# In Vivo Characterization of Major ENCODE-Predicted Classes of Noncoding Elements

> **NIH NIH UM1** · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · 2021 · $1,358,777

## Abstract

PROJECT SUMMARY
We propose to establish a Center for In Vivo Characterization of ENCODE Elements (CIViC) as part of
ENCODE Phase 4. Understanding the function of the 98% of the human genome that is noncoding remains
one of the most pressing challenges in genomics. The ENCODE Program has enabled major progress toward
obtaining genome-wide molecular signatures associated with the human and mouse genome. During
ENCODE3 our group contributed to the mapping of enhancer-associated marks, DNA methylation, and
transcriptomes from multiple mouse tissues across closely spaced time points of embryogenesis, resulting in
>750 datasets defining the in vivo epigenomic landscape during mammalian development. Our group has also
characterized over 3,000 candidate enhancer sequences in transgenic mouse assays, including more than 400
through our participation in ENCODE2 and ENCODE3. Despite this progress, enhancers are only one of many
noncoding molecular functions that have been inferred from ENCODE data. Other major proposed categories
of noncoding sequences identified through ENCODE and other publicly available data sets include DNA
elements with predicted functions, such as “super-enhancers” (very large enhancers with possibly distinct
functions) or chromatin domain boundary elements. They also include sequence classes of unknown function
primarily defined by specific assays, such as differentially methylated regions (DMRs). The functional impact
of these different classes of noncoding sequences on organismal biology and human health remains minimally
explored, representing a major limitation of the ENCODE encyclopedia. The Center for In Vivo
Characterization of ENCODE Elements will use CRISPR/Cas9 genome editing to systematically explore the
biological significance of several classes of noncoding function based on ENCODE3 data. Leveraging the
streamlined set of mouse engineering tools available in our laboratory, we will: 1. Perform integrative analysis
of ENCODE3 and complementary data sets to identify and prioritize representative sequences from 3 different
classes of noncoding elements (enhancers and super-enhancers, boundary elements, DMRs);
2. Systematically delete a total of 48 representative sequences in mice and perform RNA-seq and gross
organismal phenotyping to understand the in vivo consequences of these deletions; 3. Continue to make
transgenic enhancer characterization capabilities available to ENCODE investigators to validate and calibrate
enhancer prediction methods. We will also use transgenics and CRISPR knock-in editing to test human
disease-associated alleles of ENCODE-predicted enhancer elements. All efforts will be closely coordinated
with other ENCODE4 functional characterization groups to focus on common sets of elements to be
characterized using the full ENCODE-wide arsenal of in vitro and in vivo characterization methods. Our results
will provide an understanding of the in vivo significance of different classes of noncoding elements an...

## Key facts

- **NIH application ID:** 10241190
- **Project number:** 3UM1HG009421-04S1
- **Recipient organization:** UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
- **Principal Investigator:** Len Alexander Pennacchio
- **Activity code:** UM1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,358,777
- **Award type:** 3
- **Project period:** 2017-02-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10241190

## Citation

> US National Institutes of Health, RePORTER application 10241190, In Vivo Characterization of Major ENCODE-Predicted Classes of Noncoding Elements (3UM1HG009421-04S1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10241190. Licensed CC0.

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