Last updated:
Author(s):
Eric Van Buren, Yi Zhang, Xihao Li, Margaret Sunitha Selvaraj, Zilin Li, Hufeng Zhou, Nicholette D. Palmer, Donna K. Arnett, John Blangero, Eric Boerwinkle, Brian E. Cade, Jenna C. Carlson, April P. Carson, Yii-Der Ida Chen, Joanne Curran, Ravindranath Duggirala, Myriam Fornage, Nora Franceschini, Misa Graff, Charles Gu, Xiuqing Guo, Jiang He, Nancy Heard-Cosa, Lifang Hou, Yi-Jen Hung, Rita R. Kalyani, Sharon L. R. Kardia, Eimear Kenny, Charles Kooperberg, Brian G. Kral, Leslie Lange, Dan Levy, Changwei Li, Simin Liu, Donald Lloyd-Jones, Ruth J. F. Loos, Ani W. Manichaikul, Lisa Warsinger Martin, Rasika Mathias, Ryan L. Minster, Braxton D. Mitchell, Josyf C. Mychaleckyj, Take Naseri, Kari North, Jeff O'Connell, James A. Perry, Patricia A. Peyser, Bruce M. Psaty, Laura M. Raffield, Ramachandran S. Vasan, Susan Redline, Alex P. Reiner, Stephen S. Rich, Jennifer A. Smith, Brian Spitzer, Hua Tang, Kent D. Taylor, Russell Tracy, Satupa'itea Viali, Lisa Yanek, Wei Zhao, Jerome I. Rotter, Gina M. Peloso, Pradeep Natarajan, Xihong Lin
Publish date:
31 December 2025
Journal:
Nature Methods
PubMed ID:
41476111

Abstract

Understanding how rare genetic variants influence complex traits remains a major challenge, particularly when these variants lie in noncoding regions of the genome. The effects of variants within candidate cis-regulatory elements (cCREs) often depend on the cell type, making interpretation difficult. Here we introduce cellSTAAR, which integrates whole-genome sequencing data with single-cell assay for transposase-accessible chromatin using sequencing data to capture variability in chromatin accessibility across cell types via the construction of cell-type-specific functional annotations and regulatory elements. To reflect the uncertainty in cCRE-gene linking, cellSTAAR uses a comprehensive strategy to link cCREs to their target genes. We applied cellSTAAR to data from the Trans-Omics for Precision Medicine consortium (n ≈ 60,000) and replicated our findings using the UK Biobank (n ≈ 190,000). Across four lipid traits, cellSTAAR improved the detection of biologically meaningful associations and enhanced biological interpretability. These results demonstrate the potential of cell-type-aware approaches to boost discovery in rare variant whole-genome sequencing association studies.

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We aim to develop and apply a suite of scalable, powerful, and robust tools that can further identify the genomic determinants of health and disease,…

Institution:
Harvard School of Public Health, United States of America

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