Identification of candidate genes encoding an LDL-C QTL in baboons

Abstract

Cardiovascular disease (CVD) is the leading cause of death in developed countries, and dyslipidemia is a major risk factor for CVD. We previously identified a cluster of quantitative trait loci (QTL) on baboon chromosome 11 for multiple, related quantitative traits for serum LDL-cholesterol (LDL-C). Here we report differentially regulated hepatic genes encoding an LDL-C QTL that influences LDL-C levels in baboons. We performed hepatic whole-genome expression profiling for LDL-C-discordant baboons fed a high-cholesterol, high-fat (HCHF) diet for seven weeks. We detected expression of 117 genes within the QTL 2-LOD support interval. Three genes were differentially expressed in low LDL-C responders and 8 in high LDL-C responders in response to a HCHF diet. Seven genes (ACVR1B, CALCOCO1, DGKA, ERBB3, KRT73, MYL6B, TENC1) showed discordant expression between low and high LDL-C responders. To prioritize candidate genes, we integrated miRNA and mRNA expression profiles using network tools and found that four candidates (ACVR1B, DGKA, ERBB3, TENC1) were miRNA targets and that the miRNAs were inversely expressed to the target genes. Candidate gene expression was validated using QRT-PCR and Western blotting. This study reveals candidate genes that influence variation in LDL-C in baboons and potential genetic mechanisms for further investigation.

Keywords: cardiovascular disease; diet-responsive liver gene expression; dyslipidemia; low density lipoprotein-cholesterol.

Fig. 1.

Cluster of QTLs for multiple LDL-C traits on baboon chr 11, the ortholog of human chr 12q13.13-q14.1. The lower x axis denotes the chromosome in centmorgans (cM), and the upper x axis shows the order and location of microsatellite markers in the baboon genome (14). The LOD are shown on the y axis. Lines in the legend represent peaks of detected QTLs for each LDL-C trait. The box indicates the 2-LOD drop interval for the predominant QTL (Lmed-C). This figure has been modified from Ref. .

Fig. 2.

miRNA-mRNA interaction module in high-LDL-C responder baboons. Shown are candidate genes and miRNAs differentially expressed in response to HCHF diet challenge. Genes and miRNAs are represented as nodes. Red nodes indicate upregulated genes, and green nodes denote downregulated miRNAs. The intensity of the color indicates the degree of differential expression. Numerals below each colored node represent expression fold-change and P-values. The molecular relationship between nodes is represented as a line (edge); arrows indicate the direction of interaction.

Fig. 3.

Validation of gene expression in response to HCHF diet. The x axis shows gene IDs, and the y axis denotes gene expression normalized to 18S rRNA. Bars represent standard errors. *P ≤ 0.05.

Fig. 4.

Quantification of TENC1 protein expressed in response to HCHF diet in low and high LDL-C baboon livers. The y axis denotes protein expression normalized to β-actin; bars represent standard errors. *P ≤ 0.05.

Fig. 5.

Schematic representation of AKT1/GSK-3β and ACVR1B/SMAD signaling pathways regulation in response to HCHF diet. Major genes in the pathways are shown. Red boxes represent candidate genes in the LDL-C QTL interval. RTK, receptor tyrosine kinase; TENC1, tensin-like C1 domain containing phosphatase; DGKA, diacylglycerol kinase α; DG, diacylglycerol; ERBB2/3, epidermal growth factor receptor 2/3; PIP2/3, phosphatidylinositol bi/triphosphate; PI3K, phosphoinositide 3-kinase; AKT1, protein kinase B α; GSK3β, glycogen synthase kinase 3-β; ACVR1B/2B, activin A receptor, type IB/IIB; SMAD, mothers against decapentaplegic; CTNNB1, β-catennin; TCF/LEF, T-cell-specific/lymphoid enhancer factor; CDKN2A, cyclin-dependent kinase inhibitor 2A; SREBP2, sterol regulatory element-binding transcription factor 2. Red arrows indicate gene expression response to the HCHF diet in low LDL-C responders, and green arrows indicate gene expression response to the HCHF diet in high LDL-C responders.