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At least 235 records · Page 13Linked to original sources
PubMed2004

Identification of a zebrafish model of muscular dystrophy.

1. Large-scale mutagenic screens of the zebrafish genome have identified a number of different classes of mutations that disrupt skeletal muscle formation. Of particular interest and relevance to human health is a class of recessive lethal mutations in which muscle differentiation occurs normally, but is followed by tissue-specific degeneration reminiscent of human muscular dystrophies. 2. We have shown that one member of this class of mutations, sapje (sap), results from mutations within the zebrafish orthologue of the human Duchenne muscular dystrophy (DMD) gene. Mutations in this locus cause Duchenne or Becker muscular dystrophies in human patients and are thought to result in a dystrophic pathology by disrupting the link between the actin cytoskeleton and the extracellular matrix in skeletal muscle cells. 3. We have found that the progressive muscle degeneration phenotype of sapje-mutant zebrafish embryos is caused by the failure of somitic muscle attachments at the embryonic myotendinous junction (MTJ). 4. Although a role for dystrophin at the MTJ has been postulated previously and MTJ structural abnormalities have been identified in the dystrophin-deficient mdx mouse model, in vivo evidence of pathology based on muscle attachment failure is thus far lacking. Therefore, the sapjre mutation may provide a model for a novel pathological mechanism of Duchenne muscular dystrophy and other muscle diseases. In the present review, we discuss this finding in light of previously postulated models of dystrophin function.

Animals↗
PubMed2006

Principal components analysis corrects for stratification in genome-wide association studies.

Population stratification--allele frequency differences between cases and controls due to systematic ancestry differences-can cause spurious associations in disease studies. We describe a method that enables explicit detection and correction of population stratification on a genome-wide scale. Our method uses principal components analysis to explicitly model ancestry differences between cases and controls. The resulting correction is specific to a candidate marker's variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. Our simple, efficient approach can easily be applied to disease studies with hundreds of thousands of markers.

Algorithms↗
PubMed2001

Generalized comparative modeling (GENECOMP): a combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement.

An improved generalized comparative modeling method, GENECOMP, for the refinement of threading models is developed and validated on the Fischer database of 68 probe-template pairs, a standard benchmark used to evaluate threading approaches. The basic idea is to perform ab initio folding using a lattice protein model, SICHO, near the template provided by the new threading algorithm PROSPECTOR. PROSPECTOR also provides predicted contacts and secondary structure for the template-aligned regions, and possibly for the unaligned regions by garnering additional information from other top-scoring threaded structures. Since the lowest-energy structure generated by the simulations is not necessarily the best structure, we employed two structure-selection protocols: distance geometry and clustering. In general, clustering is found to generate somewhat better quality structures in 38 of 68 cases. When applied to the Fischer database, the protocol does no harm and in a significant number of cases improves upon the initial threading model, sometimes dramatically. The procedure is readily automated and can be implemented on a genomic scale.

Algorithms↗
PubMed2005

Transgenes as screening tools to probe and manipulate the zebrafish genome.

The zebrafish, originally an object of study as an inexpensive and prolific vertebrate embryological model with a plethora of genetic tricks, has over the past decade moved to large-scale chemical mutagenesis and recently came of age as a high throughput transgenic model with a sequenced genome nearing completion. Insertional mutagenesis, gene trapping and enhancer detection are all contributing to the increasing speed with which research in this biomedical model is progressing. We review here some of the recent developments in the emerging field of zebrafish developmental genomics and transgenesis.

Animals↗
PubMed2000

Genome-wide, large-scale production of mutant mice by ENU mutagenesis.

In the post-genome era, the mouse will have a major role as a model system for functional genome analysis. This requires a large number of mutants similar to the collections available from other model organisms such as Drosophila melanogaster and Caenorhabditis elegans. Here we report on a systematic, genome-wide, mutagenesis screen in mice. As part of the German Human Genome Project, we have undertaken a large-scale ENU-mutagenesis screen for dominant mutations and a limited screen for recessive mutations. In screening over 14,000 mice for a large number of clinically relevant parameters, we recovered 182 mouse mutants for a variety of phenotypes. In addition, 247 variant mouse mutants are currently in genetic confirmation testing and will result in additional new mutant lines. This mutagenesis screen, along with the screen described in the accompanying paper, leads to a significant increase in the number of mouse models available to the scientific community. Our mutant lines are freely accessible to non-commercial users (for information, see http://www.gsf.de/ieg/groups/enu-mouse.html).

Animals↗
PubMed2005

Identification of gene markers based on well validated and subcategorized stressed animals for potential clinical applications in PTSD.

Post-traumatic stress disorder (PTSD) is a complex mental disorder that can develop in response to traumatic experiences. The molecular mechanisms underlying the pathology of PTSD are poorly understood, and this lack of knowledge hampers our ability to find superior therapeutic approaches to the treatment of this disorder. There are two main reasons for our lack of study in this area: here is no sufficiently validated animal model and lack of large-scale studies for the search of underlying molecular mechanisms. Thus, to promote research on PTSD (especially its molecular mechanisms) and to set molecular basis for searching novel medications of this disorder, large-scale, genome-wide interrogation of a significant amount of genes based upon a well validated animal model is demanded. We hypothesize that a significant number of genes are involved in PTSD. It is only with a large number of these genes identified in specific samples of PTSD-related population, and then it is possible for a sufficient understanding of the pathology at the molecular level of a PTSD, as well as for enhancing the PTSD's therapeutic and preventative strategies. Two prerequisites are needed for testing this hypothesis: (1) relative pure samples from a well validated animal model; and (2) genome-wide screening of PTSD molecular targets. For the animal model, we suggest to use the predator-exposure paradigm, in which rats are exposed to a predator, this model has previously been evaluated behaviorally well emulated the clinical symptoms of PTSD. For a better stringency, three criteria can be used to further validate this animal model: analogous (similarity of behavior), predictive (predictability of drug response) and biological mechanism (e.g., electrophysiological and pathological change in amygdala). For large-scale molecular target screening, the new microarray technology, which can profile expression of tens of thousands genes simultaneously, is the method of choice. The validity and practicability of this hypothesis and the strategy for its testing have been supported by our preliminary laboratory data.

Animals↗
PubMed2025

SISTEM: simulation of tumor evolution, metastasis, and DNA-seq data under genotype-driven selection.

SUMMARY: SISTEM is a software package and mathematical framework for simulating tumor evolution and cell migrations at single-cell resolution. Unlike existing frameworks which simulate cancer cell populations under the neutral coalescent or using simple birth-death models, SISTEM simulates tumor populations under somatic clonal selection using an agent-based framework. SISTEM can generate mutation profiles, read counts, and DNA sequencing reads along with ground truth cell lineages and migration graphs under a number of easily customizable mutation and selection models. For improved realism, SISTEM allows for cell fitness to be driven by genomic events of various scales including single nucleotide variants, segmental gains and losses, whole-chromosomal and chromosome-arm aberrations, and whole-genome duplications. SISTEM also includes numerous migration models to simulate metastatic cancers, facilitating the exploration and evaluation of diverse migration patterns. AVAILABILITY AND IMPLEMENTATION: SISTEM is written in Python and is freely available open-source under GNU GPLv3 from: https://github.com/samsonweiner/sistem.

Software↗
PubMed2005

Comparative phylogenomics of pathogenic bacteria by microarray analysis.

DNA microarrays represent a powerful technology that enables whole-scale comparison of bacterial genomes. This, coupled with new methods to model DNA microarray data, is facilitating the development of robust comparative phylogenomics analyses. Such studies have dramatically increased our ability to differentiate between bacteria, highlighting previously undetected genetic differences and population structures and providing new insight into virulence and evolution of bacterial pathogens. Recent results from such studies have generated insights into the evolution of bacterial pathogens, the levels of diversity and plasticity in the genome of a species, as well as the differences in virulence amongst pathogenic bacteria.

Bacteria↗
PubMed2002

Applications of DNA and protein microarrays in comparative physiology.

DNA microarrays have revolutionized gene expression studies and made large-scale parallel measurement of whole genome expression a feasible technique in model species where genomes are well characterized. Such studies are perfectly suited to unraveling the complex regulation and/or interaction of both genes and proteins likely involved in most physiological processes. Gene expression profiles are currently being used to identify genes underlying a range of physiological responses. Characterization of these genes will help to elucidate the pathways and processes regulating physiological processes. Expanding the use of DNA microarrays to non-model species that have been critical in elucidating certain physiological pathways will be valuable in determining the genes associated with these processes. Approaches that do not require complete genome information have recently been applied to "non-model" organisms. As whole genomes are sequenced for non-model organisms, the application of DNA microarrays to comparative physiology will expand even further. The recent development of protein microarrays will be critical in understanding the regulation of physiological processes not accounted for at the genomic level. Together, DNA and protein microarrays provide the most thorough and efficient method of understanding the molecular basis of physiological processes to date. In turn, classical physiological approaches will be vital in characterizing and verifying the function of the novel genes identified by microarray experiments. Ultimately, DNA and protein microarray expression profiles may be used to predict physiological responses.

Journal Article↗
PubMed2005

Application of RNAi to cancer research and therapy.

The introduction of double-stranded RNA (dsRNA) into cells can effectively and specifically lead to the degradation of corresponding mRNAs in a gene-dependent manner, which is defined as RNA interfering (RNAi). This powerful technology has been widely employed to manipulate gene expression in mammalian and human cells, elucidate signal pathways and identify gene functions in a whole-genome scale. Simultaneously, many pharmaceutical companies are very interested in the research and development of RNAi-based drugs for various diseases, especially in cancers. In present review, we attempt to recapitulate the potential application of this breakthrough technology in many aspects of cancer gene therapy such as genome-scale screens, target identification and validation, functional analysis and animal models for diverse diseases.

Animals↗
PubMed2001

Modeling genetic networks and their evolution: a complex dynamical systems perspective.

After finishing the sequence of the human genome, a functional understanding of genome dynamics is the next major step on the agenda of the biosciences. New approaches, such as microarray techniques, and new methods of bioinformatics provide powerful tools aiming in this direction. In the last few years, important parts of genome organization and dynamics in a number of model organisms have been determined. However, an integrated view of gene regulation on a genomic scale is still lacking. Here, genome function is discussed from a complex dynamical systems perspective: which dynamical properties can a large genomic system exhibit in principle, given the local mechanisms governing the small subsystems that we know today? Models of artificial genetic networks are used to explore dynamical principles and possible emergent dynamical phenomena in networks of genetic switches. One observes evolution of robustness and dynamical self-organization in large networks of artificial regulators that are based on the dynamic mechanism of transcriptional regulators as observed in biological gene regulation. Possible biological observables and ways of experimental testing of global phenomena in genome function and dynamics are discussed. Models of artificial genetic networks provide a tool to address questions in genome dynamics and their evolution and allow simulation studies in evolutionary genomics.

Biological Evolution↗
PubMed2000

Modeling the feasibility of whole genome shotgun sequencing using a pairwise end strategy.

In pairwise end sequencing, sequences are determined from both ends of random subclones derived from a DNA target. Sufficiently similar overlapping end sequences are identified and grouped into contigs. When a clone's paired end sequences fall in different contigs, the contigs are connected together to form scaffolds. Increasingly, the goals of pairwise strategies are large and highly repetitive genomic targets. Here, we consider large-scale pairwise strategies that employ mixtures of subclone sizes. We explore the properties of scaffold formation within a hybrid theory/simulation mathematical model of a genomic target that contains many repeat families. Using this model, we evaluate problems that may arise, such as falsely linked end sequences (due either to random matches or to homologous repeats) and scaffolds that terminate without extending the full length of the target. We illustrate our model with an exploration of a strategy for sequencing the human genome. Our results show that, for a strategy that generates 10-fold sequence coverage derived from the ends of clones ranging in length from 2 to 150 kb, using an appropriate rule for detecting overlaps, we expect few false links while obtaining a single scaffold extending the length of each chromosome.

Cloning, Molecular↗
PubMed2005

Gene expression profiling of gilthead sea bream during early development and detection of stress-related genes by the application of cDNA microarray technology.

Large-scale gene expression studies were performed for one of the main European aquaculture species, the gilthead sea bream Sparus auratus L. For this purpose, a cDNA microarray containing 10,176 clones from a cDNA library of mixed embryonic and larval stages was constructed. In addition to its importance for aquaculture, the taxonomic position and the relatively small genome size of sea bream makes it a prospective model for evolutionary biology and comparative genomics. However, so far, no large-scale analysis of gene expression exists for this species. In the present study, gene expression was analyzed in gilthead sea bream during early development, a significant period in the determination of quantitative traits and therefore of considerable interest for aquaculture. Synexpression groups expressed primarily early and late in development were determined and were composed of both known and novel genes. Furthermore, it was possible to identify stress response genes induced by cortisol injections using the cDNA microarray generated. The creation of gene expression profiles for sea bream by microarray hybridization will accelerate identification of candidate genes involved in multifactorial traits and certain regulatory pathways and will also contribute to a better understanding of the genetic background of fish physiology, which may help to improve aquaculture practices.

Animals↗
PubMed2003

[Studies on the parasite Leishmania in the post-genomic era].

Leishmania is a protozoan parasite responsible for considerable morbidity worldwide. The pathologies caused by Leishmania infections are varying with the species. The ongoing determination of the Leishmania major genome sequence represents a milestone for Leishmania research. We discuss here the use of transcriptomics and proteomics to accelerate our understanding of key processes related to Leishmania biology. These two techniques should be useful to find genes and proteins that are expressed in a stage-specific manner and examples of the use of such techniques are provided. Both approaches will complement each others. Indeed, while a number of stage-specific genes have increased stable RNA levels, an even larger subset of the Leishmania amastigote genes are regulated at the level of translation. The availability of the Leishmania genome should also permit important advances in finding species-specific genes that could explain different pathologies. Functional genomic and proteomic approaches should also be useful for understanding the mechanisms of drug resistance in the parasite. The availability of both the Leishmania genome and of its human host or of the mouse animal model will facilitate large scale studies and increase our understanding of host-pathogen interactions.

Animals↗
PubMed2005

Revealing metabolic phenotypes in plants: inputs from NMR analysis.

Assessing the performance of the plant metabolic network, with its varied biosynthetic capacity and its characteristic subcellular compartmentation, remains a considerable challenge. The complexity of the network is such that it is not yet possible to build large-scale predictive models of the fluxes it supports, whether on the basis of genomic and gene expression analysis or on the basis of more traditional measurements of metabolites and their interconversions. This limits the agronomic and biotechnological exploitation of plant metabolism, and it undermines the important objective of establishing a rational metabolic engineering strategy. Metabolic analysis is central to removing this obstacle and currently there is particular interest in harnessing high-throughput and/or large-scale analyses to the task of defining metabolic phenotypes. Nuclear magnetic resonance (NMR) spectroscopy contributes to this objective by providing a versatile suite of analytical techniques for the detection of metabolites and the fluxes between them. The principles that underpin the analysis of plant metabolism by NMR are described, including a discussion of the measurement options for the detection of metabolites in vivo and in vitro, and a description of the stable isotope labelling experiments that provide the basis for metabolic flux analysis. Despite a relatively low sensitivity, NMR is suitable for high-throughput system-wide analyses of the metabolome, providing methods for both metabolite fingerprinting and metabolite profiling, and in these areas NMR can contribute to the definition of plant metabolic phenotypes that are based on metabolic composition. NMR can also be used to investigate the operation of plant metabolic networks. Labelling experiments provide information on the operation of specific pathways within the network, and the quantitative analysis of steady-state labelling experiments leads to the definition of large-scale flux maps for heterotrophic carbon metabolism. These maps define multiple unidirectional fluxes between branch-points in the metabolic network, highlighting the existence of substrate cycles and discriminating in favourable cases between fluxes in the cytosol and plastid. Flux maps can be used to define a functionally relevant metabolic phenotype and the extensive application of such maps in microbial systems suggests that they could have important applications in characterising the genotypes produced by plant genetic engineering.

Biotechnology↗
PubMed2006

Efficient identification of DNA hybridization partners in a sequence database.

MOTIVATION: The specific hybridization of complementary DNA molecules underlies many widely used molecular biology assays, including the polymerase chain reaction and various types of microarray analysis. In order for such an assay to work well, the primer or probe must bind to its intended target, without also binding to additional sequences in the reaction mixture. For any given probe or primer, potential non-specific binding partners can be identified using state-of-the-art models of DNA binding stability. Unfortunately, these models rely on dynamic programming algorithms that are too slow to apply on a genomic scale. RESULTS: We present an algorithm that efficiently scans a DNA database for short (approximately 20-30 base) sequences that will bind to a query sequence. We use a filtering approach, in which a series of increasingly stringent filters is applied to a set of candidate k-mers. The k-mers that pass all filters are then located in the sequence database using a precomputed index, and an accurate model of DNA binding stability is applied to the sequence surrounding each of the k-mer occurrences. This approach reduces the time to identify all binding partners for a given DNA sequence in human genomic DNA by approximately three orders of magnitude, from two days for the ENCODE regions to less than one minute for typical queries. Our approach is scalable to large DNA sequences. Our method can scan the human genome for medium strength binding sites to a candidate PCR primer in an average of 34.5 minutes. AVAILABILITY: Software implementing the algorithms described here is available at http://noble.gs.washington.edu/proj/dna-binding.

Algorithms↗
PubMed2001

A tour of structural genomics.

Structural genomics projects aim to provide an experimental or computational three-dimensional model structure for all of the tractable macromolecules that are encoded by complete genomes. To this end, pilot centres worldwide are now exploring the feasibility of large-scale structure determination. Their experimental structures and computational models are expected to yield insight into the molecular function and mechanism of thousands of proteins. The pervasiveness of this information is likely to change the use of structure in molecular biology and biochemistry.

Amino Acid Sequence↗
PubMed2006

Strong regional biases in nucleotide substitution in the chicken genome.

Interspersed repeats have emerged as a valuable tool for studying neutral patterns of molecular evolution. Here we analyze variation in the rate and pattern of nucleotide substitution across all autosomes in the chicken genome by comparing the present-day CR1 repeat sequences with their ancestral copies and reconstructing nucleotide substitutions with a maximum likelihood model. The results shed light on the origin and evolution of large-scale heterogeneity in GC content found in the genomes of birds and mammals--the isochore structure. In contrast to mammals, where GC content is becoming homogenized, heterogeneity in GC content is being reinforced in the chicken genome. This is also supported by patterns of substitution inferred from alignments of introns in chicken, turkey, and quail. Analysis of individual substitution frequencies is consistent with the biased gene conversion (BGC) model of isochore evolution, and it is likely that patterns of evolution in the chicken genome closely resemble those in the ancestral amniote genome, when it is inferred that isochores originated. Microchromosomes and distal regions of macrochromosomes are found to have elevated substitution rates and a more GC-biased pattern of nucleotide substitution. This can largely be accounted for by a strong correlation between GC content and the rate and pattern of substitution. The results suggest that an interaction between increased mutability at CpG motifs and fixation biases due to BGC could explain increased levels of divergence in GC-rich regions.

Alu Elements↗