It is unknown whether these elements are important at a genome-wide level and whether other mRNA features proximal to the stop codon significantly affect termination and readthrough efficiencies in vivo. Accordingly, we carried out ribosome profiling analyses of yeast cells expressing wild-type or temperature-sensitive eRF1 and developed bioinformatics strategies to calculate readthrough efficiency, and to identify mRNA and peptide features which influence that efficiency. We found that the stop codon (nt +1 to +3), the nucleotide after it (nt +4), the codon in the P site (nt -3 to -1), and 3’-UTR length are the most influential features in the control of readthrough efficiency, while nts +5 to +9 had milder effects. Additionally, we found low readthrough genes to have shorter 3’-UTRs compared to high readthrough genes in cells with thermally inactivated eRF1, while this trend was reversed in wild-type cells. Together, our results demonstrated the general roles of known regulatory elements in genome-wide regulation and identified several new mRNA or peptide features affecting the efficiency of translation termination and readthrough.Translation of mRNA into a polypeptide is terminated when the release factor eRF1 recognizes a UAA, UAG, or UGA stop codon in the ribosomal A site and stimulates nascent peptide release. However, stop codon readthrough can occur when a near-cognate tRNA outcompetes eRF1 in decoding the stop codon, resulting in the continuation of the elongation phase of protein synthesis. At the end of a conventional mRNA coding region, readthrough allows translation into the mRNA 3’-UTR. Previous studies with reporter systems have shown that the efficiency of termination or readthrough is modulated by  Of the 64 codons that exist for translation of the genetic code into a polypeptide chain, only UAA, UAG, and UGA signify termination of continued protein synthesis. However, the efficiency of translation termination is not the same for different mRNAs and is likely influenced by mRNA sequences proximal to these “stop” codons. Here, we sought to expand current understanding of termination efficiency by measuring termination failures, or “readthrough” on a genome-wide scale. Our analysis identified novel mRNA features that may regulate the efficiency of readthrough, including the identities of the stop codon, the penultimate codon, the proximal nucleotides, and the length of the mRNA 3’-untranslated region. As ~11% of human genetic diseases are caused by mutations that introduce premature stop codons, resulting in both accelerated mRNA decay and truncated protein products, our findings are valuable for understanding and developing therapeutics targeting premature termination of mRNA translation. Translation of an mRNA into a polypeptide is terminated when the release factor eRF1 interacts with a UAA, UAG, or UGA stop codon in the ribosomal A site and another release factor, eRF3, hydrolyzes GTP and stimulates the polypeptide release activity of eRF1 –6.cis-acting mRNA sequences.The process of readthrough was first characterized primarily in viruses, which utilize this mechanism to increase the protein-coding capacity of their compact genomes ,8. It iscis-acting elements [in vivo. Transcriptome-wide ribosome profiling studies of flies, human, and yeast cells have detected readthrough of individual mRNAs [cis-acting mRNA sequences have only been minimally investigated.Previous studies on termination using reporter systems mainly relied on the inverse relationship between termination and readthrough efficiencies, where the level of readthrough protein product was quantified to infer the efficiency of termination. These studies have shown that the extent of readthrough, and thus the efficiency of termination, is modulated by multiple elements ,5,22. Thelements ,23. Nuclelements ,25 and uelements ,16,26–28elements ,20,26,29al mRNAs ,21,30–32in vitro and in vivo [While the stop codon and its immediate 3’ flanking sequences have been studied quite extensively, with structural evidence showing certain nucleotide preferences for optimal interactions with eRF1 motifs and rRNAs ,33,34, o in vivo –38. ThesAccordingly, we have carried out ribosome profiling of yeast cells expressing a wild-type or temperature-sensitive mutant allele of eRF1 (Sup45 in yeast) and developed bioinformatics strategies to measure readthrough efficiency of individual mRNAs on a genome-wide scale, and to identify mRNA and peptide features which influence that efficiency. Our results demonstrated the general roles of known regulatory elements, such as the identities of the stop codon and the surrounding nucleotides, in genome-wide regulation and identified several new mRNA features that appear to play a role in translation termination and readthrough, including the penultimate codon in the P site (when a stop codon is in the A site) and the length of the 3’-UTR.sup45-2 (subsequently referred to as sup45-ts) mutation that minimally affects eRF1 function when cells are grown at 25°C, but renders eRF1 inactive within 30 minutes of growth at 37°C [r) of 0.98 and 0.99 on average for ribosome profiling and RNA-Seq, respectively  and eRF1 mutant yeast cells. The latter harbor the  at 37°C . Reads bectively . In addiectively . For comectively . In thesSUP45 cells at 25°C indicated that, with the stop codon in the A site, termination was completed, and ribosomes were dissociated from the mRNAs before they could be captured. The presence of footprints at this position in sup45-ts cells at 25°C suggested that the mutation slowed down termination enough for the ribosomes to be captured. When eRF1 was inactivated in sup45-ts cells grown at 37°C, or depleted in sup45-d cells, a high number of footprints was observed at the penultimate codon, indicating that ribosomes were stalling as they awaited successful termination. Similarly, the high number of footprints in rli1-d cells was also consistent with ribosome stalling, as the stop codon had entered the ribosomal A site, but a factor needed for successful recycling was lacking. Additionally, the peaks at approximately 30 nt upstream of the stop codon in sup45-ts cells at 37°C and sup45-d samples identified ribosomes stacking against those stalled at the stop codon. As a consequence of failed termination or recycling, the mutant libraries, especially from the sup45-ts cells at 37°C, had increased footprint reads in the 3’-UTR region compared to those of WT samples (sup45-ts cells at 37°C) and depletion (sup45-d) of eRF1 both caused loss of eRF1 function, these two different strategies likely resulted in loss of eRF1 function to different extent and yielded slightly different metagene profiles. While the sup45-ts strain lost normal eRF1 function within 30 minutes of the temperature shift, the sup45-d strain needed 9 hours of growth after transcription shutoff to gradually dilute the functional eRF1 protein level. In eRF1 depleted cells, although the level of functional eRF1 was significantly decreased, small amount of eRF1 still existed and was fully capable of promoting termination. The residual functional eRF1 in sup45-d cells likely resulted in a diminished quantity of 3’-UTR reads compared to those obtained with the sup45-ts strain. In addition to increased reads near the stop codons, all the mutant samples also showed increased footprint reads at the start codon and decreased footprint reads in the CDS compared to their WT counterparts. These observations are in agreement with the notion that termination and recycling steps are linked to translation initiation [To explore the consequence of eRF1 inactivation on translation, ribosome footprints were mapped relative to their respective start or stop codons based on their P-site locations and quantified . In all  samples , insets,ade2-1 and can1-100, contain premature termination codons (PTCs). Their gene specific profiles revealed an accumulation of ribosomes 5’ to the respective PTCs and increased ribosome density in the part of the CDS following the PTCs in sup45-ts cells grown at 37°C (compared to sup45-ts at 25°C or to WT cells at either temperature) .We also examined the effects of eRF1 inactivation on premature translation termination. Two alleles in our strain background, erature) . This oberature) . For thend RPS0A . Intron-sup45-ts cells grown at 37°C to be higher than that of their WT counterparts. Indeed, we saw that frame 0, which was dominant in the CDS, was also dominant in the extension, but not in the distal 3’-UTR of most strains , and the rest of the 3’-UTR  . If read strains . It is nterparts . On the nterpart . These rcis-acting effects of neighboring sequences to the readthrough of stop codons.In summary, the increased in-frame footprints in the extension region of the 3’-UTR in eRF1 mutants indicated that a lack of functional eRF1 led to stop codon readthrough globally. Hence, we developed formal criteria for the quantitation of readthrough of individual mRNAs and a bioinformatic scheme to assess the genome-wide positive and negative To dissect the relationships between readthrough efficiency (Y variable) and mRNA or nascent peptide features (X variables), we used the random forest machine learning approach ,45 to fiet al. (2020) [Since termination efficiency is not directly measurable by ribosome profiling we calculated readthrough efficiency and utilized the generally inverse relationship of termination and readthrough  ) to infeAdditional sources of noise in the data include: 1) poorly-expressed genes that result in an exaggeration of the readthrough efficiency ratios and 2) genes lacking footprints in the 3’-UTR region, for which it was challenging to distinguish lack of readthrough from insufficient sequencing depth. Inclusion of these genes confounded previous analyses and led to conflicting results. For instance, genes belonging in the “leaky” set  were highly expressed compared to genes in the “non-leaky set” (genes lacking 3’-UTR reads), but within the “leaky” set, readthrough rate was negatively correlated with gene expression . TherefoTo date, mRNA features affecting stop codon readthrough have frequently been identified 3’ of the stop codon, but we also considered the possibility that mRNA sequence on the 5’ side of the stop codon and the nascent peptide in the exit tunnel may contribute to variations in readthrough efficiencies . These fsup45-ts at 37°C, readthrough efficiency was negatively correlated with gene expression and codon optimality, consistent with previous results [Other than the mRNA features listed in  results ,31. This results , we coulIn order to identify without bias the mRNA and nascent peptide features affecting readthrough efficiency, we used two independent approaches involving the random forest algorithm ,45: 1) rTo determine which of the X variables were most responsible for the predictions, we permuted each X variable for the regression and classification models and assessed its importance by calculating either percent increase in mean squared error (%IncMSE) or Mean Decrease Accuracy (MDA). %IncMSE is the calculation of percent increase in prediction error, while MDA is the percent increase in misclassification, when the X variable was permuted. Thus, the higher the %IncMSE or MDA value is for an X variable, the more critical that variable is in predicting readthrough efficiency. We performed hierarchical clustering of these values across samples and found that in general, the eRF1 mutants were more similar to each other than to other strains in both regression and classification approaches .rli1-d, suggesting that they may play a role in recycling; however, this is only true in the classification model.In order to determine which X variables exhibited meaningful %IncMSE or MDA values, we established their baselines (negative controls) by randomly assigning one numeric value between 1–100 (random number) and one of four categorical values (random factor) to each gene before model training. Because the assignment was random, these two variables should have no influence on the prediction. Indeed, random number and random factor were among the X variables with %IncMSE and MDA values close to zero . Reassursup45-ts at 37°C and sup45-d samples. This observation is due to ribosome pile-up at those stop codons, as with canonical stop codons , and 3’-UTR length as mRNA features that control genome-wide readthrough efficiency.Previous studies using synthetic dual reporters have shown that the UGA stop codon and certain nucleotides at positions -2, -1, +4 to +9 are the most permissive features for stop codon readthrough  5,8,16,,16,22–28rli1-d cells. For nt +4, genes with C at this position had significantly higher readthrough efficiencies, and those with G had slightly lower readthrough efficiencies. These observations are in line with previous data where C was reported to allow the most readthrough and G the least [The variables that showed the strongest pattern and significance were the stop codon and the nucleotide immediately downstream (nt +4). Consistent with the notion that UGA is the most readthrough-permissive stop codon and UAA is the strongest terminator , genes whe least ,23,26,27he least .For nucleotides further into the mRNA channel 3’ of the stop codon (nt +5 to +9), only nt +9 showed clear trends: genes with A had higher readthrough efficiencies , consistent with previous reports, and genes with U had lower readthrough efficiencies . At position +5, although the differences between groups’ readthrough efficiencies and overall readthrough efficiencies were not significant in every sample, genes containing adenine had a uniform pattern of higher readthrough efficiency compared to sample median (unlike random factor), indicating that A at nt +5 was relatively readthrough-permissive.Adenine at nt -1 and -2 has been shown to be readthrough-permissive ,25, but rli1-d sample did not match with other samples. In fact, some of them appeared to be the opposite. Since other samples, even the sup45 mutants, had wild-type Rli1, the opposite patterns in rli1-d sample may suggest that nt -3 and -2 (or the amino acid they encode) played a role in a ribosome recycling step rather than the termination step. This also influenced the number of ribosomes translated into the 3’-UTR in rli1-d, as shown in the feature importance plot . For data presentation purposes, the frequencies were converted into fractions and log2 ratios of “High” or “Low” groups to the reference were computed, as shown in the heatmap (2 ratio (red) indicates an over-representation while a negative log2 ratio (blue) indicates an under-representation of X in the group compared to reference. The patterns, especially those of the “Low” readthrough group, corroborated our previous approach . For nt +5, the pattern allowed us to extrapolate that following readthrough-permissive G, were increasingly readthrough-inhibiting A, U, and C (which was most associated with termination). This information was difficult to obtain in the dual reporter assays because readthrough events were so low that they were indistinguishable from each other. Information compiled for other nucleotide positions is shown in To see whether we could extract more comprehensive information on these nucleotides, we used a different approach involving only the “High” and “Low” readthrough genes used for the classification models. χ heatmap . A positapproach . For insapproach , and witapproach , C was ssup45-ts strain at 37°C where, unlike in other strains, genes containing UGAC did not have higher readthrough efficiency than the median , genes in the “High” readthrough group, or genes in the “Low” readthrough group . Similar to the C/GU case, UUA and UUC had the same pattern despite coding for different amino acids and were distinct from their respective synonymous codons.From this analysis, two particular nucleotide combinations were likely responsible for low readthrough efficiencies, namely the C/G and U combinations and the UU and A/C combinations. In the first group, CGU and GCU were codons that appeared in genes with significantly lower readthrough efficiencies in most samples even though they code for different amino acids and were clearly distinct from their respective synonymous codons. Remarkably, genes containing CUG (leucine), which had exactly the same nucleotide composition, showed higher readthrough efficiencies compared to sample median. These opposite trends suggested that not only specific combinations of nucleotides, but also specific positional arrangements have to be optimal for efficient termination. In the second group genes containing UUA and UUC had lower readthrough efficiencies but only in WT conditions  ,49, tRNAAt the other end of the spectrum, codons that appeared in genes with significantly higher readthrough efficiencies include AUA, ACA, ACC, CUG, and GAC. Arguments similar to those made for the low readthrough set of codons applied here. First, the amino acid identity could be ruled out. Although ACA and ACC encode the same amino acid (threonine), it could be ruled out as a possible mechanism because other threonine codons showed different patterns. All five codons did not share any tRNA properties in common; however, individualized nucleotide-tRNA property combinations could not be ruled out as possible mechanisms.2 test of independence to determine whether the P-site codons with prominent effects on readthrough efficiencies tended to appear in conjunction with particular stop codons. Although statistical analysis here suffered from small sample size and the results should be interpreted with caution, we could still observe a similar trend as seen with stop codon and nt +4 in that readthrough-inhibiting features attracted one another. We found the most readthrough-inhibiting P-site codons, CGU and GCU, coexisted more frequently with UAA than UAG or UGA stop codons  in the In summary, we identified four codons  associated with lower readthrough efficiencies and five codons  associated with higher readthrough efficiencies. It is unlikely that amino acid identity by itself is the reason for this observation; rather, specific combinations of nucleotide and tRNA properties likely influence termination and readthrough.in vitro [PAB1 gene in yeast, or extension of the mRNA 3’-UTR length downstream of a PTC, leads to inefficient termination and readthrough in vivo [sup45-ts cells at 37°C and sup45-d cells while a negative correlation was observed in the respective WT strains (Poly(A)-binding protein  has been shown previously to interact with eRF3, enhancing termination efficiency in vitro . Consist in vivo . Accordi strains . These r strains , our finIn this study, we analyzed ribosome profiling data of WT and mutant yeast strains defective in translation termination or ribosome recycling to identify mRNA or peptide features that influence readthrough efficiency at a genome-wide level. First, we characterized the phenotypes of eRF1 mutant cells, which included ribosomes stalling at start and stop codons and increased in-frame footprints in 3’-UTRs compared to wild-type cells Figs . We tookTwo novel mRNA features that we found to be major determinants of readthrough efficiency were the codon in the ribosomal P site (when a stop codon is in the A site) and 3’-UTR length. For the P-site codon , our results did not support previous conclusions of AA being the most readthrough-permissive nucleotides at position -2 and -1 ,24,25 whrli1-d cells but not in wild-type or eRF1 mutant cells  was derived from the wild-type strain (HFY114) [600 of the culture reached 0.6–0.8, its temperature was shifted as follows: Cells were collected by centrifugation at 5,000 rpm for 5 min at room temperature (RT) using a JA10 rotor in a Beckman Coulter Avanti J-E centrifuge, resuspended in 400 ml of fresh YPD media, transferred to a new flask, and incubated in a 25°C water bath with shaking. After 20 min of incubation, 400 ml of pre-warmed (57°C) YPD were added to the flask, and cells were incubated in a 37°C water bath for 30 minutes with shaking. As a control for the temperature shift procedure, the same protocol was carried out except that YPD was pre-warmed to 25°C and the subsequent 30-minute incubation was at 25°C.Yeast strains used in this study are in the W303 background. The temperature-sensitive (HFY114)  by the p600 between 0.6 and 0.8 were harvested by rapid vacuum filtration and flash-frozen in liquid nitrogen in the presence of Footprinting Buffer  plus 1% TritonX-100, 0.5 mM DTT, 1 mM phenylmethylsulfonyl fluoride (PMSF) and 1X protease inhibitors. Cells were lysed in a Cryomill (Retsch) at 5 Hz for 2 min, then 10 Hz for 15 min. Lysates were clarified by ultracentrifugation in a Beckman Coulter Optima L-90K Ultracentrifuge at 18,000 rpm for 10 min at 4°C, using a 50Ti rotor. Centrifugation was repeated for the supernatant at 18,000 rpm for 15 min at 4°C.Ribosome profiling and RNA-seq libraries were prepared as described previously in our library preparation protocol for immunoprecipitated ribosomes . BrieflyFor ribosome profiling , lysatesFor RNA-Seq, total RNAs were extracted from lysates using a miRNeasy kit , depleted of genomic DNA contamination using Baseline-Zero DNase , and depleted of rRNA using a Yeast Ribo-Zero Gold rRNA removal kit  according to the manufacturer’s protocol. Multiplexed cDNA libraries were prepared with a TruSeq Stranded mRNA sample prep kit  according to the manufacturer’s protocol and sequenced  on a NextSeq500.https://www.bioinformatics.babraham.ac.uk/projects/fastqc/); cutadapt v1.9 [https://gsl.hudsonalpha.org/information/software/bam2fastq); RSEM v1.3.0 [The following software packages were used to process RNA- and ribo-seq library sequences: fastqc v0.10.1  on September 10, 2015 (S288C_reference_genome_R64-2-1_20150113). Annotations for the following classes of transcripts were parsed from the genomic gff3-formatted annotation file and processed separately: protein coding genes (6551); intron-containing genes (272); genes with 5’-UTR introns (24); frameshifted genes (47); blocked and pseudogenes (18), non-coding RNAs (ncRNAs) (16). For all but the last class, 5’- and 3’-UTR entries were added to the individual gff files employing the UTR annotations from Nagalakshmi et al. [th percentile lengths of 97 and 173 nt, respectively. Unspliced versions (pre-mRNAs) of all intron-containing genes were defined as a continuous exon extending from the start of the 5’-UTR to end of the 3’-UTR. After editing the individual parsed gff files, they were concatenated, and a fasta file with sequences of all 6952 transcripts was generated using the cufflinks gffread program. Information included in the fasta header lines generated by gffread was used to construct a transcript-to-gene-map file for use with RSEM, which was used for gene- and isoform-level quantification of transcripts. The fasta file is available at https://github.com/Jacobson-Lab/yeast_transcriptome_v5. A modified transcriptome was used for riboWaltz . The riboWaltz transcriptome contained only the spliced transcripts of protein coding genes (6551) and genes with 5’-UTR introns (24). In addition, the riboWaltz transcriptome considered the stop codon as a part of the 3’-UTR region rather than the CDS region, thus the length of CDS and 3’-UTR regions of each gene were adjusted accordingly.A customized yeast transcriptome was constructed from the S288C reference genome sequence and annotations downloaded from the Saccharomyces Genome Database . Reads aligning to non-protein coding RNAs  were removed by aligning with bowtie (-m 100–3 4–5 4 -n 2 -l 15—un) and retaining only unaligned reads. The random 4-mers introduced on both sides of each RPF during library preparation were trimmed, concatenated, and stored as an identifier “barcode” used to remove PCR duplicates by aligning reads to the transcriptome (bowtie -m 10 -n 2 -l 15 -S—best—strata) and retaining only a single barcode (and associated read) at each position where multiple reads aligned. After duplicates removal, the SAM-formatted alignment file was converted either to BAM format using samtools or to fastq format using bam2fastq for use in downstream analyses. Transcript abundance measurements were determined by RSEM with settings—seed-length 15—bowtie-m 10. Reads processing and alignment statistics can be found in The TruSeq stranded RNA-Seq libraries were processed using RSEM with no additional pre-processing.sup45-d [rli1-d [Public ribosome profiling data of sup45-d , rli1-d  [rli1-d , and theAnalyses of ribosome profiling data were performed in the R software environment (versions 3.5 and 3.6). RPFs of 20–23 nt and 27–32 nt in length were used for the analyses. P-site offsets of reads in ribosome profiling libraries were assigned using the R package riboWaltz , the reshttps://github.com/Jacobson-Lab/sup45-ts_readthrough.For analyses results that were visualized in a heatmap form, extreme results were made to fit the indicated scale in order to not jeopardize the visualization of most of the results. The actual results for each figure and associated R codes used to generate the figure are provided for reference at Random forest analyses  were impInterpretation of each performance metric is as follows. AUROC is a common metric used to assess classification model. An ROC curve is generated by plotting true positive rates (TPR) against false positive rates (FPR) of multiple classification thresholds. A straight diagonal line indicates that TPR equals to FPR, resulting in area under the curve (AUROC) of 0.5, and means the chance that the model can classify genes into the correct groups is 50%–this is no better than random chance. Thus, the higher AUROC is than 0.5, the better the model performs, and AUROC of 1 indicates a perfect classification model . AcceptaRoot mean squared error (RMSE), one of the performance metrics for regression, is the average of the distance between the predicted values and the actual values. The unit of RMSE is the same as the Y variable. Whether the error is considered large or small depends on the range of the data. For instance, an average error of ± 0.5 may be considered small for the data ranging from 0–100, but considered large for the data ranging from 0–1. Therefore, in order to easily assess the errors across samples, we normalized the RMSE by the range of the data, where the resulting normalized RMSE (NRMSE) displays the average fraction of error relative to data range.After the random forest models were trained, feature importance for each X variable was extracted with the importance function. We selected Mean Decrease Accuracy (MDA) and % Increase in Mean Squared Error (%IncMSE) as measures of feature importance for classification and regression models, respectively.S1 FigCorrelation between ribosome density (top) or mRNA abundance (bottom) in reads per kilobase per million (RPKM) of a pair of replicates for each yeast strain and growth temperature. Pearson’s correlation coefficient (r) was calculated and reported for each pair of replicates.(TIF)Click here for additional data file.S2 FigA. Average readthrough efficiency of PTC-readthrough in the ade2-1 and can1-100 alleles. PTC readthrough efficiency was calculated by dividing frame 0 footprint count downstream of the PTC to that upstream of the PTC. Average ± standard deviation of two replicates were plotted for each sample, with black dots indicating the individual data points. B. and C. Read coverage tracks from the Integrative Genomics Viewer (IGV) [B.RPL28 and C.RPS0A, in SUP45 and sup45-ts strains at 25°C and 37°C. Yellow rectangles indicate the position of termination codons in frame with the respective initiation codons under conditions where the introns are translated. Full scale for A and B equals 50 reads.er (IGV)  showing (TIF)Click here for additional data file.S3 FigSpearman’s correlation coefficient (ρ) was calculated and reported for each pair of variables.(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.


Enhancer Eβ at the murine TCRβ locus has been reported to exhibit enhanced occupancy of RNA polymerase II in developing thymocytes. Here, we investigated the transcriptional potential of Eβ in developing thymocytes and detected overlapping bidirectional transcripts at Eβ ranging between 0.7 and 1.7 kb. These noncoding transcripts are capped, polyadenylated, nuclear and expressed specifically in thymocytes. Delineation of these characteristics is important to further investigate their functional roles in mediating enhancer activity.Enhancers are well established as critical regulators of gene expression, but the mechanisms underlying the molecular basis of their specificity and activity are only partly understood. One of the most exciting recent observations is the discovery of enhancer RNA (eRNA), a class of noncoding RNAs derived from enhancer regions. Transcription of developmentally regulated enhancers has been observed to be associated with their active state. The nature of transcripts (eRNA) and their functional attributes are diverse and context dependent. The majority of eRNA are nonpolyadenylated and present in low abundance owing to their low stability, and may represent transcriptional noise. However, some eRNAs have been reported to be reasonably long and stable, are enriched in nuclei, exhibit tissue‐specific expression and may contribute to enhancer function. Transcription of enhancers has been postulated to mediate enhancer function through either the act of transcription or via the transcribed RNA  Eβ of the TCRβ locus was found to produce noncoding, convergent and bidirectional transcripts, consistent with its critical regulatory role, in developing thymocytes. It will be interesting to evaluate the functional and mechanistic significance of transcription at enhancer Eβ.Several enhancers in their active state exhibit enrichment of H3K4‐me3 and H3K27‐ac, accumulate RNA polymerase II and undergo unidirectional or bidirectional transcription. In this study, enhancer  There is overwhelming evidence, based on chromosome conformation capture analysis , to suggest that spatial proximity of enhancers and their cognate promoters, achieved via chromatin looping, is critically important  according to manufacturer's protocol. Resultant cDNA was used for end point PCR or qPCR. For strand‐specific reverse transcription quantitative PCR (RT‐qPCR) analysis, biotinylated GSPs were incorporated in a RT reaction. Biotinylated cDNA was purified using Dynabeads MyOne Streptavidin C1 magnetic beads (Invitrogen) using the protocol as previously described by us . ThereafEβ‐specific primer to detect 5′ transcription start site (TSS) of the capped transcripts. For 3′RACE, cDNA was synthesized from RNA using GeneRacer oligo‐dT primer to detect 3′ transcription end site (TES) of the polyadenylated transcripts. Specific PCR products obtained from RACE were cloned in pGEM‐T Easy vector system (Promega), and ends were determined by Sanger sequencing.Five microgram of RNA sample was subjected to 3′ rapid amplification of cDNA ends (RACE) or 5′RACE using RML‐RACE GeneRacer Kit (Invitrogen). For 5′RACE, RNA was dephosphorylated and decapped according to manufacturer's instruction. GeneRacer RNA oligo was ligated to the processed RNA, which was subsequently subjected to RT‐PCR primed with enhancer GSE55635) were previously described [http://igb.bioviz.org. RNA‐seq, ATAC‐seq and ChIP‐seq for H3K27‐ac in DN thymocytes were obtained from data series GSE80272 [https://igv.org.ChIP‐seq datasets for RNAPII, H3K4‐me1 and H3K4‐me3 in developing thymocytes  [Eβ in its activated state as well as ~ 1‐kb region flanking Eβ has significant binding of RNAPII in both DN and DP thymocytes  consisting of RNA‐seq, ATAC‐seq and ChIP‐seq for H3K27‐ac was analysed from an independent study in DN thymocytes [Eβ was enriched for H3K27‐ac and features an accessible chromatin that yielded low but discernible level of transcription in RNA‐seq analysis  . It was tes Fig. . Also, pymocytes . The anasis Fig. . Furtherh RNAPII .Eβ was associated with H3K4‐me1, H3K27‐ac and H3K4‐me3 although the abundance of these histones at Eβ was lower than the genic regions, that is DJCβ and V31 segments  to address the transcriptional potential of Eβ. RT‐PCR analysis using random hexamers and oligo‐dT primers carried out on nuclear RNA of P5424 cells revealed the presence of polyadenylated transcripts emanating from Eβ that were more than 300 nucleotides in length . Furthermore, transcripts as long 1.1 kb were observed in both sense and antisense orientation  for antisense transcripts. This might be due to low level of antisense transcripts at the examined upstream region.After confirming the transcriptional potential of enhancer Eβ and the flanking downstream region. Further, transcription was also observed at the upstream region flanking Eβ as summarized in Fig. Eβ is transcribed bidirectionally to produce polyadenylated transcripts and extend the observation of low level of transcription at Eβ based on RNA‐seq analysis in both DN and DP thymocytes [Eβ remains active in DP and SP thymocytes [Next, similar RT‐PCR analysis was performed on nuclear RNA of total thymocytes isolated from C57BL/6 mice and reasonably long polyadenylated transcripts in both antisense  and TESs (3′TES). Our analysis of the antisense transcripts in the nuclear RNA of total thymocytes revealed multiple 5′TSS both within and downstream to Eβ  located in the vicinity of 3′TES identified with pFZN‐P gave a PCR amplicon (m794‐m795r) that covered the complete span from 3′TES pFZN‐P to 5′TSS pFZN‐X  and a 3′TES (pFZN‐AA) pertaining to capped polyadenylated RNA were mapped in the upstream and downstream region flanking Eβ, as defined by deletion analysis [DJCβ2 transcription unit and 3 kb upstream to TES of gene segment V31, which is transcribed in antisense orientation. Potentially, read‐through transcription from these transcription units can be manifested as transcription at the enhancer Eβ. However, RNAPII enrichment peak at Eβ was well separated from the peaks at the neighbouring transcription units, suggesting that the detected transcripts at Eβ were not a consequence of read‐through transcription. This contention was also supported by the detection of transcription start site by 5′RACE within and in close proximity of Eβ.analysis , 24, is Eβ were found to be completely overlapping and were characterized by substantial heterogeneity at both the ends. Further these transcripts were capped and polyadenylated at both strands and apparently were co‐expressed in both the orientations. In several studies, DHS regions mapping enhancers have been found to be enriched in CAGE tag libraries [Eβ, as at many other enhancer regions, may actually represent a pool of transcripts expressed from both the strands in a given cell population, which are otherwise transcribed in a unidirectional fashion from a given allele at single cell level. RNA‐FISH analysis at several bidirectionally transcribed enhancers has indeed revealed that both the strands are only rarely co‐expressed from the same allele in a cell [Altogether, bidirectional transcripts at enhancer ibraries , 53 wheribraries , 31, a fibraries , 10, 54.ibraries . The eRNibraries , 9, 12, ibraries , 10, 16.n a cell .Eβ, we examined their levels in cells where Eβ is in active state, that is DN thymocytes and total thymocytes and compared with levels in cells where Eβ is inactive, that is cells of neonatal liver. Utilizing RT‐qPCR analysis, we observed that their expression is restricted to the thymocytes. In liver, the expression was negligible compared to the thymocytes  than the nonpolyadenylated eRNAs detected in FANTOM5 CAGE libraries (median length of 346 nucleotides) [DRReRNA, expressed in myotubules, exemplifies a fairly stable polyadenylated noncoding transcript with a half‐life of ~ 30 min and acts in trans to regulate the expression of Myogenin [Eβ based transcripts was low. Whether the abundance was low due to lower degree of transcript initiation or instability of the transcripts remains a question. Also, additional mechanisms that regulate steady state levels of the transcripts cannot be ruled out.Although majority of eRNA are capped but not polyadenylated, we observed that the transcripts at  ~ 7 min , 57 and  ~ 7 min , 54. The ~ 7 min , 50, Int ~ 7 min . Longer  ~ 7 min , 21, 54.eotides) , it can Myogenin . DespiteEβ can bind specific proteins that are crucial to stabilize its interaction with the upstream promoters and/or have a role in their subsequent activation. Since the association of eRNAs with chromatin modifying factors can influence both their binding and activity [TCRβ locus.Noncoding transcription can exert its function in diverse ways. Recently, it has been proposed that eRNAs can orchestrate higher order chromatin organization by interacting with multivalent protein complexes, leading to liquid‐liquid phase separation of the supra‐molecular assemblies along with chromatin as a means to confine their biochemical activity in a membrane‐less compartment . Therefoactivity , 65, theIgh locus was recently reported to be crucial to facilitate its transition from activated to truly functional state necessary for class switch recombination (CSR) [Ighg1) was significantly reduced leading to loss of germline transcription essential for CSR. 3′RR transcription was required for establishment, albeit not maintenance, of long‐range interactions between 3′RR‐Igh promoters. Importantly, regulation of multiple enhancer–gene pairs was differentially affected by Spt5 depletion in this study and emphasized the context dependence of the eRNA in terms of its role as well as mechanism of action – an aspect that will continue to stimulate further investigations to gain useful insights in the realm of gene regulation and other nuclear processes.Transcription of 3′RR super‐enhancer of on (CSR) . In the Eβ‐associated transcripts cannot be excluded as relatively long and polyadenylated stable eRNA have been reported to have the ability to act in trans [Eβ will provide an opportunity to dissect the role of eRNAs in regulating enhancer activity.Additional roles of in trans , 67. TheThe authors declare no conflict of interest.MS conceived the study. FU and MS designed by the experiments and FU performed the experiments. FU and MS analysed the data. FU and MS prepared the manuscript.Fig. S1. Analysis of ChIP‐seq data showing the occupancy of RNAPII, H3K4‐me1 and H3K4‐me3 at murine TCRβ locus in DP thymocytes.Fig. S2. Assessment of the span of antisense transcripts in ex vivo DN thymocytes by strand‐specific RT‐PCR using biotinylated cDNA.Fig. S3. PhyloCSF analysis of the region encompassing sense and antisense transcripts detected at active enhancer Eβ.Click here for additional data file.


Four-stranded nucleic acid secondary structures (quadruplexes) including DNA G-quadruplexes, RNA G-quadruplexes and i-Motifs display key regulatory functions in the human genome. Quadruplexes play an important role in telomere lengthening and the expression control of several cancer-related genes. In this context, quadruplex ligands are considered as potential strategies for anticancer drug discovery. Previous reviews are mainly focused on ligands targeting DNA G-quadruplexes, RNA G-quadruplexes and i-Motifs in a separate way, hindering a holistic study. The present review overcomes this limitation by providing a general overview of the recent research on ligands targeting the three different quadruplex structures in cancer.Nucleic acids can adopt alternative secondary conformations including four-stranded structures known as quadruplexes. To date, quadruplexes have been demonstrated to exist both in human chromatin DNA and RNA. In particular, quadruplexes are found in guanine-rich sequences constituting G-quadruplexes, and in cytosine-rich sequences forming i-Motifs as a counterpart. Quadruplexes are associated with key biological processes ranging from transcription and translation of several oncogenes and tumor suppressors to telomeres maintenance and genome instability. In this context, quadruplexes have prompted investigations on their possible role in cancer biology and the evaluation of small-molecule ligands as potential therapeutic agents. This review aims to provide an updated close-up view of the literature on quadruplex ligands in cancer therapy, by grouping together ligands for DNA and RNA G-quadruplexes and DNA i-Motifs. Nucleic acids have considerable potential to fold into three-dimensional secondary structures based on particular sequence motifs . Single-Experiments using computational, chemical, molecular, and cell biology methods have demonstrated that quadruplexes are very numerous in the human genome. The use of computational algorithms to search for the consensus sequence of quadruplexes helped to identify quadruplexes and reveal their enrichment . Recent n telomeric sequence [hTERT gene is also controlled by DNA G4s [TERRA) [hTERT [In this regard, quadruplexes display key cancer-related functions  Figure B. Quadrusequence , which i DNA G4s . Apart f DNA G4s . Regardi [TERRA) , and in ) [hTERT , control) [hTERT . Further) [hTERT . RNA G4s) [hTERT . In the ) [hTERT  and extr) [hTERT .In this context, quadruplex ligands have been developed and tested as tools with which to study the complexity of quadruplexes-mediated mechanisms in carcinogenesis. Therefore, thanks to its stabilization properties, the small molecule, pyridostatin, enabled DNA G4 imaging in the nuclei of cells using the G4-recognizing antibody, BG4 . The samThis study aimed to concisely review the most recent advances in quadruplex targeting in antitumoral therapy. Given that the field of quadruplexes is continuously developing, we cover the current state of the art of quadruplex ligands in cancer research. Finally, we highlight the critical questions that remain to be addressed in the promising “era of quadruplexes”. Moreover, previous reviews separately focus on DNA G4, RNA G4 and i-Motif ligands in cancer. To the best of our knowledge, the present review is the first to bring together these quadruplex ligands, all of which are relevant for cancer therapeutics. Enormous efforts are being made to target quadruplexes as a therapeutic approach given their profound implication in carcinogenesis . LigandsTo date, an arsenal of around 1000 small molecules that target quadruplexes has been reported. In the section below, quadruplex ligands with an anticancer effect are summarized. Furthermore, the respective timeline is shown in Herein we review the plethora of existing small molecules targeting DNA G4s, from classical ligands to the most recently discovered and selective binders, through the main chemo-families .c-MYC transcription factor [VEGF vascular endothelial growth factor [PDGFa platelet derived growth factor [k-RAS, the GTP-binding protein involved in transduction [BCL2 mitochondrial protein, which regulates apoptosis [k-RAS promoter in a molecular ratio of 1:1 [c-KIT [Streptomyces anulatus, was considered a potent telomerase inhibitor due to its ability to facilitate the formation of G4 structures, and thereby sequestering the single-stranded (TTAGGG)n telomeric primer molecules required for telomerase activity [c-MYB is induced by telomestatin [c-MYC promoter [Disubstituted amidoanthraquinones were the first G4 ligands to be reported. These interactive agents tightly bind to telomeric G4s and block the telomerase RNA activity by disrupting the base-pairing between G-overhang and the enzyme . One yean factor , VEGF vah factor , PDGFa ph factor , k-RAS, sduction , and BCLpoptosis . Howeverpoptosis  and trippoptosis . The natpoptosis ,56. Intepoptosis . In addio of 1:1 . Moreove1 [c-KIT . Anotheractivity . More reactivity . Apart fmestatin . The synmestatin . Since imestatin . Bisquinmestatin  and formpromoter . Moreovepromoter . Neverthpromoter . As a repromoter . The 3,6promoter . c-MYC promoter [c-MYC, c-KIT, and telomeres [BRCA1/2 deficient tumors, constituting the most advanced G4 ligand in the clinics at the moment. Subsequently, some of these synthetic ligands have entered clinical trials . CX-3543promoter . Furtherpromoter . Althougpromoter . Very repromoter . Similarelomeres . Notablyc-KIT [BCL2 [c-KIT and BCL2 leading to the suppression of their respective protein expression and thus, interfering with their oncogenic signaling pathways [MDM2 oncogene, which is a master regulator of TP53, reducing MDM2 transcription. Such an approach could be used to defeat all tumors in which the restoration of wild-type TP53 is sought [c-KIT and c-MYC [c-KIT, inhibiting its transcriptional expression [c-KIT G4s than to duplex DNA [c-MYC G4 [RET gene in cancer, encoding a receptor-type tyrosine kinase [k-RAS > c-KIT [k-RAS G4 stabilizers, that preferentially target the mutant form of k-RAS [c-MYC G4 in the submicromolar range, with a topology-selective binding and an excellent discrimination against the antiparallel telomeric G4 [VEGF promoter, stabilizing its G4, thus downregulating its transcription and exhibiting a strong antiangiogenic activity [WT1, a zinc-finger transcription factor, downregulating its transcription [Many G4 ligands have characteristic cores that can be chemically modified, rendering various analogues whose therapeutic activity in cancer is being investigated . During c-KIT ,136 and IT [BCL2 . A recenpathways . In addis sought . Recentls sought . Variouss sought  and CM03s sought  demonstrs sought . On the s sought  and to is sought . Aside fnd c-MYC . Inspirend c-MYC  and L1H1nd c-MYC , which apression . Anotherpression . Quinazoplex DNA . Howeverc-MYC G4 . Accordie kinase . Other n > c-KIT . In factof k-RAS . The ratof k-RAS . In thismeric G4 . Moreoveactivity . Within activity . Additiocription .Over the last decade, attention has been focused on the development of G4 binders with selective recognition. Firstly, we would like to note that the majority of ligands have not been evaluated in large panels of quadruplexes or across the human genome. In this regard, many of the ligands described in this section are rather promiscuous. Selectivity is further discussed in the Discussion section.Schizocommunin, an alkaloid from a fungal source, have been also designed for telomeric G4 targeting [Initially, research studies were focused on small molecules with G4-depending telomerase inhibitory activity in telomerase-positive tumor cells. Spermine-derivatized tentacle porphyrins, including TCPPSpm4 and its Zn (II) derivative (ZnTCPPSpm4), stabilize telomeric G4 with high stoichiometry and point-to-end stacking or porphyrin self-association as major binding modes . In addiargeting . Anticanargeting  and adriargeting  bind as argeting , the triargeting  and arylargeting  exhibiteargeting . Metalloargeting , whilst argeting . Λ-enantargeting . Other Rargeting . Recentlargeting .c-MYC G4 has been a priority, as c-MYC was long considered undruggable. An ellipticine analog, GQC-05, was the first-in-class c-MYC selective ligand. GQC-05 alters protein binding to the NHE III1 region within its promoter and decreases c-MYC mRNA, in agreement with a G4 stabilizing action [c-MYC G4-specific recognition and downregulation. Among them, the bis-triazolyl carbazole ligand BTC-f [c-MYC G4. BZT-Indolium downregulates c-MYC transcription and can be used for in vitro staining and live cell imaging [c-MYC G4 ligands include high-throughput screenings. For instance, in a microarray screen of 20,000 small molecules using fluorescently labeled c-MYC G4, a novel c-MYC G4-binding benzofuran scaffold compound was successfully identified [c-MYC transcription was screened. The results demonstrated that only one ligand (compound 3) functions through c-MYC G4 binding [c-MYC G4. These nanotemplates facilitate the regioselective formation of triazole products such as Tz1, a high-affinity c-MYC G4 ligand [The identification of compounds that selectively bind to g action . In factg action . Followind BTC-f , the celnd BTC-f , the found BTC-f  and the nd BTC-f  have beend BTC-f . In addi imaging . Recent entified . Through binding . Other s4 ligand .k-RAS ligands on RAS-driven tumors also gained immediate interest. Since TMPyP4 and many of its derivatives suffer from inadequate selectivity, new porphyrin derivatives were designed to discriminate between different G4 topologies, with a preference for the parallel over the antiparallel conformation. In particular, porphyrin-1  and porphyrin-2  [k-RAS promoter G4. Furthermore, a porphyrin-based photosensitizer showed preferential binding to the 3′-end of k-RAS G4 [k-RAS G4 with modest specificity over duplex DNA [k-RAS G4, with a 1:1 stoichiometry ratio and a remarkable selectivity against duplex DNA. It was also shown to inhibit the transcription of the k-RAS driver oncogene which had been long considered undruggable [Exploring the impact of taining) , were shk-RAS G4 . The fluplex DNA . A new cruggable . VEGF G4 ligands as antimetastatic therapies. Se2SAP, a core-modified expanded porphyrin analogue with significantly reduced photoreactivity and increased effectivity in G4-binding as compared with TMPyP4, was the first selective VEGF G4 binding compound identified [VEGF intramolecular G4 formation [VEGF promoter. VEGFq binds specifically to the C-rich strand, via strand invasion, stabilizing the G4 structure formed by the genomic G-rich sequence, resulting in VEGF transcriptional inhibition [Increasing interest has also been directed towards entified . PM2, a ormation . Lastly,hibition .BCL2 G4, whose fluorescence intensity is greatly enhanced in the presence of BCL2 G4 [BCL2 G4 with a good selectivity and inhibit BCL2 gene transcription [c-MYB in vitro and effectively affects its transcription [c-KIT G4 and provide a proof of concept for the inhibition of c-KIT transcription [hTERT G4 folding pathway, reducing hTERT activity through its transcriptional repression [PDGFRb G4, to favor its structure and downregulates the transcription of this growth factor receptor [FGFR2, inhibiting its activity [Stephania cepharantha, was found to recognize and stabilize the G4 in the 3′-flanking region of the signal transducer STAT3, downregulating its transcription [Other G4 ligands targeting “unique” oncogenic promoters have also emerged. An example is carbazole TO, a fluorescent probe that preferentially targets  BCL2 G4 . Moreovecription . Topoteccription . Isoallocription . A smallpression . The ellreceptor . The natactivity . Furthercription .c-MYC and c-KIT G4s [c-MYC extratelomeric structures with promising biological results [c-KIT and k-RAS [c-MYC and BCL2 genes through their respective promoter G4s [In contrast, other novel ligands were reported to be selective compounds interacting not only with a unique G4, but also with a narrow-spectrum of G4s. Among them, new substituted diquinolinyl-pyridine ligands show a preference for the parallel conformation of telomeric, -KIT G4s . The sam-KIT G4s . S4-5, a results . The trind k-RAS . Lastly,oter G4s . TERRA G4 dimer, intercalating into the 5′-5′ stacking interface of two G4s blocks with a binding stoichiometry of 1:1 [As described in the Background Section, increasing evidence suggests that UTRs, coding sequences, and splicing sites of cancer-relevant genes contain putative RNA G4s, which can be targeted. In addition, RNA G4s play important roles associated with telomeric function. For example, TMPyP4 binds to a y of 1:1 . Hereaftn-RAS 5′UTR [n-RAS G4 and subsequently repress n-RAS translation. An anionic phthalocyanine, ZnAPC, is another G4 ligand that even binds to n-RAS in the presence of abundant RNA in mammalian cells, resulting in selective cleavage of the targeted G4 upon photo-irradiation [n-RAS, its k-RAS counterpart is also targeted by specific G4 ligands. In this regard, the alkyl derivative of TMPyP4 (TMPyP4-C14), binds to G4s in the 5′UTR of k-RAS mRNA and, upon photoactivation, selectively induces mRNA degradation, resulting in k-RAS protein downregulation by approximately 90% [k-RAS transcript, repressing its translation in a dose-dependent manner [k-RAS and n-RAS mRNAs, while generating reactive oxygen species upon photoirradiation and finally downregulating both k-RAS and n-RAS expression. Therefore, these alkyl porphyrins are efficient photosensitizers for the photodynamic therapy of RAS-driven cancers [RAS, G4 targeting of other cancer-relevant genes is increasingly required. Three bisquinolinium compounds  selectively bind to the telomere shelterin protein TRF2 G4, inhibiting its protein expression in a cellular context [VEGFa 5′UTR, downregulating VEGFa translation and significantly impeding tumoral cell migration [ADAM10 5′UTR, strongly upregulating its translation [HNF4a [BAG1 5’UTR is stabilized by small-molecule ligands such as carboxypyridostatin and Phen-DC3, which reduce the expression of endogenous BAG1 isoforms [The discovery of RNA G4s in the 5′UTRs of numerous genes led to the proposal that such RNA motifs could be suitable targets for small molecules to modulate mRNA translation. The two quinolinium derivatives, RR82 and RR110, considerably reduced the translational efficiency of the AS 5′UTR . After tAS 5′UTR , and a nAS 5′UTR , stabiliadiation . In additely 90% . A biotit manner . In a mu cancers . Beyond  context . A quinaigration . A serienslation . Moreoven [HNF4a . A G4 loisoforms . BCLX gene, inhibiting the expression of its antiapoptotic isoform, activating the alternative 5’ splicing site, and expressing a proapoptotic isoform. Apparently, these effects are due to specific interactions between GQC-05 and G4s on BCLX pre-mRNA [EWSR1 protein involved in sarcoma translocations, blocking its interaction with the RNA-binding protein HNRNPH1 and regulating its splicing [hTERT splicing pattern, causing the almost complete disappearance of the active transcript and an overexpression of the inactive transcript [G4s are also present at RNA splicing sites, which reveals a novel and significant role in regulating alternative splicing and expression patterns, and thus, makes them a possible target for antitumoral G4 ligands. For example, the ellipticine GQC-05, antagonizes the major 5’ splicing site of pre-mRNA . The afosplicing . Similaranscript . In addianscript .miRNA-1587 [miRNA-149 [pre-miRNA-149 [miRNA-1587 G4 forming 1:1 and 2:1 complexes with the dimeric G4, although the derived effect has not yet been studied [TP53-driven tumors, sanguinarine was revealed as a high affinity binder with stabilization effects on the miRNA-3620-5p G4, blocking the base-pairing of miRNA-3620-5p with its target sequence [pre-miRNA-92b and was shown to inhibit its maturation. Consequently, LNA treatment rescues PTEN expression, which is suppressed by the elevated level of miRNA-92b in cancer [Recent efforts have focused on the development of ligands targeting miRNAs associated with cancer pathways, as they would allow for the simultaneous regulation of multiple mRNAs involved in carcinogenesis. Various well-known G4 binders were reported to target several miRNAs of relevance in cancer. In this way, TMPyP4 stabilizes G4s in RNA-1587  and miRNiRNA-149  and PheniRNA-149 . Moreove studied . Interessequence . Moreoven cancer .While there are hundreds of ligands that interact with DNA and RNA G4s, there are very few compounds that target i-Motifs. Several ligands act as dual i-Motif/G4-interactive compounds. Thus, we would like to highlight the importance of evaluating their behavior towards the i-Motif counterpart, when studying G4-targeting compounds. In this section, DNA i-Motif ligands that were reported to exert antitumoral activity are grouped based on telomeric or extratelomeric targeting .c-MYC i-Motif forming sequences, even at physiological pHs [The first study of a small molecule binding to an i-Motif was reported for TMPyP4, which promotes the formation of the telomeric i-Motif. This study raised the intriguing possibility that TMPyP4 triggers the formation of non-B DNA structures in both strands of the telomeres through a nonintercalative mechanism . The druical pHs . The intical pHs . Apart fical pHs ,182. In ical pHs . The cycical pHs . SMARCA4, causing its destabilization [BCL2 i-Motif ligands have been discovered. The first one was a cholestane derivative, compound NSC138948 (IMC-48). IMC-48 traps out the BCL2 i-Motif, shifting the equilibrium of secondary DNA structures and causing transcriptional overexpression of BCL2 [BCL2 i-Motif binding at a 1:1 stoichiometry [BCL2 i-Motif whilst the meta-isomer PBP2 selectively binds to BCL2 G4. As a consequence, PBP1 upregulates and PBP2 downregulates BCL2 gene expression in cancer cells [PDGFRb i-Motif-interactive selectivity, inhibiting PDGFRb promoter activity [k-RAS i-Motif. However, nitidine also stabilizes the three existing k-RAS G4s and this combined effect leads to the downregulation of k-RAS gene expression [c-MYC promoter i-Motif without significant binding to the respective G4 and duplex DNA, causing the downregulation of c-MYC transcription [VEGF promoter region with theranostic applicability. Fisetin does not induce the stabilization of the VEGF i-Motif structure but causes both fluorescence emission and the transformation of the i-Motif into a hairpin-like structure; thus, it can be used to diagnose aberrant formations in i-Motifs. Furthermore, fisetin facilitates the processivity of polymerases and this control of replication by fisetin is therapeutically important and feasible [c-MYC and BCL2 i-Motifs, were employed to promote the metal-free synthesis of specific i-Motif ligands. In order to generate selective ligands for i-Motifs over G4s and duplex DNAs, complementary c-MYC and BCL2 G4s and self-complementary duplex DNA functionalized nanotemplates have been used as control templates. Such a strategy generated cell-membrane permeable triazole leads. In vitro studies reveal that the c-MYC i-Motif leads to the downregulation of c-MYC gene expression whereas the BCL2 i-Motif leads to the upregulation of BCL2 gene expression [The model ligand TMPyP4 also targets the i-Motif found in the chromatin remodeler lization . To date of BCL2 . Additiohiometry . Enantioer cells . Other oactivity . In thispression . In contcription . Interesfeasible . Very repression . Thus fapression .Cancer is a major disease that poses a serious threat to human life and health. As a result of its complex and heterogeneous pathogenesis, there are still many challenges in cancer therapy. Finding novel anti-tumor drugs with high selectivity and few side effects is still the main focus of cancer research. As demonstrated in the present review, an imbalance in quadruplex dynamics contributes to carcinogenesis, and its manipulation by quadruplex ligands provides a novel opportunity to defeat cancer. Initial efforts were mainly focused on targeting telomeric quadruplexes in order to inhibit telomere extension in cancer cells using telomerase, whereas later studies attempted to transcriptionally modulate individual cancer genes by targeting their quadruplexes. Although there is a long way to go in the development of potent drugs, various promising lead compounds have been obtained; however, the results have thus far been limited. Firstly, at this stage, the variety of binding sites for these ligands and the differences in their effects on the quadruplex structures make it difficult to unravel how quadruplexes influence biological function, i.e., whether the stabilization or destabilization of quadruplexes promotes or inhibits gene expression. Secondly, the correlation between stabilization in vitro and cell activity is not straightforward. In particular, a G4 target characterized in vitro may not be the sole G4 targeted in cells. Furthermore, there is also inherent cell variability, which has an impact on the relationship between in vitro and in vivo results. A further point to be addressed for the majority of ligands described thus far is that they are generally characterized by high-molecular weights and protonated side chains, which may affect their cellular uptake. However, the major limitation for the clinical application of quadruplex ligands seems to be directly related to selectivity. In fact, the selectivity pattern of several quadruplex ligands is dose-dependent. Although global or multiple G4 targeting approaches may be effective, targets need to be clearly defined in advance. Other conceivable obstacles are the potential side effects of the ligands on normal tissues. Moreover, the predictive response biomarkers need to be identified if a personalized anticancer management is to be achieved. Nevertheless, given the rapid accumulation of data on quadruplex structures and the related biological functions, and the rapid development of ligands, we are confident that these limitations can be overcome. In this regard, a wealth of new derivatives with lower cytotoxicity and superior selectivity will emerge in the near future.In this review, we give an overview of a range of compounds that target quadruplexes, including DNA G4s, RNA G4s, and i-Motifs, and discuss their limitations. The quadruplex-mediated antitumoral effects reported herein may pave the way for cutting-edge therapeutic approaches in the future treatment of human cancer.


Super-enhancers (genome elements that activate gene transcription) are DNAregions with an elevated concentration of transcriptional complexes. Thesemultiprotein structures contain, among other components, the cyclin-dependentkinases 8 and 19. These and other transcriptional protein kinases are regardedas novel targets for pharmacological inhibition by antitumor drug candidates. The template synthesis of molecules (and gene transcription in particular) isone of the most essential processes in nature. This evolutionary conservativemechanism is found in all organisms, without exception: from viruses to highermammals. Its biological role consists of transmitting and consolidating geneticinformation from the template macromolecule in the offspring. The cornerstonerole of transcription is not limited to the “normal” processes,such as ontogenesis and phylogenesis, speciation, biodiversity, control ofheredity, etc. Deepening our understanding of the molecular mechanisms oftranscription allows us to grasp its fundamental significance in pathologicalprocesses. Today, it is impossible to interpret the etiology and pathogenesisof diseases without an analysis of the regulation of gene expression in apathological site. It appears reasonable to assert that differential geneexpression  andtemporal regulation of expression compared to the physiological pattern)defines the essence of a disease as a “transcriptional imbalance.”Our modern approach to therapy (targeted manipulation with specifictranscription mechanisms) is currently rooted in this understanding. Thesemechanisms in mammalian cells are unusually diverse, interchangeable, and theyremain insufficiently understood; in addition, a number of them remainunsusceptible to pharmacological regulation . Therefore, targeted “transcriptional therapy” is only inits first steps.Which structural and functional elements of the transcription apparatus can beinfluenced to regulate gene expression? Which mechanisms should one regulateand how is this problem solved in terms of the spatial organization oftranscription? Research focused on the regulatory regions of genes (promotersand enhancers) is necessary as, among the functions of these regions, areensuring proper localization of multiprotein transcriptional complexes,transcription initiation, and regulation of the transcription rate. Sinceprotein kinases are perhaps the most common targets in modern drug design, itis no coincidence that, among the various mechanisms of gene expressionregulation, transcriptional kinases (a separate class of serine/threoninephosphotransferases) are emerging as the study object, the potentialtherapeutic target.This review analyzes genomic elements where the presence of the transcriptionalmachinery is especially potent: super-enhancers and the proteins associatedwith them . We considerthese elements as the structural and functional units of the transcriptionapparatus, and as therapeutic targets in tumor cells.Definition of the conceptetal. [Oct4, Sox2, Nanog,Klf4, Esrrb, miR-290-295, etc.) These genomicregions differ from the conventional enhancers in terms of length and distancefrom the regulated gene, as well as in terms of the number and set oftranscription factors associated with them. Oct4, Sox2, Nanog, Klf4, and Esrrbproved to be the prevailing transcription factors . They are the key transcription factors that support, and caneven induce, the pluripotent state of embryonic cells, as well as Med1, acomponent of the Mediator complex. The identified areas were namedsuper-enhancers. An important feature of super-enhancers was discovered alreadyin that first study: when the level of transcription factors in the cellchanges , transcription of the corresponding genes stops, while transcriptionof the genes regulated by conventional enhancers changes insignificantly [The concept of super-enhancers was first formulated in a study focused on theregulation of gene expression in embryonic stem cells. Whyte etal.  discloseAn attempt to provide a generalized definition of a“super-enhancer” makes it necessary to draw a distinction betweenthese regions of the genome and conventional enhancers. This boundary turns outto be conditional (see below). The definition of super-enhancers is empiricaland is based on two criteria. Super-enhancers include genomic regions with thefollowing features: 1) regions containing extended up to 12.5 kb) groups ofenhancers; (2) regions with abnormally high binding of a certain set oftranscription factors  thatregulate the maintenance of the undifferentiated state of embryonic stem cells,increased binding of super-enhancers to the transcription factors closing themain signaling pathways , SMAD3 , STAT1 , andSTAT3 (LIF)) was also detected, 8.Identification of super-enhancers in the genomeFig. 1)to the right from the point at which the derivativeof the enrichment function equals 1[The most common method used to identify active super-enhancers is based on thecharacteristic epigenetic state inherent to active enhancers: monomethylation,instead of trimethylation, of lysine at position 4 of histone 3  andacetylation of lysine at position 27 of histone 3 (it “marks”active enhancers as opposed to inactive regulatory elements). At the equals 1.Along with enrichment in histone “marks,” other molecular criteriafor active transcription can be used to identify super-enhancers: sensitivityto DNase I, increased binding of transcription factors , the presence of the activators Med1 and p300. The SEdSuper-enhancers identified by any of these methods consist of only a few singleenhancers, and about 15% of the super-enhancers consist of just one enhancer. Such anThe difference between conventional enhancers and super-enhancers is clearlymanifested in the nature of the dependence of the transcription activityensured by the regulatory element and the number of transcription factors andcofactors associated with it. This dependence is linear for conventionalenhancers, while, for super-enhancers, it acquires an “all ornothing” form ,13 reseFig. 2,Fig. 3). The state ofphase separation occurs when almost all molecules interact . In this state, the transcriptionalactivity is at its maximum. The valence of the molecules in the system can grow. Mathematical modeling has shown that thetranscriptional activity of a conventional enhancer depends linearly on thevalence of the system, and for a super-enhancer, at relatively low valencevalues, phase separation occurs and transcriptional activity increases abruptlyalmost to a maximum.A phase separation model was proposed to explain the regularities ofsuper-enhancer function . The higAccording to this model, valence decreases upon inhibition of a cofactor ordeletion of the binding site. In the case of a super-enhancer, it causes asignificant drop in transcriptional activity from the maximum to the minimalvalue.In addition to DNA and protein molecules, the complex also contains enhancerRNAs (eRNAs): non-coding RNAs transcribed from the enhancers. Among them, thereare short-lived short RNAs without poly(A) regions that can be transcribed inboth directions, and longer ones with poly(A) regions (transcribed only in the5‘ → 3’ direction). eRNAs are involved in the organization ofpromoter–nhancer interactions: they increase the strength of the bindingof transcription factors to DNA, recruit and activate cofactors, and shortenthe transcriptional pause. Super-enhancers express eRNA at a higher level thanconventional enhancers do; in addition, eRNAs are more often expressed from thesuper-enhancers rather than from conventional enhancers . eRNAs cIgH locus onchromosome 14 of the human genome regulates recombination in B cells J recombination in B1 cells [Aicdalocus. Enzymes belonging to the TET family andensuring demethylation of this super-enhancer are required for isotypeswitching [Super-enhancers are much more likely to act as regulators of the key processesin normal cells and pathological processes compared to conventional enhancers. The IgHB1 cells  and isotB1 cells ). Anothewitching . Converswitching . Furtherwitching . CircRNAwitching , precludBIN1 gene, whose increasedexpression is associated with the risk of developing Alzheimer’s. In thecase of type 1 diabetes mellitus, an increased amount of mutations was found insuper-enhancers in T-helper cells. Polymorphisms associated with systemic lupuserythematosus were found to be concentrated in the super-enhancers of the keygenes for B-cells [Point mutations in the noncoding regions of the genome account for about 90% ofall disease-related mutations (according to genome-wide association studies(GWAS)). Such mutations are more common in super-enhancers than they are inconventional enhancers. This conclusion was bolstered by comparing thesuper-enhancers in different types of cells from the same patient: in theabnormal focus and outside of it. Mutations  in super-enhancers are associated with Alzheimer’s, systemic lupuserythematosus, type 1 diabetes mellitus, etc. Thus, several SNPs have beenfound in the super-enhancer of the  B-cells .SELE,VCAM1), as well as chemokine CCL2. Super-enhancers have beenactivated due to binding of the acetylated form of NF-κB to BRD4. Nosuper-enhancers were activated upon BRD4 inhibition in [Super-enhancers can also be epigenetically activated in response to externalstimuli. Thus, during inflammation, activation of the transcription factorNF-κB in endothelial cells can lead to the formation of activesuper-enhancers and maintenance of a high expression of genes whose productspromote the adhesion of leukocytes  depends on the activation of the Wntsignaling pathway; in this lineage, a super-enhancer is activated at theThe emergence of super-enhancers in tumor cells occurs according to the samemechanisms as any changes in gene expression. Both genetic .The location . In someenhancer . The ampenhancer . Focalal tumors .In a siand neck . InT-ceand neck +8+ thymocytes). When reproducing these deletionsin epithelial cells (HEK293 line) using the CRISPR/Cas9 system, asuper-enhancer-dependent activation of the oncogenes TAL1 andLMO1 was detected [An important genetic mechanism of malignant cell transformation is representedby a violation of the boundaries of topologically associating domains (TADs),which are chromosomal segments approximately 1 Mbp long that aretranscriptionally isolated from each other. The fragments of one TAD interactwith each other much more often than the fragments of different TADs. Divisioninto these domains is an evolutionarily conserved process that probably aroseto prevent the long-range interaction of enhancers and super-enhancers with“foreign” promoters. The boundaries between the TADs are thebinding sites of the CTCF transcription repressor (CCGCGNGGNGGCAG) and theCTCF–ohesin protein complexes associated with them. Mutations in thegenes encoding cohesin and CTCF, as well as in their DNA-binding sites, areoften present in transformed cells .Small ddetected .Changes in the nucleotide sequences of super-enhancers may both affect theirbinding to proteins and also cause changes in the sequences and the number ofeRNA molecules. Certain eRNAs associated with “oncogenic”super-enhancers have oncogenic properties themselves. These eRNAs are involvedin the regulation of the key processes: proliferation, apoptosis, autophagy,epithelial–esenchymal transition, and angiogenesis .c-Myc oncogene, in myelomacells [c-Myc in colon cancer cells (HCT116 and DLD1 lines) is alsosupported by a super-enhancer. Knockdown of the BRD4,MED12, and MED13/13L genes decreasedenhancer-dependent gene expression and inhibited theproliferation of colorectal cancer cells [The bromodomain protein BRD4, which binds to acetylated lysine residues inhistones , plays an important role in the epigeneticregulation of super-enhancer activity. A study focused on diffuse large B-celllymphomas showed that onethird of the BRD4 molecules in a cell are concentratedin super-enhancers. Expression of the corresponding genes was found to be verysensitive to the pharmacological inhibition of BRD4 . A low-mer cells .c-Myc, MIR155, IKZF3, and Bcl-2genes that are crucial to cell survival. The activation ofsuper-enhancers is sensitive to BRD4 inhibition: it was blocked by the compoundJQ1 [An unexpected variant of epigenetic activation of super-enhancers wasdiscovered in the study of B-cell infection with the Epstein–Barr virus.In infected cells, this virus synthesizes its own transcription factors, EBNA2,3A, 3C, and EBNA-LP, and activates some cellular ones . Thesetranscription factors form the active super-enhancers that regulate theoundJQ1 .Super-enhancers also regulate the differentiation status of tumor stem cells;this fact can be used in elaborating therapeutic strategies. For maintainingthe pluripotent state of glioma stem cells, the ELOVL2 (elongation of the verylong chain fatty acids protein 2) protein, whose expression in these cells isparticularly high and is triggered by the epigenetic activation of thecorresponding super-enhancer, is important. ELOVL2 plays a key role in thesynthesis of polyunsaturated fatty acids (components of the plasma membrane)and is also involved in the signaling from the epidermal growth factor receptor(EGFR). Selective inactivation of the ELOVL2 super-enhancer by dCas9-KRAB leadsto a post-transcriptional decrease in the EGFR level . Loss ofThis example illustrates a situation where the malignant potential of a cell isensured by the inactivation of the expression of anti-oncogenes dependent onsuper- enhancers rather than by the high expression of oncogenes caused bysuper-enhancers. In this regard, therapeutic strategies aimed at reactivatinganti-oncogene super-enhancers appear reasonable. The possibility ofimplementing this strategy is analyzed below.As mentioned above, super-enhancers make it possible to fundamentally alter thetranscriptional program, even in response to a relatively weak stimulus.Malignant transformation is often associated with the emergence (formation) oractivation of an existing, but non-functioning, super-enhancer. Therefore,super-enhancers and the associated proteins are gaining interest as targets forthe development of anticancer drugs. It is hoped that a therapeutic effect willbe achieved at relatively low concentrations of such drugs (see below).Two classes of proteins associated with super-enhancers are considered astherapeutic targets: proteins with a bromodomain (primarily BRD4) and thecyclin- dependent protein kinases CDK4/6, CDK7, CDK8, and CDK12/13.Proteins containing a bromodomainProteins carrying a conserved lysine-binding amino acid sequence, thebromodomain, ensure the functioning of super-enhancers by maintaining theactive state of chromatin through interaction with the acetylated lysineresidues in chromatin proteins. As a result of this interaction, transcriptionfactors and RNA polymerase II are recruited to super-enhancers. Inhibition ofproteins carrying the bromodomain can lead to chromatin inactivation.Myc expression and downstream transcription programs, wasobserved [BRD4 inhibitors  have shownencouraging results in preclinical models of acute myeloid leukemia andmultiple myeloma. Tumor growth retardation, as well as suppression ofobserved . A numbeobserved . The ABBobserved .Cyclin-dependent protein kinasesin vivo, and they also reduce the expression of a number ofgenes dependent on super-enhancers  [The cyclin-dependent kinases CDK4 and CDK6 play a key role in the phase changeof the G1-S cell cycle. The CDK4/6 inhibitors palbociclib, ribociclib, andabemaciclib have been included in hormone-sensitive HER2-negative breast cancerprotocols as monotherapy. As part of combination therapy, CDK4/6 inhibitors areundergoing clinical trials for other types of breast cancer . Selecticlin D1) .A special group of cyclin-dependent protein kinases does not participate in theregulation of cell cycle phases but functions as a structural and functionalcomponent of the transcription apparatus. In particular, such“transcriptional” protein kinases include CDK7, CDK8 and itsparalog CDK19 (CDK8/19), as well as CDK9 and CDK12/13 . CDK7 isc-Myc locus [THZ1, an inhibitor of CDK7  , 44, redyc locus . Clinicayc locus . RUNX1,MYB, TAL1, and GATA3oncogenes decreases in Jurkat cells under the influence of THZ531, aninhibitor of CDK12 [Super-enhancer-dependent expression of theof CDK12 . Since tof CDK12 .CDK8 plays a special role in transcription regulation. This serine/threonineprotein kinase, in cooperation with cyclin C (CCNC), the MED12, and MED13proteins, forms the regulatory CDK module of a crucial transcriptional complex:Mediator. The components of this complex are conserved in all eukaryotes. It isimportant to understand that CDK8/19, unlike other CDKs, does not regulatephase transitions in the cell cycle . The maicdk8 gene also has no significant manifestations in adult mice[cdk8 in mice is lethal at the preimplantation embryo stage[ Drosophila melanogasterleads to death at the late third instar larva and prepupal stages[Transcriptional reprogramming is not vital for an adult organism underhomeostatic conditions; longterm inhibition of CDK8/19 has no phenotypicmanifestations. Genetic (mediated by the Cre/Lox system) knockout of theult mice. Howeveryo stage, and null stages, 57.CDK8 gene knockout and pharmacologicalinhibition of kinase activity have different effects on the general patterns ofgene expression, which indicates two fundamentally different mechanisms ofCDK8/19 action: those dependent on and independent of kinase function.Importantly, the Is there a connection between CDK8/19 and super- enhancers? Inimmunoprecipitation experiments, an increased presence of CDK8 in the regionsof individual super-enhancers was detected. According to the RNA sequencingdata, two-thirds of the genes whose expression is affected by CDK8 inhibitionare the genes regulated by super-enhancers. Among super-enhancers whoserelationship with CDK8 was established in both of the aforementionedexperimental systems, there were super-enhancers of the genes encoding thetranscription factors Nanog, Oct3/4, and SOX2, as well as a significant numberof super-enhancers of the genes regulated by the Wnt signaling pathways .Transcriptional reprogramming is fundamental in the development of manypathological processes, especially tumor ones. Deregulation of CDK8/19 is oftenencountered in tumors in which CDK8 is involved in the activation of importantsignaling pathways mediated by Wnt/β-catenin , NF-κB ,TGF-β , HIF1α , or the Since CDK8/19 inhibition is practically safe in an adult organism, it ispromising to use CDK8/19 as therapeutic targets , 66, 67.CEBPA,IRF8, IRF1, and ETV6), whichslowed down cell proliferation. Meanwhile, the expression of 20% of the genesassociated with super-enhancers increased, while only a 3% increase inexpression was observed for the genes with the conventional enhancers. CDK8 wasfound to be associated with the super-enhancers of all activated genes . There were only threeinhibited genes regulated by the super-enhancers . These ratios allow [Cortistatin A is a relatively selective inhibitor of CDK8/19 kinase activity.Inhibition of these protein kinases by cortistatin A in acute myeloid leukemiacells (MOLM-14 line) increased the expression of the “antitumor”genes controlled by super-enhancers  was the same as that observed after exposure tocortistatin A. Proliferation of tumor cells is likely to depend on the“dosage” of gene expression determined by super-enhancers. It isnoteworthy that the effects were not summarized for I-BET151 and cortistatin Aused together, and that the changes in the gene expression profile were in fullalignment with those caused by I-BET151 alone. BRD4 is probably required fortranscription activation in response to cortistatin A .Acute myeloid leukemia cells are sometimes characterized by constitutiveactivation of the JAK-STAT signaling pathway. The STAT1 transcription factor isone of the main targets of CDK8 kinase activity. The content of thephosphorylated  form pSTAT1S727 is increased inthe super-enhancer regions [c-Myc oncogene, which isalso regulated by a super-enhancer, is consistent with the concept of increasedsuper-enhancer-dependent expression upon CDK8 inhibition. However, despite theactivation of c-Myc, the inhibitors werefound to exhibit an overall moderate antitumor effect [CDK8/19 inhibitors based on modified pyridines slowed the proliferation ofcolorectal cancer cells . The genr effect .et al. [MED12 andMED13/13L genes [Kuuluvainen et al. attempte3L genes .In the examples discussed above, CDK8/19 inhibition did not affect theactivated enhancers of oncogenes but led to the activation of thesuper-enhancers of the anti-oncogenes , 33. TheEarly stages of clinical trials of CDK8/19 inhibitors are currently underway.For instance, SEL120 compounds are being tested as candidate drugs againstacute myeloid leukemia, and BCD-115 are studied for possible treatment ofHER2-negative estrogen-dependent breast cancer. Trial identifiers, as well asthe analysis of the causes of the toxicity of CDK8/19 inhibitors, werepresented in .Detailed studies of the structural and functional features of genomeorganization have made it possible to formulate the concept of super-enhancersas regions with an increased content of transcription complexes. It is notsurprising that these regions are important in pathogenesis: the molecularmechanisms of diseases are associated, in one way or another, withdysregulation of gene transcription. Super-enhancers acquire a special role intumor biology: uncontrolled proliferation of transformed cells and theirevasion of therapeutic action (chemotherapy and radiation therapy) are causedby both transcription activation and by adaptive changes in their geneexpression profile. Consequently, super-enhancers  become targets ofantitumor action.The question related to the prospects of the low-molecular- weight chemicalmodulators of transcriptional CDKs in tumor therapy is especially important.The effectiveness of the first CDK inhibitors turned out to be insufficient,and general resorptive toxicity was high. Subsequently, more selectiveinhibitors of individual transcriptional protein kinases were obtained: THZ1for CDK7, THZ531 for CDK12/13, and palbociclib and ribociclib for CDK4/6. Thesecompounds have a pronounced antitumor effect in clinical situations and arebecoming parts of treatment regimens , 75.CDK8/19s are of interest as a unique target: the special selectivity oftranscription reprogramming offers a chance to replace the currently used toxicdrugs with well-tolerated agents inhibiting this mechanism. Although occurringin all age groups, acute myeloid leukemia is especially common in patients over60 years of age. The currently used treatment regimens are difficult totolerate due to the cardio- and myelotoxicity; the likelihood of early relapseis high (within the first year) ,77. In While it may be difficult to interpret super-enhancers as special“independent” regulatory elements of the genome from a generalbiology point of view, their practical importance as “accumulators”of transcription complexes for studying a pathogenesis and developingpersonalized therapy seems undeniable. This strategy involves identifying therole of a specific transcriptional mechanism in the patient  and targeting the established mechanism.


Transcription is a step in gene expression that defines the identity of cells and its dysregulation is associated with diseases. With advancing technologies revealing molecular underpinnings of the cell with ever-higher precision, our ability to view the transcriptomes may have surpassed our knowledge of the principles behind their organization. The human RNA polymerase II (Pol II) machinery comprises thousands of components that, in conjunction with epigenetic and other mechanisms, drive specialized programs of development, differentiation, and responses to the environment. Parts of these programs are repurposed in oncogenic transformation. Targeting of cancers is commonly done by inhibiting general or broadly acting components of the cellular machinery. The critical unanswered question is how globally acting or general factors exert cell type specific effects on transcription. One solution, which is discussed here, may be among the events that take place at genes during early Pol II transcription elongation. This essay turns the spotlight on the well-known phenomenon of promoter-proximal Pol II pausing as a step that separates signals that establish pausing genome-wide from those that release the paused Pol II into the gene. Concepts generated in this rapidly developing field will enhance our understanding of basic principles behind transcriptome organization and hopefully translate into better therapies at the bedside. Treatments of cancers should ideally be tailored to their specific molecular signatures. The central place and complexity of transcription regulation in normal and cancer cells offer tantalizing opportunities for precise targeting . Many anTranscription is the first step in expression of genes and genomes. The combined activity of some 20,000 human genes results in genome-wide RNA transcriptome patterns that reflect the biology and define the identity of every cell. Despite the flood of technologies describing the transcriptomes with increasing precision, our understanding of gene regulation remains fundamentally based on the knowledge gained from studies of individual genes. A long-standing gene-centric paradigm describes regulation by sequence-specific transcription factors that serve as repressors and activators, in contrast to factors broadly involved in the process of transcription that are considered basal or general . This paTwo features of Pol II transcription are of note. On the one hand, the Pol II machinery is constantly modulated by a host of activating and repressing inputs that connect transcription to the environment within and outside the cell. These second to minute-scale events underlie rapid responses to stimuli and have generated the bulk of our understanding of transcription regulation in cellular responses to environmental triggers such as heat shock, hormones such as estrogen, or innate immune responses . In addiTargeting strategies should benefit from better understanding of principles that govern the transcriptomes. This problem can be conceptually narrowed down to defining the molecular interactions that link individual genes within transcriptional networks. Given the overall conservation of the RNA polymerase II machinery , mechaniIn this section we describe some of the challenges in targeting the transcriptional machinery. These arise not only from unintended effects of drugs, which can be improved by identifying better targets and better drug design, but also from the inherent uncertainty of transcription regulation in different cellular contexts.Transcription is the ultimate target of numerous anticancer drugs that act on Pol II or the epigenetic machinery. Cancer targeting aims to either kill or reprogram cells into more benign states . To gainA second property of cancer cells is broad dysregulation of the transcriptional machinery , which aA third property of cancer cells is altered expression of genes outside of those involved in transcription. Differentially expressed genes are often marked as sources for therapeutic targets. Identifying therapeutic targets is perhaps the most common justification for basic studies over the years. Increasing our understanding of how different types of cancers work has indeed resulted in identification of targets including surface and nuclear receptors, kinases, etc . While rIdentifying causative factors for precise targeting of cancers is an attractive goal that has met serious challenges . CancersDrosophila development and stimulus responses in human cells show default repression of target genes unless activated, usually by a co-factor, thereby appearing both as repressors and activators  enhanced their dedifferentiation, but transformation of the same cells by deleting p53 or Arf tumor suppressors precluded it . SimilarIn this section we discuss a genome-wide view of transcription noting overall similarities in gene expression and highlighting potential mechanisms that might be pertinent for understanding transcriptome regulation.mRNA profiling has been widely used to identify genes with differential expression. Genome-wide gene expression patterns have been proposed as a basis to classify cancers . RNA-seqOne way to breach the boundaries of transcription control is through changing gene copy numbers. Local and chromosome-wide changes of DNA copy number is a frequent occurrence and is one of the hallmarks of cancer . ChangesWidespread accumulation of Pol II signal at promoter regions of genes has been well documented . Rather in vitro  yeast, with the latter showing pausing signatures at a significant proportion of genes (Drosophila and mammals in terms of the +1 nucleosome positioning presumably due to absence of NELF. These observations indicate that Pol II pausing is more prevalent and may be more tightly regulated in higher organisms.In considering potential biological roles of promoter-proximal Pol II pausing, it might be of significance that Pol II activity at this site is controlled by at least two distinct groups of factors: those that establish pausing and, on the other hand, those that release the Pol II from the paused state . The Negin vitro . NELF isme genes . High-reof genes . Howeverin vitro, but do appear to be essential for proper transcription in vivo (Targeting of individual NELF subunit alters the levels of its other subunits , indicat in vivo . P-TEFb  in vivo . The reqHere we discuss how transcription can be regulated by essential factors at the site of promoter-proximal Pol II pausing.E. coli, no single promoter, including for the highest expressed rRNA genes, contains a full consensus sequence of basal elements (One genome must specify the entire structure and dynamics of the transcriptomes for in every cell, but the rules of how it does so remain obscure. It is evident, however, that promoters, including core promoter basal sequence elements such as the TATA box, initiator motif, Downstream Promoter Element, etc, do not merely serve as a passive platform for the binding of regulatory factors, but actively shape the outcomes of regulatory inputs . Flexibielements . Insteadelements . Mechanielements . Differeelements .Drosophila, transcription start sites of regulatory genes contain sequences that favor both Pol II pausing and nucleosome binding at their transcription start sites (Apart from differences between promoters, another question is whether and how the genome enables the same promoters to assume distinct regulatory states. In rt sites , which rGlobal requirement for NELF- and P-TEFb raises a question about their functional relationship at the site of Pol II pausing. It has been proposed that activation of genes should proceed through pause “release,” that is, relatively increased P-TEFb activity . SustainA study from the Young lab showed that overexpression of c-Myc causes uniform amplification of all genes . Since cEither NELF or P-TEFb activities may become limiting at certain circumstances such as during rapid responses to stimuli. This raises a question of how these factors are redistributed across the genome when limited amounts or activity are available. This question is broadly related to an earlier concept of enhancer insufficiency  wherein Step-wise prioritization of essential factors retrospectively accounts for known features of mammalian transcriptomes. Some transcription factors such as HSF1 and NF-kB have been shown to act on pause release by directly or indirectly recruiting P-TEFb . P-TEFb Substantial advances are made in targeting cancers based on transcription and epigenetic signatures . Howevervia globally acting or general factors.The process of Pol II pausing is much more granular at the molecular level than described above  and incl