Co-binding by YY1 identifies the transcriptionally active, highly conserved set of CTCF-bound regions in primate genomes
- Petra C Schwalie†1, 5,
- Michelle C Ward†2, 3,
- Carolyn E Cain3,
- Andre J Faure1,
- Yoav Gilad3,
- Duncan T Odom2, 4Email author and
- Paul Flicek1, 4Email author
© Schwalie et al.; licensee BioMed Central Ltd. 2013
Received: 13 November 2013
Accepted: 31 December 2013
Published: 31 December 2013
The genomic binding of CTCF is highly conserved across mammals, but the mechanisms that underlie its stability are poorly understood. One transcription factor known to functionally interact with CTCF in the context of X-chromosome inactivation is the ubiquitously expressed YY1. Because combinatorial transcription factor binding can contribute to the evolutionary stabilization of regulatory regions, we tested whether YY1 and CTCF co-binding could in part account for conservation of CTCF binding.
Combined analysis of CTCF and YY1 binding in lymphoblastoid cell lines from seven primates, as well as in mouse and human livers, reveals extensive genome-wide co-localization specifically at evolutionarily stable CTCF-bound regions. CTCF-YY1 co-bound regions resemble regions bound by YY1 alone, as they enrich for active histone marks, RNA polymerase II and transcription factor binding. Although these highly conserved, transcriptionally active CTCF-YY1 co-bound regions are often promoter-proximal, gene-distal regions show similar molecular features.
Our results reveal that these two ubiquitously expressed, multi-functional zinc-finger proteins collaborate in functionally active regions to stabilize one another's genome-wide binding across primate evolution.
CTCF is a highly conserved, 11-zinc finger multi-functional protein [1, 2] important in regulating gene expression [3–5], insulating against enhancer-promoter interactions [6, 7], regulating splicing , as well as ensuring allele-specific expression at imprinted genes  and on the inactive X chromosome . Genome-wide studies have suggested that CTCF binding demarcates active and repressive domains [10–12] and contributes to nucleosome positioning , as well as nuclear organization and higher order chromatin structure .
CTCF's binding profile is largely (but not entirely ) invariant across mouse tissues , human cell lines  and divergent species compared to those of tissue-specific transcription factors (TFs) [17–22]. Comparisons of CTCF binding have revealed a high level of conservation in liver tissue of species separated by up to 180 million years , as well as in cell lines from human, mouse, and chicken . Additionally, CTCF has been shown to bind transposable elements in both embryonic stem cells  and differentiated tissue . While certain repeat elements have expanded CTCF target sites in several mammalian lineages, thus far there is no evidence of this process being prevalent in primates based on experiments in human and rhesus macaque .
The availability of sequenced primate genomes [23–26] and the ability to transform blood B cells into immortal lymphoblastoid cell lines (LCLs) with the Epstein-Barr virus (EBV)  facilitates functional genomics comparisons across different primate species. To date, such inter-primate studies have been carried out primarily at the level of gene expression [28–32]. However, it had already been proposed in the 1970s that phenotypic differences between primates are largely due to regulatory differences . While comparative evolutionary studies in mammals have provided insight into regulatory mechanisms, limited information is available within the primate order.
Inter-primate comparisons of regulatory evolution have been performed for histone modifications, which can explain 7% of gene expression differences among human, chimpanzee, and rhesus macaque cell lines . Further, DNA methylation studies revealed that promoter methylation differences underlie 12 to 18% of gene expression differences between humans and chimpanzees and that approximately 10% of CpG islands are significantly differentially methylated between the two species [35, 36]. Differences in the binding of transcriptional regulators have been inferred from the presence of several hundred species-specific DNase I hypersensitive sites near genes differentially expressed between humans and chimpanzees . Regulatory DNA element comparisons among primates are emerging [38, 39]; however, a comprehensive analysis of the binding of a sequence-specific factor such as CTCF across primate species has yet to be performed.
CTCF can exert its different functions through interactions with diverse protein factors [40, 41]. One such factor is Yin Yang 1 (YY1), which was originally shown to trans-activate the Tsix ncRNA during X-chromosome inactivation through its interaction with CTCF . There is a strong pattern of co-localization between these two factors at predicted boundary elements, suggesting that they could act synergistically in delimiting chromatin domains . Genome-wide chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) data have recently indicated global co-localization of CTCF and YY1 in human cells  with a specific distance constraint .
YY1 was first identified as both a repressor and an activator of the adeno-associated virus under different conditions , but, similar to CTCF, it has been attributed a broad range of distinct functions, including roles in imprinting [46–48], X-chromosome inactivation , and chromatin structure maintenance . YY1 is essential in mouse development, as its deletion results in peri-implantation lethality . A homolog of YY1, the Drosophila PHO protein, is involved in Polycomb repression [52, 53], but there is limited evidence for this in mammals, where YY1 is rather viewed as a global regulator. YY1 binding motifs are overrepresented in core promoters , with approximately 10% of human promoters containing it . Additionally, YY1 is important for initiating transcription of various transposable elements such as LINE-1s [56, 57], Alu SINEs , Herv-Ks  and LTRs .
Here, we map genome-wide CTCF binding at high resolution in seven primate species and propose that the evolutionary stability of CTCF genomic occupancy is, at least in part, linked to its co-binding with the ubiquitous TF YY1.
Evolution of CTCF binding in seven primates
The differences in CTCF binding accumulate in line with the evolutionary distance between compared species, as has been observed for more distant mammals , and pairwise binding overlap fractions between each primate species and human correlate negatively with evolutionary distance (Pearson's r = −0.92, P = 0.004; Figure 2C; Figure S2B in Additional file 1). Pairwise conservation estimates are consistent with previously published comparisons of CTCF binding in rhesus macaque and mouse liver  as well as human and gorilla LCLs . Similarly, as expected based on prior reports [21, 26], highly shared binding events show stronger ChIP enrichment, a better match to the consensus motif and a higher overlap with other cell types/tissues (in this case, liver) than species-specific binding events (Figure S2D-G in Additional file 1).
In order to determine the relationship between inter-individual and inter-species variation, we analyzed independently derived LCLs from H.sap (two LCLs), P.tro (three LCLs) and M.mul (four LCLs). While over three-quarters of the regions bound by CTCF in all four probed M.mul cell lines are also shared with five or six other primates, less than one-quarter of cell line-specific bound regions show such high overlap (Figure 2D). Conversely, binding events shared across seven species are present in the vast majority (over 80%) of the individual LCLs, in contrast to roughly half of CTCF-bound regions unique to one or two species. (Figure S2H in Additional file 1). These results indicate that regions bound by CTCF across individuals are more likely to be evolutionarily conserved than individual-specific bound regions. In sum, CTCF binding that is unstable between species also tends to be unstable between individuals within a species, and vice versa.
Evolutionarily conserved CTCF-bound regions are co-bound by YY1
In order to establish whether YY1 co-binding stabilizes CTCF binding in evolution, we performed YY1 ChIP-seq experiments in H.sap, P.tro, P.pyg and P.ham LCLs, as well as in primary liver tissue from human and mouse. YY1 binds tens of thousands of locations in all interrogated primates, as well as in mouse liver (Figure S3C in Additional file 1). Almost 10,000 regions bound by YY1 are shared across the four primates included in this analysis (4-way shared), 61% of which are also bound in human liver and 40% of which are shared with mouse liver (Figure S3C in Additional file 1). In comparison, virtually all of the 18,000 4-way shared CTCF LCL binding events are present in human liver, and approximately 50% of these are also bound in mouse liver. In other words, for both CTCF and YY1, about half of the binding events found in multiple primate species are also bound in mouse liver. Overall, pairwise YY1 binding conservation is typically lower than observed for CTCF (Figures S2B and S3D in Additional file 1). For instance, H.sap and P.tro share 48% of YY1 binding events compared to 69% of CTCF binding events, P.tro and P.pyg 62% YY1 versus 66% CTCF and P.pyg and P.ham 59% versus 71% bound regions. Nevertheless, like CTCF, YY1 binding is more highly conserved than that observed for tissue-specific TFs such as CEBPA and HNF4A .
After assessing CTCF and YY1 binding independently, we combined the two datasets to analyze the stability of regions co-bound by CTCF and YY1 (Figure 3C-E). CTCF binding events that co-localize with YY1 (CTCF-YY1) in one species are more likely to be shared with a second species (in this case human), and a similar effect is observed for YY1-bound regions that co-localize with CTCF (Figure 3D,E); reflecting this, we observed stronger sequence conservation of CTCF-YY1 co-bound locations (Figure S3E in Additional file 1). For each pair of species, the regions co-bound by CTCF and YY1 are consistently more evolutionarily stable than those bound by either one of the factors in isolation.
In summary, regions co-bound by CTCF and YY1 show enhanced sequence conservation and are more likely to exist and be bound in a second mammalian species, at both shorter and wider evolutionary distances.
Binding to repeat elements by either CTCF or YY1 does not explain most species-specific regions
As both CTCF and YY1 have previously been shown to bind to and expand species-specifically via repetitive elements [18, 21, 56–60] we analyzed the association between binding events and the repetitive genome. We found that CTCF-YY1 bound regions are less likely to overlap annotated repeats than either CTCF-only or YY1-only regions (P < 0.05; Figure S3F in Additional file 1), which is not unexpected given their high conservation. In order to determine the extent to which repetitive elements contribute to species-specific binding, we further analyzed CTCF and YY1 binding events independently.
We also searched for repeat-specific CTCF motif words, which previously revealed CTCF-bound repeat expansions in more diverse mammalian species . We detected no species-specific motif words and only a limited number of words bound at a higher frequency in primates than in other mammalian species (Figure S4B in Additional file 1). LTR13 was again identified as a CTCF-bound primate-specific repeat; however, less than 300 binding events account for this enrichment across primates, a comparatively low number considering the tens of thousands of B3-specific motif words that have shaped the CTCF binding landscape in rodent genomes .
We similarly identified which annotated repetitive elements are associated with YY1 binding. MLT1-type repeats of the ERVL-MaLR family, including MLT1F and MLT1J, are found to be significantly associated with YY1 binding (Figure 4C,D; Figure S4D and Table S3B in Additional file 1). MLT1-type repeats are not enriched in YY1 binding events in human and mouse livers, suggesting that the genomic interaction of YY1 and this repeat class might be tissue-specific, unlike the observed LTR repeat association with CTCF binding events (Figure 4E,F). Finally, we did not find an enrichment of repeat-embedded YY1 binding at or in close proximity to repeat-associated CTCF binding locations, indicating that these factors bind distinct repeats. Thus, repeats do not appear to be involved in CTCF-YY1 co-binding in the genome.
In sum, active repeat expansions have not substantially contributed to the CTCF binding repertoire in seven major primate lineages, and most species-specific CTCF and YY1 binding events do not appear to be mediated by repeat elements.
YY1 couples CTCF binding to transcriptional activity
In order to determine whether the presence of YY1 at CTCF-bound regions has an effect on transcriptional output, the expression of genes bound by only CTCF versus those bound by CTCF and YY1 were compared. Genes overlapping YY1 binding events (including YY1-only and YY1-CTCF) are significantly more highly expressed than are genes overlapping CTCF-only binding events (P < 10-16) in both human and mouse liver (Figure 6C; Figure S6D in Additional file 1).
In sum, CTCF-YY1 co-bound regions are functionally similar to YY1-only regions based on their association with increased gene expression and enrichment of Pol II, H3K4me3 and liver-specific transcriptional regulators. This means that the CTCF occupied regions co-bound by YY1 show not only stronger evolutionary stability, but also increased transcriptional activity, in contrast to the bulk of CTCF-bound regions.
Our mapping and inter-species comparison of CTCF binding in cell lines from H.sap, P.tro, G.gor, P.pyg, M.mul, P.ham and S.oed has revealed over 11,000 genomic locations bound by CTCF across primates, consistent with the high conservation of CTCF binding observed in more distant mammalian species [19, 21, 67]. This estimate was obtained despite the fact that our analytical approach did not assume that CTCF binding is conserved, and as such is likely to underestimate true inter-species overlaps [21, 22]. In contrast, other related studies have assumed conservation and minimized species-specific differences by using a dual cutoff, anchored in a single reference species [34, 68].
Despite our conservative approach, we found that 60% of CTCF-bound regions are shared between H.sap and M.mul, whereas a recent comparison across 25 million years of Drosophila sp. evolution, a similar divergence time , has revealed approximately 30% binding conservation . This discrepancy could be caused by differences in CTCF function between the chordate and arthropod phyla: CTCF is the only well-characterized insulator-binding protein in vertebrates, where it seems to be largely responsible for three-dimensional genome organization, as well as regulating various transcriptional and gene regulatory processes in collaboration with cohesin . In contrast, Drosophila sp. have multiple insulator proteins and thus may place lower constraint on CTCF binding sites.
Previous studies have shown that the expansion of repetitive elements appears to be a major mechanism by which CTCF increases its target landscape in individual mammalian lineages [18, 21, 72]. Here, we identified particular repeat types associated with CTCF binding across primates, some of which have previously been shown to associate with CTCF in human, including LTR41 in human embryonic stem cells  and LTR13 across multiple cell types [18, 63]. However, we did not find systematic evidence for a repeat-mediated expansion of CTCF binding in primate clades. This comparative quiescence of repeats that carry CTCF binding sequences in primates relative to rodents might be in part due to differences in genome transposon content and activity. For instance, mice have more lineage-specific repeat elements than humans, as well as greater transposon activity and fewer ancestral repeats [73, 74].
In searching for factors contributing to the conservation of CTCF binding we discovered that co-binding by YY1 is an ancient regulatory mechanism that appears to increase the evolutionary stability of CTCF binding in multiple mammalian species. CTCF and YY1 have previously been shown to co-localize and physically interact [9, 42, 43, 46, 75] but their combined, genome-wide interaction has not been investigated across multiple species.
Our analysis revealed that one mechanism stabilizing the protein-DNA contacts in regions co-bound by CTCF and YY1 may be their association with active chromatin and gene expression (previously reported for CTCF in [10, 76–78]). It has been shown that CTCF can interact directly with Pol II and target it to a subset of CTCF sites genome-wide . Our data now reveal that this likely occurs in the presence of YY1, because in its absence, CTCF-bound regions almost never co-localize with Pol II, H3K4me3, or tissue-specific TFs, whether proximal or distal to genes. These observations suggest that with respect to transcriptional activity, YY1 is the functionally dominant factor at co-bound locations.
Experiments performed at a single genetic locus have shown that CTCF can form a complex with YY1 and the tissue-specific factor Oct4 that binds Tsix and Xite to control X-chromosome pairing and counting in embryonic stem cells . Co-binding of CTCF and YY1 thus appears to indicate globally to the chromatin remodeling machinery which euchromatic regions are to be activated . The integration of these discoveries suggests a model wherein co-transcriptional activity of YY1-bound regions may help conserve CTCF and YY1 binding via functional deployment.
In summary, CTCF-YY1 co-bound regions are not only preferentially and highly conserved but also show hallmarks of transcriptional function that could provide selective pressure to preserve specific protein-DNA contacts across millions of years of mammalian evolution.
Materials and methods
Cell line material
Lymphoblast cell lines were obtained for seven primate species. The species, cell line and source are shown in Table S1 in Additional file 1. All cell lines were transformed by the Epstein-Barr virus except for the M.mul cell lines, which were transformed by Herpesvirus papio.
Cells were grown in suspension at a confluency of 200,000 cells/ml to 1 × 106 cells/ml in RPMI1640 media supplemented with 15% fetal bovine serum and 2 mM L-glutamine, 100 I.U/ml penicillin and 100 μg/ml streptomycin. We cross-linked 1 × 108 cells with 1% formaldehyde as previously described .
C57BL/6 J mice were housed in the Biological Resources Unit under UK Home Office licensing. Tissue was obtained from at least two independent males and formaldehyde cross-linked as described in .
Male and female human tissue samples were obtained from biopsied tissue collected at Addenbrooke's Hospital, Cambridge, and provided by the Biobank under human tissue license 08/H0308/117. Liver tissue was also obtained from the Liver Tissue Distribution Program (NIDDK contract number N01-DK-9-2310) at the University of Pittsburgh.
ChIP-seq assays were performed as previously described . Protein-bound DNA was immunoprecipitated with antibodies against CTCF (Millipore, Billerica, MA, USA, 07–729), or YY1 (Santa Cruz Biotechnology, Dallas, TX, USA, sc-281). Immunoprecipitated DNA was end-repaired, A-tailed and ligated to single-end Illumina sequencing adapters before 18 cycles of PCR amplification. DNA fragments (200 to 300 bp) were selected and 36 bp reads sequenced on an Illumina Genome Analyser II according to the manufacturer's instructions.
Published ChIP-seq experiments
The following published ChIP-seq data were used: mouse liver CTCF , mouse liver H3K4me3 and Pol II , human H3K4me3 and Pol II , human and mouse liver HNF4A and CEBPA . ENCODE data used were from the following cell lines: for CTCF, GM12878, GM12891, GM12892, GM19239, GM19240, HepG2, H1-hESC; for YY1, GM12878, GM12891, GM12892, HepG2, H1-hESC; for NFKB, GM12878 (no treatment), GM12891 (tumor necrosis factor alpha treatment), GM12892 (tumor necrosis factor alpha treatment); for Pax5, GM12878, GM12891, GM12892; and for Pol II, GM12878 . Published mouse embryonic stem cell ChIP-seq data for CTCF and YY1 were also used [19, 84]).
All computational analyses were performed with scripts written in Perl, Bioperl 1.2.3, and R version 2.11.1, using packages available in Bioconductor 2.6 (Additional file 2). Displayed error bars represent the standard error of the mean and significance levels were estimated using one-sided Wilcoxon rank-sum tests if not otherwise stated.
Read alignment and peak-calling
ChIP and input sequencing reads from all LCL datasets were aligned using Bowtie  0.12.7 with the parameters '-n 2 -m 3 -k 1 -best' to the following genome assemblies: human GRCh37, chimpanzee CHIMP2.1, gorilla gorGor3, orangutan PPYG2, macaque Mmul 1, and marmoset C. jacchus 3.2.1. All sequence, genome annotations (genes, transcripts, CpG islands) and comparative genomics data were taken from Ensembl release 60. Repeat element annotation was downloaded from the UCSC Table Browser for all species. The baboon data were aligned to the macaque genome, as it was the closest fully assembled genome. When available (all species except for marmoset), only chromosomes and not unmapped contigs were used. Aligned reads were filtered for duplicates, uncalled bases (a maximum of three Ns were allowed) and low complexity reads. Regions of high ChIP enrichment (peaks/bound regions/binding events) were detected with CCAT 3.0  on individual replicates using the parameters 'fragmentSize 100, slidingWinSize 150, movingStep 10, isStrandSensitiveMode 1, minCount 10, minScore 4.0, bootstrapPass 50' for the two TFs and 'fragmentSize 200, slidingWinSize 100, movingStep 20, isStrandSensitiveMode 0, minCount 10, minScore 4.0, bootstrapPass 50' for Pol II. Naked DNA (input) was used as control and the FDR cutoff was set to 0.1. Peaks were then merged among replicates in each organism by taking the intersection and additionally adding replicate-unique peaks with an FDR <0.05. The similarity between individual replicates was assessed by calculating the correlation (Spearman's rho) between read counts inside peak regions (Figure S1 in Additional file 1).
ChIP-seq data visualization
ChIP-seq data from each species was visualized on the corresponding species genome on the UCSC genome browser . Human (GRCh37/hg19), chimpanzee (CGSC 2.1/panTro2), gorilla (gorGor3.1/gorGor3), orangutan (WUGSC 2.0.2/ponAbe2), macaque and baboon (MGSC Merged 1.0/rheMac2), tamarin (WUGSC 2.0.2/calJac1), and mouse (NCBI37/mm9).
We performed all our inter-species comparisons based on the 6-primate EPO (PrimateEPO) and the 11-way eutherian mammals (EPO) multiple sequence alignments (MSAs) available in Ensembl Compara release 60. Binding events discovered by CCAT at an FDR of 0.05 were projected onto all study species using the MSA through the Ensembl Compara Application Programming Interface (API). We restricted the evolutionary analysis to regions of the genome included in the MSA. Each of the study species was used as anchor species, and the region of interest projected onto the other species. In order to determine the degree of commonality between the species, projections were then overlapped (≥1 bp) with binding events - that is, binding events called at an FDR of 0.05 in one species that overlap with binding events called at the same FDR in a second species are called shared. To estimate the fraction of putatively shared binding events missed by this approach, we fixed the FDR in one species (human), varied it in the other six species (up to FDR = 0.5) and calculated the new percentage overlaps (data not shown). Conservation estimates increased by less than 10% compared to the fixed values reported in the manuscript, suggesting that while the method employed here does underestimate conservation levels, this effect is limited.
Overlap numbers differed by up to tens of bound regions depending on which species was used for anchoring. The percentage overlap numbers reported in Figure 2C, Figure S2B in Additional file 1, Figure 3D-E, and Figure S3D in Additional file 1 are averages between the two analysis directions (for example, shared human-chimpanzee regions from human and chimpanzee perspective). The human-human overlap percentage was obtained by calculating the overlap fraction of our operative peak set with different LCLs when available: five different cell lines for human (ENCODE LCL GM12878, GM12891, GM12892, GM19239, GM19239, GM19240), three different LCLs for chimpanzee and four different LCLs for rhesus macaque. The median value is displayed in Figure 2C based on primate (blue square) and mammalian (grey circle) alignments. Evolutionary time between the species was obtained from  (median).
For the comparative analyses displayed in Figures 2 and 3 and Figures S2 and S3 in Additional file 1 we divided the bound regions into six different categories in each of the seven primate species (we refer to these categories as 'conservation classes'): (i) species-specific and not included in the genome-wide multiple alignments, (ii) species-specific and included in the alignments, (iii) shared between two species only, (iv) shared among three to five species, (v) shared among six species, and (vi) shared among all seven analyzed primates. We calculated the relative fraction of bound regions belonging to these six categories and displayed them as barplots in Figure S2A in Additional file 1. The median values across all seven species are shown in Figure 2A as well as the number of seven-way shared peaks (based on the human genome).
Properties of different peak categories and CTCF-YY1 binding event classes
Four peak categories (species-specific (1), shared between exactly two species (2), shared among exactly six species (6) and shared among all seven species (7)) were further analyzed for diverse properties in each single species: CCAT score (proportional to ChIP enrichment), the top NestedMica motif match score distribution (with 0 corresponding to the consensus motif), the numbers of peaks with at least one motif, overlaps with peaks called in distinct LCL cell lines when available (human, two; chimpanzee, three; macaque, four), overlaps with transcripts, CpG islands, repetitive elements, Pol II, and publicly available TF binding data from ENCODE. Barplot widths are proportional to the number of regions belonging to each category. We also performed a detailed conservation-inter-individual overlap analysis using four distinct rhesus macaque LCL lines. We selected two types of CTCF-bound regions: (1) bound in only one of the four cell lines and (2) bound in all four cell lines. We then asked how often these regions were shared with the other species and displayed the relative fractions as pie charts in Figure 2D.
Three distinct classes of CTCF/YY1 bound regions (CTCF-only, CTCF-YY1 and YY1-only regions) were analyzed for their properties, using data from four primate LCLs (human, chimpanzee, orangutan, and baboon), as well as human and mouse liver data. Additionally, previously published Pol II, H3K4me3, CEBPA, and HNF4A data in human and mouse liver were intersected with the three classes of bound regions.
Repeat element association
We tested genome-wide association of annotated repeat elements with LCL CTCF/YY1 binding events in each single species by using a binomial test. We estimated background probabilities from median overlaps of repeat elements with randomized CTCF/YY1 binding events, and corrected for multiple testing by the Benjamini-Hochberg method. Repeats that obtained a P-value ≤0.01 are included in Figure S4A,D in Additional file 1; repeats with a -log P-value >10 in at least one species are displayed in Figure 4 and Table S3 in Additional file 1.
We estimated the repeat divergence from the consensus sequence based on the number of substitutions from the consensus ('milliDiv' column in the UCSC-obtained RepeatMasker tracks) and the age of individual bound repeat elements by dividing the substitution number by the mutation rate estimated for mammalian species (2.2 × 109 per base pair per year)  and rodents (4.5 × 109 per base pair per year) . Repeat ages were used to order the heatmaps shown in Figure 4. Repeats were sorted by class in Figure S4 in Additional file 1. Repeat profile plots centered on CTCF and YY1 peak summits in human LCLs were displayed for the top two enriched repeats, LTR13/LTR41, and MLT1J/MLT1F, respectively.
where S is the species of interest and R all other species or all other species from a different branch of the evolutionary tree (considered groups were hominidae, Old World monkeys, New World monkeys, primates, and non-primate mammals). We fitted a normal distribution to normWord and chose a cutoff that corresponded to a FDR of 0.05 after multiple testing correction. All words with nocc(S) greater than the determined cutoff were selected for each species. For these selected words, we counted the number of CTCF-bound sequences of this type that are located inside annotated repeat elements. We display the log number of such words, as well as the analogous results obtained in mouse livers (for comparison) in Figure S4B in Additional file 1.
Repeat read profiles displayed in Figure 4E,F were generated by quantifying the read counts in 200 windows of 50 bp each centered around CTCF or YY1 peak summits that were contained in the repeat classes of interest. The obtained matrices were then visualized in Java TreeView while keeping the scale the same for each dataset .
Motif discovery was conducted with NestedMica  using the parameters '-minLength 5 -maxLength 30 -numMotifs 6' and a fourth order background model trained on mammalian regulatory regions (DHS) data. Discovered motifs were confirmed using MEME , with the options '-nmotifs 5 -minsites 100 -minw 6 -maxw 25 -revcomp - maxsize 500000 -dna'. We selected the top 1,000 peaks ordered by CCAT score and used 25 bp up- and downstream of the peak summit as input for motif discovery. As the obtained top motifs were virtually identical in all studied species, we merged them into a single PWM that we used in further motif analysis steps. NestedMica's nmscan with a cutoff of −15 was used for motif matching (a score of 0 corresponds to a perfect match to the motif consensus) displayed in Figure S5C in Additional file 1 are obtained from all sequences that match the CTCF and YY1 PWMs inside regions positive for both CTCF and YY1 ChIP signal.
Functional association analysis
CTCF regions co-bound with YY1 were analyzed relative to all CTCF-bound regions in Figure S6C in Additional file 1 to determine whether these regions were associated with common biological pathways using cPath within the GREAT bioinformatic tool [96, 97].
We used published liver RNA-seq data in human and mouse to test the association between YY1/CTCF binding events with transcriptional activity . Reads were mapped to Ensembl release 60 transcript annotation and transcript levels quantified using mmseq . We compared log2(transcript estimates) for transcripts overlapping YY1-only, CTCF-only, or at least one CTCF-YY1 binding event using a Wilcoxon signed-rank test and display the data as boxplots in Figure 6C and Figure S6D in Additional file 1.
CTCF and YY1 ChIP-seq data have been deposited under Arrayexpress, accession number E-MTAB-1511.
false discovery rate
lymphoblastoid cell line
multiple sequence alignment
- Pol II:
RNA polymerase II
position weight matrix
We are grateful to the Cambridge Institute Genomics and Bioinformatics Core facilities and Margus Lukk and Tim F Rayner for computational support. Thank you to the Health Protection Agency Cell culture collections and the ECACC for culturing and cross-linking the 81.3, EB176(JC), EB(JC), EB185(JC), 26 CB1, and B95-8 cell lines. We thank the New England Primate Research Center for the rhesus macaque LCLs and Chris Tyler-Smith for the GG013 gorilla LCL. This research was supported by: ERC Starting Grant and EMBO Young Investigator Award (DTO); Wellcome Trust Awards WT095908 (PF) and WT098051 (PF, DTO); NIH Grant GM084996 (YG); University of Cambridge (PCS, MCW, AJF, DTO); EMBL (PCS, AJF, PF); Cancer Research UK (MCW, DTO); Commonwealth Scholarship Commission (MCW); EMBO Short Term Fellowship (MCW).
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