Abstract
Dyslipidemia is a major risk factor for cardiovascular disease. Although many genetic factors have been unveiled, a large fraction of the phenotypic variance still needs further investigation. Chromosome 1 (Chr 1) harbors multiple gene loci that regulate blood lipid levels, and identifying functional genes in these loci has proved challenging. We constructed a mouse population, Chr 1 substitution lines (C1SLs), where only Chr 1 differs from the recipient strain C57BL/6J (B6), while the remaining chromosomes are unchanged. Therefore, any phenotypic variance between C1SLs and B6 can be attributed to the differences in Chr 1. In this study, we assayed plasma lipid and glucose levels in 13 C1SLs and their recipient strain B6. Through weighted gene co-expression network analysis of liver transcriptome and “guilty-by-association” study, eight associated modules of plasma lipid and glucose were identified. Further joint analysis of human genome wide association studies revealed 48 candidate genes. In addition, 38 genes located on Chr 1 were also uncovered, and 13 of which have been functionally validated in mouse models. These results suggest that C1SLs are ideal mouse models to identify functional genes on Chr 1 associated with complex traits, like dyslipidemia, by using gene co-expression network analysis.
Highlights
Plasma lipid levels of total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-C), Low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), are major contributors to cardiovascular diseases (Kathiresan et al, 2007)
A total of 24 modules were identified, with module M19 being significantly associated with blood lipid and glucose levels (Figure 3D)
Searching Mouse Genome Informatics database (MGI) database revealed that 13% (11 out of 84) of M19 genes are involved in blood lipid or glucose metabolism (Figure 4C), such as acyl-CoA thioesterase 11 (Acot11) (Zhang et al, 2012), cellular repressor of E1A-stimulated genes 1 (Creg1) (Tian et al, 2017), FIGURE 3 | Weighted gene co-expression network analysis of liver transcriptomes. (A) The soft thresholding index R2 (y-axis) as a function of different thresholding power b (x-axis). (B) Mean connectivity (y-axis) as a function of the power b (x-axis). (C) Twenty four co-expression modules were identified from the liver RNA-seq dataset
Summary
Plasma lipid levels of total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-C), Low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), are major contributors to cardiovascular diseases (Kathiresan et al, 2007). Current evidence demonstrates that both environmental and genetic factors contribute to these lipid levels. Discovery of the genetic regulators would be beneficial to determine individual susceptibility to dyslipidemia and eventually for developing gene therapies. Recent genome wide association studies (GWAS) in humans have linked hundreds of genetic loci to plasma lipid metabolism, including genes APOE, PCSK9, CETP, LIPC, LPL, and APOA5 (Willer et al, 2013a; Helgadottir et al, 2016). Significant achievements have been made, the identified genetic loci only explain a small portion of the phenotypic variance, suggesting most of the genetic regulators remain unknown
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