While transposons are generally silenced in somatic tissues, many transposons escape epigenetic repression in epithelial cancers, become transcriptionally active and contribute to the regulation of human gene expression. We have developed a bioinformatic pipeline for the integrated analysis of transcription factor binding and transcriptomic data to identify transposon-derived promoters that are activated in specific diseases and developmental states. We applied this pipeline to a breast cancer model, and found that the L1PA2 transposon subfamily contributes abundant regulatory sequences to co-ordinated transcriptional regulation in breast cancer. Transcription factor profiling demonstrates that over 27% of L1PA2 transposons harbour co-localised binding sites of functionally interacting, cancer-associated transcription factors in MCF7 cells, a cell line used to model breast cancer. Transcriptomic analysis reveals that L1PA2 transposons also contribute transcription start sites to up-regulated transcripts in MCF7 cells, including some transcripts with established oncogenic properties. In addition, we verified the utility of our pipeline on other transposon subfamilies, as well as on leukemia and lung carcinoma cell lines. We demonstrate that the normally quiescent regulatory activities of transposons can be activated and alter the cancer transcriptome. In particular, the L1PA2 subfamily contributes abundant regulatory sequences, and likely plays a global role in modulating breast cancer transcriptional regulation. Understanding the regulatory impact of L1PA2 on breast cancer genomes provides additional insights into cancer genome regulation, and may provide novel biomarkers for disease diagnosis, prognosis and therapy. Transposons contain cis-regulatory sequences that are recognised by the host transcriptional machinery (primarily transcription factors (TF) and RNA polymerases (RNA pol)), which they require to exploit the host transcriptional resources for their own replication7. This obligatory compatibility also enables the host genome to exapt transposon-derived regulatory sequences to modulate the regulation of host transcriptional networks.Transposons are repetitive DNA elements that are ubiquitous in eukaryotic genomes, and occupy about 45% of the human genome13. Host genes that are under the regulation of transposon sequences are involved in a diverse range of biological functions, including innate immunity and pregnancy in humans, female fertility and brain development in mice, as well as courtship song phenotype and stress response in fruit flies12.Transposons have been shown to contribute functional sequences, including TF binding sites (TFBS), promoters, enhancers and insulators, for the regulation of host genes in a variety of organisms, including humans, mice, maize and fruit flies17. The transposon-derived activation of oncogenes, called the onco-exaptation of transposons, can subsequently lead to tumour development and enhanced malignancy, as summarised in Babaian and Mager17. Specific examples of transposon-driven abnormal oncogene expression have been reported in human lymphoma, leukemia, lung cancer, bladder cancer, and breast cancer26.In addition to gene regulation in normal biological pathways, transposons may also play a regulatory role in the cancer transcriptome. In the human genome, transposons are often heavily suppressed in somatic tissues, primarily via histone tail modifications and DNA methylation; however, they can escape epigenetic repression in the cancer state, and exert regulatory activity that affects the expression of oncogenes27. Based on this theory, it is expected that regulatory functions, as well as features that account for regulatory activities will be conserved within a group of related transposons. Indeed, transposons within the same subfamilies have been demonstrated to exhibit similar regulatory activities. For example, in silico analysis has revealed the MER130 DNA transposon subfamily to be significantly enriched within active enhancers in the mouse dorsal cerebral wall10. These MER130 transposons contain a highly conserved region harbouring putative binding motifs for TFs associated with brain development, and exhibit in vitro enhancer activity in mouse embryonic neurons10. In human innate immunity, LTR retrotransposons are overrepresented in the transcriptional regulatory network2. In particular, upon interferon-gamma stimulation, the MER41 subfamily is significantly enriched in the binding sites of IRF1 and STAT1, both of which play a crucial role in immune signalling pathways2. Several MER41 transposons also contribute enhancer activity for immunity-associated genes, such as AIM2 and APOL12. In the case of pregnancy, the MER20 subfamily has been found to harbour binding sites for hormone-responsive and pregnancy-related TFs, and are overrepresented near progesterone or cAMP-responsive endometrial genes28. Epigenetic profiling indicates that these MER20 transposons can exert a diverse range of regulatory activities by acting as enhancers, insulators or repressors28. As demonstrated by examples above, transposons can exert regulatory activity at the subfamily level, and this conservation of regulatory activity allows functionally correlated genes to be regulated in a temporally or spatially specific manner.In 1971, Britten and Davidson proposed that the expansion of transposons in the host genome could have accelerated the evolution of regulatory networks, by acting as a vector to disperse regulatory elements and thereby recruiting host genes into co-regulated, co-expressed networks1. A full-length LINE1 element is approximately 6 kb in length, and contains a 5′ untranslated region (5′ UTR), two open reading frames (ORF) and a 3′ poly(A) tail1  human L1PA2 elements are over 6 kb in length, exhibiting limited divergence, deletion and insertion relative to the consensus sequence  in MCF7 cells. These L1PA2 transposons displayed an active epigenetic profile in MCF7 cells, and contributed cancer-specific promoter activity to a number of alternative or novel transcripts. Our results demonstrate that the normally quiescent regulatory activities of transposons can be unleashed following the loss of epigenetic repression, altering the cancer transcriptome. Taken together, the ubiquitous and replicative nature of the L1PA2 subfamily makes them an exemplary vector for the dispersal of co-localised transcription factor binding sites, thereby facilitating the co-ordinated regulation of genes. We demonstrate that the L1PA2 subfamily is a prominent contributor of regulatory elements in breast cancer cells, as well as leukemia and lung cancer cells, and likely play a global role in cancer transcriptional regulation. The transcriptional activation of L1PA2 transposons in cancer is correlated with alterations in the transcriptome, and may provide novel biomarkers for disease diagnosis and treatment.37. Decreased mappability within these regions may also have some effects on the appearance of depletion compared to surrounding genomic regions38. An example of TF binding, as visualised on the GTRD browser39, is shown for the L1PA2 transposon located upstream of MET, previously described by Roman-Gomez, et al.22  L1PA2 transposons harboured at least one TFBS when all experimental conditions  were considered. The 5′ UTR of L1PA2 transposons harboured abundant TFBSs, as the frequency of TF binding almost doubled in the 5′ UTR compared to neighbouring genomic regions  L1PA2 elements harboured at least one TFBS in MCF7 breast cancer cells alone.Next we analysed cell-type-specific ChIP-seq data from the ChIP-Atlas database to investigate the TF binding status of L1PA2 transposons in the context of breast cancer42. However, there is a general positive correlation between DNAse signal and transcriptional activity43. Interestingly, DNAse hypersensitivity was observed in the 5′ UTR of both bound and unbound elements; however, the strength of this signal was around twice as strong for bound elements, supporting a more open chromatin configuration and transcriptional activity from bound transposons , with a strong promoter profile (H3K4me3), and some elements potentially contained primed enhancer properties (H3K4me1) , or gene bodies (H3K36me3), but not repressive chromatin marks (H3K9me3 and H3K27me3)e1) Fig.  online. e1) Fig.  online. 48. We confirmed that in MCF7 cells, a number of L1PA2 transposons showed a consistent TF binding pattern where they were found to harbour co-localised TFBSs  co-localised with ESR1 binding sites, only 23.2% of ESR1 sites co-localised with NR2F2 sites Fig. a. This aOverall, asymmetrical co-localisation was common when considering genome-wide TFBSs Fig. a. In conTo test our hypothesis that L1PA2 transposons contributed increased regulatory activity in the cancer state, we also investigated the TF binding profile of L1PA2 transposons in the near-normal MCF10A cell line. Overall, a total of 30 TFs were identified to have binding sites within L1PA2 transposons in MCF10A cells Fig. a. It is We next sought to determine whether the transcriptional activation of L1PA2 transposons was a common feature in cancer, by investigating their TF binding activity in other cancer types. We characterised L1PA2-derived TFBSs in K562 and A549 cells, which are leukemia and lung carcinoma cell lines respectively. Similar to MCF7 cells, L1PA2 transposons were found to contribute abundant TF binding activity in the other cancer cell lines. In particular, 2,598 (52.6%) and 1,121 (22.7%) out of 4,940 L1PA2 transposons were found to contain TFBSs in K562 and A549 cells respectively. Upon further examination, 1,096 L1PA2 elements harboured TF binding activity in all three cancer cell lines, suggesting that the transcriptional activation and onco-exaptation of the L1PA2 subfamily was a common phenomenon in cancer th)  and breast cancer  52 52 Fig. c. For thWe hypothesised that the transcription factor binding activity shared amongst L1PA2 transposons was correlated with conserved motif sequences. The sequence similarity amongst L1PA2 transposons impeded de novo motif discovery (data not shown), we thus performed motif scanning analysis to identify occurrences of known binding motifs of frequently binding, oncogenic TFs  in L1PA2 sequences. Overall, 66.8%-98.3% of TF-bound L1PA2 transposons contained at least one significant motif of the corresponding TF Fig. . The maj53. To investigate the regulatory role of L1PA2-derived TF binding, the distribution of L1PA2 transposons with respect to breast cancer-associated genes was analysed using publicly available RNA-seq data from MCF7 breast cancer and MCF10A near-normal cells. 9,375 and 9,771 transcripts were up-regulated and down-regulated in MCF7 cells respectively, with 5,435 up- and 4,094 down-transcripts passing a p-value cut-off of 0.05 , and significantly depleted for down-regulated transcripts (p = 2.55E−09) , reducing the computational resources required for analysis. By contrast, the ChIP-Atlas database retains the cell line and tissue information, allowing us to assess TF binding in specific cell lines.Here we have utilised data from the GTRD and the ChIP-Atlas databases, both of which aim to catalogue and compile an extensive range of publicly available ChIP-seq datasets30. This region represents a potent reservoir of regulatory activity, harbouring binding sites for a variety of TFs, including YY1, RUNX, SOX and MYC58. The LINE1 5′ UTR, particularly the antisense promoter, also contributes significant promoter activity in a variety of cell types, affecting the expression of many genes such as SYT1, MET and JAK159.Our analysis revealed that when all TFs and experimental conditions in the GTRD database were considered, 54.2% of L1PA2 transposons contained at least one TFBS, and TFBSs often clustered within the 5′ UTR  or down-regulated (repression) transcripts in MCF7 cells. TF binding in L1PA2 transposons was correlated with the activation of nearby transcripts  into meta-clusters39. The genomic locations (hg38) of human L1PA2 elements were retrieved from the UCSC RepeatMasker table34. For each L1PA2 element, a 20 kb region centred on the transposon was defined and divided into 100 bp bins. The genomic locations of the GTRD TFBSs were intersected with the L1PA2 elements using BedTools Intersect, where an overlap was called when at least half of a TFBS overlapped with an L1PA2 transposon, using the –f option66. The number of TFBSs in each 100 bp bin was counted using BedTools Coverage66, and normalised to the total counts of TFBSs mapped to the corresponding 20 kb regions to obtain the normalised counts. The normalised counts in each bin were averaged across all L1PA2 elements containing at least one TFBS.TFBSs, defined as meta-clusters, were acquired from the GTRD database (version 19.10)40. The ChIP-Atlas dataset used in our analysis represent TFBSs identified in MCF7 cells, by over 900 publicly available ChIP-seq experiments. These studies include experiments performed on MCF7 cells subjected to a diverse range of experimental conditions, including hormone treatments with estradiol and progesterone. The ChIP-Atlas data includes TFBSs for 100 TFs in MCF7 cells. For the purpose of consistency, we referred to the TFs by the names recorded in ChIP-Atlas, instead of converting them to the protein names (e.g. ESR1 instead of ERα). The genomic coordinates of the TFBSs were converted from hg19 to hg38 using LiftOver, and only TFBSs that were successfully converted were retained for downstream analysis67. The genomic locations of the TFBSs were intersected with the L1PA2 elements using BedTools Intersect, where an overlap was called when at least half of a TFBS overlapped with an L1PA2 transposon, using the –f option66. The number of L1PA2 elements containing at least one TFBS in MCF7 cells was counted using a custom python script, and the lengths of L1PA2 transposons were calculated from their genomic coordinates. The number of L1PA2 overlaps for each TF and the number of TFs binding to each L1PA2 were counted using a custom python script.All TFBSs identified in MCF7 cells were obtained from the ChIP-Atlas database (Cell Type = “MCF-7”)35. Briefly, published DNAse-seq and ChIP-seq data were downloaded from ENCODE in the FASTQ format, and aligned to the human genome (hg38) using BWA mem69 (for data sources see Jiang and Upton35)). For each epigenetic mark, Samtools view (-c option) was used to count reads in each 100 bp bin, then values were converted to RPKM70. RPKM values were subsequently averaged across replicates. For ChIP-seq data, RPKM values were normalised to the input control by subtraction to produce the “normalised RPKM” values. Finally, RPKM values were averaged across L1PA2 transposons within the TF-bound or unbound group. Similarly, the histone tail modification profiles of the same regions in normal breast tissues were investigated (for data sources see Supplementary Table 35).L1PA2 transposons were divided into two groups based on the TF binding status in MCF7 cells. L1PA2 transposons were investigated for DNAse sensitivity, as well as active  and repressive (H3K9me3 and H3K27me3) histone tail modifications in MCF7 cells. More specifically, epigenetic states of the 20 kb region (bin = 100 bp) centred on each L1PA2 transposon were investigated using publicly available DNAse-seq and ChIP-seq datasets, as described in Jiang and Upton34. To investigate TFBS co-localisation, for each pair of L1PA2-binding TFs, the number of L1PA2 transposons containing both TFBSs was counted and the distances between the binding sites were calculated using a custom python script.To remove redundant information, overlapping L1PA2-derived binding sites of the same TF were merged to keep the most distal genomic coordinates. Locations of TFBSs in L1PA2 transposons were calculated as the distances between the middle of the binding sites and the 5′ ends of the transposons. The equivalent locations in the L1PA2 consensus sequence were then calculated by adjusting the distances by the RepStart and RepEnd information from the RepeatMasker database40. For each TF, non-L1PA2-derived TFBSs were identified by filtering out the previously identified L1PA2-derived TFBSs from genome-wide binding sites. Genomic locations of overlapping TFBSs were merged using BedTools Merge to remove redundant information66.Genome-wide binding sites for the top binding TFs  were identified using the MCF7 ChIP-seq data from ChIP-AtlasHere, we defined co-localised, or co-occurring TFBSs to be located within 500 bp of each other. For each TF, binding sites that co-localised with another TF were identified using BedTools Window . The proportion of co-localisation was calculated as the number of co-localising TFBSs divided by the total number of TFBSs for this TF. To account for asymmetrical co-localisation, the co-localisation proportions for each TF-TF combination were calculated with each factor as the denominator separately. For example, the proportion of ESR1 binding sites co-localising with SFPQ, and the proportion of SFPQ binding sites co-localising with ESR1, were calculated separately. The co-localisation proportions for L1PA2-derived and non-L1PA2-derived TFBSs were determined separately and compared using a one-tailed proportion z-test. To account for multiple testing, p-value < 6.2E−4 51. Only protein–protein interactions with experimental evidence were considered . In order to gain further insight into the pathways or diseases the TF networks were associated with, functional enrichment analysis was performed using the ToppFun tool52. Bonferroni q-value < 0.05 indicated statistical significance.To estimate the interactions between these TFs, the list of TFs binding to L1PA2 transposons in MCF7 cells was used as input for the online Multiple Proteins by Names / Identifiers search in STRING v1171. DNA sequences of L1PA2 transposons bound by each TF were extracted from the hg38 FASTA file for main chromosomes72 using BedTools Getfasta (v2.25.0) (-s option)66. Motif occurrences in L1PA2 sequences were identified using FIMO v5.0.5 (-norc option), with a statistical significance threshold of p-value < 1E−473. Positions of the discovered motifs in the L1PA2 consensus sequence were calculated using the RepStart and RepEnd information from RepeatMasker33. The distribution of discovered motifs in the consensus sequence (between 0 and 6500 bp) was visualised by plotting the middle of the adjusted positions in a histogram (bin = 5 bp). For bins that contained a high number of discovered motif sequences (peaks), a sequence logo, which was a representation of sequence conservation, was generated with the motif sequences in the corresponding bins using the WebLogo online tool v2.8.274. For the purpose of comparison, an L1PA2-specific sequence logo was generated for each TF using all discovered motif sequences.Binding motif position-weight matrices were obtained from the JASPAR 2020 database for ESR1 (MA0112.2), FOXA1 (MA0148.4) and E2F1 (MA0024.2)http://ncbi.github.io/sra-tools/)76. The quality of the sequencing data was confirmed using FastQC v0.11.8 (www.bioinformatics.babraham.ac.uk/projects/fastqc/)77. Reads were aligned to GENCODE v29 transcripts (hg38) using STAR 2.7.1a, with more permissive multi-mappers parameters 79. Transcripts were called and quantified for expression using StringTie 2.0.3 (–rf -f 0.0 -c 0.001)54. To include all annotated transcripts in our analysis, transcripts identified in each cell line were merged using StringTie 2.0.3 Merge54, and expression quantification was repeated.SRA files of publicly available RNA-seq data in MCF7 and MCF10A cells  were downloaded from the GEO database and converted to paired-end FASTQ files using command fasterq-dump –S , or less than 0.5 (down-regulated) in MCF7 cells relative to MCF10A cells.Differential transcript expression analysis was performed using Ballgown 2.16.0 in R 3.6.1, which outputted the fold changes of transcripts as well as the p-values and q-values of the statistical tests66. The exon structure and genomic locations of unknown transcripts were compared to nearby known transcripts by eye using the UCSC genome browser and information from the Ensembl database72. Unknown transcripts were considered to be associated with a known transcript if they overlapped by at least one exon.We defined the TSS of a transcript to be the position at which the transcript began. L1PA2-derived transcripts were identified by intersecting the TSSs of differentially expressed transcripts with L1PA2 transposons using BedTools Intersect66. The proportions of L1PA2 transposons located nearby the TSSs were calculated by dividing the counts by the total number of L1PA2 transposons in the corresponding TF-binding group.L1PA2 transposons were split into two groups based on their TF binding status. For each group, we identified the L1PA2 transposons that were located within 1 kb to 20 kb (in increments of 1 kb) away from an up-regulated or down-regulated TSS, using the BedTools Window -w optionTo test for the statistical significance of direct overlaps between TSSs and L1PA2 transposons, the expected numbers of up-regulated and down-regulated TSSs in TF-bound L1PA2 transposons were estimated by random rotation of the genome and the TSS locations , using a custom python script. The average number of overlaps was divided by the total number of TSSs for up-regulated or down-regulated transcripts to produce the expected probability of TSSs being located in L1PA2 by random chance. The observed number of TSSs overlapping L1PA2 transposons was counted with no rotation applied, and the statistical significance for enrichment or depletion was evaluated using a binomial test. P-value < 0.05 indicated statistical significance.34.The pipeline for investigating the regulatory activity of transposons in specific biological contexts were developed in Python. As a validation of its utility, the pipeline was applied to investigate the TF binding, binding site co-localisation and promoter activity of other primate-specific LINE1 subfamilies , a more distantly related LINE1 subfamily (L1M4b), and non-LINE1 subfamilies (LTR7C and LTR24B) in MCF7 cells. The genomic locations (hg38) of these transposons were retrieved from the UCSC RepeatMasker table40, and processed in the same way as the MCF7 data. The ChIP-Atlas data includes TFBSs for 192 TFs in K562 cells, 57 TFs in A549 cells and 41 TFs in MCF10A cells.Furthermore, we investigated the regulatory activity of L1PA2 transposons in other cell lines, including the near-normal MCF10A mammary cells, A549 (lung carcinoma) and K562 (leukemia) cells. All TFBSs (hg38) identified in these cell lines were obtained from the ChIP-Atlas database35). Similarly, the epigenetic profiles of the same regions in normal primary breast tissues were investigated (for data sources see Supplementary Table 35).The TSSs of up-regulated transcripts, as well as L1PA2 transposons harbouring TSSs of up-regulated transcripts were investigated for their epigenetic states and RNA pol II binding. Epigenetic states of the 20 kb region centred on each L1PA2 transposon or TSS (bin = 100 bp) in MCF7 cells were investigated using publicly available ChIP-seq and DNAse-seq datasets, as described above and in Jiang and Upton40 in the bed format (Cell Type Class = “Breast”), and converted to hg38 using LiftOver as previously described67. Overlapping binding sites were merged using BedTools Merge66. RNA pol II binding sites were intersected with the L1PA2 transposons using BedTools Intersect66, retaining information on the cell lines or tissues in which the binding sites were detected.RNA pol II binding data in breast tissues and cell lines (hg19) were downloaded from ChIP-AtlasSupplementary Figures.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.Supplementary Table S6.Supplementary Table S7.


To the Editor:Deltaproteobacteria forms a distinct subtype of Class II type V CRISPR‐Cas effectors and can introduce programmable double‐stranded breaks in mammalian genomes.The CRISPR‐associated catalytically inactive SpdCas9 and AsdCas12a proteins fused to effector domains, with distinct regulatory functions enables stable and efficient transcriptional repression or activation.To construct a robust and tunable gene repression system, we first created a gene encoding a human codon optimized dCasX fused with the repressive chromatin modifier domain named KRAB Figure  and S2. Furthermore, we examined the effect of repressed endogenous c‐MYC, a well‐studied oncogene that positively regulates cell proliferation,We reasoned that the CRISPRi platform provides a modular protein effector recruitment system, which may also be useful for gene activation when coupled with transcription activators. To test if we can activate gene expression in human cells with dCasX, we fused a hybrid VP64‐p65‐Rta (VPR) tripartite activator to dCasX Figure  and S2. The effect of TP53 expression activated by dCasX‐VPR was assessed on the bladder cancer cells. CCK‐8 assay results indicated that TP53 activation decreased 5637 and T24 bladder cancer cells proliferation Figure . Then, tPrevious studies have shown that CasX is much smaller than Cas9, but is more efficient in genome editing.In conclusion, the CRISPR/dCasX system can be used to screen for both loss‐of‐function and gain‐of‐function phenotypes in a modular format and may produce an anticaner effect when driven by cancer‐specific promoters.The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.Qian Zhang, Yuchen Liu and Ying Gan were responsible for the study design and supervision and wrote the paper. Congcong Cao, Lin Yao and Aolin Li performed the experiments. Quan Zhang, Zhenan Zhang and Xiaofei Wang performed data analysis. All authors approved the final version of the manuscript.National Natural Science Foundation of China, Grant Numbers: 82072826, 81872088, 81972867, 81773257; Peking University Medicine Fund of Fostering Young Scholars' Scientific & Technological Innovation, Grant Number: BMU2020PYB028; Natural Science Foundation of Guangdong, Grant Number: 2018B030306023; Shenzhen Municipal Government of China, Grant Numbers: RCYX20200714114701035, JCYJ20180507184642475.SUPPORTING INFORMATIONClick here for additional data file.


The ability to regulate chromatin organization is particularly important in neurons, which dynamically respond to external stimuli. Accumulating evidence shows that lncRNAs play important architectural roles in organizing different nuclear domains like inactive chromosome X, splicing speckles, paraspeckles, and Gomafu nuclear bodies. LncRNAs are abundantly expressed in the nervous system where they may play important roles in compartmentalization of the cell nucleus. In this review we will describe the architectural role of lncRNAs in the nuclei of neuronal cells. The cell nucleus is a highly organized organelle composed of many functional and structural domains . Silent Neuronal cells might be of particular interest when it comes to analyzing nuclear architecture and organization, as different types of neurons differ significantly in terms of nuclear size and chromatin organization . They dyRecently, long non-coding RNAs (lncRNAs) were described as potent organizers of nuclear architecture ,19. The XIST lncRNA (described below) [MALAT1, can reshape the local nuclear landscape by redistributing particular chromatin domains to active or silent nuclear compartments [NEAT1, and MALAT1 recruit proteins to form nuclear bodies like Gomafu bodies, paraspeckles, and speckles, respectively [LncRNAs can affect nuclear organization by several mechanisms. They may act as epigenetic modulators of chromatin states, thus affecting local chromatin accessibility. Numerous lncRNAs have been shown to interact with epigenetic modifiers like polycomb proteins or methyltransferases and recruit them to particular gene loci . In turnd below) . Additioartments . Moreoveectively ,38,39,40In 1949, Barr and Berttram  describeEach female cell has only one active X chromosome (Xa), where the second one is transcriptionally inactivated during embryonic development and forms the Barr body, named after its finder. The paternal and maternal copies are randomly silenced in cells of females, which results in the haphazard distribution of actively transcribed genes inherited from both parents on X chromosomes. The inactivation of one copy of chromosome X of females is necessary to balance gene expression quantity in males and females. Moreover, in 1967, Susumu Ohno proposed that the monoallelic expression of X-linked genes in mammals should be compensated by the twofold transcriptional up-regulation of the active X in both males and females . HoweverDrosophila sex chromosomes by Muller [roX1 and roX2, which together with five proteins  form the male-specific lethal (MSL) complex. The two lncRNAs are essential for MSL complex assembly and targeting to the X chromosome, where it stimulates transcription of the X-related genes [The full dosage compensation is achieved epigenetically on many levels and was first described for y Muller . In fruied genes .XIST), a type of lncRNA. It is initiated at the X-chromosome inactivation center (XIC) of the putative inactive X (Xi) chromosome, where the XIST gene is localized and expressed [REPA, TSIX, XITE, and JPX, which are involved in the regulation of XIST expression [TSIX, transcribed from the antisense strand of XIST, is a negative regulator of its expression, and together with XITE controls the allelic choice of the active X chromosome [REPA and JPX, are shown to be positive regulators of XIST [XIST RNA expression and binding at the nucleation center, the silencing spreads throughout the chromosome. Inactivation of the 150 Mb long chromosome is quite a challenge and requires a specific spreading mechanism. Artificial placement of XIC on an autosome results in its silencing induced by the ectopic expression of XIST and coating of DNA by the transcript; however, induced inactivation is not as efficient, suggesting some sequence specificity [XIST and silencing spreading to the whole Xi [XIST transcript, and in the case of nucleolar localization two other lncRNAs, namely FIRRE and DXZ4 [XIST sequence, six such domains have been identified. The A–F repeats, which are conserved between humans and mice, overlap with blocks of tandem repeats of unique short sequences, containing motifs specific for RNA binding proteins involved in coordinated silencing of X-linked genes [X chromosome inactivation (XCI) during development is a dynamic, multi-step, and highly organized process, which is fully dependent on X-inactive specific transcript /heterogeneous nuclear ribonucleoprotein U (hnRNPU), a nuclear matrix protein [XIST and is indispensable for XIST chromosomal localization [XIST results in the dispersion of XIST in the nucleoplasm and lack of Xi silencing and Barr body formation [XIST expression [XIST as well the binding of SPEN is dispensable for XIST chromosomal localization in cis. SPEN is involved in the recruitment of several members of the repressor complexes like NCoR/SMRT and NuRD, and activation of deacetylation [XIST B and C repeats [XIST recruits over 80 proteins [ protein . SAF-A/h protein , and med protein . Its bin protein . Throughlization . Knockinormation . In turnpression  and in tpression . The latpression . Howevertylation . Loss oftylation , as deac repeats . Polycom repeats . Overallproteins ,83,84, wproteins .Dzx4/DZX4 repeat is located. The Xa is organized similarly to autosomes into more than 100 topologically associated domains (TADs), on average 1 Mb long, consisting of smaller chromatin loops frequently linking enhancers and promoters. The Xi megadomains are composed of several dozen super loops (between 7 and 74 Mb long) some of which are anchored at regions containing genes of lncRNA: LOC550643, XIST, DXZ4, and FIRRE. The unique architecture of Xi depends fully on XIST, as inducible XIST expression in male mouse cells resulted in increased interaction frequencies along the chromosome, separation of two megadomains, and a final structure similar to female Xi [XIST lacking A-repeat region, which is responsible for Xi coating and RNA polymerase II exclusion, was induced, male X chromosome structure was not affected.Inactivated X chromosome has a very unusual structure, which was shown in detail using chromosomal conformation capture-based techniques ,86. Bothemale Xi . InteresXIST binding and highly condensed chromatin. However, gene-poor and gene-rich as well as expressed and repressed segments were evenly distributed within the whole Xi CT. The super-resolution microscopy showed the details of Xi ultrastructure. It is not a solid, uniformly condensed region of chromatin, but is reminiscent of a sponge-like structure filled with slightly collapsed interchromatin channels. They start at the nuclear pores and meander between areas of the tightly packed chromatin [The differences in chromatin contacts are reflected in the morphology of chromosome X territories ,89. The hromatin . This agXIST. The introduction of XIC or XIST itself to autosomes is sufficient for their perinucleolar targeting from the mid to late S phase of the cell cycle [Firre in mouse fibroblasts disrupts perinucleolar Xi localization and H3K27me3 levels. However, upon Firre depletion, no reactivation of X-linked genes was observed. Interestingly, in electrically-stimulated motor neurons, the nucleolar satellite observed by Barr and Bertram was moving away from the nucleolus [XIST interaction with membrane attachment nuclear envelope proteins, namely lamin B receptor (LBR), lamina-associated protein 2 (LAP2), and SUN domain-containing protein 2 (SUN2) [As was mentioned, the Xi was observed for the first time in female cat neurons adjacent to the nucleolus . Later sll cycle ,91. Moreucleolus . Similarucleolus . Unfortuucleolus , perinuc2 (SUN2) ,84. Bind2 (SUN2) .XIST lncRNA.In summary, Xi’s unusual ultrastructure and localization to nucleolar and nuclear vicinities is fully dependent on XIST lncRNA coating [From 3% to 5% of genes located on mouse Xi chromosome are active, and even more so humans, where up to 30% of genes escape silencing ,96,97. T coating . They ar coating ,100,101. coating  uncovereKDMC5 coding lysine-specific demethylase 5C , the mutations of which cause Claes–Jensen type XLID (CJ-XLID), a rare syndrome accounting for approximately 1–3% of all XLID cases. KDM5C plays a critical role in constraining transcription during neuronal differentiation and maturation by removing from the histone tail active posttranslational modification, H3K4me3/2 [KDM5C and XIST genes are significantly over-expressed in lymphoblastoid cells and postmortem brains of female patients with bipolar disorder or major depression. The authors suggested that over-expressed XIST lncRNA may excessively recruit XIST-binding complexes and by this impair XCI, or the XIST overexpression might be the response compensating inefficient XCI. The subtle alteration of XCI, which is the cause or the consequence of XIST over-expression, results in the unbalanced expression of X-linked genes including X inactivation escapees like KDM5C, which in turn regulates the expression of other genes involved in proper brain function. Interestingly, among genes differentially expressed in women, in those who developed co-morbid chronic musculoskeletal pain (CMSP) and posttraumatic stress syndrome (PTSS) in consequence of motor vehicle collision, 40 genes were localized on the X chromosome [XIST lncRNA, possible partial derepression of Xi, and later development of CMSP and PTSS.Genes that escape X-chromosome inactivation may be particularly important in brain function. In humans, the X chromosome bears about 5% of the whole genome, yet it contains about 15% of all known genes associated with intellectual disability. This makes the X chromosome an attractive target in neurobiological research. There are 141 X-linked intellectual disability (XLID) genes, the duplication of which results in some form of mental retardation , suggest3K4me3/2 . In addi3K4me3/2 ,108. Add3K4me3/2  found thromosome . MoreoveKDMC5 and NLGN4X may be engaged in the specific neurocognitive profile of TS [XIST locus. It has been shown that the presence of the ring X chromosome was related to cognitive impairments, low IQ scores, and mental retardation, and its size correlated with the severity of neuro-cognitive disabilities. Not only deficiency but also the excess of X chromosomes like in Klinefelter syndrome (KS) has unfavorable consequences for neuro-cognitive functions. A total of 80–90% of KS patients have classical 47,XXY karyotype, and the rest show even more sex chromosomes . The supernumerary X chromosomes undergo silencing, except for the escapees’ genes. Their altered expression can be involved in the KS phenotype, namely tall stature, gynecomastia, hypogonadism, absent spermatogenesis, changes in brain structures, motor, verbal, and cognition deficits as well as psychiatric disorders from major depression to bipolar disorder to schizophrenia, which are all more frequently diagnosed in KS individuals as compared to the general population [XIST and other lncRNAs in the regulation of Xi structure, localization, silencing, and in consequence transcriptional activity of X-linked genes, the alternation of which has deleterious consequences for neuro-cognitive functions.Another line of evidence of the escapees’ importance in brain function comes from the data on sex chromosome aneuploidies, which occur in 1/500 birth in humans. Human karyotype can be described as 46,XX or 46,XY, standing for 46 autosomes ad two sex chromosomes. As many as 99% of embryos with 45,X karyotype die in utero due to defects in placenta development. The surviving 1% express severe phenotypes of Turner syndrome (TS), including ovarian dysgenesis, short stature, webbed neck, and other physical abnormalities accompanied by deficits in visuospatial reasoning skills, executive function, social cognition, and aberrant brain structure . So far,le of TS . Approxile of TS . The rinpulation ，116,117.NEAT1) is one of the key architectural lncRNAs and is responsible for paraspeckle formation. This lncRNA is transcribed by RNA pol II [NEAT1_1  and longer NEAT1_2 (23 kb in humans) [NEAT1_1 is also found in paraspeckles; however, its role is dispensable for their formation or maintenance [NEAT1_2 molecules and 6.5 NEAT1_1 molecules [Drosophila melanogaster behavior human splicing (DBHS) proteins [NEAT1 RNA [NEAT1_2 and paraspeckle proteins is strong and stable as chemical extraction of NEAT1_2 from paraspeckles requires harsh conditions [Nuclear Enriched Autosomal Transcript 1/Nuclear Paraspeckle Assembly Transcript 1   The long humans) ,121,122.ntenance ,123. On olecules . More thproteins . Severalproteins . Proteinproteins . HoweverEAT1 RNA . The intnditions .NEAT1_2 transcription-dependent manner near the NEAT1 locus and spread into the nucleoplasm [NEAT1 promoter contains binding sites for a variety of transcription factors, and several pathways regulating NEAT1 expression have been described, most of which are connected with stress response [NEAT1_2 is crucial for paraspeckle assembly, as it provides a scaffold that binds NONO dimers [NEAT1_2 initiates oligomerization of other DHSB proteins, which leads to paraspeckle assembly via a phase-separation mechanism [NEAT1_2 folded Vi-shape, so that its 3′ and 5′ ends localize in the shell region of the paraspeckle and its middle part occupies the core region. This organization impacts the distribution of paraspeckle proteins. DHSB proteins colocalize with the NEAT1_2 mid part in the core of paraspeckles, while proteins like TARDBP, RBM14, or BRG1 with other SWI/SNF complex proteins colocalize with the NEAT1 ends [NEAT1_2 transcription [NEAT1 may bind active chromatin sites and that its localization changes significantly in response to changes in transcription [NEAT1_1 can directly interact with promoters of a particular set of genes and induce the active chromatin state favorable for transcription. This is probably mediated via the interaction of NEAT1 with histone H3 and its modifications H3K9Ac and H3K4me3. This raises the question of whether it fulfills this function independently or as a part of paraspeckles, and consequently, whether paraspeckles are freely diffusing bodies or whether they might bind to the chromatin. Interestingly, a recent study by Grosh et al. has provided evidence that paraspeckles might be tethered to chromatin most probably by forming a triple helix structure [NEAT1 might affect 3D genome architecture by acting as a molecular bridge between chromatin and paraspeckles [Paraspeckles form in a leoplasm ,119. Theleoplasm . Studiesresponse . A detaiO dimers . Bindingechanism . ParaspeAT1 ends ,133. Thecription . The usecription . Moreovecription , workingtructure . If so, speckles ,135.NEAT1 to bind microRNAs. Consequently, paraspeckles are considered as a “buffer” for various miRNAs, thus affecting the transcription of numerous genes targeted by these miRNAs [Paraspeckles form in numerous cell lines and various tissues; however, it seems that they are not vital for cell viability, at least under normal conditions . Till noe miRNAs ,140,141.e miRNAs ,142,143.NEAT1 in the neuronal cell nucleus. The expression of both NEAT1 isoforms in the brain, as estimated by qPCR, is very low [NEAT1_1 showed modest expression, while NEAT1_2 was hardly detectable [NEAT1 levels were analyzed using FISH in particular parts of the nervous system [NEAT1_1 [NEAT1_2 could not be detected in the spinal cord motor neurons. In tissue samples from young and old mice, the only detectable isoform of NEAT1 was NEAT1_1. In contrast to neurons, single-cell RNA-seq data showed that NEAT1 expression in glial cells is relatively high [Despite accumulating data, still very little is known about the role of very low ,144,145.s system . Analysi[NEAT1_1 . FurtherNEAT1 does not have any significant impact on mouse viability or neuronal functions, though it does impact the development of the corpus luteum [NEAT1 knockout mice show an exaggerated response to physiological stress. In these mice, neurons were hyperexcitable, most probably due to the up-regulated voltage-gated Na+ influx [NEAT1 in the brain leads to the perturbations in alternative splicing, which particularly affects genes related to RNA metabolism, synaptic functions, and neurological diseases [NEAT1 knockdown alters the expression of genes serving neuroprotective roles, and downregulation of key paraspeckle proteins like NONO or SFPQ negatively affects cell viability [NEAT1 might be important for proper neuronal functioning. However, the analysis of the role of NEAT1 in neuronal activity has given contradicting results. Lipovich et al. [NEAT1 function in the human neocortex. Using brain samples from human patients suffering from epilepsy, they identified NEAT1 as one of the lncRNAs upregulated in brain areas of increased activity. Next, using the SH-SY5Y neuroblastoma cell line, they confirmed these results showing that under chronic depolarization, NEAT1 expression was upregulated within 4 h. Those results were, however, contradicted by recent data obtained by Butler et al. [NEAT1 levels decrease after KCl stimulation. The results were confirmed in the animal model. After 1 h of contextual fear conditioning, mice had significantly reduced NEAT1 levels in the dorsal hippocampus. The reduction of NEAT1 levels was coupled with an increase in cFos expression both in cultured cells and in mouse brains. Importantly, in adult mice, changes in NEAT1 level were correlated with perturbations in hippocampus-dependent memory formation. The researchers proposed the mechanism according to which NEAT1 affects the chromatin accessibility by interacting with EHMT2 methyltransferase and adding methyl marks to H3K9 [NEAT1 might affect neuronal excitability [NEAT1 expression is inversely correlated with the expression of ion channel genes. Moreover, they provided evidence that it can also directly interact with potassium channel interacting proteins. These proteins are one of the key components engaged in regulating neuronal excitability [NEAT1 may act as a scaffold that upon neuronal activation, releases modulatory proteins to fine-tune the excitatory response [NEAT1 upon neuronal activation might induce the release of potassium channel proteins from the nucleus into the cytosol. This data shows that NEAT1 is involved in processes crucial for the proper functioning of neurons. Additional evidence that NEAT1 is important for these cells comes from the analysis of neuronal aging and pathological conditions. Accumulating data show that NEAT1 can be dysregulated in aging brains and several neuronal diseases, such as Huntington’s disease, amyotrophic lateral sclerosis (ALS), or frontotemporal dementia (FTD) [NEAT1 might be either up- or down-regulated. The imbalance in NEAT1 expression is often accompanied by mutations in various paraspeckle proteins like TDP-43 or FUS [NEAT1 becomes upregulated and is excessively bound to TDP-43, which contributes to decreased neuronal cell viability [NEAT1 knockdown could reverse this effect, and it appeared to have a similarly negative impact on neuronal viability as upregulation. This led them to the conclusion that any imbalance in NEAT1 expression in motor neurons might have negative impact on the cell viability [NEAT1 has been observed in a mouse model of Huntington’s disease and ataxia types 1,2, and 7 [NEAT1 is downregulated in the hippocampus at the early stages of AD [NEAT1 expression level is important for neurons, its imbalance might contribute to the development of a pathological phenotype.Until recently, it has been thought that loss of s luteum . Howevers luteum . The gro+ influx . Moreovediseases . Interesiability . These dh et al.  provide r et al. . Using N to H3K9 . Similar to H3K9 . This grtability . They shtability . Residinresponse . Transieia (FTD) ,153,154.3 or FUS ,156. Oneiability . Interes2, and 7 . On the es of AD  These daNEAT1 is necessary for paraspeckles to form, then what level of this transcription will result in the appearance of paraspeckles?It seems that at least some of these diseases are accompanied by de novo paraspeckle formation in the neuronal cell nucleus. Probably the first evidence for the possible formation of paraspeckles in neuronal cells was shown by Nishimoto et al., who analyzed paraspeckles in amyotrophic lateral sclerosis (ALS) tissue samples from mice and humans . ShelkovNEAT1 plays an important role in neuronal activation, the fundamental process in the neuronal cell. It seems that NEAT1 acts independently of paraspeckles, as available data show that normal neurons lack these nuclear domains. This suggests that at basal conditions (silent neurons), the main role is played by the NEAT1_1 transcript. However, under stress conditions, the cell switches to longer NEAT1 isoform synthesis. The appearance of NEAT1_2 leads to nucleation of paraspeckles, which help the cell to restore balance.Together this data show that though barely detectable in the neuronal cell nucleus, MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) was originally identified in a screen for RNAs, the levels of which were altered in early-stage lung cancers, and was found to be upregulated in tumors with a high ability to metastasize [MALAT1 has high sequence conservation in vertebrates [MALAT1 gene is transcribed by RNA pol II, and its transcription gives rise to ~7 kb lncRNA. It is highly enriched in nuclear bodies called splicing speckles, where it might play a role in regulating the protein composition of these nuclear bodies [astasize  Unlike mtebrates . The MALr bodies .MALAT1, different types of RNAs can be found, including pre-mRNAs and snoRNAs [MALAT1 are enriched in the speckle periphery [Splicing speckles are liquid-like nuclear bodies enriched in serine/arginine (SR) splicing factors and SR-like proteins. The human interphase nucleus contains 20–40 speckles, ranging in size from 0.5 to several micrometers in diameter . Both sp snoRNAs ,168,169.eriphery .It has been shown that actively transcribed genes can associate with nuclear speckles ,178,179,MALAT1 has been shown to play various roles. Due to its ability to affect the levels of speckle components and interact with different speckle proteins, it participates in regulating speckle number and organization [MALAT1 can also regulate their availability for the downstream processes [MALAT1 regulates the levels of miRNA while being associated with nuclear speckles, as miRNA processing machinery was found in splicing speckles [MALAT1 knockout has no obvious effect on speckle formation and maintenance [MALAT1 significantly affected speckle morphology. This deletion perturbed MALAT1-protein interactions, indicating that they might be important in speckle stabilization. It also resulted in the mislocalization of MALAT1 to the cytoplasm, where it “hijacked” speckle protein TDP-43, leading to the formation of the cytotoxic TDP-43 inclusions. These results suggested that MALAT1 might be also important for proteostasis [MALAT1 binds numerous active gene sites and has been shown to control gene expression in cis [trans [MALAT1 might tether splicing speckles to chromatin fiber [MALAT1, together with another lncRNA, TUG1, has been shown to affect the 3D nuclear organization. Both lncRNAs act to relocate the growth control genes from the repressing environment of polycomb bodies to the transcriptionally active milieu of splicing speckles by interacting with Polycomb 2 (Pc2) protein present on gene promoters [As a component of splicing speckles, nization ,170,183.nization ,38 and rrocesses . Though speckles . Interesntenance ,186. Thuntenance  has showeostasis . MALAT1 n in cis  and trans [trans . Due to in fiber . Accordiromoters . In thisromoters .MALAT1 in neuronal cell nuclei. MALAT1-enriched nuclear speckles are a common feature of the neuronal nucleus [MALAT1 is expressed in neurons at high levels [MALAT1 in primary cortical neurons results in their increased excitability [MALAT1 is upregulated in high-activity areas of the neocortex in patients with epilepsy, and its expression pattern suggested that it is engaged in the regulation of activity-dependent genes [MALAT1 in cultured hippocampal neurons led to decreased synaptic density [Little is known about the role of  nucleus , where t nucleus . Consideh levels ,145,186.tability . Resultsnt genes . Moreove density , which sMALAT1 in neurons due to its ability to sponge miRNAs. The interaction of MALAT1 with miR-30 is involved in the regulation of neurite outgrowth in hippocampal neurons [MALAT1 was downregulated, which led to an increase in miR-30a miRNA and, in consequence, inhibition of autophagic pathways [MALAT1 levels were significantly elevated in the hippocampi of rats with epilepsy, and its downregulation exerted a protective effect on neuronal survival [MALAT1 is upregulated in the PD mouse model, and its ability to sponge miR-124 was one of the causes of neuronal apoptosis [MALAT1 was significantly decreased [MALAT1 might play contradictory roles, though at least some of them, e.g., MALAT1–miRNA interaction, might have a neuroprotective function [Several papers point to the importance of the regulatory role of  neurons . It alsopathways . MALAT1 survival . Similarpoptosis . On the ecreased . Its oveecreased . Thus, ifunction ,197.GOMAFU, also known as MIAT  or RNCR2 , was highly expressed in differentiating neural progenitor cells. In the mature brain, GOMAFU was detected in a subset of postmitotic neurons including retinal ganglion and amacrine cells of the retina, and pyramidal cells in the cerebral cortex layer V and CA1 region of the hippocampus. It formed distinct nuclear bodies but yet failed to colocalize with markers of known nuclear domains like PML and Cajal bodies, nuclear speckles, paraspeckles, or nucleolus. Therefore, the authors suggested that GOMAFU forms a new kind of nuclear domain embedded in the nuclear matrix. Unlike speckles and paraspeckles, GOMAFU body formation and maintenance were not dependent on transcriptional activity. Later studies have suggested that GOMAFU is involved in the regulation of several neuronal processes like retinal cell fate specification [GOMAFU expression did not present any developmental drawbacks but exhibited hyperactive behavior and sensitivity to psychostimulants, which was associated with an increased extracellular concentration of dopamine in the same brain region known to be involved in addiction [GOMAFU is downregulated in cortical neurons in the response to activation. Additionally, its decreased level was found in the cortical gray matter of the superior temporal gyrus of schizophrenia patients [GOMAFU lead to the alternative splicing patterns in transcripts of the synaptic plasticity-related genes. As GOMAFU was shown to bind splicing factors QKI and SRSF1 (serine/arginine-rich splicing factor 1), it is proposed to regulate alternative splicing of transcripts involved in neuronal activation and pathology of schizophrenia. Studies of the Nakagawa group [GOMAFU interaction with two other well-recognized splicing factors, SF1 and CELF3. Both proteins assembled into a novel nuclear domain, called by the authors CS bodies, which were sensitive to transcription inhibition and RNAse treatment. Surprisingly, despite the dependence between the expression of CELF3 protein and transcription of GOMAFU, CS bodies did not contain GOMAFU RNA itself. All the aforementioned publications point out the activity-dependent function of GOMAFU in the postmitotic neurons. Even though the exact molecular pathways are poorly recognized, this abundant lncRNA, which forms a unique nuclear domain in a specific subset of mature neurons, plays an important role in the regulation of genes involved in neuronal plasticity.The study of Sone and colleagues  showed tfication , neuronafication ,201, thefication , and cogfication ,203. Morfication . Knockouddiction . Transcrpatients . The loswa group ,206 seemIn summary, we have described how lncRNAs shape the neuronal nucleus architecture and stand behind its dynamic plasticity. In the context of neuron-related diseases, we discuss how lncRNA imbalances might contribute to the pathological phenotype by affecting the organization of subnuclear domains. It is not yet clear how nuclear architecture translates to gene expression, but accumulating data point to a link between them.The significance and exact molecular mechanisms underlying lncRNA function in neuronal plasticity are still far from understood. Altogether, these studies indicate that lncRNAs and RNA binding proteins reside in specific nuclear compartments that dynamically respond to neuronal stimulation.


Drosophila melanogaster, the bithorax Hox cluster contains three Hox genes , along with a number of lncRNAs, most with unknown functions. Here, we investigated the function of a lncRNA, lncRNA:PS4 that originates in the second intron of Ubx and is transcribed in the antisense orientation to Ubx. The expression pattern of lncRNA:PS4 is complementary to Ubx in the thoracic primordia, and the lncRNA:PS4 coding region overlaps the location of the large insertion that causes the dominant homeotic mutation Contrabithorax-1 (Cbx-1Ubx), which partially transforms Drosophila wings into halteres via ectopic activation of Ubx. This led us to investigate the potential role of this lncRNA in regulation of Ubx expression. The Cbx-1Ubx mutation dramatically changes the pattern of lncRNA:PS4, eliminating the expression of most lncRNA:PS4 sequences from parasegment 4  and ectopically activating lncRNA:PS4 at high levels in the abdomen . These changes, however, did not lead to changes in the Ubx embryonic transcription pattern. Targeted deletion of the two promoters of lncRNA:PS4 did not result in the change of Ubx expression in the embryos. In the genetic background of a Cbx-1Ubx mutation, the lncRNA:PS4 mutation does slightly enhance the ectopic activation of Ubx protein expression in wing discs and also slightly enhances the wing phenotype seen in Cbx-1Ubx heterozygotes.Long noncoding RNAs (lncRNAs) have been implicated in a variety of processes in development, differentiation, and disease. In  Xist which controls female X chromosome inactivation in mammals  are a ubiquitous group of RNA transcripts that are over 200 nucleotides long, do not code for potential proteins or peptides longer than 100 amino acids, and are transcribed from a variety of genomic locations, including enhancers, promoters, and intergenic regions . Such lnHox genes—evolutionarily conserved complexes of genes coding for homeobox-containing transcriptional factors that control axial patterning in bilateral animals  contains three Hox genes: Ultrabithorax (Ubx), abdominal-A, and Abdominal-B, as well as many noncoding RNAs  insertional mutation (Contrabithorax is a dominant mutation that results in a transformation of some adult structures of the second thoracic segment (T2) into those of the third thoracic segment (T3), e.g., transforming wings into halteres  and treated with Turbo DNA-free kit (Ambion) to remove DNA.We used 5′ and 3′ RACE  to determine the start and the end of in situ hybridization was performed as previously described (Ubx cDNA probe was generated from the BSUbx1a plasmid (Ubx nascent transcripts was prepared with a pBluescript plasmid clone that included the 5′-most 1.5 kb of the first intron of Ubx. The wingless probe was generated from a 3 kb clone in pBluescript plasmid (a gift from B. Cohen). lncRNA:PS4 transcription was detected via the M probe (upstream of Cbx-1Ubx insertion), or the X probe , using the protocol described in pCFD4 vector and its sequence was GGAGTAAATTTATCTGGCTCT . The guide RNA sequence targeting the “downstream” promoter was placed under the control of the U6:3 promoter and its sequence was GGTTCATTTCATTTGCCCAA . gRNA cloning was verified by sequencing.To generate a targeted deletion of the sequences encompassing both putative promoters of y1sc*v1; P{CaryP-v+}attP40/CyO] were crossed to females carrying Vasa-Cas9 transgene either on the X chromosome (Bloomington stock No. 52669) or on the third chromosome (Bloomington stock No. 51324) and the progeny of these crosses was back-crossed. To screen for the presence of the desired deletions, we PCR-amplified the region surrounding the lncRNA:PS4 promoters from whole-fly genomic DNA, followed by sequencing of the PCR fragments. One line of transgenic flies was isolated from the cross to a female with a Vasa-Cas9 transgene on the third chromosome. This line has a 324 bp deletion that eliminates both the upstream promoter and the downstream promoter of lncRNA:PS4. Homozygotes for this deletion chromosome survive to adulthood at 5% the expected frequency, although this effect on viability does not map to the 324 bp deletion or to the Ubx region, as the chromosome with the small deletion is fully viable when crossed to a chromosome bearing the 109Ubx mutation [109Df(3R)Ubx], which deletes the entire Ubx locus.Transgenic lines carrying the gRNA construct were generated by BestGene Inc . Males of this gRNA line  were obtained from Bloomington Drosophila Stock Center (stock No. 3433). This fly strain has had the deletion for the pbx/bxd region crossed away from the insertional Cbx-1Ubx mutation, so is wild type for sequences upstream of the Ubx transcription unit. Cbx-1Ubx adult wing phenotypes were assessed in Cbx-1/TM3SbUbx flies that were obtained by crossing Cbx-1/TapXa, apXaUbx flies to lncRNA:PS4ΔP/TM3Sb flies; the resulting Cbx-1/TM3SbUbx flies were maintained as a stock. Ubx protein expression in the wing discs of Cbx-1Ubx heterozygotes was assessed in Cbx-1/TM3Sb, Kr-GFPUbx, obtained via the cross of Cbx-1/TapXa, apXaUbx flies to the lncRNA:PS4/TM3Sb Kr-GFP fliesCbx-1/TM3Sb. Ubx and Cbx-1/TM3Sb, Kr-GFPUbx flies had identical wing phenotypes3. Pc mutant flies  were obtained from Bloomington Drosophila Stock Center (stock No. 106475). Cbx-1/Pc3Ubx flies were obtained via a cross between 3),Pc3/TM1ln(3R)P, separated by 116 bp and located 14,299 and 14,182 bp downstream of the transcription start site of Ubx, respectively. Promoter site 2 is preceded by a good match, TCATTT, to the Drosophila InR promoter consensus sequence of TCAGTY . The predicted length of lncRNA:PS4 transcription unit was 9833 bp for transcripts starting from promoter P1 and 9715 bp for transcripts starting from promoter P2.Using 5′ RACE, we determined that f TCAGTY . Promotef TCAGTY  also incf TCAGTY . Promotef TCAGTY . In our lncRNA:PS4 transcript contains no introns. The only potential protein coding region identified by PhyloCSF in the lncRNA:PS4 transcript could in theory encode a 39 amino acid peptide, MLQMPTVKTKVPCCHFMNCFCSVGKSTTLTLATHKVLPS apXa, apXa flies (Bloomington). This allowed us to map the Cbx-1Ubx insertion location to position 16,721,339 of Chromosome 3R . Thus, the Cbx-1Ubx insertion is located within the lncRNA:PS4 transcribed region, 1.06 kb downstream of the lncRNA:PS4 P2 transcription start site.In order to determine the exact location of Cbx-1Ubx insertion profoundly changes the extent and the pattern of lncRNA:PS4 embryonic transcription , apparently because of an additional mutation elsewhere on the third chromosome, since trans-heterozygotes of the lncRNA:PS4 promoter deletion over a deletion of the Ubx locus [109Df(3R)Ubx], resulted in viable adults at approximately wild-type frequencies. We then examined if the deletion of lncRNA:PS4 promoters resulted in ectopic activation of Ubx protein in larval wing discs, or in wing abnormalities. The wing discs and the wings of the surviving homozygous adults were similar to those of flies heterozygous for the deletion and contained no wing deformations  mutants enhance the amount and extent of Ubx expression in the wing disc of Cbx-1Ubx mutants , these inconsistent findings might be explained by the different genetic backgrounds in which HOTAIR mutant alleles were tested. As described here, the function of lncRNA:PS4 transcripts also seem sensitive to genetic background, as lncRNA:PS4 mutant animals only exhibit ectopic expression of Ubx and abnormal wing shapes in the background of a Cbx-1Ubx mutant allele. In some respects, the Materials and Methods section are listed in the Reagents Table. The GenBank accession number of lncRNA:PS4 is OK501974.Strains and plasmids are available upon request. Reagents and primer sequences not included in the G3 online.This research was supported by NIH grant R01HD28315 to W.M. The authors declare that there is no conflict of interest.jkab374_Supplementary_Figures-TablesClick here for additional data file.jkab374_Supplementary_DataClick here for additional data file.


Methodological advances in conformation capture techniques have fundamentally changed our understanding of chromatin architecture. However, the nanoscale organization of chromatin and its cell-to-cell variance are less studied. Analyzing genome-wide data from 733 human cell and tissue samples, we identified 2 prototypical regions that exhibit high or absent hypersensitivity to deoxyribonuclease I, respectively. These regulatory active or inactive regions were examined in the lymphoblast cell line K562 by using high-throughput super-resolution microscopy. In both regions, we systematically measured the physical distance of 2 fluorescence in situ hybridization spots spaced by only 5 kb of DNA. Unexpectedly, the resulting distance distributions range from very compact to almost elongated configurations of more than 200-nm length for both the active and inactive regions. Monte Carlo simulations of a coarse-grained model of these chromatin regions based on published data of nucleosome occupancy in K562 cells were performed to understand the underlying mechanisms. There was no parameter set for the simulation model that can explain the microscopically measured distance distributions. Obviously, the chromatin state given by the strength of internucleosomal interaction, nucleosome occupancy, or amount of histone H1 differs from cell to cell, which results in the observed broad distance distributions. This large variability was not expected, especially in inactive regions. The results for the mechanisms for different distance distributions on this scale are important for understanding the contacts that mediate gene regulation. Microscopic measurements show that the inactive region investigated here is expected to be embedded in a more compact chromatin environment. The simulation results of this region require an increase in the strength of internucleosomal interactions. It may be speculated that the higher density of chromatin is caused by the increased internucleosomal interaction strength. Conformation capture techniques are limited to measuring contact probability. Here, we focused on a complementary aspect by measuring physical distances of loci, with a genomic distance of ∼5 kb in single cells. This range of distances of approximately 100 nm is crucial for mediating the physical contact of transcription factors and other regulatory elements. Microscopy data delivered the complete distance distribution of two prototypic regions with regulatory active and inactive chromatin, respectively. Unexpectedly, we found very broad distributions of distances in both regions. Computer simulations of a coarse-grained model of these regions showed that the variance of the single-cell measurements can be explained only by the combinations of different influencing factors. This emphasizes the large cell-to-cell variance in the processes regulating chromatin compaction even in inactive regions.For almost 100 years, it has been known that interphase chromatin can be distinguished by means of light microscopy into less dense euchromatin and denser packed heterochromatin . Later, The landscape of chromatin states is much more diverse than the originally described euchromatin and heterochromatin suggest. By analyzing genome-wide distribution patterns of chromatin-associated proteins, posttranslational histone modifications and DNase I hypersensitivity with algorithms such as ChromHMM and Segway, investigators have proposed up to 51 chromatin classes , 20, 21.Posttranslational histone modifications of the active chromatin classes, such as acetylation, may reduce nucleosome interaction strength and thus participate, among other mechanisms such as through ATP-dependent remodelers, in producing an open, less densely packed chromatin , 27, 28.A remarkable feature of chromatin is its dynamic nature, which has been observed in several fluorescence imaging studies , 39, 40 Computational studies show a close link between nucleosome positions and the spatial organization of chromatin , which wIn our research, we investigated structural differences between active and inactive 5-kb chromatin segments of prototypical chromatin regions, selected on the basis of the presence or absence of DNase I hypersensitivity, using oligonucleotide-based fluorescence in situ hybridization (oligoFISH). By measuring the distance between labeled endpoints with systematic 3D stimulated emission depletion (STED) microscopy and comparing these data with Monte Carlo simulations of a coarse-grained model ,54, we aFor a more detailed description of the methods and procedures described in this section, please refer to the supporting material2 and regularly tested for mycoplasma contamination.Human erythroleukemia K562 cells (ATCC: CCL243) received from the Stamatoyannopoulos lab were grown in RPMI 1640 medium  supplemented with 10% fetal bovine serum  and 1% v/v penicillin/streptomycin  in cell culture flasks. Cells were cultured at 37°C in a humidified atmosphere containing 5% COUniversally active and inactive genomic regions were assessed by using the index of consensus DHSs of Meuleman et al.  derived Oligonucleotide probes for STED microscopy: We tiled 30 non-overlapping oligonucleotides (40-mers) across each target region (1.5–2 kb), selected for uniqueness and a higher density than afforded by other published design tools optimized for whole-genome coverage or chromosome walking , 57, 58.supporting materialSTED microscopy was carried out on a 3D STED microscope  equipped with 2 pulsed excitation lasers , 1 pulsed depletion laser , and Avalanche photodiodes for detection. A 100× UPlanSApo 1.4 NA oil immersion objective  was used for all of the acquisitions. Pairs of FISH spots labeled with different dyes were detected in confocal scans, and high-resolution STED detail stacks were acquired only around these points of interest.Supervised machine learning was used as a quality control step to automatically classify STED stacks into “good” or “bad.” Detailed spot analysis was performed on the analyzable good data to determine the coordinates of both FISH spots in their respective STED channels. The algorithm searched for the spot pair with the brightest signal by using a Laplacian-of-Gaussian blob detector and saved their subpixel coordinates derived from fitting a multidimensional Gaussian using the Levenberg-Marquardt algorithm for further statistical analysis. For measurements with 2D depletion, 3D coordinates were transformed into projected 2D coordinates by omitting the z coordinate.Simulation software: The software was developed in the Wedemann group in the last few decades and used in many studies. It was written in C++ and was adapted for the use of shared-memory parallel architectures according to the OpenMP standard. The replica exchange algorithm was implemented for distributed memory architectures using Message Passing Interface. The software cannot be made public at the moment, since it contains code under copyright by other parties.M replicas of the system were simulated with Metropolis MC simultaneously, each at a different temperature, Ti. After a fixed number of MC simulation step replicas with adjacent temperatures , the temperature is swapped with the probability  algorithm was used to create a statistically relevant set of configurations satisfying the Boltzmann distribution . To overbability :(1)min[1approach . This alapproach . Simulat6 MC steps and 90 × 106 steps for 6 kT per replica after simulated annealing. For checking the convergence, we analyzed the end-to-end distance and the energy as parameters. To determine the point when equilibrium was reached, we analyzed visually the plots with the number of steps on a logarithmic scale. Only configurations after that point were used in the analysis. From analysis of the autocorrelation of energy and end-to-end distance, we estimated that configurations are uncorrelated after 10 × 103 steps for systems with 4-kT maximum interaction strength and 20 × 103 steps for 6 kT  was calculated by minimizing the squared differences between the bins of a histogram of the microscopically measured FISH spot distances (A) and a linear combination of the histograms of simulation results with varying nucleosome occupancies (B–G). Quadratic programming (via the quadprog package in R) was used to find a solution in which the contributions of the individual simulations are non-negative and equal 1.A mixture histogram H was caistances A and a upancies B–G. Qua∗ 0.34 nm (size of 1 base)/7 /7 . For 5-khttps://doi.org/10.17605/OSF.IO/ZJWXM. Simulation trajectories are in an easily readable XML format  but also in more than 730 samples from human cells and tissues. Moreover, this region is flanked upstream and downstream by highly active chromatin. For inactive chromatin, the selection criteria were a minimal number of repetitive elements and missing DHS over 30 kb in more than 730 human samples. In K562 cells, the region without DHSs spans over 2 Mb. The selected 20-kb inactive region is also located on chromosome 11  (B). For each of these 20-kb regions, 5 oligoFISH probe sets  were designed, dividing the 20 kb into 4 approximately 5-kb-long segments from midpoint to midpoint of the respective probe set . Each oligoFISH probe set consisted of 30 oligonucleotides (directly fluorescently labeled 40mers) covering a region of approximately 1.5–2 kb (A and B). These small genomic distances are expected to result in spatial distances falling below the resolution limit of light microscopy . By using reconstituted chromatin, we showed that STED microscopy can resolve distances between the ends of chromatin consisting of ∼5 kb DNA and up to 25 nucleosomes  B. For e1.5–2 kb , A and Bcroscopy , which icroscopy . Using Sleosomes . The disA; B and Recent studies reveal a high cell-to-cell variance of the spatial genome organization , 70, 71.C). Shorter double spot distances indicate a higher degree of chromatin compaction, whereas larger distances suggest less compaction. Thus, data from our measurements are in line with published data showing active chromatin to be less compacted compared to inactive chromatin . Both regions do not show CCCTC-binding factor (CTCF) binding sites and are therefore not anchors for chromatin loops.For a more in-depth analysis, we selected a 5-kb segment for both the active and inactive regions, which are representative of the respective group in 2D STED measurements. We chose interval AB for the active region and CD for the inactive region , A and BGSM920557). These data are unsuitable for our coarse-grained model, as it requires non-overlapping unique nucleosome positions as input. Therefore, we computed the most probable non-overlapping nucleosome populations by applying the NucPosSimulator (A and B. Nucleosome positions of the respective flanking regions can be found in C) . Both values are in the range of the NRL of chromosome 11. To cross-check the effects of possible inaccuracies in the positions of the nucleosomes, additionally we determined the nucleosome positions for both regions and flanking regions from lymphoblastoid cell lines , we have used a value from the upper range of the literature values (6 kT) to simulate this chromatin type. Conversely, the active region features many posttranslational histone modifications (A), and we thus used a lower value (4 kT) to compute the respective configurations.The strength of the internucleosomal energy is another important parameter in all coarse-grained models and depends on the solvent  and histications A, and wThe microscopic data shown so far are 2D data, which underestimate the real 3D distances between the FISH spots since the cells are expected to be rotated randomly relative to the optical axis of the microscope. Only 3D single-cell microscopy allows the study of real distances between 2 spots on a single-cell level and to compare data between microscopy and simulation. Therefore, we performed 3D STED measurements, which require careful correction for refractive index mismatch between the immersion fluid of the objective lens and the embedding medium . The computed distribution was narrower, and the mean distance was approximately a standard deviation shorter than the microscopically measured distribution (B).The 3D STED measurements for the 5-kb AB interval in the active chromatin region revealed distances ranging from <50 to 250 nm, with a mean distance of 115 nm . The same was done by replacing two (D), three (E), four (F), and five (G) nucleosomes according to the rank order of the nucleosome occupancy signal. In fact, a reduction of the total nucleosome number resulted in increasingly larger mean distances, but none of the individual distributions were comparable with the microscopically measured distribution. By applying a least squares fit, the different distance distributions were combined and resulted in a mixed distance histogram that mimics the microscopic data better than each of the underlying histograms, as indicated by a reduction in the root mean square error (H) (see I and J). These configurations show local accumulations of a few nucleosomes connected by stretches with low nucleosome occupancy. These structures are remarkably similar to recently published light and electron microscopic data of interphase chromatin (K and L). Linker histone H1 does not change the distance distributions in this case either (I and J).We hypothesized that in the cell population used for the microscopy experiment, the number of bound nucleosomes varies from cell to cell. This hypothesis was tested by computer simulations, in which the least probable nucleosomes were removed. To find the nucleosomes with the lowest occupancy signal, we analyzed the mean value from the occupancy data calculated by NucPosSimulator , three E, four E), four F, and fand five G nucleore error H (see M (H) see . Visuali (H) see , I and Jhromatin ,14,78. Thromatin , K and Le either , I and JA process that is obviously accompanied by major changes in chromatin structure and in which nucleosomes are also temporarily removed from the chromatin structure is DNA replication in the S phase of the cell cycle. Fluorescence-activated cell sorting of cells with fluorescently labeled DNA was used to generate G1, S, and G2 phase fractions for further analysis . MicroscA). Similar to the active chromatin, the histogram of the inactive region also contains large distances that cannot be explained by replicating DNA (A and B). As argued earlier, an increase in the interaction energy to 6 kT seems to be more realistic for simulating inactive chromatin. This approach delivered configurations with the mean value of the simulated distance distribution in the correct range but symmetrical and not skewed to smaller values (C). Obviously, additional mechanisms compact the inactive chromatin of the investigated region.Microscopic data of the inactive region CD show the expected shift of the histogram to shorter distances, indicating more condensed chromatin A. Similting DNA . 3D STEDting DNA , A and Br values C. ObvioGenome-wide data on the level of H3K9me3 (GEO: GSM733776) and H3K27me3 (GEO: GSM733658) histone modifications show in the inactive region CD only background levels, which can be found throughout the genome. Also, repetitive DNA sequences (RepeatMasker) are not enriched. The levels of these markers are significantly lower than in regions known to be compacted by heterochromatinization or by binding the Polycomb group proteins. Therefore, other mechanisms must be considered, such as the binding of linker histone 1 (H1), which has long been known to have a chromatin-compacting effect ,79. H1 iD) and 43 nm less for 6 kT (E). To explore the effects of different stoichiometry of H1, we performed computer simulations of a random 50% nucleosome binding (1:2). Here, the compaction is less pronounced, and the mean is approximately 12 nm smaller than without H1 (F). Visualizations of exemplary simulated configurations are shown in G–I.In fact, simulations with a stochiometric H1 to nucleosome ratio of 1:1 led to more compact configurations, with a mean value of 27 nm less for 4 kT D and 43for 6 kT E. To exthout H1 F. VisuaIn summary, similar to the active region the experimental data of the inactive region can only be explained by a cell-to-cell variability but including a stronger internucleosomal interaction and binding of H1.By using high-throughput super-resolution microscopy, we studied the nanoscale organization of 5-kb chromatin segments that are located in regulatory active and inactive chromatin. The data shown here contain information that differs for fundamental reasons from that of published conformation capture data sets such as Hi-C. While microscopy measures the physical distances between genomic loci, conformation capture methods assess how often direct contacts between genomic elements occur . Most coIn both active and inactive chromatin, 3D spatial distances between the endpoints of the 5-kb segments differ from cell to cell, resulting in a broad distance distribution, with the mass of the distribution shifted more to shorter values in inactive chromatin. In contrast, simulations with different nucleosome occupancies, changed strength of the internucleosomal energies, or deviations from stoichiometric H1 binding led to far narrower distance distributions. Therefore, the large width of the distance distribution seems to be a feature that is caused by the summation of cell-to-cell differences in the resulting histogram.A), a result that is consistent with genome-wide measurements  While at certain positions nucleosomes are positioned with high precision , nucleosFor most of the 1600 known transcription factors , there aAs described earlier, the microscopic measurements of inactive chromatin revealed a compaction that can be explained by an increase in the strength of internucleosomal interactions and by the additional introduction of the linker histone H1. Microscopic measurements showed that the inactive region investigated here is expected to be embedded in a more compact chromatin environment . It can B also show weakly bound nucleosomes in this chromatin class, but this does not exclude further mechanisms causing elongated chromatin configurations. Regardless, the large variation in physical distances between spots with a genomic distance of 5 kb from cell to cell suggests that inactive chromatin is also subject to continuous reorganization.Similar to the active regions, microscopic data of the inactive region also show elongated chromatin configurations (>200 nm) in individual cells. In analogy to active chromatin, this could indicate variable nucleosome occupancy in inactive chromatin as well. In fact, the data shown in in vivo more variety exists . The properties of these systems are expected to be in the range of the already-broad range of different simulated systems presented here.In each computer simulation, a system has a certain number of nucleosomes, amount of bound H1, and internucleosomal interaction strength. It can be expected that A and A). Apparently, thermodynamically driven spontaneous movements can bring regulatory elements into close contact with their promoters that are only a few kilobases distant from one another. Considering that in the human genome, 142,000 enhancer-like elements fall within 2 kb from the nearest transcription start site  on chroart site , such spA, A, B–J; B–I; D; and B–L). The manuscript was written by H.H. and G.W., with support from all of the authors.This study was conceived and supervised by H.H., G.W., J.A.S., and H.L. K.B. performed all of the microscopic experiments, including sample preparation and STED imaging shown in


TERT promoter mutation and tumorigenesis of UC. Also, TERT promoter mutation has great potential for diagnosis, as well as prognosis in UC treatment, and this is also applicable for the liquid biopsy techniques. In this review, we discuss the progress in these areas and highlight the challenges, clinical potential, and future direction for developing UC treatment methods.Urothelial carcinoma (UC) is a common urological malignancy with a high rate of disease recurrence. Telomerase activity, a hallmark of cancer characterized by overcoming the replicative senescence, is upregulated in over 90% of patients with UC. Somatic mutations in the promoter region of telomerase reverse transcriptase (TERT) are frequently detected in UC, and drive telomerase activity. Recent studies have demonstrated a strong association between  FGFR3 or TP53 mutations, the promoter of telomerase reverse transcriptase (TERT) is among the most frequently mutated genomic region in UC tissue  are reported in the bladder , and upper tract urothelial carcinoma (UTUC) that occurs in the renal pelvis or ureter corresponds to a small subset of UC . UBC is C tissue , 9. BecaC tissue , 11. Alttability –14, and tability . In thisin situ hybridization technique, whereas telomere length variability was prevalent in bladder cells with either short or long telomeres  or upregulating TERT , and C250T (g.1295250 C>T in GRCh37). These two hotspot C to T transitions are typically heterozygous and form the same 11 base pair sequences of “CCCCTTCCGGG” , melanoma (71%), UBC (67%), UTUC (47%), and hepatocellular carcinoma (HCC) (44%)  (44%) . Conversutations . Althougmelanoma –28, gliomelanoma , HCC  creates a de novo binding site of GA-binding protein A (GABPA), an E-twenty-six (ETS) family transcription factor, in close proximity to a native ETS binding site in the wild-type TERT promoter  and acetylation (H3K9Ac), and promotes GABPA binding to this region , amplification of this region using PCR is more challenging than that of the genomic regions in the exome. To amplify these regions efficiently, some additives are used to prevent non-specific amplification of products during PCR.Therefore, the genetic analysis using these techniques can provide useful molecular information and offer various advantages not only as a non-invasive biomarker, but also as an early indicator of minimal residual disease, recurrence, drug resistance, or metastasis. Therefore, it is believed to replace the tissue needle biopsy technique in the near future . Liquid requency . UROSEEK and MLL . We demoCR assay , 62. SinTERT promoter mutation in plasma or urine specimens from patients with UTUC or UBC. The sensitivity of TERT promoter mutation assessed using urine liquid biopsy was relatively high, ranging from approximately 50% to 70% for UBC and 30–50% for UTUC   , suggestle tumor . Additiofor UTUC , 62. ForTERT promoter mutation in plasma cfDNA ranged from 10–23% in metastatic UBC and 17% in metastatic UTUC  located at the distal region of the promoter. This interesting distinct methylation pattern indicates that the core promoter region and THOR are functionally different loci regulating TERT . IN-5401 and INO-9012 are both mixtures of synthetic plasmids, including TERT antigen. Peptide vaccines have been used in various clinical trials with limited success. Since various reports indicate that TERT promoter mutations in UC is gradually being well defined. There are growing evidences that TERT promoter mutation followed by genomic instability is a key step in the tumorigenesis of UC. Furthermore, the detection of TERT promoter mutations in bodily fluids using liquid biopsy is a potential biomarker for UC diagnosis as well as prognosis. Although larger prospective studies are required, liquid biopsy targeting TERT promoter mutation might make a significant contribution to improve the prognosis and quality of life of patients with UC in the near future.The biological function of Conception and design: all authors. Administrative support: KF. Provision of study materials or patients: all authors. Collection and assembly of data: YH. Data analysis and interpretation: YH. Manuscript writing: YH. All authors contributed to the article and approved the submitted version.This study was supported by Osaka University Grant, and JSPS KAKENHI Grant Number JP 20K18139.GN: Equity or royalty from the licensed technologies from Johns Hopkins that are related to the work described in this paper.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.