Dataset Information


Ontogenic changes in hematopoietic hierarchy determine pediatric specificity and disease phenotype in fusion oncogene-driven myeloid leukemia-ATACseq

ABSTRACT: ATACseq analyses between iEG (ETO2-GLIS2) and CTRL fetal primary cells and myeloid or CD41 iEG cells lines. Briefly, cells were isolated from iEG mice and cultured for 24 hours in RPMI supplemented with 10% FBS, cytokines (mIL3, mIL6, mSCF, mTPO, mFLT3l) and 100 ng/ml Doxycyclin. After cell lysis, transposition and purification step, the transposed DNA fragments were amplified by polymerase chain reaction (PCR) between 12 and 18 depending on the number of cells at the beginning (50,000 to 6,000) using adapters from the Nextera index kit (illumina). PCR purification was performed using Agencourt AMPure XP magnetic beads (Beckman Coulter A63880) in order to remove large fragments and remaining primers. Library quality was assessed using an Agilent 2100 Bioanalyzer using a High Sensitivity DNA chip (Agilent Technologies 5067-4626). Libraries were sequenced using Novaseq-6000 sequencer (Illumina) (50bp paired-end reads). Quality control of reads was performed using FastQC 0.11.7 and multiQC 1.5. The reads were aligned to the reference genome mm10 with bwa (aln 0.7.17). After alignment, we removed reads mapping to the mitochondrial genome, PCR duplicate reads and reads with a mapping quality lower than 20 using samtools (v 1.9). Final read counts for all mouse datasets ranged from 37 to 128 million reads. Mapped reads were normalized to bins per million (BPM) and were converted to bigwig format using deeptools (v3.2.0). Peak calling, differential analysis, annotation and motif analysis was performed using macs2 (V 2.1.2), Diffbind R package (v 2.8.0 in R-3.5.1 with threshold log2(1.5)), and homer (v4.10.4, and respectively.

INSTRUMENT(S): Illumina NovaSeq 6000


PROVIDER: E-MTAB-8375 | ArrayExpress | 2019-10-15



altmetric image


Ontogenic Changes in Hematopoietic Hierarchy Determine Pediatric Specificity and Disease Phenotype in Fusion Oncogene-Driven Myeloid Leukemia.

Lopez Cécile K CK   Noguera Esteve E   Stavropoulou Vaia V   Robert Elie E   Aid Zakia Z   Ballerini Paola P   Bilhou-Nabera Chrystèle C   Lapillonne Hélène H   Boudia Fabien F   Thirant Cécile C   Fagnan Alexandre A   Arcangeli Marie-Laure ML   Kinston Sarah J SJ   Diop M'Boyba M   Job Bastien B   Lecluse Yann Y   Brunet Erika E   Babin Loélia L   Villeval Jean Luc JL   Delabesse Eric E   Peters Antoine H F M AHFM   Vainchenker William W   Gaudry Muriel M   Masetti Riccardo R   Locatelli Franco F   Malinge Sébastien S   Nerlov Claus C   Droin Nathalie N   Lobry Camille C   Godin Isabelle I   Bernard Olivier A OA   Göttgens Berthold B   Petit Arnaud A   Pflumio Françoise F   Schwaller Juerg J   Mercher Thomas T  

Cancer discovery 20191029 12

Fusion oncogenes are prevalent in several pediatric cancers, yet little is known about the specific associations between age and phenotype. We observed that fusion oncogenes, such as ETO2-GLIS2, are associated with acute megakaryoblastic or other myeloid leukemia subtypes in an age-dependent manner. Analysis of a novel inducible transgenic mouse model showed that ETO2-GLIS2 expression in fetal hematopoietic stem cells induced rapid megakaryoblastic leukemia whereas expression in adult bone marro  ...[more]

Similar Datasets

2017-02-04 | E-MTAB-3019 | ArrayExpress
| GSE79720 | GEO
| GSE79719 | GEO
2018-08-24 | GSE118902 | GEO
2014-08-27 | E-GEOD-53711 | ArrayExpress
| GSE70377 | GEO
| GSE70274 | GEO
2015-01-26 | E-GEOD-56844 | ArrayExpress
2019-03-27 | E-MTAB-7695 | ArrayExpress
2014-01-09 | E-GEOD-42679 | ArrayExpress