Biology subjects

Kartha, V. K.

Publications and source records attributed to Kartha, V. K..

6 recordsLinked to original sources

bioRxiv2023

Cell of origin epigenetic priming determines susceptibility to Tet2 mutation

Hematopoietic stem cell mutations can result in clonal hematopoiesis (CH) but the clinical outcomes are heterogeneous. The nature of the founder mutation and secondary mutations likely drive emergent neoplastic disease. We investigated how the state of the cell of origin where the Tet2 mutation occurs affects susceptibility to that commonly occurring CH mutation. Here, we provide evidence that risk is written in the epigenome of the cell of origin. By characterizing cell states that underlie myeloid differentiation and linking this information to an inducible system to assess myeloid progenitor clones, we provide evidence that epigenetic markers of the cell where Tet2 mutation occurs stratifies clonal behaviors. Specifically, Sox4 fosters a global cell state of high sensitization towards Tet2 KO. Using GMP and primary HSC models, we show that Sox4 promotes cell dedifferentiation, alters cell metabolism and increases the in vivo clonal output of mutant cells. Our results validate the hypothesis that epigenetic features can predispose specific clones for dominance and explain why an identical mutation can result in different outcomes.

cancer biology↗

bioRxiv2023

Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements

Cis-regulatory elements control gene expression and are dynamic in their structure, reflecting changes to the composition of diverse effector proteins over time1-3. Here we sought to connect the structural changes at cis-regulatory elements to alterations in cellular fate and function. To do this we developed PRINT, a computational method that uses deep learning to correct sequence bias in chromatin accessibility data and identifies multi-scale footprints of DNA-protein interactions. We find that multi-scale footprints enable more accurate inference of TF and nucleosome binding. Using PRINT with single-cell multi-omics, we discover wide-spread changes to the structure and function of candidate cis-regulatory elements (cCREs) across hematopoiesis, wherein nucleosomes slide, expose DNA for TF binding, and promote gene expression. Activity segmentation using the co-variance across cell states identifies "sub-cCREs" as modular cCRE subunits of regulatory DNA. We apply this single-cell and PRINT approach to characterize the age-associated alterations to cCREs within hematopoietic stem cells (HSCs). Remarkably, we find a spectrum of aging alterations among HSCs corresponding to a global gain of sub-cCRE activity while preserving cCRE accessibility. Collectively, we reveal the functional importance of cCRE structure across cell states, highlighting changes to gene regulation at single-cell and single-base-pair resolution.

genomics↗

bioRxiv2021

Functional Inference of Gene Regulation using Single-Cell Multi-Omics

Cells require coordinated control over gene expression when responding to environmental stimuli. Here, we apply scATAC-seq and scRNA-seq in resting and stimulated human blood cells. Collectively, we generate [~]91,000 single-cell profiles, allowing us to probe the cis-regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multi-omic data, we develop FigR - a framework to computationally pair scATAC-seq with scRNA-seq cells, connect distal cis-regulatory elements to genes, and infer gene regulatory networks (GRNs) to identify candidate TF regulators. Utilizing these paired multi-omic data, we define Domains of Regulatory Chromatin (DORCs) of immune stimulation and find that cells alter chromatin accessibility prior to production of gene expression at time scales of minutes. Further, the construction of the stimulation GRN elucidates TF activity at disease-associated DORCs. Overall, FigR enables the elucidation of regulatory interactions across single-cell data, providing new opportunities to understand the function of cells within tissues.

genomics↗

bioRxiv2020

Chromatin potential identified by shared single cell profiling of RNA and chromatin

Cell differentiation and function are regulated across multiple layers of gene regulation, including the modulation of gene expression by changes in chromatin accessibility. However, differentiation is an asynchronous process precluding a temporal understanding of the regulatory events leading to cell fate commitment. Here, we developed SHARE-seq, a highly scalable approach for measurement of chromatin accessibility and gene expression within the same single cell. Using 34,774 joint profiles from mouse skin, we develop a computational strategy to identify cis-regulatory interactions and define Domains of Regulatory Chromatin (DORCs), which significantly overlap with super-enhancers. We show that during lineage commitment, chromatin accessibility at DORCs precedes gene expression, suggesting changes in chromatin accessibility may prime cells for lineage commitment. We therefore develop a computational strategy (chromatin potential) to quantify chromatin lineage-priming and predict cell fate outcomes. Together, SHARE-seq provides an extensible platform to study regulatory circuitry across diverse cells within tissues.

genomics↗

bioRxiv2019

Droplet-based combinatorial indexing for massive scale single-cell epigenomics

While recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution, the throughput and quality of these methods have limited the widespread adoption of these technologies. Here, we describe a droplet microfluidics platform for single-cell assay for transposase accessible chromatin (scATAC-seq) for high-throughput single-cell profiling of chromatin accessibility. We use this approach for the unbiased discovery of cell types and regulatory elements within the mouse brain. Further, we extend the throughput of this approach by pairing combinatorial indexing with droplet microfluidics, enabling single-cell studies at a massive scale. With this approach, we measure chromatin accessibility across resting and stimulated human bone marrow derived cells to reveal changes in the cis- and trans- regulatory landscape across cell types and upon stimulation conditions at single-cell resolution. Altogether, we describe a total of 502,207 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

genomics↗

bioRxiv2017

CaDrA: A computational framework for performing candidate driver analyses using binary genomic features

Identifying complementary genetic drivers of a given phenotypic outcome is a challenging task that is important to gaining new biological insight and discovering targets for disease therapy. Existing methods aimed at achieving this task lack analytical flexibility. We developed Candidate Driver Analysis or CaDrA, a framework to identify functionally-relevant subsets of binary genomic features that, together, are associated with a specific outcome of interest. We evaluate CaDrAs sensitivity and specificity for typically-sized multi-omic datasets, and demonstrate CaDrAs ability to identify both known and novel drivers of oncogenic activity in cancer cell lines and primary tumors.

bioinformatics↗