Genome-wide association studies have shown variation at 14q We sought to decipher causal variant s at 14q While the aetiology of ALL is poorly understood evidence implicates initiating transforming events occuring in utero [ 1 , 2 , 3 ], with secondary events required for transition to malignancy [ 4 ]. We sought to identify the causal polymorphism s for the 14q Material and methods Ethics Samples and clinicopathological information were collected with ethical board approval. Informed consent was granted from all participants.
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Genome-wide association studies have shown variation at 14q We sought to decipher causal variant s at 14q While the aetiology of ALL is poorly understood evidence implicates initiating transforming events occuring in utero [ 1 , 2 , 3 ], with secondary events required for transition to malignancy [ 4 ].
We sought to identify the causal polymorphism s for the 14q Material and methods Ethics Samples and clinicopathological information were collected with ethical board approval.
Informed consent was granted from all participants. Controls comprised individuals from the Heinz Nixdorf Recall study [ 14 ]. Meta-analysis was undertaken using META v1 [ 18 ]. Data were viewed using balanced Knight-Ruiz normalisation at 5 kb resolution. Hi-C data in Supplementary Fig. Lentiviral particles were produced in HEKT cells as described [ 20 , 21 ]. Polyclonal populations were used for all assays. Cell identity was confirmed using Promega PowerPlex 16 microsatellite testing kit.
For luciferase assays, cells were electroporated and promoter activity was assayed using a Dual-Luciferase assay Promega. Full methods are described in Supplementary material. BigDye v3. Peaks were called using MACS2 2. Biological replicates contained three technical replicates. PCR-quantitation, by standard curve method.
Electrophoretic mobility shift assay EMSAs were performed as described in ref. Full methods are described in Supplementary materials. Cell growth assay Cell viability was quantified using a final concentration of 0. Plates were incubated for 24 h in the dark and absorbance read at nm.
Gene and transcript abundance were quantified using RSEMv1. Raw gene counts were analysed using EdgeR [ 30 ] and DeSeq2 [ 31 ]. Results Epigenomic profiling of the 14q We verified imputation of rs by sequencing cases. Conditional analysis provided no evidence for an additional independent association. Referencing SNPdb. Blue lines denote transcription factor ChIP-Seq peaks. To exclude the potential of a looping cis-regulatory interaction we examined GM Hi-C data [ 19 ].
This revealed an interaction between the 14q Kruskal—Wallis P-value computed against all genotypes. REH cells transfected with constructs containing the rsA risk allele displayed 1. Raw signal normalised to input DNA left y-axis. T-test P-values. We used HaploReg v4. Two mismatches within the motif of ZNF overlapping rs Fig. Yellow boxes highlight base mismatches. Left x-axis raw signal normalised to input DNA, right y-axis, fold enrichment hashed bars vs IgG control. Reads mapping to each allele lead SNPs in the 14q Moreover the risk allele bias was higher for rs than either rs or rs These data are consistent with increased transcriptional activity due to allele-specific promoter acetylation.
Absorbance nm normalised to 0 h matched shRNA control shown on y-axis. Case-specific breakpoints are denoted by coloured vertical lines. Findings were consistent with direct regulation for 13 of 73 top differentially expressed genes. Although in one case breakpoints truncated the terminal 13 amino acids of CEBPE this affected a region of no known function suggesting no functional impact, and in a second case the coding sequence was unaffected. Discussion Our data provide a plausible mechanism of increased ALL risk at 14q This suggests that modulation of expression due to allele-specific binding of transcription factors is complex and the aggregate of multiple interacting proteins.
Previously, Wiemels et al.
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Where noise levels exceed the Workplace Exposure Standard of 85 dB over an 8-hour day, you must deal with the hazard by:. Acknowledgements We thank Genomes analysis group for making individual call sets publicly available. What does the software do? Methods for calling genetic variants from sequence data are rapidly evolving beyond single nucleotide polymorphisms SNPsto more complex variants such as short insertions and deletions indelsshort tandem repeats STRsmulti-nucleotide polymorphisms MNPsstructural variations SVs and others. This solution delivers color-accurate designs and proofs based on real inks on real substrates without the need to fingerprint the press.