scholarly journals No Expression Divergence despite Transcriptional Interference between Nested Protein-Coding Genes in Mammals

Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1381
Author(s):  
Raquel Assis

Nested protein-coding genes accumulated throughout metazoan evolution, with early analyses of human and Drosophila microarray data indicating that this phenomenon was simply due to the presence of large introns. However, a recent study employing RNA-seq data uncovered evidence of transcriptional interference driving rapid expression divergence between Drosophila nested genes, illustrating that accurate expression estimation of overlapping genes can enhance detection of their relationships. Hence, here I apply an analogous approach to strand-specific RNA-seq data from human and mouse to revisit the role of transcriptional interference in the evolution of mammalian nested genes. A genomic survey reveals that whereas mammalian nested genes indeed accrued over evolutionary time, they are retained at lower frequencies than in Drosophila. Though several properties of mammalian nested genes align with observations in Drosophila and with expectations under transcriptional interference, contrary to both, their expression divergence is not statistically different from that between unnested genes, and also does not increase after nesting. Together, these results support the hypothesis that lower selection efficiencies limit rates of gene expression evolution in mammals, leading to their reliance on immediate eradication of deleterious nested genes to avoid transcriptional interference.

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.


Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5651
Author(s):  
Eleftheria Papaioannou ◽  
María del Pilar González-Molina ◽  
Ana M. Prieto-Muñoz ◽  
Laura Gámez-Reche ◽  
Alicia González-Martín

Cancer immunology research has mainly focused on the role of protein-coding genes in regulating immune responses to tumors. However, despite more than 70% of the human genome is transcribed, less than 2% encodes proteins. Many non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), have been identified as critical regulators of immune cell development and function, suggesting that they might play important roles in orchestrating immune responses against tumors. In this review, we summarize the scientific advances on the role of ncRNAs in regulating adaptive tumor immunity, and discuss their potential therapeutic value in the context of cancer immunotherapy.


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.


MicroRNA ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Arathi Jayaraman ◽  
Tong Zhou ◽  
Sundararajan Jayaraman

Background: Although the protein-coding genes are subject to histone hyperacetylation-mediated regulation, it is unclear whether microRNAs are similarly regulated in the T cell leukemia Jurkat. Objective: To determine whether treatment with the histone modifier Trichostatin A could concurrently alter the expression profiles of microRNAs and protein-coding genes. Methods: Changes in histone hyperacetylation and viability in response to drug treatment were analyzed, respectively, using western blotting and flow cytometry. Paired global expression profiling of microRNAs and coding genes was performed and highly regulated genes validated by qRT-PCR. The interrelationships between the drug-induced miR-494 upregulation, the expression of putative target genes, and T cell receptor-mediated apoptosis were evaluated using qRT-PCR, flow cytometry, and western blotting following lipid-mediated transfection with specific anti-microRNA inhibitors. Results: Treatment of Jurkat cells with Trichostatin A resulted in histone hyperacetylation and apoptosis. Global expression profiling indicated prominent upregulation of miR-494 in contrast to differential regulation of many protein-coding and non-coding genes validated by qRT-PCR. Although transfection with synthetic anti-miR-494 inhibitors failed to block drug-induced apoptosis or miR-494 upregulation, it induced the transcriptional repression of the PVRIG gene. Surprisingly, miR-494 inhibition in conjunction with low doses of Trichostatin A enhanced the weak T cell receptor-mediated apoptosis, indicating a subtle pro-survival role of miR-494. Interestingly, this pro-survival effect was overwhelmed by mitogen-mediated T cell activation and higher drug doses, which mediated caspase-dependent apoptosis. Conclusion: Our results unravel a pro-survival function of miR-494 and its putative interaction with the PVRIG gene and the apoptotic machinery in Jurkat cells.


2021 ◽  
Author(s):  
Peerzada Tajamul Mumtaz ◽  
Basharat Bhat ◽  
Eveline M. Ibeagha-Awemu ◽  
Qamar Taban ◽  
Mengqi Wang ◽  
...  

Abstract Background Long noncoding RNAs (lncRNAs) are now proven as essential regulatory elements, playing diverse role in many biological processes including mammary gland development. However, little is known about their roles in bovine lactation process. There are very few reports available to date on the role of lncRNAs in lactation physiology and mammary glands development in cattle. Results To identify and characterize the roles of lncRNAs in bovine lactation, milk derived mammary epithelial cells (MEC) from Jersey (high milk producer) and Kashmiri cattle (low milk producer) at early, mid and late lactation stages were used. The lncRNA transcriptome of the samples (n=18) was studied using next generation RNA sequencing technology. 633 putative lncRNAs were identified, 76 of which were differentially expressed (DE) between comparison between the three stages of lactation. Additionally, 56 DE lncRNAs were identified from 9 Jersey and 9 Kashmir samples. Correlation of DE lncRNAs with protein-coding genes resulted in a comprehensive list of lncRNA-mRNA co-expressed pairs. Most of the DE lncRNAs showed positive correlations with protein coding genes in Jersey compared to Kashmiri cattle where they were mainly negatively correlated, which could be one of the underlying mechanisms responsible for the differential milking performance between the two breeds. In addition, a number of the DE lncRNAs were paired with the most DE milk quality genes like GPAM, LPL, ABCG2, etc. indicative of their potential regulatory effects on milk quality genes. KEGG pathways analysis of potential cis and trans target genes of DE lncRNAs indicated that 27 and 48 pathways were significantly enriched in Kashmiri and Jersey respectively, including mTOR signaling, PI3K-Akt signaling and RAP1 signaling pathways. These pathways have been proven to play key roles in lactation biology and mammary gland development. Conclusions Our study mapped the expression profiles of lncRNAs across lactation stages and their relationships with candidate genes related to milk quality and yield traits in Jersey and Kashmiri cattle. These findings provide a valuable resource for the study of the regulatory mechanisms involved in the lactation process as well as facilitate understanding of the role of lncRNAs in bovine lactation biology.


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