Stability of gene rankings from RNAi screens

Motivation: Genome-wide RNA interference (RNAi) experiments are becoming a widely used approach for identifying intracellular molecular pathways of specific functions. However, detecting all relevant genes involved in a biological process is challenging, because typically only few samples per gene knock-down are available and readouts tend to be very noisy. We investigate the reliability of top scoring hit lists obtained from RNAi screens, compare the performance of different ranking methods, and propose a new ranking method to improve the reproducibility of gene selection. Results: The performance of different ranking methods is assessed by the size of the stable sets they produce, i.e. the subsets of genes which are estimated to be re-selected with high probability in independent validation experiments. Using stability selection, we also define a new ranking method, called stability ranking, to improve the stability of any given base ranking method. Ranking methods based on mean, median, t-test and rank-sum test, and their stability-augmented counterparts are compared in simulation studies and on three microscopy image RNAi datasets. We find that the rank-sum test offers the most favorable trade-off between ranking stability and accuracy and that stability ranking improves the reproducibility of all and the accuracy of several ranking methods. Availability: Stability ranking is freely available as the R/Bioconductor package staRank at http://www.cbg.ethz.ch/software/staRank. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

netprioR: a probabilistic model for integrative hit prioritisation of genetic screens

In the post-genomic era of big data in biology, computational approaches to integrate multiple heterogeneous data sets become increasingly important. Despite the availability of large amounts of omics data, the prioritisation of genes relevant for a specific functional pathway based on genetic screening experiments, remains a challenging task. Here, we introduce netprioR, a probabilistic generative model for semi-supervised integrative prioritisation of hit genes. The model integrates multiple network data sets representing gene–gene similarities and prior knowledge about gene functions from the literature with gene-based covariates, such as phenotypes measured in genetic perturbation screens, for example, by RNA interference or CRISPR/Cas9. We evaluate netprioR on simulated data and show that the model outperforms current state-of-the-art methods in many scenarios and is on par otherwise. In an application to real biological data, we integrate 22 network data sets, 1784 prior knowledge class labels and 3840 RNA interference phenotypes in order to prioritise novel regulators of Notch signalling in Drosophila melanogaster. The biological relevance of our predictions is evaluated using in silico and in vivo experiments. An efficient implementation of netprioR is available as an R package at http://bioconductor.org/packages/netprioR.ISSN:1544-611

Cell-type-specific processing of the amyloid precursor protein by Presenilin during Drosophila development

The cleavage of proteins within their transmembrane domain by Presenilin (PS) has an important role in different signalling pathways and in Alzheimer's disease. Nevertheless, not much is known about the regulation of PS activity. It has been suggested that substrate recognition by the PS complex depends only on the size of the extracellular domain independent of the amino-acid sequence and that PS activity is constitutive in all cells that express the minimal components of the complex. We report here the development of an in vivo reporter system that allowed us to analyse the processing of human amyloid precursor protein (APP) and the Notch receptor tissue specifically during Drosophila development in the living organism. Using this system, we demonstrate differences between APP and Notch processing and show that PS-mediated cleavage of APP can be regulated in different cell types independent of the size of the extracellular domain

In Vivo Reconstitution of γ-Secretase in Drosophila Results in Substrate Specificity▿

The intramembrane aspartyl protease γ-secretase plays a fundamental role in several signaling pathways involved in cellular differentiation and has been linked with a variety of human diseases, including Alzheimer's disease. Here, we describe a transgenic Drosophila model for in vivo-reconstituted γ-secretase, based on expression of epitope-tagged versions of the four core γ-secretase components, Presenilin, Nicastrin, Aph-1, and Pen-2. In agreement with previous cell culture and yeast studies, coexpression of these four components promotes the efficient assembly of mature, proteolytically active γ-secretase. We demonstrate that in vivo-reconstituted γ-secretase has biochemical properties and a subcellular distribution resembling those of endogenous γ-secretase. However, analysis of the cleavage of alternative substrates in transgenic-fly assays revealed unexpected functional differences in the activity of reconstituted γ-secretase toward different substrates, including markedly reduced cleavage of some APP family members compared to cleavage of the Notch receptor. These findings indicate that in vivo under physiological conditions, additional factors differentially modulate the activity of γ-secretase toward its substrates. Thus, our approach for the first time demonstrates the overall functionality of reconstituted γ-secretase in a multicellular organism and the requirement for substrate-specific factors for efficient in vivo cleavage of certain substrates

In vivo reconstitution of gamma-secretase in Drosophila results in substrate specificity.

The intramembrane aspartyl protease gamma-secretase plays a fundamental role in several signaling pathways involved in cellular differentiation and has been linked with a variety of human diseases, including Alzheimer's disease. Here, we describe a transgenic Drosophila model for in vivo-reconstituted gamma-secretase, based on expression of epitope-tagged versions of the four core gamma-secretase components, Presenilin, Nicastrin, Aph-1, and Pen-2. In agreement with previous cell culture and yeast studies, coexpression of these four components promotes the efficient assembly of mature, proteolytically active gamma-secretase. We demonstrate that in vivo-reconstituted gamma-secretase has biochemical properties and a subcellular distribution resembling those of endogenous gamma-secretase. However, analysis of the cleavage of alternative substrates in transgenic-fly assays revealed unexpected functional differences in the activity of reconstituted gamma-secretase toward different substrates, including markedly reduced cleavage of some APP family members compared to cleavage of the Notch receptor. These findings indicate that in vivo under physiological conditions, additional factors differentially modulate the activity of gamma-secretase toward its substrates. Thus, our approach for the first time demonstrates the overall functionality of reconstituted gamma-secretase in a multicellular organism and the requirement for substrate-specific factors for efficient in vivo cleavage of certain substrates

Interference of human and Drosophila APP and APP-like proteins with PNS development in Drosophila

The view that only the production and deposition of Aβ plays a decisive role in Alzheimer's disease has been challenged by recent evidence from different model systems, which attribute numerous functions to the amyloid precursor protein (APP). To investigate the potential cellular functions of APP and its paralogs, we use transgenic Drosophila as a model. Upon overexpression of the APP-family members, transformations of cell fates during the development of the peripheral nervous system were observed. Genetic analysis showed that APP, APLP1 and APLP2 induce Notch gain-of-function phenotypes, identified Numb as a potential target and provided evidence for a direct involvement of Disabled and Neurotactin in the induction of the phenotypes. The severity of the induced phenotypes not only depended on the dosage and the particular APP-family member but also on particular domains of the molecules. Studies with Drosophila APPL confirmed the results obtained with human proteins and the analysis of flies mutant for the appl gene further supports an involvement of APP-family members in neuronal development and a crosstalk between the APP family and Notch

A Deterministic Analysis of Genome Integrity during Neoplastic Growth in <i>Drosophila</i>

<div><p>The development of cancer has been associated with the gradual acquisition of genetic alterations leading to a progressive increase in malignancy. In various cancer types this process is enabled and accelerated by genome instability. While genome sequencing-based analysis of tumor genomes becomes increasingly a standard procedure in human cancer research, the potential necessity of genome instability for tumorigenesis in <i>Drosophila melanogaster</i> has, to our knowledge, never been determined at DNA sequence level. Therefore, we induced formation of tumors by depletion of the <i>Drosophila</i> tumor suppressor Polyhomeotic and subjected them to genome sequencing. To achieve a highly resolved delineation of the genome structure we developed the Deterministic Structural Variation Detection (DSVD) algorithm, which identifies structural variations (SVs) with high accuracy and at single base resolution. The employment of long overlapping paired-end reads enables DSVD to perform a deterministic, i.e. fragment size distribution independent, identification of a large size spectrum of SVs. Application of DSVD and other algorithms to our sequencing data reveals substantial genetic variation with respect to the reference genome reflecting temporal separation of the reference and laboratory strains. The majority of SVs, constituted by small insertions/deletions, is potentially caused by erroneous replication or transposition of mobile elements. Nevertheless, the tumor did not depict a loss of genome integrity compared to the control. Altogether, our results demonstrate that genome stability is not affected inevitably during sustained tumor growth in <i>Drosophila</i> implying that tumorigenesis, in this model organism, can occur irrespective of genome instability and the accumulation of specific genetic alterations.</p></div

Genomic context analysis can indicate mutational mechanisms causing SVs.

<p>(A) DNA sequence and insertion frequency of the 10 most commonly inserted sequences identified within the control genome. For the tumor the tenth most frequently inserted sequence corresponds to CA with 897 insertions. For the sake of a clear representation the eleventh most frequently inserted sequence (AAA, 894 insertions) is shown. (B) The fraction of single base insertions within simple repeats consisting of the same base type, computed with respect to all single base insertions. Simple repeats of a minimum length of 4 were considered. (C) A genome browser view of a genomic locus containing two insertions (I/V), two deletions (II/IV) and one tandem duplication (III). As indicated by the discordant coverage and horizontal bars, these high-confidence SVs are both identified within the tumor and the control genomes, and have therefore been inherited from the parental strains.</p

Coding sequences are less susceptible to SV accumulation.

<p>(A) Genome browser view depicting the concordant and discordant coverage of the control (blue) and the tumor (red) samples across two protein-coding genes, and identified SVs therein. The detected insertions and deletions localize outside of coding sequences, and affect introns, intergenic spaces and UTRs. (B) Genome-wide breakpoint distribution across distinct functional compartments. Different subsets of the genome were selected according to following characteristics: <i>genome</i> corresponds to the full-length genome; the <i>unique genes</i> do not share common positions with any other gene; <i>overlapping genes</i> are non-unique genes; <i>exonic</i> regions, containing <i>3′UTRs, 5′UTRs</i> and coding sequences (<i>CDS</i>) were obtained from the unique genes in order to avoid ambiguity; In addition, <i>intronic</i> and <i>intergenic</i> regions as well as donor/acceptor splice sites (<i>splice sites</i>) were considered. For each subset the number of contained breakpoints was computed and normalized to the total length.</p