Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene

2Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue, defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with body mass index and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will throw light on the mechanism by which Sgcg may protect from the development of obesity.

References Powered by Scopus

Analysis of relative gene expression data using real-time quantitative PCR and the 2<sup>-ΔΔC</sup>T method

149923Citations
N/AReaders
Get full text

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm

5432Citations
N/AReaders
Get full text

Diagnosis and classification of diabetes mellitus

0
4589Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Identification of shared genetic architecture between non-alcoholic fatty liver disease and type 2 diabetes: A genome-wide analysis

6Citations
N/AReaders
Get full text

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

4Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Kuhn, T., Kaiser, K., Lebek, S., Altenhofen, D., Knebel, B., Herwig, R., … Al-Hasani, H. (2022). Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene. Human Molecular Genetics, 31(23), 4019–4033. https://doi.org/10.1093/hmg/ddac150

Readers' Seniority

Tooltip

Professor / Associate Prof. 1

50%

Researcher 1

50%

Readers' Discipline

Tooltip

Agricultural and Biological Sciences 1

25%

Biochemistry, Genetics and Molecular Bi... 1

25%

Veterinary Science and Veterinary Medic... 1

25%

Arts and Humanities 1

25%

Save time finding and organizing research with Mendeley

Sign up for free