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, 15 (1), 860

Genetic and Epigenetic Regulation of Gene Expression in Fetal and Adult Human Livers


Genetic and Epigenetic Regulation of Gene Expression in Fetal and Adult Human Livers

Marc Jan Bonder et al. BMC Genomics.


Background: The liver plays a central role in the maintenance of homeostasis and health in general. However, there is substantial inter-individual variation in hepatic gene expression, and although numerous genetic factors have been identified, less is known about the epigenetic factors.

Results: By analyzing the methylomes and transcriptomes of 14 fetal and 181 adult livers, we identified 657 differentially methylated genes with adult-specific expression, these genes were enriched for transcription factor binding sites of HNF1A and HNF4A. We also identified 1,000 genes specific to fetal liver, which were enriched for GATA1, STAT5A, STAT5B and YY1 binding sites. We saw strong liver-specific effects of single nucleotide polymorphisms on both methylation levels (28,447 unique CpG sites (meQTL)) and gene expression levels (526 unique genes (eQTL)), at a false discovery rate (FDR) < 0.05. Of the 526 unique eQTL associated genes, 293 correlated significantly not only with genetic variation but also with methylation levels. The tissue-specificities of these associations were analyzed in muscle, subcutaneous adipose tissue and visceral adipose tissue. We observed that meQTL were more stable between tissues than eQTL and a very strong tissue-specificity for the identified associations between CpG methylation and gene expression.

Conclusions: Our analyses generated a comprehensive resource of factors involved in the regulation of hepatic gene expression, and allowed us to estimate the proportion of variation in gene expression that could be attributed to genetic and epigenetic variation, both crucial to understanding differences in drug response and the etiology of liver diseases.


Figure 1
Figure 1
Study design and distribution of CpG sites. (A) Study design describing the investigated biomaterials and analyses performed. *) conservation compared across tissues; #) compared in fetal vs adult livers. (B) Distribution of the location of differentially methylated CpG sites between fetal and adult livers. The bar plot shows the percentage of differentially methylated CpG sites (y-axis) that are hypermethylated (black bars) or hypomethylated (grey bars) in fetal livers compared to adult livers in CpG islands, shores, shelves and other regions of the genome. (C) Distribution of differentially expressed and methylated genes depending on the relation to CpG islands. Pie charts illustrating the distribution of CpG island regions in case of significant increased or decreased gene expression and significant hyper- or hypomethylation.
Figure 2
Figure 2
Expression levels of transcription factors in fetal and adult livers. Box plots of the log2 transformed expression levels (y-axis) are shown for the adult and fetal liver samples (x-axis). The transcripts for HNF1A and HNF4A were expressed at significantly higher levels in the adult livers, while YY1, GATA1, STAT5A and STAT5B were expressed at higher levels in the fetal livers.
Figure 3
Figure 3
Distribution of the direction of the expression and methylation correlation coefficient. (A) Proportion of eQTM effects (y-axis) grouped by the absolute Spearman correlation coefficient. Grey and black colors represent negative and positive correlation between expression probe and methylation CpG site, respectively. (B) Proportion of eQTM effects (y-axis) grouped by the distance between expression probe and CpG site in kilobase pair (kb). Grey and black colors represent negative and positive correlation between expression probe and methylation CpG site, respectively.
Figure 4
Figure 4
Venn diagram of the overlap of QTLs in four tested tissues. The number of overlapping (A) eQTL, (B) meQTLs, (C) eQTMs in shown for adult human liver, VAT, SAT and muscle samples.

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    1. Sabatti C, Service SK, Hartikainen A-L, Pouta A, Ripatti S, Brodsky J, Jones CG, Zaitlen NA, Varilo T, Kaakinen M, Sovio U, Ruokonen A, Laitinen J, Jakkula E, Coin L, Hoggart C, Collins A, Turunen H, Gabriel S, Elliot P, McCarthy MI, Daly MJ, Järvelin M-R, Freimer NB, Peltonen L. Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet. 2009;41:35–46. doi: 10.1038/ng.271. - DOI - PMC - PubMed
    1. Qi L, Cornelis MC, Kraft P, Stanya KJ, Linda Kao WH, Pankow JS, Dupuis J, Florez JC, Fox CS, Paré G, Sun Q, Girman CJ, Laurie CC, Mirel DB, Manolio TA, Chasman DI, Boerwinkle E, Ridker PM, Hunter DJ, Meigs JB, Lee C-H, Hu FB, van Dam RM. Genetic variants at 2q24 are associated with susceptibility to type 2 diabetes. Hum Mol Genet. 2010;19:2706–2715. doi: 10.1093/hmg/ddq156. - DOI - PMC - PubMed
    1. Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat Genet. 2010;42:579–589. doi: 10.1038/ng.609. - DOI - PMC - PubMed
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