Identification of genetic elements in metabolism by high-throughput mouse phenotyping

Area of Science:

• Genetics
• Metabolomics
• Systems Biology

Background:

• Metabolic diseases pose a global health challenge, with their genetic underpinnings not fully elucidated.
• Characterizing unannotated mammalian metabolic genes is crucial for advancing our understanding of metabolic disease etiology.

Purpose of the Study:

• To identify novel genes associated with metabolic phenotypes using a genome-wide approach.
• To uncover previously uncharacterized genes and their potential roles in metabolic diseases.
• To explore regulatory networks connecting genes involved in metabolic processes.

Main Methods:

• Analysis of metabolic phenotypic data from 2016 knockout mouse strains via the International Mouse Phenotyping Consortium (IMPC).
• Comparison of human orthologues of uncharacterized genes with data from five Genome-Wide Association Study (GWAS) consortia.
• Identification of common regulatory elements and transcription factor binding sites in gene promoters.

Main Results:

• 974 gene knockouts exhibited significant metabolic phenotypes.
• 429 genes showed no prior association with metabolism, and 51 genes were functionally unannotated.
• 23 candidate genes linked to uncharacterized genes were associated with metabolic diseases in human GWAS.
• Identification of a co-regulated gene network associated with metabolic phenotypes.

Conclusions:

• Systematic mouse phenotyping is effective in identifying novel genes involved in metabolic disease.
• The study provides a foundation for the functional annotation of the genome concerning metabolic functions.
• Uncovered gene networks offer new targets for understanding and potentially treating metabolic disorders.