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Results for “Genomic profiling”

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At least 991 records · Page 55Linked to original sources
PubMed2004

Cross-species comparison of genome-wide expression patterns.

The rapid accumulation of microarray data from multiple species provides unprecedented opportunities to study the evolution of biological systems. Recent studies have used cross-species comparisons of expression profiles to annotate gene functions, to draw evolutionary inferences concerning specific biological processes and to study the global properties of expression networks.

Animals↗
PubMed2001

Genomic strategies to identify mammalian regulatory sequences.

With the continuing accomplishments of the human genome project, high-throughput strategies to identify DNA sequences that are important in mammalian gene regulation are becoming increasingly feasible. In contrast to the historic, labour-intensive, wet-laboratory methods for identifying regulatory sequences, many modern approaches are heavily focused on the computational analysis of large genomic data sets. Data from inter-species genomic sequence comparisons and genome-wide expression profiling, integrated with various computational tools, are poised to contribute to the decoding of genomic sequence and to the identification of those sequences that orchestrate gene regulation. In this review, we highlight several genomic approaches that are being used to identify regulatory sequences in mammalian genomes.

Animals↗
PubMed2026

A chromosome-level genome assembly and developmental transcriptome profiling reveal stage-specific remodeling of the molecular chaperone system in Helicoverpa armigera.

Helicoverpa armigera is one of the most destructive lepidopteran pests worldwide owing to its remarkable polyphagy, long-distance migration, and rapid adaptation to insecticides. Here, we present a chromosome-level genome assembly of H. armigera generated from a field-collected individual in southwestern China, providing a valuable resource for future population genomic and pangenome studies. Developmental transcriptome analyses of first-instar larvae, fifth-instar larvae, and adults identified 6817, 3519, and 5518 differentially expressed genes, respectively, including 797 shared among all developmental transitions. Functional enrichment and co-expression network analyses revealed extensive transcriptional reprogramming, characterized by coordinated regulation of glycolysis, the tricarboxylic acid (TCA) cycle, and fatty acid β-oxidation, indicating dynamic metabolic remodeling during development. Genome-wide analysis identified 77 heat shock protein (HSP) genes belonging to six subfamilies. These genes were unevenly distributed across chromosomes, with HSP20 members exhibiting extensive tandem duplication. Expression profiling revealed pronounced stage specificity, suggesting progressive remodeling of molecular chaperone networks during development. Early larvae primarily relied on HSP40/HSP60/HSP70 and HSP10/HSP60 chaperone systems; fifth-instar larvae exhibited HSP20-centered proteostasis; and adults predominantly expressed HSP40 together with multiple HSP70 members, accompanied by enrichment of stress response and metamorphosis-related functions. This study provides new insights into developmental transcriptional regulation, metabolic remodeling, and stage-specific specialization of molecular chaperone networks in H. armigera, establishing a foundation for future studies of stress adaptation, population genomic variation, and developmental mechanisms.

Cotton bollworm↗
PubMed2006

A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA).

MicroRNAs represent a class of short (approximately 22 nt), noncoding regulatory RNAs involved in development, differentiation, and metabolism. We describe a novel microarray platform for genome-wide profiling of mature miRNAs (miChip) using locked nucleic acid (LNA)-modified capture probes. The biophysical properties of LNA were exploited to design probe sets for uniform, high-affinity hybridizations yielding highly accurate signals able to discriminate between single nucleotide differences and, hence, between closely related miRNA family members. The superior detection sensitivity eliminates the need for RNA size selection and/or amplification. MiChip will greatly simplify miRNA expression profiling of biological and clinical samples.

Animals↗
PubMed2000

Functional analysis of the yeast genome.

Just as Saccharomyces cerevisiae itself provides a model for so many processes essential to eukaryotic life, we anticipate that the methods and the mindset that have moved yeast biological research "beyond the genome" provide a prototype for making similar progress in other organisms. In this review I describe the experimental processes, results and utility of the current large-scale experimental approaches that use genomic data to provide a functional analysis of the yeast genome.

DNA Footprinting↗
PubMed2003

The naturalist in a world of genomics.

Functional genomics provides new opportunities to address issues of fundamental interest in evolutionary biology and suggests many new research directions that are ripe for evolutionary investigation. New types of data, and the ability to study biological processes from a whole genome perspective, are likely to have a profound impact on evolutionary biology and ecology. To illustrate, we discuss how genomewide gene expression studies can be used to reformulate questions about trade-offs and pleiotropy. We then touch on some of the new research opportunities that the application of functional genomics affords to evolutionary biologists. We end with some brief notes about how evolutionary biology and comparative approaches will probably have an impact on functional genomics.

Animals↗
PubMed2004

A rapid method for illustrating features in both coding and non-coding regions of a genome.

A bitmap display of the Fourier spectra has been developed which allows convenient whole chromosome scanning for genes and other features. Use of a limited sliding window gives rapid visualization and localization of coding regions in the chromosomes, as well as non-coding features such as repetitive DNA. The method works particularly well on organisms with a skewed base composition, to provide an overview of genomic features.

Algorithms↗
PubMed2005

Unraveling genomic regulatory networks in the simple chordate, Ciona intestinalis.

The draft genome of the primitive chordate, Ciona intestinalis, was published three years ago. Since then, significant progress has been made in utilizing Ciona's genomic and morphological simplicity to better understand conserved chordate developmental processes. Extensive annotation and sequencing of staged EST libraries make the Ciona genome one of the best annotated among those that are publicly available. The formation of the Ciona tadpole depends on simple, well-defined cellular lineages, and it is possible to trace the lineages of key chordate tissues such as the notochord and neural tube to the fertilized egg. Electroporation methods permit the targeted expression of regulatory genes and signaling molecules in defined cell lineages, as well as the rapid identification of regulatory DNAs underlying cell-specific gene expression. The recent sequencing of a second Ciona genome (C. savignyi) permits the use of simple alignment algorithms for the identification of conserved noncoding sequences, including microRNA genes and enhancers. Detailed expression profiles are now available for almost every gene that encodes a regulatory protein or cell-signaling molecule. The combination of gene-expression profiles, comparative genome analysis, and gene-disruption assays should permit the determination of high-resolution genomic regulatory networks underlying the specification of basic chordate tissues such as the heart, blood, notochord, and neural tube.

Animals↗
PubMed2002

Trends in genomic analysis of the cardiovascular system.

OBJECTIVE: To evaluate the opportunities afforded cardiovascular medicine by the comprehensive and integrative approaches of genomics in cellular physiology. We present a meta-analysis of recently reported results obtained by means of high-throughput technologies (complementary DNA and oligonucleotide arrays, serial analysis of gene expression [SAGE]), as well as more traditional molecular biology approaches (real-time polymerase chain reaction, differential display, and others). DATA SOURCES: Newly published articles identified on PubMed and additional data provided by authors on-line (where available). CONCLUSIONS: The impact of genomic analysis on cardiovascular research is already visible. New genes of cardiovascular interest have been discovered, while a number of known genes have been found to be changed in unexpected contexts. The patterns in the variation of expression of many genes correlate well with the models currently used to explain the pathogenesis of cardiovascular diseases. Much more work has yet to be done, however, for the full exploitation of the immense informative potential still dormant in the genomic technologies.

Cardiovascular Diseases↗
PubMed2003

Phase-independent rhythmic analysis of genome-wide expression patterns.

We introduce a model-based analysis technique for extracting and characterizing rhythmic expression profiles from genome-wide DNA microarray hybridization data. These patterns are clues to discovering rhythmic genes implicated in cell-cycle, circadian, or other biological processes. The algorithm, implemented in a program called RAGE (Rhythmic Analysis of Gene Expression), decouples the problems of estimating a pattern's wavelength and phase. Our algorithm is linear-time in frequency and phase resolution, an improvement over previous quadratic-time approaches. Unlike previous approaches, RAGE uses a true distance metric for measuring expression profile similarity, based on the Hausdorff distance. This results in better clustering of expression profiles for rhythmic analysis. The confidence of each frequency estimate is computed using Z-scores. We demonstrate that RAGE is superior to other techniques on synthetic and actual DNA microarray hybridization data. We also show how to replace the discretized phase search in our method with an exact (combinatorially precise) phase search, resulting in a faster algorithm with no complexity dependence on phase resolution.

Algorithms↗