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At least 487 records · Page 27Linked to original sources
PubMed1999

Identification of genomic regions controlling experimental autoimmune uveoretinitis in rats.

The present study attempts to identify specific genetic loci contributing to experimental autoimmune uveoretinitis (EAU) susceptibility in F2 progeny of resistant Fischer (F344/N) and susceptible Lewis (LEW/N) inbred rats. F2 progeny of F344/N x LEW/N inbred rats were immunized with the R16 peptide of interphotoreceptor retinoid-binding protein (IRBP). A genome-wide scan was conducted using 125 simple sequence length polymorphism markers in selected F2 animals that developed severe eye disease or remained unaffected to identify phenotype:genotype co-segregation. The F2 population (n = 1287) demonstrated a wide range of histologically assessed EAU scores (assessed on a scale of 0-4). The disease incidence and severity were not consistent with a simple Mendelian inheritance model. Of the F2 hybrid rats, 60% developed EAU, implying the existence of a potent susceptibility locus with incomplete penetrance associated with the LEW genome or a more complex polygenic model of inheritance. Two genomic regions, on chromosomes 4 and 12, showed strong genetic linkage to the EAU phenotype (P < 0.0016), suggesting the presence of susceptibility loci in these chromosomal regions. In conclusion, we have identified two genomic candidate intervals from D4Arb8 to D4Mit17 on chromosome 4 and from the chromosome end to D12Arb8 on chromosome 12, that appear to influence EAU susceptibility in LEW/F344 rats. Further analysis of these genomic regions may lead to identification of the susceptibility genes and to characterization of their function.

Animals↗
PubMed2025

Genome-wide CRISPR Screening Identifies NF&#x3ba;B and c-MET as Druggable Targets to Sensitize Lenvatinib Treatment in Hepatocellular Carcinoma.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC), the dominant form of liver cancer, is a leading cause of cancer death worldwide. Sorafenib and lenvatinib have long been the 2 limited options of first-line treatments for patients with unresectable advanced HCC. However, the single-drug treatment strategy only shows modest survival benefit, mostly because of the survival ability of cancer cells to activate alternative pathways for compensation. In this study, we aim to identify druggable targets contributing to lenvatinib resistance and evaluate the efficacy of combining respective inhibitors and lenvatinib on HCC. METHODS: Genome-scale clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 knockout library screening was applied on the vehicle group and lenvatinib treatment group. Identified druggable candidates were validated individually on HCC cell models. Therapeutic effects of the combined treatment of inhibitors of candidate genes and lenvatinib were evaluated in vitro and in vivo. RESULTS: We successfully identified NFKB1 and MET as critical drivers for the development of lenvatinib resistance in HCC cells. By perturbing the 2 genes with either CRISPR knockout or RNA interference approaches, lenvatinib treatments were significantly sensitized. Moreover, using small molecules QNZ and cabozantinib to target NFKB1 and MET, respectively, this together with lenvatinib could synergistically induce apoptosis and suppress HCC growth in vitro and in vivo. CONCLUSION: Our results demonstrated that genome-wide CRISPR/Cas9 screening is a powerful tool for the design of rational combinational cancer therapy and provided candidate genes possible for combined treatments with lenvatinib to improve therapy efficacy.

Carcinoma, Hepatocellular↗
PubMed2004

The impact of SNP density on fine-scale patterns of linkage disequilibrium.

Linkage disequilibrium (LD) is a measure of the degree of association between alleles in a population. The detection of disease-causing variants by association with neighbouring single nucleotide polymorphisms (SNPs) depends on the existence of strong LD between them. Previous studies have indicated that the extent of LD is highly variable in different chromosome regions and different populations, demonstrating the importance of genome-wide accurate measurement of LD at high resolution throughout the human genome. A uniform feature of these studies has been the inability to detect LD in regions of low marker density. To investigate the dependence of LD patterns on marker selection we performed a high-resolution study in African-American, Asian and UK Caucasian populations. We selected over 5000 SNPs with an average spacing of approximately 1 SNP per 2 kb after validating ca 12 000 SNPs derived from a dense SNP collection (1 SNP per 0.3 kb on average). Applications of different statistical methods of LD assessment highlight similar areas of high and low LD. However, at high resolution, features such as overall sequence coverage in LD blocks and block boundaries vary substantially with respect to marker density. Model-based linkage disequilibrium unit (LDU) maps appear robust to marker density and consistently influenced by marker allele frequency. The results suggest that very dense marker sets will be required to yield stable views of fine-scale LD in the human genome.

Black or African American↗
PubMed2002

Asymmetric functional divergence of duplicate genes in yeast.

Most duplicate genes are eliminated from a genome shortly after duplication, but those that remain are an important source of biochemical diversity. Here, I present evidence from genome-scale protein-protein interaction data, microarray expression data, and large-scale gene knockout data that this diversification is often asymmetrical: one duplicate usually shows significantly more molecular or genetic interactions than the other. I propose a model that can explain this divergence pattern if asymmetrically diverging duplicate gene pairs show increased robustness to deleterious mutations.

Environment↗
PubMed2001

FLEXGene repository: from sequenced genomes to gene repositories for high-throughput functional biology and proteomics.

The vast amount of information generated by the human genome sequencing project and related projects has given rise to a new paradigm in experimental biology. This new paradigm invokes the experimentation and data analysis at genome-wide scales, as well as the generation of new technologies and resources that take full advantage of the available sequence information. The Institute of Proteomics at Harvard Medical School is building a comprehensive, characterized, arrayed and flexible gene repository that will allow full exploitation of the genomic information by enabling functional genomics as well as protein expression, purification and analysis at genome wide scale. The FLEXGene repository (Full Length EXpression-ready) will contain clones representing the complete set of open reading frames (ORFs) of different organisms including H. sapiens and several pathogens and model organisms. The clones are constructed using recombination-based cloning technology so that hundreds or thousands of coding regions can be transferred into any expression vector in a parallel and timely mode, allowing the broadest variety of experiments to be carried out.

Animals↗
PubMed2002

An HMM model for coiled-coil domains and a comparison with PSSM-based predictions.

MOTIVATION: Large-scale sequence data require methods for the automated annotation of protein domains. Many of the predictive methods are based either on a Position Specific Scoring Matrix (PSSM) of fixed length or on a window-less Hidden Markov Model (HMM). The performance of the two approaches is tested for Coiled-Coil Domains (CCDs). The prediction of CCDs is used frequently, and its optimization seems worthwhile. RESULTS: We have conceived MARCOIL, an HMM for the recognition of proteins with a CCD on a genomic scale. A cross-validated study suggests that MARCOIL improves predictions compared to the traditional PSSM algorithm, especially for some protein families and for short CCDs. The study was designed to reveal differences inherent in the two methods. Potential confounding factors such as differences in the dimension of parameter space and in the parameter values were avoided by using the same amino acid propensities and by keeping the transition probabilities of the HMM constant during cross-validation. AVAILABILTY: The prediction program and the databases are available at http://www.wehi.edu.au/bioweb/Mauro/Marcoil

Algorithms↗
PubMed2004

Development of a targeted transgenesis strategy in highly differentiated cells: a powerful tool for functional genomic analysis.

Functional genomic analysis is a challenging step in the so-called post-genomic field. Identification of potential targets using large-scale gene expression analysis requires functional validation to identify those that are physiologically relevant. Genetically modified cell models are often used for this purpose allowing up- or down-expression of selected targets in a well-defined and if possible highly differentiated cell type. However, the generation of such models remains time-consuming and expensive. In order to alleviate this step, we developed a strategy aimed at the rapid and efficient generation of genetically modified cell lines with conditional, inducible expression of various target genes. Efficient knock-in of various constructs, called targeted transgenesis, in a locus selected for its permissibility to the tet inducible system, was obtained through the stimulation of site-specific homologous recombination by the meganuclease I-SceI. Our results demonstrate that targeted transgenesis in a reference inducible locus greatly facilitated the functional analysis of the selected recombinant cells. The efficient screening strategy we have designed makes possible automation of the transfection and selection steps. Furthermore, this strategy could be applied to a variety of highly differentiated cells.

Animals↗
PubMed2003

A large-scale, gene-driven mutagenesis approach for the functional analysis of the mouse genome.

A major challenge of the postgenomic era is the functional characterization of every single gene within the mammalian genome. In an effort to address this challenge, we assembled a collection of mutations in mouse embryonic stem (ES) cells, which is the largest publicly accessible collection of such mutations to date. Using four different gene-trap vectors, we generated 5,142 sequences adjacent to the gene-trap integration sites (gene-trap sequence tags; http://genetrap.de) from >11,000 ES cell clones. Although most of the gene-trap vector insertions occurred randomly throughout the genome, we found both vector-independent and vector-specific integration "hot spots." Because >50% of the hot spots were vector-specific, we conclude that the most effective way to saturate the mouse genome with gene-trap insertions is by using a combination of gene-trap vectors. When a random sample of gene-trap integrations was passaged to the germ line, 59% (17 of 29) produced an observable phenotype in transgenic mice, a frequency similar to that achieved by conventional gene targeting. Thus, gene trapping allows a large-scale and cost-effective production of ES cell clones with mutations distributed throughout the genome, a resource likely to accelerate genome annotation and the in vivo modeling of human disease.

Animals↗
PubMed1999

Mathematical simulation and analysis of cellular metabolism and regulation.

MOTIVATION: A better understanding of the biological phenomena observed in cells requires the creation and analysis of mathematical models of cellular metabolism and physiology. The formulation and study of such models must also be simplified as far as possible to cope with the increasing complexity demanded and exponential accumulation of the metabolic reconstructions computed from sequenced genomes. RESULTS: A mathematical simulation workbench, DBsolve, has been developed to simplify the derivation and analysis of mathematical models. It combines: (i) derivation of large-scale mathematical models from metabolic reconstructions and other data sources; (ii) solving and parameter continuation of non-linear algebraic equations (NAEs), including metabolic control analysis; (iii) solving the non-linear stiff systems of ordinary differential equations (ODEs); (iv) bifurcation analysis of ODEs; (v) parameter fitting to experimental data or functional criteria based on constrained optimization. The workbench has been successfully used for dynamic metabolic modeling of some typical biochemical networks (Dolgacheva et al., Biochemistry (Moscow), 6, 1063-1068, 1996; Goldstein and Goryanin, Mol. Biol. (Moscow), 30, 976-983, 1996), including microbial glycolytic pathways, signal transduction pathways and receptor-ligand interactions. AVAILABILITY: DBsolve 5. 00 is freely available from http://websites.ntl.com/ approximately igor.goryanin. CONTACT: gzz78923@ggr.co.uk

Algorithms↗
PubMed2005

Comparative genomics of the pennate diatom Phaeodactylum tricornutum.

Diatoms are one of the most important constituents of phytoplankton communities in aquatic environments, but in spite of this, only recently have large-scale diatom-sequencing projects been undertaken. With the genome of the centric species Thalassiosira pseudonana available since mid-2004, accumulating sequence information for a pennate model species appears a natural subsequent aim. We have generated over 12,000 expressed sequence tags (ESTs) from the pennate diatom Phaeodactylum tricornutum, and upon assembly into a nonredundant set, 5,108 sequences were obtained. Significant similarity (E < 1E-04) to entries in the GenBank nonredundant protein database, the COG profile database, and the Pfam protein domains database were detected, respectively, in 45.0%, 21.5%, and 37.1% of the nonredundant collection of sequences. This information was employed to functionally annotate the P. tricornutum nonredundant set and to create an internet-accessible queryable diatom EST database. The nonredundant collection was then compared to the putative complete proteomes of the green alga Chlamydomonas reinhardtii, the red alga Cyanidioschyzon merolae, and the centric diatom T. pseudonana. A number of intriguing differences were identified between the pennate and the centric diatoms concerning activities of relevance for general cell metabolism, e.g. genes involved in carbon-concentrating mechanisms, cytosolic acetyl-Coenzyme A production, and fructose-1,6-bisphosphate metabolism. Finally, codon usage and utilization of C and G relative to gene expression (as measured by EST redundance) were studied, and preferences for utilization of C and CpG doublets were noted among the P. tricornutum EST coding sequences.

Animals↗
PubMed2006

Quantitative analysis of dental microwear in threespine stickleback: a new approach to analysis of trophic ecology in aquatic vertebrates.

1. The threespine stickleback Gasterosteus aculeatus is an important model organism in studies of genomic and phenotypic evolution, adaptation and speciation. Fossil Gasterosteus offer the potential to test models derived from studies of extant fishes over true evolutionary time-scales. Competition for food resources, for example, plays an important part in stickleback speciation, causing divergence in food gathering traits and ecological character displacement, but it is not possible to test this model in fossils because evidence of diet is almost never preserved. 2. We demonstrate here that quantitative analysis of dental microwear, a technique previously applied only to mammals, provides a reliable guide to the dietary preferences of stickleback. Teeth from stickleback raised under laboratory conditions exhibit microwear patterns that vary systematically according to substrate coarseness and whether fishes feed on Daphnia within the water column, or on chironomid larvae from the bottom. Furthermore, microwear data exhibit a progressive shift in their distribution that tracks differences in experimental feeding treatments. 3. Microwear in wild populations also exhibits a relationship with feeding. In blind assessments of trophic niche based on microwear patterns we were able to correctly assign all but one equivocal population to trophic group. Microwear data from wild stickleback exhibit a shift in distribution comparable with that observed across the range of treatments in the laboratory and these allow populations to be ranked according to the degree to which they approach fully benthic or fully limnetic feeding. 4. Our results demonstrate that microwear has the potential to be a powerful tool in the analysis of fish trophic ecology, particularly in the analysis of species pairs and niche differentiation. It has advantages over the trophic snapshot provided by analysis of stomach contents in that microwear reflects feeding and food preferences over a longer period of time, and can be applied where these data are unavailable. Furthermore, it is applicable to extinct organisms and fossils, allowing the role of trophic ecology, niche partitioning and competition over evolutionary time-scales to be investigated for the first time.

Animals↗
PubMed1998

Background and Overview of Comparative Genomics.

Comparative genomics---the cross-referencing of information on genome organization between species---provides an additional dimension to the Human Genome Project and can derive much information from it for the benefit of animal health and animal breeding. Arrangements of genes and other DNA sequences may be determined by a variety of genetic and physical techniques, at resolutions from the gross cytological level to the level of the single base pair. Gross arrangements and rearrangements can also be charted by comparative chromosome painting. Genome organization may then be compared across mammal---and other vertebrate---species. Genetic mapping is well advanced in several livestock species as well as rodent model species, and outline maps are available for at least 30 mammal species in eight orders. At the time of this writing, maps are being rapidly constructed for chicken and fish species. Comparisons, even over vast evolutionary time scales, show that the mammal genome---indeed, the vertebrate genome---has been highly conserved. Thus, information about location and function of genes is directly transferable across species and should greatly accelerate the search for genes that specify inherited diseases in domestic mammals and humans as well as genes that specify economically important traits.

Journal Article↗
PubMed1998

Genome dynamics, evolution, and protein modeling in the olfactory receptor gene superfamily.

The human olfactory subgenome represents several hundred olfactory receptor (OR) genes in a dozen or more clusters on several chromosomes. One OR gene cluster on human chromosome 17 has been characterized by us in detail. Based on a large-scale DNA sequence analysis, we have identified events of gene duplication and fusion as well as the generation of pseudogenes. The latter instances of 'gene death' could underlie the widespread phenomenon of human specific anosmias. Sixteen OR coding regions were found on this cluster, and six of them are pseudogenes. One of these pseudogenes, OR17-23, was found to be an intact open reading frame in an old world monkey. This may be a reflection of an OR repertoire diminution in man. A homology model of the OR protein was constructed by utilizing the rich information available on approximately 200 OR sequences. The putative odorant complementarity determining regions (CDR) was found to consist of 20 hypervariable residues facing an interior caving defined by transmembrane helices 3, 4 and 5. Such a model could be useful in analyzing additional OR gene sequences in the human genome in terms of odorant binding.

Base Sequence↗
PubMed2002

Ab initio protein structure prediction on a genomic scale: application to the Mycoplasma genitalium genome.

An ab initio protein structure prediction procedure, TOUCHSTONE, was applied to all 85 small proteins of the Mycoplasma genitalium genome. TOUCHSTONE is based on a Monte Carlo refinement of a lattice model of proteins, which uses threading-based tertiary restraints. Such restraints are derived by extracting consensus contacts and local secondary structure from at least weakly scoring structures that, in some cases, can lack any global similarity to the sequence of interest. Selection of the native fold was done by using the convergence of the simulation from two different conformational search schemes and the lowest energy structure by a knowledge-based atomic-detailed potential. Among the 85 proteins, for 34 proteins with significant threading hits, the template structures were reasonably well reproduced. Of the remaining 51 proteins, 29 proteins converged to five or fewer clusters. In the test set, 84.8% of the proteins that converged to five or fewer clusters had a correct fold among the clusters. If this statistic is simply applied, 24 proteins (84.8% of the 29 proteins) may have correct folds. Thus, the topology of a total of 58 proteins probably has been correctly predicted. Based on these results, ab initio protein structure prediction is becoming a practical approach.

Algorithms↗
PubMed2006

Genomewide linkage scan for obsessive-compulsive disorder: evidence for susceptibility loci on chromosomes 3q, 7p, 1q, 15q, and 6q.

Obsessive-compulsive disorder (OCD) is the tenth most disabling medical condition worldwide. Twin and family studies implicate a genetic etiology for this disorder, although specific genes have yet to be identified. Here, we present the first large-scale model-free linkage analysis of both extended and nuclear families using both 'broad' (definite and probable diagnoses) and 'narrow' (definite only) definitions of OCD. We conducted a genome-scan analysis of 219 families collected as part of the OCD Collaborative Genetics Study. Suggestive linkage signals were revealed by multipoint analysis on chromosomes 3q27-28 (P=0.0003), 6q (P=0.003), 7p (P=0.001), 1q (P=0.003), and 15q (P=0.006). Using the 'broad' OCD definition, we observed the strongest evidence for linkage on chromosome 3q27-28. The maximum overall Kong and Cox LODall score (2.67) occurred at D3S1262 and D3S2398, and simulation based P-values for these two signals were 0.0003 and 0.0004, respectively, although for both signals, the simulation-based genome-wide significance levels were 0.055. Covariate-linkage analyses implicated a possible role of gene(s) on chromosome 1 in increasing the risk for an earlier onset form of OCD. We are currently pursuing fine mapping in the five regions giving suggestive signals, with a particular focus on 3q27-28. Given probable etiologic heterogeneity in OCD, mapping gene(s) involved in the disorder may be enhanced by replication studies, large-scale family-based linkage studies, and the application of novel statistical methods.

Chromosomes, Human↗
PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor&#x2012;recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗
PubMed2003

The high road to success: how investing in ethics enhances corporate objectives.

There is a growing gap between the tidal wave of information emerging from the Human Genome Project and other molecular biology initiatives, and the clinical research needed to transform these discoveries into new diagnostics and therapeutics. While genomics-based technologies are being rapidly integrated into pharmaceutical R&D, many steps in the experimental process are still reliant on traditional surrogate model systems whose predictive power about human disease is incomplete or inaccurate. There is a growing trend underway in the research community to introduce actual human disease understanding as early as possible into discovery, thereby improving accuracy of results throughout the R&D continuum. Such an approach (known as clinical genomics: the large scale study of genes in the context of actual human disease) requires the availability of large quantities of ethically and legally sourced, high-quality human tissues with associated clinical information.Heretofore, no source could meet all of these requirements. Ardais Corporation was the first to address this need by pioneering a systematized, standardized network for the collection, processing, dissemination and research application of human tissue and associated clinical information, all of which rest on the highest ethical standards. Based on a novel model of collaboration between industry and the academic/medical community, Ardais has created procedures, structures, technologies, and information tools that collectively compromise a new paradigm in the application of human disease to biomedical research. Ardais now serves as a clinical genomics resource to dozens of academic researchers and biopharmaceutical companies, providing products and services to accelerate and improve drug discovery and development.

Advisory Committees↗
PubMed2005

[Application of RNAi in gene-deficient models].

RNA interference (RNAi), a process of sequence-specific gene silence,can effectively and specifically suppress the activity of corresponding mRNAs in a gene-dependent manner induced by double-stranded RNA (dsRNA). This powerful technology has been widely employed to manipulate gene expression in mammalian and human cells, elucidate signal transduction pathways and identify gene functions in a whole-genome scale. Simultaneously, it also displays a bright and fascinating future in the research and development of RNAi-based drugs for various diseases such as viral infections, cancers, metabolic disorders and genetic diseases. In present review, we attempt to recapitulate the application of this breakthrough technology in establishing gene-deficient models and show the alluring foreground of RNAi-based gene therapy in these diseases.

Animals↗