According to Phys.org, Harvard chemist Brian Liau and his collaborators have developed TDAC-seq (Targeted Deaminase Accessible Chromatin sequencing), a revolutionary genome mapping tool that reveals how genetic perturbations alter chromatin structure at single-nucleotide resolution. Published in Nature Methods, the technology enables researchers to systematically study the 98% of noncoding DNA that regulates gene activity, previously considered the genome’s “dark matter.” The team, including graduate students Heejin Roh and Simon Shen and postdoctoral scholar Hui Si Kwok, leveraged the bacterial enzyme DddA to mark open DNA by converting cytosine to thymine without breaking DNA strands. They demonstrated the platform’s power by applying it to regulatory regions controlling fetal hemoglobin, directly relevant to sickle cell disease treatment. This breakthrough promises to transform both basic genetic understanding and therapeutic development for genetic disorders.
Sponsored content — provided for informational and promotional purposes.
The Technical Innovation Behind Single-Nucleotide Resolution
The core innovation of TDAC-seq lies in its clever combination of CRISPR genome editing with base-editing enzymes in a way that previous chromatin accessibility methods couldn’t achieve. Traditional approaches like ATAC-seq provide bulk measurements across cell populations, but TDAC-seq’s use of DddA enables tracking of individual DNA molecules after CRISPR perturbations. What makes this particularly sophisticated is that DddA operates without creating double-strand breaks in DNA, which is crucial because such breaks can themselves alter chromatin structure and confound measurements. The team’s optimization of DddA variants to achieve high mutation rates while maintaining specificity represents a significant biochemical engineering challenge that they successfully overcame.
The Data Analysis Hurdle and Solution
As Simon Shen noted, this new type of data required fundamentally new analytical approaches. The challenge wasn’t just generating the data but interpreting the complex patterns of cytosine-to-thymine conversions across targeted genomic regions. Traditional sequencing analysis pipelines are designed for detecting genetic variants or measuring gene expression, not for precisely mapping chromatin accessibility changes following hundreds of simultaneous CRISPR edits. The team had to develop computational methods that could distinguish signal from noise in these long-read sequencing datasets while accounting for the specific biochemical properties of DddA’s activity. This represents a growing trend in genomics where technological advances in wet-lab methods must be matched by equally sophisticated computational innovations.
Beyond Sickle Cell: Broader Therapeutic Applications
While the sickle cell disease application demonstrates immediate clinical relevance, the platform’s true potential lies in its generalizability to any genetic disorder with noncoding regulatory elements. Most common diseases—from autoimmune disorders to neurodegenerative conditions—have genetic risk variants located in regulatory regions rather than protein-coding sequences. TDAC-seq could systematically test how these disease-associated variants alter chromatin accessibility across different cell types and developmental stages. This capability is particularly valuable for designing gene therapies that target regulatory elements rather than directly correcting mutations, potentially offering safer and more durable treatments for complex genetic conditions.
Transforming Drug Discovery and Development
The pharmaceutical industry has long struggled with understanding why certain genetic variants correlate with disease risk without knowing their functional consequences. TDAC-seq provides a direct way to test these variants systematically, potentially accelerating target identification and validation. More importantly, it enables researchers to screen multiple therapeutic strategies simultaneously in relevant cell types, moving beyond simple cell lines to primary cells and stem cell models. This could significantly reduce the high failure rates in early-stage drug development by providing more physiologically relevant data about how potential therapies actually affect gene regulation at the molecular level.
Scalability and Implementation Challenges
Despite its promise, TDAC-seq faces several practical challenges before widespread adoption. The method requires sophisticated molecular biology expertise and computational resources that may limit its accessibility to well-funded academic labs and pharmaceutical companies initially. Scaling the technology to screen thousands of regulatory elements across multiple cell types and conditions will require further optimization of both the wet-lab protocols and computational pipelines. Additionally, interpreting the functional consequences of observed chromatin accessibility changes remains complex, as the relationship between accessibility and gene expression isn’t always straightforward. The team’s planned expansion to more cell types will be crucial for establishing the platform’s broad utility across different biological contexts.
