NEW YORK (GenomeWeb) – The National Institute of Mental Health is seeking grant applications for projects that will expand the efforts of the PsychENCODE consortium (PEC) by helping build comprehensive maps of non-coding functional elements in the human brain.
According to the NIMH, funded projects will use unbiased genome-wide approaches, computational methods, and experimental assays to identify and characterize functional genomic elements in both healthy and diseased human brains, and correlate these findings with development of mental illnesses and outcomes relevant to brain function and dysfunction.
PsychENCODE is a public/private effort that was established to discover non-coding functional genomic elements in the brain and elucidate their role in the molecular pathophysiology of psychiatric disorders. It ultimately aims to generate spatio-temporal reference maps of functional genomic elements affecting human brain function and create a public resource of multidimensional genomic data.
"The PEC is making substantial headway and is actively sharing the resources that are being generated within the research community," the NIMH said in the funding opportunity announcement. "However, progress in this area is only just beginning and much work is still needed to comprehensively characterize the functional diversity of genetic regulation in the brain at various genomic scales."
To that end, the NIMH said it intends to fund research focused on discovering and characterizing the full spectrum of non-coding functional genomic elements — including enhancers, promoters, silencers, non-coding RNAs, and chromatin interactions — across brain regions, cell types, and developmental time periods to elucidate their roles in the molecular pathophysiology of mental illness through genome-wide examination of various human cell and tissue sources. The agency is also interested in studies that identify human-specific functional regulatory elements, preferably in different neural and glial cell types across brain regions in patient populations.
Examples of research that is appropriate for this funding opportunity include the identification of transcriptomic, epigenomic, and proteomic signatures specific to disease states compared to healthy control brains, both within and across disorders; the spatio-temporal analysis of changes in RNA splicing, transcript and protein isoforms, allele-specific expression, chromatin conformation, and quantitative trait loci in the context of neuropsychiatric disorders; and the development of novel analytical and computational methods to perform integrative analysis of multi-omic data generated within the PEC and across large scale genome wide efforts in order to build predictive models of disease using systems biology approaches.
Additional details about the funding opportunity can be found here and here.