%0 Journal Article %J BMC Genomics %D 2017 %T Regulatory network changes between cell lines and their tissues of origin %A Lopes-Ramos*, Camila M %A Paulson*, Joseph N %A Chen, Cho-Yi %A Kuijjer, Marieke L %A Fagny, Maud %A Platig, John %A Sonawane, Abhijeet R %A DeMeo, Dawn L %A Quackenbush, John %A Kimberly Glass %X

Background
Cell lines are an indispensable tool in biomedical research and often used as surrogates for tissues. Although there are recognized important cellular and transcriptomic differences between cell lines and tissues, a systematic overview of the differences between the regulatory processes of a cell line and those of its tissue of origin has not been conducted. The RNA-Seq data generated by the GTEx project is the first available data resource in which it is possible to perform a large-scale transcriptional and regulatory network analysis comparing cell lines with their tissues of origin.

Results
We compared 127 paired Epstein-Barr virus transformed lymphoblastoid cell lines (LCLs) and whole blood samples, and 244 paired primary fibroblast cell lines and skin samples. While gene expression analysis confirms that these cell lines carry the expression signatures of their primary tissues, albeit at reduced levels, network analysis indicates that expression changes are the cumulative result of many previously unreported alterations in transcription factor (TF) regulation. More specifically, cell cycle genes are over-expressed in cell lines compared to primary tissues, and this alteration in expression is a result of less repressive TF targeting. We confirmed these regulatory changes for four TFs, including SMAD5, using independent ChIP-seq data from ENCODE.

Conclusions
Our results provide novel insights into the regulatory mechanisms controlling the expression differences between cell lines and tissues. The strong changes in TF regulation that we observe suggest that network changes, in addition to transcriptional levels, should be considered when using cell lines as models for tissues.

%B BMC Genomics %V 18 %P 723 %G eng %U https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-4111-x