Robertson FM (2010) IDrugs "High-Content Analysis--CHI's Seventh Annual Conference--Developments in HCA and Pathway Analysis."

Robertson FM

[IDrugs, 2010]

CHI''s Seventh Annual Conference on High-Content Analysis (HCA), held in San Francisco, incorporated topics covering new developments in the field of HCA, including hardware and software updates, new biological models for HCA and pathway analysis. This conference report highlights selected presentations on the use of HCA for the characterization of stem cells, cell-colony analysis, the validation of disease models and the identification of antiparasitic compounds.

Granell C et al. (2011) Chaos "Mesoscopic analysis of networks: applications to exploratory analysis and data clustering."

Arenas A, Gomez S, Granell C

[Chaos, 2011]

We investigate the adaptation and performance of modularity-based algorithms, designed in the scope of complex networks, to analyze the mesoscopic structure of correlation matrices. Using a multiresolution analysis, we are able to describe the structure of the data in terms of clusters at different topological levels. We demonstrate the applicability of our findings in two different scenarios: to analyze the neural connectivity of the nematode Caenorhabditis elegans and to automatically classify a typical benchmark of unsupervised clustering, the Iris dataset, with considerable success.

(1992) "Morphogenesis, an Analysis of the Development of Biological Forms"

[1992]

(1998) "A practical guide to the analysis of genes and proteins"

[1998]

(2009) "Methods of Behavior Analysis in Neuroscience."

[2009]

With contributions from more than 40 field specialists, Methods of Behavior Analysis in Neuroscience reflects six years of updates to its first bestselling edition and elucidates new behavioral approaches that are quickly becoming field standards. This second edition features new material on the relevance of transgenic mouse models for Alzheimer's disease, behavioral methods for assessing the cognitive impairment associated with major psychotic disorders, the revival of the scopolamine reversal model for assessing the clinical relevance of new AD drugs, and new approaches to assessing the cognitive impairment in aged mice.

Bensaddek D et al. (2015) Proteomics "Micro-proteomics with iterative data analysis: proteome analysis in C. elegans at the single worm level."

Kenyon CJ, Narayan V, Gartner A, Lamond AI, Nicolas A, Bensaddek D, Murillo AB

[Proteomics, 2015]

Proteomics studies typically analyze proteins at a population level, using extracts prepared from tens of thousands to millions of cells. The resulting measurements correspond to average values across the cell population and can mask considerable variation in protein expression and function between individual cells or organisms. Here, we report the development of micro-proteomics for the analysis of C. elegans, a eukaryote composed of 959 somatic cells and 1,500 germ cells, measuring the worm proteome at a single organism level to a depth of 3,000 proteins. This includes detection of proteins across a wide dynamic range of expression levels (> 6 orders of magnitude), including many chromatin-associated factors involved in chromosome structure and gene regulation. We apply the micro-proteomics workflow to measure the global proteome response to heat-shock in individual nematodes. This shows variation between individual animals in the magnitude of proteome response following heat-shock, including variable induction of heat-shock proteins. The micro-proteomics pipeline thus facilitates the investigation of stochastic variation in protein expression between individuals within an isogenic population of C. elegans. All data described in this study are available online via the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd), an open access, searchable database resource. This article is protected by copyright. All rights reserved.

Meier B et al. (2020) DNA Repair (Amst) "Analysis of mutational signatures in C. elegans: Implications for cancer genome analysis."

Meier B, Gerstung M, Gartner A, Volkova NV

[DNA Repair (Amst), 2020]

Genome integrity is constantly challenged by exogenous and endogenous insults, and mutations are associated with inherited disease and cancer. Here we summarize recent studies that utilized C. elegans whole genome next generation sequencing to experimentally determine mutational signatures associated with mutagen exposure, DNA repair deficiency or a combination of both and discuss the implications of these results for the understanding of cancer genome evolution. The experimental analysis of wild-type and DNA repair deficient nematodes propagated under unchallenged conditions over many generations revealed increased mutagenesis in approximately half of all DNA repair deficient strains, its rate, except for DNA mismatch repair, only being moderately increased. The exposure of wild-type and DNA repair defective strains to selected genotoxins, including UV-B and ionizing radiation, alkylating compounds, aristolochic acid, aflatoxin-B1, and cisplatin enabled the systematic analysis of the relative contributions of redundant repair modalities that mend DNA damage. Combining genotoxin exposure with DNA repair deficiency can manifest as altered mutation rates and/or as a change in mutational profiles, and reveals how different DNA alterations induced by one genotoxin are repaired by separate DNA repair pathways, often in a highly redundant way. Cancer genomes provide a snapshot of all mutational events that happened prior to cancer detection and sequencing, necessitating computational models to deduce mutational signatures using mathematical best fit approaches. While computationally deducing signatures from cancer genomes has been tremendously successful in associating some signatures to known mutagenic causes, many inferred signatures lack a clear link to a known mutagenic process. Moreover, analytical signatures might not reflect any distinct mutagenic processes. Nonetheless, combined effects of mutagen exposure and DNA damage-repair deficiency are also present in cancer genomes, but cannot be as easily detected owing to the unknown histories of genotoxic exposures and because biallelic in contrast to monoallelic DNA repair deficiency is rare. The impact of damage-repair interactions also manifests through selective pressure for DNA repair gene inactivation during cancer evolution. Using these considerations, we discuss a theoretical framework that explains why minute mutagenic changes, possibly too small to manifest as change in a signature, can have major effects in oncogenesis. Overall, the experimental analysis of mutational processes underscores that the interpretation of mutational signatures requires considering both the primary DNA lesion and repair status and imply that mutational signatures derived from cancer genomes may be more variable than currently anticipated.

Lin Xue et al. (2007) International Worm Meeting "Tools for microarray data analysis and their application to a cross-experiment analysis of gene expression in C. elegans."

Lin Xue, Jim Lund

[International Worm Meeting, 2007]

Over fifty genomic gene expression studies C. elegans have been published. These include spotted microarray, Affymetrix chip, and SAGE datasets. Access to this data is limited by its scattered location and different data formats. To facilitate exploratory analysis of the gene expression data in C. elegans, we collected this data and constructed a gene expression database containing all the published C. elegans expression datasets. A web-based program allows gene expression clusters of any combination of entered genes and expression datasets to be viewed (http://elegans.uky.edu/gl/madisplay). Over three hundred lists of genes from figures or tables in the published gene expression studies were extracted from the publications and made available in the GeneLists database. This database links each list to the cluster expression viewer. The GeneLists database also contains GO, KEGG, and other functionally annotated gene lists. We used these tools to examine in a systematic fashion the mean expression of gene lists in the set of C. elegans microarray experiments. Seventy-nine percent of publication derived gene lists show a strong expression change (p-value <0.001) in more than one experiment with the median being 14 out of the 128 experiments derived from the fifty publications. This indicates that groups of genes identified in one publication typically show strong expression changes in many other experiments.

Tadas Jucikas et al. (2009) European Worm Neurobiology Meeting "Worm Analysis Toolbox 1.0: A worm behaviour analysis toolbox for single Worm Tracker 2.0"

William Schafer, Victoria Butler, Tadas Jucikas, Eviatar Yemini

[European Worm Neurobiology Meeting, 2009]

The nematode Caenorhabditis elegans is widely used for the analysis of nervous system function. Changes in worm behaviour caused by genetic mutations or neuronal ablations can be observed and recorded with the low cost, feature-rich single worm tracker, Worm Tracker 2.0, which we have developed together with the Sternberg lab. This work describes the Worm Analysis Toolbox 1.0, a method developed to analyze video data collected by Worm Tracker 2.0 and to extract a wide variety of biologically relevant features. The current release allows the calculation of morphological features, including worm length, width, fatness, head and tail colouration and locomotion parameters such as velocity, flex, bending frequency, track amplitude, track wavelength and reconstruction of the path of the worm. Together, Worm Tracker 2.0 and Worm Analysis Toolbox 1.0 establish a powerful phenotyping system, capable of comparing data collected by different laboratories. We are using this system to start the generation of a seed C. elegans phenotypic database that will be used to explore the relative similarities of mutant phenotypes and detect behavioural differences under multiple experimental conditions. Worm Tracker 2.0 and Worm Analysis Toolbox 1.0 are both available online at http://www.mrc-lmb.cam.ac.uk/wormtracker/ .

Wilkins AS (1992) "Genetic Analysis of Animal Development, 2nd edition"

Wilkins AS

[1992]