Back

Generation of a new Adar1p150-/- mouse demonstrates isoform-specific roles in embryonic development and adult homeostasis.

Liang, Z.; Walkley, C.; Heraud-Farlow, J.

2022-08-31 genetics
10.1101/2022.08.31.506069 bioRxiv
Show abstract

The RNA editing enzyme Adenosine deaminase acting on RNA 1 (ADAR1) is an essential regulator of innate immune activation by both cellular and viral dsRNA. Adenosine-to-Inosine (A-to-I) editing by ADAR1 modifies the sequence and structure of endogenous dsRNA and masks it from the cytoplasmic dsRNA sensor melanoma differentiation-associated protein 5 (MDA5), preventing innate immune activation. Loss of function mutations in ADAR are associated with rare autoinflammatory disorders including Aicardi-Goutieres Syndrome (AGS), defined by a constitutive systemic upregulation of type I interferon (IFN). The murine Adar gene encodes two protein isoforms with distinct functions: ADAR1p110 is constitutively expressed and localizes to the nucleus, whereas ADAR1p150 is primarily cytoplasmic and is inducible by IFN. Recent studies have demonstrated the critical requirement for ADAR1p150 to suppress innate immune activation by self dsRNAs, however, detailed in vivo characterization of the role of ADAR1p150 during development and in adult mice is lacking. We developed a new ADAR1p150-specific knockout mouse mutant based on a single nucleotide deletion that resulted in the loss of the ADARp150 protein without affecting ADAR1p110 expression. The Adar1p150-/- died embryonically at E11.5-E12.5 due to cell death in the fetal liver accompanied by an activated IFN response. Somatic loss of ADAR1p150 in adults was lethal and caused rapid hematopoietic failure, demonstrating an ongoing requirement for ADAR1p150 in vivo. The generation and characterization of this mouse model demonstrates the essential role of ADAR1p150 in vivo and provides a new tool for dissecting the functional differences between ADAR1 isoforms and their physiological contributions.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.