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Results for “Functional Genomics”

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At least 973 records · Page 54Linked to original sources
PubMed2003

piggyBac-based insertional mutagenesis and enhancer detection as a tool for functional insect genomics.

Transposon mutagenesis provides a fundamental tool for functional genomics. Here we present a non-species-specific, combined enhancer detection and binary expression system based on the transposable element piggyBac: For the different components of this insertional mutagenesis system, we used widely applicable transposons and distinguishable broad-range transformation markers, which should enable this system to be operational in nonmodel arthropods. In a pilot screen in Drosophila melanogaster, piggyBac mutator elements on the X chromosome were mobilized in males by a Hermes-based jumpstarter element providing piggyBac transposase activity under control of the alpha1-tubulin promoter. As primary reporters in the piggyBac mutator elements, we employed the heterologous transactivators GAL4delta or tTA. To identify larval and adult enhancer detectors, strains carrying UASp-EYFP or TRE-EYFP as secondary reporter elements were used. Tissue-specific enhancer activities were readily observed in the GAL4delta/UASp-based systems, but only rarely in the tTA/TRE system. Novel autosomal insertions were recovered with an average jumping rate of 80%. Of these novel insertions, 3.8% showed homozygous lethality, which was reversible by piggyBac excision. Insertions were found in both coding and noncoding regions of characterized genes and also in noncharacterized and non-P-targeted CG-number genes. This indicates that piggyBac will greatly facilitate the intended saturation mutagenesis in Drosophila.

Animals↗
PubMed2003

Impact of genome-wide functional analyses on cell biology research.

The availability of complete genome sequences for a variety of organisms, coupled with novel approaches that allow evaluation of the functions of thousands of genes in parallel, have the potential to greatly impact on cell biology research. Functional genomic approaches in Saccharomyces cerevisiae are beginning to make significant contributions to the understanding of complex biological systems.

Animals↗
PubMed2006

ChIP-chip comes of age for genome-wide functional analysis.

In the post-genome era, attention has focused on the functions of genome sequences and how they are regulated. The emerging epigenomic changes and the interactions between cis-acting elements and protein factors may play a central role in gene regulation. To understand the crosstalk between DNA and protein on a genome-wide scale, one emerging technique, called ChIP-chip, takes the strategy of combining chromatin immunoprecipitation with microarray. This new high-throughput strategy helps screen the targets of critical transcription factors and profile the genome-wide distribution of histone modifications, which will enable the feasibility of conducting a large-scale study, such as the Human Epigenome Project.

Animals↗
PubMed2004

The non-photosynthetic, pathogenic green alga Helicosporidium sp. has retained a modified, functional plastid genome.

A fragment of the Helicosporidium sp. (Chlorophyta: Trebouxiophyceae) plastid genome has been sequenced. The genome architecture was compared to that of both a non-photosynthetic relative (Prototheca wickerhamii) and a photosynthetic relative (Chlorella vulgaris). Comparative genomic analysis indicated that Helicosporidium and Prototheca are closely related genera. The analyses also revealed that the Helicosporidium sp. plastid genome has been rearranged. In particular, two ribosomal protein-encoding genes (rpl19 and rps23) appeared to have been transposed, or lost from the Helicosporidium sp. plastid genome. RT-PCR reactions demonstrated that the retained plastid genes were transcribed, suggesting that, despite rearrangement(s), the Helicosporidium sp. plastid genome has remained functional. The modified plastid genome architecture is a novel apomorphy that indicates that the Helicosporidia are highly derived green algae, more so than Prototheca spp. As such, they represent a promising model to study organellar genome reorganizations in parasitic protists.

Algal Proteins↗
PubMed2026

Predicting genome-wide functional constraints with GPN-Star.

Genomic language models have emerged as a powerful approach for learning genome-wide functional constraints directly from DNA sequences1. However, standard genomic language models adapted from natural language processing often require large model sizes and computational resources, yet still fall short of classical evolutionary models in predictive tasks2-4. Here we introduce a genomic pretrained network with species tree and alignment representations (GPN-Star), which is a biologically grounded genomic language model featuring a phylogeny-aware architecture that leverages whole-genome alignments and species trees to model evolutionary relationships explicitly. Trained on alignments spanning vertebrate, mammal and primate evolutionary timescales, GPN-Star achieves state-of-the-art performance across a wide range of variant effect prediction tasks in both coding and non-coding regions of the human genome. Analyses across timescales show task-dependent advantages of modelling more recent versus deeper evolution. To demonstrate its potential to advance human genetics, we show that GPN-Star substantially outperforms previous methods in prioritizing pathogenic and fine-mapped genome-wide association study variants, yields strong enrichments of complex trait heritability and improves power in rare variant association testing5. Extending beyond humans, we train GPN-Star for five model organisms-Mus musculus, Gallus gallus, Drosophila melanogaster, Caenorhabditis elegans and Arabidopsis thaliana-demonstrating the robustness and generalizability of the framework. Taken together, these results position GPN-Star as a scalable, powerful and flexible tool for genome interpretation, well suited to leverage the growing abundance of comparative genomics data.

Journal Article↗
PubMed2004

Proteomics in the chicken: tools for understanding immune responses to avian diseases.

The entire chicken genome sequence will be available by the time this review is in press. Chickens will be the first production animal species to enter the "postgenomic era." This fundamental structural genomics achievement allows, for the first time, complete functional genomics approaches for understanding the molecular basis of chicken normo- and pathophysiology. The functional genomics paradigm, which contrasts with classical functional genetic investigations of one gene (or few) in isolation, is the systematic holistic genetic analyses of biological systems in defined contexts. Context-dependent gene interactions are the fundamental mechanics of all life. Functional genomics uses high-throughput large-scale experimental methods combined with statistical and computational analyses. Projects with expressed sequence tags in chickens have already allowed the creation of cDNA microarrays for large-scale context-dependant mRNA analysis (transcriptomics). However, proteins are the functional units of almost all biological processes, and protein expression very often bears no correlation to mRNA expression. Proteomics, a discipline within functional genomics, is the context-defined analysis of complete complements of proteins. Proteomics bridges the "sequence-to-phenotype gap;" it complements structural and other functional genomics approaches. Proteomics requires high capital investment but has ubiquitous biological applications. Although currently the fastest-growing human biomedical discipline, new paradigms may need to be established for production animal proteomics research. The prospective promise and potential pitfalls of using proteomics approaches to improve poultry pathogen control will be specifically highlighted. The first stage of our recently established proteomics program is global protein profiling to identify differentially expressed proteins in the context of the commercially important pathogens. Our trials and tribulations in establishing our proteomics program, as well some of our initial data to understand chicken immune system function, will be discussed.

Animals↗
PubMed2001

What is bioinformatics? A proposed definition and overview of the field.

BACKGROUND: The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. OBJECTIVES: Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. METHODS: Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. RESULTS AND CONCLUSIONS: Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

Computational Biology↗
PubMed2004

The role of emerging genomics and proteomics technologies in cancer drug target discovery.

Cancer drugs have traditionally been identified in screens designed to produce broad biological end points such as cell death. A serious undesired outcome of drugs discovered in these screens is that the mechanism of drug action is unknown and such drugs often have adverse side effects. Designing cancer drugs that act on specific targets offer the advantage that the mechanism of drug action can be understood and accurately monitored in clinical trials leading to development of better drugs. The pharmacological industry has recently shifted to a target directed drug discovery model. However, until recently potential cancer drug targets comprised of only a small fraction of the human genome. The human genome project and high-throughput structural and functional genomics have dramatically increased the number of cancer drug targets. Deciphering cancer drug targets requires the understanding of biochemical pathways that are affected in the cancer genome. It has been suggested that utilization of Single-nucleotide polymorphisms (SNPs) will aid in identifying individuals at high risk of developing certain cancers, and will also help in development of tailored medication or identify genetic profiles of specific drug action and toxicity. Achieving successful new cancer drug development schemes will require a merger of research disciplines that include pharmacology, genomics, comparative genomics, functional genomics, proteomics and bioinformatics. In this review the significance and challenges of these rapidly evolving technologies in cancer drug target discovery are discussed.

Animals↗
PubMed2001

The neprilysin (NEP) family of zinc metalloendopeptidases: genomics and function.

Neprilysin (NEP), a thermolysin-like zinc metalloendopeptidase, plays an important role in turning off peptide signalling events at the cell surface. It is involved in the metabolism of a number of regulatory peptides of the mammalian nervous, cardiovascular, inflammatory and immune systems. Examples include enkephalins, tachykinins, natriuretic and chemotactic peptides. NEP is an integral plasma membrane ectopeptidase of the M13 family of zinc peptidases. Other related mammalian NEP-like enzymes include the endothelin-converting enzymes (ECE-1 and ECE-2), KELL and PEX. A number of novel mammalian homologues of NEP have also recently been described. NEP family members are potential therapeutic targets, for example in cardiovascular and inflammatory disorders, and potent and selective inhibitors such as phosphoramidon have contributed to understanding enzyme function. Inhibitor design should be facilitated by the recent three-dimensional structural solution of the NEP-phosphoramidon complex. For several of the family members, however, a well-defined physiological function or substrate is lacking. Knowledge of the complete genomes of Caenorhabditis elegans and Drosophila melanogaster allows the full complement of NEP-like activities to be analysed in a single organism. These model organisms also provide convenient systems for examining cell-specific expression, developmental and functional roles of this peptidase family, and reveal the power of functional genomics.

Animals↗
PubMed2005

Characterization of 954 bovine full-CDS cDNA sequences.

BACKGROUND: Genome assemblies rely on the existence of transcript sequence to stitch together contigs, verify assembly of whole genome shotgun reads, and annotate genes. Functional genomics studies also rely on transcript sequence to create expression microarrays or interpret digital tag data produced by methods such as Serial Analysis of Gene Expression (SAGE). Transcript sequence can be predicted based on reconstruction from overlapping expressed sequence tags (EST) that are obtained by single-pass sequencing of random cDNA clones, but these reconstructions are prone to errors caused by alternative splice forms, transcripts from gene families with related sequences, and expressed pseudogenes. These errors confound genome assembly and annotation. The most useful transcript sequences are derived by complete insert sequencing of clones containing the entire length, or at least the full protein coding sequence (CDS) portion, of the source mRNA. While the bovine genome sequencing initiative is nearing completion, there is currently a paucity of bovine full-CDS mRNA and protein sequence data to support bovine genome assembly and functional genomics studies. Consequently, the production of high-quality bovine full-CDS cDNA sequences will enhance the bovine genome assembly and functional studies of bovine genes and gene products. The goal of this investigation was to identify and characterize the full-CDS sequences of bovine transcripts from clones identified in non-full-length enriched cDNA libraries. In contrast to several recent full-length cDNA investigations, these full-CDS cDNAs were selected, sequenced, and annotated without the benefit of the target organism's genomic sequence, by using comparison of bovine EST sequence to existing human mRNA to identify likely full-CDS clones for full-length insert cDNA (FLIC) sequencing. RESULTS: The predicted bovine protein lengths, 5' UTR lengths, and Kozak consensus sequences from 954 bovine FLIC sequences (bFLICs; average length 1713 nt, representing 762 distinct loci) are all consistent with previously sequenced mammalian full-length transcripts. CONCLUSION: In most cases, the bFLICs span the entire CDS of the genes, providing the basis for creating predicted bovine protein sequences to support proteomics and comparative evolutionary research as well as functional genomics and genome annotation. The results demonstrate the utility of the comparative approach in obtaining predicted protein sequences in other species.

5' Untranslated Regions↗
PubMed2005

Genome complexity and repetitive DNA in metazoans from extreme marine environments.

As genomics converges with ecology and evolution to identify the fundamental linkages between genome structure and function, genome and transcriptome complexity will need to be measured in organisms from more diverse habitats, most often in the absence of complete sequence data. Here, we describe the complexity of ten genomes measured by a novel, high-throughput fluorescence-based kinetic hybridization assay. We applied the Shannon information index, H, and a related, fluorescence-adjusted index, H(f), as unique metrics of the hybridization kinetics to complement the conventional rate constant, k. A strong, positive relationship was present between H(f), and the repetitive DNA content of five eukaryotic genomes previously determined by Cot kinetic analyses (Onchorynchus keta, Ilyanassa obsoleta, Bos taurus, Limulus polyphemus, Saccharyomyces cerevisiae). This relationship was used to characterize the complexity of previously unstudied genomic samples in five metazoan taxa from three marine environments, including deep-sea hydrothermal vents (Alvinella pompejana), the temperate subtidal (Streblospio benedicti), and Antarctic coastal bays (Sterechinus neumayeri, Odontaster validus, Tritonia antarctica). Contrary to the predictions of nucleotypic theory, Antarctic invertebrates consistently had the lowest quantities of repetitive DNA in conjunction with low metabolic rates and highly protracted rates of cell division and larval development. Conversely, hydrothermal vent species with rapid cell division and growth do not have significantly different genome sizes or particularly low amounts of repetitive DNA as compared to non-vent, deep-sea taxa. Furthermore, there appears to be a positive correlation between the temperature at which the most abundant repetitive sequence classes anneal and habitat thermal stability. Thus, our study reveals a potential shift in repetitive sequence representation between these extreme environments that may be related to genome function in species living at these different thermal regimes.

Animals↗
PubMed2023

DisP-seq reveals the genome-wide functional organization of DNA-associated disordered proteins.

Intrinsically disordered regions (IDRs) in DNA-associated proteins are known to influence gene regulation, but their distribution and cooperative functions in genome-wide regulatory programs remain poorly understood. Here we describe DisP-seq (disordered protein precipitation followed by DNA sequencing), an antibody-independent chemical precipitation assay that can simultaneously map endogenous DNA-associated disordered proteins genome-wide through a combination of biotinylated isoxazole precipitation and next-generation sequencing. DisP-seq profiles are composed of thousands of peaks that are associated with diverse chromatin states, are enriched for disordered transcription factors (TFs) and are often arranged in large lineage-specific clusters with high local concentrations of disordered proteins and different combinations of histone modifications linked to regulatory potential. We use DisP-seq to analyze cancer cells and reveal how disordered protein-associated islands enable IDR-dependent mechanisms that control the binding and function of disordered TFs, including oncogene-dependent sequestration of TFs through long-range interactions and the reactivation of differentiation pathways upon loss of oncogenic stimuli in Ewing sarcoma.

DNA↗
PubMed2004

Lipidic carriers of siRNA: differences in the formulation, cellular uptake, and delivery with plasmid DNA.

RNA interference (RNAi) has become a popular tool for downregulating specific gene expression in many species, including mammalian cells [Novina, C. D., and Sharp, P. A. (2004) The RNAi revolution, Nature 430, 161-164]. Synthetic double-stranded RNA sequences (siRNA) of 21-23 nucleotides have been shown in particular to have the potential to silence specifically gene function in cultured mammalian cells. As a result, there has been a significant surge of interest in the application of siRNA in functional genomics programs as a means of deciphering specific gene function. However, for siRNA functional genomics studies to be valuable and effective, specific silencing of any given target gene is essential, devoid of nonspecific knockdown and toxic side effects. For this reason, we became interested in investigating cationic liposome/lipid-mediated siRNA delivery (siFection) as a meaningful and potentially potent way to facilitate effective functional genomics studies. Accordingly, a number of cationic liposome/lipid-based systems were selected, and their formulation with siRNA was studied, with particular emphasis on formulation parameters most beneficial for siRNA use in functional genomics studies. Cationic liposome/lipid-based systems were selected from a number of commercially available products, including lipofectAMINE2000 and a range of CDAN/DOPE systems formulated from different molar ratios of the cationic cholesterol-based polyamine lipid N(1)-cholesteryloxycarbonyl-3,7-diazanonane-1,9-diamine (CDAN) and the neutral helper lipid dioleoyl-L-alpha-phosphatidylethanolamine (DOPE). Parameters that were been investigated included the lipid:nucleic acid ratio of mixing, the extent of cationic liposome/lipid-nucleic acid complex (lipoplex) formation plus medium used, the lipoplex particle size, the mode of delivery, and dose-response effects. Results suggest that concentrations during siRNA lipoplex (LsiR) formation are crucial for maximum knockdown, but the efficacy of gene silencing is not influenced by the size of LsiR particles. Most significantly, results show that most commercially available cationic liposome/lipid-based systems investigated here mediate a significant nonspecific downregulation of the total cellular protein content at optimal doses for maximal specific gene silencing and knockdown. Furthermore, one pivotal aspect of using siRNA for functional genomics studies is the need for at least minimal cellular toxicity. Results demonstrate that CDAN and DOPE with and without siRNA confer low toxicity to mammalian cells, whereas lipofectAMINE2000 is clearly toxic both as a reagent and after formulation into LsiR particles. Interestingly, LsiR particles formulated from CDAN and DOPE (45:55, m/m; siFECTamine) seem to exhibit a slower cellular uptake than LsiR particles formulated from lipofectAMINE2000. Intracellularly, LsiR particles formulated from CDAN and DOPE systems also appear to behave differently, amassing in distinct but diffuse small nonlysosomal compartments for at least 5 h after siFection. By contrast, LsiR particles formulated from lipofectAMINE2000 accumulate in fewer larger intracellular vesicles.

Apoptosis↗
PubMed2001

The human genome, implications for oral health and diseases, and dental education.

We are living in an extraordinary time in human history punctuated by the convergence of major scientific and technological progress in the physical, chemical, and biological ways of knowing. Equally extraordinary are the sparkling intellectual developments at the interface between fields of study. One major example of an emerging influence on the future of oral health education is at the interface between the human genome, information technology, and biotechnology with miniaturizations (nanotechnology), suggesting new oral health professional competencies for a new century. A great deal has recently been learned from human and non-human genomics. Genome databases are being "mined" to prompt hypothesis-driven "postgenomic" or functional genomic science in microbial models such as Candida albicans related to oral candidiasis and in human genomics related to biological processes found in craniofacial, oral, and dental diseases and disorders. This growing body of knowledge is already providing the gene content of many oral microbial and human genomes and the knowledge of genetic variants or polymorphisms related to disease, disease progression, and disease response to therapeutics (pharmacogenomics). The knowledge base from human and non-human genomics, functional genomics, biotechnology, and associated information technologies is serving to revolutionize oral health promotion, risk assessment using biomarkers and disease prevention, diagnostics, treatments, and the full range of therapeutics for craniofacial, oral, and dental diseases and disorders. Education, training, and research opportunities are already transforming the curriculum and pedagogy for undergraduate science majors, predoctoral health professional programs, residency and specialty programs, and graduate programs within the health professions. In the words of Bob Dylan, "the times they are a-changing."

Biotechnology↗
PubMed2006

Interactions among genomic structure, function, and evolution revealed by comprehensive analysis of the Arabidopsis thaliana genome.

The genome in a higher organism consists of a number of types of nucleotide sequence-specialized components, with each having tens of thousands of members or elements. It is crucial for our understanding of how a genome as an entity is organized, functions, and evolves to determine how these components are organized in the genome and how they relate with each other; however, no such knowledge is available. Here, we report a comprehensive analysis of the organization and interaction of all 40 components constituting the genome of the plant model species, Arabidopsis thaliana, at the whole-genome and chromosome levels. The 40 components include (i) 6 genome structural components consisting of GC%, genes, retrotransposons, DNA transposons, simple repeats, and low complex repeats; (ii) 3 evolutionarily critical features consisting of recombination rate, nucleotide substitutions, and nucleotide insertions/deletions; and (iii) 31 categories of genes with different functions and numbers of functions. We show that the distributions of 39 of the 40 components of the genome (excepting GC%) deviate significantly from the random distribution model and different types of the genome components are significantly correlated. These results remained to be true even when the genomic regions, such as centromeric regions, where transposable and repeat elements are abundant were excluded from the analyses. These findings suggest that DNA molecules contained in the Arabidopsis genome are each organized and structured from their constituting components in an unambiguous manner and that different types of the components that constitute or characterize the genome interact. The analysis also showed that each chromosome consists of a similar set of the components at similar densities, suggesting that the unique organization and interaction pattern of the components in each chromosome may represent, at least in part, the identity of a chromosome or a genome at the genome level, thus partly accounting for the phenotypic variation among different species. The data also provide comprehensive and new insights into many phenomena significant in genome biology, with which we particularly discuss the variation of genetic recombination. The variation of genetic recombination rate along a chromosomal arm is shaped, not only by the distribution of simple repeats, retrotransposons, DNA transposons, and nucleotide substitutions, but also by the functions of genes contained, especially those with multiple functions, suggesting that variation of genetic recombination along a chromosomal arm is the result of interactions among the components constituting local genome structure, function, and evolution.

Arabidopsis↗
PubMed2006

Understanding mouse models of disease through metabolomics.

Metabolomics is widely applicable to a number of fields including toxicology, plant metabolism and functional genomics. In the area of functional genomics, a number of studies have demonstrated the potential of this approach, which combines high-throughput metabolite profiling with computer-assisted pattern recognition approaches. In this review, recent applications of metabolomics to understanding mouse models of disease are considered. This includes studies on the impact of mouse strain on disease models, as well as metabolic profiling of cardiovascular, metabolic and neurodegenerative diseases. This versatile tool is set to increase in popularity as functional genomic approaches produce more mouse models for phenotyping.

Animals↗