Literature DB >> 22884873

Discovery and characterization of new transcripts from RNA-seq data in mouse CD4(+) T cells.

Andrew Paul Hutchins1, Stéphane Poulain, Hodaka Fujii, Diego Miranda-Saavedra.   

Abstract

Despite the routine application of RNA-seq technology to profile cellular transcriptomes and report novel splice variants, the identification and validation of new transcripts remain underexplored. We prepared two RNA-seq libraries from resting and T cell receptor-stimulated mouse CD4(+) T cells. Transcripts unknown to Ensembl represent as much as 5% of the assembled transcripts and are robustly expressed but do not show the same degree of evolutionary conservation or exon distribution of known transcripts, or of novel splice isoforms. Here we present a straightforward and generally applicable computational/experimental workflow that we apply to characterise and experimentally validate 23 mouse transcripts from the RNA-seq libraries that were uncharacterised by Ensembl. Of these, 7 are not supported by any transcript database and therefore are likely to encode new messages. Furthermore, we also report the fast up-regulation of important regulatory molecules only 4 h post-stimulation of the T cell receptor, which calls for a more detailed investigation into early CD4(+) T cell activation mechanisms.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22884873     DOI: 10.1016/j.ygeno.2012.07.014

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  9 in total

1.  De novo transcriptome assembly facilitates characterisation of fast-evolving gene families, MHC class I in the bank vole (Myodes glareolus).

Authors:  M Migalska; A Sebastian; M Konczal; P Kotlík; J Radwan
Journal:  Heredity (Edinb)       Date:  2016-10-26       Impact factor: 3.821

2.  LINC00892 Is an lncRNA Induced by T Cell Activation and Expressed by Follicular Lymphoma-Resident T Helper Cells.

Authors:  Ingram Iaccarino; Fatme Mourtada; Sarah Reinke; Paurnima Patil; Gero Doose; Gianni Monaco; Steve Hoffmann; Reiner Siebert; Wolfram Klapper
Journal:  Noncoding RNA       Date:  2022-06-01

Review 3.  Genomic and computational approaches to dissect the mechanisms of STAT3's universal and cell type-specific functions.

Authors:  Andrew Paul Hutchins; Diego Diez; Diego Miranda-Saavedra
Journal:  JAKSTAT       Date:  2013-05-20

4.  glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data.

Authors:  Andrew Paul Hutchins; Ralf Jauch; Mateusz Dyla; Diego Miranda-Saavedra
Journal:  Cell Regen (Lond)       Date:  2014-01-24

5.  HAfTs are novel lncRNA transcripts from aflatoxin exposure.

Authors:  B Alex Merrick; Justin S Chang; Dhiral P Phadke; Meredith A Bostrom; Ruchir R Shah; Xinguo Wang; Oksana Gordon; Garron M Wright
Journal:  PLoS One       Date:  2018-01-19       Impact factor: 3.240

6.  Transcriptome analysis of developing lens reveals abundance of novel transcripts and extensive splicing alterations.

Authors:  Rajneesh Srivastava; Gungor Budak; Soma Dash; Salil A Lachke; Sarath Chandra Janga
Journal:  Sci Rep       Date:  2017-09-14       Impact factor: 4.379

7.  Antibody-induced internalisation of retroviral envelope glycoproteins is a signal initiation event.

Authors:  Veera Panova; Jan Attig; George R Young; Jonathan P Stoye; George Kassiotis
Journal:  PLoS Pathog       Date:  2020-05-26       Impact factor: 6.823

8.  Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE.

Authors:  Efthimios Bothos; Pantelis Hatzis; Panagiotis Moulos
Journal:  Methods Protoc       Date:  2022-03-18

Review 9.  Transposable elements at the center of the crossroads between embryogenesis, embryonic stem cells, reprogramming, and long non-coding RNAs.

Authors:  Andrew Paul Hutchins; Duanqing Pei
Journal:  Sci Bull (Beijing)       Date:  2015-10-13       Impact factor: 11.780

  9 in total

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