Toxoplasma gondii. We show a striking activation of host cell genes that regulate a number of cellular processes, some of which are protective of the host cell, others likely to be advantageous to the pathogen. The simultaneous capture of host and parasite genomic information allowed us to gain insights into the regulation of the T. gondii genome. We show how chromatin accessibility and transcriptional profiling together permit novel annotation of the parasite’s genome, including more accurate mapping of known genes and the identification of new genes and cis-regulatory elements. Motif analysis reveals not only the known T. gondii AP2 transcription factor-binding site but also a previously-undiscovered candidate TATA box-containing motif at one-quarter of promoters. By inferring the transcription factor and upstream cell signaling responses involved in the host cell, we can use genomic information to gain insights into T. gondii’s perturbation of host cell physiology. Our resulting model builds on previously-described human host cell signalling responses to T. gondii infection, linked to induction of specific transcription factors, some of which appear to be solely protective of the host cell, others of which appear to be co-opted by the pathogen to enhance its own survival.To gain insights into the molecular interactions of an intracellular pathogen and its host cell, we studied the gene expression and chromatin states of human fibroblasts infected with the Apicomplexan parasite  The infection of a cell by an intracellular pathogen is accompanied by substantial changes in cellular homeostasis, reflected by activation and suppression of cell signaling pathways such as those regulating metabolism, cell division and cell death . Some ofToxoplasma gondii. This apicomplexan intracellular parasite is extremely successful, with an estimated one-quarter of humans chronically infected [in utero. We now recognize many of the events occurring during T. gondii infection of host cells [We focus here on human cell infection by infected , causingst cells , giving The application of genomic assays to cells infected by a eukaryotic pathogen yields rich but complex information. These assays can test transcription and its regulatory control from two organisms simultaneously, with some of the transcriptional and regulatory changes in the genome of the host cell likely to be a protective response to the infection, but other changes potentially advantageous for the pathogen, reflecting the molecular hijacking of host cell physiology. We also obtain a snapshot of the transcription and its regulation in the pathogen’s genome. The host loci at which regulatory changes are occurring are highly likely to include those mediating evolutionary selection, including host regulatory loci located distantly from genes in the non-coding majority of the genome, loci that would otherwise be difficult to identify and characterize using sequence information alone.T. gondii genome, showing that it is free of DNA methylation [T. gondii histones define cis-regulatory loci [T. gondii, revealing host responses, pathogen genomic regulation during the tachyzoite stage of T. gondii life cycle, and a new annotation of genes and cis-regulatory loci in the T. gondii genome, yielding insights into candidate transcription factor binding sites and the organization of T. gondii’s apicoplast genome. We also demonstrate how we can infer from observations of transcriptional perturbation insights into host cell signaling pathway alterations occurring in response to intracellular infection by this common pathogen.We have previously characterized transcriptional regulatory information in the hylation  and thatory loci . In thisin vitro infection with the T. gondii RH strain in the tachyzoite stage of the life cycle . RNA-seq reads were aligned to a reference genome that combined both the human and T. gondii genomes simultaneously, an approach that shows more accurate representations in studies of infected host cells [S1 Table).We performed RNA sequencing (RNA-seq) of human foreskin fibroblasts (HFFs), before and 24 hours after st cells . We showADAMTS15, a member of the A Disintegrin and Metalloprotease with Thrombospondin Motifs (ADAMTS) gene family. These metalloproteases function as regulators of extracellular matrix (ECM) composition, potentially enhancing cell migration by removing collagen barriers [Fig 1C), the RNA-seq data showed four of the nine genes encoding interacting proteins to have increased levels of expression in infected cells . Matrix metalloproteases have been previously found to be overexpressed in response to T. gondii infection of astrocytes [The single most markedly upregulated gene was barriers , 9. By utrocytes  and dendtrocytes , potentitrocytes .S2 Table). This analysis revealed three main subnetworks, one revealing a host cell immune response, a second the initiation of cell division, and a third reflecting activation of metabolic pathways . The immune response subnetwork included upregulation of the NFKB1, ORAI1, and IL6 genes, indicative of activation of both the innate and adaptive immune responses [TGFB, CXCL6, TNFSF15 and XCL1, which prompt the recruitment of immune cells to the location of an ongoing infection [PRKDC, CASP2, and ATR [CYP27B1, DGAT2, FASN, and PCSK9 [T. gondii has to acquire from the host cell [To gain insights into the properties of the broader group of upregulated genes, we performed a gene set enrichment analysis (GSEA), reducing the gene ontology (GO) terms by semantic similarity  [S2 Fig), in addition to an average of 28% fewer T. gondii reads, and therefore was removed from the comparison with the interpretation that this sample did not achieve a degree of infection comparable to the other replicates. We used DESeq2 [Fig 2A). Of these DARs, only 51 (9.6%) were located within 5 kb of annotated transcription start sites, indicated that chromatin accessibility changes mostly occur at distal regulatory elements .To gain insights into the mechanism for the host transcriptional changes during TAC-seq)  in the fd DESeq2  to identFig 2B). When we performed an analysis of the same DNA sequences using the vertebrate core motif database JASPAR2020, the same motifs were significantly enriched, accompanied by more NFκB family members and a broader group of candidate TFs (S3 Table).To gain insights into the transcription factors (TFs) potentially mediating these changes in chromatin accessibility, we performed motif enrichment analysis using MEME-ChIP  on the cFig 1E–1G. To maximize our confidence of an association between a DAR and a gene, we focused on those within 5 kb of an annotated gene transcription start site (TSS), identifying DARs containing only one of these motifs , and asked whether binding site motifs for each TF was enriched for genes mediating one or more of the cellular properties altered during infection. We show these results in Fig 2D. While all three TF binding motifs were associated with genes mediating immune responses, the RELA (NFκB) motif was enriched at those genes alone, while AP-1 (FOSB::JUNB) motifs were also enriched at genes involved with cell division and metabolic processes, and the motifs for RREB1, which mediates RAS-MAPK signaling [We asked the question whether these three TFs were distinctively associated with the major groups of differentially expressed genes shown in ignaling , are assT. gondii genome. We could therefore use the ME49 reference genome for T. gondii to align RNA-seq reads, detecting 3 or more reads in ≥2 replicates at 6,653 genes , of which 6,191 genes (93%) showed expression in all three replicates (S4 Table). Focusing on this last group of consistently expressed genes, we used hierarchical clustering to identify groups with high (391 genes), medium , or low  levels of expression . Using the gene ontology (GO) annotations of T. gondii ME49 genes from ToxoDB (toxodb.org), we found that highly expressed genes are enriched for protein translation processes, medium expression genes for proteosome and catabolic protein processes, and low expression genes for RNA processing and genomic activity (S5 Table). Overall, our enrichment analysis reveals a hierarchy of biological functions of differentially-expressed genes during the tachyzoite stage of T. gondii related to their roles during infection.Our RNA-seq dataset in infected cells included transcripts from the T. gondii genome, using the T. gondii ME49 reference genome for alignment, representing a follow up to our prior microarray ChIP study of 650 kb of the T. gondii genome [T. gondii [Using the ATAC-seq dataset from the infected cells, we were able profile the loci with accessible chromatin genome-wide in the . gondii –37.T. gondii ME49 genome. The reads exhibited the expected fragment size distribution characteristic of nucleosome free and nucleosomally-organized fragments , with the exception of reads originating from the apicoplast chromosome, where there is no evidence of nucleosomal organization .Within the ATAC-seq sample, a mean of 34.6% of reads across the replicates mapped to the Fig 4A). The majority of these peaks (96.1%) were located within 5 kb of an annotated genomic feature, with 91.1% located <1 kb from a transcription start site. When we compared the distribution of ATAC-seq peaks to annotated transcription start sites (TSS), we found a skewing upstream , reflecting many gene annotations for which the TSS is located substantially downstream from the open chromatin region where the start of the RNA-seq reads is also apparent .A total of 4,672 unique peaks were called across all replicates, with the fraction of reads located within peaks (FrIP score ) averagiFig 5A). Inspecting these loci, we found examples of what appear to be new, unannotated genes , unannotated anti-sense transcripts , the use of alternative TSS within bodies of annotated genes  and distal cis-regulatory elements . The combination of ATAC-seq and RNA-seq appears to permit more detailed annotation of the genome than would each assay on its own.Some ATAC-seq peaks were not located close to annotated TSS. We explored the representation of RNA-seq reads near this subset of peaks and performed K-nearest neighbors (KNN) clustering to define 5 clusters T. gondii transcriptional regulation. We used de novo motif enrichment analysis with MEME-ChIP [-20) motifs .The chromatin accessibility dataset provided a novel opportunity to define candidate TF binding sites involved in EME-ChIP  and idenT. gondii motif that we identified is the purine-rich AAAAAGGAAGAAA sequence, located at 267 open chromatin regions. The next most abundant motif that we found is the known apicomplexan AP2 TF binding site GCATGCA, first found in other apicomplexan parasites, Plasmodium falciparum, Theileria, and Cryptosporidium [T. gondii studies [The most abundant poridium –42. The  studies .Fig 6B). The candidate TATA box-containing motif is present at the promoters of 25.1% of T. gondii genes, comparable to the estimates of 20% of yeast promoters [Fig 6C).We found the three motifs to be frequently co-located within the same gene promoters. In 1,349 genes all three of the motifs were found in the promoter region  showing the AP2 motif at loci that open chromatin at intronic regions of the LINC02703 and PCMTD1 genes, while panel C shows the purine-rich motif at the bidirectional promoter of TENM3-AS1/ ENSG00000248266, with chromatin opening at this locus associated with increased local transcription. While these findings could certainly represent a chance occurrence of overlap of the T. gondii TF motifs at loci that are undergoing chromatin remodelling during infection purely due to host TF activities, we speculate that it is possible that T. gondii TFs access the host nucleus and influence host chromatin states directly. The data presented define candidate loci for further exploration.Finally, we asked the exploratory question whether there was any evidence that TFs from hromatin –48. We uT. gondii and the response of the infected human host cell, by studying gene expression and chromatin responses concurrently. We note that there have been elegant prior transcriptional [This is the first study that looks simultaneously at the transcriptome and chromatin organization of both the host cell and an intracellular apicomplexan parasite during infection. Our goal was to gain insights into the interaction between the activity of the well-studied parasite iptional , 50 and iptional , 51, 52,iptional , 53 of aiptional  that shoiptional , a reminT. gondii, and the mitotic gene response reflective of prior observations of enhancement of cell cycle progression following T. gondii infection [The host gene expression changes are abundant, and mirror the results of several prior studies, including the induction of immune response genes , and thenfection . In ordeT. gondii infection. It is known that T. gondii exports into the host cell the GRA24 protein, which complexes with [Fig 7 we present a model for cell signaling pathways influencing JUN and RREB1, implicating the ERK1/2 and SAPK/JUNK MAPK signaling that are known to be induced by T. gondii infection [Leishmania [Plasmodium and Theileria [T. gondii TFs directly influence host cell chromatin . This Fig 7 model is undoubtedly incomplete but serves to illustrate how these genomic assay data can be used to infer a lot more about the pathogen-host interaction than just host transcriptional outcomes alone.We were then able to add further step of inference by asking how these TFs could be altered in their functions with xes with  and induxes with . The TFsxes with , but thenfection , 63 in tishmania , Plasmodheileria  infectioT. gondii genome. We observe that stratification of tachyzoite gene expression by expression levels correlates with function. Mapping ATAC-seq peaks generally enriches the region close to the annotated transcription start site (TSS) of T. gondii genes, but we see numerous examples of open chromatin located at substantial distances from TSSs , providing a resource for improved TSS/promoter annotation in the T. gondii genome. We also find that there are ATAC-seq peaks more than 5 kb from any TSS, and show in Fig 5 how the combination of ATAC-seq and RNA-seq data allows new genes, antisense transcripts, intragenic alternative promoters and distal cis-regulatory elements to be predicted, a resource for enhancing the annotation of the T. gondii genome.The data also reveal new insights into the T. gondii reassuringly rediscovered the known AP2 TF motif [cis-regulatory loci in T. gondii. The presence of the TATA motif within the TCGGCTTATATTC sequence raises the possibility that T. gondii does, in fact, use a TATA box [Motif analysis of the loci of open chromatin in TF motif –42. We aTATA box .In summary, the combined study of host and parasite transcription and its regulation offers insights into the conflict between the host and pathogen, with some evidence for host physiology being harnessed by the pathogen for its own purposes. The ability to infer through molecular genomic studies insights into cell signaling is relatively novel and typically an underutilized potential insight from molecular genomics studies, and is made possible by focusing on TFs as the mediators of molecular genomic changes.2. T. gondii Type I tachyzoites (RHΔHxΔKu80) were also maintained at 37°C with 5% CO2 by infecting 25 cm2 flasks containing confluent HFFs every 48 hours.Cell and parasite cultures were maintained as previously described . Human F2 flasks containing freshly egressed T. gondii tachyzoites were then passaged through a 25-gauge needle three times to lyse out any remaining intracellular tachyzoites from their hosts, and the tachyzoites were spun down at 3,000 rpm for 8 minutes. 75 cm2 flasks containing confluent HFFs were then infected with these tachyzoites using a multiplicity of infection (MOI) of 3, and 24 hours after the infection the percentage of infected cells per flask was calculated. Flasks counted as at least 80% infected at this time were harvested by scraping. A flask containing HFFs to be used as an uninfected control was also harvested in parallel by scraping. The cells were pelleted by centrifugation at 1,300 rpm for 5 minutes. The cells were harvested such that both RNA and DNA could be extracted from the same flask for each biological replicate, and a total of three biological replicates of both the control and infected flasks were harvested in total for each assay.The 25 cmGenomic DNA (gDNA) was extracted from each sample as follows: 500 μL 10% SDS and 10 μL RNase A (10 mg/mL) were added to each sample followed by an incubation at 37°C for 1 hour. 50 μL of proteinase K (20 mg/mL) was then added and the samples were incubated at 55°C overnight. An equal volume of saturated phenol was then added to each tube, and the samples were mixed slowly at room temperature for 15 minutes. The samples were then spun down at 3,000 rpm for 10 minutes and the supernatant was collected. A total of 3 phenol extractions were performed, followed by 2 chloroform extractions. The samples were then pipetted into a dialysis bag and further purified at 4°C through three changes of a 20x NaCl, sodium citrate (SSC) buffer over the course of 24 hours. Dehydration was then performed by covering each sample in a pile of polyethylene glycol (PEG) for ~1 hour. The PEG was rinsed from each dialysis bag and the gDNA extracted from each sample was collected.RNA was extracted using TRIzol reagent (Invitrogen Cat. # 15596018) according to the manufacturer’s instructions as follows. One milliliter of TRizol was added to each sample and incubated at room temperature for 5 minutes. A volume of 200 μL of chloroform was added to each sample and the tubes were shaken vigorously for 15 seconds and then incubated for 2–3 minutes at room temperature. The samples were then centrifuged at 12,000 rpm for 15 minutes at 4°C, and the aqueous phase of each sample were collected. Following this, 0.5 mL of 100% isopropanol was added to the aqueous phase, and the samples were incubated for 10 minutes at room temperature, followed by centrifugation at 12,000 g for 10 minutes at 4°C. The supernatant was removed from each tube and the pellet was washed in 1 mL of 75% ethanol and centrifuged at 7,500 g for 5 minutes at 4°C. The supernatant was again removed and the pellet was air dried for 5 minutes. The RNA pellet was then resuspended in RNase-free water and incubated at 55°C for 10 minutes. Following the RNA extraction, the samples were then treated with DNase to remove contaminating gDNA, and further purified using the miRNeasy Mini Kit (QIAGEN cat# 217004). The Bioanalyzer was used to assess total RNA integrity prior to library preparation, and only samples with an RNA integrity number (RIN) greater than 8 was used for further downstream library preparation..Directional RNA-seq libraries were prepared as previously described by our lab . One micT. gondii infected HFFs were harvested at 24 hours post-infection. To prepare the nuclei, we spun 75,000 cells at 500 g for 5 minutes. Each sample was washed using 50 μL of cold 1x PBS. Samples were then centrifuged at 500 g for 5 minutes. Cells were lysed in cold lysis buffer . Immediately following lysis, nuclei were spun at 500 g for 10 minutes at 4°C. The pellet was then resuspended in the transposase reaction mix .The assay for transposase accessible chromatin (ATAC)-seq libraries were prepared as previously described . A total.The transposition reaction was carried out for 30 minutes at 37°C and the samples were then purified using a Zymo DNA Clean and Concentrator purification kit. Following the purification, we amplified the libraries with the following PCR conditions: 72°C for 5 minutes; 98°C for 30 seconds; and a total of 10 cycles of 98°C for 10 seconds; 63°C for 30 seconds; 1 minute for 72°C. Libraries were purified using Agencourt AMpure beads. Libraries were further amplified using the PCR conditions: 98°C for 30 seconds; and a total of 14 cycles of 98°C for 10 seconds; 63°C for 30 seconds and 72°C for 1 minute. The six ATAC-seq samples were multiplexed on a single lane of the Illumina Hi-Seq 2500 to obtain 100 bp paired-end reads, which resulted in a mean of 53 million reads per sample T. gondii (ME49) genome using Hisat2 (version 2.0.4) [T. gondii fractions using samtools (version 1.9) [101 bp single-end reads were trimmed to remove low quality base calls and Illumina universal adapters using Trim Galore! (version 0.6.5) with default parameters and then assessed using fastQC (version 0.11.4) and multiqc (version 1.10.1) . Trimmedn 2.0.4)  with defion 1.9) . Alignedion 1.9)  and Qualion 1.9) . Alignedion 1.9)  in unionion 1.9)  normalizion 1.9) , and vieion 1.9) .T. gondii ME49 was downloaded from ToxoDB. For T. gondii, only the infected replicates were analyzed.Differential expression analysis was performed using DESeq2 and gene set enrichment analysis performed using clusterProfiler (version 4.0.5) . A gene T. gondii (ME49) genome using bwa mem (version 0.7.17) [101 bp paired-end reads were trimmed to remove low quality base calls and Illumina universal adapters using Trim Galore! (version 0.6.5) with default parameters and then assessed using fastQC (version 0.11.4) and multiqc (version 1.10.1). Trimmed reads were aligned to a combined human (GRCh38), human decoy (GRCh38), and  0.7.17)  with def 0.7.17) , Picard  0.7.17)  were use 0.7.17)  was used 0.7.17)  using de 0.7.17) . Reprodu 0.7.17)  and Geno 0.7.17) . AlignmeT. gondii ME49 was downloaded from ToxoDB (toxodb.org). For T. gondii, only the infected replicates were analyzed.Differential accessibility analysis was performed using DESeq2 and gene set enrichment analysis was performed on annotated peaks using clusterProfiler. A gene ontology annotation for de novo motif discovery, 100 bp fragments were extracted from the middle of the top 1,000 differentially accessible upregulated or downregulated peaks and input into MEME-ChIP (version 5.4.1) [Differentially accessible peaks were annotated using ChipPeakAnno (version 3.26.4)  with parn 5.4.1)  with defn 5.4.1)  was usedn 5.4.1)  to identde novo motif discovery, 100 bp fragments were extracted from the middle of all reproducible peaks in the infected condition and input into MEME-ChIP with default parameters. To detect potential T. gondii-specific transcription factors acting on the human genome, de novo motifs were searched against the human differentially accessible peak sequences using FIMO (version 5.4.1) [Reproducible peaks in the infected condition were annotated using ChipPeakAnno with parameters adjusted to output all overlapping features within 5 kb upstream or downstream of the nearest transcription start site. For n 5.4.1) .S1 Fig(TIF)Click here for additional data file.S2 FigThe analysis shows that one infected sample (I1) clusters with the uninfected samples (U1-3). We interpreted this to indicate that the infection in this replicate was poor, and excluded this I1 sample from further analyses.(TIF)Click here for additional data file.S3 FigThe location of ATAC-seq peaks (left) and differentially-accessible regions  relative to annotated transcription start sites (TSS) in the human genome. Whereas ATAC-seq peaks are strongly enriched at TSS, only 51 (9.6%) of DARs are located within 5 kb of annotated transcription start sites (yellow shading).(TIF)Click here for additional data file.S4 FigS3 Table.We see the RELA, RREB1 and FOSB::JUNB motifs now accompanied by many other transcription factor motifs, including many NFκB family members and AP-1 targets. These are all listed in (TIF)Click here for additional data file.S5 FigT. gondii to be consistently greater than 2 million in all replicates. In (B) we illustrate how most genes in the T. gondii genome are represented consistently across replicates, also showing this quantitatively in the UpSet plot of panel (C).In (A) we show the number of RNA-seq reads from (TIF)Click here for additional data file.S6 FigT. gondii nuclear genome, whereas in (B) we see no evidence for such nucleosomal organization in reads mapping to the T. gondii apicoplast DNA.The expected nucleosomal periodicity pattern of chromatin is revealed from the insert size plots of panel (A), representing the reads aligning to the (TIF)Click here for additional data file.S7 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 TableWe present a raw counts file with data for each replicate, and the normalized counts file on which our analyses were based.(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 TableWe list the 46 candidate loci and the associated motifs.(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.


MIR528 expression in maize are still poorly explored. Here we analyzed the zma-MIR528a promoter region and found conserved transcription factor binding sites related to diverse signaling pathways, including the nitrate (TGA1/4) and auxin (AuxRE) response networks. Accumulation of both pre-miR528a and mature miR528 was up-regulated by exogenous nitrate and auxin treatments during imbibition, germination, and maize seedling establishment. Functional promoter analyses demonstrated that TGA1/4 and AuxRE sites are required for transcriptional induction by both stimuli. Overall, our findings of the nitrogen- and auxin-induced zma-MIR528a expression through cis-regulatory elements in its promoter contribute to the knowledge of miR528 regulome.In recent years, miR528, a monocot-specific miRNA, has been assigned multifaceted roles during development and stress response in several plant species. However, the transcription regulation and the molecular mechanisms controlling  MIR genes is controlled by the action of the DNA-dependent RNA polymerase II (Pol II) along with general and specific transcription factors  . The remiewed by ). A cappiewed by ,4).MIR gene expression 2, and 0.orted by .−1 mg−1.Promoter activity was determined for each construct by measuring GUS enzymatic activity with 4-Methylumbelliferyl-β-D-glucuronide (4-MUG) as substrate. After incubation and treatments, protoplasts were harvested, and protein extracts were collected following the protocol reported by . Fluores


Myh genes transcription depends on three-dimensional chromatin conformation interaction, but the mechanistic details remain to be determined.Skeletal muscles consist of fibers of differing contractility and metabolic properties, which are primarily determined by the content of myosin heavy chain (MYH) isoforms . The regulation of Myh genes using 4C-seq (circular chromosome conformation capture coupled to high-throughput sequencing). The interaction profile of Myh genes changed between fast quadriceps and slow soleus muscles. Combining chromatin immunoprecipitation-sequencing (ChIP-seq) and transposase accessible chromatin with high-throughput sequencing (ATAC-seq), we found that a 38 kb intergenic region interacting simultaneously with fast Myh genes promoters controlled the coordinated expression of fast Myh genes. We also identified four active enhancers of Myh7, and revealed that binding of MYOG and MYOD increased the activity of Myh7 enhancers.In this study, we characterized the interaction profiles of Myh genes expression.This study provides new insight into the chromatin interactions that regulate The online version contains supplementary material available at 10.1186/s12864-022-08737-9. Myh genes transcriptional regulation has not been fully elucidated.Skeletal muscle is the most abundant tissue in mammalian bodies, accounting for about 40% of body weight, and comprises a diverse group of tissues with highly diverse origins, shapes, and differential susceptibility to injuries, drugs, and diseases . In mammcis-regulatory elements (CREs) that are found in intronic, exonic, or intergenic regions [. found that the enhancers of the TWIST1 gene were critical for mesoderm development, and homozygous deletion of eTw5-7 enhancers reduced TWIST1 expression in the limb bud and caused pre-axial polydactyly [. showed that an enhancer of the Cebpe gene was necessary for granulocyte differentiation. Its deletion resulted in decreased Cebpe expression and severely blocked granulocyte differentiation [Myh genes super enhancers (SE) is responsible for the non-stochastic robust coordinated fast Myh genes expression in the hundreds of body myonuclei present in adult myofibers [Myh genes is not known.Enhancers are primary  regions , 5. Spat regions . For exantiation . Dos Sanyofibers . Recent yofibers  and genoyofibers . HoweverMyh genes between oxidative soleus and glycolytic quadriceps muscles. In addition, we identified active enhancers regulating Myh genes transcription. Our findings add to the knowledge of Myh genes regulation.Circular chromosome conformation capture coupled to high-throughput sequencing (4C-seq) and related technologies  are potent methods for studying three-dimensional nuclear organization. 4C-seq is an unbiased “one-versus-all” approach used to detect all genomic regions interacting with a specific fragment of choice . It can Myh7 and Myh2, and Myh1 and lower levels of Myh4 expression in soleus muscle compared with quadriceps muscle  from soleus and quadriceps muscles in two biological replicates. We obtained approximately 42 million filtered reads, with an average of 2.6 million reads for each 4C-seq data, and approximately 18%–68% of the total reads were distributed on the viewpoint chromosome. Seventy-five percent (12/16) of the 4C datasets conformed to the “cis/overall ratio of > 40%” criteria  were 10.2, 9.7, 9.5 and 11.0, respectively  were 5.2, 5.8, 5.4 and 4.2, respectively , consistent with the fact that Myh7 is on another chromosome  than in the fast quadriceps muscle (mainly expressing the three clustered fast genes). Consistent with this, 20.7% of interaction sites were shared among three genes in the soleus muscle, but only 11.3% were shared in the quadriceps muscle  and ATAC-seq peaks . As a result, 93% (40/43) of the candidate active enhancers contained at least one conserved element  of the potential enhancers identified were located in a 38 kb intergenic region . This region shows strong enrichment of the active histone mark, H3K27ac, chromatin accessibility, and interacts simultaneously with the fast Myh3 and Myh2, we evaluated the activity of candidate enhancers with strong interactions with promoters in quadriceps muscle, which mainly expresses Myh4. We selected nine candidate active enhancers for luciferase reporter assays. We first identified the essential promoter region for Myh4 transcription activation. Luciferase vectors driven by serial deletions of Myh4 promoter were constructed and co-transfected with pRL-TK into H293T cells. Myh4-pro3 (-639 to + 385) showed the highest relative luciferase activity compared with the other fragments (P < 0.01)  and Myh4-Qua-E5 had the most robust transcription activity (~ 6.2-fold higher compared with the empty vector)  and is mainly expressed in the soleus muscle. However, few studies have investigated enhancers in Myh7 gene transcription [Myh7 gene that were active in soleus, but not quadriceps, muscle. Visual inspection of the genomic profile showed that the active histone marker, H3K27ac, and chromatin accessibility, which are strongly associated with transcriptional activity, were strongly enriched in Myh7-expressing soleus muscle compared with Myh7 non-expressing quadriceps muscle  showed the highest relative luciferase activity compared with other fragments (P < 0.01)  luciferase activity compared with the control vectors, and Myh7-Sol-E4 had the most robust transcription activity (~ 2.8-fold higher compared with the empty vector)  under in vitro culture conditions, and this cell line is widely used to investigate the molecular biology of muscle development. Therefore, we performed 4C-seq experiments with the Myogenic regulatory factors (MRFs) are critical regulators of vertebrate skeletal muscle genes during early and adult myogenesis by binding to sequence-specific DNA elements  in the promoters of muscle genes. , 29. RecMyh7 expression.To verify the binding of MYOG and MYOD to the above enhancer regions, we analyzed available mouse myoblast cell line and primary skeletal muscle cell ChIP-seq datasets for myogenesis-specific factors (MYOG and MYOD). We also observed that MYOG and MYOD bind strongly to Myh7-Sol-E1 and Myh7-Sol-E4 in C2C12-MTs and primary skeletal muscle cells  and is mainly expressed in the quadriceps muscle, while Myh7, encoding the slow myosin heavy chain subtype (MyHCI), is mainly expressed in the soleus muscle. Consistently, differential analysis of publicly available RNA-seq data showed that the absolute log2 Fold Change of Myh1 and Myh2 was 0.6 and 1.2, respectively, indicating that the expression levels of Myh1 and Myh2 were not significantly different in quadriceps and soleus muscles. However, the absolute log2 Fold Change of Myh4 and Myh7 was 5.7 and 4.1, respectively, indicating that the expression levels of Myh4 and Myh7 were significantly different between the two muscles. Moreover, enrichment of H3K4me2  and H3Ksibility ) around  muscles .β-globin locus, common regulatory sequences called locus control regions (LCRs) dynamically interact with different promoters within the locus to activate individual globin isoforms [Myh genes promoters shows similarity to the human β-globin locus [Myh genes promoters to control the coordinated expression of fast Myh genes. Recent studies have also shown that two adjacent genes can be expressed at specific times through shared enhancers [Myh genes, consistent with previous findings. In quadriceps muscle, which predominately expresses Myh4, strong and specific interactions between the 38 kb intergenic region and the Myh4 promoter were observed. In soleus muscle, which mainly expresses the Myh7 gene, we observed approximately no difference in interaction intensity between the 38 kb intergenic region and the fast Myh genes promoters. These results indicate that the interaction between the Myh4 promoter and the 38 kb intergenic region plays an important regulatory role in quadriceps muscle, which may affect fast myofiber formation. However, we have not yet elucidated which active enhancer or combination of active enhancers could be responsible for sequential and specific Myh genes expression in fast quadriceps and slow soleus muscles. In the mouse genome, an intergenic region 50 kb upstream of the Myh2 gene and 4 kb upstream of a long intergenic noncoding RNA (lincRNA) (2310065F04Rik) was identified as linc-MYH, which coordinates fiber-type gene expression [Myh3 and Myh2 is a super-enhancer composed of multiple enhancer elements, and that the fast Myh genes promoters compete for the super-enhancer [In mammals, some genes clustered at particular genomic loci show coordinated expression to perform similar functions. Transcriptional activation of clustered genes is associated with a dynamic three-dimensional chromatin architecture at these sites . For exaisoforms . The intin locus . We founnhancers . We obsepression . Recentlenhancer . The 38 Myh7 encodes the slow myosin heavy chain subtype (MyHCI) and is highly expressed in oxidative skeletal muscles. We identified four candidate active enhancers by combining 4C-seq with ChIP-seq and ATAC-seq peaks in soleus muscle. The function of muscle regulatory regions can be highly divergent in vitro and in vivo [Myh7 between soleus and C2C12-MT cells, indicating that these enhancers may be functionally conserved and play a crucial role in regulating the Myh7 gene. Enhancers can act as integrated platforms for TF binding, leading to controlled cell/tissue-specific gene expression [ in vivo ; howeverpression . Enhancepression . The MRFpression , 45. As pression . MYOG plpression –49. Knocpression . In vivopression . TFs binpression . Our respression –56. Myogpression . They copression –60. MRFspression .Myh7 gene remains to be studied.Our results show that the luciferase activity of Myh7-Sol-E1 and Myh7-Sol-E4 constructs increased significantly after MYOG and MYOD overexpression, which indicates that the enhancer activity of Myh7-Sol-E1 and Myh7-Sol-E4 regions requires the binding of MYOG and MYOD. Whether these transcription factors are essential for the transcriptional activation of Myh genes in mice oxidative soleus and glycolytic quadriceps muscles. We identified active enhancers of Myh genes and revealed the important roles of MYOG and MYOD in regulating Myh7 gene expression.In this study, we constructed high-resolution genome-wide interaction maps of All research involving animals was conducted according to Regulations for the Administration of Affairs Concerning Experimental Animals , and approved by the animal ethical and welfare committee (AEWC) of Sichuan Agricultural University under permit No. DKY-B2019202011. This study was carried out in compliance with the ARRIVE guidelines.Thirty male C57BL/6 J mice (7–8 weeks old) were purchased from Chengdu Dossy Experimental Animals Co., Ltd . All mice were euthanized, and their quadriceps and soleus muscles were rapidly isolated and stored in liquid nitrogen for subsequent experiments.2. For the C2C12 induction of differentiation, 60–70% confluent cells were cultured in DMEM supplemented with 2% horse serum . The differentiation media were changed every two days.C2C12 and H293T cells were kindly provided by the Cell Bank of the Chinese Academy of Sciences . 293FT cells were purchased from Thermo Fisher Scientific. Cells were grown in DMEM  supplemented with 10% FBS  and 1% penicillin–streptomycin  at 37℃ under 5% COQuadriceps (Quad) and soleus (Sol) of the hind limb were dissected and were coated in optimal cutting temperature (OCT) compound, then snap-frozen in liquid nitrogen-chilled isopentane. Muscles samples were sliced into 12-μm-thick cross-sections using a cryostat at -20 °C. The tissue sections were dried at room temperature for 15 min. SDH staining was performed manually in a solution containing nitroblue tetrazolium chloride , following the manufacturer’s instructions.−ΔΔCt method after normalization to mRNA expression of the housekeeping gene Gapdh. The student’s t-test was used for assessing significance . The primer sequences are listed in Additional file Tissue total RNA was extracted using TRIzol reagent . For qRT-PCR, RNA was reverse-transcribed using HiScript III 1st Strand cDNA Synthesis Kit with gDNA wiper  following the manufacturer’s instructions. Quantitative RT-PCR (qRT-PCR) amplification was performed on a CFX96 Touch  using the ChamQ Universal SYBR qPCR Master Mix . PCR amplification parameters were 95 °C (30 s) and 40 cycles of 95 °C (10 s), 60 °C (30 s). All samples were repeated in triplicate. Relative expression levels of mRNAs were calculated using the 24C libraries preparation was performed following the previously described protocol , 16 withp-value < 0.05) were identified using r3Cseq. The raw read counts at each interaction site were used for differential analysis using the DESeq2 R package, where each interaction site is considered as a feature (or gene). The DESeq2 was used to find differentially interacting sites, defined as sites with an absolute log2 Fold Change greater than 1 and an adjusted p-value < 0.05.4C-seq analysis was performed using the pipe4C pipeline  and R-paPublically available ChIP-seq sequencing data of H3K27ac and ATAC-seq datasets for Quad and Sol were downloaded from the Gene Expression Omnibus (GEO) database under accession ID GSE123879. MYOG and MYOD ChIP-seq sequencing datasets for mouse myoblast cell line and primary skeletal muscle cell were downloaded from the GEO database under accession ID GSE49313 and GSE56077.ChIP-seq and ATAC-seq raw reads were aligned to the mouse mm10 genome using BWA (version 0.7.17). PCR duplicates of ChIP-seq and ATAC-seq data were removed with samtools and Picard (version 1.124), respectively. ChIP-seq peaks were called by macs2 (version 2.2.7.1) using the “–nomodel” parameter. Overlapping peaks were merged for replicate experiments before further analysis. The bigwig files were generated by bedGraphToBigWig (version 2.8), and were visualized in IGV.4C-seq interaction peak generated by pipe4C simultaneous enrichment with H3K27ac and ATAC-seq peaks eliminate annotated promoter and interchromosomal regions. We manually selected the position of the maximum signal (≤ 1000 bp) of ATAC-seq was defined as candidate active enhancers. The genomic coordinates of candidate active enhancers are shown in Additional file Myh4 and Myh7 promoter of a series of 5'—deletion and 3' fragments -1481/ + 385 (Myh4-pro1), -1214/ + 385 (Myh4-pro2), -639/ + 385 (Myh4-pro3), -317/ + 385 (Myh4-pro4), + 57/ + 385 (Myh4-pro5) and -1426/ + 283 (Myh7-pro1), -987/ + 283 (Myh7-pro2), -537/ + 283 (Myh7-pro3), -127/ + 283 (Myh7-pro4), + 140/ + 283 (Myh7-pro5), and candidates active enhancer sequence were amplified from mouse genomic DNA using 2 × Phanta Flash Master Mix . Each promoter fragment was ligated into a pGL3-Basic reporter vector (Promega) upstream of the luciferase gene, using KpnI and HindIII  restriction sites. Subsequently, the candidate enhancer region was cloned into a pGL3-promoter reporter vector that contains a Firefly luciferase gene driven by the promoter with the highest relative luciferase activity.The The coding sequence (CDS) of MYOD and MYOG were amplified from cDNA using 2 × Phanta Flash Master Mix . Each CDS fragment was ligated into a pEGFP-N1 vector using HindIII  restriction sites. The primer combinations used to construct each vector are shown in Additional file All constructs were verified using Sanger sequencing and cotransfected with a Renilla luciferase control plasmid into H293T cells in quadruplicate. Transfection was performed using Lipofectamine™ 3000 (Thermo Fisher Scientific) following the manufacturer’s protocol. 36 h post-transfection Firefly and Renilla luciferase activity were determined using the dual-luciferase reporter assay kit (Promega) according to manufacturer’s instructions, on a Promega GloMax® 96 Microplate Luminometer. All of the relative luciferase activities were normalized to the same protein concentration.P < 0.05 is considered statistically significant.The Student t-test (two-tailed) was performed to determine the statistical significance of the experimental results. All data were expressed as mean ± SEM. Additional file 1: Table S1. Detailed quality metrics of each 4C data.Additional file 2: Table S2. Summary of metrics in 4C-seq analysis in quadriceps and soleus.Additional file 3: Table S3. The genomic coordinates and conserved element analysis.Additional file 4: Table S4. The primer for RT-PCR.Additional file 5: Table S5. The primer for 4C-seq library construction.Additional file 6: Table S6. The PCR primers of constructed pGL3-basic and pEGFP-N1 vectors.Additional file 7: Figure S1. Scatter plot showing interactions of Myh genes in quadriceps and soleus.Additional file 8: Figure S2. Circos plots of genome-wide interaction sites of Myh genes.Additional file 9: Figure S3. The average absolute log2Fold Change of all differential interaction sites of the Myh genes.Additional file 10: Figure S4. Myh7-Sol-E1 and Myh7-Sol-E4 transcription factor enrichment analysis.Additional file 11: Figure S5. Schematic workflow of the 4C-seq procedure.Additional file 12: Figure S6. Schematic viewpoint selection of Myh genes.


PTPRK and thymocyte-selection-associated (THEMIS) genes. As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind this association using thymocyte genomic data. In four thymocyte populations, we identified 253 DNA sequence motifs underlying histone modifications. The G insertion allele of rs138300818, associated with protection from diabetes, created thymocyte motifs for multiple histone modifications and thymocyte types. In a parallel approach to identifying variants that alter transcription factor binding motifs, the same variant disrupted a predicted motif for Rfx7, which is abundantly expressed in the thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while expression quantitative trait locus and chromatin conformation data associate the insertion with lower THEMIS expression. Extending the analysis to other T1D loci further highlighted rs66733041 affecting the GATA3 transcription factor binding in the AFF3 locus. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development of early-onset T1D.We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes (T1D) diagnosed below the age of 7 years between the  The HLA class II and I genes play an important role in the development of T1D and other autoimmune diseases, with the strongest risk conveyed by the HLA class II DRB1*03-DQB1*02/DRB1*0401-DQB1*0302 genotype. In addition, over 100 other genetic loci have been associated with T1D-CD8- double-negative cells to CD4+CD8+ double-positive cells. In positive selection, thymocytes are limited to those with sufficient TCR binding to the HLA proteins. The cells with affinity to HLA class II proteins found on antigen-presenting cells differentiate towards CD4+ T-helper cells; and the ones with affinity to HLA class I proteins expressed by most cells differentiate towards CD8+ T-killer cells. Negative selection then excludes the T cells targeting the self, thus protecting from autoimmunity5. Therefore, thymus has been suggested to play a role in the development of T1D and other autoimmune diseases7. Support for this hypothesis came from a genome-wide association study (GWAS) on T1D where the susceptibility loci were enriched on active enhancer sites in the thymus, in addition to T, B, and NK cells and CD34+ stem cells8. Furthermore, a recent single-cell RNA sequencing (scRNA-seq) study on developing mouse thymus identified a modest enrichment of GWAS signals from T1D and other autoimmune diseases especially in the thymus blood cell populations9.The HLA proteins bind pathogen and self-antigen fragments, peptides, which are then recognized by highly variable T cell antigen receptors (TCR), found on the T cell surface. In the thymus, the T cell precursors, called thymocytes, are first matured from CD410. Recently it has been shown in mice that intestinal dendritic cells can engulf gut bacteria and traffic to the thymus where the bacterial antigens are presented to the T cell immune system11. Hence, expression of insulin in the human thymus is protective for T1D and now the expression of bacterial antigens early in life in the thymus adds to the body’s attempts to establish and maintain immune tolerance to insulin.The training of the immune system occurs particularly in early childhood when the body is adapting to the changing environment. The thymus itself is proportionally largest at birth, and nearly disappears in adults. Therefore, the role of the thymus in autoimmunity is likely most pronounced for childhood autoimmune diseases. For example, we have discovered in the infant gut microbiome a cross-reactive mimotope of insulin—the primary autoantigen in T1D—encoded in the commensal bacterial transketolase enzyme12. Our recent genetic analysis identified a novel locus on chromosome 6q22.33 associated with earlier diagnosis of T1D 13; the locus was associated with diabetes particularly among those diagnosed in the first 7 years12. The association is located between the thymocyte selection associated (THEMIS) and Protein tyrosine phosphatase, receptor type K (PTPRK) genes. The locus has been previously associated with other autoimmune diseases including multiple sclerosis14 and Crohn’s disease15. Colocalization analysis of the expression quantitative trait locus (eQTL) data in whole blood suggested that the AAD association co-localises with the THEMIS eQTL signal such that the minor alleles—protective for T1D—were associated with decreased THEMIS expression; and to limited extend with the PTPRK expression12. THEMIS plays a regulatory role in both positive and negative T cell selection during late thymocyte development16. Specifically in the positive selection, THEMIS inactivates the tyrosine phosphatase SHP-1 and thereby lowers the TCR signalling threshold, enabling thymocytes to be stimulated by weak agonists17. While PTPRK is widely expressed and regulates a variety of cellular processes including cell growth and differentiation, studies of the spontaneous deletion in Long Evans Cinnamon (LEC) rats indicated that also PTPRK is required for the thymocyte maturation into CD4+ positive T cells, and that the PTPRK expression in the thymus peaks in the double-negative thymocytes18.Several of the T1D-associated HLA and non-HLA variants lower the age-at-diagnosis (AAD) of T1D19. Indeed, it has been shown that DNA sequence variants can disrupt TF binding, leading to altered gene expression20. In this study, we hypothesized that the association at the recently identified 6q22.33 locus near the THEMIS gene is mediated through regulatory processes in the thymocytes. Utilizing extensive genomic data from the thymus and other tissues, combined with deep-learning-base prediction of TF binding sites, we aimed to pinpoint the likely causal variants and the functional mechanisms underlying the association  binding sites and active chromatin regions, suggesting a regulatory role for disease outcome13. Look-up of the variants in the promoter capture Hi-C (PCHiC) data for chromatin interactions indicated that many of the 58 SNPs were located in DNA fragments that interact with the PTPRK  and THEMIS (in Naïve CD8+ T cells) promoter regions  in the credible set of likely causal variants across three linkage disequilibrium (LD) blocs; the posterior probability of the underlying causal variant being within the three blocks was estimated 0.96, 0.50, and 0.42, respectively25. Genome-wide histone modification marks, including H3K4me3, H3K4me1, H3K27ac, H3K36me3, and H3K27me3, were available from the Blueprint epigenomics project26 for thymocytes that were dissected to four cell types . The number of peaks ranged from 7088 to 55,622 per experiment  and had significantly different p-value for the REF and ALT alleles (Ediff (PREF − PALT) < 5.88 × 10 – 4; Supplementary Table +αß cells, with the score for motif-sequence similarity of 38.73 (p = 2.5 × 10 – 13) for the alternative G-insertion allele, and − 17.85 (p = 0.0001) for the reference allele  < 5.88 × 10 – 4). A similar motif affected by the same rs138300818 substitution was identified in altogether 16 cell type and histone modification combinations, including all the four studied thymocyte cell types, and H3K27ac, H3K4me3 and H3K27me3 peaks. These thymocyte regulatory motifs overlapping rs138300818 did not resemble any known vertebrate TF-binding motifs evaluated with the tomtom sequence similarity analysis (E > 0.05).We then evaluated whether the 253 obtained sequence motifs for the thymocyte regulatory regions match the DNA sequences flanking the 58 credible set SNPs on the chr6q22.33 locus Fig. . Indeed,20, we utilized DeepBind,a deep learning-based method that predicts the affinity of TFs to DNA sequences29, as a parallel approach to identify the credible set SNPs that alter TF binding motifs , double positive (Q), and αβ entry T cells  = 2.32), Rfxdc2, and Rfx3, supporting the DeepBind findings , and with THEMIS .The variant rs138300818 has a minor allele frequency (MAF) of 0.155 (1000 Genomes [1000G] European population) for the G allele insertion, and it belongs to the highest 96% posterior probability group for association with AAD on the 6q22.33 locus31, 9% demonstrated allele-specific sequence similarity to thymocyte motifs (Ediff (PREF − PALT) < 5.88 × 10 − 4); however, only two variants had significant allelic difference in scores (Ediff (ScREF − ScALT) < 5.88 × 10 − 4; Table +CD4+CD8+ cells  and other tissues, but also with higher SKAP2 expression in brain  and lower expression of homeobox genes .We extended the search of overlapping thymocyte motifs to other T1D susceptibility loci. Out of 1,165 examined credible set variants from 20 susceptibility lociAFF3 locus matched a thymocyte motif . Neither of these SKAP2 or AFF3 variants had PCHiC interactions in thymocytes or in primary blood cells.Second, the reference allele of rs66733041 on tif Fig.  and bindtif Fig. , which wPTPRK and THEMIS genes32. As the thymus is likely to play a major role in early-onset autoimmune diseases, and the THEMIS gene contributes to the thymocyte selection in the thymus, we hypothesised that the underlying causal genetic variant would affect a regulatory motif active in thymocytes. Based on histone modification peak calls across the genome in four thymocyte cell types, we identified DNA sequence motifs recurring in these regulatory regions in thymocytes  cells, and Rfx7 binding sites are found in promoter regions of genes either up or down-regulated upon Rfx7 knock-out in mice33. RFX5 regulates transcription of HLA class II genes, and mutations inactivating RFX5 cause bare lymphocyte syndrome, a severe condition with primary HLA class II deficiency34. In the developing human thymus24, RFX7 was coexpressed with THEMIS in the same T cell populations , found that the major G allele was associated with higher THEMIS gene and exon 1 expression in CD4+ and CD8+ T cells ex vivo35. Through LD, this finding extends also to rs138300818. Finally, the role of the rs138300818 variant in early-onset T1D was further supported by chromatin conformation interactions with both PTPRK and THEMIS in the thymus and naïve CD8 cells.The regulatory relevance of rs138300818 was further strengthened by the detection of non-coding RNA expression in all the studied thymocyte cells overlapping rs138300818. eQTL data suggested that the RFX5/7 binding rs138300818 reference allele is associated with higher THEMIS contributes to both positive17 and negative16 thymocyte selection, whereby dysregulation of the negative selection is believed to contribute to T-cell-mediated autoimmune diseases such as T1D36. In the rat, a spontaneous frameshift mutation in Themis leading to its disruption, resulted in a reduction of CD4+ cells in the thymus, further leading to reduction of blood CD4+ T lymphocytes; the mutation was associated with the development of inflammatory bowel disease37. Whereas the role of THEMIS is evident in thymocytes, also PTPRK has been implicated in regulating the development of CD4+ T cells18 in addition to a variety of other cellular processes. Of note, PTPRK is contiguous to THEMIS in all sequenced vertebrates, and the three Themis-like genes in vertebrate genomes are located close to Ptprk paralogs38. Altogether the results suggest that the rs138300818 insertion creates a common regulatory thymocyte motif that simultaneously disrupts the RFX5/7 motif, interfering with the THEMIS (and PTPRK) gene expression, leading to protection from early-onset T1D.AFF3 locus, a 12 basepair insertion allele at rs66733041 created a thymocyte motif and TF binding motifs for Atf3 and GATA3. GATA3 protein expression is upregulated in the early double-negative thymocytes39 and the protein plays an important role throughout the T cell development40. GATA3 directly regulates many critical genes and TFs both in the thymus and in peripheral T cell lineages, while demonstrating cell-type-specific binding patterns and gene regulation41. Furthermore, GATA3 was found to regulate active and repressive histone modifications at target enhancers, supporting the relevance of our approach41. Interestingly, variants in the GATA3 gene were recently identified as a novel susceptibility locus for T1D3.We further extended the analysis to all previously fine-mapped T1D SNPs. Two out of the 1,165 studied T1D-associated variants significantly affected a thymocyte motif. In the diff (ScREF − ScALT) < 5.88 × 10 − 4) were indel variants. Indeed, indels have been reported to have an important role in modifying TF binding sites, and thus, regulating gene expression42. When considering only the less stringent allelic difference in p-values (Ediff (PREF − PALT) < 5.88 × 10 − 4), many more variants demonstrated allelic difference. As many disease-associated non-indel variants have been suggested to alter TF binding sites43, the comparative score distribution employed in this work may be too stringent and less sensitive to non-indel variants and capture only the most striking differences.All the three variants with a significant allelic difference for thymocyte motif similarity  in thymocytes, recent thymic emigrants, or other relevant cells.The main limitation of this work is the lack of functional work to confirm the findings. Nevertheless, it is of note that both our parallel, independent approaches to search for SNPs altering either thymocyte or TF binding motifs point to the same rs138300818 variant. Furthermore, existing functional work shows that a variant in LD with rs138300818 is associated with 28. While the lead findings at rs138300818 and in AFF3 (rs66733041) were found for histone modification peaks, rs142852921 in SKAP2 reached a significant difference in score only for the pseudostate 10, “distal active promoter”.Another limitation of this work is the sparsity of the thymocyte data. As only a few histone modification peaks were measured for each of the four individuals, and different histone modification combinations were available for each, it was not possible to define chromatin states within each individual. This was overcome by combining histone modification peaks across different biological replicates into pseudo-chromatin states, following a previously reported annotation, e.g., combining H3K4me1 and H3K27Ac signals for pseudostate 7, i.e., active enhancersPTPRK-THEMIS locus was linked to thymocytes through chromatin conformation data from the thymus, and as the RFX7 was highly expressed in the thymus. While we hypothesized that the causal genetic variant in the 6q22.33 locus would affect a regulatory motif active in the thymocytes, our genome-wide search for such motifs may have missed some more specific regulatory motifs only found in the 6q22.33 region.It should be noted that many of the identified thymocyte motifs were similar across the thymocyte cell types and histone modification peaks, which are not necessarily specific to thymocytes. This was reflected in the thymocyte motif comparison with known TF binding motifs, revealing 11 TFs, out of which most are expressed in nearly all tissues. Interestingly, SP3 has the highest expression in the thymus across the FANTOM5 tissues, supporting its relevance in thymocytes. Furthermore, the rs138300818 in the To conclude, the use of two parallel approaches and versatile biological data on thymocytes suggests that the rs138300818 insertion protects from early-onset T1D through affecting regulatory elements in thymocytes, including RFX5/7 binding. Functional studies are needed to confirm our findings.25. Resulting thymocyte motifs were integrated with the 58 credible set variants on the 6q22.33 locus, and 1,165 other SNPs for T1D, to identify SNPs that disrupt DNA motifs identified in the thymocyte epigenetic data. In addition, we applied a deep-learning method to identify credible set variants that alter TF binding motifs  for four individuals. Available peaks included H3K4 trimethylation (H3K4me3), H3K4 monomethylation (H3K4me1), H3K27 acetylation (H3K27ac), H3K36 trimethylation (H3K36me3), and H3K27 trimethylation (H3K27me3). Samples were dissected to CD3 − CD4+CD8+ thymocytes, CD3+CD4+CD8+ thymocytes, CD4+αβ thymocytes, and CD8+αβ thymocytes. Total RNA-seq data was available and downloaded for these cell types for one individual.Genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) data on histone modification marks were available from the Blueprint epigenomics projecthttps://genome.ucsc.edu/cgi-bin/hgLiftOver) when necessary.Human reference genome DNA sequence primary assembly and exon annotations were downloaded from Ensembl (ftp.ensembl.org/pub/release-92/) for human genome build GRCh38, release 92. DNA positions were updated from human genome build GRCh37 to GRCh38 using the UCSC liftover tool -transformed lymphoblastoid cell line GM1287844, and for pancreatic islets22 using the CHiCP browser45. Interactions with CHiCAGO score > 5 were considered high-confidence21. eQTL associations were queried in the GTEX v8  and eQTLgen whole blood cis-eQTL databases46. We queried RNA expression data for the genes of interest from Human Protein Atlas (HPA) version 18, for HPA, Genotype-Tissue Expression (GTEx), and Functional Annotation of Mammalian Genomes 5 (FANTOM5) transcriptome data sets.3D chromatin conformation capture data based on Promoter capture Hi-C (PCHiC) were obtained for 16 primary blood cell types and thymus47 and intersect tool were used for processing the histone modification peaks. Histone modification peaks were limited to those with peak fold change ≥ 3 and q-value < 0.0001. To enrich the search for active DNA sites, we limited the ChIP-seq peaks to those with total RNA-seq overlapping the peak, defined as mean RNA-seq depth ≥ 0.001 over the peak length, using UCSC bigWigSummary and bigWigAverageOverBed utilities (http://hgdownload.soe.ucsc.edu/admin/exe/). Finally, histone modification peaks of the same cell type, but from different biological repeats , were pooled together , pseudostate 9 (H3K4me1 and H3K27Ac), pseudostate 10 , pseudostate 11 (H3K4me3 and H3K4me1), and pseudostate 12 (H3K4me3 and H3K27Ac), available for a subset of the thymocytes , targeting 20 motifs. As by default, 600 sequences were randomly selected for initial motif discovery. Significant motifs were defined as E-value < 0.01/17 cell type and histone mark combinations/20 motifs = 2.94 × 10 − 5. The resulting motifs were compared to the in vivo and in silico vertebrate DNA motifs  with tomtom tool27; significant similarity was defined as q-value < 0.01.Fasta sequences were extracted for each peak with the bedtools getfasta tool. Motif discovery was performed using MEME Suite49. Sequence overlap with the discovered thymocyte motifs was studied with the FIMO tool from the MEME suite27. Significant motif overlap was considered as PREF or PALT < 0.01/253 significant thymocyte motifs (from MEME)/58 SNPs = 6.81 × 10 − 7. The thymocyte motif overlap was calculated similarly for SNPs in the credible sets associated with T1D31. Significant motif overlap was considered as PREF or PALT < 0.01/253 significant thymocyte motifs/1,165 SNPs = 3.39 × 10 − 8.FASTA sequences were extracted for ± 30 bp around the 58 credible set SNPs for both the reference and alternative allele from Ensembl (build GRCh38) using R jsonlite package v.1.5diff (PREF − PALT) for the difference in p-value between the REF and ALT alleles by calculating a z-score as /, and converting the z-score into an E-value  assuming two-tailed normal distribution. Ediff (ScREF − ScALT) for the difference in score between the REF and ALT alleles was calculated in a similar manner. These scores are conservative, as only those SNP—motif pairs are considered where at least one of the SNP alleles had nominally significant (p < 0.05) similarity with a motif sequence. Distributions were calculated separately for each of the 17 cell-type—histone modification combinations, and Ediff (PREF − PALT) and Ediff (ScREF − ScALT) < 0.01/17 = 5.88 × 10 − 4 were considered significant.We calculated an E-value E29 to assess allele-specific TF binding for the 58 SNPs in the credible set on the the 6q22.33 locus, as well as the two T1D SNPs affecting thymocyte motifs, comparing the 30 bp sequences flanking the SNPs. DeepBind was run using default parameters and all non-deprecated TFs delivered with the distribution (N = 927).We employed DeepBind v0.1130 implemented in http://trap.molgen.mpg.de/cgi-bin/trap_two_seq_form.cgi for the same SNP sequeences. We used all JASPAR motifs contrasted to the human promoter background model, adjusted with the Benjamini–Hochberg method.We additionally conducted transcription factor affinity prediction (TRAP) with sTRAP algorithmSupplementary Information.


A aterosclerose é a causa mais comum de doença cardiovascular em todo o mundo, ela está associada a uma alta incidência de eventos clínicos. O acúmulo de evidências elucidou que os RNAs longos não codificantes (LncRNAs) são uma nova classe de transcritos com papéis críticos nos processos fisiopatológicos da aterosclerose. Nesta revisão, resumimos o progresso recente dos LncRNAs no desenvolvimento da aterosclerose. Descrevemos principalmente os diversos mecanismos regulatórios dos LncRNAs nos níveis transcricionais e pós-transcricionais. Este estudo pode fornecer informações úteis sobre os LncRNAs como alvos terapêuticos ou biomarcadores para o tratamento da aterosclerose. Nos últimos anos, estudos têm revelado o importante papel dos RNAs não codificantes de proteínas nos processos fisiopatológicos de várias doenças.7 De acordo com o comprimento, os RNAs não codificantes (ncRNAs) podem ser divididos em RNAs não codificantes longos  e RNAs não codificantes pequenos .8 Em muitas pesquisas, algumas funções regulatórias e efeitos biológicos de pequenos ncRNAs foram demonstrados.11 A função de muitos LncRNAs é desconhecida, mas um número crescente de LncRNAs foi caracterizado.No genoma de mamífero, os RNAs codificantes de proteínas são apenas <3%.8 Os LncRNAs estão localizados principalmente no núcleo e no citoplasma.12 No citoplasma, os LncRNAs podem se ligar aos ribossomos13 ou originar-se do genoma mitocondrial.14 Os primeiros relatórios mostram que muitos LncRNAs não podem codificar proteínas porque não possuem fases de leitura aberta (ORFs) ou contêm poucas ORFs. Mas evidências emergentes sugerem que alguns LncRNAs contêm pequenas ORFs que codificam pequenas proteínas ou micropeptídeos, que são considerados reguladores-chave em vários processos biológicos.16 Estudos demonstram que os LncRNAs desempenham papéis críticos na função das células endoteliais e do músculo liso vascular (VSMC), na ativação de macrófagos, no metabolismo lipídico e a resposta inflamatória.18 Nesta revisão, discutimos principalmente a regulação dos LncRNAs que estão envolvidos no processo fisiopatológico da aterosclerose em níveis transcricionais e pós-transcricionais.A biossíntese do lncRNA é semelhante à do mRNA. Os LncRNAs são transcritos pela RNA polimerase II, mas não possuem fases de leitura abertas e estão em uma expressão mais baixa do que os genes codificantes de proteínas.A patogênese da aterosclerose é acompanhada por disfunção celular, como proliferação, apoptose e migração. O resultado é a formação de células espumosas e o acúmulo de placas.20 Os critérios de classificação também incluem as várias funções na regulação do gene local: cis- (regulação da expressão de genes proximais) e trans- (regulação da expressão de genes distantes).21 Além disso, os transcritos de LncRNAs também podem ser categorizados em lineares ou circulares.22De acordo com a correlação entre a localização genômica e genes codificadores de proteínas, os LncRNAs podem ser divididos em (1) LncRNAs intergênicos (LincRNAs) que expressam genes codificadores de proteínas como uma unidade independente. (2) LncRNAs intrônicos que derivam dos íntrons de genes codificadores de proteínas. (3) LncRNAs anti-senso transcritos da direção oposta dos genes que codificam proteínas. (4) LncRNAs senso que se sobrepõem aos exons de genes que codificam proteínas na mesma fita. (5) potenciadores que se originam no potenciador de genes que codificam proteínas. (6) LncRNAs bidirecionais que são transcritos a partir dos promotores bidirecionais divergentes.23O mecanismo de funcionamento dos LncRNAs não foi completamente elucidado, mas pode ser classificado aproximadamente em vários grupos: 1. a regulação da transcrição está incorporada na interferência da transcrição, remodelação da cromatina e promoção da transcrição; 2. níveis pós-transcricionais se manifestam no controle da tradução da regulação do splicing de mRNAs e até mesmo como esponjas para miRNAs; 3. Outros contêm localização de proteínas, replicação de telômeros e interferência de RNA etc. Além disso, seus mecanismos de direcionamento para regular a expressão de genes são resumidos como o seguinte: sinais, iscas, guias e estruturas.24 Os LncRNAs de ação trans podem interagir com RNA polimerases e fatores de alongamento da transcrição ou servir como um arcabouço para complexos de modificação da cromatina para regular os genes distantes.25Os LncRNAs podem exercer sua regulação transcricional por meio de mecanismos de ação cis e ação trans. . Os LncR26 A região é adjacente a um LincRNA denominado RNA não codificador anti-senso no lócus INK4 .27 Holdt LM et al.,28 revelaram que a expressão de ANRIL estava correlacionada com a gravidade da aterosclerose por afetar a transcrição dos mRNAs, e o ANRIL também foi detectado em placas ateroscleróticas em seu estudo.28O estudo Wellcome Trust Case Control Consortium (WTCCC) e os estudos de associação do genoma completo descobriram que uma região no cromossomo 9p21 (Chr9p21) estava fortemente associada à doença arterial coronariana.27 O complexo polycomb repressivo-1 (PRC-1) e o complexo polycomb repressivo-2 (PRC-2) são dois tipos de proteínas de grupo polycomb envolvidas na manutenção do estado da cromatina.29 Suas subunidades CBX7 e SUZ12 se ligam ao ANRIL separadamente para silenciar o lócus CDKN2A/B através da trimetilação de H3 lisina27 (K27H3).31 Ainda, a repressão de CDKN2A/B pode estar relacionada à proliferação celular e apoptose no processo de aterosclerose.32Dois genes codificadores de proteínas, inibidores de quinase dependentes de ciclina  e a estrutura de leitura alternativa (ARF) no cromossomo 9p21, estão ligados a ANRIL inextricavelmente, os quais são supressores de tumor.28 descobriram que ANRIL estava em posição de exercer uma função reguladora na expressão de genes distantes em trans. O elemento Alu, que marca o promotor dos genes trans-regulados de ANRIL, é decisivo para a trans-regulação linear de ANRIL. As proteínas PcG, desencadeadas pela ligação com ANRIL, eram altamente abundantes a jusante dos motivos Alu.33 O recrutamento de proteínas PcG poderia regular a expressão dos genes alvo  e atenuar funções pró-aterogênicas mediadas por ANRIL, como células adesão, proliferação e apoptose.33 Além disso, ANRIL desempenha um papel fundamental nos processos inflamatórios através da via TNF-α/NF-kB-ANRIL/YY1-IL6/8. As proteínas associadas a PRC Yin Yang 1(YY1), um fator de transcrição, formam um complexo funcional com ANRIL.33 O complexo ANRIL-YYI se liga aos loci promotores de IL6/8 e estimula seu recrutamento na sinalização de TNF-α/NF-κB, levando à inflamação vascular.34Holdt et al.,35 A expressão de MALAT1 é regulada para baixo em placas ateroscleróticas em comparação com artérias não ateroscleróticas.36 Michalik et al.,37 descobriram que o silenciamento de MALAT1 inibiu a mudança de um estado promigratório para um proliferativo das células endoteliais, resultando na redução do crescimento de vasos.37 E MALAT1 também atua como um andaime molecular para interagir com o Polycomb 2 não metilado (Pc2); a expressão de Pc2 promove a SUMOilação de E2F1 e regula modificações de histonas para aumentar a proliferação celular.38MALAT1, localizado no cromossomo 11q13, é descrito pela primeira vez como lncRNA associado a metástases de tumores de pulmão.39 MALAT1 pode estar envolvido na resposta LPS inflamatória induzida via sinalização LPS/TLR4/NF-κB. MALAT1 interage com as subunidades p65/p50 de NF-κB, inibindo a ligação de p65/p50 a promotores alvo, como TNF-α e IL-6, atenuando uma inflamação excessiva.40Em um experimento de controle, Gast et al.,39 observaram que os níveis séricos de TNF, IL-6 e IFN-γ estavam aumentados nos camundongos ApoE -/- deficientes em MALAT1, causando disfunção imunológica e aterosclerose agravada.41 CD36, um receptor eliminador de classe B, é necessário para a absorção de lipídios de ox-LDL.42 A superexpressão de MALAT1 induz o recrutamento de β-catenina no promotor CD36 para aumentar a transcrição de CD36, promovendo a captação de lipídios em macrófagos e acelerando a formação de células espumosas em placas ateroscleróticas.41No metabolismo lipídico, MALAT1 pode ser regulado positivamente em macrófagos durante a estimulação ox-LDL.43 Além disso, ASI et al.,44 descobriram que a expressão de NEAT1 foi regulada positivamente em células do músculo liso vascular (VSMCs) após lesão vascular in vivo e in vitro, levando a um estado de cromatina inativa em genes específicos de SM por meio da ligação com o modificador de cromatina WDR5. A repressão da expressão de genes específicos de SM mudou VSMCs para fenótipo proliferativo, promovendo a proliferação e migração de VSMCs e, assim, a formação de neoíntima.44NEAT1, um transcrito adjacente de MALAT1, pode aumentar a formação de paraspeckles em oxLDL-macrófago induzido, que suprime a captação de lipídios ligando-se ao mRNA de CD36 para inibir a expressão de CD36 e estimula a resposta inflamatória por meio da fosforilação de p65 para promover a secreção de TNFα.45A expressão de lincRNA-p21 foi regulada negativamente nas placas ateroscleróticas. O LincRNA-p21 diminuiu a interação MDM2/p53 e aumentou a interação p300/p53 para facilitar a atividade transcricional de p53, levando à repressão da formação neointimal, a inibição da proliferação celular e o aumento da apoptose em VSMCs e células macrófagos mononucleares in vitro e vivo.46 A expressão ectópica de LncRNA-HOTTIP, induzida por TNF-α ou fator de crescimento derivado de plaquetas (PDGFBB), aumenta a expressão de marcadores proliferativos ciclina D1 e PCNA através da via Wnt/β-catenina, subsequentemente estimulando a proliferação e migração de células endoteliais.47 A O-GlcNAcilação modula a ativação do promotor HAS2-AS1, o transcrito anti-senso natural HAS2-AS1 pode regular a transcrição de HAS2 em cis através da remodelação da estrutura da cromatina,48 HAS2 pode estar relacionado à proliferação de VSMCs,50 recrutamento de macrófagos,50 migração de VSMCs e formação de neoíntima,52 e resposta inflamatória.52 A expressão de LncRNA RP11-714G18.1 na placa aterosclerótica é baixa. Ainda assim, pode regular positivamente a expressão do gene LRP2BP próximo para prejudicar a migração celular, suprimir a adesão de ECs aos monócitos, reduzir a neoangiogênese, diminuir a apoptose de VSMCs e promover a produção de óxido nítrico. Além disso, o LRP2BP sérico foi positivamente relacionado ao colesterol de lipoproteína de alta densidade.53Além disso, alguns outros LncRNAs estão envolvidos no processo AS no nível transcricional, mas as descrições são limitadas. A superexpressão de LncRNA-MeXis em macrófagos pode facilitar a reversão do transporte de colesterol pelos macrófagos através do eixo LXR-MeXis-Abca1, sugerindo que LncRNA-MeXis desempenha um papel protetor no desenvolvimento de aterosclerose.54 LEENE pode melhorar a função endotelial aumentando a transcrição inicial do RNA da eNOS.55 Lethe Lin et al.,56 atua como uma isca lncRNA para interagir com a subunidade RelA do NF-κB e inibe a ligação de RelA ao DNA de genes alvo, como IL6, SOD2, IL8, atenuando a resposta inflamatória.56 LncRNA-TSLP induz a transcrição de HOTAIR através da via PI3K/AKT-IRF1, promovendo a proliferação e migração de células endoteliais na aterosclerose.57 Além disso, a TSLP induzida por ox-LDL pode se ligar a células dendríticas (DCs) para ativar a inflamação Th58 que está relacionado à gravidade e progressão da AS.59HOXC-AS1 pode suprimir o acúmulo de colesterol em macrófagos por meio da promoção da expressão de HOXC6 em níveis de mRNA.24Os LncRNAs atuam principalmente como RNAs endógenos competidores (ceRNAs) ou miRNAs “esponja” interagindo com miRNAs no processo de aterosclerose no nível de regulação pós-transcricional.  Além dis61 descobriram que MALAT1 “esponja” o miR-503 para reduzir a liberação de citocinas pró-inflamatórias, atenuando a inflamação da placa.61 Além disso, o supressor de sinalização de citocina 1 (SOCS1) é a proteína alvo do miR-155 que regula negativamente a sinalização do transdutor de sinal da quinase ativada de Janus (JAK) e do ativador da transcrição (STAT). MALAT1 poderia diminuir a regulação de miR-155 e aumentar a expressão de SOCS1 para aliviar a inflamação e apoptose na aterosclerose.62 Assim, MALAT1 pode desempenhar um papel protetor por meio da interação com miRNAs na patogênese da aterosclerose.MALAT1 atua como ceRNA na lesão de células induzidas por ox-LDL e desempenha um papel protetor na doença aterosclerose. MALAT1 poderia competir com miR-22-3p por RNA endógeno e regular positivamente os genes alvo CXCR2 e AKT de miR-22-3p para inibir a apoptose de células endoteliais e promover a migração de ECs e angiogênese.60 Cremer S et al.,63 e inibe a adipogênese ao direcionar PPAR-g.64 O silenciamento de H19 aumenta significativamente a expressão de miR-130b, que melhora a inflamação e a síntese de lipídios em células Raw264.7 tratadas com LDL-ox.65 O H19 pode acelerar a proliferação e impedir a apoptose em VSMCs estimulados por LDL-ox, suprimindo diretamente a expressão de miR-148b e aumentando a expressão do gene WNT1 do miR-148b alvo.66A expressão de lncRNA H19 foi regulada positivamente em macrófagos tratados com LDL-ox. MiR-130b regula a resposta inflamatória diminuindo os níveis translacionais de TNF-α, Sp1, NF-κB com estimulação lipídica67 O MIAT interfere nas vias do miR-149-5p para aumentar o nível de CD47 em macrófagos, promovendo a vulnerabilidade da placa.68 A formação do eixo MIAT/miR-181b/STAT3 desempenha um papel crítico nas células do músculo liso vascular da aorta humana induzidas por ox-LDL (HA-VSMCs) e células mononucleares humanas (U937). O MIAT regula para cima o transdutor de sinal e o ativador do nível da proteína de transcrição 3 (STAT3) por meio do sequestro de miR-181b, promovendo subsequentemente a proliferação, facilitando a parada do ciclo celular e inibindo a apoptose em células HA-VSMCs e U937.69O LncRNA-MIAT pode estar envolvido na progressão da placa aterosclerótica. O MIAT é expresso principalmente nos macrófagos de placas ateroscleróticas avançadas. Com o tratamento ox-LDL, a expressão de MIAT é regulada positivamente. A molécula anti-fagocítica CD47, um gene alvo de miR-149-5p, está relacionada à depuração de células apoptóticas e núcleos necróticos70 descobriram que NEAT1 foi significativamente regulado positivamente na presença de ox-LDL e serviu como uma esponja para reprimir a expressão de miR-342-3p, aumentando o nível sérico de IL-6, IL-1β, COX-2 e colesterol total levando para acelerar o processo de inflamação e a formação de células espumosas.70 LncRNA-TUG1 poderia regular negativamente a expressão de miR-26a e aumentar o mRNA e o nível de proteína de TRPC6 para facilitar a apoptose das células endoteliais.71 Zhang et al.,72 revelou que o TUG1 esponjou miR-133a e regulou positivamente a expressão do fator de crescimento de fibroblastos 1 (FGF1), resultando em aumento da hiperlipidemia e resposta inflamatória excessiva agravou a lesão aterosclerótica.72NEAT1 também estava envolvido no processo aterosclerótico como ceRNA, exceto para a remodelação da cromatina no nível transcricional. Wang et al.,73 LincRNA-p21 funciona como ceRNA para promover a apoptose de ECs e induz a progressão do ciclo celular ao direcionar o miR-130b.74 LncRNA-GAS5 regula negativamente a expressão de miR-21 para aumentar a expressão de morte celular programada 4 (PDCD4), suprimindo a proliferação de ECs e desencadeando a apoptose de ECs.75Além disso, mais e mais estudos demonstraram que muitos LncRNAs relacionados à aterosclerose desempenham um papel crucial na patogênese da AS, interagindo com miRNAs no nível pós-transcricional. LINC00305 atua como uma esponja endógena para miR-136 e inibe a expressão de miR-136 para suprimir a proliferação de células endoteliais vasculares e aumentar a apoptose.24 tal como localização de partículas de RNP em plantas leguminosas, extensão do telômero durante a replicação do DNA em eucariotos,76 reduzindo o siRNA gerado por Dicer e afetando a expressão de genes regulados por Dicer.77 No entanto seu mecanismo molecular subjacente relacionado ao desenvolvimento de aterosclerose permanece desconhecido.Os LncRNAs podem funcionar através da localização de proteínas, replicação de telômeros e interferência de RNA em alguns processos,Tomados em conjunto, os LncRNAs podem estar envolvidos em vários processos associados à aterosclerose, incluindo resposta inflamatória, metabolismo lipídico e função celular. Eles regulam a patologia da aterosclerose em níveis epigenéticos, transcricionais e pós-transcricionais, como remodelamento da cromatina, promoção da transcrição e competição endógena por miRNAs. Portanto, os LncRNAs podem servir como novos marcadores diagnósticos e alvos terapêuticos promissores para aterosclerose e doenças vasculares. Além disso, todos esses papéis possíveis nos processos fisiopatológicos abriram espaços para decifrar a função e o mecanismo dos LncRNAs em doenças cardiovasculares e outras doenças, como tumores, doenças renais e nervosas. 1 Atherosclerosis (AS), the principal driver of CVDs worldwide, is a lipid-driven chronic inflammatory process with endothelial dysfunction, foam cells formation and final plaque buildup.2 This process is accompanied by cells proliferation, apoptosis, and the release of pro-inflammatory factors3 (4Cardiovascular diseases (CVDs) are regarded as a global health problem that accounts for 17.9 million deaths every year.factors3 . These c5 That fraction of the coding gene makes, therefore, hard to explain the complex regulatory mechanism of the organism. In recent years, accumulating studies have revealed the important role of non-coding protein RNAs in the pathophysiological processes of various diseases.7 According to the length, the non-coding RNAs (ncRNAs) can be divided into long non-coding RNA  and small non-coding RNA .8 In many researches, some small ncRNAs’ regulatory functions and biological effects have been demonstrated.11 The function of many lncRNAs is unknown, but an increasing number of lncRNAs have been characterized.In the mammalian genome, the encoded protein RNAs are only < 3%.8 LncRNAs are mainly located within the nucleus and cytoplasm.12 In the cytoplasm, lncRNAs can bind with ribosomes13 or originate from the mitochondrial genome.14 Early reports show that many lncRNAs can’t encode proteins because they lack open reading frames (ORFs) or contain few ORFs. But emerging evidence suggests that some lncRNAs contain small ORFs encoding small proteins or micropeptides, which are regarded as key regulators in various biological processes.16 Studies demonstrate that lncRNAs play critical roles in the function of endothelial and vascular smooth muscle cells (VSMC), macrophage activation, lipid metabolism and inflammatory response.18 In this review, we mainly discuss the regulation of lncRNAs are involved in the pathophysiologic process of atherosclerosis at transcriptional and post-transcriptional levels.The biosynthesis of lncRNA is similar to that of mRNA. LncRNAs are transcribed by RNA polymerase II but lack open reading frames, and they are in a lower expression than protein-coding genes.The pathogenesis of atherosclerosis is accompanied by cell dysfunction, such as proliferation, apoptosis, and migration. The result is foam cells formation and plaque buildup.20 The criteria of classification also include the various functions in local gene regulation: cis-  and trans- (regulating distant genes expression).21 Besides, lncRNAs transcripts can also be categorized into linear or circular.22According to the correlation between the genomic location and protein-coding genes, lncRNAs can be divided into (1) intergenic lncRNAs (lincRNAs) that express protein-coding genes as an independent unit. (2) intronic lncRNAs that derive from the introns of protein-coding genes. (3) antisense lncRNAs transcribed from the opposite direction of protein-coding genes. (4) sense lncRNAs that overlap with exons of protein-coding genes on the same strand. (5) enhancers that originate in the enhancer of protein-coding genes. (6) bidirectional lncRNAs that are transcribed from the divergent bidirectional promoters.23The mechanism of lncRNAs functioning has not been completely elucidated, but it can be classified roughly into several groups: 1. transcriptional regulation is embodied in transcriptional interference, chromatin remodeling and promotion of transcription; 2. post-transcriptional levels manifest in mRNAs splicing regulation translational control and even as sponges for miRNAs; 3. Others contain protein localization, telomere replication, and RNA interference, etc. Furthermore, their targeting mechanisms for regulating gene expression are summarized as the following: signals, decoys, guides and scaffolds.24 Trans-acting lncRNAs can interact with RNA polymerases and transcription elongation factors or serve as a scaffold for chromatin modification complexes to regulate the distant genes.25LncRNAs can exert their transcriptional regulation through cis-acting and trans-acting mechanisms.  LncRNAs 26 The region is adjacent to a lincRNA named antisense non-coding RNA in the INK4 locus .27 Holdt LM et al.28 had revealed that ANRIL expression was correlated with atherosclerosis severity by affecting mRNAs’ transcription, and the ANRIL was also detected in atherosclerotic plaques in their study.28The Wellcome Trust Case Control Consortium (WTCCC) study and the genome-wide association studies found that a region on chromosome 9p21 (Chr9p21) was strongly associated with coronary artery disease strongly.27 The polycomb repressive complex-1 (PRC-1) and polycomb repressive complex-2 (PRC-2) are two kinds of polycomb group proteins involved in maintaining chromatin state.29 Their subunits CBX7 and SUZ12 bind ANRIL separately to silence CDKN2A/B locus through H3 lysine27 (K27H3) trimethylation.31 Yet, the repression of CDKN2A/B may be related to cell proliferation and apoptosis in the atherosclerosis process.32Two protein-coding genes, cyclin-dependent kinase inhibitors and the alternative reading frame (ARF) on chromosome 9p21, are tied to ANRIL inextricably, which are tumor suppressors.28 found that ANRIL was in a position to exert a regulatory function in distant gene expression in trans. Alu element, marking the promoter of the ANRIL trans-regulated genes, is decisive for linear ANRIL trans-regulation. PcG proteins, triggered by binding with ANRIL, were highly abundant downstream of the Alu motifs.33 The recruitment of PcG proteins could regulate the expression of the target genes  and attenuate ANRIL-mediated pro-atherogenic functions, such as cell adhesion, proliferation, and apoptosis.33 Furthermore, ANRIL plays a pivotal role in the inflammatory processes through TNF-α/NF-kB-ANRIL/YY1-IL6/8 pathway. PRC-associated proteins Yin Yang 1 (YY1), a transcriptional factor, form a functional complex with ANRIL.33 ANRIL-YYI complex binds to IL6/8 promoter loci and stimulates their recruitment in the TNF-α/NF-κB signaling, leading to vascular inflammation.34Holdt et al.35 MALAT1 expression is downregulated in atherosclerotic plaques in comparison to non-atherosclerotic arteries.36 Michalik et al.37 found that silencing of MALAT1 inhibited a switch from a promigratory to a proliferative state of the endothelial cells, resulting in the reduction of vessel growth.37 And MALAT1 also acts as a molecular scaffold to interact with unmethylated Polycomb 2 (Pc2); the expression of Pc2 promotes E2F1 SUMOylation and regulates histone modifications to increase cell proliferation.38MALAT1, located on chromosome 11q13, is first described as lncRNA associated with metastasis of lung tumors.39 observed that the serum levels of TNF, IL-6, and IFN-γ were increased in the MALAT1-deficient ApoE-/- mice, causing immune dysfunction and aggravated atherosclerosis.39 MALAT1 may be involved in the LPS‐induced inflammatory response via LPS/TLR4/NF-κB signaling. MALAT1 interacts with NF-κB subunits p65/p50, inhibiting p65/p50 binding to target promoters such as TNF-α and IL-6, then attenuating an excessive inflammation.40In a control experiment, Gast et al.41 CD36, a class B scavenger receptor, is required for lipid uptake of ox-LDL.42 MALAT1 overexpression induces the recruitment of β-catenin on the CD36 promoter to enhance CD36 transcription, promoting lipid uptake in macrophages and accelerating the foam cell formation in atherosclerotic plaques.41In lipid metabolism, MALAT1 may be upregulated in macrophages during ox-LDL stimulation.43 Besides, Ahmed ASI et al.44 found that NEAT1 expression was upregulated in vascular smooth muscle cells (VSMCs) after vascular injury in vivo and in vitro, leading to an inactive chromatin state in SM-specific genes through binding with the chromatin modifier WDR5. The repression of SM-specific genes expression switched VSMCs to proliferative phenotype, promoting VSMCs proliferation and migration and thereby neointima formation.44NEAT1, an adjacent transcript of MALAT1, can enhance the paraspeckles formation in oxLDL-induced macrophage, which suppresses lipid uptake by binding CD36 mRNA to inhibit CD36 expression and stimulates inflammatory response via phosphorylating p65 to promote TNF-α secretion.45The expression of lincRNA-p21 was downregulated in the atherosclerotic plaques. LincRNA-p21 decreased MDM2/p53 interaction and increased p300/p53 interaction to facilitate the transcriptional activity of p53, leading to the repression of neointimal formation, the inhibition of cell proliferation and the enhancement of apoptosis in VSMCs and mononuclear macrophage cells in vitro and vivo.46 Ectopic expression of lncRNA-HOTTIP, induced by TNF-α or platelet-derived growth factor (PDGFBB), increases proliferative markers cyclin D1 and PCNA expression through the Wnt/β-catenin pathway, subsequently prompting the endothelial cell proliferation and migration.47 The O-GlcNAcylation modulates HAS2-AS1 promoter activation, HAS2-AS1 natural antisense transcript can regulate HAS2 transcription in cis through remodeling chromatin structure,48 HAS2 may be related to VSMCs proliferation,50 macrophages recruitment,50 VSMCs migration and neointima formation,52 inflammatory response.52 The expression of lncRNA RP11-714G18.1 in atherosclerotic plaque is low. Still, it can upregulate nearby gene LRP2BP expression to impair cell migration, suppress the adhesion of ECs to monocytes, reduce the neoangiogenesis, decrease VSMCs apoptosis and promote nitric oxide production. Furthermore, the serum LRP2BP was positively related to high-density lipoprotein cholesterol.53Also, some other lncRNAs are involved in the AS process at the transcriptional level, but the descriptions are limited. The overexpression of lncRNA-MeXis in macrophages may facilitate macrophage reversing cholesterol transport via the LXR-MeXis-Abca1 axis, suggesting that lncRNA-MeXis plays a protective role in the development of atherosclerosis.54 LEENE can improve endothelial function by enhancing eNOS initial RNA transcription.55 Lethe Lin et al.56 acts as a decoy lncRNA to interact with the NF-κB subunit RelA and inhibits RelA binding to target genes DNA, such as IL6, SOD2, IL8, attenuating the inflammatory response.56 LncRNA-TSLP induces HOTAIR transcription through PI3K/AKT-IRF1 pathway, promoting endothelial cell proliferation and migration in atherosclerosis.57 Besides, ox-LDL induced TSLP may bind to dendritic cells (DCs) to activate the Th17 inflammation,58 which is related to the severity and progression of AS.59HOXC-AS1 may suppress the cholesterol accumulation in macrophages via promoting HOXC6 expression at mRNA levels.24LncRNAs mainly act as competing endogenous RNAs (ceRNAs) or miRNAs “sponge” interacting with miRNAs in the process of atherosclerosis at the post-transcriptional regulation level.  Furtherm60 Cremer S et al.61 found that MALAT1 “sponged” miR-503 to reduce the release of pro-inflammatory cytokines, attenuating plaque inflammation.61 Besides, the suppressor of cytokine signaling 1 (SOCS1) is the target protein of miR-155 that negatively regulates Janus activated kinase (JAK)-signal transducer and activator of transcription (STAT) signaling. MALAT1 could downregulate miR-155 and increase the expression of SOCS1 to alleviate the inflammation and apoptosis in atherosclerosis.62 Thus, MALAT1 may play a protective role via interacting with miRNAs in the pathogenesis of atherosclerosis.MALAT1 acts as ceRNA in ox-LDL-induced cells injury and plays a protective role in atherosclerosis disease. MALAT1 could compete with miR-22-3p for endogenous RNA and upregulate the target genes CXCR2 and AKT of miR-22-3p to inhibit endothelial cells apoptosis and promote the ECs migration and angiogenesis.63 and inhibits adipogenesis by targeting PPAR-g.64 Silencing of H19 significantly increases the expression of miR-130b, which ameliorates inflammation and lipid synthesis in ox-LDL-treated Raw264.7 cells.65 H19 can accelerate proliferation and impede apoptosis in ox-LDL-stimulated VSMCs by directly suppressing miR-148b expression and enhancing miR-148b target gene WNT1 expression.66The expression of lncRNA H19 was up-regulated in ox-LDL treated macrophages. MiR-130b regulates the inflammatory response by decreasing the translational levels of TNF-α, Sp1, NF-κB with lipid stimulation67 MIAT interferes with miR-149-5p pathways to increase the CD47 level in macrophages, promoting plaque vulnerability.68 The formation of the MIAT/miR-181b/STAT3 axis plays a critical role in ox-LDL induced human aorta vascular smooth muscle cells (HA-VSMCs) and human mononuclear cells (U937). MIAT up-regulates signal transducer and activator of transcription 3 (STAT3) protein level through sequestering miR-181b, subsequently promoting proliferation, facilitating cell cycle arrest and inhibiting apoptosis in HA-VSMCs and U937 cells.69LncRNA-MIAT may be involved in atherosclerotic plaque progression. MIAT is mainly expressed in the macrophages of advanced atherosclerotic plaques. With the ox-LDL treatment, the expression of MIAT is upregulated. Anti-phagocytic molecule CD47, a target gene of miR-149-5p, is related to apoptotic cell clearance and necrotic cores.70 found that NEAT1 was significantly upregulated in the presence of ox-LDL and served as a sponge to repress the expression of miR-342-3p, increasing the serum level of IL-6, IL-1β, COX-2, and total cholesterol leading to accelerating inflammation process and the formation of foam cells.70 LncRNA-TUG1 could down-regulate the expression of miR-26a and increase the mRNA and protein level of TRPC6 to facilitate the endothelial cells apoptosis.71 Lei Zhang et al.72 revealed that TUG1 sponged miR-133a and up-regulated fibroblast growth factor 1 (FGF1) expression, resulting in increased hyperlipidemia and excessive inflammatory response aggravated atherosclerotic lesion.72NEAT1 was also involved in the atherosclerotic process as ceRNA except for remodeling chromatin at the transcriptional level. Lei Wang et al.73 LincRNA-p21 functions as ceRNA to promote ECs apoptosis and induces cell cycle progression by targeting the miR-130b.74 LncRNA-GAS5 negatively regulates miR-21 expression to enhance programmed cell death 4 (PDCD4) expression, suppressing ECs proliferation and triggering ECs apoptosis.75In addition, more and more studies have demonstrated that plenty of atherosclerosis-related lncRNAs plays a crucial role in the pathogenesis of AS by interacting with miRNAs at the post-transcriptional level. LINC00305 acts as an endogenous sponge for miR-136 and inhibits miR-136 expression to suppress the vascular endothelial cells proliferation and enhance apoptosis.24 such as localizing RNP particles in legume plants, extending telomere during DNA replication in eukaryote,76 reducing Dicer-generated siRNA and affecting the expression of Dicer-regulated genes.77 While their underlying molecular mechanism related to the development of atherosclerosis remains unknown.LncRNAs may function through protein localization, telomere replication and RNA interference in some processes,Taken together, lncRNAs can be involved in several processes associated with atherosclerosis, including inflammatory response, lipid metabolism and cells function. They regulate the pathology of atherosclerosis at epigenetic, transcriptional and post-transcriptional levels, such as chromatin remodeling, promotion of transcription and competing endogenous for miRNAs. Therefore, lncRNAs may serve as promising novel diagnostic markers and therapeutic targets for atherosclerosis and vascular diseases. Moreover, all of these possible roles in physiopathologic processes have opened venues to decipher the function and mechanism of lncRNAs in cardiovascular diseases and other diseases, such as tumors, renal diseases and nervous diseases.