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Whole transcriptome sequencing of Philadelphia positive acute lymphoblastic leukemia (ALL) by RNA-seq: an exhaustive overview of novel point mutations, gene expression and alternative splicing profiles

Authors :
Iacobucci, Ilaria
Ferrarini, Alberto
Giacomelli, Enrico
Xumerle, Luciano
Ferrari, Anna
Papayannidis, Cristina
Ottaviani, Emanuela
Paolini, Stefania
Messa, Francesca
Cilloni, Daniela
Vitale, Antonella
Pane, Fabrizio
Soverini, Simona
Saglio, Giuseppe
Foà, Robin
Baccarani, Michele
Delledonne, Massimo
Martinelli, Giovanni
SAZZINI, MARCO
LONETTI, ANNALISA
Iacobucci, Ilaria
Ferrarini, Alberto
Sazzini, Marco
Lonetti, Annalisa
Giacomelli, Enrico
Xumerle, Luciano
Ferrari, Anna
Papayannidis, Cristina
Ottaviani, Emanuela
Paolini, Stefania
Messa, Francesca
Cilloni, Daniela
Vitale, Antonella
Pane, Fabrizio
Soverini, Simona
Saglio, Giuseppe
Foà, Robin
Baccarani, Michele
Delledonne, Massimo
Martinelli, Giovanni
Publication Year :
2010

Abstract

Background: Although the pathogenesis of BCR-ABL1+ ALL is mainly related to the expression of BCR-ABL1, additional genetic lesions are supposed to be involved in its development and progression. Aim: In order to define the full repertoire of leukemia-related mutations, changes in expression profiles and alternative splicing (AS) events, the leukemia transcriptome of a BCR-ABL1+ ALL patient at diagnosis and relapse was sequenced using a Whole Transcriptome Sequencing (RNA-Seq) approach. Methods: Poly(A) RNA from blast cells was used to prepare cDNA libraries for Illumina/Solexa Genome Analyzer. Obtained sequence reads were mapped to the human genome reference sequence (UCSC hg18) to identify single nucleotide variants (SNVs). Reads that showed no match were mapped to a dataset of all possible splice junctions created in silico to identify AS events. The number of reads corresponding to RNA from known exons was also estimated and a normalized measure of gene expression level (RPKM) was computed. Results: RNA-seq analysis generated 13.9 and 15.8 million reads from de novo and relapsed ALL samples, respectively, detecting transcripts from 62% and 64% of human annotated genes. Low RPKM estimates (0.01

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.od......4094..28175ec6cc20ef82bbfc58b435111e99