Dataset Information

Human Epistatic Interaction Controls IL7R Splicing and Increases Multiple Sclerosis Risk.

ABSTRACT: Multiple sclerosis (MS) is an autoimmune disorder where T cells attack neurons in the central nervous system (CNS) leading to demyelination and neurological deficits. A driver of increased MS risk is the soluble form of the interleukin-7 receptor alpha chain gene (sIL7R) produced by alternative splicing of IL7R exon 6. Here, we identified the RNA helicase DDX39B as a potent activator of this exon and consequently a repressor of sIL7R, and we found strong genetic association of DDX39B with MS risk. Indeed, we showed that a genetic variant in the 5' UTR of DDX39B reduces translation of DDX39B mRNAs and increases MS risk. Importantly, this DDX39B variant showed strong genetic and functional epistasis with allelic variants in IL7R exon 6. This study establishes the occurrence of biological epistasis in humans and provides mechanistic insight into the regulation of IL7R exon 6 splicing and its impact on MS risk.

SUBMITTER: Galarza-Munoz G

PROVIDER: S-EPMC5456452 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Human Epistatic Interaction Controls IL7R Splicing and Increases Multiple Sclerosis Risk.

Galarza-Muñoz Gaddiel G Briggs Farren B S FBS Evsyukova Irina I Schott-Lerner Geraldine G Kennedy Edward M EM Nyanhete Tinashe T Wang Liuyang L Bergamaschi Laura L Widen Steven G SG Tomaras Georgia D GD Ko Dennis C DC Bradrick Shelton S SS Barcellos Lisa F LF Gregory Simon G SG Garcia-Blanco Mariano A MA

Cell 20170301 1

Multiple sclerosis (MS) is an autoimmune disorder where T cells attack neurons in the central nervous system (CNS) leading to demyelination and neurological deficits. A driver of increased MS risk is the soluble form of the interleukin-7 receptor alpha chain gene (sIL7R) produced by alternative splicing of IL7R exon 6. Here, we identified the RNA helicase DDX39B as a potent activator of this exon and consequently a repressor of sIL7R, and we found strong genetic association of DDX39B with MS ris ...[more]

PMID: 28340352

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Project description:An epistatic interaction between two genes occurs when the phenotypic impact of one gene depends on another gene, often exposing a functional association between them. Due to experimental scalability and to evolutionary significance, abundant work has been focused on studying how epistasis affects cellular growth rate, most notably in yeast. However, epistasis likely influences many different phenotypes, affecting our capacity to understand cellular functions, biochemical networks adaptation, and genetic diseases. Despite its broad significance, the extent and nature of epistasis relative to different phenotypes remain fundamentally unexplored. Here we use genome-scale metabolic network modeling to investigate the extent and properties of epistatic interactions relative to multiple phenotypes. Specifically, using an experimentally refined stoichiometric model for Saccharomyces cerevisiae, we computed a three-dimensional matrix of epistatic interactions between any two enzyme gene deletions, with respect to all metabolic flux phenotypes. We found that the total number of epistatic interactions between enzymes increases rapidly as phenotypes are added, plateauing at approximately 80 phenotypes, to an overall connectivity that is roughly 8-fold larger than the one observed relative to growth alone. Looking at interactions across all phenotypes, we found that gene pairs interact incoherently relative to different phenotypes, i.e. antagonistically relative to some phenotypes and synergistically relative to others. Specific deletion-deletion-phenotype triplets can be explained metabolically, suggesting a highly informative role of multi-phenotype epistasis in mapping cellular functions. Finally, we found that genes involved in many interactions across multiple phenotypes are more highly expressed, evolve slower, and tend to be associated with diseases, indicating that the importance of genes is hidden in their total phenotypic impact. Our predictions indicate a pervasiveness of nonlinear effects in how genetic perturbations affect multiple metabolic phenotypes. The approaches and results reported could influence future efforts in understanding metabolic diseases and the role of biochemical regulation in the cell.

Dataset Information

Human Epistatic Interaction Controls IL7R Splicing and Increases Multiple Sclerosis Risk.

Publications

Human Epistatic Interaction Controls IL7R Splicing and Increases Multiple Sclerosis Risk.

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