Biology subjects

Stephan-Otto Attolini, C.

Publications and source records attributed to Stephan-Otto Attolini, C..

4 recordsLinked to original sources

bioRxiv2018

chroGPS 2.0: differential analysis of epigenome maps in R.

1In the last years, after systematic mapping of epigenomics data from multiple organisms, tissues and cell lines, the ability to efficiently integrate, visualize and compare such information remains a challenge. Here we present chroGPS version 2, a major update of our previously developed software chroGPS, for visualization and differential analysis of epigenomes. Methods are provided for efficient integration and comparison of data from different conditions or biological backgrounds, accounting and adjusting for systematic biases in order to provide an efficient and statistically robust base for differential analysis. We also include functionalities for general data assessment and quality control prior to comparing maps, such as functions to study chromatin domain conservation between epigenomic backgrounds, to detect gross technical outliers and also to help in the selection of candidate marks for de-novo epigenome mapping.\n\nAvailabilityhttps://www.bioconductor.org/packages/release/bioc/html/chroGPS.html - Contact: oscar.reina@irbbarcelona.org

bioinformatics↗

bioRxiv2018

Adjusting for systematic technical biases in risk assessment of gene signatures in transcriptomic cancer cohorts

In recent years, many efforts in clinical and basic research have focused on finding molecular features of tumor samples with prognostic or classification potential. Among these, the association of the expression of gene signatures with survival probability is of special interest given its relatively direct applicability in the clinic and its power to shed insights into the molecular basis of cancer.\n\nAlthough great efforts have been invested in data processing to control for unknown sources of variability in a gene-wise manner, little is known about the behaviour of gene signatures with respect to the effect of technical variables.\n\nHere we show that the association of signatures with survival may be biased due to technical reasons and propose a simple and low intensive methodology based on correction by expectation under gene randomization. The resulting estimates are centred around zero and ensure correct asymptotic inference. Moreover, our methodology is robust against spurious correlations between global dataset tendencies and clinical outcome.\n\nAll tools (will be soon) available in the \"HRunbiased\" R package as well as processed datasets for colorectal and breast cancer.

bioinformatics↗

bioRxiv2018

Blimp-1 mediates the temporal control of embryonic tube maturation

The specification of tissue identity during embryonic development requires precise spatiotemporal coordination of gene expression. Many transcription factors required for the development of organs have been identified and their expression patterns are known; however, the mechanisms through which they coordinate gene expression in time remain poorly understood. Here we show that hormone-induced transcription factor Blimp-1 participates in the temporal coordination of tubulogenesis in Drosophila melanogaster by regulating the expression of many genes involved in tube maturation. In particular, we demonstrate that Blimp-1 regulates the expression of genes involved in chitin deposition and F-actin organization. We show that Blimp-1 is involved in the temporal control of lumen maturation by regulating the beginning of chitin deposition. We also report that Blimp-1 represses a variety of genes involved in tracheal maturation. Finally, we reveal that the kinase Btk29A serves as a link between Blimp-1 transcriptional repression and apical extra-cellular matrix organization.

developmental biology↗

bioRxiv2017

Drosophila larval brain neoplasms present tumour-type dependent genome instability

Single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) are found at different rates in human cancer. To determine if these genetic lesions appear in Drosophila tumours we have sequenced the genomes of 17 malignant neoplasms caused by mutations in l(3)mbt, brat, aurA, or lgl. We have found CNVs and SNPs in all the tumours. Tumour-linked CNVs range between 11 and 80 per sample, affecting between 92 and 1546 coding sequences. CNVs are in average less frequent in l(3)mbt than in brat lines. Nearly half of the CNVs fall within the 10 to 100Kb range, all tumour samples contain CNVs larger that 100 Kb and some have CNVs larger than 1Mb. The rates of tumour-linked SNPs change more than 20-fold depending on the tumour type: late stage brat, l(3)mbt, and aurA and lgl lines present median values of SNPs/Mb of exome of 0.16, 0.48, and 3.6, respectively. Higher SNP rates are mostly accounted for by C>A transversions, which likely reflect enhanced oxidative stress conditions in the affected tumours. Both CNVs and SNPs turn over rapidly. We found no evidence for selection of a gene signature affected by CNVs or SNPs in the cohort. Altogether, our results show that the rates of CNVs and SNPs, as well as the distribution of CNV sizes in this cohort of Drosophila tumours are well within the range of those reported for human cancer. Genome instability is therefore inherent to Drosophila malignant neoplastic growth at a variable extent that is tumour type dependent.\n\nAUTHOR SUMMARYDrosophila models of malignant growth can help to understand the molecular mechanisms of malignancy. These models are known to exhibit some of the hallmarks of cancer like sustained growth, immortality, metabolic reprogramming, and others. However, it is currently unclear if these fly models are affected by genome instability, which is another hallmark of many human malignant tumours. To address this issue we have sequenced and analysed the genomes of a cohort of seventeen fly tumour samples. We have found that genome instability is a common trait of Drosophila malignant tumours, which occurs at an extent that is tumour-type dependent, at rates that are similar to those of different human cancers.

cancer biology↗