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Considering the kinetics of mRNA synthesis in the analysis of the genome and epigenome reveals determinants of co-transcriptional splicing

When messenger RNA splicing occurs co-transcriptionally, the potential for kinetic control based on transcription dynamics is widely recognized. Indeed, perturbation studies have reported that when transcription kinetics are perturbed genetically or pharmacologically splice patterns may change. Howe...

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Detalles Bibliográficos
Autores principales: Davis-Turak, Jeremy C., Allison, Karmel, Shokhirev, Maxim N., Ponomarenko, Petr, Tsimring, Lev S., Glass, Christopher K., Johnson, Tracy L., Hoffmann, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333389/
https://www.ncbi.nlm.nih.gov/pubmed/25541195
http://dx.doi.org/10.1093/nar/gku1338
Descripción
Sumario:When messenger RNA splicing occurs co-transcriptionally, the potential for kinetic control based on transcription dynamics is widely recognized. Indeed, perturbation studies have reported that when transcription kinetics are perturbed genetically or pharmacologically splice patterns may change. However, whether kinetic control is contributing to the control of splicing within the normal range of physiological conditions remains unknown. We examined if the kinetic determinants for co-transcriptional splicing (CTS) might be reflected in the structure and expression patterns of the genome and epigenome. To identify and then quantitatively relate multiple, simultaneous CTS determinants, we constructed a scalable mathematical model of the kinetic interplay of RNA synthesis and CTS and parameterized it with diverse next generation sequencing (NGS) data. We thus found a variety of CTS determinants encoded in vertebrate genomes and epigenomes, and that these combine variously for different groups of genes such as housekeeping versus regulated genes. Together, our findings indicate that the kinetic basis of splicing is functionally and physiologically relevant, and may meaningfully inform the analysis of genomic and epigenomic data to provide insights that are missed when relying on statistical approaches alone.