Dataset Information

Human variation in population-wide gene expression data predicts gene perturbation phenotype.

ABSTRACT: Population-scale datasets of healthy individuals capture genetic and environmental factors influencing gene expression. The expression variance of a gene of interest (GOI) can be exploited to set up a quasi loss- or gain-of-function "in population" experiment. We describe here an approach, huva (human variation), taking advantage of population-scale multi-layered data to infer gene function and relationships between phenotypes and expression. Within a reference dataset, huva derives two experimental groups with LOW or HIGH expression of the GOI, enabling the subsequent comparison of their transcriptional profile and functional parameters. We demonstrate that this approach robustly identifies the phenotypic relevance of a GOI allowing the stratification of genes according to biological functions, and we generalize this concept to almost 16,000 genes in the human transcriptome. Additionally, we describe how huva predicts monocytes to be the major cell type in the pathophysiology of STAT1 mutations, evidence validated in a clinical cohort.

SUBMITTER: Bonaguro L

PROVIDER: S-EPMC9614568 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Human variation in population-wide gene expression data predicts gene perturbation phenotype.

Bonaguro Lorenzo L Schulte-Schrepping Jonas J Carraro Caterina C Sun Laura L LL Reiz Benedikt B Gemünd Ioanna I Saglam Adem A Rahmouni Souad S Georges Michel M Arts Peer P Hoischen Alexander A Joosten Leo A B LAB van de Veerdonk Frank L FL Netea Mihai G MG Händler Kristian K Mukherjee Sach S Ulas Thomas T Schultze Joachim L JL Aschenbrenner Anna C AC

iScience 20221012 11

Population-scale datasets of healthy individuals capture genetic and environmental factors influencing gene expression. The expression variance of a gene of interest (GOI) can be exploited to set up a quasi loss- or gain-of-function "in population" experiment. We describe here an approach, huva (human variation), taking advantage of population-scale multi-layered data to infer gene function and relationships between phenotypes and expression. Within a reference dataset, huva ...[more]

PMID: 36310583

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Project description:Chromosomal aneuploidy is a defining feature of carcinomas and results in tumor-entity specific genomic imbalances. For instance, most sporadic colorectal carcinomas carry extra copies of chromosome 7, an aneuploidy that emerges already in premalignant adenomas, and is maintained throughout tumor progression and in derived cell lines. A comprehensive understanding on how chromosomal aneuploidy affects nuclear organization and gene expression, i.e., the nucleome, remains elusive. We now analyzed a cell line established from healthy colon mucosa with a normal karyotype (46,XY) and its isogenic derived cell line that acquired an extra copy of chromosome 7 as its sole anomaly (47,XY,+7). We studied structure/function relationships consequent to aneuploidization using genome-wide chromosome conformation capture (Hi-C), RNA sequencing and protein profiling. The gain of chromosome 7 resulted in an increase of transcript levels of resident genes as well as genome-wide gene and protein expression changes. The Hi-C analysis showed that the extra copy of chromosome 7 is reflected in more interchromosomal contacts between the triploid chromosomes. Chromatin organization changes are observed genome-wide, as determined by changes in A/B compartmentalization and topologically associating domain (TAD) boundaries. Most notably, chromosome 4 shows a profound loss of chromatin organization, and chromosome 14 contains a large A/B compartment switch region, concurrent with resident gene expression changes. No changes to the nuclear position of the additional chromosome 7 territory were observed when measuring distances of chromosome painting probes by interphase FISH. Genome and protein data showed enrichment in signaling pathways crucial for malignant transformation, such as the HGF/MET-axis. We conclude that a specific chromosomal aneuploidy has profound impact on nuclear structure and function, both locally and genome-wide. Our study provides a benchmark for the analysis of cancer nucleomes with complex karyotypes.

Dataset Information

Human variation in population-wide gene expression data predicts gene perturbation phenotype.

Publications

Human variation in population-wide gene expression data predicts gene perturbation phenotype.

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