scholarly journals Ribo-Seq and RNA-Seq of TMA46 (DFRP1) and GIR2 (DFRP2) knockout yeast strains

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1162
Author(s):  
Artyom A. Egorov ◽  
Desislava S. Makeeva ◽  
Nadezhda E. Makarova ◽  
Dmitri A. Bykov ◽  
Yanislav S. Hrytseniuk ◽  
...  
Keyword(s):  
Mrna Translation ◽  
Gene Expression Omnibus ◽  
Ribosome Profiling ◽  
Rna Seq ◽  
General Stress Response ◽  
Ncbi Gene Expression Omnibus ◽  
Ribosome Stalling ◽  
Link Type ◽  
Gene Level

In eukaryotes, stalled and collided ribosomes are recognized by several conserved multicomponent systems, which either block protein synthesis in situ and resolve the collision locally, or trigger a general stress response. Yeast ribosome-binding GTPases RBG1 (DRG1 in mammals) and RBG2 (DRG2) form two distinct heterodimers with TMA46 (DFRP1) and GIR2 (DFRP2), respectively, both involved in mRNA translation. Accumulated evidence suggests that the dimers play partially redundant roles in elongation processivity and resolution of ribosome stalling and collision events, as well as in the regulation of GCN1-mediated signaling involved in ribosome-associated quality control (RQC). They also genetically interact with SLH1 (ASCC3) helicase, a key component of RQC trigger (RQT) complex disassembling collided ribosomes. Here, we present RNA-Seq and ribosome profiling (Ribo-Seq) data from S. cerevisiae strains with individual deletions of the TMA46 and GIR2 genes. Raw RNA-Seq and Ribo-Seq data as well as gene-level read counts are available in NCBI Gene Expression Omnibus (GEO) repository under GEO accession GSE185458 and GSE185286.

scholarly journals Genetic removal of p70 S6K1 corrects coding sequence length-dependent alterations in mRNA translation in fragile X syndrome mice

2020 ◽  
Author(s):  
Sameer Aryal ◽  
Francesco Longo ◽  
Eric Klann
Keyword(s):  
Protein Synthesis ◽  
Fragile X Syndrome ◽  
Fragile X ◽  
Mrna Translation ◽  
Ribosome Profiling ◽  
Sequence Length ◽  
Rna Seq ◽  
Double Knockout ◽  
Coding Sequence ◽  
Mental Retardation Protein

AbstractLoss of the fragile X mental retardation protein (FMRP) causes fragile X syndrome (FXS). FMRP is widely thought to repress protein synthesis, but its translational targets and modes of control remain in dispute. We previously showed that genetic removal of p70 S6 kinase 1 (S6K1) corrects altered protein synthesis as well as synaptic and behavioral phenotypes in FXS mice. In this study, we examined the gene-specificity of altered mRNA translation in FXS and the mechanism of rescue with genetic reduction of S6K1 by carrying out ribosome profiling and RNA-Seq on cortical lysates from wild-type, FXS, S6K1 knockout, and double knockout mice. We observed reduced ribosome footprint abundance in the majority of differentially translated genes in the cortices of FXS mice. We used molecular assays to discover evidence that the reduction in ribosome footprint abundance reflects an increased rate of ribosome translocation, which is captured as a decrease in the number of translating ribosomes at steady state, and is normalized by inhibition of S6K1. We also found that genetic removal of S6K1 prevented a positive-to-negative gradation of alterations in translation efficiencies (RF/mRNA) with coding sequence length across mRNAs in FXS mouse cortices. Our findings reveal the identities of dysregulated mRNAs and a molecular mechanism by which reduction of S6K1 prevents altered translation in FXS.

scholarly journals Transcriptome Analysis of the Thymus in Short-Term Calorie-Restricted Mice Using RNA-seq

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zehra Omeroğlu Ulu ◽  
Salih Ulu ◽  
Soner Dogan ◽  
Bilge Guvenc Tuna ◽  
Nehir Ozdemir Ozgenturk
Keyword(s):  
Calorie Restriction ◽  
Critical Role ◽  
Gene Expression Omnibus ◽  
Cdna Libraries ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Ncbi Gene Expression Omnibus ◽  
Important Player ◽  
Feeding Regimes ◽  
Geo Database

Calorie restriction (CR), which is a factor that expands lifespan and an important player in immune response, is an effective protective method against cancer development. Thymus, which plays a critical role in the development of the immune system, reacts to nutrition deficiency quickly. RNA-seq-based transcriptome sequencing was performed to thymus tissues of MMTV-TGF-α mice subjected to ad libitum (AL), chronic calorie restriction (CCR), and intermittent calorie restriction (ICR) diets in this study. Three cDNA libraries were sequenced using Illumina HiSeq™ 4000 to produce 100 base pair-end reads. On average, 105 million clean reads were mapped and in total 6091 significantly differentially expressed genes (DEGs) were identified (p<0.05). These DEGs were clustered into Gene Ontology (GO) categories. The expression pattern revealed by RNA-seq was validated by quantitative real-time PCR (qPCR) analysis of four important genes, which are leptin, ghrelin, Igf1, and adinopectin. RNA-seq data has been deposited in NCBI Gene Expression Omnibus (GEO) database (GSE95371). We report the use of RNA sequencing to find DEGs that are affected by different feeding regimes in the thymus.

scholarly journals A curated transcriptome dataset collection to investigate the development and differentiation of the human placenta and its associated pathologies

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 305 ◽  
Author(s):  
Alexandra K. Marr ◽  
Sabri Boughorbel ◽  
Scott Presnell ◽  
Charlie Quinn ◽  
Damien Chaussabel ◽  
...  
Keyword(s):  
Human Placenta ◽  
Large Scale ◽  
Current Knowledge ◽  
Single Gene ◽  
Gene Expression Omnibus ◽  
Ncbi Gene Expression Omnibus ◽  
Link Type ◽  
Interactive Query ◽  
Public Repositories ◽  
Data Browsing

Compendia of large-scale datasets made available in public repositories provide a precious opportunity to discover new biomedical phenomena and to fill gaps in our current knowledge. In order to foster novel insights it is necessary to ensure that these data are made readily accessible to research investigators in an interpretable format. Here we make a curated, public, collection of transcriptome datasets relevant to human placenta biology available for further analysis and interpretation via an interactive data browsing interface. We identified and retrieved a total of 24 datasets encompassing 759 transcriptome profiles associated with the development of the human placenta and associated pathologies from the NCBI Gene Expression Omnibus (GEO) and present them in a custom web-based application designed for interactive query and visualization of integrated large-scale datasets (http://placentalendocrinology.gxbsidra.org/dm3/landing.gsp). We also performed quality control checks using relevant biological markers. Multiple sample groupings and rank lists were subsequently created to facilitate data query and interpretation. Via this interface, users can create web-links to customized graphical views which may be inserted into manuscripts for further dissemination, or e-mailed to collaborators for discussion. The tool also enables users to browse a single gene across different projects, providing a mechanism for  developing new perspectives on the role of a molecule of interest across multiple biological states. The dataset collection we created here is available at: http://placentalendocrinology.gxbsidra.org/dm3.

scholarly journals GEO2RNAseq: An easy-to-use R pipeline for complete pre-processing of RNA-seq data

2019 ◽  
Author(s):  
Bastian Seelbinder ◽  
Thomas Wolf ◽  
Steffen Priebe ◽  
Sylvie McNamara ◽  
Silvia Gerber ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Species ◽  
Gene Expression Omnibus ◽  
Rna Seq ◽  
Sequencing Data ◽  
Interacting Species ◽  
Link Type ◽  
Fastq Format ◽  
Standard Tool ◽  
Processing Steps

ABSTRACTIn transcriptomics, the study of the total set of RNAs transcribed by the cell, RNA sequencing (RNA-seq) has become the standard tool for analysing gene expression. The primary goal is the detection of genes whose expression changes significantly between two or more conditions, either for a single species or for two or more interacting species at the same time (dual RNA-seq, triple RNA-seq and so forth). The analysis of RNA-seq can be simplified as many steps of the data pre-processing can be standardised in a pipeline.In this publication we present the “GEO2RNAseq” pipeline for complete, quick and concurrent pre-processing of single, dual, and triple RNA-seq data. It covers all pre-processing steps starting from raw sequencing data to the analysis of differentially expressed genes, including various tables and figures to report intermediate and final results. Raw data may be provided in FASTQ format or can be downloaded automatically from the Gene Expression Omnibus repository. GEO2RNAseq strongly incorporates experimental as well as computational metadata. GEO2RNAseq is implemented in R, lightweight, easy to install via Conda and easy to use, but still very flexible through using modular programming and offering many extensions and alternative workflows.GEO2RNAseq is publicly available at https://anaconda.org/xentrics/r-geo2rnaseq and https://bitbucket.org/thomas_wolf/geo2rnaseq/overview, including source code, installation instruction, and comprehensive package documentation.

scholarly journals Elysium: RNA-seq Alignment in the Cloud

2018 ◽  
Author(s):  
Alexander Lachmann ◽  
Zhuorui Xie ◽  
Avi Ma’ayan
Keyword(s):  
Job Scheduling ◽  
Rna Seq ◽  
Skill Levels ◽  
Transcript Quantification ◽  
Link Type ◽  
Genome Wide ◽  
Gene Level ◽  
Programming Knowledge ◽  
Computational Resources ◽  
Alignment Step

MotivationRNA-sequencing (RNA-seq) is currently the leading technology for genome-wide transcript quantification. Mapping the raw reads to transcript and gene level counts can be achieved by a variety of aligners and pipelines. The diversity of processing options reduces interoperability. In addition, the alignment step requires significant computational resources and basic programming knowledge. Elysium enables users of all skill levels to perform a uniform and free RNA-seq alignment in the cloud.ResultsThe Elysium infrastructure is comprised of four components: A file upload API that enables storage of FASTQ files on Amazon S3 without Amazon credentials; an API to handle the cloud alignment job scheduling for uploaded files; and a graphical user interface (GUI) to provide intuitive access to users that do not have command-line access skills.AvailabilityThe Elysium source code is available under the Apache Licence 2.0 on GitHub at: https://github.com/maayanlab/elysiumThe service of cloud based RNA-seq alignment is freely accessible through the Elysium GUI at: http://elysium.cloud

scholarly journals A curated transcriptome dataset collection to investigate the development and differentiation of the human placenta and its associated pathologies

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 305 ◽  
Author(s):  
Alexandra K. Marr ◽  
Sabri Boughorbel ◽  
Scott Presnell ◽  
Charlie Quinn ◽  
Damien Chaussabel ◽  
...  
Keyword(s):  
Human Placenta ◽  
Large Scale ◽  
Current Knowledge ◽  
Single Gene ◽  
Gene Expression Omnibus ◽  
Ncbi Gene Expression Omnibus ◽  
Link Type ◽  
Interactive Query ◽  
Public Repositories ◽  
Data Browsing

Compendia of large-scale datasets made available in public repositories provide a precious opportunity to discover new biomedical phenomena and to fill gaps in our current knowledge. In order to foster novel insights it is necessary to ensure that these data are made readily accessible to research investigators in an interpretable format. Here we make a curated, public, collection of transcriptome datasets relevant to human placenta biology available for further analysis and interpretation via an interactive data browsing interface. We identified and retrieved a total of 24 datasets encompassing 759 transcriptome profiles associated with the development of the human placenta and associated pathologies from the NCBI Gene Expression Omnibus (GEO) and present them in a custom web-based application designed for interactive query and visualization of integrated large-scale datasets (http://placentalendocrinology.gxbsidra.org/dm3/landing.gsp). We also performed quality control checks using relevant biological markers. Multiple sample groupings and rank lists were subsequently created to facilitate data query and interpretation. Via this interface, users can create web-links to customized graphical views which may be inserted into manuscripts for further dissemination, or e-mailed to collaborators for discussion. The tool also enables users to browse a single gene across different projects, providing a mechanism for  developing new perspectives on the role of a molecule of interest across multiple biological states. The dataset collection we created here is available at: http://placentalendocrinology.gxbsidra.org/dm3.

scholarly journals GREIN: An Interactive Web Platform for Reanalyzing GEO RNA-seq Data

2018 ◽  
Author(s):  
Naim Al Mahi ◽  
Mehdi Fazel Najafabadi ◽  
Marcin Pilarczyk ◽  
Michal Kouril ◽  
Mario Medvedovic
Keyword(s):  
Gene Expression ◽  
User Interfaces ◽  
Web Application ◽  
Statistical Power ◽  
Functional Characterization ◽  
Gene Expression Omnibus ◽  
Rna Seq ◽  
Link Type ◽  
Front End ◽  
User Friendly

ABSTRACTThe vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Interactive Navigator) which provides user-friendly interfaces to manipulate and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,500) of already processed datasets. The front-end user interfaces provide a wealth of user-analytics options including sub-setting and downloading processed data, interactive visualization, statistical power analyses, construction of differential gene expression signatures and their comprehensive functional characterization, and connectivity analysis with LINCS L1000 data. The combination of the massive amount of back-end data and front-end analytics options driven by user-friendly interfaces makes GREIN a unique open-source resource for re-using GEO RNA-seq data. GREIN is accessible at: https://shiny.ilincs.org/grein, the source code at: https://github.com/uc-bd2k/grein, and the Docker container at: https://hub.docker.com/r/ucbd2k/grein.

scholarly journals Transcriptome-wide interrogation of the functional intronome by spliceosome profiling

2017 ◽  
Author(s):  
Weijun Chen ◽  
Jill Moore ◽  
Hakan Ozadam ◽  
Hennady P. Shulha ◽  
Nicholas Rhind ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Rna Processing ◽  
Mrna Translation ◽  
Ribosome Profiling ◽  
Rna Seq ◽  
Full Understanding ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Nucleotide Resolution ◽  
Single Nucleotide Resolution

SUMMARYFull understanding of eukaryotic transcriptomes and how they respond to different conditions requires deep knowledge of all sites of intron excision. Although RNA-Seq provides much of this information, the low abundance of many spliced transcripts (often due to their rapid cytoplasmic decay) limits the ability of RNA-Seq alone to reveal the full repertoire of spliced species. Here we present “spliceosome profiling”, a strategy based on deep sequencing of RNAs co-purifying with late stage spliceosomes. Spliceosome profiling allows for unambiguous mapping of intron ends to single nucleotide resolution and branchpoint identification at unprecedented depths. Our data reveal hundreds of new introns in S. pombe and numerous others that were previously misannotated. By providing a means to directly interrogate sites of spliceosome assembly and catalysis genome-wide, spliceosome profiling promises to transform our understanding of RNA processing in the nucleus much like ribosome profiling has transformed our understanding mRNA translation in the cytoplasm.

scholarly journals RiboPlotR: a visualization tool for periodic Ribo-seq reads

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Hsin-Yen Larry Wu ◽  
Polly Yingshan Hsu
Keyword(s):  
Mrna Translation ◽  
Untranslated Regions ◽  
Rna Seq ◽  
Color Coding ◽  
Link Type ◽  
Genome Wide ◽  
Non Coding Rnas ◽  
Gene Structures ◽  
Small Orfs ◽  
Reading Frames

Abstract Background Ribo-seq has revolutionized the study of genome-wide mRNA translation. High-quality Ribo-seq data display strong 3-nucleotide (nt) periodicity, which corresponds to translating ribosomes deciphering three nts at a time. While 3-nt periodicity has been widely used to study novel translation events such as upstream ORFs in 5′ untranslated regions and small ORFs in presumed non-coding RNAs, tools that allow the visualization of these events remain underdeveloped. Results RiboPlotR is a visualization package written in R that presents both RNA-seq coverage and Ribo-seq reads in genomic coordinates for all annotated transcript isoforms of a gene. Specifically, for individual isoform models, RiboPlotR plots Ribo-seq data in the context of gene structures, including 5′ and 3′ untranslated regions and introns, and it presents the reads for all three reading frames in three different colors. The inclusion of gene structures and color-coding the reading frames facilitate observing new translation events and identifying potential regulatory mechanisms. Conclusions RiboPlotR is freely available (https://github.com/hsinyenwu/RiboPlotR and https://sourceforge.net/projects/riboplotr/) and allows the visualization of translated features identified in Ribo-seq data.

scholarly journals Compression of quantification uncertainty for scRNA-seq counts

2020 ◽  
Author(s):  
Scott Van Buren ◽  
Hirak Sarkar ◽  
Avi Srivastava ◽  
Naim U. Rashid ◽  
Rob Patro ◽  
...  
Keyword(s):  
Negative Binomial ◽  
General Procedure ◽  
Computation Time ◽  
Statistical Testing ◽  
Rna Seq ◽  
Testing Framework ◽  
Link Type ◽  
Gene Level ◽  
Mean And Variance ◽  
Improved Performance

AbstractMotivationQuantification estimates of gene expression from single-cell RNA-seq (scRNA-seq) data have inherent uncertainty due to reads that map to multiple genes. Many existing scRNA-seq quantification pipelines ignore multi-mapping reads and therefore underestimate expected read counts for many genes. alevin accounts for multi-mapping reads and allows for the generation of “inferential replicates”, which reflect quantification uncertainty. Previous methods have shown improved performance when incorporating these replicates into statistical analyses, but storage and use of these replicates increases computation time and memory requirements.ResultsWe demonstrate that storing only the mean and variance from a set of inferential replicates (“compression”) is sufficient to capture gene-level quantification uncertainty. Using these values, we generate “pseudo-inferential” replicates from a negative binomial distribution and propose a general procedure for incorporating these replicates into a proposed statistical testing framework. We show reduced false positives when applying this procedure to trajectory-based differential expression analyses. We additionally extend the Swish method to incorporate pseudo-inferential replicates and demonstrate improvements in computation time and memory consumption without any loss in performance. Lastly, we show that the removal of multi-mapping reads can result in significant underestimation of counts for functionally important genes in a real dataset.Availability and implementationmakeInfReps and splitSwish are implemented in the development branch of the R/Bioconductor fishpond package available at http://bioconductor.org/packages/devel/bioc/html/fishpond.html. Sample code to calculate the uncertainty-aware p-values can be found on GitHub at https://github.com/skvanburen/[email protected]

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