scholarly journals Control of Gene Expression in Senescence through Transcriptional Read-Through of Convergent Protein-Coding Genes

Cell Reports ◽  
2017 ◽  
Vol 21 (9) ◽  
pp. 2433-2446 ◽  
Author(s):  
Lisa Muniz ◽  
Maharshi Krishna Deb ◽  
Marion Aguirrebengoa ◽  
Sandra Lazorthes ◽  
Didier Trouche ◽  
...  
Author(s):  
Adham Safieddine ◽  
Emeline Coleno ◽  
Abdel-Meneem Traboulsi ◽  
Oh Sung Kwon ◽  
Frederic Lionneton ◽  
...  

AbstractLocal translation allows for a spatial control of gene expression. Here, we used high-throughput smFISH to screen centrosomal protein-coding genes, and we describe 8 human mRNAs accumulating at centrosomes. These mRNAs localize at different stages during cell cycle with a remarkable choreography, indicating a finely regulated translational program at centrosomes. Interestingly, drug treatments and reporter analyses revealed a common translation-dependent localization mechanism requiring the nascent protein. Using ASPM and NUMA1 as models, single mRNA and polysome imaging revealed active movements of endogenous polysomes towards the centrosome at the onset of mitosis, when these mRNAs start localizing. ASPM polysomes associate with microtubules and localize by either motor-driven transport or microtubule pulling. Remarkably, the Drosophila orthologs of the human centrosomal mRNAs also localize to centrosomes and also require translation. These data identify a conserved family of centrosomal mRNAs that localize by active polysomes transport mediated by nascent proteins.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Adham Safieddine ◽  
Emeline Coleno ◽  
Soha Salloum ◽  
Arthur Imbert ◽  
Abdel-Meneem Traboulsi ◽  
...  

AbstractLocal translation allows for a spatial control of gene expression. Here, we use high-throughput smFISH to screen centrosomal protein-coding genes, and we describe 8 human mRNAs accumulating at centrosomes. These mRNAs localize at different stages during cell cycle with a remarkable choreography, indicating a finely regulated translational program at centrosomes. Interestingly, drug treatments and reporter analyses reveal a common translation-dependent localization mechanism requiring the nascent protein. UsingASPMandNUMA1as models, single mRNA and polysome imaging reveals active movements of endogenous polysomes towards the centrosome at the onset of mitosis, when these mRNAs start localizing. ASPM polysomes associate with microtubules and localize by either motor-driven transport or microtubule pulling. Remarkably, theDrosophilaorthologs of the human centrosomal mRNAs also localize to centrosomes and also require translation. These data identify a conserved family of centrosomal mRNAs that localize by active polysome transport mediated by nascent proteins.


2017 ◽  
Author(s):  
Cristina Cruz ◽  
Monica Della Rosa ◽  
Christel Krueger ◽  
Qian Gao ◽  
Lucy Field ◽  
...  

AbstractTranscription of protein coding genes is accompanied by recruitment of COMPASS to promoter-proximal chromatin, which deposits di- and tri-methylation on histone H3 lysine 4 (H3K4) to form H3K4me2 and H3K4me3. Here we determine the importance of COMPASS in maintaining gene expression across lifespan in budding yeast. We find that COMPASS mutations dramatically reduce replicative lifespan and cause widespread gene expression defects. Known repressive functions of H3K4me2 are progressively lost with age, while hundreds of genes become dependent on H3K4me3 for full expression. Induction of these H3K4me3 dependent genes is also impacted in young cells lacking COMPASS components including the H3K4me3-specific factor Spp1. Remarkably, the genome-wide occurrence of H3K4me3 is progressively reduced with age despite widespread transcriptional induction, minimising the normal positive correlation between promoter H3K4me3 and gene expression. Our results provide clear evidence that H3K4me3 is required to attain normal expression levels of many genes across organismal lifespan.


2020 ◽  
Vol 35 (5) ◽  
pp. 1230-1245 ◽  
Author(s):  
L C Poulsen ◽  
J A Bøtkjær ◽  
O Østrup ◽  
K B Petersen ◽  
C Yding Andersen ◽  
...  

Abstract STUDY QUESTION How does the human granulosa cell (GC) transcriptome change during ovulation? SUMMARY ANSWER Two transcriptional peaks were observed at 12 h and at 36 h after induction of ovulation, both dominated by genes and pathways known from the inflammatory system. WHAT IS KNOWN ALREADY The crosstalk between GCs and the oocyte, which is essential for ovulation and oocyte maturation, can be assessed through transcriptomic profiling of GCs. Detailed transcriptional changes during ovulation have not previously been assessed in humans. STUDY DESIGN, SIZE, DURATION This prospective cohort study comprised 50 women undergoing fertility treatment in a standard antagonist protocol at a university hospital-affiliated fertility clinic in 2016–2018. PARTICIPANTS/MATERIALS, SETTING, METHODS From each woman, one sample of GCs was collected by transvaginal ultrasound-guided follicle aspiration either before or 12 h, 17 h or 32 h after ovulation induction (OI). A second sample was collected at oocyte retrieval, 36 h after OI. Total RNA was isolated from GCs and analyzed by microarray. Gene expression differences between the five time points were assessed by ANOVA with a random factor accounting for the pairing of samples, and seven clusters of protein-coding genes representing distinct expression profiles were identified. These were used as input for subsequent bioinformatic analyses to identify enriched pathways and suggest upstream regulators. Subsets of genes were assessed to explore specific ovulatory functions. MAIN RESULTS AND THE ROLE OF CHANCE We identified 13 345 differentially expressed transcripts across the five time points (false discovery rate, <0.01) of which 58% were protein-coding genes. Two clusters of mainly downregulated genes represented cell cycle pathways and DNA repair. Upregulated genes showed one peak at 12 h that resembled the initiation of an inflammatory response, and one peak at 36 h that resembled the effector functions of inflammation such as vasodilation, angiogenesis, coagulation, chemotaxis and tissue remodelling. Genes involved in cell–matrix interactions as a part of cytoskeletal rearrangement and cell motility were also upregulated at 36 h. Predicted activated upstream regulators of ovulation included FSH, LH, transforming growth factor B1, tumour necrosis factor, nuclear factor kappa-light-chain-enhancer of activated B cells, coagulation factor 2, fibroblast growth factor 2, interleukin 1 and cortisol, among others. The results confirmed early regulation of several previously described factors in a cascade inducing meiotic resumption and suggested new factors involved in cumulus expansion and follicle rupture through co-regulation with previously described factors. LARGE SCALE DATA The microarray data were deposited to the Gene Expression Omnibus (www.ncbi.nlm.nih.gov/gds/, accession number: GSE133868). LIMITATIONS, REASONS FOR CAUTION The study included women undergoing ovarian stimulation and the findings may therefore differ from a natural cycle. However, the results confirm significant regulation of many well-established ovulatory genes from a series of previous studies such as amphiregulin, epiregulin, tumour necrosis factor alfa induced protein 6, tissue inhibitor of metallopeptidases 1 and plasminogen activator inhibitor 1, which support the relevance of the results. WIDER IMPLICATIONS OF THE FINDINGS The study increases our understanding of human ovarian function during ovulation, and the publicly available dataset is a valuable resource for future investigations. Suggested upstream regulators and highly differentially expressed genes may be potential pharmaceutical targets in fertility treatment and gynaecology. STUDY FUNDING/COMPETING INTEREST(S) The study was funded by EU Interreg ÔKS V through ReproUnion (www.reprounion.eu) and by a grant from the Region Zealand Research Foundation. None of the authors have any conflicts of interest to declare.


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.


2012 ◽  
Vol 209 (13) ◽  
pp. 2455-2465 ◽  
Author(s):  
Katia Basso ◽  
Christof Schneider ◽  
Qiong Shen ◽  
Antony B. Holmes ◽  
Manu Setty ◽  
...  

The BCL6 proto-oncogene encodes a transcriptional repressor that is required for germinal center (GC) formation and whose de-regulation is involved in lymphomagenesis. Although substantial evidence indicates that BCL6 exerts its function by repressing the transcription of hundreds of protein-coding genes, its potential role in regulating gene expression via microRNAs (miRNAs) is not known. We have identified a core of 15 miRNAs that show binding of BCL6 in their genomic loci and are down-regulated in GC B cells. Among BCL6 validated targets, miR-155 and miR-361 directly modulate AID expression, indicating that via repression of these miRNAs, BCL6 up-regulates AID. Similarly, the expression of additional genes relevant for the GC phenotype, including SPI1, IRF8, and MYB, appears to be sustained via BCL6-mediated repression of miR-155. These findings identify a novel mechanism by which BCL6, in addition to repressing protein coding genes, promotes the expression of important GC functions by repressing specific miRNAs.


2021 ◽  
Vol 4 (1) ◽  
pp. e00144
Author(s):  
K.A. Deinichenko ◽  
G.S. Krasnov ◽  
S.P. Radko ◽  
K.G. Ptitsyn ◽  
V.V. Shapovalova ◽  
...  

Missing (MP) and functionally uncharacterized proteins (uPE1) comprise less than 5% of the total number of proteins encoded by human Chr18 genes. Within half a year, since the January 2020 version of NextProt, the number of entries in the MP+uPE1 datasets changed, mainly due to the achievements of antibody-based proteomics. Assuming that the proteome is closely related to the transcriptome scaffold, quantitative PCR, Illumina HiSeq, and Oxford Nanopore Technology were applied to characterize the liver samples of three male donors in comparison with the HepG2 cell line. The data mining of the Expression Atlas (EMBL-EBI) and the profiling of biopsy samples by using orthogonal methods of transcriptome analysis have shown that in HepG2 cells and the liver, the genes encoding functionally uncharacterized proteins (uPE1) are expressed as low as for the missing proteins (less than 1 copy per cell), except the selected cases of HSBP1L1, TMEM241, C18orf21, and KLHL14. The initial expectation that uPE1 genes might be expressed at higher levels than MP genes, was compromised by severe discrepancies in our semi-quantitative gene expression data and in public databanks. Such discrepancy forced us to revisit the transcriptome of Chr18, the target of the Russian C-HPP Consortium. Tanglegram of highly expressed genes and further correlation analysis have shown the severe dependencies on the mRNA extraction method and the analytical platform. Targeted gene expression analysis by quantitative PCR (qPCR) and high-throughput transcriptome profiling (Illumina HiSeq and ONT MinION) for the same set of samples from normal liver tissue and HepG2 cells revealed the detectable expression of 250+ (92%) protein-coding genes of Chr18 (at least one method). The expression of slightly more than 50% protein-coding genes was detected simultaneously by all three methods. Correlation analysis of the gene expression profiles showed that the grouping of the datasets depended almost equally on both the type of biological material and the experimental method, particularly cDNA/mRNA isolation and library preparation.


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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