Phased Genome-Scale Epigenetic Maps via Proximity Ligation
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Solution Overview
Problem
Current methods for determining the 3D architecture of chromatin are inadequate, failing to map all chromatin loops and associate each loop with a single DNA element due to low resolution, which hinders the identification of looping proteins and the prediction of genetic variants' effects on protein binding and gene expression.
Innovation Solution
A method for generating phased genome-scale nuclease sensitivity, DNA methylation, and protein-binding maps by enzymatically fragmenting chromatin, performing proximity ligation, and sequencing ligation junctions to determine DNA contacts and cut sites, allowing for high-resolution phasing of chromatin fragments onto individual homologs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods (ChIP-Seq, Dnase-Seq) are used to determine chromatin structure, then protein binding and chromatin accessibility can be detected, but resolution is insufficient (15 kb localization) and cannot associate loops with single DNA elements
Solution Approach 1:
The method segments the chromatin mapping problem into distinct functional components: nuclease sensitivity mapping to identify accessible regions, DNA methylation mapping to identify regulatory elements, and protein-binding mapping to identify bound proteins. Each component is mapped at high resolution independently, then integrated to achieve complete loop-DNA element association that exceeds the capability of any single conventional method
Solution Approach 2:
The invention merges multiple sequencing assays (nuclease sensitivity, DNA methylation, protein-binding) into a unified phased mapping approach. By combining these assays on the same phased genome-scale data, the method achieves comprehensive chromatin structure characterization at high resolution, resolving loops to single DNA elements and identifying associated proteins and regulatory elements simultaneously
2Quantity of substance
If in situ Hi-C is used to improve 3D genome mapping, then more reads are obtained (order of magnitude increase), but peaks remain diffuse at 1 kb resolution
Solution Approach 1:
The method changes the measurement parameters by using phased genome-scale mapping with multiple assay types instead of relying solely on Hi-C contact frequency. This approach transforms the data structure from diffuse contact maps to precise, phased maps that can resolve peaks at single-base-pair resolution by leveraging the phased nature of the data and integrating multiple orthogonal measurements
3Adaptability or versatility
If two separate assays (ChIP-Seq and Dnase-Seq) are used to identify looping proteins and chromatin accessibility, then comprehensive data can be collected, but datasets are inaccurate and shallow (2/3 of CTCF loop anchors lack annotated Dnase footprint)
Solution Approach 1:
The invention merges ChIP-Seq, Dnase-Seq, and new phased mapping assays into a unified approach where all measurements are performed on the same phased genome-scale data. This integration ensures that looping proteins, chromatin accessibility, and DNA elements are identified in the same experimental context, eliminating the mismatch and inaccuracy that arises from using separate assays on different cell populations
Solution Approach 2:
The phased mapping approach provides internal feedback and validation: nuclease sensitivity patterns validate chromatin accessibility calls, DNA methylation patterns validate regulatory element identification, and protein-binding patterns validate loop anchor identification. This cross-validation within the unified phased framework significantly improves dataset accuracy and reliability compared to separate assays
4Loss of information
If external phased SNP data is used to predict variant effects, then genetic variants can be linked to function, but the linking process is difficult and requires external data
Solution Approach 1:
The phased genome-scale mapping method generates its own phased data internally, eliminating the need for external phased SNP data. The method self-phases the chromatin structure, DNA methylation, and protein-binding data, providing complete variant-function linkage information from the experiment itself rather than requiring integration with external datasets
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the creation of detailed, high-resolution maps that accurately identify chromatin loops, looping proteins, and the effects of genetic variants on protein binding and gene expression, improving our understanding of chromatin structure and its role in gene regulation.
Implementation Method 1
enzymatically fragmenting chromatin
Implementation Method 2
performing proximity ligation
Implementation Method 3
sequencing ligation junctions to determine DNA contacts and cut sites
Implementation Method 4
phasing the sequenced chromatin fragments onto individual homologs in the cell based on DNA contacts
Data Source
AI summary
Disclosed are methods for obtaining genome scale and fully phased epigenetic maps in a cell. The method enables maintaining intact chromatin structure and interrogating chromatin structure using chromatin accessibility maps. DNA contacts are used to fully phase the epigenetic and chromatin contact maps.