Essential genes from genome-wide screenings as a resource for neuropsychiatric disorders gene discovery.
Wei ZhangJoao de QuevedoGabriel Rodrigo FriesPublished in: Translational psychiatry (2021)
Genome-wide screenings of "essential genes", i.e., genes required for an organism or cell survival, have been traditionally conducted in vitro in cancer cell lines, limiting the translation of results to other tissues and non-cancerous cells. Recently, an in vivo screening was conducted in adult mouse striatum tissue, providing the first genome-wide dataset of essential genes in neuronal cells. Here, we aim to investigate the role of essential genes in brain development and disease risk with a comprehensive set of bioinformatics tools, including integration with transcriptomic data from developing human brain, publicly available data from genome-wide association studies, de novo mutation datasets for different neuropsychiatric disorders, and case-control transcriptomic data from postmortem brain tissues. For the first time, we found that the expression of neuronal essential genes (NEGs) increases before birth during the early development of human brain and maintains a relatively high expression after birth. On the contrary, common essential genes from cancer cell line screenings (ACEGs) tend to be expressed at high levels during development but quickly drop after birth. Both gene sets were enriched in neurodevelopmental disorders, but only NEGs were robustly associated with neuropsychiatric disorders risk genes. Finally, NEGs were more likely to show differential expression in the brains of neuropsychiatric disorders patients than ACEGs. Overall, genome-wide central nervous system screening of essential genes can provide new insights into neuropsychiatric diseases.
Keyphrases
- genome wide
- dna methylation
- genome wide identification
- copy number
- bioinformatics analysis
- induced apoptosis
- gene expression
- poor prognosis
- squamous cell carcinoma
- high throughput
- genome wide analysis
- electronic health record
- case control
- resting state
- small molecule
- transcription factor
- oxidative stress
- functional connectivity
- machine learning
- single cell
- newly diagnosed
- white matter
- young adults
- deep learning
- big data
- subarachnoid hemorrhage
- papillary thyroid
- pi k akt
- pregnant women
- lymph node metastasis
- squamous cell
- chronic kidney disease
- prognostic factors
- prefrontal cortex