RNA helicase-dependent gene looping impacts messenger RNA processing

Abstract

DDX5 and DDX17 are DEAD-box RNA helicase paralogs which regulate several aspects of gene expression, especially transcription and splicing, through incompletely understood mechanisms. A transcriptome analysis of DDX5/DDX17-depleted human cells confirmed the large impact of these RNA helicases on splicing and revealed a widespread deregulation of 3' end processing. In silico analyses and experiments in cultured cells showed the binding and functional contribution of the genome organizing factor CTCF to chromatin sites at or near a subset of DDX5/DDX17-dependent exons that are characterized by a high GC content and a high density of RNA Polymerase II. We propose the existence of an RNA helicase-dependent relationship between CTCF and the dynamics of transcription across DNA and/or RNA structured regions, that contributes to the processing of internal and terminal exons. Moreover, local DDX5/DDX17-dependent chromatin loops spatially connect RNA helicase-regulated exons with their cognate promoter, and we provide the first direct evidence that de novo gene looping modifies alternative splicing and polyadenylation. Overall our findings uncover the impact of DDX5/DDX17-dependent chromatin folding on pre-messenger RNA processing.

Figure 1.

(A) Validation of DDX5 and DDX17 depletion. Quantification of protein level (top) corresponds to the mean expression value normalized to actin ± S.E.M. (n = 3). RNA levels (bottom) were calculated from RNA-seq data and represented as the mean normalized read count ± S.E.M. (n = 3). Unpaired t-test (*** P-val < 0.001). (B). Representative examples of genes presenting an increased RNA-seq coverage beyond their 3′ end in condition of silencing of both DDX5 and DDX17 (red), compared to a control siRNA (blue). The RefSeq genomic annotation is shown for each gene (in black), as well as the gene orientation (black arrow). The respective width of each window corresponds to 53, 46, 74, 35, 115 and 111 kb. For each gene, all the reads originate from the same strand and there was no antisense transcript. (C) Steady-state quantification of read-through transcripts. The amount of each RNA product, measured by RT-qPCR using primers spanning the PAS (pA-span) or at a variable distance downstream of the gene (do_distance), as indicated on the diagram, was normalized to the total amount of the corresponding regular mRNA, measured with primers localized near the 3′ end of the gene (total). Data are represented as the mean values ± S.E.M. of independent experiments (n = 5–7) normalized to the control sample, set to 1. Paired t-test (*P-val < 0.05; **P-val < 0.01; ***P-val < 0.001). (D) Meta-gene analysis of the distribution of total RNAPII across the genes presenting siDDX5/DDX17-dependent transcriptional read-through. The analysis spans from 10 kb upstream of the TSS to 10 kb downstream of the PAS. The close-up view shows only the 10 kb region downstream of the PAS. (E). Quantification of pulled-down read-through transcripts. RNA from siDDX5/DDX17-treated cells were pulled-down using biotinylated ASOs targeting constant exonic regions of NCKAP5L or SH3TC1 transcripts. RNA products expressed from these two genes were then quantified in the pulled-down fraction, using primer pairs located in the regular transcript, across the PAS or downstream of the gene, as indicated. For the control pull-down, we used ASOs specific for a different gene (KATNB1). Data are represented as the percentage of bound RNA relative to input material (mean value of 3 independent experiments ± S.E.M.). Paired t-test (* P-val < 0.05; ** P-val < 0.01; *** P-val < 0.001). (F) Venn diagram showing the number of genes presenting a 3′ end cleavage defect or at least one alternative splicing event in absence of DDX5/DDX17, as predicted from the RNA-seq data (set with [ΔPSI] > 0.1). The lower diagram shows the number of alternative cassette exons misregulated upon DDX5/DDX17 depletion. The term ‘activated’ or ‘repressed’ refers to DDX5/DDX17 activity on the corresponding exons, i.e. exons that are skipped or included upon siDDX5/DDX17 treatment, respectively.

Figure 2.

(A) Relative distribution of CTCF binding sites at and around the first (F) and last exons of genes showing siDDX5/DDX17-induced defect in 3′ end cleavage (purple) compared to unregulated genes (Ctrl, grey). (B) Relative distribution of CTCF binding sites at and around the exons that are skipped (red, top panel) or included (blue, bottom panel) upon DDX5/DDX17 depletion. Control sets of exons include exons skipped or included upon depletion of the SRSF1 splicing regulator, and all internal exons that are neither dependent on DDX5/DDX17, nor dependent on SRSF1 (Ctrl exons). (C) Relative distribution of CTCF binding sites at and around the first (F) and last exons of genes containing at least one internal DDX5/DDX17-dependent alternative exon (in red). (D) Frequency of intragenic looping in genes harboring DDX5/DDX17-dependent exons, based on ChIA-PET datasets (for CTCF, Cohesin and RNAPII). Left panel: looping between the first and last exon of genes with siDDX5/DDX17-induced defect in 3′ end cleavage (purple), compared to unregulated genes. Central panel: looping between the first and last exons of genes containing DDX5/DDX17-dependent alternative exons (red), SRSF1-dependent exons or other exons. Right panel: looping betwen the internal exon regulated by DDX5/DDX17 or SRSF1 and the first exon of its cognate gene. (E) Orientation of the pairs of CTCF sites corresponding to chromatin loops analysed in D between the first and internal or last exons. Only exon pairs found in ChIA-PETs datasets using CTCF, SMC1 or RAD21 antibodies were selected for this analysis, with a weight 2 in at least one dataset. The different orientations of CTCF site pairs are depicted on the right. (F) Basal steady-state expression of transcripts of which 3′ end cleavage is regulated (light purple) or not (grey) by DDX5/DDX17. Within DDX5/DDX17-dependent genes, those that present evidence for head-to-tail proximity (dark purple) are even more highly expressed than other genes. Only transcripts with a basemean expression >5 were considered for the analysis. ANOVA with Kruskal-Wallis non-parametric tests (* P-val < 0.05; **** P-val < 0.0001).

Figure 3.

(A) Western-blot showing the expression of DDX5, DDX17 and CTCF in presence of siRNA targeted against DDX5/DDX17 and CTCF transcripts. (B) Quantification of the transcriptional read-through induced by DDX5/DDX17 and/or CTCF depletion on selected genes. Details are as in Figure 1B. Data are represented as the mean value ± S.E.M. of independent experiments (n = 6). Statistical comparison between each condition (including the unshown control condition) was calculated using a one-way ANOVA (Holm–Sidak's multiple comparison tests: * P-val < 0.05; ** P-val < 0.01; *** P-val < 0.001). (C) RT-PCR analysis measuring the inclusion of a selection of alternative exons in absence of DDX5/DDX17 and/or CTCF. The ΔPSI corresponds to the difference between the PSI (percent spliced-in) score of each depleted sample and the control sample. Details are as in (B). (D) Genomic organization of the SH3TC1 gene, with the position of CTCF binding sites. The red arrow indicates the deleted CTCF site (CTCF 3′), which is in the same orientation as the gene (+). The bottom panel shows the sequence of the region around the CTCF site (boxed in red), and the resulting sequence in the ΔCTCF cell line. (E) ChIP-qPCR analysis in the parental (WT) and ΔCTCF cell lines. Data are represented as the mean binding enrichment of CTCF compared to a negative gene-free region ± S.E.M. of two independent experiments. (t-test, * P-val < 0.05). (F) Quantification of the basal level of read-through transcripts in the parental (WT) and ΔCTCF cell lines. Data were normalized to the expression of total transcripts, as described in Figure 1, and then expressed as the mean reported to the read-through observed in WT cells, set to 1 (t-test, *** P-val < 0.001). (G) Quantification of SH3TC1 read-through transcripts in WT and ΔCTCF cells, in presence (siCtrl) or in absence (siDDX5/17) of DDX5/DDX17. For each condition, data are expressed as the mean value ± S.E.M. of the amount of read-through products (measured with the ‘do_1.7kb’ primers) normalized to total SH3TC1 transcripts (n = 4). Two-way ANOVA corrected for multiple comparisons by controlling the false dicovery rate (** q-val < 0.01; *** q-val < 0.001).

Figure 4.

(A) Genomic organization of the NCS1 gene, with the position of CTCF binding sites. Exon 5 (co-regulated by DDX5/DDX17 and CTCF) and exon 8 (regulated only by DDX5/DDX17) are framed in red and green, respectively. The position of primers used for ChIP-qPCR (black) and 3C (blue) experiments is indicated. (B) ChIP-qPCR analysis showing the effect of DDX5/DDX17 depletion on CTCF binding at various positions along the NCS1 gene. Data are represented as the mean binding enrichment of CTCF compared to a negative gene-free region, ± S.E.M. of independent experiments (n = 7). Paired t-test (* P-val < 0.05; *** P-val < 0.001). (C) 3C experiment showing the relative spatial proximity between various sites of the NCS1 gene and the promoter (anchor, A), in presence or absence of DDX5/DDX17. The X-axis represents the distance (in kilobases) of each primer relative to the Anchor. Data are represented as the mean signal normalized to the signal at the anchor ± S.E.M. (n = 4 independent experiments). Mann–Whitney test (* P-val < 0.05). (D) Proposed folding of the NCS1 gene around CTCF sites (orange circles). Only the regulated exons are represented. Upon DDX5/DDX17 depletion, the 3D organization of the gene is altered, especially contacts between the promoter and the 3′ end region. At the RNA level this is associated with altered splicing and 3′ end cleavage. (E) Genomic organization of the PRMT2 gene, with the position of CTCF binding sites. Promoter-proximal exon 2 is framed in blue. The position of primers used for ChIP-qPCR (black) and 3C (blue) experiments is indicated. (F) 3C experiment showing the relative spatial proximity between various sites of the PRMT2 gene and the promoter (anchor, A), in presence or absence of DDX5/DDX17. Details are as in (C). (G) ChIP-qPCR analysis showing the effect of DDX5/DDX17 depletion on CTCF binding along the PRMT2 gene. Details are as in (B). (H) Quantification of the transcriptional read-through induced by DDX5/DDX17 depletion on the PRMT2 gene. Details are as in Figure 1B. (I) Proposed folding of the PRMT2 gene around CTCF sites (orange circles). Upon DDX5/DDX17 depletion, the contact between the promoter and the 3′ end of the gene is altered. At the RNA level, this is associated with increased exon 2 inclusion and altered 3′ end cleavage.

Figure 5.

(A) ChIP-qPCR analysis showing the relative binding of RNAPII to several exons of the NCS1 gene, relative to the beginning of the gene (TSS). The genomic organization of the NCS1 gene is shown in Figure 4A. Details are as in Figure 4B. (B) Meta-exon analysis of the distribution of RNAPII across DDX5/DDX17-dependent exons. Exons were split into two groups depending on their distance to the closest CTCF binding site (left: exons distant from a CTCF site; right: exons close to a CTCF site). The analysis extended across 10 kb windows upstream and downstream of the exons. For each condition (siCtrl and siDDX5/DDX17) the mean RNAPII coverage (n = 3) was normalized to the TSS of the genes. (C) Meta-exon analysis of the distribution of RNAPII across terminal exons. DDX5/DDX17-dependent exons (split into 2 groups as in B) were also compared to other unregulated terminal exons. Details are as in (B). Black lines at the bottom indicate the bins at which a statistical difference in RNAPII coverage was found between the two conditions (paired t-test, P-val < 0.05). (D) GC content of DDX5/DDX17-dependent internal alternative exons (as in B) and their 2 kb intronic flanking regions. Wilcoxon test (**** P-val < 1e–12; ***** P-val < 1e–16). (E) GC content of DDX5/DDX17-dependent terminal exons (as in C) and their 2 kb intronic flanking regions.

Figure 6.

(A) Genomic organization of the FBLN1 gene, with the position of CTCF binding sites (black), primers used for 3C experiments (blue) and RT-qPCR amplicons (red). (B) CLOuD9 strategy for the FBLN1 gene. The specific gRNAs targeted the two dCas9 proteins at the promoter and downstream of the proximal PAS (PAS1), allowing the de novo formation of a loop between these loci upon addition of abscisic acid (ABA). (C) 3C-PCR experiment (using DpnII enzyme) showing the looping between the promoter and the PAS1 of the FBLN1 gene upon addition of ABA. Data are represented as the mean value ± S.E.M. of independent experiments (n = 3). Mann–Whitney test (* P-val < 0.05). (D) RT-qPCR quantifying the relative amount of transcripts using FBLN1 PAS1 compared to longer transcripts using PAS2 or PAS3 (ext2 and ext3), in the presence of DMSO or ABA. The right panel represents the data as the ratio between PAS1 and ext2 or ext3 transcripts. Data are represented as the mean value ± S.E.M. of independent experiments (n = 4). Paired t-test (* P-val < 0.05). (E) Genomic organization of the EYA3 gene, with the position of CTCF binding sites and primers used for 3C experiments (in blue). The alternative exon 7 is framed in red, control exons 2 and 9 are also indicated. (F) CLOuD9 strategy for the EYA3 gene. The specific gRNAs targeted the two dCas9 proteins respectively at the promoter and near exon 7, allowing the de novo formation of a loop between these loci upon addition of abscisic acid (ABA). (G) 3C-PCR experiment (using HindIII enzyme) showing the looping between the promoter and exon 7 of the EYA3 gene upon addition of ABA. Details are as in C. (H) RT-qPCR showing the inclusion of EYA3 exon 7 and control exons 2 and 9 in presence of DMSO or ABA. Experiments were performed with a specific RNA guide near EYA3 exon 7 or with an unrelated guide in the ZNF618 gene (Ctrl). Data are represented as the mean value ± S.E.M. of independent experiments (n = 3). t-test (* P-val < 0.05).