Histone KMTs of H3K36me maintains euchromatin by antagonizing H3K27me3 spreading and influencing 3D genome organization at TADs boundaries, thus participating in transcriptional program maintenance. Cell type-specific barcoding of genomes requires the establishment of hundreds of heterochromatin domains where heterochromatin-associated repressive complexes hinder chromatin accessibility thereby silencing genes. At heterochromatin–euchromatin borders, regulation of accessibility not only depends on the delimitation of heterochromatin but may also involve interplays with nearby genes and their transcriptional activity, or alternatively on histone modifiers, chromatin barrier insulators, and more global demarcation of chromosomes into 3D compartmentalized domains and topological-associating domain (TADs). Here, we show that depletion of H3K36 di- or tri-methyl histone methyltransferases dMes-4/NSD or Hypb/dSet2 induces reproducible increasing levels of H3K27me3 at heterochromatin borders including in nearby promoters, thereby repressing hundreds of genes. Furthermore, dMes-4/NSD influences genes demarcated by insulators and TAD borders, within chromatin hubs, unlike transcription-coupled action of Hypb/dSet2 that protects genes independently of TADs. Insulator mutants recapitulate the increase of H3K27me3 upon dMes-4/NSD depletion unlike Hypb/dSet2. Hi-C data demonstrate how dMes-4/NSD blocks propagation of long-range interactions onto active regions. Our data highlight distinct mechanisms protecting genes from H3K27me3 silencing, highlighting a direct influence of H3K36me on repressive TADs. Eukaryotic genomes are globally partitioned into two major active and inactive A and B compartments, or euchromatin and heterochromatin, respectively, which largely contribute to cell-type gene expression programming. High-resolution genome mapping of the major histones post-translational modifications and of their chromatin-associated proteins writing, reading, or erasing these histone marks  revealedCell type-specific silencing of gene expression requires notably polycomb repressive complexes (PRC1 and 2) that contribute to mediate repression by di/trimethylation of lysine 27 on histone H3 (H3K27me2/3) and binding of CBX and EED subunits to these marks . H3K27meCaenorhabditis elegans, the histone methyltransferase (HMT) MES-4 ensures both di- and tri-methylation of H3K36 (H3K36-me1/me2/me3) that may antagonize H3K27me3 (Drosophila with dMes-4 (NSD1/2/3 homolog) and HypB/dSet2 (SETD2 homolog), which may be responsible of transcription-coupled H3K36-me2 and -me3, respectively. It remains to be shown whether it is the di- or tri- methylated state of H3K36 that can block H3K27me3 self-propagation  occurs co-transcriptionally . AlthougH3K27me3  and MET-H3K27me3 . Other epagation . dMes-4/pagation . Furtherpagation . This trpagation . Yet it Here, we performed a genome-wide comparative analysis of the H3K27me3 histone marks in control versus dMes-4/NSD- or Hypb/dSet2-depleted cells. The depletion of Hypb/dSet2 leads to some H3K27me3 spreading, notably over genes flanking a H3K27me3 repressive domain border that do not coincide with a topological-associating domain (TAD) border. In contrast, dMes-4/NSD protects genes flanking a TAD border and that can assemble into 3D chromatin hubs. Accordingly, our novel Hi-C data show that depletion of dMes-4/NSD extend long-range interactions out of the inactive TADs, to the same regions where H3K27me3 spreading is also detected, unlike for Hypb/dSet2. Our results highlight how dMes-4/NSD and Hypb/dSet2 may help sustaining the active state of genes depending on the positioning of the heterochromatin–euchromatin borders at the border of a TAD, or not.We sought to test which of H3K36me2- or H3K36me3-methylated states may antagonize the spreading of H3K27me3. Both H3K36-me2 and -me3 mark euchromatin domains flanking repressive heterochromatin TADs . The aveDrosophila melanogaster, namely, dMes-4/NSD (NSD homolog) and HypB/dSet2 (SETD2 homolog), are responsible for H3K36-me2 and -me3 deposition, respectively. Accordingly, depletion of dMes-4/NSD or of Hypb/dSet2 , and more rarely in intergenic regions. Accordingly, heatmaps showed that upon both depletions, the net increase in H3K27me3 levels most often mapped over gene bodies  . Taken altogether, our data thus indicated that compromising H3K36me2 or H3K36me3 levels by either dMes-4/NSD or Hypb/dSet2 depletion could both impair the blocking of H3K27me3 spreading, as notably detected over gene bodies.Genomic bins harboring increased H3K27me3 levels upon depletion of either HMT were preferentially encountered in gene bodies compared with random distribution . Thus, although the variations in H3K27me3 may not reflect a change in the positioning of core H3K27me3 domains, depletion of dMes-4/NSD and Hypb/dSet2 could still expose genes to silencing through spreading of H3K27me3 marks. Such phenomenon is mostly encountered within gene bodies and not in enhancers localized outside of gene bodies  among the clusters of genes down-regulated upon either Hypb/dSet2  or dMes-4/NSD (clusters D2–D3) as identified in our differential expression analysis .List of Gene Ontologies (GOs) found to be enriched . This contrasted with genes with higher levels of H3K27me3 uniquely detected upon depletion of Hypb/dSet2 . Overall, sites with both increases of H3K27me3 and down-regulation of genes upon depletion of either dMes-4/NSD or Hypb/dSet2 showed a distinct distribution over the H3K27me3 borders , prompted us to re-evaluate their relative influence on H3K27me3 levels. Although their depletion led to a significant overlap . Accordingly, probing long-range interactions (LRIs) by aggregation of Hi-C data, as previously developed .H3K27me3 domains represent the mostly marked TADs in Drosophila , and aboWhether histone modifiers and the resulting modifications represent a cause or a consequence of topology has been a recurrent question . We sougOur above analyses highlight a role of dMes-4/NSD in maintaining genes flanked by insulators and TAD borders away from nearby repressive environment. Of note, mutants of Drosophila insulator proteins that specifically impaired 3D looping similarly led to H3K27me3 spreading over heterochromatin borders, depending on levels of insulator-mediated LRIs . We thusTaken altogether, our data thus unravel that although dMes-4/NSD and Hypb/dSet2 are involved in highly related H3K36 methylated states, these KMTs could preferentially antagonize H3K27me3 silencing depending on distinct contexts, thereby reinforcing TAD-based demarcation or transcription-coupled H3K36me epigenetically .Our data highlight two possible mechanisms for how KMTs of H3K36 may protect genes from H3K27me3 repression. In the first model, the demarcation from heterochromatin may involve H3K36me3 in antagonizing H3K27me3 spreading over genes localized within repressive heterochromatin domains. This occurs through transcription-coupled H3K36 trimethylation by Hypb/dSet2, hence requiring genes to block H3K27me3, in agreement with the interaction of Hypb/dSet2 with Pol II to mediate H3K36me3 along transcription. Such mechanism may protect moderately expressed genes particularly prone to H3K27me3 spreading, that is, as for genes within a repressive TAD. The second mechanism further involves chromatin domains in 3D. In this instance, impairing H3K36me2 appears to be sufficient to spread repressive TADs to the nearby genes, across topological borders. The spreading of H3K27me3 may then be accompanied by the extension of the topological domain. This may account, at least in part, for how epigenetic factors may contribute to topological demarcation and the folding of chromatin into TADs in Drosophila  and of eC. elegans to humans by directly impeding on enzymatic activity of PRC2 . For analysis of Pol II pausing, cells were treated with either flavopiridol  at 1 μM during 30 min, or DRB  at 50 μM during 30 min, or DMSO control .Exponentially growing S2 cells were depleted by dsRNAs against dMes-4/NSD or Hypb/Set2 compared with mock-depletions (dsRNAs against luciferase) as previously described . Preparag at 4°C). DNA pellets were washed twice (70% ethanol), dried, and resuspended in H2O. Chromatin immunoprecipitations were quantified by qPCR  or high-throughput sequencing (ChIP-seq). Data are available at GSE146993. Sources of commercially available antibodies were as follows: H3K36me1 , H3K36me2 , H3K36me3 , H3K27me3 , Pol II total .10 millions of Schneider S2 cells were cross-linked with 0.8% formaldehyde (FA)  for 10 min. Crosslinking was stopped with 150 mM glycine. After two washes with PBS1X NaBu 10 mM, cells were permeabilized for 20 min with 500 μl PBS1X 0.2% Triton X-100 and 10 mM NaBu. After centrifugation, pellets were washed with lysis buffer  and resuspended in LB + 1% SDS and 0.5% N-lauroylsarcosyl for 30 min at 4°C. Samples were sonicated for 5 × 30 s on–off cycles at 4°C . Protein A or protein G beads were coated with 0.1 mg/ml BSA NEB for 2 h at 4°C. 5 μg of antibodies were mixed with 20 μl beads and incubated overnight at 4°C (in LB 0.1% SDS). Meanwhile, chromatin samples were pre-cleared overnight at 4°C in LB with 10 μl of beads. After four washes with LB + 0.1% SDS, antibody-coupled beads were incubated 4 h with pre-cleared chromatin. After four washes with LB + 0.1% SDS, two washes with TE 1X, elution was carried out at 70°C for 20 min in 10 mM EDTA, 1% SDS, and 50 mM of Tris–HCl (pH 8.0). Crosslinking was reversed overnight at 65°C. IP samples and inputs were incubated at 37°C for 30 min with RNAse A, and then at 55°C for 2 h with 250 μl of TE + 140 mg/ml of glycogen and 400 μg/ml of proteinase K. DNA was extracted by phenol–chloroform followed by incubation with 1.3 ml of 100% ethanol for 30 min at −80°C and centrifugation  or for quantifying expression by RT-qPCR . The names of the closest nearby gene associated with each primer are provided both in the CG and FBgn formats.Table S2. https://github.com/CuvierLab/depierre_perrois_H3K27K36_analysis_scripts.Scripts related to data processing, data integration, visualization, and statistical analysis are available on our GitHub: D. melanogaster reference genome r6.13/dm6 (http://ftp.flybase.net/genomes/Drosophila_melanogaster/dmel_r6.13_FB2016_05/) using Burrows-Wheeler Aligner (BWA 0.7.15 [https://bioconductor.org/packages/release/data/annotation/html/TxDb.Dmelanogaster.UCSC.dm6.ensGene.html).Adapter sequences were trimmed (cutadapt 1.8.3 ) and cheA 0.7.15 ). UniqueA 0.7.15 ) with a Preprint) with a bin size configuration of 200 bp that were filtered according to their significant enrichment in H3K27me3 (compared with input) with an FDR of 1 × 10−4. Detected H3K27me3 domains were then merged when separated by non-mappable regions to avoid considering non-mappable regions as H3K27me3 domain borders (see GitHub). The same minimal size of >1,500 bp was chosen for H3K27me3 heterochromatin domains or the intervening euchromatic domain. Differential analysis of H3K27me3 variation  was computed as follows:H3K27me3 domains were detected using normR R packages Preprinton e.g.,  was perfD. melanogaster reference genome r6.13/dm6 (http://ftp.flybase.net/genomes/Drosophila_melanogaster/dmel_r6.13_FB2016_05/) using STAR Aligner (STAR 2.5.2b [After trimming adapters (cutadapt 1.8.3 ) and a qR 2.5.2b ). ProcesR 2.5.2b ) with a P-value < 0.05. Clustering of co-regulated genes  were generated using the genome-wide Hi-C kit from Arima Genomics S2 cells treated with siMes-4/NSD and siHypB/dSet2 compared with control siLuc (control luciferase gene that does not exist in Drosophila). Hi-C data were processed using a standard pipeline using Juicer (GSE146994) were visualized using 2D plots  either as observed (upper row) or observed/expected (lower row), at 1 kb resolution, using the sqrt format coverage (sqrt). The same procedure was applied to our data or to external data . Dendrograms . For Fidrograms ; EV3 werGSE146994). External data were downloaded from NCBI GEO data with following accession numbers: H3K9me3 from GSE99027 (GSE113470 (GSE85191 (GSE130211 (GSM2776906 (GSM2776903 (GSM3106537 (GSE97965 (All RNA-seq, ChIP-seq, and Hi-C data pertaining to this study were deposited to GEO of NCBI (GSE99027 ; H3 totaSE113470 ; H3K27acGSE85191 ; H3K27meSE130211 ; externaM2776906 ; H3K36meM2776903 ; H3K36meM3106537 . Hi-C daGSE97965 .


Alternative splicing is a widespread regulatory phenomenon that enables a single gene to produce multiple transcripts. Among the different types of alternative splicing, intron retention is one of the least explored despite its high prevalence in both plants and animals. The recent discovery that the majority of splicing is co-transcriptional has led to the finding that chromatin state affects alternative splicing. Therefore, it is plausible that transcription factors can regulate splicing outcomes.We provide evidence for the hypothesis that transcription factors are involved in the regulation of intron retention by studying regions of open chromatin in retained and excised introns. Using deep learning models designed to distinguish between regions of open chromatin in retained introns and non-retained introns, we identified motifs enriched in IR events with significant hits to known human transcription factors. Our model predicts that the majority of transcription factors that affect intron retention come from the zinc finger family. We demonstrate the validity of these predictions using ChIP-seq data for multiple zinc finger transcription factors and find strong over-representation for their peaks in intron retention events.This work opens up opportunities for further studies that elucidate the mechanisms by which transcription factors affect intron retention and other forms of splicing.https://github.com/fahadahaf/chromirSource code available at The online version contains supplementary material available at 10.1186/s13059-023-02885-1. Alternative splicing is a widespread regulated phenomenon that enables a single gene to encode structurally and functionally different transcripts , 2. The enomenon , 5, and enomenon . Many dienomenon , 9. For enomenon .In recent years, efforts have been made to understand the regulation of IR and the factors that contribute to it. Braunschweig et al.  recentlyDeep neural networks have become the tool of choice for exploring complex biological phenomena such as gene expression and chromatin state –28. A reIn this study, we demonstrate that deep learning models can distinguish with good accuracy regions of open chromatin associated with IR from other intronic regions of open chromatin. By analyzing the motifs learned by the network, we find that specific families of TFs are associated with IR events, mostly members of the zinc finger family of TFs; results of ChIP-seq experiments for multiple zinc finger TFs in the K562 cell line, one of three tier 1 ENCODE cell lines, support our findings for this association. Analysis of knockdown experiments of some of these TFs suggest they function as splicing enhancers by binding the flanking exons of IR events. Our work provides convincing evidence for a novel role of TFs in the regulation of IR, proposing a promising direction for further research.In order to discover the sequence elements that regulate IR via its coupling with chromatin state, we trained and evaluated deep learning models to distinguish DHSs associated with IR events from non-IR DHSs in human and assessed and compared their performance. As IR DHSs, we used regions in which a DHS overlapping IR event was detected in at least one DNase I-seq experiment in a compendium of 164 samples; IR events were extracted from the Ensembl gene models as described in the “Our results were generated using a one-hot encoding of the sequence of DHS regions. We note that word2vec embeddings provided a small improvement in accuracy, as shown in Additional file q-value p-value of 0.01 or better for the three different architectures , we found that 21 out of the 25 motif hits discovered by the purely convolutional architecture were common across the three architectures.The filters of convolutional networks can be readily interpreted as motifs. To do so, we implemented the strategy described elsewhere , 29 (seementclass2pt{minimMost of the IR motifs had significant hits in the C2H2 zinc finger family of TFs (C2H2 ZF). Non-IR motifs on the other hand, were predominantly matched to the Homeodomain and Sox families of TFs see Fig. b. Zinc fp-value threshold used for searching for TF hits, we found three significant hits in the IR motifs, and two significant hits in non-IR motifs. This is compared with 22 TF hits in IR motifs and 23 TF hits in non-IR motifs. Details of those matches are found in the github repository of this project. This suggests that TFs play a major role in IR in comparison to RNA-binding proteins, perhaps as a result of our focus on regions of open chromatin.We also searched for motif matches to RNA-binding proteins in the CISBP-RNA database  using thTo validate our findings using experimental data, we downloaded K562 ENCODE ChIP-seq datasets for all the zinc finger TFs identified by our model, resulting in six datasets. Using these datasets, we tested TF binding enrichment in IR vs. non-IR events, following a strategy similar to our previous work : for eacp-value of 0.05 and above . These results suggest that regulation of IR is orchestrated by complex interactions among TFs, predominantly from the C2H2 ZF family.It is well known that TFs often function in tandem with each other to regulate their targets. To extract such regulatory interactions, we have recently developed a method called SATORI to interpret deep architectures that use  filters . SATORI  filters  databasedatabase : 17 of tIn our motif analysis, we found that the C2H2 zinc finger family of TFs has a strong association with IR events: Over skipping , and sugTo validate our predictions on the association of these TFs with IR, we used ChIP-seq data for multiple zinc finger TFs: MAZ, EGR1, SP1, ZBTB7A, SP2, and ZNF263. We observed much higher occupancy of these TFs in IR events in the K562 human cell line, validating the model’s predictions. Robson et al.  have repThere are multiple potential mechanisms by which TFs can affect co-transcriptional splicing. First, TFs are known to be critical in establishing chromatin state, which in turn can regulate alternative splicing by a purely kinetic model of the coupling between transcription and splicing whereby higher speeds of transcription in regions of accessible chromatin give less time for the spliceosomal machinery to recognize and splice those introns co-transcriptionally , 54, 55.adaptor system model whereby DNA-binding proteins recognize a histone modification and recruit a splicing regulator that affects the splicing outcome . Methylsee also , and itssee also , 60. HisIn this work, we focused on the local coupling of accessible chromatin and IR. We expect that non-local interactions through chromatin loop anchors like those that allow enhancers to affect promoter activity  can affeUsing deep learning to model intragenic DHSs allowed us to explore the regulatory elements that are predictive of IR in an unbiased fashion and identify TFs as key contributors to the regulation of IR. Further experimental work is required in order to validate the role of TFs in IR regulation. This will be supported by extensions of the model that allow tissue-specific prediction of the IR state of regions of open chromatin, and create the chromatin-mediated IR code. Furthermore, the modularity of deep learning will allow the extension of the model to incorporate other sources of data indicative of chromatin state such as histone modifications. Much in the same way chromatin loop anchors allow enhancers to affect the activity of promoter regions and affect gene expression , there iWe used DNase I-seq data from 125 human immortalized cell-lines and tissues from the ENCODE database  and 39 cNext, we extracted IR events from the Ensembl GRCh37 (hg19) reference annotations, utilizing code from SpliceGrapher  and iDifN is the length of the sequence. Each position in the sequence is represented by the columns of the matrix with a non-zero value at a position corresponding to one of the four DNA nucleotides. To represent a sequence using embedding, we first decomposed it into overlapping k-mers of length k and then used a word2vec model [k-mer into an m-dimensional vector space. This gave us an embedding matrix of dimensions k-mers by producing similar embedding vectors for k-mers that tend to co-occur.We used two methods to transform the sequences into input for our neural networks: one-hot encoding and sequence embedding. For one-hot encoding, a sequence is represented as a ec model  to map ei is the current output index, and j is the index of the filter. A is the length of the filter (window size) and B is the number of input channels: 4 for DNA one-hot encoding, d in case of word2vec embeddings, and number of previous layer filters in case of higher convolutional layers. The output of a convolutional layer is produced by applying a non-linear activation function to the result of the convolution operation. We use the rectified linear unit (ReLU) which is given by:In this work, we investigated several network architectures. The primary network element, a one-dimensional convolutional layer, scans a set of filters against the matrix representing the input sequence. Formally, we can express the convolution operation as:Next, the size of the output is reduced by max-pooling where the maximum value in a window of a pre-determined size is selected. This reduces the input size for the next layer and also leads to invariance to small shifts in the input sequence.We also incorporated a multi-head self-attention layer as the basis for an alternative deep learning model. Attention is a powerful feature that is able to model dependencies within an input sequence regardless of their distances . By doinFirst, the data was split into training, validation, and test sets with orted in  and finementclass2pt{minimAs a baseline we used the large-scale gapped kmer SVM (gkm-SVM), called the LS-GKM . This veTo interpret the deep learning models, we extracted sequence motifs using the weights (filters) of the first convolutional layer, similar to the methodology described by Kelley et al. . We seleWe downloaded ChIP peaks of all the TFs that were detected as enriched in IR events from the ENCODE database . Next, wWe downloaded RNA-seq data for knockdown of the following TFs in K562 from the ENCODE database: MAZ, SP1, SP2, E2F4 . In addition, we used wild-type K562 (accession number GEO:GSE33480). We computed differential IR events in the knockdown samples with respect to baseline K562 using iDiffIR . AnalysiTo discover regulatory interactions between TFs we used SATORI , which tAdditional file 1. Supplementary Material. The Supplement includes additional tables and figures.Additional file 2. Review History.


However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtains comparable results of chromatin loops across datasets generated from diverse imaging technologies. SnapFISH is freely available at  Multiplexed DNA FISH technologies are powerful tools to reveal chromatin spatial organisation. Here, the authors developed SnapFISH, a computational pipeline to identify chromatin loops from multiplexed DNA FISH data. Disruption of chromatin organization can lead to gene dysregulation, and has been associated with a variety of human developmental disorders, neuropsychiatric diseases, and cancers2. Different from proximity-ligation assays4 that infer the 3D genome through indirect measurement of DNA sequence contacts, chromatin tracing, as an emerging microscopy-based technology, can visualize bright spots corresponding to individual targeted genomic segments arrayed along chromatin fibers, and map their physical location in three-dimensional space. This rich imaging data permits the direct measurement of Euclidean distances between targeted genomic segments of interest—such as promoters and distal cis-regulatory elements - allowing an intimate look into the organization of chromosomes5. During the last decade, a number of chromatin tracing technologies have emerged, including multiplexed DNA fluorescence in situ hybridization (FISH)7, DNA-MERFISH8, DNA seqFISH+10, ORCA11, MINA12, Hi-M13, OligoFISSEQ14 and IGS15 (more details can be found in recent review articles17). These techniques can resolve the spatial location of discrete targeted genomic segments with tens of nanometer precision in single cells. They have been used to image the entire mammalian genome at megabase (Mb) resolution10, one full chromosome at 50 kilobase (Kb) resolution8, and a few selected regions at 2.5 Kb ~ 30 Kb resolution19, promising to uncover novel insights into chromatin folding and its role in gene regulation5.How chromatin folds inside the nucleus is a fundamental question in the study of genome structure and function20 as “dots” at the corners of topologically associating domains, and recently identified from single cell Hi-C data22 and imaging data18, chromatin loops are defined as pairs of genomic loci with closer spatial proximity compared to other pairs of loci in the local neighborhood region20. Chromatin loops between enhancers and promoters have been used to infer target genes for distal enhancers23. Chromatin loops between CTCF binding sites are associated with the formation of topological associating domains24, which are megabase sized chromatin domains constraining enhancer-promoter interactions. Extensive studies have demonstrated that chromatin loops play an essential role in maintaining the 3D structure of the genome and facilitating gene regulation28.Chromatin loops are a key structural feature of chromatin spatial organization, and may serve as the structural basis of gene regulation. Originally discovered from bulk Hi-C datacount-based statistical framework to model chromatin contact frequency29. As a result, these tools are inherently not directly applicable to imaging data, which allow the continuous measurement of Euclidean distances between targeted genomic segments of interest. To the best of our knowledge, no method is available to identify chromatin loops from such imaging data. In the wake of the rapid development of chromatin tracing technologies, tailored computational methods to reliably identify chromatin loops from imaging data have become more critical. Importantly, such loop analysis methods may advance our understanding of the relationships between genome structure and gene regulation.The functional importance of chromatin loops makes it important to develop loop callers tailored to different input experimental datasets , a computational pipeline to identify chromatin loops from multiplexed DNA FISH data. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH can accommodate datasets generated from diverse imaging technologies.21 pipeline for single cell Hi-C data, SnapFISH also treats each imaged cell as an independent unit, to boost the statistical power of identifying chromatin loops. Specifically, SnapFISH takes multiplexed DNA FISH single bright spot localization data as input, and outputs the predicted chromosomal location of chromatin loops. Briefly, SnapFISH first collects the 3D localization coordinates of each genomic segment targeted by FISH (hereafter referred to as targeted segment) in each cell . Next, for all pairs of targeted segments found within a 1D genomic distance range of 100 Kb ~ 1 Mb, SnapFISH compares the pairwise Euclidean distances between the pair of interest and its local neighborhood region , and FDR is less than 10% , suggesting that SnapFISH can achieve higher sensitivity for loops with higher strength.In order to optimize the SnapFISH algorithm, we re-analyzed a publicly available DNA seqFISH+ dataset from mouse embryonic stem cells (mESCs)32. Taken together, our results show that when applying to mESC DNA seqFISH+ data, SnapFISH can accurately and reliably identify loops that were previously identified from mESC bulk Hi-C data.As one illustrative example in chromosome 2, Fig. Sox2 locus18 . The 205 Kb chromosomal target region  imaged in the experiments spans both the promoter of the Sox2 gene and its super-enhancer, which is located ~100 Kb downstream. Previous studies have identified a chromatin loop between the Sox2 promoter and its super-enhancer via 5C33, and validated the functional importance of such loop via the CRISPR experiment, which showed that deletion of the super-enhancer reduces >90% of the Sox2 expression34. The mESCs used in the original study18 have two haplotypes: the CAST allele and the 129 allele. Distinct from the abovementioned mESC DNA seqFISH+ data where one cannot differentiate between the paternal and maternal alleles, the CAST allele contains a 7.5Kb insertion containing 4 CTCF-binding sites (hereafter referred to as 4CBS) between the Sox2 promoter and its super-enhancer, while the 129 allele does not contain the insertion. The multiplexed DNA FISH experiments involved 41 probe sets, each corresponding to individual 5 Kb genomic target segments tiling the 205 Kb region of interest. In addition, there was one extra probe for the 7.5 Kb insertion on the CAST allele, which permits the differential identification of the CAST allele and the 129 allele in the same nucleus. A previous study18 showed that the CAST allele-specific 7.5 Kb 4CBS insertion resulted in weaker chromatin looping strength between the Sox2 promoter and its super-enhancer.Encouraged by the results from 25 Kb resolution mESC DNA seqFISH+ data, we then applied SnapFISH to the finer resolution (5 Kb) multiplexed DNA FISH data. Specifically, a multiplexed DNA FISH dataset has previously been generated from mESCs to investigate the chromatin conformation at the 18 in an allele-specific manner  from a total of 1416 cells  using SnapFISH. The average targeted segment detection efficiency is 71.9% and 69.3% for the CAST allele and the 129 allele, respectively. We first computed the average Euclidean distances . Specifically, Mateo et al. imaged the 170 Kb region around the Sox2 gene  in mESCs, which consists of 34 5 Kb targeted segments. Across all 6007 imaged alleles, the average targeted segment detection efficiency is 56.9%. Consistent with the results in multiplexed DNA FISH data, SnapFISH identified the Sox2 enhancer-promoter loop , with an average targeted segment detection efficiency of 40.9%. Due to the relatively low targeted segment detection efficiency, we only applied SnapFISH to the excitatory neurons10 consisting of 1,895 cells , and identified 87 loops , including active promoter mark H3K4me3, two active enhancer marks H3K27ac and H3K4me1, and the open chromatin region mark ATAC. Figure Myc and the transcription end site of gene Pvt1. Both loop anchors overlap H3K27ac peaks and ATAC-seq peaks. We obtained similar results when applying SnapFISH to three additional mouse brain cell types  and FDR < 10% Fig. .We group nearby loop candidates within a pre-specified gap into clusters, where the gap is twice the size of the bin resolution. In other words, we define the gap to be 10 Kb for 5 Kb resolution multiplexed DNA FISH data and 5 Kb resolution OCRA data, and 50 Kb for 25 Kb resolution DNA seqFISH+ data. Among each cluster, we select the pair of targeted segments with the minimal FDR as the summit. The final loop list consists of cluster summits with population-level contact frequency >=1/3, and singletons with population-level contact frequency >=1/2. Detailed justification of threshold values can be found in Supplementary Information Section Sox2 promoter and super-enhancer, respectively. We further defined a SnapFISH-identified 5 Kb bin resolution loop as “overlapped” with the Sox2 enhancer-promoter, if and only if the SnapFISH loop anchors are within 10 Kb of Sox2 promoter-super-enhancer loop anchors.We defined chr3:34,645,000–34,655,000 and chr3:34,755,000–34,765,000 as the two 10 Kb bins containing In this study, we re-analyzed the publicly available datasets (see details in the “Data Availability” section below). No statistical method was used to predetermine sample size. No data were excluded from the analyses. The experiments were not randomized. The investigators were not blinded to allocating during experiments and outcome assessment. In addition, we evaluated the reproducibility of SnapFISH among biological replicates (see details in Supplementary Information Section Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Dataset 1Supplementary Dataset 2Reporting SummarySource Data


Runt-related transcription factors (RUNX) play critical roles in skeletal development, metabolism, and diseases. In mammals, three RUNX members, namely RUNX1, RUNX2, and RUNX3, play distinct and redundant roles, although RUNX2 is a dominant factor in skeletal development and several skeletal diseases. This review is to provide an overview of the current understanding of RUNX-mediated transcriptional regulation in different skeletal cell types.Advances in chromatin immunoprecipitation and next-generation sequencing (ChIP-seq) have revealed genome-wide RUNX-mediated gene regulatory mechanisms, including their association with cis-regulatory elements and putative target genes. Further studies with genome-wide analysis and biochemical assays have shed light on RUNX-mediated pioneering action and involvements of RUNX2 in lipid–lipid phase separation.Emerging multi-layered mechanisms of RUNX-mediated gene regulations help us better understanding of skeletal development and diseases, which also provides clues to think how genome-wide studies can help develop therapeutic strategies for skeletal diseases. Runx2 is essential for osteoblast specification and chondrocyte hypertrophy. During osteogenesis, skeletal progenitors initially commit to forming RUNX2-positive osteoblast precursors, which then differentiate into RUNX2- and SP7-double-positive osteoblast precursors [Sp7 is genetically downstream of Runx2 [Runx2-deficient mice, osteoblast differentiation was arrested and no Sp7 was detected [Runx2 is weakly expressed in proliferating columnar chondrocytes but is markedly upregulated as chondrocytes exit the cell cycle and become pre-hypertrophic and subsequently hypertrophic chondrocytes. The ectopic expression of Runx2 in columnar chondrocytes accelerates chondrocyte hypertrophy [Runx2 prevents normal hypertrophic cartilage mineralization [The runt-related transcription factor (RUNX) was first identified as an essential regulator of early embryonic segmentation in Drosophila . RUNX geecursors . Sp7 is of Runx2 . In Runxdetected . In chonertrophy  and the lization .Runx1 and Runx3 expression partially overlaps with Runx2 expression; these have redundant and distinct roles in association with RUNX2 in skeletal cells. In osteogenesis, RUNX1 and RUNX3 positively regulate osteoblast proliferation and differentiation, and RUNX1 functions as a compensatory factor for RUNX2 [Runx1 is expressed in mesenchymal cells and proliferating chondrocytes, whereas Runx3 is highly expressed in hypertrophic chondrocytes. The complete knockout of both Runx1 and Runx2 results in sternal abnormalities [Runx2 and Runx3 results in a complete loss of cartilage and bone mineralization [or RUNX2 , 12. Durmalities , whereaslization .Runx2 and redundant or distinct roles of Runx1 and Runx3 are also highlighted in skeletal metabolisms and diseases in adult stages. Bone mineral density decreases upon Runx2 deficiency in adult stages [Runx2-deficiency in adult skeletons in mice, Runx1- or Runx3-deficiency results in milder phenotypes [The crucial roles of t stages , whereasenotypes , 14. RUNenotypes . During enotypes –19. In tth lysine residue of the histone H3 protein (H3K4me3) represents an active promoter, and the acetylation of the lysine residue at the N-terminal position 27 of the histone H3 protein (H3K27ac) indicates an active enhancer. Overall, these provide a theory called “histone code”: the combination of histone modifications defines an epigenetic status in cells [Transcription is a key process where genes are transcribed into proteins that exhibit their biological functions. Transcript profiles are distinct depending on the cell type and physiological and pathological conditions. Transcription is tightly regulated by enhancers, cis-regulatory elements (CREs), where multiple transcriptional regulators coordinately act , 21. To in cells . In addiin cells   by binding to its distal enhancers [The examination of RUNX2-binding sites at various stages of osteoblast differentiation revealed dynamic changes in the RUNX2-DNA-binding sites. Wu et al. performed a clustering analysis of RUNX2 binding in conjunction with transcript profiles at various time points in an in vitro differentiation culture of the pre-osteoblastic MC3T3-E1 cell line . The resnhancers .TAPT1), protein RIC1 homolog (RIC1), and fibroblast growth factor 20 (FGF20). The expression of these genes was downregulated in an osteoarthritic mouse model, whereas their expression was rescued by RUNX1 overexpression, in conjunction with protection against cartilage destruction [The ChIP-seq of RUNX1, RUNX2, and RUNX3 has been performed in chondrocytes in vitro , 19. AltRunx3-deficient mice showed that RUNX3 directly regulated aggrecan (Acan) and proteoglycan 4 (Prg4). Prg4 functions as a boundary lubricant in the articular cartilage to decrease wear and friction. Acan is another anabolic factor in the cartilage. Thus, RUNX3 likely exhibits anabolic functions by regulating Prg4 and Acan during cartilage metabolism.Nagata et al. performed RUNX3 ChIP-seq on primary cells isolated from the superficial zone of the mouse articular cartilage •. The asRunx2-deficient chondrocytes treated with IL-1β revealed that the expression of Col2a1, a cartilage anabolic factor, was downregulated in Runx2-deficient cells treated with IL-1β, whereas it did not significantly change between the control and Runx2-deficient cells without IL-1β treatment. Motif analysis and reporter assays further showed that SRY-box transcription factor 9 (SOX9), a chondrocyte master regulator, compensated for RUNX2 during Col2a1 transcription. However, upon inflammation, SOX9 expression decreased, resulting in a decrease in anabolic factors including Col2a1. On the other hand, Mmp13, a catabolic factor, was downregulated because of Runx2 deficiency regardless of IL-1β treatment. These data suggest that RUNX2 acts as an anabolic and catabolic factor in different conditions, where Sox9 possibly compensates for RUNX2-mediated regulatory networks during the progression of OA. Notably, in the RUNX1 ChIP-seq analysis, the authors focused on RUNX1–DNA binding from the < 3 kb proximal promoter, whereas in RUNX2 and RUNX3 ChIP-seq studies, the authors investigated DNA binding from the > 500 bp distal enhancer far from the TSS. Thus, a comprehensive analysis in the same setting will help better understand detailed gene regulatory mechanisms underlying the different biological outcomes of the effects of the three RUNX members. Nagata et al. performed RUNX2 ChIP-seq using primary chondrocytes in vitro •. Here, Col1a2-flanking region in osteoblasts but not in chondrocytes. RUNX2 binding to CREs in the Col10a1-flanking region was detected in chondrocytes but not in osteoblasts. Consistent with these results, chromatin accessibility showed distinct cell-type signatures. Overall, cell-type-distinct RUNX2-DNA binding highlighted distinct cell-type target genes. Osteoblast-specific RUNX2 targets included Col1a1, Col1a2, Ostn, Fgf18, Dlx5, and Mef2c, whereas chondrocyte-specific targets included Col2a1, Col10a1, Bmpr1b, Sox5, and Creb3l2. Common target genes are also present in osteoblasts and chondrocytes. Notably, even for common target genes, such as Spp1, the distribution of RUNX2–DNA binding and chromatin accessibility around the genes was different between osteoblasts and chondrocytes [We recently reported a RUNX2 ChIP-seq study on primary osteoblasts and chondrocytes coupled with the ATAC-seq analysis of sorted skeletal cells in neonatal mice, providing insights into RUNX2-mediated regulatory mechanisms in a near in vivo setting ••. Becaudrocytes . These rFoxa2, Foxa3, and Foxc1, supporting their indispensable roles in hypertrophic chondrocytes [Sp7, Dlx3, Dlx5, and Dlx6 were highly expressed in the cells, supporting essential roles in osteogenesis [RUNX2 and cell-type-specific TFs are associated with CREs in osteoblasts and chondrocytes. FOX motifs were exclusively enriched in RUNX2-bound regions in hypertrophic chondrocytes. Gene expression analysis showed the high expression of related TFs, including drocytes –36. In tdrocytes  was specogenesis . In addiogenesis –43. BecaRunx2 in fibroblasts led to its DNA binding in closed chromatin regions, where chromatin accessibility was gained later [Runx2 ablation in Sp7-positive osteoblast precursors [Runx2-dependent” regions were distal from the TSS, enriched with the consensus RUNX motif, and highly associated with genes related to skeletal system development [Recently, a model of “pioneer factors” has been proposed; “pioneer factors” are supposed to facilitate the opening of closed chromatin sites . In thised later ••. The hecursors ••. The “elopment ••. Theseelopment •. Thus, Consistent with RUNX2, RUNX1 and RUNX3 have been suggested to act as pioneer factors in different cell types . RUNX1 hPhase separation is the basis for the formation of membrane-less organelles in cells and is involved in many biological processes. Recent studies have indicated that the assembly of transcription machinery at genomic sites occurs via liquid–liquid phase separation, leading to the formation of transcriptional condensates , 51. At However, the involvement of other RUNX members in phase separation remains to be clarified. RUNX2 IDR sequences are not well-conserved compared with those of RUNX1 or RUNX3, suggesting that phase separation may occur only with RUNX2. However, a recent study showed that the RUNX2 repression domain at the C-terminus is required for phase separation in cardiomyocytes, where RUNX2 interacted with arachidonate 5-lipoxygenase . This reGenome-wide studies have provided valuable insights into diverse aspects of gene regulation, including DNA-binding regions, histone modification, chromatin accessibility, and lipid–lipid phase separation. RUNX plays a critical role in controlling gene regulatory networks via diverse mechanisms. The fields that still require further exploration are as follows: (1) the development of therapeutic strategies based on insights gained from genome-wide analyses and (2) a deeper understanding of the human genetic variants that contribute to diseases.First, as described earlier, cis-regulatory actions are dynamic and cell-state-specific. Gene regulatory mechanisms underlying pathological conditions and tissue regeneration should be investigated. It is worth identifying disease-specific gene regulatory networks and manipulating them for treatment and disease diagnosis. CRISPR technology for epigenomic editing may be helpful . InteresSecond, from a human genetics perspective, extensive genome-wide association studies (GWAS) have identified associations between the human genome, skeletal development, and diseases , 59. Not


Dentro desse grupo de enfermidades, destaca-se a doença arterial coronariana, responsável por cerca de 12% dos óbitos totais no Brasil3 Esse fato é devido a diferentes fatores, incluindo diminuição da isquemia e dos sintomas, melhora da qualidade de vida, diminuição da ocorrência de infartos e, sobretudo, diminuição da mortalidade.4Além das mudanças do estilo de vida como abolição do tabagismo, perda de peso com prática regular de atividades físicas, controle de comorbidades, notadamente o diabetes e a hipertensão arterial sistêmica e o tratamento medicamentoso com antiagregantes plaquetários, betabloqueadores e estatinas, importante parcela dos pacientes necessita de tratamento objetivando a revascularização do miocárdio. Pacientes diabéticos, multiarteriais, com lesões no tronco da artéria coronária esquerda maiores do que 50% ou com função ventricular esquerda deprimida são os que mais se beneficiam.3 Durante esses procedimentos, artérias e/ou veias autólogas são usadas para o by-pass de artérias coronárias parcial ou totalmente ocluídas por placas ateroscleróticas. As cirurgias podem ser feitas de acordo com uma variedade de técnicas, desde o uso ou não de circulação extracorpórea até procedimentos minimamente invasivos, utilizando apenas enxertos arteriais, sendo importante a escolha adequada da melhor estratégia para cada perfil de paciente.3A modalidade de revascularização melhor indicada para os pacientes com as características descritas acima é a cirúrgica, por apresentar vantagens como aumento das chances de revascularização completa, diminuição de futuras reintervenções coronarianas e menor chance de complicações quando comparada com intervenções percutâneas.5Apesar dos grandes avanços ao longo do tempo, como melhora da técnica cirúrgica propriamente dita e aumento da variedade dos tipos de procedimentos, avanços na anestesia e dos materiais utilizados, aceita-se que o uso de biomarcadores poderia adicionar informações prognósticas importantes. No entanto, pesquisas de caráter molecular são incipientes e pouco frequentes até o momento.5 que teve como objetivo avaliar a expressão do gene PTEN e a expressão de sua proteína em amostras de tecido atrial direito e no sangue de 22 pacientes submetidos à cirurgia de revascularização do miocárdio em centro único. As amostras foram colhidas em dois momentos distintos, antes da cirurgia e após o término da circulação extracorpórea.Nesse sentido, destaca-se o estudo de Tahtasakal et al.,phosphatase and tensin homolog deleted on chromosome 10) localiza-se no cromossomo 10q236 e foi inicialmente identificado em 19977 como supressor tumoral.7 Estudos subsequentes classificaram-no também como regulador negativo de importantes vias de sinalização moleculares associadas com crescimento, proliferação e sobrevivência celulares, principalmente a via da fosfatidilinositol-3-kinase (PI3K)/AKT,6 concorrendo também para a modulação de outros processos biológicos, como lipogênese, glicólise e apoptose.9O gene PTEN . It presents advantages such as increased chances of complete revascularization, reduction of future coronary artery interventions, and less chance of complications compared to percutaneous interventions.5Despite major advances over time, such as improvements in the surgical technique itself and an increase in the variety of procedures, advances in anesthesia, and the materials used, it is accepted that the use of biomarkers could add important prognostic information. However, research of a molecular nature is incipient and infrequent so far.5 is relevant. It aimed to evaluate the PTEN gene’s expression and its protein’s expression in right atrial tissue samples and the blood of 22 patients undergoing CABG in a single center. Samples were collected at two different times, before surgery and after the end of the cardiopulmonary bypass.In that regard, the study by Tahtasakal et al.6 and was initially identified in 19977 as a tumor supressor.7 Subsequent studies also classified it as a negative regulator of important molecular signaling pathways associated with cell growth, proliferation, and survival, mainly the phosphatidylinositol-3-kinase (PI3K)/AKT pathway6 contributing to the modulation of other biological processes, such as lipogenesis, glycolysis, and apoptosis.9The PTEN gene (phosphatase and tensin homolog deleted on chromosome 10) is located on chromosome 10q235 They then concluded on the possible role of PTEN as a prognostic marker of coronary artery disease in the coming years. However, some points still deserve discussion.The main result presented by the authors was a substantial increase in gene expression and the protein encoded by PTEN in tissue samples from the right atrium, a recognized biomarker site of cardiac proteomics.10First, all surgeries were performed under cardiopulmonary bypass, a recognized and safe method that replaces cardiopulmonary functions and facilitates the confection of anastomoses after aortic clamping and diastolic cardiac arrest. Due, however, to the passage of blood through non-endothelial surfaces and non-pulsatile blood flow, relevant changes may occur in greater or lesser intensity in physiology. In a minority of cases, systemic inflammatory response syndrome, coagulopathies, low cardiac output syndrome, and myocardial ischemia-reperfusion injury at the cellular level are described, for example.Thus, it is necessary to clarify the extent to which the increase in gene expression of PTEN and its respective protein was also due to the stress induced by cardiopulmonary bypass.11 This data may be related to increases in PTEN expression, which, as already mentioned, actively participates in the metabolic regulation of lipids and glucose and mitochondrial metabolism.6 Likewise, it is important to remember that PTEN is subject to post-translational changes and epigenetic regulatory mechanisms.12 Added to these data is that other genes act together with PTEN on coronary artery disease13 in processes that take place simultaneously.Another aspect to be considered is that other factors, such as hypoxia induced by aortic clamping and reperfusion, may act as additional stress factors for cardiomyocytes, which start to obtain a large part of their energy through glucose instead of fatty acids.Despite the above considerations and having evaluated only 22 patients, the study in question has some other points that deserve to be highlighted, such as being the first to evaluate the PTEN gene in the context of myocardial revascularization, deepening the subcellular analysis during an extensively performed procedure and proven to be beneficial for several subgroups of patients. Thus, the way is paved for new research that aims to define prognostic markers and new therapeutic targets in this clinical setting.


Paralichthys olivaceus) is an economically important aquaculture fish species broadly cultivated in east Asia, mainly along the coast of the Bohai and Yellow Seas in China, as well as the coast of Korea and east Japan. Natural and cultivated P. olivaceus may suffer from cold stress during the winter months. In this study, modulated transcriptomic responses to 10 °C acute cold stress were investigated in the gills, hearts, livers, and spleens of P. olivaceus. Based on transcriptome and weighted gene coexpression network analysis, tissue-specific cold responsive modules (CRMs) were identified, which revealed a cascade of specific cellular responses to cold stress in different tissues. Our results illustrate the diverse and modulated regulation of the cellular process and stress response to low temperature, which provide essential insights for the conservation and cultivation of P. olivaceus in cold water.Low temperature is an often overlooked stress that many fish face due to both natural and anthropogenic causes. Japanese flounder , an important aquaculture species in east Asia. Histological examination suggested different levels of injury among P. olivaceus tissues after cold shock, mainly in the gills and livers. Based on transcriptome and weighted gene coexpression network analysis, 10 tissue-specific cold responsive modules (CRMs) were identified, revealing a cascade of cellular responses to cold stress. Specifically, five upregulated CRMs were enriched with induced differentially expressed genes (DEGs), mainly corresponding to the functions of “extracellular matrix”, “cytoskeleton”, and “oxidoreductase activity”, indicating the induced cellular response to cold shock. The “cell cycle/division” and “DNA complex” functions were enriched in the downregulated CRMs for all four tissues, which comprised inhibited DEGs, suggesting that even with tissue-specific responses, cold shock may induce severely disrupted cellular functions in all tissues, reducing aquaculture productivity. Therefore, our results revealed the tissue-specific regulation of the cellular response to low-temperature stress, which warrants further investigation and provides more comprehensive insights for the conservation and cultivation of P. olivaceus in cold water.Low temperature is among the important factors affecting the distribution, survival, growth, and physiology of aquatic animals. In this study, coordinated transcriptomic responses to 10 °C acute cold stress were investigated in the gills, hearts, livers, and spleens of Japanese flounder ( Temperature, as the major environmental stimulating factor, has essential effects on almost all biological processes in organisms, affecting their physiological and metabolic activities, immune and antioxidative responses, growth and behavior, as well as migration, especially for poikilothermic teleost species ,2. In thA sharp reduction in ambient temperature is defined as cold shock, which has the potential to cause a rapid decline in body temperature, resulting in a cascade of physiological and behavioral responses . TeleostIn addition, many studies have pointed out that tissues involved in the physiological response and acclimation to low-temperature stress can exhibit tissue-specific characteristics ,9,10. FoRecently, with the increasing abundance of sequencing data, weighted gene coexpression network analysis (WGCNA) is a powerful method that has been used to provide a comprehensive understanding of gene interaction networks. WGCNA focuses on the modulated regulation of the full-complement gene sets that comprise complex networks, transitioning data analysis from being gene-centric to systematically network-centric . TherefoParalichthys olivaceus) is an economically important aquaculture teleost species broadly cultivated in east Asia, mainly along the coast of the Bohai and Yellow Seas in China, as well as along the coast of Korea and east Japan [P. olivaceus [P. olivaceus, there are several months of cold winter, with the lowest temperature being 0 °C [P. olivaceus growth rate significantly decrease and reduces aquaculture productivity [P. olivaceus specimens were subjected to 10 °C acute cold shock stress to observe the cellular damage to the gill, heart, liver, and spleen tissues, and transcriptome data were comprehensively analyzed with WGCNA. The results present a fundamental reference for cold shock damage in different P. olivaceus tissues and provide vital insights for the conservation and cultivation of P. olivaceus in cold water.Japanese flounder  were obtained from Nanshan market, Qingdao, China, and acclimated in seawater in a laboratory aquarium  for one week. The seawater was aerated and refreshed once per day. Then, the P. olivaceus specimens were randomly divided into two groups: a control group under a temperature of 18 °C, and an acute cold shock group, which were abruptly transferred to 10 °C sea water for a short term of 6 h. There were 9 specimens in each group with 3 individuals in each of the 3 tanks as replicates, and no fish died during the experiment. Circulating water refrigerators  were employed to maintain the cold temperature. After the cold shock challenge, P. olivaceus specimens were euthanized with MS-222, and the gill, heart, liver and spleen tissues from each specimen were sampled and stored at −80 °C with lipid nitrogen for RNA isolation and in Bouin’s fluid for histological observation.A total of 18 adult P. olivaceus tissues from Bouin’s fluid were dehydrated following a successive ethanol gradient of 50%, 70%, 90%, 95%, and 100%. Then, the tissue samples were transparentized with xylene and ethanol mixture, embedded into paraffin, and sliced into a thickness of 5 µm. The samples were further dewaxed and stained with hematoxylin and eosin (H&E)  following the traditional method [To observe the histological changes under cold stress, the l method . FinallyP. olivaceus were sampled and frozen with liquid nitrogen. Total RNA was isolated using a method with SparkZol Reagent . The genomic DNA contamination was removed by RNase-free DNase I  treatment. The total RNA was then qualified and quantified by 1.5% agarose gel electrophoresis and spectrophotometry, respectively. The RNA samples were further employed for RNA sequencing library preparation and high-throughput sequencing. The RNA sequencing was conducted on an Illumina Hiseq 4000 platform at the Beijing Novogene company .The gill, heart, liver, and spleen tissues of P. olivaceus under cold shock stress, 24 transcriptome datasets from four tissues  of both the control and cold shock groups were analyzed. After trimming adaptors and removing low-quality reads, the clean reads were mapped against the P. olivaceus genome using the Hisat and StringTie pipeline [q-value of <0.05 and |log2FoldChange(FC)| > 1.5. The R package clusterProfiler 4.0 was employed for Gene Ontology (GO) functional enrichment analysis. TBtools [2FC values.To investigate the gene expression profiles of pipeline  with defpipeline . Differe TBtools  was utilP. olivaceus tissue samples with WGCNA R library [p < 0.05). Furthermore, GO terms were enriched for genes in each module as the functional annotation by EnrichPipeline [WGCNA  was cond library . A gene Pipeline . CytoscaPipeline .P. olivaceus gills compared with those of the control group, and the supporting structure of the gill filament shrunk and the branchial lamellae were curlier (Eleutheronema tetradactylum) gills under cold shock, in which the branchial lamellae of E. tetradactylum shrunk, swelled, and curved [P. olivaceus hearts between the cold shock group and the control group , 270 (80 up- and 190 downregulated), 140 (57 up- and 83 downregulated), and 457 (234 up- and 223 downregulated) differentially expressed genes  were identified in the gill, heart, liver, and spleen tissues, respectively (period circadian protein homolog 2 (PER2) and the four downregulated DEGs shared by the four tissues were interleukin-10 receptor subunit beta (Il10rb), C-X-C motif chemokine 10 (CXCL10), putative nuclease HARBI1 (HARBI1), and serine/threonine-protein phosphatase (PPP3CA). Moreover, the abundant tissue-specific DEGs indicated the particular gene sets participating in the diverse cellular processes in P. olivaceus tissues. Specifically, the tissue-specific upregulated DEGs were enriched in GO terms including “cell growth”, “demethylase activity”, “extracellular matrix,” and “immune response” in the gills; “circulatory system”, “oxidation”, “extracellular region”, and “cytoskeleton” in the hearts; “heme oxidation”, “lipase inhibitor activity”, and “cellular metabolic process” in the livers; and “transmembrane transport”, “cell cycle”, and “cell growth” in the spleens , including 5 modules enriching activated and inhibited DEGs each (FDR < 0.05) for gills (turquoise and pink), hearts (yellow), livers (turquoise and cyan), and spleens (pink and red), respectively; while two, three, two, and one modules were enriched in downregulated DEGs (FDR < 0.05) for gills (green-yellow and purple), hearts , livers (green-yellow and blue), and spleens (green-yellow), respectively  could act as a receptor for entry into the epithelial and endothelial cells of the gills; integrin alpha-11 (ITGA11) is the receptor for collagen; and cell antigen CD34 is the adhesion molecule mediating the attachment of stem cells to the extracellular matrix (ECM) [P. olivaceus gill filaments and lamella under the cold shock stress. Moreover, the downregulated DEGs, mainly from the “cell cycle” and “cell division” functions, were interlinked in the gill-specific networks (DNA polymerase (POLA2 and POLE2) and histone (H2B and H3) play essential roles in transcription regulation, DNA repair, DNA replication, and chromosomal stability; cyclin-dependent kinase inhibitor 1 (CDKN1A) may be involved in the p53/TP53-mediated inhibition of cellular proliferation in response to DNA damage; and protein mis12 is required for normal chromosome alignment and segregation and for kinetochore formation during mitosis [P. olivaceus under heat shock, in which the upregulated functions were mainly enriched in the cellular response to stimuli, protein refolding, and regulation of apoptotic process, while the downregulated functions were mostly enriched in DNA repair and replication, as well as the cell cycle [P. olivaceus gills under both heat [P. olivaceus gills under both heat and cold shock stresses.In the CRMs, many DEGs represented tissue-specific regulation under cold shock challenge b, which unctions  were intunctions . Therefoix (ECM) ,34,35. Anetworks . For ins mitosis ,37,38. Tll cycle . Interesoth heat  and coldxin actin-binding repeat-containing protein 2 (XIRP2) can protect actin filaments from depolymerization; leiomodin-3 (LMOD3) increases the rate of actin polymerization; and microtubule-associated protein 6 (MAP6) specifically shows microtubule cold-stabilizing activity [P. olivaceus heart, which could interact with the circulatory functional gene endothelin  to cope with cold stress (superoxide dismutase (SOD3), which can protect the extracellular space from the toxic effects of reactive oxygen intermediates [P. olivaceus cardiovascular system (tubulins (TUBA and TUBB) are the major constituents of microtubules; myosin (Myo16) is an actin-based motor molecules with ATPase activity, which can serve in intracellular movements; homeodomain-interacting protein kinase 2 (HIPK2) is involved in transcription regulation, p53/TP53-mediated cellular apoptosis, and regulation of the cell cycle [P. olivaceus heart under cold stress. A sharp temperature decline can lead to impaired cardiac contractile function in fish, as the thin filaments in the cardiac muscle are less sensitive to Ca2+ at lower temperatures [Oncorhynchus mykiss) cardiac actin-myosin ATPase activity showed more Ca2+ sensitivity than that of rats, which may help O. mykiss to offset the cardioplegic effects of cold [In the heart-specific upregulated DEGs, cellular-structure-related functions such as “actin filament” and “cytoskeleton” were enriched. For example, activity ,40,41,42d stress . Moreovemediates , was alsr system . In addill cycle ,44,45,46eratures . For exa of cold . Moreove of cold .P. olivaceus livers than in other tissues from the network (heme oxygenase (HMOX) catalyzes the oxidative cleavage of heme, which can protect against cold-injury-induced cell loss and damage [DNA polymerase (POLE) and cell division control protein (CDC45) are both required for the initiation of chromosomal DNA replication. Mitochondrial ribosome-associated GTPase 2 (GTPBP5) plays a role in the regulation of the mitochondrial ribosome assembly and of translational activity, all suggesting the inhibited function of the “cell cycle” and “cell division” [inositol polyphosphate-5-phosphatase A (INPP5A) and phosphatidylinositol 4,5-bisphosphate 5-phosphatase A (INPP5J) were interlinked as the up- and downregulated DEGs in the network, respectively  (SLCs in transmembrane transport [DNA replication licensing factors (MCM2 and MCM3), G2/mitotic-specific cyclin-B (CCNB3), kinesin-like proteins , and mitotic spindle assembly checkpoint protein (MAD2A) can prevent the onset of anaphase until all chromosomes are properly aligned at the metaphase plate [Proliferating cell nuclear antigen (PCNA) is also involved in the control of eukaryotic DNA replication by increasing the polymerase’s processability during elongation of the leading strand [Oreochromis niloticus), immune and antioxidative process were affected, and xanthine oxidase, peroxidase, catalase, and superoxide dismutase played an important role [P. olivaceus spleens, which may warrant further investigation of their specific functions.Moreover, several spleen-specific upregulated DEGs interlinked in the networks were membrane- and (ion)-transporter activity-related genes , such asSLC43A3) , which iransport . In addise plate ,61,62. Pg strand ,63  and occludin (OCLN) genes were clustered as hub genes in the network  are actin-based motor molecules serve in intracellular movements; epithelial splicing regulatory protein 1 (ESPR1) regulates the formation of epithelial-cell-specific isoforms; and syntaxin-19 (STX19) plays a role in endosomal trafficking of the epidermal growth factor receptor [P. olivaceus gills and livers under cold stress  and DNA replication complex GINS proteins , both playing essential roles in the initiation of DNA synthesis [G2/mitotic-specific cyclins (CCNA2 and CCNE2), interacting with cyclin-dependent kinase (CDK), are important for the control of the cell cycle at the G2/M (mitosis) transition [cell division cycle associated family proteins (CDCA5 and CDCA8) play a vital role in efficient DNA double-stranded break repair; DNA replication licensing factors  are the replicative helicases essential for DNA replication initiation and elongation in eukaryotic cells; kinesin-like proteins  play a role in chromosome segregation during mitosis; and protein mises  are required for normal chromosome alignment and segregation [P. olivaceus tissues under cold shock. It was reported that many types of mammalian cells failed to undergo the G(2)/M transition after cooling from 37 °C to 16–20 °C, while the progress at G(1)/S was not affected by the same temperatures [P. olivaceus gills and livers under heat shock [Danio rerio) and common carp (Cyprinus carpio) under cold stress are mostly involved in oxidative phosphorylation, protein folding and degradation, RNA processing, and translation, which comprise the set of evolutionarily conserved cold-responsive mechanisms in teleosts [P. olivaceus gill, heart, liver and spleen tissues during the cold shock, which warrants comprehensive investigation of their functions in further studies.More interestingly, the green-yellow module, representing the downregulated DEGs from all four tissues, was enriched in functions mainly including “cell cycle”, “cell division”, “DNA package complex”, “chromosomal region”, and “response to stress” , indicatynthesis ,50, wereansition . Moreoveregation ,70,71,72eratures . Moreoveeratures . In teleat shock ,53, and teleosts . TherefoP. olivaceus) tissues under cold shock stress. The tissue-specific modulated expression regulation of genes was observed in response to acute cold shock, which was mainly found in the activated “extracellular matrix” and “cytoskeleton” functions, as well as in the inhibited “cell cycle” and “DNA complex” functions in all tested tissues. These findings indicated that even with different levels of tissue-specific responses, cold shock may induce severely disrupted cellular functions in many P. olivaceus tissues, which reduce aquaculture productivity. Therefore, further investigation into the functions of specific CRM networks will provide more comprehensive insights into the cold adaptation mechanisms and will enable better conservation and cultivation of P. olivaceus in cold water.The poikilothermal teleost species present diverse temperature responses reflected in the tissue-specific cellular, antioxidative and immune statuses. This study performed a systematic transcriptomic and gene coexpression network survey in Japanese flounder (


Here, we describe the use of a real-time, fluorescent-aptamer-based method to quantitate steady-state transcription rates of the Mycobacterium tuberculosis RNA polymerase. We present clear controls to show that the assay specifically reports on promoter-dependent, full-length RNA transcription rates that are in good agreement with the kinetics determined by gel-resolved, α-32P NTP incorporation experiments. We illustrate how the time-dependent changes in fluorescence can be used to measure regulatory effects of nucleotide concentrations and identity, RNAP and DNA concentrations, transcription factors, and antibiotics. Our data showcase the ability to easily perform hundreds of parallel steady-state measurements across varying conditions with high precision and reproducibility to facilitate the study of the molecular mechanisms of bacterial transcription.The first step in gene expression is the transcription of DNA sequences into RNA. Regulation at the level of transcription leads to changes in steady-state concentrations of RNA transcripts, affecting the flux of downstream functions and ultimately cellular phenotypes. Changes in transcript levels are routinely followed in cellular contexts via genome-wide sequencing techniques. However,   Escherichia coli promoters can differ in rates of promoter opening by factors of 103–104, resulting in initiation events ranging from once per second to once per generation neration . The resneration , bringinmK  and/or maxV  without changes in the free RNAP concentration. Alternatively, constitutively active promoters are affected by cell growth-rate-dependent changes in the free RNAP concentration, independent of changes in mK and/or maxV , we describe a workflow for the calibration and quantification of RNA concentration in multi-round initiation kinetics analyzed with a Michaelis-Menten approach. Most significantly, we illustrate the utility of this approach for the investigation of mechanisms of transcriptional regulation by NTP concentration, transcription factors, and antibiotic inhibitors, all derived from high-throughput measurements under steady-state conditions.Fluorescent light-up aptamers are RNA sequences that bind small molecule fluorophore dyes and generate a large fluorescence enhancement. They have been used in numerous applications (reviewed in ) includi T7 RNAP  and with T7 RNAP . These a T7 RNAP . Importaoli RNAP  and in aoli RNAP . Here, wMtb ribosomal RNA promoter (rrnAP3), the Spinach-mini aptamer  in length, were ordered from Twist Bioscience , containing the sequences corresponding to the  aptamer  and the rminator  . Purified E. coli GreB was a generous gift from Irina Artsimovitch (The Ohio State University) , Mtb CarD , Mtb RbpA , and E. coli GreB .The  methods ,46. Mtb escribed ,46. E. cversity) . Protein−1 cm−1. Rifampicin  and Fidaxomicin  solids were dissolved in DMSO and molar concentrations were determined by weight (Fidaxomicin) or by absorbance using an extinction coefficient at 470 nm of 15,300 M−1 cm−1 (All transcription reactions were performed with NTPs (Thermo Scientific), 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) dye , and RiboLock RNase inhibitors . DFHBI concentration was determined using an extinction coefficient at 420 nm of 31,611 MM−1 cm−1   with the corresponding Gen5 analysis software. DFHBI fluorescence was measured with a tungsten light source equipped with a 505 nm long-pass dichroic mirror, excited with a 460 ± 40 nm bandpass filter, and the resulting emission signal was monitored with a 528 ± 20 nm bandpass filter. Data was acquired at a read height of 7.00 mm, typically in 20–30 s intervals, with varying total acquisitions times, not exceeding 75 min.2, 5 μM ZnCl2, 20 μM EDTA, 5% (v/v) glycerol (defined as transcription buffer) with 1 mM DTT and 0.1 mg/mL BSA. From these master mixes, a volume of 9 μl for each technical replicate was transferred to an individual well in a 384 well, low volume, round-bottom, non-binding polystyrene assay plate . For the negative controls, which represent the entirety of the reaction components except for DNA, 1 μl of transcription buffer was added to account for the remaining 10% of the final reaction volume (10 μl). Wells were covered with an optical adhesive to prevent sample evaporation . The plate was then incubated for 10 min at 25°C, followed by a 30 s shake agitation in the microplate reader. An initial reading of the negative controls was used to scale the automatic gain adjustment to the background signal with an arbitrary value of 1000 RFUs and was applied to all the subsequent reads. The adhesive cover was removed, and the transcription reaction was initiated with 1 μl DNA unless otherwise indicated. Multichannel pipettors were used to reduce the initiation time difference across wells. Once the DNA was added, the plate was agitated for 15 sec before starting the kinetic measurements. Unless otherwise stated, the reaction master mixes always contained 20 μM DFHBI and 0.4 U/μl RNase inhibitors. For additional details regarding reaction specifics for individual titrations, including titrations measured under single-round conditions, see Transcription reaction master mixes containing 90% of the final volume included the RNAP holoenzyme, NTPs, DFHBI, and RNase inhibitors. Based on the volumes added for each corresponding buffer addition and concentrated stock component, the final solution conditions were 20 mM Tris (pH 8.0 at 25°C), 40 mM NaCl, 75 mM K-glutamate, 10 mM MgClMtb σA RNAP holoenzyme and DFHBI concentrations were varied and always included unless otherwise indicated. 20 nM of α-32P UTP was added to label the nascent RNA transcripts via incorporation by RNAP. Reactions were initiated by addition of circular plasmid constructs containing either 5 nM Mtb rrnAP3 or a template lacking a promoter . Using a statistical weighting from multiple technical replicates per condition and a user inputted s of fit , an unbiFor analyses of titration data that yielded hyperbolic concentration dependencies in steady-state rates, a Michaelis-Menten equation was applied, fitting the data to Equation 1v represents the steady-state rate and S represents the titrated substrate, either DNA or individual NTPs. Steady-state rates determined in some NTP titrations were not well-described by Equation maxV, an apparent mK , and the exponent n.where mK,app as the NTP concentration that results in half maximal velocity, which is equivalent to the standard operational definition of mK when n = 1. It should be noted that while this equation is functionally identical to the Hill equation, if a non-unity n is the result of the kinetics from a single-site-binding system, then n is only effectively demonstrative of the type (positive/negative) and magnitude of cooperativity. In such a case, n has no specific physical meaning as it does in more traditional cases such as cooperative binding of multiple ligands (50IC) of Rifampicin and Fidaxomicin, the concentration-dependent reduction in steady-state rates was fit to Equation Here, we define  ligands . The kinmaxV, m,appK, n and 50IC values are those obtained from the fit of the averaged data set. For simplicity, only a single representative independent experiment is shown in the plots. For gel-based quantifications, average values and standard deviations from 2 to 3 independent experiments are reported.For all fluorescent data presented unless otherwise indicated, between 2 and 4 independent experiments were collected for each condition tested. Within each independent experiment, standard deviations from 2 to 3 technical replicates were used as a statistical weight during the linear regression analyses. All non-linear regression analyses were performed using the standard deviations of the independent experiments as a statistical weight. Errors in https://github.com/egalburt/aptamer-flux-fitting).The MATLAB code used for automated linear regression analyses has been made publicly available and can be accessed with the following GitHub link . Specifically, –60 to +31 of rrnAP3 was included to account for any upstream-promoter interactions as well as the initially transcribed sequences, both of which can regulate initiation kinetics. Inclusion of the genomic initially transcribed sequence, rather than just positioning the aptamer sequence to start at the +1 position, provides for unaltered promoter escape, which is known to become rate limiting under certain conditions  a lag time, (ii) a linear increase and (iii) roll-off from the linear regime that begins to plateau over time , leadint signal . Based ot signal ,55. As GR2 value (goodness of fit) is compared to a threshold set by the user to evaluate whether the fit was adequately linear or whether a further reduction in the time frame should be attempted  and an ∼5-fold increase in the apparent mK  . These results indicate that we can confidently assign the fitted kinetic parameters to a rrnAP3-derived product under these experimental conditions.We performed analogous NTP titrations on the promoterLESS circular plasmid template. Compared to the kinetic parameters obtained with the ) Figure , inset. ) Figure , we intein vivo global rate of transcription largely independent of gene concentration  and linear PCR templates (250 bp) to provide different numbers of non-rrnAP3 specific interaction sites for the RNAP.In bacterial cells there exists a large molar excess of genomic DNA relative to the amount of free RNAP, making the ntration . Under tcription ,61) and rrnAP3 circular plasmid (0.1–50 nM) at two different concentrations of Mtb RNAP (20 and 100 nM)  Figure , B and o) Figure  as expec) Figure . Of note) Figure . These orrnAP3 promoter sequence  revealed a specific band of the expected length in accordance with the position of the termination sequence on the circular plasmid containing the rrnAP3 promoter but not on the promoterLESS circular plasmid template  other than the promoter region being studied and they are not considered further.Our fluorescence measurements clearly exhibit a promoter dependence Figure . As expee Figure . In addie Figure . As thesMtb RNAP with 5 nM rrnAP3 circular plasmid DNA  of the other three NTPs  than the subsequent NTPs are frequently required for promoter-specific initiation, especially on ribosomal RNA promoters where incorporation of the iNTP increases the population of open complexes at equilibrium, which can be a rate-limiting step ,64. We hs Figure . Each ins Figure . When ths Figure  was unabr Figure . As preds Figure . Notablye Figure , D. Furte Figure , consiste Figure . Even thin vitro, the most common approach is to use single timepoint measurements to compare transcription in the presence and absence of the factor. However, by only evaluating a single timepoint for each condition there is no guarantee or confirmation that the measurements are representative of changes occurring throughout a steady-state process. In contrast, the aptamer assay directly measures the effect of transcription factors in real-time and by focusing the analysis on the linear regime in an unbiased manner, ensures that factor-dependent changes are quantified under steady-state conditions. To demonstrate the use of the assay in analysis of transcription factor effects, we turned to two well-studied Mtb transcription factors, CarD and RbpA.When evaluating the effect of a transcription factor rrnAP3 promoter  and revalent . To thisial RNAP .Mtb or E. coli RNAP with 5 nM Mtb rrnAP3 circular plasmid template  and Mtb RNAP (17 ± 2 nM) were within error  than on Mtb RNAP (138 ± 92 nM) .,75.Mtb o) Figure , consist E. coli ,76.The fluorescence experiments presented here are an attractive alternative technique to the standard radiolabeled-nucleotide incorporated gel-based approaches when used to quantitate steady-state transcription kinetics, especially when used in a plate-reader format as described. Hundreds of conditions can be measured in real-time with several technical replicates in a single experiment. We estimate that the throughput is on the order of a hundred times that of standard gel-based approaches, where the real-time measurements facilitate a more precise and accurate determination and quantification of the steady-state regime. As the steady-state rate of full-length transcription  is a crucial metric when considering the flux of biological processes that use RNA as a substrate , use of E. coli RNAP , includs Figure ,88. Mecholi RNAP ,14,16,17Given these fluorescent experiments were all performed in a 384 well plate, the assay lends itself naturally to questions that require large data sets. We conclude by summarizing a few exciting possible directions.in vitro to expand our knowledge of gene regulatory mechanisms.Using sequence to predict transcriptional activity remains a challenge, as the context of the entire promoter must be considered when examining how sequence affects initiation kinetics . Using t50ICs as described here. To develop structural hypotheses for the mechanism of transcription initiation inhibitors (or classes of inhibitors), titrations of NTPs or promoter DNA could be performed to determine the type of inhibition  via quantification of changes in m,appK and/or maxV (As we illustrated the utility of the fluorescence assay in measuring antibiotic inhibition Figure , the hig/or Vmax .gkad761_Supplemental_FileClick here for additional data file.