Literature DB >> 28957710

Two's company: studying interspecies relationships with dual RNA-seq.

Thomas Wolf1, Philipp Kämmer2, Sascha Brunke2, Jörg Linde3.   

Abstract

Organisms do not exist isolated from each other, but constantly interact. Cells can sense the presence of interaction partners by a range of receptors and, via complex regulatory networks, specifically react by changing the expression of many of their genes. Technological advances in next-generation sequencing over the recent years now allow us to apply RNA sequencing to two species at the same time (dual RNA-seq), and thus to directly study the gene expression of two interacting species without the need to physically separate cells or RNA. In this review, we give an overview over the latest studies in interspecies interactions made possible by dual RNA-seq, ranging from pathogenic to symbiotic relationships. We summarize state-of-the-art experimental techniques, bioinformatic data analysis and data interpretation, while also highlighting potential problems and pitfalls starting from the selection of meaningful time points and number of reads to matters of rRNA depletion. A short outlook on new trends in the field of dual RNA-seq concludes this review, looking at sequencing of non-coding RNAs during host-pathogen interactions and the prediction of molecular interspecies interactions networks.
Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

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Year:  2017        PMID: 28957710     DOI: 10.1016/j.mib.2017.09.001

Source DB:  PubMed          Journal:  Curr Opin Microbiol        ISSN: 1369-5274            Impact factor:   7.934


  13 in total

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Journal:  Genes (Basel)       Date:  2018-07-19       Impact factor: 4.096

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5.  The combined analysis as the best strategy for Dual RNA-Seq mapping.

Authors:  Eliandro Espindula; Edilena Reis Sperb; Evelise Bach; Luciane Maria Pereira Passaglia
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Authors:  Ross T Slater; Lucy R Frost; Sian E Jossi; Andrew D Millard; Meera Unnikrishnan
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Journal:  Bioinformatics       Date:  2020-02-01       Impact factor: 6.937

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Journal:  mBio       Date:  2020-02-18       Impact factor: 7.867

9.  High-resolution analysis of the pneumococcal transcriptome under a wide range of infection-relevant conditions.

Authors:  Rieza Aprianto; Jelle Slager; Siger Holsappel; Jan-Willem Veening
Journal:  Nucleic Acids Res       Date:  2018-11-02       Impact factor: 16.971

10.  The Transcriptional Profile of Trichophyton rubrum Co-Cultured with Human Keratinocytes Shows New Insights about Gene Modulation by Terbinafine.

Authors:  Monise Fazolin Petrucelli; Josie Budag Matsuda; Kamila Peroni; Pablo Rodrigo Sanches; Wilson Araújo Silva; Rene Oliveira Beleboni; Nilce Maria Martinez-Rossi; Mozart Marins; Ana Lúcia Fachin
Journal:  Pathogens       Date:  2019-11-29
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