Massively parallel functional dissection of regulatory elements

Thesis (Ph.D.)--University of Washington, 2012

Massively parallel decoding of mammalian regulatory sequences supports a flexible organizational model

Despite continual progress in the cataloging of vertebrate regulatory elements, little is known about their organization and regulatory architecture. Here we describe a massively parallel experiment to systematically test the impact of copy number, spacing, combination and order of transcription factor binding sites on gene expression. A complex library of ∼5,000 synthetic regulatory elements containing patterns from 12 liver-specific transcription factor binding sites was assayed in mice and in HepG2 cells. We find that certain transcription factors act as direct drivers of gene expression in homotypic clusters of binding sites, independent of spacing between sites, whereas others function only synergistically. Heterotypic enhancers are stronger than their homotypic analogs and favor specific transcription factor binding site combinations, mimicking putative native enhancers. Exhaustive testing of binding site permutations suggests that there is flexibility in binding site order. Our findings provide quantitative support for a flexible model of regulatory element activity and suggest a framework for the design of synthetic tissue-specific enhancers

Systematic Dissection of Coding Exons at Single Nucleotide Resolution Supports an Additional Role in Cell-Specific Transcriptional Regulation

<div><p>In addition to their protein coding function, exons can also serve as transcriptional enhancers. Mutations in these exonic-enhancers (eExons) could alter both protein function and transcription. However, the functional consequence of eExon mutations is not well known. Here, using massively parallel reporter assays, we dissect the enhancer activity of three liver eExons (<i>SORL1</i> exon 17, <i>TRAF3IP2</i> exon 2, <i>PPARG</i> exon 6) at single nucleotide resolution in the mouse liver. We find that both synonymous and non-synonymous mutations have similar effects on enhancer activity and many of the deleterious mutation clusters overlap known liver-associated transcription factor binding sites. Carrying a similar massively parallel reporter assay in HeLa cells with these three eExons found differences in their mutation profiles compared to the liver, suggesting that enhancers could have distinct operating profiles in different tissues. Our results demonstrate that eExon mutations could lead to multiple phenotypes by disrupting both the protein sequence and enhancer activity and that enhancers can have distinct mutation profiles in different cell types.</p></div

Functional enhancer assays.

<p>Bar charts representing the luciferase activity of 15 selected eExon candidates relative to the empty vector (<i>pGL4.23</i>) and the apolipoprotein E (ApoE) liver enhancer <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004592#pgen.1004592-Simonet1" target="_blank">[50]</a>, used as a positive control. Ten exons showed significant luciferase activity in HepG2 cells (A) and eight exons in mouse liver (B), when compared to the empty vector. The results represent the means ± standard deviation of 3–5 independent experiments (*p<0.05; t-test).</p

Regulatory profiles of eExons in mouse liver and HeLa cells.

<p>Estimated effect sizes of all possible nucleotide substitutions based on coefficients from position variant (gray bars) models for each eExon. Multiple linear regressions with sets of ten adjacent positions as predictors were used to analyze the F-statistic of these models that represent the extent to which the model is predictive of the outcome (blue shadow). Both log2 of fold change relative to reference sequence (left; y-axes) and F-statistic (right; y-axes) are plotted for each eExon in mouse liver (A–C) and HeLa cells (D–F): <i>SORL1</i> exon 17 (A,D), <i>TRAF3IP2</i> exon 2 (B,E) and <i>PPARG</i> exon 6 (C,F). Significant effect mutation clusters with a differential profile between mouse liver and HeLa cells that overlap predicted HNF4A binding sites are illustrated by blue dotted rectangles, while mutation clusters that overlap predicted AP-1 binding sites and remained unchanged in both experiments are marked by red dotted rectangles.</p

MPRA regulatory profiles of three liver eExons.

<p>(A–C) Estimated effect size of all possible nucleotide substitutions based on coefficients from a trivariate (A:green, C:blue, G:yellow, T:red) model are shown for all three liver eExons: (A) <i>SORL1</i> exon 17, (B) <i>TRAF3IP2</i> exon 2 and (C) <i>PPARG</i> exon 6. Effect sizes are shown only for positions where model coefficients had associated <i>P</i>-values≤0.01. (D, E) Mutation effect sizes in regions overlapping predicted TFBS in <i>SORL1</i> exon 17. A predicted HNF4A site at positions 259–272 (D; blue dashed box) and predicted AP-1 site at positions 322–327 (E; red dashed box) are shown along with the effect size for each possible substitution. The consensus TFBS (top colored motif) and the tested eExon sequence (black) are shown above. In E, SNV 325 G>C that increases the similarity to an AP-1 consensus sequence is shown in bold and the location of the donor splice site is also indicated.</p

HNF4A and AP-1 alter eExon enhancer activity.

<p>(A) All three eExons show enhancer activity in HEK293T cells only when co-transfected with HNF4A and/or AP-1, a heterodimeric protein composed of c-Fos and c-Jun. Co-transfection of both HNF-4 and AP-1 shows an additive effect in <i>SORL1</i> exon 17 but not in <i>TRAF3IP2</i> exon 2 and <i>PPARG</i> exon 6. Both HNF4A and AP-1 response elements show significant luciferase activity when transfected with HNF4A or AP-1 respectively. (B) eExon SNVs that alter AP-1 and HNF4A sites affect enhancer activity in HEK293T cells. For <i>SORL1</i> exon 17, SNVs overlapping predicted HNF4A (260G>T, 264G>A) and AP-1 (322T>G) sites had lower luciferase activity in HNF4A and/or AP-1 transfected cells, while SNVs (393A>T, 399T>A) coinciding with a predicted NF-1 TFBS had similar luciferase activity as the reference sequence. For <i>TRAF3IP2</i> exon 2, a SNV (373G>T) generating a predicted AP-1 site had higher luciferase activity in control as well as HNF4A and/or AP-1 transfected cells. SNVs 384T>A and 390T>A in <i>PPARG</i> exon 6 alter a predicted AP-1 site that did not reduce enhancer activity in AP-1 transfected cells. The luciferase activity results are relative to the Renilla activity and represent the means ± standard deviation of three independent experiments.</p