We propose to systematically investigate and characterize sequence elements that are necessary for genome function in their native context in contrast to existing high- throughput assays of genome function that detect sequence elements that are sufficient for function. We will accomplish this goal with three specific aims. We will develop a novel Multiplexed Editing Regulatory Assay (MERA) to test the effect of thousands of targeted mutations in native regulatory regions in a single experiment (Aim 1). We will use MERA to characterize the regulation of key developmental genes, the function of selected regulatory elements, and the gene expression effects of SNPs that are discovered in GWAS studies (Aim 2). Using these data we will build a model that will allow us to predict the bases that comprise the necessary genome and estimate the effect of non-coding genotype on gene expression (Aim 3). Through our new experimental and computational method we will help lay the groundwork for a novel paradigm in revealing the effect of human variation at base pair resolution.

Public Health Relevance

We will develop a new method to measure in living cells the function of millions of individual letters that comprise the human genome. We will use this method to develop a catalog of the consequences of genomic variation on cellular function and health. As part of our work we will examine the importance of genome differences found in individuals with Type 2 Diabetes.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG008754-04
Application #
9718241
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Gilchrist, Daniel A
Project Start
2016-09-09
Project End
2020-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Shen, Max W; Arbab, Mandana; Hsu, Jonathan Y et al. (2018) Predictable and precise template-free CRISPR editing of pathogenic variants. Nature 563:646-651
Kang, Daniel; Sherwood, Richard; Barkal, Amira et al. (2017) DNase-capture reveals differential transcription factor binding modalities. PLoS One 12:e0187046
Banerjee, Budhaditya; Sherwood, Richard I (2017) A CRISPR view of gene regulation. Curr Opin Syst Biol 1:1-8
Betancur, Paola A; Abraham, Brian J; Yiu, Ying Y et al. (2017) A CD47-associated super-enhancer links pro-inflammatory signalling to CD47 upregulation in breast cancer. Nat Commun 8:14802
Rajagopal, Nisha; Srinivasan, Sharanya; Kooshesh, Kameron et al. (2016) High-throughput mapping of regulatory DNA. Nat Biotechnol 34:167-74
Arbab, Mandana; Sherwood, Richard I (2016) Self-Cloning CRISPR. Curr Protoc Stem Cell Biol 38:5B.5.1-5B.5.16
Barkal, Amira A; Srinivasan, Sharanya; Hashimoto, Tatsunori et al. (2016) Cas9 Functionally Opens Chromatin. PLoS One 11:e0152683