Faculty, Staff and Student Publications

Authors

    Language

    English

    Publication Date

    5-23-2022

    Journal

    Genes

    DOI

    10.3390/genes13050929

    PMID

    35627314

    PMCID

    PMC9140347

    PubMedCentral® Posted Date

    5-23-2022

    PubMedCentral® Full Text Version

    Post-print

    Abstract

    Gene expression plays a key role in health and disease. Estimating the genetic components underlying gene expression can thus help understand disease etiology. Polygenic models termed "transcriptome imputation" are used to estimate the genetic component of gene expression, but these models typically consider only the cis regions of the gene. However, these cis-based models miss large variability in expression for multiple genes. Transcription factors (TFs) that regulate gene expression are natural candidates for looking for additional sources of the missing variability. We developed a hypothesis-driven approach to identify second-tier regulation by variability in TFs. Our approach tested two models representing possible mechanisms by which variations in TFs can affect gene expression: variability in the expression of the TF and genetic variants within the TF that may affect the binding affinity of the TF to the TF-binding site. We tested our TF models in whole blood and skeletal muscle tissues and identified TF variability that can partially explain missing gene expression for 1035 genes, 76% of which explains more than the cis-based models. While the discovered regulation patterns were tissue-specific, they were both enriched for immune system functionality, elucidating complex regulation patterns. Our hypothesis-driven approach is useful for identifying tissue-specific genetic regulation patterns involving variations in TF expression or binding.

    Keywords

    Binding Sites, Gene Expression Regulation, Immune System, Protein Binding, Transcription Factors, transcriptional regulation, transcriptome imputation, transcription factor polymorphism

    Published Open-Access

    yes

    Share

    COinS
     
     

    To view the content in your browser, please download Adobe Reader or, alternately,
    you may Download the file to your hard drive.

    NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.