# (Epi)Genomics Core

> **NIH NIH U19** · UNIVERSITY OF CHICAGO · 2021 · $527,263

## Abstract

SUMMARY
While GWAS have identified hundreds of genetic variants in at least 150 loci associated with asthma and
allergic diseases (AAD), the translation of those findings into a better understanding of asthma etiology have
lagged significantly. This is due, in part, to the fact that most AAD-associated variants are in noncoding
sequences, often at great distance from genes. The underlying consensus is that a number of these variants
impart their effects in disease risk by disrupting the regulatory properties of regulatory elements, such as
enhancers and promoters. The challenges to efficiently extract hypothesis-generating information from GWAS
loci include i) identifying the causal variant(s) in each GWAS locus, ii) determining the type of regulatory
element in which these variants are mapped, iii) inferring the tissue-specificity of these regulatory elements, iv)
defining the target genes for these regulatory elements, and v) demonstrating a phenotypic effect of these
variants. This Center proposal aims to develop a computational and experimental framework to tackle all these
outstanding challenges. In Project 1, an innovative statistical and computational framework will be developed
to link functional annotations in AAD-associated loci to identify candidate variants, regulatory sequences and
genes that are mediating the genetic association. These annotations will be generated from cells obtained in
Project 2, which iteratively will also be able to test some of the predictions made from Project 1 in in vitro and in
vivo models. The generation of the functional annotations necessitate the use of several state-of-the-art
genomics strategies. The goal of the (Epi)Genomics Core (EGC) is to serve as the genomics data generation
hub for this Center. We propose t carry over 500 whole-genome assays in multiple asthma-relevant primary
cell types obtained in Project 2. In Aim 1 we will generate transcription and chromatin accessibility maps for
each of these cells under baseline and stimulated conditions. We will utilize a suite of complementary
chromatin accessibility assays, including ATAC-seq, KAS-sew and whole genome bisulfite sequencing, in
addition to RNA-seq to generate dynamic transcription maps in each cell line in response to specific stimuli. In
Aim 2 we will “wire” regulatory elements to their target genes, utilizing chromatin conformation capture. Finally,
we will test the regulatory potential of thousands of candidate variants identified in Project 1 in a massively
parallel reporter assay. The combination of comprehensive functional annotations in multiple cell types and
states represent an ambitious departure from the traditional efforts to link variants to function in single loci to a
systematic approach that interrogates the whole genome at once. We anticipate that our research strategy will
generate a large number of specific hypothesis that will be pursued in similar ways to what we propose in
Project 2. As such, the EGC will serve as ...

## Key facts

- **NIH application ID:** 10261989
- **Project number:** 1U19AI162310-01
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Marcelo A. Nobrega
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $527,263
- **Award type:** 1
- **Project period:** 2021-07-19 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10261989

## Citation

> US National Institutes of Health, RePORTER application 10261989, (Epi)Genomics Core (1U19AI162310-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10261989. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*