Journal Article

Meta-analysis reveals conserved cell cycle transcriptional network across multiple human cell types

Giotti, Bruno, Freeman, Tom C., Joshi, Anagha

2017

Overview

Background Cell division is central to the physiology and pathology of all eukaryotic organisms. The molecular machinery underpinning the cell cycle has been studied extensively in a number of species and core aspects of it have been found to be highly conserved. Similarly, the transcriptional changes associated with this pathway have been studied in different organisms and different cell types. In each case hundreds of genes have been reported to be regulated, however there seems to be little consensus in the genes identified across different studies. In a recent comparison of transcriptomic studies of the cell cycle in different human cell types, only 96 cell cycle genes were reported to be the same across all studies examined. Results Here we perform a systematic re-examination of published human cell cycle expression data by using a network-based approach to identify groups of genes with a similar expression profile and therefore function. Two clusters in particular, containing 298 transcripts, showed patterns of expression consistent with cell cycle occurrence across the four human cell types assessed. Conclusions Our analysis shows that there is a far greater conservation of cell cycle-associated gene expression across human cell types than reported previously, which can be separated into two distinct transcriptional networks associated with the G 1 /S-S and G 2 -M phases of the cell cycle. This work also highlights the benefits of performing a re-analysis on combined datasets.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V
• Subject: Algorithms / Animal Genetics and Genomics / Annotations / Biomedical and Life Sciences / Cell cycle / Cell Cycle - genetics / Cell division / Cluster Analysis / Clustering / Computational Biology - methods / Data processing / Databases, Genetic / Datasets / Eukaryotes / Fibroblasts / Fourier transforms / Gene expression / Gene Expression Profiling / Gene Ontology / Gene Regulatory Networks / Genes / Genomes / Genomics / Humans / Life Sciences / Meta-analysis / Microarrays / Microbial Genetics and Genomics / Molecular machines / Molecular Sequence Annotation / Ontology / Organ Specificity - genetics / Plant Genetics and Genomics / Principal components analysis / Proteomics / Regular / Regular Article / Reproducibility of Results / Studies / Systems Biology - methods / Transcription / Transcription (Genetics) / Transcriptome / Transcriptomic methods