# Inferring diploid 3D chromatin structures from bulk and single-cell Hi-Cdata

> **NIH NIH F31** · UNIVERSITY OF WASHINGTON · 2020 · $39,785

## Abstract

Project Summary/Abstract
The 3D organization of the genome plays a key role in many cellular processes, such as gene regulation,
differentiation, and the cell cycle. Assays like Hi-C measure DNA-DNA contacts in a high-throughput fashion.
Inferring from such data accurate 3D models of how chromosomes fold can yield insights that are hidden in the
raw data. Many methods exist to infer the 3D structures of haploid genomes, but diploid genomes pose a much
more challenging problem because Hi-C data does not inherently distinguish between the alleles. Additionally,
while single-cell experiments have made clear that chromatin structure exhibits a great deal of heterogeneity
within a population, the sparsity of single-cell Hi-C data poses additional difficulties for inference. We have
recently published a method to infer 3D diploid genomes by building upon a probabilistic framework we previously
developed for haploid data. We propose to apply this method to model diploid yeast genomes in order to further
characterize mitotic homolog pairing in yeast. We also propose to extend this method to work with single-cell
data, and to validate and integrate our method with microscopy of chromatin sites and nuclear proteins. We will
thereby provide an integrated 3D model of high-resolution imaging and DNA sequence.

## Key facts

- **NIH application ID:** 9991077
- **Project number:** 1F31GM134642-01A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Alexandra Gesine Cauer
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $39,785
- **Award type:** 1
- **Project period:** 2020-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9991077

## Citation

> US National Institutes of Health, RePORTER application 9991077, Inferring diploid 3D chromatin structures from bulk and single-cell Hi-Cdata (1F31GM134642-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9991077. Licensed CC0.

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