes previously unknown for their cell cycle regulation, includes almost half of the genes involved in primary metabolism, suggesting that these "house-keeping" genes are not constitutively transcribed during the cell cycle, as often assumed. Gene and module co-expression clustering reveal co-regulated pathways and suggest functionally coupled genes. In addition, an evolutionary analysis of the cell cycle network shows a high correlation between co-expression and co-evolution. Most co-expression modules have strong phylogenetic signals, with broadly conserved genes and clade-specific genes predominating different substructures of the cell cycle co-expression network. We also found that conserved genes tend to determine the expression profile of their module. We describe the first phylogenetic and single-nucleotide-resolution transcriptomic analysis of a bacterial cell cycle network. In addition, the study suggests how evolution has shaped this network and provides direct biological network support that selective pressure is not on individual genes but rather on the relationship between genes, which highlights the importance of integrating phylogenetic analysis into biological network studies. Examination of 5 typical cell cycle types (5 samples), each with 3 biological replicates

ORGANISM(S): Caulobacter vibrioides

SUBMITTER: Gang Fang 

PROVIDER: E-GEOD-46915 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

Similar Datasets

2014-10-16 | E-GEOD-57364 | biostudies-arrayexpress
2014-10-16 | E-GEOD-57365 | biostudies-arrayexpress
2013-05-15 | GSE46915 | GEO
2015-11-10 | E-GEOD-73925 | biostudies-arrayexpress
2016-08-06 | E-GEOD-71860 | biostudies-arrayexpress
2023-11-09 | PXD040223 | Pride
2005-01-01 | MODEL1011080003 | BioModels
2024-02-01 | PXD048886 | Pride
2019-12-16 | PXD012739 | Pride
2014-01-10 | E-GEOD-53955 | biostudies-arrayexpress