Work was conducted through 3 work packages (WPs). WP1 consisted in developing an analysis framework to identify gene co-activity across dozens of human tissues. For this, the Fellow deployed large-scale statistical analysis using large computing clusters to produce millions of computations. Moreover, thousands of mutations linked to gene activity were identified using previously established methods. WP2 sought to exploit the dataset developed in WP1 to obtain biologically-relevant insights, in particular with the aim of understanding the molecular and evolutionary reasons of gene co-activity. WP3 involved the use of state-of-the-art datasets of single cell measurements (high-detail molecular data) to allow the identification of nearby gene co-activity per individual, something not previously attempted in the field. Several pertinent findings were obtained, including:
- The commonalities of gene co-activity patterns across different human tissues
- The role of shared regulatory elements in gene co-activity
- The effect of mutations in gene co-activity and disease
Overview of the results and their dissemination
Besides novel biological insights, the action produced the following concrete results:
- A novel framework to perform nearby gene co-activity analysis
- A comprehensive map of gene co-activity and associated mutations for each human tissue
- Gene and enhancer co-activity maps derived from single cell data in two human cell types
These results were disseminated in the following manner:
- Two scientific publications, one published in a peer-reviewed scientific journal and another available as a preprint and currently in revision in a peer-reviewed journal
- Ribeiro, D.M. Rubinacci, S., Ramisch, A. et al. The molecular basis, genetic control and pleiotropic effects of local gene co-expression. Nat Commun 12, 4842 (2021).
https://doi.org/10.1038/s41467-021-25129-x(opens in new window) - Ribeiro, D.M. Ziyani, C., Delaneau, O. Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis. bioRxiv (2021).
https://doi.org/10.1101/2021.12.14.472573(opens in new window) - The novel framework was made available though commonly used code repositories (github)
- Maps of gene co-activity were made available to the scientific community through a dedicated public database
- Results were further disseminated through 7 conferences, including through plenary talks at the major international conferences in the field, and 6 other seminars