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      Environmental influences on RNA processing: Biochemical, molecular and genetic regulators of cellular response

      1 , 2
      Wiley Interdisciplinary Reviews: RNA
      Wiley

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          Abstract

          RNA processing has emerged as a key mechanistic step in the regulation of the cellular response to environmental perturbation. Recent work has uncovered extensive remodeling of transcriptome composition upon environmental perturbation and linked the impacts of this molecular plasticity to health and disease outcomes. These isoform changes and their underlying mechanisms are varied-involving alternative sites of transcription initiation, alternative splicing, and alternative cleavage at the 3' end of the mRNA. The mechanisms and consequences of differential RNA processing have been characterized across a range of common environmental insults, including chemical stimuli, immune stimuli, heat stress, and cancer pathogenesis. In each case, there are perturbation-specific contributions of local (cis) regulatory elements or global (trans) factors and downstream consequences. Overall, it is clear that choices in isoform usage involve a balance between the usage of specific genetic elements (i.e., splice sites, polyadenylation sites) and the timing at which certain decisions are made (i.e., transcription elongation rate). Fine-tuned cellular responses to environmental perturbation are often dependent on the genetic makeup of the cell. Genetic analyses of interindividual variation in splicing have identified genetic effects on splicing that contribute to variation in complex traits. Finally, the increase in the number of tissue types and environmental conditions analyzed for RNA processing is paralleled by the need to develop appropriate analytical tools. The combination of large datasets, novel methods and conditions explored promises to provide a much greater understanding of the role of RNA processing response in human phenotypic variation. This article is categorized under: RNA Processing > RNA Editing and Modification RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Mechanisms RNA Processing > Splicing Regulation/Alternative Splicing.

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          Most cited references81

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          Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

          Recent molecular studies have revealed that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels, and phenotypic output 1–5 , with important functional consequences 4,5 . Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs 1,2 or proteins 5,6 simultaneously because genomic profiling methods 3 could not be applied to single cells until very recently 7–10 . Here, we use single-cell RNA-Seq to investigate heterogeneity in the response of bone marrow derived dendritic cells (BMDCs) to lipopolysaccharide (LPS). We find extensive, and previously unobserved, bimodal variation in mRNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization (RNA-FISH) for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.
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            The evolutionary landscape of alternative splicing in vertebrate species.

            How species with similar repertoires of protein-coding genes differ so markedly at the phenotypic level is poorly understood. By comparing organ transcriptomes from vertebrate species spanning ~350 million years of evolution, we observed significant differences in alternative splicing complexity between vertebrate lineages, with the highest complexity in primates. Within 6 million years, the splicing profiles of physiologically equivalent organs diverged such that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are cis-directed. However, a subset of pronounced splicing changes are predicted to remodel protein interactions involving trans-acting regulators. These events likely further contributed to the diversification of splicing and other transcriptomic changes that underlie phenotypic differences among vertebrate species.
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              Computational methods for transcriptome annotation and quantification using RNA-seq.

              High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.
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                Author and article information

                Journal
                Wiley Interdisciplinary Reviews: RNA
                WIREs RNA
                Wiley
                1757-7004
                1757-7012
                October 2018
                January 2019
                September 14 2018
                January 2019
                : 10
                : 1
                : e1503
                Affiliations
                [1 ]RNA Therapeutics Institute, University of Massachusetts Medical School Worcester Massachusetts
                [2 ]Center for Molecular Medicine and Genetics, and Department of Obstetrics and GynecologyWayne State University Detroit Michigan
                Article
                10.1002/wrna.1503
                6294667
                30216698
                dce32547-c247-4c98-8b10-56545349afd7
                © 2019

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

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