Beyond enhancer-promoter contact : leveraging deep learning to connect super-resolution DNA traces to transcription

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Abstract/Contents

Abstract
Chromatin architecture plays an important role in gene regulation. Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. However, leveraging these complex datasets with a computationally unbiased method has not been achieved. In this dissertation, I present a deep learning-based approach to better understand to what degree chromatin structure relates to the transcriptional state of individual cells. Furthermore, I explore methods to "unpack the black box" to determine in an unbiased manner which structural features of chromatin regulation are most important for gene expression state. I apply this approach to the Optical Reconstruction of Chromatin Architecture dataset of the Bithorax gene cluster in Drosophila and show it significantly outperforms previous contact-focused methods. This work finds the structural information is distributed across the domain, overlapping and extending beyond domains identified by prior genetic analyses. Individual enhancer-promoter interactions are a minor contributor to predictions of activity.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2021; ©2021
Publication date 2021; 2021
Issuance monographic
Language English

Creators/Contributors

Author Rajpurkar, Aparna Rajiv
Degree supervisor Boettiger, Alistair
Thesis advisor Boettiger, Alistair
Thesis advisor Bhatt, Ami (Ami Siddharth)
Thesis advisor Kundaje, Anshul, 1980-
Thesis advisor Winslow, Monte
Degree committee member Bhatt, Ami (Ami Siddharth)
Degree committee member Kundaje, Anshul, 1980-
Degree committee member Winslow, Monte
Associated with Stanford University, Department of Genetics

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Aparna Rajiv Rajpurkar.
Note Submitted to the Department of Genetics.
Thesis Thesis Ph.D. Stanford University 2021.
Location electronic resource

Access conditions

Copyright
© 2021 by Aparna Rajiv Rajpurkar
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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