Epistasis of transcriptomes reveals synergism between transcriptional activators Hnf1alpha and Hnf4alpha

Abstract

The transcription of individual genes is determined by combinatorial interactions between DNA-binding transcription factors. The current challenge is to understand how such combinatorial interactions regulate broad genetic programs that underlie cellular functions and disease. The transcription factors Hnf1alpha and Hnf4alpha control pancreatic islet beta-cell function and growth, and mutations in their genes cause closely related forms of diabetes. We have now exploited genetic epistasis to examine how Hnf1alpha and Hnf4alpha functionally interact in pancreatic islets. Expression profiling in islets from either Hnf1a(+/-) or pancreas-specific Hnf4a mutant mice showed that the two transcription factors regulate a strikingly similar set of genes. We integrated expression and genomic binding studies and show that the shared transcriptional phenotype of these two mutant models is linked to common direct targets, rather than to known effects of Hnf1alpha on Hnf4a gene transcription. Epistasis analysis with transcriptomes of single- and double-mutant islets revealed that Hnf1alpha and Hnf4alpha regulate common targets synergistically. Hnf1alpha binding in Hnf4a-deficient islets was decreased in selected targets, but remained unaltered in others, thus suggesting that the mechanisms for synergistic regulation are gene-specific. These findings provide an in vivo strategy to study combinatorial gene regulation and reveal how Hnf1alpha and Hnf4alpha control a common islet-cell regulatory program that is defective in human monogenic diabetes.

Figure 1. Hnf1a and Hnf4a expression in mutant models.

(A,B) Expression of Hnf1a and Hnf4a mRNA in islets from (A) Hnf4a^pKO and (B) Hnf1a^+/− male mice. Results were normalized to Hprt mRNA and are expressed relative to littermate wild-type controls. * P<0.05.

Figure 2. Hnf1α and Hnf4α regulate a common set of genes.

(A) Correlation of mutant/wild-type Log2 gene expression ratios in Hnf4a^pKO versus Hnf1a^+/− islets. (B) Validation of 22 genes using gene-specific qPCR. (C) Heatmap of expression ratios in Hnf4a^pKO and Hnf1a^+/− islets for the 50 most downregulated genes in Hnf4a^pKO islets. (D) Expression of Hnf1a-dependent genes in Hnf4a^pKO islets. Grey dots represent average expression values of genes in Hnf4a^pKO versus control islets. We superimposed red dots to show the subset of genes downregulated in Hnf1a^+/− islets. (E) Expression of Hnf4a-dependent genes in Hnf1a^+/− islets. Grey dots are expression values of all genes, superimposed blue dots are the subset of genes downregulated in Hnf4a ^pKO islets.

Figure 3. Expression of Hnf1α targets is impaired in Hnf4a-deficient islets.

(A) Alternate models of Hnf1α and Hnf4α network structures that could potentially underlie the similar transcriptomes in Hnf4a^pKO and Hnf1a^+/− islets, and expected functional perturbation of Hnf1α bound genes in each case. (B) The analysis of previously reported , mouse liver binding datasets showed that Hnf1α and Hnf4α preferentially bind the same genes, as reported in human islets and liver. Hypergeometric distributions were tested to calculate significance values. (C) Hnf1α, Hnf4α and Hnf1α/Hnf4α binding were enriched in genes that were significantly downregulated 2-fold in Hnf4a^pKO and Hnf1a ^-/- islets. Hypergeometric distributions were tested to calculate significance values. (D) Most significant over-represented evolutionary conserved sequence element in 10 Kb surrounding transcription start sites of genes that were downregulated in Hnf4a^pKO islets. The canonical HNF1 matrix is shown below. Motifs matching Hnf4α, or Hnf1α and Hnf4α binding sequences were also overrepresented in genes downregulated in Hnf4a^pKO and Hnf1a ^-/- islets, respectively (not shown).

Figure 4. Epistasis reveals functional synergism between Hnf1α and Hnf4α.

(A) Schematic representation of the genetic approach used to test functional interactions between Hnf1a and Hnf4a in a hypothetical gene that is downregulated 50% of wild type values in both Hnf4a^pKO and Hnf1a^+/− islets. (B,C) Distribution of ε values (see results for explanation) for control genes (B), or for all genes that were downregulated in both single mutant mice (C). (D) Observed gene expression ratios in Hnf4a^pKO Hnf1a^+/− islets (white circles) and expected changes in a non-epistatic model (black circles) for each gene that was significantly downregulated in both single mutant mice.

Figure 5. Gene-specific mechanisms for functional synergism.

We tested Hnf1α binding in Hnf4a-deficient islets in 8 genes that are bound by Hnf1α and Hnf4α in wild type islets and are downregulated in Hnf1a and Hnf4a-deficient islets. Hnf1α binding in Hnf4a-deficient islets was unaltered in 5/8 genes examined, was partially reduced in two genes, and was abrogated in one gene. (A) Schematic representations of PCR products (black thick lines) used for Hnf1α and Hnf4α ChIPs, and high affinity HNF1 (red vertical lines) and HNF4 (blue vertical lines) binding sequences. (B) Gene expression in wild type and Hnf4a-deficient islets assayed by quantitative PCR. Results are normalized by expression levels of Actb mRNA, and are shown as fold-changes relative to wild type islets. (C,D) Hnf1α and Hnf4α binding in wild type (black bars) and Hnf4a-deficient (white bars) islets. Results are expressed as fold over Actb negative control regions. Tbp is shown as an independent negative control for both ChIP and gene expression studies. * P<0.05.

Figure 6. Model of the Hnf1α/Hnf4α regulatory network in pancreatic islets.

In islets, Hnf1α controls Hnf4a gene transcription, while both Hnf1α and Hnf4α activate common targets synergistically.