HCA Data Explorer

Cell type-specific and disease-associated eQTL in the human lung

Updated December 11, 2023

Common genetic variants confer substantial risk for chronic lung diseases, including pulmonary fibrosis (PF). Defining the genetic control of gene expression in a cell-type-specific and context-dependent manner is critical for understanding the mechanisms through which genetic variation influences complex traits and disease pathobiology. To this end, we performed single-cell RNA-sequencing of lung tissue from 67 PF and 49 unaffected donors. Employing a pseudo-bulk approach, we mapped expression quantitative trait loci (eQTL) across 38 cell types, observing both shared and cell type-specific regulatory effects. Further, we identified disease-interaction eQTL and demonstrated that this class of associations is more likely to be cell-type specific and linked to cellular dysregulation in PF. Finally, we connected PF risk variants to their regulatory targets in disease-relevant cell types. These results indicate that cellular context determines the impact of genetic variation on gene expression, and implicates context-specific eQTL as key regulators of lung homeostasis and disease.

Nicholas BanovichTranslational Genomics Research Institutenbanovich@tgen.org
Heini Natri1
Christina Del Azodi2
Lance Peter1
Chase Taylor3
Sagrika Chugh2
Robert Kendle1
Mei-i Chung1
David Flaherty3
Brittany Matlock3
Carla Calvi3
Timothy Blackwell4
Lorraine Ware3
Matthew Bacchetta3
Rajat Walia5
Ciara Shaver3
Jonathan Kropski4
Davis McCarthy2
Nicholas Banovich1
1Translational Genomics Research Institute
2St. Vincent’s Institute of Medical Research, Melbourne Integrative Genomics
3Vanderbilt University Medical Center
4Vanderbilt University Medical Center, Department of Veterans Affairs Medical Center
5Norton Thoracic Institute
Ida Zucchi

To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/7bc1f14b-5e64-4c7f-86b0-23596b97e2aa

Supplementary links are provided by contributors and represent items such as additional data which can’t be hosted here; code that was used to analyze this data; or tools and visualizations associated with this specific dataset.

1.https://github.com/tgen/banovichlab/tree/master/ILD_eQTL
GEO Series Accessions:INSDC Study Accessions:

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Analysis Portals

None

Project Label

eQTL-lung

Species

Homo sapiens

Sample Type

specimens

Anatomical Entity

lung

Organ Part

lung parenchyma

Selected Cell Types

Unspecified

Disease Status (Specimen)

8 disease statuses

Disease Status (Donor)

8 disease statuses

Development Stage

human adult stage

Library Construction Method

10x 5' v1

Nucleic Acid Source

single cell

Paired End

false

Analysis Protocol

processed_matrix_generation, pseudo_bulk, raw_matrix_generation

File Format

6 file formats

Cell Count Estimate

475.0k

Donor Count

92
fastq.gz254 file(s)mtx.gz127 file(s)rds.gz5 file(s)tar.gz1 file(s)tsv.gz254 file(s)xlsx1 file(s)