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Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

ABSTRACT: Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and explore functional relationships. We performed a genome-wide RNAi screen in human cells and used quantitative descriptors derived from high-throughput imaging to generate multiparametric phenotypic profiles. We show that profiles predicted functions of genes by phenotypic similarity. Specifically, we examined several candidates including the largely uncharacterized gene DONSON, which shared phenotype similarity with known factors of DNA damage response (DDR) and genomic integrity. Experimental evidence supports that DONSON is a novel centrosomal protein required for DDR signalling and genomic integrity. Multiparametric phenotyping by automated imaging and computational annotation is a powerful method for functional discovery and mapping the landscape of phenotypic responses to cellular perturbations.

SUBMITTER: Fuchs F

PROVIDER: S-EPMC2913390 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

Fuchs Florian F Pau Gregoire G Kranz Dominique D Sklyar Oleg O Budjan Christoph C Steinbrink Sandra S Horn Thomas T Pedal Angelika A Huber Wolfgang W Boutros Michael M

Molecular systems biology 20100601

Genetic screens for phenotypic similarity have made key contributions to associating genes with biological processes. With RNA interference (RNAi), highly parallel phenotyping of loss-of-function effects in cells has become feasible. One of the current challenges however is the computational categorization of visual phenotypes and the prediction of biological function and processes. In this study, we describe a combined computational and experimental approach to discover novel gene functions and ...[more]

PMID: 20531400

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Project description:BackgroundAtaxia Telangiectasia (A-T) is an inherited multisystem disorder with cerebellar neurodegeneration. The relationships between imaging metrics of cerebellar health and neurological function across childhood in A-T are unknown, but may be important for determining timing and impact of therapeutic interventions.PurposeTo test the hypothesis that abnormalities of cerebellar structure, physiology and cellular health occur in childhood A-T and correlate with neurological disability, we performed multiparametric cerebellar MRI and establish associations with disease status in childhood A-T.MethodsProspective cross-sectional observational study. 22 young people (9 females / 13 males, age 6.6-17.8 years) with A-T and 24 matched healthy controls underwent 3-Tesla MRI with volumetric, diffusion and proton spectroscopic acquisitions. Participants with A-T underwent structured neurological assessment, and expression / activity of ataxia-telangiectasia mutated (ATM) kinase were recorded.ResultsAtaxia-telangiectasia participants had cerebellar volume loss (fractional total cerebellar volume: 5.3% vs 8.7%, P < 0.0005, fractional 4th ventricular volumes: 0.19% vs 0.13%, P < 0.0005), that progressed with age (fractional cerebellar volumes, r = -0.66, P = 0.001), different from the control group (t = -4.88, P < 0.0005). The relationship between cerebellar volume and age was similar for A-T participants with absent ATM kinase production and those producing non-functioning ATM kinase. Markers of cerebellar white matter injury were elevated in ataxia-telangiectasia vs controls (apparent diffusion coefficient: 0.89 × 10-3 mm2 s-1 vs 0.69 × 10-3 mm2 s-1, p < 0.0005) and correlated (age-corrected) with neurometabolite ratios indicating impaired neuronal viability (N-acetylaspartate:creatine r = -0.70, P < 0.001); gliosis (inositol:creatine r = 0.50, P = 0.018; combined glutamine/glutamate:creatine r = -0.55, P = 0.008) and increased myelin turnover (choline:creatine r = 0.68, P < 0.001). Fractional 4th ventricular volume was the only variable retained in the regression model predicting neurological function (adjusted r2 = 0.29, P = 0.015).ConclusionsQuantitative MRI demonstrates cerebellar abnormalities in children with A-T, providing non-invasive measures of progressive cerebellar injury and markers reflecting neurological status. These MRI metrics may be of value in determining timing and impact of interventions aimed at altering the natural history of A-T.

Project description:While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have important functions in the nervous system.

Dataset Information

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

Publications

Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.

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