Biology subjects

Weber, M.

Publications and source records attributed to Weber, M..

58 records · Page 4Linked to original sources

bioRxiv2019

Managing genomic variant calling workflows with Swift/T

Genomic variant discovery is frequently performed using the GATK Best Practices variant calling pipeline, a complex workflow with multiple steps, fans/merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Here we describe a wrapper for the GATK-based variant calling workflow using the Swift/T parallel scripting language. Standard built-in features include the flexibility to split by chromosome before variant calling, optionally permitting the analysis to continue when faulty samples are detected, and allowing users to analyze multiple samples in parallel within each cluster node. The use of Swift/T conveys two key advantages: (1) Thanks to the embedded ability of Swift/T to transparently operate in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.,) a single workflow is trivially portable across numerous clusters; (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, conditional on the analysts choice, which makes the workflow easy to maintain. This modular design permits separation of the workflow into multiple stages and the request of resources optimal for each stage of the pipeline. While Swift/Ts implicit data-level parallelism eliminates the need for the developer to code parallel analysis of multiple samples, it does make debugging of the workflow a bit more difficult, as is the case with any implicitly parallel code. With the above features, users have a powerful and portable way to scale up their variant calling analysis to run in many traditional computer cluster architectures.\n\nhttps://github.com/ncsa/Swift-T-Variant-Calling\n\nhttp://swift-t-variant-calling.readthedocs.io/en/latest/

bioinformatics↗

bioRxiv2018

Distinct oncogenes drive distinct genome and epigenome alterations in human mammary epithelial cells

Gene expression differences, combined with distinct patterns of genomic rearrangements and epigenetic modifications, have laid the bases of molecular classification of breast cancer. Different molecular subtypes are thought to originate from different cell lineages in the mammary gland, but the early activation of an oncogene could also play a role. It is, however, difficult to discriminate the respective inputs of oncogene activation or cell type of origin in the natural history of the tumor. In this work, we have designed an experimental strategy aiming at determining whether activation of distinct oncogenic pathways in human mammary epithelial cells (HMEC) could lead to different patterns of genetic and epigenetic changes. We show that initial activation of CCNE1, WNT1 and RASv12, which activate distinct oncogenic pathways, in shp53 immortalized HMECs results in different and reproducible profiles of mRNA and miRNA expression, copy number alterations (CNA) and DNA methylation modifications. Noticeably, HMECs transformed by RAS bore very specific profiles of CNAs and DNA methylation, clearly distinct from those shown by CCNE1 and WNT1 transformed HMECs.\n\nGenes impacted by CNAs and CpG methylation in the RAS and the CCNE1/WNT1 clusters showed clear differences, illustrating the activation of distinct pathways. Our data show that early activation of distinct oncogenic pathways leads to active adaptive events resulting in specific sets of CNAs and DNA methylation changes. We, thus, propose that activation of different oncogenes could have a role in reshaping the genetic landscape of breast cancer subtypes.\n\nAuthor summaryGenetic and epigenetic changes are at the center of cancer development. Breast cancer molecular subtypes are defined on differences in genetic and epigenetic profiles and it is generally assumed these subtypes originate from different cell lineages in the mammary gland. We propose that founding oncogenic mutations could also have an impact. To address this question, we designed an experimental model, based on the ectopic expression of different oncogenes in human mammary epithelial cells (HMEC), and monitored genetic and DNA methylation changes occurring at different stages of cell transformation. We show that transformation of HMEC by distinct oncogenes resulted in clearly different and reproducible patterns of genetic and DNA methylation changes. Genes whose expression was modified by either CNAs or CpG methylation were consistent with the dominant pathways activated and reflected the phenotypes in the respective models. We propose that DNA methylation and CNA changes correspond to adaptive responses to the activation of the oncogenic pathways. Our data strongly suggest that early activation of distinct oncogenic insults will not only impinge on the phenotypic characteristics of the resulting tumors, but also have a strong impact on their genomic and epigenetic landscapes.

cancer biology↗

bioRxiv2017

Development of an HPTLC method for determination of hypoglycin A in aqueous extracts of seedlings and samaras of Acer species

Hypoglycin A (HGA) is a toxin contained in seeds of the sycamore maple tree (Acer pseudoplatanus). Ingestion of this amino acid causes equine atypical myopathy (AM) in Europe. Another variety, A. negundo, is claimed to be present where AM cases were reported in the US. For unknown reasons, occurrence of this disease has increased. It is important to define environmental key factors that may influence toxicity of samaras from Acer species. In addition, the content of HGA in seedlings needs to be determined since AM outbreaks, during autumn period when the seeds fall but also during spring when seeds are germinating. The present study aims to validate a reliable method using high performance thin layer chromatography for determination and comparison of HGA in samaras and seedlings.\n\nThe working range of the method was between 20 g HGA to 408 g HGA per ml water, corresponding to 12 - 244 mg/kg fresh weight or 40 - 816 mg/kg dry weight, taking into account of an arbitrary average dry matter content of 30%. Instrumental limit of detection and limit of quantification were of 10 g HGA/ml and 20 g HGA/ml water, respectively. Instrumental precision was 4% (RSD on 20 repeated measurements) while instrumental accuracy ranged between 86% and 121% of expected value. The HGA recovery of the analytical method estimated from spiked samaras and seedlings samples ranged between 63 and 103%. The method was applied to 9 samples of samaras from Acer pseudoplatanus, A. platanoides and A. campestre and 5 seedlings samples from A. pseudoplatanus. The results confirm detection of HGA in samaras from A. pseudoplatanus and the absence of detection in samaras of other tested species. They also suggest that detected levels of HGA are highly variable. This confirmed the suitability of the method for HGA detection in samaras or seedling.

pharmacology and toxicology↗

bioRxiv2017

Cell-Accurate Optical Mapping Across The Entire Developing Heart

Organogenesis depends on orchestrated interactions between individual cells and morphogenically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighbouring cells, which is established and fine-tuned during development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca2+-mapping of all cells in the entire heart during the looping stage in live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs.

biophysics↗