Evidence map›Paper›PMID 42039472›Full record

ArticlebioRxiv : the preprint server for biology2026

Single-cell full-length transcriptome of human lung reveals genetic effects on isoform regulation beyond gene-level expression.

Bolun Li, Thong Luong, Elelta Sisay, Jinhu Yin, Zixuan Eleanor Zhang, Maryam Vaziripour, Ju Hye Shin, Yongmei Zhao, Bao Tran, Jinyoung Byun and 20 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors.

Bolun LiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7078-7107
Thong LuongDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Elelta SisayDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jinhu YinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Zixuan Eleanor ZhangDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Maryam VaziripourCenter for Genomic and Precision Medicine, Texas A&M Health, Houston, TX, USA.
Ju Hye ShinDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Yongmei ZhaoNCI Sequencing Facility, Frederick, MD, USA.
Bao TranNCI Sequencing Facility, Frederick, MD, USA.
Jinyoung ByunDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.
Yafang LiDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.
Chia Han LeeDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Maura O'NeillNCI CCR Protein Characterization Laboratory, Frederick, MD, USA.
Thorkell AndressonNCI CCR Protein Characterization Laboratory, Frederick, MD, USA.
Yoon Soo ChangDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Steven GazalCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Maria Teresa LandiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Nathaniel RothmanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Erping LongInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Qing LanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Christopher I AmosDepartment of Internal Medicine, University of New Mexico, Albuquerque, NM, USA.
Anny Xiaobo ZhouDivision of Pulmonary and Critical Care, Department of Medicine; Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
Tongwu ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jin Gu LeeDepartment of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jianxin ShiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Nicholas MancusoCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Jun XiaCenter for Genomic and Precision Medicine, Texas A&M Health, Houston, TX, USA.
Haoyu ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Eun Young KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jiyeon ChoiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic regulation of splicing uniquely contributes to trait-associated genome-wide association studies (GWAS) signals. However, quantitative trait loci (QTL) analysis using short-read sequencing of bulk tissues fails to capture full-length and cell-type-specific isoforms. Here, we present an isoform-level lung cell atlas from 129 never-smoking Korean women using single-cell long-read RNA-sequencing, identifying abundant unannotated and cell-type-specific isoforms. Isoform-level signatures of 37 lung cell types display a larger difference and therefore improve cell-type classification compared to gene-level expression. Notably, isoform-QTLs (isoQTLs) detect unannotated and/or cell-type-specific isoforms with independent genetic regulation from expression-QTL (eQTL), supported by enriched splicing functional elements. IsoQTLs nominate susceptibility isoforms from previously unexplained lung function and cancer GWAS loci, via eQTL-independent signals. We highlight a potentially functional novel variant of

Identifiers

PMID42039472
PMCPMC13107204

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.