Biology subjects

Boutros, M.

Publications and source records attributed to Boutros, M..

8 recordsLinked to original sources

bioRxiv2018

Evidence of functional long-range Wnt/Wg in the developing Drosophila wing epithelium

Wnts are secreted proteins that regulate cell fate specification during development of all metazoans. Wnt proteins were proposed to spread over several cell diameters to activate signalling directly at a distance. In the Drosophila wing epithelium, an extracellular gradient of Wingless (Wg, the homolog of Wnt1) was observed extending over several cells away from producing cells. However, it was also recently shown that a membrane-tethered Neurotactin-Wg fusion protein (NRT-Wg) can rescue the loss-of endogenous Wg, leading to proper patterning of the wing. Therefore, whether Wg spreading is required for correct tissue patterning during development remains controversial and the functional range of wild-type Wg is unclear. Here, by capturing secreted Wg on distally located cells we show that the Wg gradient acts directly up to eleven cell distances. Cells located outside the reach of extracellular Wg depend on the Frizzled2 receptor to maintain target gene expression. We find that NRT-Wg is not restricted to the producing cells and propose that it can rescue signalling defects by perdurance in the receiving cells. These results provide insight into the mechanisms by which Wnt proteins mediate patterning of a rapidly growing tissue.

developmental biology↗

bioRxiv2018

Time-resolved mapping of genetic interactions to model rewiring of signaling pathways

Context-dependent changes in genetic vulnerabilities are important to understand the wiring of cellular pathways and variations in different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic networks over time or in response to external stresses are lacking. To analyze the plasticity of genetic interactions, we performed an arrayed combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to endpoints assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity.

genomics↗

bioRxiv2018

WEADE: a workflow for enrichment analysis and data exploration

Data analysis based on enrichment of Gene Ontology terms has become an important step in exploring large gene or protein expression datasets and several stand-alone or web tools exist for that purpose. However, a comprehensive and consistent analysis downstream of the enrichment calculation is missing so far. With WEADE we present a free web application that offers an integrated workflow for the exploration of genomic data combining enrichment analysis with a versatile set of tools to directly compare and intersect experiments or candidate gene lists of any size or origin including cross-species data. Lastly, WEADE supports the graphical representation of output data in the form of functional interaction networks based on prior knowledge, allowing users to go from plain expression data to functionally relevant candidate sub-lists in an interactive and consistent manner.

bioinformatics↗

bioRxiv2017

Decoding the regulatory logic of the Drosophila male stem cell system

In the past decade, the importance of the niche to provide regulatory inputs to balance stem cell self-renewal and differentiation has become clear. However, the regulatory interplay between stem cells and their niche at the whole genome level is still poorly understood. To elucidate the mechanisms controlling stem cells and their progenies as they progress through their developmental program at the transcriptional level, we recorded the regulatory program of two independent cell lineages in the Drosophila testis stem cell model. To this end, we identified genes active in the soma or germline as well as genome-wide binding profiles of two essential transcription factors, Zfh-1 and Abd-A, expressed in somatic support cells and crucial for fate acquisition of both cell lineages. Our data identified key roles for TOR signalling, signal processing V-ATPase proton pumps and the nuclear transport engaged nucleoporins and we demonstrate their importance in controlling germline maintenance, proliferation and differentiation from the support side. To make our dataset publicly available and support quick and intuitive data mining, we generated an interactive online analysis tool. Applying our tool for comparative analysis, we uncovered conserved core gene sets of adult stem cells across species boundaries. We have tested the functional relevance of these genes in the Drosophila testis and intestine and find a striking overrepresentation of stem cell defects when the corresponding genes were depleted. In summary, our dataset and interactive platform represents a versatile tool for identifying novel gene networks active in diverse stem cell types and provides a valuable resource for elucidating the multifaceted regulatory inputs required to guide proper stem cell behaviour.

developmental biology↗

bioRxiv2017

A Map Of Genetic Interactions In Cancer Cells

Cancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and, as a side effect, create new vulnerabilities for potential therapeutic exploitation. To systematically identify genotype-dependent vulnerabilities and synthetic lethal interactions, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework that integrates CRISPR/Cas9 screens originating from many different libraries and laboratories to build genetic interaction maps. It builds on analytical approaches that were established for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cell lines combining functional data with information on genetic variants to explore the relationships of more than 2.1 million gene-background relationships. In addition to known dependencies, our analysis identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities associated with aberrant Wnt/{beta}-catenin signaling identified GANAB and PRKCSH as new positive regulators of Wnt/{beta}-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data is included.

systems biology↗

bioRxiv2017

Sorting & Sequencing Flies By Size: Identification Of Novel TOR Regulators And Parameters For Successful Sorting

As DNA sequencing throughput increases, novel strategies for discovering genes that affect traits of interest become available. One strategy starts with a population of animals and selects individuals over multiple generations for a particular trait. Subsequent whole genome sequencing should identify loci affecting this trait. We apply this strategy by sorting flies for wing length over 18 generations, obtaining two populations that differ in wing length by 20%. Flies with longer wings had increased overall body sizes and elevated TOR activity, suggesting that genetic variation targets TOR signaling to influence body size. High-throughput sequencing of big and small flies identified thousands of single nucleotide polymorphisms that differed between the two populations, leading us to identify five novel regulators of TOR signaling. Surprisingly, stochastic simulations of the process show that large fractions of the genetic differences between the big and small flies are probably biological false positives, selected by chance by random drift. We employ these computer simulations to identify experimental setup parameters to improve the signal-to-noise ratio for successfully running sort-and-sequence experiments - a resource which will hopefully be useful for the community.

genetics↗

bioRxiv2017

CRISPRAnalyzeR: Interactive analysis, annotation and documentation of pooled CRISPR screens

Pooled CRISPR/Cas9 screens are a powerful and versatile tool for the systematic investigation of cellular processes in a variety of organisms. Such screens generate large amounts of data that present a new challenge to analyze and interpret. Here, we developed a web application to analyze, document and explore pooled CRISR/Cas9 screens using a unified single workflow. The end-to-end analysis pipeline features eight different hit calling strategies based on state-of-the-art methods, including DESeq2, MAGeCK, edgeR, sgRSEA, Z-Ratio, Mann-Whitney test, ScreenBEAM and BAGEL. Results can be compared with interactive visualizations and data tables. CRISPRAnalyzeR integrates meta-information from 26 external data resources, providing a wide array of options for the annotation and documentation of screens. The application was developed with user experience in mind, requiring no previous knowledge in bioinformatics. All modern operating systems are supported.\n\nAvailability and online documentation: The source code, a pre-configured docker application, sample data and a documentation can be found on our GitHub page (http://www.github.com/boutroslab/CRISPRAnalyzeR). A tutorial video can be found at http://www.crispr-analyzer.org.

bioinformatics↗

bioRxiv2017

HTSvis: A web app for exploratory data analysis and visualization of arrayed high-throughput screens

The analysis and visualization of arrayed high-throughput screens (HTS), such as cell-based RNAi or small-molecule HTS experiments, requires specialized computational methods. Software packages such as the R/Bioconductor package cellHTS have been developed to support the analysis and are broadly used by the high-throughput screening community. However, exploratory data analysis and integration of screening results remains challenging due to the size of produced data tables in multi-channel experiments and the lack of user-friendly tools to integrate and visualize screening results. Here we present HTSvis, an R/Shiny open-source web application for interactive visualization and exploratory analysis of arrayed high-throughput data. Using a light-weight infrastructure suitable for desktop computers, HTSvis can be used to visualize raw data, perform quality control and interactively visualize screening results from single- to multi-channel measurements, such as image-based, screens. Input data can either be a result file obtained upon analysis with cellHTS or a generic table with raw or analyzed data from, e.g. a high-content microscopy screen. HTSvis can be downloaded from http://github.com/boutroslab/HTSvis.

bioinformatics↗