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Determinants of expression variability.

ABSTRACT: The amount of tissue-specific expression variability (EV) across individuals is an essential characteristic of a gene and believed to have evolved, in part, under functional constraints. However, the determinants and functional implications of EV are only beginning to be investigated. Our analyses based on multiple expression profiles in 41 primary human tissues show that a gene's EV is significantly correlated with a number of features pertaining to the genomic, epigenomic, regulatory, polymorphic, functional, structural and network characteristics of the gene. We found that (i) EV of a gene is encoded, in part, by its genomic context and is further influenced by the epigenome; (ii) strong promoters induce less variable expression; (iii) less variable gene loci evolve under purifying selection against copy number polymorphisms; (iv) genes that encode inherently disordered or highly interacting proteins exhibit lower variability; and (v) genes with less variable expression are enriched for house-keeping functions, while genes with highly variable expression tend to function in development and extra-cellular response and are associated with human diseases. Thus, our analysis reveals a number of potential mediators as well as functional and evolutionary correlates of EV, and provides new insights into the inherent variability in eukaryotic gene expression.

SUBMITTER: Alemu EY

PROVIDER: S-EPMC3973347 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Determinants of expression variability.

Alemu Elfalem Y EY Carl Joseph W JW Corrada Bravo Héctor H Hannenhalli Sridhar S

Nucleic acids research 20140115 6

The amount of tissue-specific expression variability (EV) across individuals is an essential characteristic of a gene and believed to have evolved, in part, under functional constraints. However, the determinants and functional implications of EV are only beginning to be investigated. Our analyses based on multiple expression profiles in 41 primary human tissues show that a gene's EV is significantly correlated with a number of features pertaining to the genomic, epigenomic, regulatory, polymorp ...[more]

PMID: 24435799

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Project description:ObjectivesWe examined state variations in assisted living (AL) regulatory policies for admission/retention, staffing/training, medication management, and dementia care. Factors associated with domain-specific and overall regulatory stringency were identified.DesignThis observational study used the following data sources: 2019 review of state AL regulations; 2019 national inventory of AL communities; 2014 Government Accountability Office survey of Medicaid agencies; 2016 Genworth Cost of Care Survey; and the 2018 Nursing Home Compare.Setting and participantsFinal analyses included 46 states (excluding Alaska, Kentucky, Louisiana, and West Virginia) and the District of Columbia.MethodsFor each regulatory domain of interest (dependent variables), we generated policy scores by conducting content analysis of state regulatory databases. States were assigned points for presence of each policy (eg, staff training). The number of points assigned to each policy was divided by the total possible number of policy-related points, producing state stringency scores (between 0% and 100%) for each policy domain. Independent variables included market-level characteristics (eg, AL monthly cost), state generosity (eg, proportion of Medicaid aged using AL services), quality of care (eg, percent of nursing homes with few deficiencies), and others. Descriptive analyses and multivariable logistic regression models with stepwise selection were used.ResultsWe found significant variations in all policy domains across states. No single policy appeared to clearly dominate a state's rank. AL bed supply, monthly AL cost, proportion of Medicaid beneficiaries receiving AL services, and other variables were significantly associated with regulatory stringency of the domains examined.Conclusions and implicationsThere were substantial variations in regulatory stringency across states. Several market and state generosity measures were identified as potential determinants of stringency, but the direction of these associations appeared to depend on what was being regulated. Future studies should examine how regulatory stringency affects access to and care quality in ALs.

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Determinants of expression variability.

Publications

Determinants of expression variability.

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