scholarly journals The Integrator complex cleaves nascent mRNAs to attenuate transcription

2019 ◽  
Author(s):  
Deirdre C. Tatomer ◽  
Nathan D. Elrod ◽  
Dongming Liang ◽  
Mei-Sheng Xiao ◽  
Jeffrey Z. Jiang ◽  
...  

ABSTRACTCellular homeostasis requires transcriptional outputs to be coordinated, and many events post transcription initiation can dictate the levels and functions of mature transcripts. To systematically identify regulators of inducible gene expression, we performed high-throughput RNAi screening of the Drosophila Metallothionein A (MtnA) promoter. This revealed that the Integrator complex, which has a well-established role in 3’ end processing of small nuclear RNAs (snRNAs), attenuates MtnA transcription during copper stress. Integrator complex subunit 11 (IntS11) endonucleolytically cleaves MtnA transcripts, resulting in premature transcription termination and degradation of the nascent RNAs by the RNA exosome, a complex also identified in the screen. Using RNA-seq, we then identified >400 additional Drosophila protein-coding genes whose expression increases upon Integrator depletion. We focused on a subset of these genes and confirmed that Integrator is bound to their 5’ ends and negatively regulates their transcription via IntS11 endonuclease activity. Many non-catalytic Integrator subunits, which are largely dispensable for snRNA processing, also have regulatory roles at these protein-coding genes, possibly by controlling Integrator recruitment or RNA polymerase II dynamics. Altogether, our results suggest that attenuation via Integrator cleavage limits production of many full-length mRNAs, allowing precise control of transcription outputs.

2013 ◽  
Vol 103 (5) ◽  
pp. 479-487 ◽  
Author(s):  
Efrén Remesal ◽  
Blanca B. Landa ◽  
María del Mar Jiménez-Gasco ◽  
Juan A. Navas-Cortés

Populations of Sclerotium rolfsii, the causal organism of Sclerotium root-rot on a wide range of hosts, can be placed into mycelial compatibility groups (MCGs). In this study, we evaluated three different molecular approaches to unequivocally identify each of 12 previously identified MCGs. These included restriction fragment length polymorphism (RFLP) patterns of the internal transcribed spacer (ITS) region of nuclear ribosomal DNA (rDNA) and sequence analysis of two protein-coding genes: translation elongation factor 1α (EF1α) and RNA polymerase II subunit two (RPB2). A collection of 238 single-sclerotial isolates representing 12 MCGs of S. rolfsii were obtained from diseased sugar beet plants from Chile, Italy, Portugal, and Spain. ITS-RFLP analysis using four restriction enzymes (AluI, HpaII, RsaI, and MboI) displayed a low degree of variability among MCGs. Only three different restriction profiles were identified among S. rolfsii isolates, with no correlation to MCG or to geographic origin. Based on nucleotide polymorphisms, the RPB2 gene was more variable among MCGs compared with the EF1α gene. Thus, 10 of 12 MCGs could be characterized utilizing the RPB2 region only, while the EF1α region resolved 7 MCGs. However, the analysis of combined partial sequences of EF1α and RPB2 genes allowed discrimination among each of the 12 MCGs. All isolates belonging to the same MCG showed identical nucleotide sequences that differed by at least in one nucleotide from a different MCG. The consistency of our results to identify the MCG of a given S. rolfsii isolate using the combined sequences of EF1α and RPB2 genes was confirmed using blind trials. Our study demonstrates that sequence variation in the protein-coding genes EF1α and RPB2 may be exploited as a diagnostic tool for MCG typing in S. rolfsii as well as to identify previously undescribed MCGs.


2021 ◽  
Vol 90 (1) ◽  
pp. 193-219
Author(s):  
Emmanuel Compe ◽  
Jean-Marc Egly

In eukaryotes, transcription of protein-coding genes requires the assembly at core promoters of a large preinitiation machinery containing RNA polymerase II (RNAPII) and general transcription factors (GTFs). Transcription is potentiated by regulatory elements called enhancers, which are recognized by specific DNA-binding transcription factors that recruit cofactors and convey, following chromatin remodeling, the activating cues to the preinitiation complex. This review summarizes nearly five decades of work on transcription initiation by describing the sequential recruitment of diverse molecular players including the GTFs, the Mediator complex, and DNA repair factors that support RNAPII to enable RNA synthesis. The elucidation of the transcription initiation mechanism has greatly benefited from the study of altered transcription components associated with human diseases that could be considered transcription syndromes.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail Pomaznoy ◽  
Ashu Sethi ◽  
Jason Greenbaum ◽  
Bjoern Peters

Abstract RNA-seq methods are widely utilized for transcriptomic profiling of biological samples. However, there are known caveats of this technology which can skew the gene expression estimates. Specifically, if the library preparation protocol does not retain RNA strand information then some genes can be erroneously quantitated. Although strand-specific protocols have been established, a significant portion of RNA-seq data is generated in non-strand-specific manner. We used a comprehensive stranded RNA-seq dataset of 15 blood cell types to identify genes for which expression would be erroneously estimated if strand information was not available. We found that about 10% of all genes and 2.5% of protein coding genes have a two-fold or higher difference in estimated expression when strand information of the reads was ignored. We used parameters of read alignments of these genes to construct a machine learning model that can identify which genes in an unstranded dataset might have incorrect expression estimates and which ones do not. We also show that differential expression analysis of genes with biased expression estimates in unstranded read data can be recovered by limiting the reads considered to those which span exonic boundaries. The resulting approach is implemented as a package available at https://github.com/mikpom/uslcount.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lars Gabriel ◽  
Katharina J. Hoff ◽  
Tomáš Brůna ◽  
Mark Borodovsky ◽  
Mario Stanke

Abstract Background BRAKER is a suite of automatic pipelines, BRAKER1 and BRAKER2, for the accurate annotation of protein-coding genes in eukaryotic genomes. Each pipeline trains statistical models of protein-coding genes based on provided evidence and, then predicts protein-coding genes in genomic sequences using both the extrinsic evidence and statistical models. For training and prediction, BRAKER1 and BRAKER2 incorporate complementary extrinsic evidence: BRAKER1 uses only RNA-seq data while BRAKER2 uses only a database of cross-species proteins. The BRAKER suite has so far not been able to reliably exceed the accuracy of BRAKER1 and BRAKER2 when incorporating both types of evidence simultaneously. Currently, for a novel genome project where both RNA-seq and protein data are available, the best option is to run both pipelines independently, and to pick one, likely better output. Therefore, one or another type of the extrinsic evidence would remain unexploited. Results We present TSEBRA, a software that selects gene predictions (transcripts) from the sets generated by BRAKER1 and BRAKER2. TSEBRA uses a set of rules to compare scores of overlapping transcripts based on their support by RNA-seq and homologous protein evidence. We show in computational experiments on genomes of 11 species that TSEBRA achieves higher accuracy than either BRAKER1 or BRAKER2 running alone and that TSEBRA compares favorably with the combiner tool EVidenceModeler. Conclusion TSEBRA is an easy-to-use and fast software tool. It can be used in concert with the BRAKER pipeline to generate a gene prediction set supported by both RNA-seq and homologous protein evidence.


2021 ◽  
Author(s):  
Hanneke Vlaming ◽  
Claudia A Mimoso ◽  
Benjamin JE Martin ◽  
Andrew R Field ◽  
Karen Adelman

Organismal growth and development rely on RNA Polymerase II (RNAPII) synthesizing the appropriate repertoire of messenger RNAs (mRNAs) from protein-coding genes. Productive elongation of full-length transcripts is essential for mRNA function, however what determines whether an engaged RNAPII molecule will terminate prematurely or transcribe processively remains poorly understood. Notably, despite a common process for transcription initiation across RNAPII-synthesized RNAs, RNAPII is highly susceptible to termination when transcribing non-coding RNAs such as upstream antisense RNAs (uaRNAs) and enhancers RNAs (eRNAs), suggesting that differences arise during RNAPII elongation. To investigate the impact of transcribed sequence on elongation potential, we developed a method to screen the effects of thousands of INtegrated Sequences on Expression of RNA and Translation using high-throughput sequencing (INSERT-seq). We found that higher AT content in uaRNAs and eRNAs, rather than specific sequence motifs, underlies the propensity for RNAPII termination on these transcripts. Further, we demonstrate that 5' splice sites exert both splicing-dependent and autonomous, splicing-independent stimulation of transcription, even in the absence of polyadenylation signals. Together, our results reveal a potent role for transcribed sequence in dictating gene output at mRNA and non-coding RNA loci, and demonstrate the power of INSERT-seq towards illuminating these contributions.


Author(s):  
Zhaolian Lu ◽  
Zhenguo Lin

ABSTRACTThe molecular process of transcription by RNA Polymerase II is highly conserved among eukaryotes (“classic model”). Intriguingly, a distinct way of locating transcription start sites (TSSs) was found in a budding yeast Saccharomyces cerevisiae (“scanning model”). The origin of the “scanning model” and its underlying genetic mechanisms remain unsolved. Herein, we applied genomic approaches to address these questions. We first identified TSSs at a single-nucleotide resolution for 12 yeast species using the nAnT-iCAGE technique, which significantly improved the annotations of these genomes by providing accurate 5’boundaries of protein-coding genes. We then infer the initiation mechanism of a species based on its TSS maps and genome sequences. We found that the “scanning model” had originated after the split of Yarrowia lipolytica and the rest of budding yeasts. An adenine-rich region immediately upstream of TSS had appeared during the evolution of the “scanning model” species, which might facilitate TSS selection in these species. Both initiation mechanisms share a strong preference for pyrimidine-purine dinucleotides surrounding the TSS. Our results suggested that the purine is required for accurately recruiting the first nucleotide, increasing the chance of being capped during mRNA maturation, which is critical for efficient translation initiation. Based on our findings, we proposed a model of TSS selection for the “scanning model” species. Besides, our study also demonstrated that the intrinsic sequence feature primarily determines the distribution of initiation activities within a core promoter (core promoter shape).


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2705-2705 ◽  
Author(s):  
Lara Rizzotto ◽  
Arianna Bottoni ◽  
Tzung-Huei Lai ◽  
Chaomei Liu ◽  
Pearlly S Yan ◽  
...  

Abstract Chronic lymphocytic leukemia (CLL) follows a variable clinical course mostly dependent upon genomic factors, with a subset of patients having low risk disease and others displaying rapid progression associated with clonal evolution. Epigenetic mechanisms such as DNA promoter hypermethylation were shown to have a role in CLL evolution where the acquisition of increasingly heterogeneous DNA methylation patters occurred in conjunction with clonal evolution of genetic aberrations and was associated with disease progression. However the role of epigenetic mechanisms regulated by the histone deacetylase group of transcriptional repressors in the progression of CLL has not been well characterized. The histone deacetylases (HDACs) 1 and 2 are recruited onto gene promoters and form a complex with the histone demethylase KDM1. Once recruited, the complex mediate the removal of acetyl groups from specific lysines on histones (H3K9 and H3K14) thus triggering the demethylation of lysine 4 (H3K4me3) and the silencing of gene expression. CLL is characterized by the dysregulation of numerous coding and non coding genes, many of which have key roles in regulating the survival or progression of CLL. For instance, our group showed that the levels of HDAC1 were elevated in high risk as compared to low risk CLL or normal lymphocytes and this over-expression was responsible for the silencing of miR-106b, mR-15, miR-16, and miR-29b which affected CLL survival by modulating the expression of key anti-apoptotic proteins Bcl-2 and Mcl-1. To characterize the HDAC-repressed gene signature in high risk CLL, we conducted chromatin immunoprecipitation (ChIP) of the nuclear lysates from 3 high risk and 3 low risk CLL patients using antibodies against HDAC1, HDAC2 and KDM1 or non-specific IgG, sequenced and aligned the eluted DNA to a reference genome and determined the binding of HDAC1, HDAC2 and KDM1 at the promoters for all protein coding and microRNA genes. Preliminary results from this ChIP-seq showed a strong recruitment of HDAC1, HDAC2 and KDM1 to the promoters of several microRNA as well as protein coding genes in high risk CLL. To further corroborate these data we performed ChIP-Seq in the same 6 CLL samples to analyze the levels of H3K4me2 and H3K4me3 around gene promoters before and after 6h exposure to the HDACi panobinostat. Our goal was to demonstrate that HDAC inhibition elicited an increase in the levels of acetylation on histones and triggered the accrual of H3K4me2 at the repressed promoter, events likely to facilitate the recruitment of RNA polymerase II to this promoter. Initial analysis confirmed a robust accumulation of H3K4me2 and H3K4me3 marks at the gene promoters of representative genes that recruited HDAC1 and its co-repressors in the previous ChIP-Seq analysis in high risk CLL patients. Finally, 5 aggressive CLL samples were treated with the HDACi abexinostat for 48h and RNA before and after treatment was subjected to RNA-seq for small and large RNA to confirm that the regions of chromatin uncoiled by HDACi treatment were actively transcribed. HDAC inhibition induced the expression of a large number of miRNA genes as well as key protein coding genes, such as miR-29b, miR-210, miR-182, miR-183, miR-95, miR-940, FOXO3, EBF1 and BCL2L11. Of note, some of the predicted or validated targets of the induced miRNAs were key facilitators in the progression of CLL, such as BTK, SYK, MCL-1, BCL-2, TCL1, and ROR1. Moreover, RNA-seq showed that the expression of these protein coding genes was reduced by 2-33 folds upon HDAC inhibition. We plan to extend the RNA-seq to 5 CLL samples with indolent disease and combine all the data to identify a common signature of protein coding and miRNA genes that recruited the HDAC1 complex, accumulated activating histone modifications upon treatment with HDACi and altered gene and miRNA expression after HDAC inhibition in high risk CLL versus low risk CLL. The signature will be than validated on a large cohort of indolent and aggressive CLL patients. Our final goal is to define a signature of coding and non coding genes silenced by HDACs in high risk CLL and its role in facilitating disease progression. Disclosures Woyach: Acerta: Research Funding; Karyopharm: Research Funding; Morphosys: Research Funding.


2013 ◽  
Vol 21 (3-4) ◽  
pp. 118-124 ◽  
Author(s):  
Rajendra Bhadane ◽  
Rupali Bhadane ◽  
Dhananjay Meshram

Guanine rich sequences have the ability to fold into stable 4 stranded structures called G-quadruplex under physiological concentrations of Na+ or K+. G-quadruplexes are found in telomeres, being stable structures under the control of telomerase binding proteins. They are also identified throughout the genome and are enriched in promoter regions of protein coding genes, upstream and downstream of the transcription initiation sites. A number of these promoter quadruplexes have been investigated for several proto-oncogenes. The formation of these quadruplexes can lead to chemical intervention of gene expression using a G-quadruplex binding ligand. We review location, configuration, and stabilization of these quadruplexes in some of the important promoters with regards to their potential as anticancer target.


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