This proposal integrates and builds upon our combined experience and strengths, and on technological advances in in the wider scientific community. We will expand our understanding of the biology and sequence-based encryption of transcriptional regulatory instructions in clinically pertinent neuronal populations, focusing on neuronal populations implicated in Schizophrenia (SZ) and related neuropsychiatric disorders. In recent years, we have taken significant strides in characterizing regulatory control at specific neurogenic loci by generating, validating and publicly depositing huge catalogs of neuronal enhancers. We have developed and implemented computational strategies to identify key motif combinations that recognize neuronal enhancers, and used them to develop sequence-based vocabularies (classifiers) for neuroanatomical domains (forebrain, midbrain, hindbrain) and homogenous isolated cell populations. By integrating our experiences in functional and computational genetics and genomics we have already been able to indict several disease-associated variants in pertinent biological processes. Efforts to understand the architecture of human complex disease through Genome Wide Association Studies have drawn increased attention to potential roles played by regulatory variation. Thus, illuminating the connections between regulatory variants and disease risk is an important step towards understanding disease biology. We will systematically assay the regulatory potential of sequences encompassing disease-(SZ)- associated variation, determining the allele-specific activity of identified enhancers and determining their regulatory control by in vitro cellular assays and in whole organisms (Neuron-specific transgenic reporter zebrafish;
(Aim 1). Further, to expand neuron-specific annotation to regulatory sequences genome-wide, we propose detailed characterization of cell-type appropriate genome-wide regulatory sequence catalogs, isolating labeled dopaminergic/Glutamatergic/GABAergic neurons ex vivo, functionally validating the catalogs and developing computational classifiers to identify human enhancers with activity in specific neuronal subtypes (Aim 2). Finally, we will determine the relationship between SZ-associated distal-acting regulatory sequences and their cognate genes using cutting edge Chromatin Conformation Capture (3C)-based strategies to reveal putative enhancers-promoter interactions, connect SZ-associated, non-coding loci with genes and determine the regulatory potential of distal sequences identified in this way (Aim 3). This proposal takes significant steps towards understanding neuropsychiatric disease by creating a neuronal regulatory lexicon that can inform our observation of disease-associated variation in non-coding, putative regulatory sequence space and by directly exploring the regulatory roles of SZ associated DNA variants.

Public Health Relevance

We wish to better understand how DNA sequence encodes regulatory instructions, dictating when and where critical genes are to be switched on/off. We will focus on types of neurons and on specific genes that are implicated in Schizophrenia, and related neuropsychiatric disorders. Our work will provide insights into the identity, composition and biological requirement for these gene switches, improving our understanding of how DNA variation disrupts them in common genetic disorders and how we might be able to intervene.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH106522-02
Application #
9242723
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Arguello, Alexander
Project Start
2016-03-11
Project End
2021-12-31
Budget Start
2018-01-01
Budget End
2018-12-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Genetics
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205
Avramopoulos, Dimitrios (2017) Neuregulin 3 and its roles in schizophrenia risk and presentation. Am J Med Genet B Neuropsychiatr Genet :
Eckart, Nicole; Song, Qifeng; Yang, Rebecca et al. (2016) Functional Characterization of Schizophrenia-Associated Variation in CACNA1C. PLoS One 11:e0157086