Dataset Information

Massively parallel phenotyping of coding variants in cancer with Perturb-seq

ABSTRACT: Genome sequencing studies have identified millions of somatic variants in cancer, but it remains challenging to predict the phenotypic impact of most. Experimental approaches to distinguish impactful variants often use phenotypic assays that report on predefined gene-specific functional effects in bulk cell populations. Here, we develop an approach to functionally assess variant impact in single cells by pooled Perturb-seq. We measured the impact of 200 TP53 and KRAS variants on RNA profiles in over 300,000 single lung cancer cells, and used the profiles to categorize variants into phenotypic subsets to distinguish gain-of-function, loss-of-function and dominant negative variants, which we validated by comparison with orthogonal assays. We discovered that KRAS variants did not merely fit into discrete functional categories, but spanned a continuum of gain-of-function phenotypes, and that their functional impact could not have been predicted solely by their frequency in patient cohorts. Our work provides a scalable, gene-agnostic method for coding variant impact phenotyping, with potential applications in multiple disease settings.

ORGANISM(S): Homo sapiens

PROVIDER: GSE161824 | GEO | 2021/10/01

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: The identification of causal variants responsible for disease associations from genome-wide association studies (GWAS) facilitates functional understanding of the disease mechanisms implicated by GWAS. One of the earliest GWAS associations to COPD spans an intragenic region within FAM13A, but the causal variants at this loci have not yet been identified. Massively parallel reporter assays (MPRA) can be used to prioritize functional regulatory variants in a high-throughput manner. Methods: We used an integrated approach using fine-mapping in over 10,000 subjects from COPD GWAS studies, two MPRA experiments, traditional reporter assays, chromatin conformation capture, and CRISPR-based gene editing to characterize COPD-associated regulatory variants in FAM13A in human bronchial epithelial cell lines. Results: Conditional genetic association and fine mapping analyses identified two independent COPD association signals in FAM13A. MPRA identified 45 common functional regulatory variants, and six COPD-associated putative functional variants were prioritized for further functional investigation. Three variants demonstrated significant activity in traditional reporter assays, and one variant, rs2013701, was selected for further testing in the endogenous genomic context based on a direction of effect consistent with postulated mechanisms of FAM13A-mediated COPD susceptibility. CRISPR-based genome editing for this variant confirmed allele-specific effects on FAM13A expression and altered rates of cellular proliferation, providing multiple levels of functional characterization for this COPD-associated variant. Conclusions: Comprehensive screening for regulatory variants near FAM13A identified the presence of extensive functional regulatory variation within a 250kb window of FAM13A in HBECs. Focused functional evaluation of the COPD-associated functional variants in LD with the two independent association signals in this region prioritized the common variant rs2013701, for which multiple parallel lines of functional evidence confirm allelic effects on FAM13A regulation.

Dataset Information

Massively parallel phenotyping of coding variants in cancer with Perturb-seq

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets