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. 2018 Jun 20;46(11):5455-5469.
doi: 10.1093/nar/gky244.

Transcription Start Site Analysis Reveals Widespread Divergent Transcription in D. Melanogaster and Core Promoter-Encoded Enhancer Activities

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Free PMC article

Transcription Start Site Analysis Reveals Widespread Divergent Transcription in D. Melanogaster and Core Promoter-Encoded Enhancer Activities

Sarah Rennie et al. Nucleic Acids Res. .
Free PMC article

Abstract

Mammalian gene promoters and enhancers share many properties. They are composed of a unified promoter architecture of divergent transcripton initiation and gene promoters may exhibit enhancer function. However, it is currently unclear how expression strength of a regulatory element relates to its enhancer strength and if the unifying architecture is conserved across Metazoa. Here we investigate the transcription initiation landscape and its associated RNA decay in Drosophila melanogaster. We find that the majority of active gene-distal enhancers and a considerable fraction of gene promoters are divergently transcribed. We observe quantitative relationships between enhancer potential, expression level and core promoter strength, providing an explanation for indirectly related histone modifications that are reflecting expression levels. Lowly abundant unstable RNAs initiated from weak core promoters are key characteristics of gene-distal developmental enhancers, while the housekeeping enhancer strengths of gene promoters reflect their expression strengths. The seemingly separable layer of regulation by gene promoters with housekeeping enhancer potential is also indicated by chromatin interaction data. Our results suggest a unified promoter architecture of many D. melanogaster regulatory elements, that is universal across Metazoa, whose regulatory functions seem to be related to their core promoter elements.

Figures

Figure 1.
Figure 1.
Fly regulatory elements are associated with divergent transcription initiation. (A, B) Genome browser views around FlyBase annotated TSSs of the Cg25C (also known as Col4a1) gene (A) and a vri intragenic dCP STARR-seq enhancer (B). DNase-seq, control CAGE, and exosome KD CAGE data are shown. All four replicates per CAGE condition are displayed (red: minus strand, blue: plus strand). For visibility reasons, the scales of CAGE signal differ between strands and are provided below each panel. See Supplementary Figures S8 and S9 for RT-qPCR validations. (C) Distributions of exosome sensitivity, ranging between 0 (insensitive) to 1 (CAGE expression not observed without exosome KD), for eRNAs (associated with dCP STARR-seq enhancers), FlyBase mRNAs, FlyBase ncRNAs and PROMPTs (upstream of and antisense to annotated FlyBase gene TSSs). (D) Cumulative fraction (vertical axis) of plus strand CAGE TCs that are within a certain distance (horizontal axis) of minus strand CAGE TCs. The percentages of divergent events are highlighted for distances of 250 and 500 bp.
Figure 2.
Figure 2.
Transcriptional directionality, expression level and exosome sensitivity reveal major groupings of D. melanogaster regulatory elements. (A) Manual labeling and properties of the six identified clusters of transcribed DHSs with similar transcriptional directionality, expression levels, and exosome sensitivities (displayed in box-and-whisker plots). DHS clusters associated with stable or unstable RNAs on their major strands are indicated above DHS cluster labels. See Supplementary Figure S4 for a schematic of the measures used for clustering and the strategy behind expression quantification of DHSs. The lower and upper hinges of boxes correspond to the first and third quartiles of data, respectively, and the whiskers extends to the largest and smallest data points no further away than 1.5 times the interquartile range. For improved visibility, outlier data points are not visualized. (B) The number of DHSs in each cluster that are in close proximity with divergent (head-to-head) FlyBase gene TSS pairs (divergent gene pair), stand-alone FlyBase gene TSSs (unidirectional gene), or distal from FlyBase gene TSSs. (C) The percentage of DHSs in each cluster that are overlapping with or are distal to called STARR-seq enhancers, broken up by those overlapping with hkCP enhancers, dCP enhancers or both classes.
Figure 3.
Figure 3.
DNA sequence elements impact the stability, directionality and expression strengths of regulatory elements. (A, B) Frequencies of RNA processing motifs (A: 5′ splice site, B: polyadenylation site) downstream of CAGE summits broken up by DHS class and strand. Vertical axes show the average number of predicted sites per bp within an increasing window size from the TSS (horizontal axis) in which the motif search was done. 0 indicates the expected hit frequency from random genomic background. (C) Histogram of de novo-assembled transcript counts (vertical axis), broken up by number of exons and associated DHS class. (D) Fraction of transcribed DHSs (vertical axis) with an identified core promoter element (TATA, Inr, DPE, or MTE) at a given position relative to the major (left panels) and minor (right panels) strand CAGE summits. (E) Fraction of transcribed DHSs within each DHS class (vertical axis) associated with at least one out of nine core promoter elements identified on one or both strands. In addition, the fraction of DHSs with no core promoter elements are shown (none). (F) Hierarchical Ward agglomerative clustering of motif match scores for the nine considered core promoter elements on major and minor strands of transcribed DHSs. Ten clusters of core promoter element compositions are shown. (G) DHS class enrichments, calculated as the fraction of DHSs in each DHS class associated with each core promoter element cluster versus the fraction of total transcribed DHSs, displayed in log2 scale enrichment, broken up by major and minor strand. See Supplementary Figure S13 for DHS class enrichments for all core promoter clusters.
Figure 4.
Figure 4.
PROMPT transcription is impeded by positional and core promoter element constraints. (A) Densities of the distances between DHS major strand CAGE summits and the closest upstream antisense FlyBase gene TSS (head-to-head composition) for unidirectional stable and unidirectional stable w/ PROMPT DHSs. (B) The number of divergent and unidirectional events (vertical axis) for CAGE TCs at various distances from the closest upstream antisense FlyBase gene TSS (head-to-head composition). Divergent events were defined as divergent TC summits within 500 bp. (C) Fraction of unidirectional stable and unidirectional stable w/ PROMPT DHSs positioned >2,000 bp from the closest upstream antisense FlyBase gene TSS having core promoter elements Inr, DRE, Trl, TATA, Ohler1, and Ohler6 on major and minor strands. (D) Densities (vertical axis) of distances between transcribed DHSs to TAD boundaries (horizontal axis) for unidirectional stable and unidirectional stable w/ PROMPT DHSs.
Figure 5.
Figure 5.
Histone modifications and architectural protein binding reflect enhancer potential. (A) Heat map representing DHS class proportions of binarised ChIP-chip data. Rows and columns are hierarchically clustered and binding is defined as at least one binding event observed within ±100 bp of the major strand CAGE summit. (B) Detailed binding enrichments for H3K4me3 at weak bidirectional unstable and unidirectional stable w/ PROMPT DHSs, broken up according to STARR-seq enhancer potential (overlapping either a hkCP or dCP enhancer), based on binding proportions within 5,000 bp from the CAGE summit. Grey represents background distribution based on randomized locations, generated 10 times per plot. See also Supplementary Figure S14 for the profiles of H3K4me1, H3K18ac, H2AV. (C) Normalized H3K4me3 ChIP-seq data (vertical axis) versus binned dCP (left) and hkCP (right) STARR-seq signal (horizontal axes). Spearman’s rho statistics calculated on non-binned data are displayed in the top right corners of panels. (D) Like C but for normalized H3K4me1 ChIP-seq data. Box-and-whisker plots (C, D) displayed as in Figure 2A.
Figure 6.
Figure 6.
Enhancer potential is related to local endogenous expression levels. (A) DHS major strand CAGE expression levels (log10 TPM, vertical axis) versus binned hkCP STARR-seq signal (horizontal axis). (B) Like (A), but for binned dCP STARR-seq signal. Spearman’s rho statistics calculated on non-binned data are displayed in the top right corners of panels. See also Supplementary Figure S15 for quantitative relationships between expression levels and H3K4me1, H3K4me3, and H3K27ac. Box-and-whisker plots (A, B) displayed as in Figure 2A.
Figure 7.
Figure 7.
Chromatin architectures suggest multiple layers of transcriptional regulation. (A) Fractions of DHSs per class, out of either the total within or between annotated TADs. The number of DHSs in each class is denoted on top of bars. (B) The change in log(odds) of grouping within the same TAD for DHS classes, split according to DHS class. Significance stars interpreted as: *P < 0.1, **P < 0.01 or ***P < 0.001.

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