About

Irene Kaplow is an Assistant Professor and Principal Investigator at Carnegie Mellon University. She holds a B.S. in Mathematics from the Massachusetts Institute of Technology, an M.S. in Computer Science from Stanford University, and a Ph.D. in Computer Science from Stanford University. Her professional webpage is https://imk1.github.io/, and she can be contacted via ikaplow@andrew.cmu.edu. The page provides her academic background and current position but does not include detailed information about her research focus or key contributions.

Research topics

• Biology
• Evolutionary biology
• Genetics
• Medicine
• Computational biology
• Internal medicine
• Psychology
• Virology
• Neuroscience
• Mathematics

Selected publications

• Integrative analysis reveals extensive interactions among C2H2 zinc finger proteins at chromatin loop anchors

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-08

  articleOpen access

  Abstract Cys2-His2 -zinc-finger proteins (C2H2-ZFPs) form the largest class of human transcription factors, yet their potential role (s) in higher-order genome organization has remained largely poorly defined. To date, only a small number of family members, e.g., CTCF and YY1, have been shown to function in chromatin organization. Here, we examined the global relationship between C2H2-ZFPs and long-range chromatin interactions (LRIs). By integrating ChIP-seq datasets for 216 C2H2-ZFPs and genome-wide maps of chromatin looping, we observe that more than 40% of the human C2H2-ZFPs are significantly enriched at LRI anchors. We found that depletion of a subset of such C2H2-ZFPs is associated with altered expression of genes linked by the LRIs they occupy. To investigate whether protein-protein interactions (PPIs) contribute to this pattern, we generated a large-scale interactome using affinity purification followed by mass spectrometry experiments, encompassing 345 C2H2-ZFPs, and LUMIER binary interaction assays for 204 C2H2-ZFPs. We identified 1,732 binary interactions, suggesting extensive connectivity among the C2H2-ZFP family members. Integrative analysis of PPI, ChIP-seq, and chromatin interaction datasets revealed that interacting C2H2-ZFP pairs are significantly co-enriched at LRIs and frequently localize to either the same or opposing loop anchors. Finally, by correlating ChIP-seq with cancer mutational datasets, we observe that DNA-binding sites of ∼35% of LRI-associated C2H2-ZFPs overlap somatic mutations in cancer genomes. Together, our results reveal a widespread network of C2H2-ZFP interactions associated with chromatin loop anchors, providing an important resource for elucidating mechanisms regulating chromatin organization.

  PublisherOA PDFDOI

• A gene regulatory element modulates myosin expression and controls cardiomyocyte response to stress

  Genome Research · 2025-10-22

  articleOpen access

  A hallmark of heart disease is gene dysregulation and reactivation of fetal gene programs. Reactivation of these fetal programs has compensatory effects during heart failure, depending on the type and stage of the underlying cardiomyopathy. Thousands of putative cardiac gene regulatory elements have been identified that may control these programs, but their functions are largely unknown. Here, we profile genome-wide changes to gene expression and chromatin structure in cardiomyocytes derived from human pluripotent stem cells. We identify and characterize a gene regulatory element essential for regulating MYH6 expression, which encodes human fetal myosin. Using chromatin conformation assays in combination with epigenome editing, we find that gene regulation is mediated by a direct interaction between MYH6 and the enhancer. We also find that enhancer activation alters cardiomyocyte response to the hypertrophy-inducing peptide endothelin-1. Enhancer activation prevents polyploidization as well as changes in calcium dynamics and metabolism following stress with endothelin-1. Collectively, these results identify regulatory mechanisms of cardiac gene programs that modulate cardiomyocyte maturation, affect cellular stress response, and could serve as potential therapeutic targets.

  PublisherOA PDFDOI

• A gene regulatory element modulates myosin expression and controls cardiomyocyte response to stress

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-20

  preprintOpen access

  A hallmark of heart disease is gene dysregulation and reactivation of fetal gene programs. Reactivation of these fetal programs has compensatory effects during heart failure, depending on the type and stage of the underlying cardiomyopathy. Thousands of putative cardiac gene regulatory elements have been identified that may control these programs, but their functions are largely unknown. We profile genome-wide changes to gene expression and chromatin structure in cardiomyocytes derived from human pluripotent stem cells. We identify and characterize a gene regulatory element essential for the regulation of MYH6 , which encodes human fetal myosin. Using chromatin conformation assays in combination with epigenome editing, we find that gene regulation is mediated by direct interaction between MYH6 and the enhancer. We also find that enhancer activation alters cardiomyocyte response to the hypertrophy-inducing peptide endothelin-1. Enhancer activation prevents polyploidization and changes in calcium dynamics following stress with endothelin-1. Collectively, these results identify regulatory mechanisms of cardiac gene expression programs that modulate cardiomyocyte maturation, cellular stress response, and could serve as potential therapeutic targets.

  PublisherOA PDFDOI

• An in vivo systemic massively parallel platform for deciphering animal tissue-specific regulatory function

  Frontiers in Genetics · 2025-04-09 · 13 citations

  articleOpen access

  Introduction: Transcriptional regulation is an important process wherein non-protein coding enhancer sequences play a key role in determining cell type identity and phenotypic diversity. In neural tissue, these gene regulatory processes are crucial for coordinating a plethora of interconnected and regionally specialized cell types, ensuring their synchronized activity in generating behavior. Recognizing the intricate interplay of gene regulatory processes in the brain is imperative, as mounting evidence links neurodevelopment and neurological disorders to non-coding genome regions. While genome-wide association studies are swiftly identifying non-coding human disease-associated loci, decoding regulatory mechanisms is challenging due to causal variant ambiguity and their specific tissue impacts. Methods: Massively parallel reporter assays (MPRAs) are widely used in cell culture to study the non-coding enhancer regions, linking genome sequence differences to tissue-specific regulatory function. However, widespread use in animals encounters significant challenges, including insufficient viral library delivery and library quantification, irregular viral transduction rates, and injection site inflammation disrupting gene expression. Here, we introduce a systemic MPRA (sysMPRA) to address these challenges through systemic intravenous AAV viral delivery. Results: We demonstrate successful transduction of the MPRA library into diverse mouse tissues, efficiently identifying tissue specificity in candidate enhancers and aligning well with predictions from machine learning models. We highlight that sysMPRA effectively uncovers regulatory effects stemming from the disruption of MEF2C transcription factor binding sites, single-nucleotide polymorphisms, and the consequences of genetic variations associated with late-onset Alzheimer‘s disease. Conclusion: SysMPRA is an effective library delivering method that simultaneously determines the transcriptional functions of hundreds of enhancers in vivo across multiple tissues.

  PublisherDOI

• Challenges in Predicting Chromatin Accessibility Differences between Species

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-11-10

  preprintOpen accessSenior authorCorresponding

  Enhancers are transcriptional regulatory elements that help drive phenotypic diversity, yet they often undergo rapid sequence evolution despite functional conservation, posing a challenge for predicting their function across species. Machine learning models that predict quantitative enhancer activity using DNA sequence have not previously been evaluated for their ability to predict quantitative differences across orthologous regions. Here, we trained convolutional neural networks (CNNs) on a regression task to predict chromatin accessibility, which is a proxy for enhancer activity, in the liver across five mammals, and we developed a novel framework to evaluate cross-species performance. We demonstrated that training on multiple species improves model generalization to both species used in training and held-out species. However, the models consistently achieved poor performance in predicting quantitative differences in accessibility between species at orthologous regions. Our study highlights the challenges in using regression models to predict chromatin accessibility changes between species.

  PublisherDOI

• Vocal learning–associated convergent evolution in mammalian proteins and regulatory elements

  Science · 2024-02-29 · 34 citations

  articleOpen access

  Vocal production learning (“vocal learning”) is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat ( Rousettus aegyptiacus ) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

  PublisherOA PDFDOI

• Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer’s disease

  PLoS Computational Biology · 2024-08-26 · 3 citations

  articleOpen accessCorresponding

  Alzheimer's disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, and neuroinflammatory responses. Both resident microglia and peripheral immune cells have been associated with the immune component of AD. However, the relative contribution of resident and peripheral immune cell types to AD predisposition has not been thoroughly explored due to their similarity in gene expression and function. To study the effects of AD-associated variants on cis-regulatory elements, we train convolutional neural network (CNN) regression models that link genome sequence to cell type-specific levels of open chromatin, a proxy for regulatory element activity. We then use in silico mutagenesis of regulatory sequences to predict the relative impact of candidate variants across these cell types. We develop and apply criteria for evaluating our models and refine our models using massively parallel reporter assay (MPRA) data. Our models identify multiple AD-associated variants with a greater predicted impact in peripheral cells relative to microglia or neurons. Our results support their use as models to study the effects of AD-associated variants and even suggest that peripheral immune cells themselves may mediate a component of AD predisposition. We make our library of CNN models and predictions available as a resource for the community to study immune and neurological disorders.

  PublisherDOI

• ATAC-seq for human iPSC-CM following GSK3 inhibition v1

  2024-10-19

  preprintOpen access

  This protocol describes Omni ATAC-seq methods in human iPSC-CM following growth with or without GSK3 inhibition using CHIR99021.

  PublisherOA PDFDOI

• RNA-seq for human iPSC-CM following GSK3 inhibition v1

  2024-10-18

  preprintOpen access

  This protocol describes RNA-seq methods in human iPSC-CM following growth with or without GSK3 inhibition using CHIR99021.

  PublisherOA PDFDOI

• HiCAR for human iPSC-CM following enhancer perturbations v1

  2024-10-19

  preprintOpen access

  This protocol describes ATAC-seq methods in human iPSC-CM following growth with or without GSK3 inhibition using CHIR99021.

  PublisherOA PDFDOI

Frequent coauthors

• Kerstin Lindblad‐Toh

  Uppsala University

  106 shared

• Morgan Wirthlin

  Carnegie Mellon University

  103 shared

• Tomás Marquès‐Bonet

  Universitat Autònoma de Barcelona

  87 shared

• Alyssa J. Lawler

  Carnegie Mellon University

  87 shared

• Elinor K. Karlsson

  77 shared

• BaDoi N. Phan

  Carnegie Mellon University

  70 shared

• Andreas R. Pfenning

  Carnegie Mellon University

  68 shared

• Klaus‐Peter Koepfli

  Conservation Biology Institute

  68 shared

Labs

• The Kaplow LabPI

Education

• B.S., Mathematics with a minor in Biology

  Massachusetts Institute of Technology

  2010

• Ph.D., Computer Science

  Stanford University

  2017