Cross-species deployment of lamprey elements identifies the deep conservation of lamprey SoxE1 enhancer activity, mediating homologous expression in jawed vertebrates. Our data provide insight into the core GRN elements conserved to the base of the vertebrates and expose others that are unique to lampreys.The neural crest (NC) is an embryonic cell population that contributes to key vertebrate-specific features including the craniofacial skeleton and peripheral nervous system. Here we examine the transcriptional and epigenomic profiles of NC cells in the sea lamprey, in order to gain insight into the ancestral state of the NC gene regulatory network (GRN). Transcriptome analyses identify clusters of co-regulated genes during NC specification and migration that show high conservation across vertebrates but also identify transcription factors (TFs) and cell-adhesion molecules not previously implicated in NC migration. ATAC-seq analysis uncovers an ensemble of  An understanding of the ancestral state of the neural crest (NC) gene regulatory network (GRN) gives insight into vertebrate evolution. Here, the authors use transcriptomic and chromatin accessibility analyses of the lamprey NC, as well as cross-species enhancer assays, to identify GRN elements conserved throughout vertebrates. The advent of the NC with its contributions to numerous tissues and organs is thought to have played an essential role in the diversification of vertebrates3. Elucidating how the genetic signals involved in NC specification were modified over the course of vertebrate evolution is key to understanding how this diverse assemblage evolved and expanded4. This requires a detailed picture of how the NC GRN functioned in the vertebrate ancestor. To this end, the sea lamprey, a basal vertebrate, serves as a good model. Morphologically, these animals are considered living fossils with a body-plan that has remained consistent over at least the last 400 million years5.The neural crest (NC) is a migratory embryonic cell population that is unique to vertebrates. NC cells form in association with the developing central nervous system, which they delaminate from after undergoing an epithelial-to-mesenchymal transition (EMT). They subsequently migrate throughout the body to give rise to a plethora of derivative cell types6. By taking a candidate gene approach to compare lamprey and gnathostome TFs and signalling molecules, we previously showed that many key NC genes were conserved in expression and function between lamprey and jawed vertebrates7. These results suggested that the basic NC GRN was already present at the base of vertebrates, although some key regulators were missing from the lamprey NC specifier module7.The current view of the NC GRN has been compiled from data generated in jawed vertebrates12. Progress in reconstructing the NC GRN of jawless vertebrates, however, has been limited owing to incomplete genomic information. Recently, a germline genome assembly for the sea lamprey, that unlike previous assemblies13 is not affected by DNA-elimination14 and has an increased contiguity to near chromosome-scale resolution15, has made it possible to interrogate the regulatory genome of this basal vertebrate with increased confidence.Recently, our understanding of the NC GRN in gnathostomes has been increased with the advent of next-generation sequencing techniques including RNA-seq, ChIP-seq and ATAC-seqcis-regulatory elements. Importantly, we identify enhancer elements that drive expression in the lamprey NC, and provide evidence that regulation of a SoxE family gene is conserved between jawless and jawed vertebrates. By adapting high-throughput tools to the lamprey, our data provide insight into the ancestral state of the NC GRN.Here, we explore the dynamics of gene expression and chromatin accessibility during cranial NC specification and migration in the sea lamprey. By comparing our genome-wide representation of the active lamprey NC transcriptome to that of jawed vertebrates, our analyses highlight the components of the NC GRN that are conserved and likely to be essential for NC specification. We analyse the chromatin accessibility in the NC cells of two lamprey species, and find that cross-species mapping highlights putative 16 T18, T20 and T21  including premigratory, early-delaminating and/or late-delaminating NC cells at Tahara (T) stageT21 Fig. , respect15. Principal component analysis (PCA) of DNT count data showed clear separation along principal component 1 (PC1), which accounted for 90% of the variance, reflecting the developmental stage of the tissue . Of these, 5400 were enriched at T21, whereas 3706 were depleted  were depleted at T21, consistent with studies showing that Wnt expression is dynamically modulated during NC delamination and migration20. Genes play a role in neural tube development, such as Pax6a and BMP4, as well as NC specifier genes like SoxE genes (SoxE1 and SoxE2), Foxd3, Msx2, Tfap2A and Tfap2B were increased by at least twofold at T21 when compared with T18, whereas other genes including several Hox, Tbx and Gata TFs were depleted  were upregulated at T20 when compared with T18  were enriched , which displayed low expression at both T18 and T20 that increased at T21 , as well as signalling receptors and ligands , secreted matrix remodelling enzymes , collagens (Col3a1/4a1/4a6) and lamprey orthologues involved in organisation of the extracellular matrix  , neurons  and glia  Dsc1/2) and Sdk1, and extracellular matrix proteins, such as Vitrin , which interacts directly with Sox1024 and inhibits canonical Wnt signalling in cancer25, showed increased expression at T20, whereas EHF , proposed to have a role as a tumour-suppressor in prostate cancer26 and oncogene in ovarian cancer27, showed elevated expression at T21. Fli1 and Satb2, which are expressed in the developing branchial arch cartilage and mesenchyme29, and Nfatc, which forms a complex with Sox10 during Schwann cell differentiation30, were also elevated at T21 .Gene Ontology (GO) analysis of genes enriched at T18, and thus depleted at T21, highlighted terms associated with the NC GRN signalling module, including Wnt and FGF signalling Fig. . Terms aBmp4 and Tfap2b were clearly expressed in the DNT at T21, whereas Tfap2b was maintained in the migratory NC at T23. Interestingly, Fli1 expression was also associated with the DNT at T21, indicating that this factor may have an early role in NC development, as well as being expressed in the branchial arches later on. Similarly, Zfhx4, which is enriched in the migratory NC in the chicken12 was associated with the neural tube and branchial arches, suggesting a role in both early and later NC development. Col6A1 was most strongly expressed adjacent to the neural tube, surrounding the developing otic placode, where it likely supports NC cell migration31. Sdk1 and Vitrin were expressed in the region coinciding with the neural tube and delaminating NC at T23. Sdk1 was also associated with the developing branchial arch mesenchyme at T23. Tead1, a TF that is involved in regulating cell proliferation during development and in cancer32, was expressed in the neural tube as well as the migratory NC at T23. The zinc finger protein Bnc2, which is implicated in craniofacial development33 and adult pigmentation34, was associated with the DNT and the developing branchial arch mesenchyme at T23. Sdk1, Vitrin and Bnc2 expression at T21 was possibly too low for detection by in situ hybridisation , whereas Tead1 was expressed most strongly in the mid-brain region including the NC  revealed the dynamics of chromatin accessibility genome-wide over the course of development  that displayed increased accessibility at T21 and T23 compared with T20  and Tfap2B (intronic cluster 4).We were particularly interested T20 Fig. . Gene onT20 Fig. . In addicis-regulatory elements may single them out as functional enhancers during.To quantify the significance of these EMT clusters, we plotted the ATAC-seq signal levels of our peaksets at T20 against those at T23 and calculated the Pearson correlation coefficient for all intergenic and intronic clusters , as well those that play a role in EMT (GRHL236), suggested that these clusters harbour cis-regulatory elements that provide connections between NC GRN players. Enrichment of CTCF-binding sites in all intergenic clusters further suggests these peaks may represent putative cis-regulatory elements.We used TF-binding site motif analysis to further interrogate the ATAC-seq ifs Fig. . GRHL2, ifs Fig. . The preCluster 1 for intergenic and intronic peaksets had a distinct TF-binding site profile from the other clusters, which resembled the binding profile of our promoter peakset (annotated and novel promoter peaks), and was enriched for motifs found in the HOMER promoter motif library Fig. . These c11. We used in silico two-way combinatorial analysis to test for evidence of multiple TF co-activity at putative cis-regulatory elements. Focussing on intergenic cluster 5, we selected 18 TFs that displayed enriched motifs and enriched gene expression at T21   Fig. . Combinacis-regulatory elements, we used peaks from our EMT clusters that were associated with loci of known NC GRN genes in enhancer-reporter assays. An element, located 16.6 kb downstream of the SoxE1 locus   Fig. . This sucis-regulatory regions into modules that drive expression in specific tissues, including the NC. Sea lamprey cis-regulatory elements for Hox-α2 that drive gene expression in the neural tube, somites and NC are found in a 9-kb region upstream of Hox-α2, whereas elements that drive expression in the NC and somites alone are located within 4-kb of the Hox-α2 locus38. Recently, a core 1.5-kb region within the 4-kb enhancer (elementA) was shown to recapitulate the activity of the full 4-kb element39. These findings are confirmed by our ATAC-seq data set. We found that a ~ 1.5 kb element encompassing an ATAC-seq positive region at ~ − 8.5 kb drove reporter expression that was restricted to the neural tube . Alternatively, this transcript might be a byproduct or a facilitator, of chromatin looping linking the upstream enhancer to the Hox-α2 promoter.Interestingly, our RNA-seq data revealed bidirectional transcription from these loci, a known occurrence at active enhancers15, whereas 70% were associated with ATAC-seq positive regions. The gnathostome HoxA locus is known to harbour lncRNAs, including HOTAIRM142 and HOTTIP43, which have been shown to modulate gene expression in cis. The putative lncRNA, identified between Hox-α3 and Hox-α2, is significantly enriched in the DNT at T21 when compared to T18 , suggesting it may regulate Hox-α expression in the neural tube and/or NC at T21.The antisense transcript is one of 6257 putative long non-coding (lnc)RNAs identified in our transcriptome. In all, 48% of these overlap with predicted lncRNA from adult sea lamprey brain, heart, kidney and gonad RNA-seq datasets37. We generated transgenic zebrafish carrying the lamprey SoxE1 enhancer upstream of a minimal promoter and GFP using the Activator (Ac)/Dissociation (Ds) (Ac/Ds) transposition system44, which facilitates highly efficient transgenesis in zebrafish45, and resulted in seven independent integrations of the SoxE1 enhancer:GFP cassette. Although only weak reporter expression was visible in F0 embryos, the F1 generation displayed striking heterospecific reporter expression in the branchial arches by ~ 30 hpf, mirroring the enhancer activity in the lamprey at T23 8. At HH18, citrine expression was visible in the branchial arches and in the dorsal root ganglia, alongside and occasionally overlapping NC2:cherry reporter expression, which was used a marker for the NC46  in zebrafish embryos, resulting from crossing our lamprey SoxE1 enhancer transgenic line reporting EGFP to a transgenic line expressing DsRed in the branchial arches  and neuronal  NC derivative fates. As development progresses and bona fide NC cells begin to delaminate (T21), enrichment terms changed to those characterising NC and stem cell programmes as well as autonomic nervous system formation. Interestingly, the lamprey NC GRN lamprey differs from that of zebrafish in that it lacks the NC sub-programme involved in the specification of the enteric nervous system (ENS). This is consistent with studies showing that the lamprey may lack vagal NC and that the lamprey ENS may have much later onset48.Analysis of the lamprey NC transcriptional network provides global insight into the evolution of NC transcriptional programmes. At premigratory NC stages (T20) in the lamprey, we observed similar gene enrichments in categories equivalent to those observed in zebrafish21 and suggests links between early specification factors and their downstream effectors. TFs and signalling molecules associated with the NC specification module  are upregulated at T20 and co-regulated with genes associated with delamination, including cell adhesion and cytoskeletal factors. Later, at T21, TFs associated with NC migration  are co-expressed with genes associated with active migration, including signalling receptors, their ligands and secreted matrix remodelling enzymes. Interestingly, these genes are co-expressed with genes involved in NC differentiation. Future analysis using this resource to investigate direct links between co-regulated genes will allow expansion of the global structure of the lamprey NC GRN.Analysis of co-expression clusters using WGCNA increases the resolution of the putative lamprey NC GRNC. elegans, where ATAC-seq analysis of whole animals at early embryonic, larval and adult stages revealed dynamically regulated cis-regulatory regions with tissue-specific activity49, we have performed this analysis using dissected cell populations predominantly, but not exclusively, comprised of NC cells at three successive stages of lamprey development. Together, these studies show that the dynamic signature associated with changes in chromatin accessibility over time can be used to pinpoint putative tissue-specific regulatory regions.Our analysis of chromatin dynamics in the lamprey NC enabled the identification of tissue-specific enhancers. Similar to studies from cis-regulatory regions. Although the evolutionary distance between the sea lamprey and gnathostomes precludes identification of cis-regulatory elements based on sequence conservation, the ATAC-seq reads from brook lamprey, L.planeri, were successfully mapped cross-species to the genome of the sea lamprey, P. marinus. This suggests that the putative functional non-coding elements have been conserved between the two lamprey species over the last 40 million years37. Thus, mapping the brook lamprey ATAC-seq data to the sea lamprey genome has enabled identification of conserved genomic regions.Interestingly, we show that heterospecific analysis of ATAC-seq data from different lamprey species can provide clues for the location of conserved SoxE enhancer drives tissue-specific reporter expression in the zebrafish and chicken NC. Interestingly, experiments in the invertebrate chordate, amphioxus, where the entire amphioxus SoxE locus and flanking genes were integrated into the zebrafish genome, resulted in reporter expression in the neural tube and tail bud, but not in the NC50. This suggests that a NC enhancer for SoxE expression is not present in the vicinity of the SoxE locus in amphioxus. Together, these results support the hypothesis that the acquisition of novel enhancers in early vertebrates was critical for the evolution of the NC-specific gene expression. Gain-of-function cis-regulatory changes, such as the appearance of new TF binding sites, likely facilitated co-option of pre-existing gene batteries, including the pro-chondrocytic SoxE genes and other mesenchymal gene programmes, into NC-like cells at the neural plate border2. Indeed, we show that the lamprey SoxE1 enhancer harbours putative binding site motifs for important NC TFs, including Tfap2 and SoxE factors, that activate and maintain SoxE transcription in the chick52, zebrafish53 and lamprey21. A Hox site is also present and could possibly control the activity pattern of the enhancer confined to specific regions of cranial NC conserved across vertebrate taxa38. By knocking out the TFs associated with these binding sites in our transgenic zebrafish carrying the lamprey enhancer, we provide evidence to support the hypothesis that either single or a combination of TF binding sites mediate the conserved enhancer activity in the NC.We show that a lamprey 54. This suggests that the functionality of cis-regulatory regions is independent of sequence constraint. We provide functional evidence that this hypothesis holds true to the base of the vertebrates by revealing that a cis-regulatory sequence from an agnathan, that does not align to the gnathostome genome, is able to drive tissue-specific gene expression in two gnathostome species. This conserved regulatory grammar may have been maintained over evolutionary time through positive-selection promoted by a requirement for co-operative binding of diverse TFs to direct tissue-specific gene expression. Support for this hypothesis comes from a recent study that analysed the location of binding sites for four liver-essential TFs across five mammalian species and found that cis-regulatory modules that harbour sites for all four TFs were more likely to be conserved than those with fewer shared sites55. It is plausible that physical interactions between the TFs have a role in the evolution and selection of higher order combinatorial TF binding. Indeed, thermodynamic biophysical modelling shows that the evolution of a functional binding site can be accelerated by cooperativity between adjacent TFs56.Taken together, our results suggest that the evolution of key TF-binding motifs was central to NC GRN evolution and that conservation of TF binding at these sites is important for the conservation of the NC GRN. Previous analyses of cis-regulatory TF-binding patterns across gnathostomes showed that, whereas binding motifs are conserved across species, their alignment or positioning is not14, we have presented a genome-wide representation of gene expression and chromatin dynamics during lamprey cranial NC development. A limitation of our approach, which relied on dissection, is that analysed samples included some dorsal neural and ectodermal tissues, and thus our data represent a mixed cell population rather than a pure NC one. However, by focussing our analyses on the genes and chromatin regions that are being dynamically modified during the analysed time-points we were able to extract the expected signature for the cranial NC cells, which unlike skin and neural cells within this mixed cell population, are highly metabolically active and transcriptionally dynamic, owing to a later onset of their specification in the embryo. Taken together, our analyses uncover critical components of the NC GRN that are shared across vertebrates, as well as expose new players whose further investigation will expand our current view of the genetics of NC development.In summary, by taking advantage of our highly contiguous germline genome assemblyPetromyzon marinus) were supplied by the US Fish and Wildlife Service and Department of the Interior. Embryos obtained by in vitro fertilisation, were grown to the desired stage in compliance with California Institute of Technology Institutional Animal Care and Use Committee protocol #1436. Brook lamprey (L. planeri) embryos and ammocoete larvae were collected from a shallow river in the New Forest National Park, United Kingdom, with permission from the Forestry Commission and maintained in filtered river water at 13–19 °C. Prior to dissection, embryos were dechorionated in 0.1 × Marc’s Modified Ringers buffer (MMR) in a dish lined with 1% agarose. For dissection, embryos were moved into a shallow well in the agarose. T18, T20 and T21 DNTs including premigratory, early-delaminating and/or late-delaminating NC cells were dissected from the head using an eye-lash knife. T20 and T23 heads were dissected using forceps.Adult sea lamprey  and whole embryos (two groups of 10) at T20. Tissue was lysed in the Ambion RNAqueous Total RNA Isolation kit lysis buffer (AM1931), set on ice for 15 mins with occasional vortexing, flash frozen in liquid nitrogen and stored at − 80 °C. RNA was extracted using the Ambion RNAqueous Micro Total RNA isolation kit and assessed using the Agilent Bioanalyser. Sequencing libraries were prepared from 100 ng RNA per sample using the NEBNExt Ultra Directional RNA Library Prep Kit for Illumina (E7420) in combination with the NEBNext Poly(A) mRNA Magnetic Isolation Module (E7490) and NEBNext High-Fidelity 2 × PCR Master Mix (M0451S). Libraries were indexed and enriched by 15 cycles of amplification. Library preparation was assessed using the Agilent TapeStation and libraries quantified by Qubit. The concentration of library pools was assessed with the KAPA Library Quantification Kit (KK4835). Multiplexed library pools were sequenced using paired-end 75–100 bp runs on the Illumina NextSeq500 platform for DNT libraries and on the Illumina HiSeq2500 platform for T20 heads and embryos.m Hepes, pH7.5), followed by the addition of an equal volume of trypsin  at room temperature for a total of up to 15 mins. Dissociated cells were passed over a 40-μm cell strainer into Hanks’ solution  and centrifuged at 500 × g for 7 mins at room temperature. The supernatant was removed and fresh Hank’s solution applied. 50,000 cells were counted out and centrifuged for 5 minutes at 500 × g at 4 °C and washed with cold 2/3 phosphate-buffered saline (PBS) by centrifugation for 5 minutes at 500 × g, 4 °C. The cells were resuspended in 50 μl cold lysis buffer  and centrifuged for 10 mins at 500 × g at 4 °C. Cells were tagmented using the Illumina Nextera kit (FC-121–1030) in a 50 μl reaction for 30 mins at 37 °C. To stop tagmentation, EDTA was added to final concentration of 50 nm and the reaction was incubated at 50 °C for 30 mins. Tagmented DNA was cleaned up using the Qiagen MinElute PCR purification Kit (28004) and amplified using the NEB Q5 High-Fidelity 2 × Master Mix (M0492S) for 14 cycles. The amplified library was cleaned up using the Qiagen MinElute PCR purification Kit (28004) and XP AMPure beads (Beckman Coulter A63880). Tagmentation efficiency was assessed using Agilent TapeStation and libraries quantified by Qubit. The concentration of ATAC library pools was assessed with the KAPA Library Quantification Kit (KK4835). Multiplexed library pools were sequenced using paired-end 40 bp runs on the Illumina NextSeq500 platform. The high correlation of the mapped ATAC-seq signal between biological replicates at each stage (Pearson’s R > 0.9) confirms the reproducibility of our experimental approach  with 10% fetal bovine serum at 19 °C. Tissue was first dissociated by pipetting up and down in dispase . Reads were trimmed to remove low quality bases using Sickle (https://githubcom/najoshi/sickle) using the parameters -l 30 -q 20.Read quality was evaluated using FastQC (15 using STAR (v2.4.2)57 . Separate transcriptomes for DNT sample datasets or head and embryo sample data sets were assembled de novo with Cufflinks followed by Cuffmerge using default parameters58 to make a consensus transcriptome from all the data sets. Read counts for DNT data sets were obtained with Subread featureCounts (v1.4.6-p4)59 using the Cuffmerge consensus transcriptome in SAF format as a reference (featureCounts -p -B -M -F SAF -s 2 -T4 -a $SAF -o $OUT $IN.bam). Differential expression and PCA were performed on the DNT readcount data sets using DESeq2 (v.1.8.2)60. Weighted correlation network analysis (WGCNA)22 was performed on the variance stabilised normalised gene count tables generated by DESeq2  according to the pipeline detailed in the online WGCNA tutorial (https://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/WGCNA/). A soft-thresholding power of 20 and minimum module size of 100 was used for WGCNA. Both of these analyses were run on the R platform . The average normalised gene counts that were associated with ATAC-seq peakset clusters for stage T21 samples  were plotted in R using ggPlot geom-violin. Output transcript lists from the differential expression analysis and WGCNA were annotated using the gene models associated with the sea lamprey germline genome assembly. Hox and Sox genes shown in figures were manually annotated with lamprey-specific gene names. Heatmaps of the average variance stabilised normalised gene counts were generated in R using pheatmap. Gene Ontology (GO) analysis was performed on annotated differentially expressed gene sets using the genes with baseMean value > 20, log2 FoldChange > 1 for upregulated and < −1 for downregulated genes and p-adjusted value < 0.01. The PANTHER Overrepresentation Test (v11)61 was used with complete GO term databases for Mus musculus . Output GO terms were filtered to only contain terms that were enriched by at least threefold.Reads were mapped to the sea lamprey germline genome assembly62 intersect. The remaining transcripts were used in a blastx search using default parameters against the UniProt/Swiss-Prot database. Any transcripts that shared > 30% sequence identity with known proteins with an e-value >  1E−2 were eliminated. Any unspliced transcripts were removed and, using bedtools intersect, the list of putative lncRNAs were limited to transcripts that were within 5 kb of a coding gene and originated from the opposite strand to this closest gene. Subread featureCounts was used to determine the length of the remaining transcripts (featureCounts -p -B -F SAF -s 2 -T4 -a $SAF -o $OUT $IN.bam), and those < 200 bp in length were eliminated.To identify putative lncRNAs in our transcriptome, first transcripts that overlapped with coding genes in the germline genome annotation on the same strand were eliminated using bedtools(v.2.15.0)15 using Bowtie263 (bowtie2 --phred33 -p4 -X 2000 --very-sensitive -x $GENOME −1 $R1.fastq −2 $R2.fastq -S $OUT.sam). Duplicates were removed with Picard  MarkDuplicates and the distribution of fragment sizes assessed with Picard (v1.83) CollectInsertSizeMetrics. Replicate bam files for each developmental stage were merged with SAMtools64 and filtered with BamTools65 to remove unpaired reads and reads mapped to the mitochondrial chromosome. Filtered bam files were down-sampled to match the file with the lowest number of reads using Picard (v1.83) DownsampleSam. Downsampled bam files were sorted by name using SAMtools and paired-end bed files were obtained using bedtools(v.2.15.0)62 bamtobed bedpe. Reads were extended to a read length of 100 bp. Peak-calling was performed using MACS266 . Output peak files (.xls) for each developmental stage were converted to bed format and merged with bedtools merge to create one consensus peakset. The consensus peakset was annotated with HOMER  annotatePeaks.pl using the Cuffmerge gene models (with genes less than 1500 bp in length removed) as a reference. Annotated peaks were separated into intergenic, intronic and promoter peaksets according to their HOMER annotation. Promoter peaks were filtered with bedtools flank to only include elements that overlapped a region of up to 2 kb upstream of the sea lamprey germline genome gene models (bedtools flank -i promoters.bed -g germline_genome.chrom.sizes -l 2000 -r 0 –s). Intergenic peaks that overlapped with promoters annotated in the sea lamprey germline genome gene models (i.e. gene models that were not present in the de novo cuffmerge assembly) were identified with bedtools intersect and moved to the promoter peakset. The intergenic and intronic peaksets were further filtered to only contain peaks that were <50,000 bp away from genes that were enriched at stage T21 in comparison with T18 . k-means clustering of ATAC-seq signal over the final peaksets was carried out using SeqMINER67. Read counts for the ATAC-seq signal were obtained with Subread featureCounts (v1.4.6-p4) using the peakset clusters in SAF format as a reference (featureCounts -p -F SAF -T4 -a peaksetCluster.saf). Correlation analysis on ATAC-seq readcount data was performed in R using plot and cor (method=“pearson”). GO analysis was performed on the differentially expressed genes associated with intergenic and intronic “EMT” clusters using the PANTHER Overrepresentation Test (v11)61 with complete GO term databases for Mus musculus. Output GO terms were filtered to only contain terms that were enriched by at least 1.8-fold. Remaining GO terms were summarised with REVIGO68 and subsequently filtered to only contain terms with −log10 p value < −1.5.Reads were mapped to the sea lamprey germline genome assemblySoxE1 enhancer cluster, Supplementary Data P values < α/m. Co-binding predictions were plotted using the Circlize package in R (v.3.2.3). HOMER (v.4.7) annotatePeaks.pl with options –m and –mscore, was used to locate enriched motifs that were identified using findMotif.pl in the full-length SoxE1 enhancer.Motif analysis was performed on the intergenic and intronic peakset clusters with HOMER v4.7) findMotif.pl using a random set of 2329  non-coding genomic regions as control. Heatmaps were generated in R using ggPlot geom-tile. To assess predicted co-binding frequencies for 18 selected TF motifs (selected based on their expression levels) enriched in intergenic cluster 5 .69 by In-Fusion HD cloning (Clontech) and sequenced. ISec-I meganuclease-mediated transgenesis69 was performed in sea lamprey embryos. At 2–6 hours post fertilisation, single-celled embryos were injected with the ISec-I vector digestion mix at 20 ng/μl and maintained at 18 °C in 0.1 × MMR for the remainder of their development. At 1 dpf embryos were transferred to 96-well plates until 6 dpf when they were returned to petri dishes, and screened daily for reporter expression. Live embryos were imaged on a depression slide using a Zeiss Scope.A1 microscope fitted with a Zeiss AxioCam MRm camera and Zeiss ZEN 2012 software (blue edition).A region of ~ 1.5 kb encompassing the ATAC-seq positive accessible chromatin region to be tested was amplified by PCR from sea lamprey genomic DNA using primers designed with SnapGene (Clontech), cloned into the HLC GFP reporter vectorm Triethanolamine (TEA) a total of three times. Embryos were treated with 0.25% Acetic Anhydride in TEA for 12 mins, and then in 0.50% Acetic Anhydride for another 12 mins. Embryos were washed 2 × 5 mins in PBST, then refixed in 4% Formaldehyde  and rinsed 3 ×5 mins or more in PBST. Embryos were then rinsed 3 × 5–10 mins in Hybridisation Buffer (hyb), then incubated for 3 h at 68 °C in 500 µl of fresh hyb. This solution was replaced with fresh, hot hybridisation buffer preincubated with each appropriate antisense digoxigenin-labelled riboprobe diluted to ~ 1 ng/mL of hyb and vials were incubated at 68 °C overnight with slow, minimal shaking. After 12–16 h, hybridisation solution was removed and replaced with fresh hyb. Samples were washed 3 × 30 min in pre-heated hyb solution. Most hyb was removed, except for ~ 500 µL, and an equivalent volume of pre-heated 2 × SSC was added, lightly mixed, and vials were incubated at 68 °C for 15 mins. Samples were then washed 3 × 30 mins in 2 × SSC, followed by 3 × 30 mins in 0.2 × SSC. Glass vials were allowed to slowly equilibrate to room temperature, then embryos were rinsed several times in RT MABT, then rinsed into MABT block (1 × MAB plus 2% Roche blocking solution and 0.1% Tween). Embryos were incubated in 500 µL of fresh MABT block for 1 h at RT, and then blocking solution was replaced with antibody solution and left to incubate overnight at 4 °C with slow shaking. Vials were washed twice with MABT block, 30 min each, then washed 5 × 30 mins in MABT, and 2 × 60 mins or more in MABT. Embryos were removed from borosilicate vials and placed into 12-well culture plates, rinsed 3 × 10 min in alkaline phosphatase buffer. Buffer was replaced with BM Purple and samples were kept dark. When colour reaction was complete, embryos were rinsed in MABT, then post-fixed in 4% paraformaldehyde overnight at 4 °C. For imaging, embryos were dehydrated in a graded series of ethanols, rinsed in 100% methanol 4–5 times, and cleared for 3 × 3–5 mins in Murray’s Clear . Murray’s Clear was removed and replaced with Permount, and embryos were individually mounted on slides, with coverslips having clay feet to act as spacers. Embryos were visualised on a Zeiss Axioimager.Lamprey embryos were placed in glass vials and fixed overnight at 4 °C in MEMFA. They were then rinsed in PBST, dehydrated in a graded series of ethanol washes and stored in 100% ethanol at − 20 °C. Embryos to be analysed were transferred to fresh 100% ethanol in 1-dram glass vials. Embryos were rehydrated and rinsed three times for 5 mins each in PBST. Embryos were treated with 20 µg/ml solution of proteinase K in PBST at room temperature, for precisely three minutes, then immediately rinsed twice in PBST. Samples were then washed five minutes in 0.1 Embryos were fixed at 4 °C overnight in 4% paraformaldehyde in PBS. Fixed embryos were incubated in PBS with 5% sucrose for 4 h at room temperature, followed by incubation overnight at 4 °C in 15% sucrose in PBS. Embryos were transferred into pre-warmed 7.5% gelatine in 15% sucrose in PBS and incubated overnight at 37 °C, before being transferred to pre-warmed 20% gelatine in PBS. Embryos were embedded in rubber moulds and frozen by immersion in liquid nitrogen. Blocks were cryosectioned at 6–10 µm. Gelatine was removed from the slides by a 5-minute incubation in PBS pre-warmed to 37 °C. For Immunostaining, slides were incubated overnight at room temperature in Alexa 488 conjugated anti-GFP antibody  in blocking solution (10% donkey serum in PBS with 0.1% Triton X-100). Sections were imaged on a Zeiss LSM 780 inverted confocal microscope with Zeiss ZEN 2011 (black edition).L. planeri genomic DNA was extracted from the heads of three individual ammocoete larvae. Tissue was treated with Proteinase K overnight at 50 °C, followed by phenol-chloroform extraction and ethanol precipitation. PCR was first performed with the same primers used to clone the P. marinus SoxE1 enhancer . This product was further amplified in a secondary PCR using primers specific to the L. planeri genomic sequence obtained from ATAC-seq data . PCR products were sequenced and resulting sequences were merged using Fragment Merger70 and aligned using SnapGene (Clontech) to generate a consensus sequence. The consensus sequence was aligned to the P. marinus SoxE1 enhancer sequence from the germline genome assembly and the L. planeri embryonic ATAC-seq consensus sequence using Clustal Omega in SnapGene (Clontech). The presented alignment was prepared with BOXSHADE  using the “ASCII_differences” output format.Guide for the Care and Use of Laboratory Animals. The lamprey SoxE1 enhancer was cloned into the Ac/Ds-E1b-EGFP vector (http://www.addgene.org/102417/) using In-fusion cloning (Clontech) and co-injected with Ac transposase mRNA into one-cell-stage zebrafish embryos. Injected F0s were screened for founders. Positive F1s were grown to reproductive age and backcrossed to F0s to obtain embryos with bright expression.This study was carried out in accordance to procedures authorised by the UK Home Office in accordance with UK law  and the recommendations in the Zebrafish embryos were fixed in 4% paraformaldehyde for 1 h at room temperature and washed in PBT (1 × PBS containing 0.5% Triton X-100 and 2% DMSO). When necessary embryos were bleached prior to being blocked in either 10% Donkey serum or 3% BSA in PBT for 2 h and washed in antibody solution  overnight at 4 °C. Embryos were washed several times in PBT before adding the secondary antibody  in combination with Hoescht (1:1000) for 2 h at room temperature. After several PBT washes, embryos were imaged in whole-mount on a Zeiss LSM 780 upright multiphoton confocal microscope with Zeiss ZEN 2011 (black edition). To obtain sections of whole-mount immunostained samples, embryos were cryoprotected in 30% sucrose in PBS and embedded in OCT by immersion in liquid nitrogen. Sections were imaged on a Zeiss LSM 880 inverted confocal microscope with Zeiss ZEN 2.3 (black edition).71, a kit containing a DNA probe set, a DNA HCR amplifier, and hybridisation, wash and amplification buffers were purchased from Molecular Instruments for each target mRNA. The GFP and SoxE1 probes initiate B3 (Alexa-546) and B4 (Alexa-647) amplifiers, respectively. Embryos were fixed overnight at 4 °C in MEMFA. They were then rinsed in PBST, dehydrated in a graded series of ethanol washes and stored in 100% ethanol at − 20 °C. Following rehydration, embryos were treated with 10 mg/ml Proteinase K for 2.5 min and post-fixed in 4% paraformaldehyde for 20 min. Embryos were incubated with the probes in hybridisation solution overnight at 37 °C and, following appropriate washes, incubated in the hairpin solution in amplification buffer overnight at room temperature protected from light. Embryos were imaged in whole-mount using a Zeiss LSM 780 upright multiphoton confocal microscope with Zeiss ZEN 2011 (black edition).For in situ hybridisation chain reaction (HCR)72 five positive F2 zebrafish embryos from a single F1 parent outcrossed to wild type were collected and genomic DNA extracted. Approximately 500 ng of genomic DNA was digested overnight with AluI in a 30 μl reaction. Digested genomic DNA was purified using phenol-chloroform followed by ethanol precipitation before ligation with annealed splinkerette adaptors (CGAATCGTAACCGTTCGTACGAGAATTCGTACGAGAATCGCTGTCCTCTCCGGCCACAGGCGATTAT and ATAATCGCCTGTGGCCAAATCTATACGTATAGAT) using T4 DNA ligase at 16 °C overnight in a thermal cycler. The adaptor-ligated genomic DNA was purified using Zymo Research Clean & Concentrate (Cat. # D4003) and 20 ng of purified product used in a primary PCR reaction. PCR was performed using the following primers: CGAATCGTAACCGTTCGTACGAGAA (binding to adaptor) and GTTTCCGTCCCGCAAGTTAA (binding to Ds-3′ integration arm), with 63 °C annealing temperature and 3 min extension time. 1 μl of primary PCR reaction was then used in 50 μl nested PCR reaction using the following primers: TCGTACGAGAATCGCTGTCCTCTC (binding to adaptor) and CGGTAGAGGTATTTTACCGAC (binding to Ds-3′ integration arm), with 60 °C annealing temperature and 5 mins extension time. The nested PCR was run on agarose gel to visualise number of integrations.For splinkerette analysisSoxE1 enhancer was cloned into the pTK vector73 with EGFP replaced by citrine, using In-fusion cloning (Clontech). Fertilised wild-type chicken eggs were obtained from Henry Stewart & Co (Norfolk). HH8 chicken embryos were electroporated in ovo. The SoxE1-pTK-citrine and NC2-pTK-mCherry46 constructs were injected into the neural tube at 3.0 μg/μl each and electroporated bilaterally with 3 + 3 50 ms pulses at 12.5 V with 100 ms rest between pulses. The embryos were incubated at 37 °C until HH18 and imaged in whole-mount using a Zeiss LSM 780 upright multiphoton confocal microscope with Zeiss ZEN 2011 (black edition).The lamprey hoxb2a, hoxb3a, hoxa2b, sox10 and tfap2a were annealed and RNA in vitro transcribed using HiScribe T7 Quick High Yield RNA Synthesis Kit , followed by purification using MEGAclear Transcription Clean-Up Kit . To maximise mutagenesis, a pool of up to two sgRNAs per target gene (Supplementary Table 74 into one-cell stage embryos obtained by crossing Tg(SoxE1_dwnstrm1-E1b:EGFP)ox 164 and Tg(tcf21:DsRed2)pd3775. For each condition , ~ 25–30k DsRed2-positive cells that included branchial arches were obtained from 3 days post fertilisation (dpf) embryos by FACS on BD FACSAria Fusion. Total RNA was extracted and DNaseI-treated according to manufacturer’s protocol using RNAqueous-Micro Total RNA Isolation Kit . Reverse transcription was performed on three biological replicates using GoScript Reverse Transcriptase Mix + Oligo(dT) . To quantify levels of EGFP transcripts, qPCR was performed using Fast SYBR Green Master Mix  on Applied Biosystems 7500 Fast system using the following primers: EGFP at 300 nm final concentration: F_EGFP (AAGGGCATCGACTTCAAGGA) and R_EGFP (TGATGCCGTTCTTCTGCTTG); bactin at 150 nm final concentration: beta-actin_E3 (AATCCCAAAGCCAACAGAGA) and beta-actin_E4 (ACATACATGGCAGGGGTGTT) with three technical replicates per biological replicate. Results were analysed using the delta–delta Ct method.Oligo templates for guide RNAs (sgRNAs) targeting splice acceptor/exon boundaries of functional domains for Further information on research design is available in the  InformationSupplementary Dataset 1Supplementary Dataset 2Supplementary Dataset 3Supplementary Dataset 4Reporting SummaryDescription of Additional Supplementary FilesPeer Review File


Oligodendrocytes provide metabolic and functional support to neuronal cells, rendering them key players in the functioning of the central nervous system. Oligodendrocytes need to be newly formed from a pool of oligodendrocyte precursor cells (OPCs). The differentiation of OPCs into mature and myelinating cells is a multistep process, tightly controlled by spatiotemporal activation and repression of specific growth and transcription factors. While oligodendrocyte turnover is rather slow under physiological conditions, a disruption in this balanced differentiation process, for example in case of a differentiation block, could have devastating consequences during ageing and in pathological conditions, such as multiple sclerosis. Over the recent years, increasing evidence has shown that epigenetic mechanisms, such as DNA methylation, histone modifications, and microRNAs, are major contributors to OPC differentiation. In this review, we discuss how these epigenetic mechanisms orchestrate and influence oligodendrocyte maturation. These insights are a crucial starting point for studies that aim to identify the contribution of epigenetics in demyelinating diseases and may thus provide new therapeutic targets to induce myelin repair in the long run. Oligodendrocytes (OLs) are myelinating glial cells within the central nervous system (CNS) that insulate neuronal axons to provide them with trophic, metabolic and functional support. OLs are generated from oligodendrocyte precursor cells (OPCs) via a consecutive process of cell cycle exit, maturation, and differentiation . OPCs arOPCs arise from the ventricular zone during early development, proliferate and migrate their way into the different developing areas of the brain, where they differentiate into myelin-forming OLs . Unlike The regulatory network of transcription factors that controls OL lineage development has been extensively studied over the past decades ,11,12. TThe main transcription factors that regulate OL lineage progression belong to the helix-loop-helix (HLH) family, such as the oligodendrocyte transcription factors (OLIG), hairy and enhancer-of-split homologs (HES) and inhibitor or differentiation (ID) proteins. OLIG2 is considered as one of the major and indispensable transcription factors during different stages of OL development. It is an essential factor during OPC specification, enhances OPC migration during early development, but also functions as a promoting factor of OL differentiation and regeneration in the adult life ,14,15. IAnother family of transcriptional regulators are HMG-domain transcription factors, that are classified as the sex determining region Y-box (SOX) family, of which SOX10 is a well-established regulator involved in terminal OL differentiation and myelination, through its direct binding to the promoter region of myelin genes to enhance their ,23. InteAn additional class of OL-related transcription factors are zinc finger proteins (ZFP). Yin Yang 1 (YY1) stimulates OL differentiation by silencing inhibitor proteins, such as ID4 and TCF4 . Other ZAll the transcriptional regulators influence OL differentiation mainly by controlling the expression of genes that encode for the essential myelin-associated proteins, such as the myelin basic protein (MBP), proteolipid protein (PLP) and myelin-associated glycoprotein (MAG) ,36. The OL lineage development and the regulation of the associated transcriptional program is highly influenced by various epigenetic processes. Epigenetic mechanisms are defined as modifications that affect gene expression without altering the DNA sequence itself and are heritable from mother to daughter cell ,39. EpigDNA methylation, in particular CG methylation, is one of the most studied and long-lasting epigenetic modifications. CG methylation involves the addition of a methyl-group (–CH3) to a cytosine base followed by a guanine nucleotide, referred to as 5′cytosine–guanine–3′ dinucleotide (CpG) site. Although various definitions exist, so-called ‘CpG islands’ cover regions of more than 300 bp with a C/G-content of 50% at minimum and are mostly found within the promoters of protein coding genes . MethylaDnmt1 gene in embryonic progenitor cells led to OPC growth arrest and resulted in severe hypomyelination. Moreover, this loss of Dnmt1 seemed to alter splicing events, such as exon skipping and intron retention, in genes related to myelination, lipid metabolism and the cell cycle, indicating a crucial role of DNA methylation in relation to alternative splicing during neonatal OL development [Dnmt3a showed impaired OL differentiation and a reduced ability to remyelinate affected axons after injury [Tet mRNA levels was associated with increased expression of HLH inhibitory transcription factors, such as ID2 and HES5, leading to suppression of myelin gene expression [One of the first studies that linked DNA methylation to OL development showed that neonatal rats treated with the DNMT-inhibitor 5-azacytidine (5-aza), displayed disrupted gliogenesis, concomitant with hypomyelination of the 11-day-old optic nerve. Postnatal inhibition of DNA methylation resulted in a reduced number of oligodendrocytes, whilst the number of astrocytes was less affected, indicating a higher vulnerability of OPCs to changes in DNA methylation . Likewiselopment . Althougelopment . After lr injury . Together injury . Even thpression . It howeIn relation to the transcriptional regulatory network of OL development, it has been shown that DNA methylation can regulate the temporal expression of these transcription factors. In a study of Huang et al., PRMT5 was identified as a pro-differentiation factor that binds to CpG-rich islands within the ID2 and ID4 genes. Subsequent DNA methylation of these regions led to silencing of the transcriptional inhibitors and resulted in OL differentiation . In a siHistone modifications encompass a wide range of post-translational changes on histone tails, such as histone (de)acetylation, methylation, ubiquitination, and phosphorylation. These modifications can act separately or together to orchestrate chromatin dynamics and structure. Depending on the obtained histone code, DNA accessibility for polymerases and transcription factors can be either promoted or hampered .The most prevalent type of histone modifications is (de)acetylation of the lysine (K) residues. Acetylation is established by histone acetyltransferases (HATs), whilst removal of the acetyl groups is maintained by histone deacetylases (HDACs). Histone acetylation neutralizes the positive charge of the lysine residues, resulting in a weaker interaction between the histone proteins and the DNA, eventually leading to an ‘open’ chromatin structure. Consequently, HDACs function to make the chromatin more compact, thereby preventing transcriptional processes from occurring ,60. WherId2, Id4 and Hes5, where it can block the expression of these genes [Interestingly, HDACs can also regulate and promote OL development in a (partly) histone-independent manner, as interaction of HDACs with other transcriptional regulators can result in repressive complexes that counteract the expression of OPC differentiation inhibitors. For instance, studies conducted on murine OPCs have shown that the pro-differentiation factor YY1 is recruited via HDAC1 to the promoter region of se genes . Proteinse genes . Furtherse genes .Another type of histone modification that has been associated with OL development is histone methylation. Histone methylation can occur either on lysine or arginine side chains and is associated with both activation and repression of transcription, depending on the site of methylation . During Olig2 promoter in order to regulate its expression during early development [Cdh7, an ATP-dependent chromatin remodeler of the chromodomain helicase DNA-binding (CHD) family. CHD7 is highly expressed in differentiating OLs, and functions synergistically with SOX10 to enhance myelin-associated gene expression. Furthermore, CHD7 promotes the expression of other positive transcription factors during OL maturations, such as Myrf and Olig1 [Next to the abovementioned histone-modifying enzymes, ATP-dependent chromatin remodeling complexes have also been recently shown to influence and orchestrate OPC differentiation. These complexes make use of ATP as an energy source to reposition nucleosomes, thereby altering histone accessibility and gene transcription . The helelopment . As a poelopment . One of nd Olig1 . Interesnd Olig1 ,76.Small non-coding RNAs (ncRNAs) are powerful endogenous regulators of gene expression. Many ncRNAs have been comprehensively described, such as Piwi-interacting RNAs (piRNAs), small interfering RNAs (siRNAs) and miRNAs, with these latter being the most widespread and abundant ncRNAs . MiRNAs Sox6, Hes5 and Pdgfrα), its increase stimulates OPCs to exit from the proliferative cycle and enter differentiation [Hes5 and Sox6, miR-219 indirectly elevates the expression of monocarboxylate transporters, leading to increased OL numbers and enhanced protein levels of MBP and CNP, which subsequently attenuates cuprizone-induced demyelination [During OL development, a coordinated interplay between multiple miRNAs determines OPC cell fate by downregulating intrinsic and extrinsic transcription factor expression ,84. The ntiation . By supplination . MiR-219lination . MiR-219lination ,89. Furtlination ,91.In contrast to the induction of several miRNAs, miR-9 is downregulated during OL differentiation ,93. In lMany other miRNAs have been described to be either positively or negatively involved in OL differentiation processes. In vivo studies have shown an increased generation of myelin proteins upon miR-146a overexpression in primary OPCs following demyelinating injuries, thereby highlighting the positive relationship between miR-146a and OL differentiation ,100. SimCurrent knowledge about the strong involvement of epigenetic mechanisms in OL development has led to new perspectives on OL- and myelin-related pathologies. Over the past years, a considerable amount of research has been conducted with regard to aberrant epigenetic regulation and its impact on OL regeneration and myelin repair. Hence, in this part of the review, we focus on what is known about epigenetic malfunctioning during OL regeneration and remyelination, both in the context of ageing and myelin-related pathologies.It is generally known that regenerative processes become less efficient with increasing age. A classic example is age-related deficits in remyelination, a process which is entirely dependent on OL regeneration to restore the myelin sheath ,107,108.Up to now, only one study has connected changes in methylation in OPCs/OLs to cellular ageing . Rat OPCIn a study conducted by Pusic et al., aged rats were exposed to a youthful environment in a Marlau-style enrichment cage to assess the effect on remyelination capacity ,116. EnvMultiple sclerosis (MS) is a multi-faceted immune-driven demyelinating disease of the CNS. MS is characterized by inflammation-induced demyelination during the early stages, which eventually results in gradual neurological disability as the disease progresses ,118. ThePAD2 gene is hypomethylated in normal appearing white matter (NAWM) of MS patients, compared to control samples [PAD2 hypomethylation leads to a higher expression of the enzyme, which finally results in the destabilization and degradation of the myelin sheath in MS white matter. PAD2 hypomethylation is, surprisingly, not brain-specific but can also be observed in peripheral blood mononuclear cells (PBMCs) of MS patients [MOG gene, which is associated with OL cell death and demyelinating events in the brain [Analysis of MS postmortem samples revealed increased levels of MBP citrullination, a post-translational modification which renders the MBP protein less stable, leads to the degradation of myelin and can eventually result in the development of an auto-immune response against myelin ,130. MBPpatients . In a sihe brain . The corhe brain ,134,135,BCL2L2, NDRG1) and myelination  were hypermethylated and decreased in expression in MS-affected tissue, compared to controls [An epigenome-wide DNA methylation study (EWAS) was conducted on MS NAWM postmortem samples. Genes responsible for OL survival . In contrast, OLs present in early MS lesions show the presence of deacetylated histones [Another study that analyzed postmortem brain tissue of MS patients showed higher levels of histone acetylation in oligodendrocytes within chronic MS lesions, compared to non-neurological controls. These changes are associated with elevated HAT transcript levels and higher expression of inhibitory regulators , which target enzymes that are involved in the production of neurosteroids . OpposinIt is however noteworthy that most of the abovementioned studies have been conducted on bulk tissue, leading to a possible noise introduced by the cellular heterogeneity. Since the observed epigenetic changes could be strongly influenced by cellular variation or cell numbers, cell type-specific validation is recommended to circumvent such bias ,142.Even though MS is regarded as the most common myelopathy of the CNS, many other neurological diseases are characterized by oligodendroglial injury and myelin disruption. Here, we briefly discuss how epigenetic changes impact OL regeneration and remyelination in relation to these other demyelinating diseases.Ischemic stroke, caused by a cerebral artery occlusion, is an important cause of death worldwide and the majority of survivors often struggle from severe neurological disabilities throughout the lifespan. Molecularly, ischemic stroke can be characterized by a disrupted architecture of neuronal synapses, neuronal loss and loss of glial cells, including oligodendrocytes, leading to prominent white matter demyelination . During ABCD1 gene and characterized by progressive demyelination of the CNS [MBP, PLP1, MOG and CNP were hypermethylated in X-ALD patients compared to age-matched controls. Furthermore, transcriptional inhibitors (ID4 and SOX2) displayed an increased expression in these patients, suggesting a disturbed HDAC activity [LMNB1), which leads to overexpression of LMNB1 and causes severe myelin loss [X-linked adrenoleukodystrophy (X-ALD) is a genetic disorder caused by a mutation in the  the CNS . An impo the CNS . X-ALD p the CNS . An EWASactivity . In lineactivity . Anotherlin loss . Intereslin loss .SOX10 is hypermethylated in brains of patients with schizophrenia, which is directly associated with a decreased expression of SOX10 and other OL-related genes [Schizophrenia has also been associated with OL dysfunction. Interestingly, the CpG island within the promoter region of ed genes .It is clear that epigenetic modifications strongly influence OL development and functional remyelination in a wide variety of diseases. Targeting these epigenetic alterations could therefore be considered as a new therapeutic strategy to overcome remyelination failure. Most attempts to pharmacologically manipulate epigenetic modulations are based on the use of inhibitors of epigenetic enzymes, such as 5-aza, TSA and valproic acid (VPA) ,164. HowAutologous cell-based therapies have emerged as a promising technique to restore OL dysfunction. Mature and fully differentiated OLs derived from induced pluripotent stem cells (iPSCs) have shown to successfully remyelinate axons in rodents . InteresIn this review, we have discussed how different epigenetic modifications influence OL development and lineage progression and how this is dysregulated in demyelinating conditions. Epigenetic mechanisms function as a precise gateway control system that governs the transcriptional machinery in a spatiotemporal manner. In CNS demyelinating diseases, these epigenetic mechanisms are found to be altered, concomitant with increased levels of transcriptional inhibitors and resulting in a differentiation block of OPCs. Targeting these epigenetic processes, either by pan-inhibitors or via CRISPR/Cas9-mediated epigenetic editing, could therefore be a potential strategy to boost OL differentiation and (re)myelination. Taken together, epigenetic research has earned its place within the universe of OL development and further studies will contribute to the complete understanding of CNS myelin disorders.


LGALS3) is a glycan-binding protein that regulates a diverse range of pathophysiological processes contributing to the pathogenesis of human diseases. Previous studies have found that galectin-3 levels are up-regulated in the liver by a host of different injurious stimuli. The underlying epigenetic mechanism, however, is unclear. Here we report that conditional knockout of Brahma related gene (BRG1), a chromatin remodeling protein, in hepatocytes attenuated induction of galectin-3 expression in several different animal models of liver injury. Similarly, BRG1 depletion or pharmaceutical inhibition in cultured hepatocytes suppressed the induction of galectin-3 expression by treatment with LPS plus free fatty acid . Further analysis revealed that BRG1 interacted with AP-1 to bind to the proximal galectin-3 promoter and activate transcription. Mechanistically, DNA demethylation surrounding the galectin-3 promoter appeared to be a rate-limiting step in BRG1-mediated activation of galectin-3 transcription. BRG1 recruited the DNA 5-methylcytosine dioxygenase TET1 to the galectin-3 to promote active DNA demethylation thereby activating galectin-3 transcription. Finally, TET1 silencing abrogated induction of galectin-3 expression by LPS plus palmitate in cultured hepatocytes. In conclusion, our data unveil a novel epigenetic pathway that contributes to injury-associated activation of galectin-3 transcription in hepatocytes.Galectin-3 (encoded by  Transcriptional regulation in mammalian cells is acutely influenced by the epigenetic machinery, which includes DNA and histone modifying enzymes, chromatin remodeling proteins, and non-coding regulatory RNAs . DNA is Brahma related gene (BRG1) is the core component of the mammalian SWI/SNF chromatin remodeling complex . Along wLGALS3, belongs to a family of glycan-binding proteins regulating such fundamental cellular functions as proliferation, migration, differentiation, apoptosis, and inflammation . To induce liver injury, 6∼8 week male mice were fasted overnight before receiving a single injection of APAP (Sigma) at 300 mg/kg. Alternatively, 6∼8 week male mice were given a single injection of CCl4  as previously described  that carry short hairpin RNA (shRNA) targeting Brg1 (GCUGGAGAAGCAGCAGAAG) as previously described  mice were obtained by crossing the f/f mice  with theescribed . To induescribed . Alternaescribed . To sileescribed .Primary mouse hepatocytes were isolated and maintained as previously described . HepG2 cGapdh mRNA values. All experiments were repeated three times.RNA was extracted with the RNeasy RNA isolation kit (Qiagen). Reverse transcriptase reactions were performed as previously described using a SuperScript First-strand Synthesis System (Invitrogen) . Real-tiWhole cell lysates were obtained by re-suspending cell pellets in RIPA buffer with freshly added protease inhibitor tablet (Roche). Immunoprecipitation was performed essentially as previously described . BrieflyLGALS3 promoter (-402/-73), 5′-AATTTGTAGTCAGTTCCCTAG-3′ and 5′-AAATACTCCCAGCCCCGC-3; for LGALS3 promoter (-1276/-959), 5′-ATACCTGGTTTTCTCCATAG-3′ and 5′-ATATTGCCTATAAGCTACCC-3′.Chromatin immunoprecipitation assays were performed essentially as described before . In briepost hoc Scheffe analyses were performed to evaluate the differences using an SPSS package . The differences between two  groups were determined by two-sided, unpaired Student’s t-test.Data are presented as mean ± SEM. For experiments concerning multiple groups, one-way ANOVA with 4 was administered for 6 weeks. Hepatic galectin-3 expression was significantly up-regulated in CCl4-injected mice at the mRNA  demethylation on the galectin-3 promoter we naturally hypothesized that it may interact and recruit the TET family of dioxygenases to the galectin-3 promoter. As shown in Galectin-3 levels are sensitive to the disruption of cellular homeostasis . Here weSMARCA4 promoter encoding BRG1 has yet to be functionally characterized. SMARCA4 mRNA to down-regulate BRG1 expression in human lung cancer cells. In addition, specific ubiquitin ligases have been also been identified for BRG1  transcription in endothelial cells . KDM3A hfor BRG1 . Clearlyfor BRG1 . Dragomifor BRG1 . More reteatosis . TherefoWe provide evidence to implicate an interaction between BRG1 and the DNA dioxygenase TET1 in the induction of galectin-3 expression. Fazzio and colleagues have previously shown that BRG1 and TET1 can be purified from the same mega-protein complex in embryonic stem cells (ESCs) . CoincidIn summary, our data unveil a novel epigenetic pathway that contributes to galectin-3 trans-activation during liver injury. Further studies using animal models will not only validate the current working model  but provThe raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.The animal study was reviewed and approved by the Nanjing Medical University Ethics Committee on Humane Treatment of Experimental Animals.YX and MF conceived the project. ZL, FL, MF, CJ, and YX designed the experiments. ZL, FL, QW, CJ, and MF performed the experiments, collected the data, and analyzed the data. CJ, CD, and MF provided funding and supervised the project. YX wrote the manuscript with inputs from all authors.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We demonstrate that in vivo enhancers specify muscles in accordance with myofiber composition, show little resemblance to cultured myotube enhancers, and identify glycolytic and oxidative muscle-specific regulators. Moreover, we find that voluntary wheel running and muscle-specific peroxisome proliferator–activated receptor gamma coactivator-1 alpha (Pgc1a) transgenic (mTg) overexpression, which stimulate endurance performance in mice, result in markedly different changes to the epigenome. Exercise predominantly leads to enhancer hypoacetylation, whereas mTg causes hyperacetylation at different sites. Integrative analysis of regulatory regions and gene expression revealed that exercise and mTg are each associated with myocyte enhancer factor (MEF) 2 and estrogen-related receptor (ERR) signaling and transcription of genes promoting oxidative metabolism. However, exercise was additionally associated with regulation by retinoid X receptor (RXR), jun proto-oncogene (JUN), sine oculis homeobox factor (SIX), and other factors. Overall, our work defines the unique enhancer repertoires of skeletal muscles in vivo and reveals that divergent exercise-induced or PGC1α-driven epigenomic programs direct partially convergent transcriptional networks.Skeletal muscles consist of fibers of differing metabolic activities and contractility, which become remodeled in response to chronic exercise, but the epigenomic basis for muscle identity and adaptation remains poorly understood. Here, we used chromatin immunoprecipitation sequencing of dimethylated histone 3 lysine 4 and acetylated histone 3 lysine 27 as well as transposase-accessible chromatin profiling to dissect  The epigenomic basis for the identity and adaptation of different muscle groups is poorly understood. This study reveals chromatin landscapes across muscle groups and their dynamic response to either exercise or overexpression of PPAR gamma coactivator 1 alpha. Myh7, Myh2, Myh1, and Myh4, respectively. Oxidative muscles have high levels of Myh7 and are rich in mitochondria and myoglobin (Mb), densely vascularized, and fatigue resistant, thereby supporting endurance. Conversely, glycolytic muscles have high levels of Myh4 and use glucose and anaerobic respiration, facilitating movements that require rapid energy availability )  compared with Quad from untrained wild-type controls . Accordingly, no differentially dimethylated regions were identified in Ex Quad, and only 32 differentially H3K4me2-marked regions were found in mTg Quad compared with controls . However, H3K27ac was far more dynamic . Additionally, we performed an unsupervised clustering of all H3K27ac-marked regions identified in Quad from all experimental conditions  and Sol of untrained mice . This analysis revealed that untrained and mTg Quad share a high degree of similarity, whereas Ex Quad exhibits the most disparate H3K27ac landscape. These findings led us to conclude that overexpression of Pgc1a reprograms the H3K27ac landscape to an intermediate profile between untrained Quad and untrained Sol, whereas exercise shifts Quad regulatory region activity to more closely resemble an untrained Sol than an untrained Quad.Next, we interrogated the chromatin regulatory landscape of Ex and mTg mice in a manner similar to our previous analysis. ChIP-seq in the Quad of Ex or mTg mice revealed that H3K4me2 marks were highly correlated  or PGC1α-modified regions (PMRs) localized outside of gene promoters . More than half of EMRs and PMRs colocalized with H3K4me2 peaks, and the remainder generally exhibited lower but apparent H3K4me2 signals suggestive of active enhancers . Over 85%  of EMRs were hypoacetylated in Ex Quad ( top), whereas more than 68%  of PMRs were hyperacetylated in mTg Quad ( bottom). Remarkably, only 10% of differentially acetylated genomic regions (274 peaks) were cotargeted by exercise and Pgc1a overexpression . These findings suggested that exercise targets enhancers that appear PGC1α independent, and it more often suppresses than increases their activity.To understand the epigenomic impact of exercise and the degree to which it is mimicked by Fig 6G). Quantitative analysis of H3K4me2 and H3K27ac marks within 1 kb of the EMR centers confirmed significant overall exercise-induced reductions of each modification, with 18% loss in H3K4me2 and 50% loss in H3K27ac . Additionally, to test the durability of H3K27ac changes at EMRs, we subjected mice to 4 weeks of voluntary wheel running but removed wheels 72 hours prior to tissue harvest for H3K27ac ChIP-seq. Significant hypoacetylation (11% reduced) persisted at EMRs in these detraining mice , although the difference was more moderate than in continuously trained animals. In mTg mice, we also observed a modest yet significant (7%) overall reduction in H3K27ac signal at EMRs but no change in H3K4me2 . At PMRs, H3K4me2 marks were slightly reduced in both Ex and mTg mice, whereas H3K27ac marks were accentuated by 60% in mTg mice but diminished by 25% in Ex mice . Notably, mTg muscles had enriched levels of F4/80 and Cd11b, as well as Cd31 and vascular endothelial growth factor A (Vegfa), in line with their reportedly increased tissue-resident macrophage content and vascularity  [MyoD]), and MTs (myogenin [MyoG]) indicated no changes in the cellular composition of Ex muscles despite higher Mb levels from chronic training . These findings suggested that the epigenome of Ex muscle reflects its native cell population, whereas altered cellularity could contribute to signals in mTg tissue. Overall, these findings indicated that exercise and PGC1α differentially target a subgroup of skeletal muscle cis-regulatory domains and their activities.To further examine differentially acetylated sites, we quantified H3K27ac and H3K4me2 marks centered on EMRs and PMRs in Ex and mTg mice as well as their respective controls. At EMRs, Ex mice generally exhibited H3K27ac hypoacetylation  ,35. HoweFig 7A) and were enriched for basic leucine zipper domain factors (bZIP) , CCAAT box-binding transcription factor (CTF), transcription factor 3 (TCF3), and NK2 homeobox (NKX2) binding sites . Consistent with motif predictions, ChIP qPCR analysis confirmed occupancy of c-JUN at a subset of hyperacetylated EMRs . In contrast, hyperacetylated PMRs mapped to genes controlling lipid metabolism ( top) and were overrepresented in MEF2 and ERR motifs ( left). Hypoacetylated EMRs localized to lipid metabolic and muscle contraction genes as well as interferon, insulin, and cytokine signaling components  and were enriched in MEF2, SIX, pre-B-cell leukemia homeobox1 (PBX1), nuclear receptor (NR), and NRF motifs . In line with motif predictions, SIX1 binding was detected at a subset of hypoacetylated EMRs . In contrast, hypoacetylated PMRs annotated to genes implicated in apoptosis, differentiation, polyamine metabolism, and bone morphogenetic protein (BMP) and G-protein–coupled signaling, and they contained recognition sites for TEAD, MYOG, BTB domain and CNC homolog (BACH), and JUN ( bottom and  right). Thus, differential enhancer analysis predicted exercise to direct MEF, SIX, NRs, and bZIPs to tissue remodeling and metabolic gene enhancers, whereas PGC1α was anticipated to coactivate ERR and MEF2 at sites along lipid metabolic genes.We next performed DNA motif analyses at hyper- and hypoacetylated peak sets for both EMRs and PMRs and annotated these to nearby genes. Hyperacetylated EMRs localized to genes involved angiogenesis, matrix remodeling, and chemokine and platelet-derived growth factor (PDGF) signaling . In contrast, significant activity scores were all higher in mTg muscle and included ARID and many homeobox motifs . Although footprinting produced a number of different motifs than our EMR and PMR H3K27ac-based analyses, it is notable that many transcription factors do not leave measurable footprints on DNA and thus limit this approach [To complement our histone mark–based analysis, we performed ATAC-seq in Quad skeletal muscles and identified peaks from sedentary control , exercise-trained , and mTg mice . Although we identified few differences between conditions with respect to open chromatin regions , we further analyzed our data sets to detect small stretches of DNA protected from transposase cleavage due to transcription factor binding, which are known as DNA footprints. Using the Hmm-based identification of transcription factor footprints (HINT)-ATAC computational pipeline , we idenapproach .p-value < 0.05) ( left). mTg mice demonstrated many more changes in expression, with 2,843 up-regulated and 2,739 down-regulated genes ( right). Principal component analysis confirmed that genotype was the dominant variable, whereas exercise was secondary, and experimental replicates from each condition clustered tightly . Nearly two-thirds of exercise-regulated transcripts were also impacted by Pgc1a overexpression , and expression changes positively correlated among 89%  of these between the two models . Genes altered similarly in Ex and mTg muscles were implicated in glucose, nucleotide, and particularly, fatty acid metabolism, as well as insulin and mammalian target of rapamycin (mTOR) signaling ( clusters 1 and 4). However, 115 genes were oppositely controlled by Ex and mTg and annotated to genes with functions in muscle structure and regulation of reactive oxygen species . Additionally, 541 transcripts were altered by exercise but not impacted by Pgc1a overexpression. These exercise-exclusive targets were associated with muscle development and contraction, extracellular matrix organization, and protein and nucleotide metabolism . In summary, despite eliciting highly divergent epigenomic profiles, exercise and Pgc1a overexpression similarly regulate transcription among metabolic genes, but exercise is distinct in its control of tissue-remodeling genes.To understand the transcriptional impacts of the Ex- and mTg-induced epigenomic programs, we used mRNA-seq of quadriceps to comprehensively analyze gene expression in these models compared with sedentary wild-type controls. Ex mice exhibited 779 significantly induced and 783 suppressed genes . Additionally, we interrogated Myh isoforms using antibodies to MYH4 (type IIb), MYH1 (type IIx), MYH2 (type IIa), and MYH7 (type I) . Glycolytic type IIb fibers were diminished by 14% and 20%, whereas more oxidative type IIa fibers were increased by 103% and 32% in Ex and mTg mice, respectively, compared with controls. However, type I and type IIx content was selectively increased in mTg mice by 73% and 141% compared with controls but was not substantially changed in Ex muscle. Hence, exercise or Pgc1a overexpression promote oxidative metabolism and myofiber switching, but myofiber profiles are distinct in these models.To assess the functional consequences of exercise- and PGC1α-induced transcription, we performed immunohistochemical analysis of skeletal muscle. In line with the similar oxidative transcriptomic profiles of Ex and mTg mice, succinate dehydrogenase staining was increased in both models compared with controls, although staining was considerably more ubiquitous in mTg animals . In the first, we tested the extent to which EMRs, the regions exhibiting the greatest changes in H3K27ac modification, could account for exercise-induced changes in gene expression using the Binding and Expression Target Analysis (BETA) pipeline [Fig 9B). The predominance of repressed genes corresponded to a negative regulatory potential for EMRs , consistent with the overall impact of exercise to cause hypoacetylation at these sites. Ontologies for EMR-associated up-regulated targets, such as Acyl-CoA dehydrogenase long chain (Acadl) , included genes implicated in muscle contraction, fiber organization, and fatty acid degradation . Ontologies for EMR-associated down-regulated genes, such as Myh4 ( right), included glycogen breakdown, muscle development, and carbohydrate catabolism . Consistent with our motif analysis for all EMRs , the subset of EMRs associated with altered gene expression by BETA was enriched in motifs for bZIPs and NRs . However, the majority of genes regulated by exercise lacked EMRs, indicating that dynamic changes in H3K27ac only captured a subset of transcriptionally relevant regulatory events at nearby enhancers and promoters.We next integrated our transcriptomic and epigenomic modification analyses to gain insight into the transcription factors responsible for skeletal muscle adaptation to exercise. To do so, we used two complementary approaches . To implement IMAGE, we defined active regulatory regions as sites exhibiting H3K27ac and H3K4me2 peaks or H3K27ac peaks and accessible chromatin based on ATAC-seq. Motifs within these 33,067 active regulatory regions were then analyzed for their impact on exercise-induced transcription. IMAGE analysis identified 50 transcription factors with significant predicted roles in exercise programming (S1 Table). Among these, 13 emerged as causal factors with high or medium confidence. The nuclear hormone receptors ERR and retinoid X receptor (RXR) along with JUN were top scoring, followed by forkhead box protein O4 (FOXO4), NFYB, zinc finger protein 91 (ZFP91), TEAD, signal transducer and activator of transcription 5A (STAT5A), activating transcription factor 4 (ATF4), nuclear factor kappa B subunit 2 (NFKB2), MEF2A, cytoplasmic polyadenylation element binding protein 1 (CPEB1), T-box 15 (TBX15) . Compared with IMAGE analysis in mTg mice (S2 Table), NFKB2, ZFP91, ATF4, and TBX15 were uniquely identified as causal factors in exercise. To verify motif predictions from our analyses, we compared genome-wide DNA binding sites of transgenically expressed Errg in Quad [ left), in keeping with the strong enrichment of ERR/NR binding sites predicted in our motif analysis. Similarly, transgenic ERRγ binding was detected at 46%  of exercise-regulated genes ( right). Hypergeometric tests confirmed that the ERRγ enrichment at EMRs and exercise-regulated genes is highly enriched relative to its binding at all Quad H3K27ac-marked regions  or all Quad-expressed genes , respectively. These findings attest to the role for ERRs in skeletal muscle adaptation and validate our analytical methods to reveal the epigenomic regulators of exercise.To more fully reveal regulators of exercise-induced adaptation, our second approach applied a recently developed method known as Integrated analysis of Motif Activity and Gene Expression (IMAGE) , which u in Quad  to EMRs.Muscle differentiation and adaptation have been extensively studied, but epigenome-level analyses of skeletal muscle in vivo are lacking. Using ChIP-seq of H3K4me2 and H3K27ac, we have established maps for regulatory regions and their activities in different muscle groups. These profiles pointed to MEF2, SIX1, NUR77, ERR, and NFAT as key determinants of developmental myofiber specification. Integrative regulatory region and gene expression analysis also enabled us to predict causal effectors of skeletal muscle adaptation, revealing several well-known factors, such as ERR and RXR nuclear hormone receptors, JUN, MEF2, SIX, and many less-characterized mediators of exercise-induced programming.Our findings indicate that the tissue environment plays a key role in shaping skeletal muscle enhancer networks. Muscles exhibit a substantial number of distinguishing regulatory features, including enhancers and SEs suited to their specific contractile properties and functional demands. Remarkably, muscle regulatory regions are uncorrelated with those identified in differentiated C2C12 MTs. It has long been recognized that gene regulation in vitro and in vivo are discrepant, likely because of genotypic alterations in immortalized cells and lack of developmental, mechanical, or environmental stimuli that can change the activities of transcription factors . ReminisA number of transcription factors implicated in genetic studies of muscle development and fiber-type specification were identified in our analysis, providing new insight into their epigenomic coordination within different muscle groups. MEF2 sites emerged as the most statistically enriched among skeletal muscle active regulatory regions and subsets of muscle group–specific sites, highlighting the critical role for MEF2 proteins in myogenesis and myofiber programming . SIX motPgc1a overexpression, their epigenomic signatures are highly distinctive and suggest the participation of different factors in muscle reprogramming.PGC1α-driven reprogramming of skeletal muscle enhances skeletal muscle oxidative metabolism and endurance, but the extent to which it mimics the signaling effects of exercise has been unclear. At the level of the epigenome, we found thousands of H3K27ac signal differences between these models. PMRs were associated with hyperacetylation and markedly enriched in MEF2 and ERR motifs, whereas EMRs were surprisingly hypoacetylated and contained an abundance of MEF2 and NR half sites. The basis for the dichotomy of H3K27ac signals in EMRs and PMRs, particularly in light of their similar motifs, remains an unresolved question. It is possible that MEF2 could favor the nuclear retention of HDACs in the setting of chronic training, in contrast to the dismissal of class II HDACs observed with acute exercise . AlternaPgc1a transgenesis results in its constitutive overexpression. Our interrogations of exercise-trained mice were performed within 6 hours or 72 hours of their last bout of wheel running, when Pgc1a levels were not elevated, whereas mTg mice exhibited chronic elevations in Pgc1a. Thus, timing of analysis and differing levels of PGC1α in Ex versus mTg mice may have contributed to divergence in epigenomic signals between the two models, especially because H3K27ac has a half-life of only approximately 2.3 hours [The unique epigenomic and transcriptional profiles identified in Ex and mTg mice may also be influenced by timing and intrinsic differences in our models, as well as limitations in our analysis. Exercise transiently up-regulates and activates PGC1α –51, wher.3 hours . Whereas.3 hours ,11,13,14.3 hours ,54, whic.3 hours  to two-t.3 hours  of regulMany transcriptional regulators have been linked to muscle adaptation, yet their relative contributions have been unknown. We have delineated these and identified undescribed or minimally characterized factors in exercise-directed remodeling. Enhancer activity and IMAGE-based analyses each revealed ERR, RXR, JUN, and MEF2 motifs as top scoring, attesting to the primacy of NRs and downstream effectors of MAPK and calcineurin signaling in muscle transcriptional remodeling –60. AddiPgc1a impairs exercise-induced angiogenesis, it does not impact exercise-induced fiber-type transformation [Health improvements associated with exercise are multifaceted, so understanding skeletal muscle adaptation and its molecular basis could provide insight to therapy for a variety of diseases. PGC1α and ERR-driven pathways are beneficial in the context of many skeletal muscle maladies including atrophy ,70, mitoormation ,83. Evenormation . Accordiormation  will be 2 inhalation followed by cervical dislocation.All mouse work was approved by the Northwestern University Institutional Animal Care and Use Committee (IACUC) (protocol number IS00005071). All animal care and procedures adhered to the United States Public Health Service (USPHS) regulations and applicable federal and local laws. All mice were euthanized using COMale C57BL/6J mice (7–8 weeks old) were purchased from Jackson Laboratories and maintained with free access to chow and water. For voluntary exercise studies, mice were randomly assigned to individual cages with or without free access to wheels at 8 weeks of age for 4 weeks. Ex mice were harvested 4–6 hours after the last bout of exercise. Detraining mice were harvested 72 hours after their last bout of exercise. Skeletal muscle–specific mTg mice were generously provided by Dr. Bruce Spiegelman. Male transgenic and wild-type littermates were used for all experiments.g for 10 minutes, and the pellet was resuspended in buffer containing 1% SDS, 10 mM EDTA, and 50 mM Tris, and then it was passed through 70-μm Filcons (BD Biosciences) to purify nuclei in the flowthrough. The isolated nuclei were sonicated for 10 cycles  using a Diagenode Bioruptor to shear chromatin into 200–1,000-bp fragments. Fixed, sonicated chromatin was incubated with antibody against H3K4me2 (AbCam #32356) or H3K27ac (Active Motif #39133) overnight. Antibody complexes were precipitated with anti-rabbit IgG paramagnetic beads (ThermoFisher). Chromatin was de-cross-linked, purified, and used to generate libraries using KAPA DNA Library Preparation kits (Kapa Biosystems). During library preparation, adapter-ligated ChIP DNA was size selected to obtain inserts of 200–500 bp using a PippenHT (Sage Science). Libraries were assessed by both a Bioanalyzer (Agilent) and qPCR-based quantification (Kapa Biosystems) and sequenced on an Illumina NextSeq 500 using 75-bp single-end reads. Read counts are listed in S3 Table.ChIP was performed as previously described , with mog for 10 minutes, and the isolated nuclei were cross-linked at room temperature, first with 2 mM disuccinimidyl glutarate for 20 minutes and then with 1% formaldehyde for 5 minutes. After quenching with 125 mM glycine, cross-linked nuclei were rinsed with cold PBS and then sheared in a buffer containing 1% SDS, 10 mM EDTA, and 50 mM Tris for six cycles  using a Diagenode Bioruptor to shear chromatin into 200–1,000-bp fragments. Fixed, sonicated chromatin was incubated with 7.5–10 μg of antibody against MED1 (Bethyl Labs #A300-793A) or NFATc1 (Millipore #MABS409) and 3 μg of SIX1 (Proteintech #10709-1AP), c-JUN , or normal rabbit IgG (Santa Cruz #2027) overnight. Antibody complexes were precipitated with anti-rabbit or anti-mouse IgG paramagnetic beads (ThermoFisher) for sequencing or with protein A agarose beads (Millipore) for qPCR. Chromatin was de-cross-linked, and DNA was isolated using MinElute PCR purification columns (Qiagen). Library preparation for MED1 and NFAT ChIP samples was performed as described above. ChIP qPCR assays for SIX1 and c-JUN were performed in technical duplicates. Primer sequences for ChIP qPCR are listed in For transcription factor (TF) ChIP, when performing sequencing, quadriceps from five animals or Sol from 10 animals were pooled to make one biological sample, whereas for qPCR validation, quadriceps from two animals or Sol from five animals were pooled to make one sample. Muscles were harvested, minced, and processed using a Polytron tissue homogenizer in buffer . The homogenate was then dounced (approximately 10 strokes), and serial filtering from 150 μm to 30 μm was performed. Filtrate was then spun at 600g for 10 minutes at 4°C. Nuclear pellets were subjected to transposition and library preparation [Muscles were dissected, frozen in liquid nitrogen, and pulverized with a Covaris CP02 cryoPREP. Approximately 30 mg of powdered frozen tissue was transferred to 1.5-ml tubes and resuspended in ice-cold nuclei lysis buffer containing 20 mM Tris-HCl, 50 mM EDTA, 5 mM spermidine, 0.15 mM spermine, 0.1% mercaptoethanol, and 40% glycerol (pH 7.5). Samples were filtered through Miracloth (EMD Millipore) and centrifuged at 1,100Errg transgenic muscle were reanalyzed in the same way for comparisons. Tag directories were generated using “makeTagDirectory” using the -tbp 1 option to limit the number of reads starting at the same position to 1.For ChIP-seq, raw sequence reads were aligned to the mouse reference genome (mm10) using Bowtie version 1.1.2  using “-Further analysis of ChIP-seq and ATAC-seq was performed with HOMER . Peaks fTo generate the tag density scatter plots and histograms, tags were quantified using HOMER’s “annotatePeaks.pl” command, with either “-size 1000” option or “-size 6000 -hist 10” options, for scatter plots and histograms, respectively. H3K4me2 and H3K27ac distribution plots were generated by quantifying tags using HOMER’s “annotatePeaks.pl” command with “-size 6000 -hist 25 or 50” and specifying the “-ghist” option, whereas ATAC-seq distribution plots were generated using the same command but with “-size 4000.” Morpheus  was usedHOMER's “getDifferentialPeaksReplicates.pl” command was also used to find peaks that were differentially methylated or acetylated between any two muscle groups or in quadriceps of the two different models compared with respective controls. For these analyses, peak lists combining all peaks from the comparison conditions were assembled. One condition was used as the target, and the other was used as background. The option “-balanced” was used to allow data to be quantile normalized. To characterize enriched motifs near differentially acetylated peaks, we used HOMER’s “findMotifsGenome.pl” command to scan the entire peak by using “-size given” with standard background. Gene ontologies for ChIP-seq data were generated using GREAT  by annotATAC-seq data were analyzed for transcription factor footprints using the Regulatory Genomics Toolbox application HINT  using thIntegrative ChIP and RNA-seq analysis was conducted using BETA  and IMAGMuscles were harvested and snap frozen in liquid nitrogen. Tissues were homogenized in 1 mL TriZol (Qiagen) using the Mo Bio Powerlyzer. RNA was isolated using RNeasy columns (Qiagen). RNA quality was assessed using a Bioanalyzer (Agilent) to ensure RIN scores > 7.0 prior to library construction. Sequencing libraries were constructed using Illumina TruSeq Stranded mRNA sample prep kits. Libraries were quantified using both a Bioanalyzer (Agilent) and qPCR-based quantification (Kapa Biosystems), and they were sequenced on an Illumina NextSeq 500 instrument using 75-bp single-end reads.p-value < 0.05) via the RNA-seq Alignment (v1.1.1) DESeq2 (v1.1.0) BaseSpace application (Illumina). Direct comparisons were made between control and Ex animals, as well as between control and mTg animals to generate lists of differentially expressed genes. Volcano plots were generated using GraphPad Prism 7.0 (GraphPad Software). Principal component analysis was performed using a web-based tool, ClustVis [Sequenced reads were aligned to the mm10 reference mouse genome using STAR , and difClustVis . MorpheuClustVis  was usedClustVis . EnrichmPreviously published data sets of RNA-seq were reanalyzed in the same way as our own primary expression data. For comparisons in EDL, Quad, Sol, and Dia of C57BL/6J mice, sequence read archive SRP110541 was used . Fpkm va36b4. Primer sequences are listed in S5 Table.cDNAs were synthesized from RNA using iScript cDNA synthesis kits (Bio-Rad). Quantitative real-time PCR analysis was performed with SYBR Green Master Mix (Bio-Rad) and analyzed using a Bio-Rad CFX384 Touch Real-Time PCR System. Expression was determined using the relative standard curve method and normalized to the housekeeping gene 2O, and mounted with Prolong Antifade Diamond (Invitrogen). All slides were imaged on an Olympus VS120 slide scanner.Muscle was frozen in OCT embedding compound and cut with 10-μm transverse cryo-sections taken at midbody at least 150 μm apart. For immunostaining, muscle sections were fixed with ice-cold acetone, washed with PBS, and incubated in blocking solution  for 1 hour at room temperature. Next, primary antibodies diluted in blocking solution were added and incubated overnight at 4°C. The following mouse monoclonal antibodies from Developmental Studies Hybridoma Bank were used for fiber staining: BA-F8, type I (1:10 dilution); SC-71, type 2A (1:30 dilution); and BF-F3, type 2B (1:10 dilution). The next day, slides were washed with PBS and incubated with secondary antibodies for 1 hour at room temperature, washed, and mounted with Prolong Antifade Diamond. For SDH staining, slides were thawed and covered in incubating solution  for 90 minutes at 37°C. Slides were then incubated at 23°C for 15 minutes in formal calcium , washed in twice-distilled Ht test or two-way ANOVA followed by multiple comparisons analysis with Tukey’s correction was used to compare qPCR gene expression between two or multiple groups, respectively. Spearman correlation analysis was performed on normalized ChIP-seq tag counts for all pairwise comparison scatterplots. One-way ANOVA with Tukey’s correction was performed on normalized ChIP-seq tag counts to compare quadriceps versus Sol and Ex or mTg with control. All sample sizes and p-values are listed in the figure legends.We used Microsoft Excel, GraphPad Prism 7.0 (GraphPad Software), and Sigmaplot 11.0 to perform the statistical analyses. Student’s unpaired All RNA-seq, ChIP-seq, and ATAC-seq data are deposited in GEO SuperSeries accession #GSE123879.S1 Figs) was calculated for each scatterplot. (C) Genomic distributions of H3K4me2 (left) and H3K27ac (right) peaks across the four muscle groups in promoter, intragenic, and intergenic regions.  Scatterplots of normalized H3K4me2 (D) and H3K27ac (E) tag counts at genomic regions marked by H3K4me2 and H3K27ac tags in pairwise comparisons of four different muscle groups. Correlation coefficient (rs) was calculated for each scatterplot (n = 2/group). (F) Heatmap of motifs enriched in H3K27ac peaks for EDL, Quad, Sol, and Dia, with p-values represented in color. Numerical values for all panels are available in  Scatterplots of normalized H3K4me2 (A) and H3K27ac (B) tag counts for individual ChIP-seq replicates in the four muscle groups. Correlation coefficient (r(TIF)Click here for additional data file.S2 Fign = 4/group. (B) H3K27ac tags within 50 kb around the TSS for genes differentially expressed (log2 fold change > 1.5) in Quad > Sol (left) or Sol > Quad (right); n = 2/group, ***p < 0.001. (C) ATAC-seq tags within 50 kb around the TSS for genes differentially expressed (log2 fold change > 1.5) in Quad > Sol (left) or Sol > Quad (right); n = 2/group, **p < 0.01, ***p < 0.001. Numerical values for all panels are available in (A) Similarity matrix for Fpkm values from RNA-seq data for EDL, Quad, Dia, and Sol. Pearson correlation coefficient (r) is represented in color; (TIF)Click here for additional data file.S3 Fign = 5/group). Data are represented as means ± SEM. **p < 0.01, ***p < 0.001. (B) Histograms of NFAT tags within 1.5 kb of Sol-specific H3K27ac peak centers in Quad and Sol (left); quantification of NFAT tag densities at Sol-specific H3K27ac peaks in Quad and Sol; ***p < 0.001 (right). (C) Representative UCSC browser tracks of H3K27ac (top) and NFAT (bottom) ChIP-seq in Quad (yellow) and Sol (red) along a Sol-specific H3K27ac region with predicted NFAT motif (green) showing NFAT binding specifically in Sol. (D) ChIP qPCR validation of SIX1 binding in Quad (left) and Sol (right). Enrichment is plotted as percent of input using technical duplicate control IgG and SIX1 ChIPs. Numerical values for all panels are available in (A) qPCR expression analysis of transcription factors predicted from motif analyses in Quad and Sol ((TIF)Click here for additional data file.S4 Fign = 13). (B) Scatterplots of normalized H3K4me2 tag counts at genomic regions marked by H3K4me2 in pairwise comparisons of Sed control versus Ex quadriceps (left) and Wt versus mTg quadriceps (right). Correlation coefficient (rs) was calculated for each scatterplot (n = 2/group). (C) Comparison matrix listing the numbers of differential H3K4me2 peaks in Ex or mTg Quads compared with controls. (D) Histograms of H3K27ac tags within 6 kb of EMR peak centers (top) and quantification of H3K27ac tag densities at EMR peaks (bottom) in control mice and detrained mice that were removed from running wheels for 72 hours following their last bout of exercise; n = 2/group; ***p < 0.001. (E) Histograms showing distribution of H3K27ac tags within 6 kb of PMR peak centers in mTg and Ex mice and their respective controls; n = 2/group. (F) Quantification of H3K4me2 (left) and H3K27ac (right) tag densities at PMRs in Wt, mTg, Sed, and Ex Quads. n = 2/group, ***p < 0.001. (G) Relative gene expression of immune cell, vascular endothelial, satellite cell, and myogenic markers in quadriceps from control, Ex, and mTg mice (n = 5/group). Data are represented as means ± SEM. **p < 0.01, ***p < 0.001. (H) Top ontologies for genes annotated to hyperacetylated (top) or hypoacetylated (bottom) PMRs in mTg Quads. (I) Motifs enriched in H3K27ac peaks that are specifically hyperacetylated (left) and hypoacetylated (right) in mTg Quads. Numerical values for all panels are available in Pgc1a transgenic; PGC1α, peroxisome proliferator–activated receptor gamma, coactivator-1 alpha; PMR, PGC1α-modified region; Quad, quadriceps femoris; Sed, sedentary; Wt, wild-type.(A) Wheel counts of mice during 4 weeks of voluntary exercise ((TIF)Click here for additional data file.S5 FigPgc1a transgenic.(A) Activity scores for footprints in control versus Ex. Factors producing a significant activity score are shown in red, and motifs for the top 10 are shown below. (B) Activity scores for footprints in control versus mTg. Factors producing a significant activity score are shown in red, and motifs for the top 10 are shown below. Numerical values for all panels are available in (TIF)Click here for additional data file.S6 Fign = 2/group). (B) Representative immunofluorescence staining images of four Myh isoforms in gastrocnemius from control, Ex, and mTg mice. Myh7 (type I) is blue, Myh2 (type IIa) is green, Myh1 (type IIx) is black, and Myh4 (type IIb) is red. Vertical bars next to the images show percentages of the different fiber types (n = 2/group). Ex, exercised; mTg, muscle-specific Pgc1a transgenic; Myh, myosin heavy chain; Pgc1a, peroxisome proliferator–activated receptor gamma, coactivator 1 alpha; SDH, succinate dehydrogenase.(A) Representative images of SDH staining in gastrocnemius of control, Ex, and mTg mice ((TIF)Click here for additional data file.S1 Tablep-value. IMAGE, integrated analysis of motif activity and gene expression.Rows arranged in ascending order of (PDF)Click here for additional data file.S2 Tablep-value. IMAGE, integrated analysis of motif activity and gene expression.Rows arranged in ascending order of (PDF)Click here for additional data file.S3 TableChIP-seq, chromatin immunoprecipitation sequencing.(PDF)Click here for additional data file.S4 TableChIP, chromatin immunoprecipitation; qPCR, quantitative PCR.(PDF)Click here for additional data file.S5 TableqPCR, quantitative PCR.(PDF)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S2 DataH3K4me2, histone 3 lysine 4 dimethylation.(ZIP)Click here for additional data file.S3 DataH3K4me2, histone 3 lysine 4 dimethylation; H3K27ac, histone 3 lysine 27 acetylation.(ZIP)Click here for additional data file.S4 DataH3K27ac, histone 3 lysine 27 acetylation.(ZIP)Click here for additional data file.S5 DataEDL, extensor digitorum longus.(ZIP)Click here for additional data file.S6 DataQuad, quadriceps femoris.(ZIP)Click here for additional data file.S7 DataSol, soleus.(ZIP)Click here for additional data file.S8 DataDia, diaphragm.(ZIP)Click here for additional data file.S9 Data(XLSX)Click here for additional data file.S10 Data(XLSX)Click here for additional data file.S11 Data(XLSX)Click here for additional data file.S12 Data(XLSX)Click here for additional data file.