ArticlePLoS computational biology2010
Gene expression variability within and between human populations and implications toward disease susceptibility.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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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.
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Who cites it
58 citing papers in PubMed, 104 citations in OpenAlex.
- Article
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- Long-read transcriptomics of a diverse human cohort reveals ancestry bias in gene annotation.Nature communications · 2025Article
- Detecting and quantifying heterogeneity in susceptibility using contact tracing data.PLoS computational biology · 2024Article
- A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data.Nature communications · 2024Article
- Direct inference and control of genetic population structure from RNA sequencing data.Communications biology · 2023Article
- Characterizing the landscape of gene expression variance in humans.PLoS genetics · 2023Article
- Outlining the Clinical Profile ofGenes · 2023Article
- Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation.Molecular medicine (Cambridge, Mass.) · 2023Article
- A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data.bioRxiv : the preprint server for biology · 2023Article
- Endogenous miRNA-Based Innate-Immunity against SARS-CoV-2 Invasion of the Brain.International journal of molecular sciences · 2023Review
- Comparative studies of genomic and epigenetic factors influencing transcriptional variation in two insect species.G3 (Bethesda, Md.) · 2022Article
- MicroRNA biomarkers in frontotemporal dementia and to distinguish from Alzheimer's disease and amyotrophic lateral sclerosis.Neural regeneration research · 2022Review
- Article
- Natural variation of the cardiac transcriptome in humans.RNA biology · 2021Article
- Increased gene expression variability in BRCA1-associated and basal-like breast tumours.Breast cancer research and treatment · 2021Article
- Prioritizing and characterizing functionally relevant genes across human tissues.PLoS computational biology · 2021Article
- Variation of microRNA expression in the human placenta driven by population identity and sex of the newborn.BMC genomics · 2021Article
- Identification of human long noncoding RNAs associated with nonalcoholic fatty liver disease and metabolic homeostasis.The Journal of clinical investigation · 2021Article
- CRELD1 modulates homeostasis of the immune system in mice and humans.Nature immunology · 2020Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Variations in gene expression level might lead to phenotypic diversity across individuals or populations. Although many human genes are found to have differential mRNA levels between populations, the extent of gene expression that could vary within and between populations largely remains elusive. To investigate the dynamic range of gene expression, we analyzed the expression variability of ∼18, 000 human genes across individuals within HapMap populations. Although ∼20% of human genes show differentiated mRNA levels between populations, our results show that expression variability of most human genes in one population is not significantly deviant from another population, except for a small fraction that do show substantially higher expression variability in a particular population. By associating expression variability with sequence polymorphism, intriguingly, we found SNPs in the untranslated regions (5' and 3'UTRs) of these variable genes show consistently elevated population heterozygosity. We performed differential expression analysis on a genome-wide scale, and found substantially reduced expression variability for a large number of genes, prohibiting them from being differentially expressed between populations. Functional analysis revealed that genes with the greatest within-population expression variability are significantly enriched for chemokine signaling in HIV-1 infection, and for HIV-interacting proteins that control viral entry, replication, and propagation. This observation combined with the finding that known human HIV host factors show substantially elevated expression variability, collectively suggest that gene expression variability might explain differential HIV susceptibility across individuals.
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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.