The Experts below are selected from a list of 49257 Experts worldwide ranked by ideXlab platform
Daryl P Shanley - One of the best experts on this subject based on the ideXlab platform.
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Detecting translational regulation by change point analysis of ribosome profiling data sets
RNA, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While during normal translation, ribosome density is constant along the length of the mRNA coding region, this can be altered in response to translational regulatory events. In the present study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modeling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq data set obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artifacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g., premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new transcript Isoforms.
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Detecting translational regulation by change point analysis of ribosome profiling datasets
bioRxiv, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new Gene Isoforms.
Anze Zupanic - One of the best experts on this subject based on the ideXlab platform.
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Detecting translational regulation by change point analysis of ribosome profiling data sets
RNA, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While during normal translation, ribosome density is constant along the length of the mRNA coding region, this can be altered in response to translational regulatory events. In the present study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modeling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq data set obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artifacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g., premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new transcript Isoforms.
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Detecting translational regulation by change point analysis of ribosome profiling datasets
bioRxiv, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new Gene Isoforms.
Vance Lemmon - One of the best experts on this subject based on the ideXlab platform.
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Isoform diversity and regulation in peripheral and central neurons revealed through rna seq
PLOS ONE, 2012Co-Authors: Jessica K Lerch, Frank Kuo, Dario Motti, Richard W Morris, John L Bixby, Vance LemmonAbstract:To fully understand cell type identity and function in the nervous system there is a need to understand neuronal Gene expression at the level of Isoform diversity. Here we applied Next Generation Sequencing of the transcriptome (RNA-Seq) to purified sensory neurons and cerebellar granular neurons (CGNs) grown on an axonal growth permissive substrate. The goal of the analysis was to uncover neuronal type specific Isoforms as a prelude to understanding patterns of Gene expression underlying their intrinsic growth abilities. Global Gene expression patterns were comparable to those found for other cell types, in that a vast majority of Genes were expressed at low abundance. Nearly 18% of Gene loci produced more than one transcript. More than 8000 Isoforms were differentially expressed, either to different degrees in different neuronal types or uniquely expressed in one or the other. Sensory neurons expressed a larger number of Genes and Gene Isoforms than did CGNs. To begin to understand the mechanisms responsible for the differential Gene/Isoform expression we identified transcription factor binding sites present specifically in the upstream genomic sequences of differentially expressed Isoforms, and analyzed the 3′ untranslated regions (3′ UTRs) for microRNA (miRNA) target sites. Our analysis defines Isoform diversity for two neuronal types with diverse axon growth capabilities and begins to elucidate the complex transcriptional landscape in two neuronal populations.
John C. Mathers - One of the best experts on this subject based on the ideXlab platform.
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Detecting translational regulation by change point analysis of ribosome profiling data sets
RNA, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While during normal translation, ribosome density is constant along the length of the mRNA coding region, this can be altered in response to translational regulatory events. In the present study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modeling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq data set obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artifacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g., premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new transcript Isoforms.
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Detecting translational regulation by change point analysis of ribosome profiling datasets
bioRxiv, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new Gene Isoforms.
Thomas B. L. Kirkwood - One of the best experts on this subject based on the ideXlab platform.
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Detecting translational regulation by change point analysis of ribosome profiling data sets
RNA, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While during normal translation, ribosome density is constant along the length of the mRNA coding region, this can be altered in response to translational regulatory events. In the present study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modeling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq data set obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artifacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g., premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new transcript Isoforms.
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Detecting translational regulation by change point analysis of ribosome profiling datasets
bioRxiv, 2014Co-Authors: Anze Zupanic, John E. Hesketh, John C. Mathers, Thomas B. L. Kirkwood, Sushma-nagaraja Grellscheid, Catherine Meplan, Daryl P ShanleyAbstract:Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and Gene Isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new Gene Isoforms.