Differential correlation network analysis of rectal transcriptomes reveals cystic fibrosis-related disturbance

Tweetable abstract Cystic fibrosis: an unsupervised differential correlation network reanalysis of rectal transcriptomic data reveals promising targets for mechanistic research: FAU, SRP14 and GDI2. The value of results is highlighted by already known key role of FAU in cystic fibrosis. Background: Intestinal pathology in cystic fibrosis (CF) remains mechanistically underexplored. Aim: We hypothesized that differential correlation network analysis of expression data would reveal hub genes of CF-related disturbance in the large bowel. Materials & methods: Transcriptomes of 29 rectal tissue samples were accessed at ArrayExpress (E-GEOD-15568 by Stanke et al.). Results: We identified 279 transcript pairs differentially correlating in CF and controls, including: ESRRA and RPL18 (r(CF) = 0.55; r(controls) = -0.68; p(adj) = 1.60 x 10(-100)), SRP14 and FAU (r(CF) = -0.69; r(controls) = 0.48; p(adj) = 2.99 x 10(-90)), SRP14 and GDI2 (r(CF) = -0.34; r(controls) = 0.60; p(adj) = 1.05 x 10(-78)). The genes related to membrane protein targeting (q = 8.34 x 10(-14)) and one cluster was clearly linked to male infertility. Conclusion: FAU, SRP14 and GDI2 may be involved in a compensatory protein trafficking mechanism in CF rectum, highlighting their potential therapeutic value.

Automated summary

In this study, an unsupervised differential correlation network reanalysis of rectal transcriptomic data revealed promising targets for mechanistic research of intestinal pathology in cystic fibrosis (CF), including FAU, SRP14, and GDI2. These genes may be involved in a compensatory protein trafficking mechanism in the CF rectum, highlighting their potential therapeutic value.