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DOI 10.1038/s41592-025-02919-5

Медицинская библиотека · Nature methods · 2025

cellSTAAR: incorporating single-cell-sequencing-based functional data to boost power in rare variant association testing of noncoding regions.

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

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Аннотация

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.

Для цитирования: Van Buren Eric, Zhang Yi, Li Xihao, Selvaraj Margaret Sunitha, Li Zilin, Zhou Hufeng, Palmer Nicholette D, Arnett Donna K, Blangero John, Boerwinkle Eric, Cade Brian E, Carlson Jenna C, Carson April P, Chen Yii-Der Ida, Curran Joanne, Duggirala Ravindranath, Fornage Myriam, Franceschini Nora, Graff Misa, Gu Charles, Guo Xiuqing, He Jiang, Heard-Cosa Nancy, Hou Lifang, Hung Yi-Jen, Kalyani Rita R, Kardia Sharon L R, Kenny Eimear, Kooperberg Charles, Kral Brian G, Lange Leslie, Levy Dan, Li Changwei, Liu Simin, Lloyd-Jones Donald, Loos Ruth J F, Manichaikul Ani W, Martin Lisa Warsinger, Mathias Rasika, Minster Ryan L, Mitchell Braxton D, Mychaleckyj Josyf C, Naseri Take, North Kari, O'Connell Jeff, Perry James A, Peyser Patricia A, Psaty Bruce M, Raffield Laura M, Vasan Ramachandran S, Redline Susan, Reiner Alex P, Rich Stephen S, Smith Jennifer A, Spitzer Brian, Tang Hua, Taylor Kent D, Tracy Russell, Viali Satupa'itea, Yanek Lisa, Zhao Wei, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Rotter Jerome I, Peloso Gina M, Natarajan Pradeep, Lin Xihong. cellSTAAR: incorporating single-cell-sequencing-based functional data to boost power in rare variant association testing of noncoding regions.. Nature methods. 2025. DOI: 10.1038/s41592-025-02919-5.

Предметные рубрики MeSH

HumansSingle-Cell AnalysisWhole Genome SequencingGenome-Wide Association StudyGenetic VariationRegulatory Sequences, Nucleic AcidChromatinPolymorphism, Single NucleotideGenome, Human
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