New chimeric RNAs in acute myeloid leukemia.

Autor:	Rufflé F; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Audoux J; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Boureux A; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Beaumeunier S; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Gaillard JB; Laboratoire de Cytologie et Cytogénétique, CHU Caremeau, Nîmes, France., Bou Samra E; Institut Curie, PSL Research University, Paris, France.; Université Paris Sud, Université Paris-Saclay, Orsay, France., Megarbane A; Institut Jérôme Lejeune, Paris, France., Cassinat B; Laboratoire de Biologie Cellulaire, Hôpital Saint-Louis, Assistance publique - Hôpitaux de Paris (AP-HP), Paris, France., Chomienne C; Laboratoire de Biologie Cellulaire, Hôpital Saint-Louis, Assistance publique - Hôpitaux de Paris (AP-HP), Paris, France.; Hôpital Saint-Louis, Université Paris Diderot, INSERM UMRS 1131, Paris, France., Alves R; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France.; Instituto Tecnológico Vale, Nazaré, Belém, PA, Brazil., Riquier S; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Gilbert N; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France., Lemaitre JM; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France., Bacq-Daian D; CEA Institut de Génomique, Centre National de Génotypage, Evry, France., Bougé AL; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Philippe N; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France., Commes T; Institut de Médecine Régénératrice et de Biothérapie, INSERM U1183, CHU Montpellier, Montpellier, France.; Institut de Biologie Computationnelle, Université Montpellier, Montpellier, France.
Jazyk:	angličtina
Zdroj:	F1000Research [F1000Res] 2017 Aug 02; Vol. 6. Date of Electronic Publication: 2017 Aug 02 (Print Publication: 2017).
DOI:	10.12688/f1000research.11352.1
Abstrakt:	Background: High-throughput next generation sequencing (NGS) technologies enable the detection of biomarkers used for tumor classification, disease monitoring and cancer therapy. Whole-transcriptome analysis using RNA-seq is important, not only as a means of understanding the mechanisms responsible for complex diseases but also to efficiently identify novel genes/exons, splice isoforms, RNA editing, allele-specific mutations, differential gene expression and fusion-transcripts or chimeric RNA (chRNA). Methods: We used Crac, a tool that uses genomic locations and local coverage to classify biological events and directly infer splice and chimeric junctions within a single read. Crac's algorithm extracts transcriptional chimeric events irrespective of annotation with a high sensitivity, and CracTools was used to aggregate, annotate and filter the chRNA reads. The selected chRNA candidates were validated by real time PCR and sequencing.  In order to check the tumor specific expression of chRNA, we analyzed a publicly available dataset using a new tag search approach. Results:   We present data related to acute myeloid leukemia (AML) RNA-seq analysis. We highlight novel biological cases of chRNA, in addition to previously well characterized leukemia chRNA. We have identified and validated 17 chRNAs among 3 AML patients: 10 from an AML patient with a translocation between chromosomes 15 and 17 (AML-t(15;17), 4  from patient with normal karyotype (AML-NK) 3 from a patient with chromosomal 16 inversion (AML-inv16). The new fusion transcripts can be classified into four groups according to the exon organization. Conclusions:  All groups suggest complex but distinct synthesis mechanisms involving either collinear exons of different genes, non-collinear exons, or exons of different chromosomes. Finally, we check tumor-specific expression in a larger RNA-seq AML cohort and identify new AML biomarkers that could improve diagnosis and prognosis of AML. Competing Interests: Competing interests: No competing interests were disclosed.
Databáze:	MEDLINE
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