Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Genome analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57Linked to original sources
PubMed1993

[Amylase-producing plasma cell dyscrasia. Genomic analysis in a case of intramuscular tumor formation and a review of the literature].

We describe a 53-year-old male patient with multiple myeloma (IgA, kappa) who showed massive intramuscular tumors and hyperamylasemia of the salivary (S) type 10 months after initial diagnosis. Suspension culture of the abnormal plasma cells in the pleural fluid showed the production of S-amylase, which was confirmed by the expression of S-amylase mRNA comigrating with salivary gland mRNA. Cytogenetic analysis of the cells showed common abnormalities 1p+q-and 8q+. They expressed IL-6 mRNA, but not c-myc mRNA. Neither structural abnormality nor amplification was detected in the alleles of S amylase, and c-myc using Southern blot analysis. All of the eight patients with plasma cell dyscrasia with hyperamylasemia reported so far (including the present one) are Japanese, and showed S-type hyperamylasemia and extramedullary tumor formation at initial diagnosis or during the course of the disease. All of the four patients in whom cytogenetic analysis was performed had structural abnormalities of chromosome 1, on which the S-amylase gene is known to be located, although the break point were variable.

Amylases↗
PubMed1995

[Genome analysis and health insurance].

In spite of the public opinion that believes genetic testing to be a preferred method of risk assessment before concluding an insurance contract, private medical expenses insurers in Germany do not make any use of this screening procedure. The scrutiny of insurance proposals is restricted to the assessment of the state of health at the moment of underwriting without the proposer having to submit to any medical tests at all. The coverage of presently unknown, i.e. potential, risks, on the contrary, is subject of the health insurance contract. Idea and technique of health insurance business would be contradicted by assessing each individual risk until the prospective damage will be known and charged with the commensurate premium. If an individual has had a specific genetic testing, though, the results of these tests are to be considered in the same way as other medical tests and will need to be declared on proposal forms.

Genetic Diseases, Inborn↗
PubMed1993

[Diagnostic clue and genomic analysis of LDH-M subunit deficiency].

Lactate dehydrogenase (LDH) M(A) subunit deficiency was first discovered by urinary discoloration and a discrepancy of laboratory data. Since then, five other families with this disorder have been reported in the Japanese population. The response of pyruvate concentration after forearm ischemic work is specific for LDH-M subunit deficiency. During strenuous exercise ATP production is significantly impaired and muscle tissue is damaged. A genetic study revealed a deletion of 20 base-pairs in exon 6 of the LDH-M gene in four families that were homozygous and one family that was heterozygous for LDH-M subunit deficiency. This mutation results in a frame-shift translation and premature termination. In addition to this mutation, we found a nonsense mutation at codon 328 in exon 7 in an individual heterozygous for LDH-M subunit deficiency, and a deletion of 3 base-pairs, TGT at codon 127 in exon 3 in a proposita who was homozygous and in her parents who were heterozygous for LDH-M subunit deficiency in the fifth family. Therefore, molecular heterogeneities were revealed in genetic mutations of LDH-M subunit deficiency.

Adolescent↗
PubMedDate not supplied

[Computer searching of new targets for antimicrobial drugs based on comparative analysis of genomes].

The progress in genome research allows to use genomic databases for drug discovery. The major interest consists in their usage for searching of new molecular targets for new drugs. It is especially important in the area of new antimicrobial drugs creation. In recent years, the applicability of genome analysis for solution of this problem was shown by different authors. We propose an approach for searching new targets for antimicrobial drugs based upon comparative analysis of genomes and samples from molecular databases. For each protein encoded by the target microorganism genome the conformance to a number of medico-biological and technological requirements was tested. The obtained evaluations were used for selection of potential targets. The approach was implemented in the original software GenMesh. It was successfully tested with known targets of drugs against tuberculosis when correct valuations were obtained. The attempt of new targets selection for design of new drugs against tuberculosis was done with reliable results.

Anti-Infective Agents↗
PubMed2004

Gene expression microarray analysis and genome databases facilitate the characterization of a chromosome 22 derived homogeneously staining region.

Karyotype and fluorescence in situ hybridization (FISH) analyses previously identified a homogeneously staining region (HSR) derived from chromosome 22 in OV90, an epithelial ovarian cancer (EOC) cell line. Affymetrix expression microarrays in combination with the UniGene and Human Genome Browser databases were used to identify the candidate genes comprising the amplicon of the HSR, based on comparison of expression profiles of OV90, EOC cell lines lacking HSRs and primary cultures of normal ovarian surface epithelial (NOSE) cells. A group of probe sets displaying a minimum 3-fold overexpression with a high reliability score (P-call) in OV90 were identified which represented genes that mapped within a 1-2 Mb interval on chromosome 22. A large number of probe sets, some of which represent the same genes, displayed no evidence of overexpression and/or low reliability scores (A-call). An investigation of the probe set sequences with the Affymetrix and Sanger Institute Chromosome 22 Group databases revealed that some of the probe sets displaying discordant results for the same gene were complementary to intronic sequences and/or the antisense strand. Microarray results were validated by RT-PCR. Genomic analysis suggests that the HSR was derived from the amplification of a 1.1 Mb interval defined by the chromosomal map positions of ZNF74 and Hs.372662, at 22q11.21. The deduced amplicon is derived from a complex region of chromosome 22 that harbors low-copy repeats (LCRs). The amplicon contains 18 genes as likely targets for gene amplification. This study illustrates that large-scale expression microarray analysis in combination with genome databases is sufficient for deducing target genes associated with amplicons and stresses the importance of investigating probe set design before engaging in validation studies.

Cell Line, Tumor↗
PubMed2006

SIGMA: a system for integrative genomic microarray analysis of cancer genomes.

BACKGROUND: The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. RESULTS: We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. CONCLUSION: In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA) of cancer genomes, can be accessed at http://sigma.bccrc.ca.

Adenocarcinoma↗
PubMed2005

A model of the statistical power of comparative genome sequence analysis.

Comparative genome sequence analysis is powerful, but sequencing genomes is expensive. It is desirable to be able to predict how many genomes are needed for comparative genomics, and at what evolutionary distances. Here I describe a simple mathematical model for the common problem of identifying conserved sequences. The model leads to some useful rules of thumb. For a given evolutionary distance, the number of comparative genomes needed for a constant level of statistical stringency in identifying conserved regions scales inversely with the size of the conserved feature to be detected. At short evolutionary distances, the number of comparative genomes required also scales inversely with distance. These scaling behaviors provide some intuition for future comparative genome sequencing needs, such as the proposed use of "phylogenetic shadowing" methods using closely related comparative genomes, and the feasibility of high-resolution detection of small conserved features.

Animals↗
PubMed2003

A novel complexity measure for comparative analysis of protein sequences from complete genomes.

Analysis of sequence complexities of proteins is an important step in the characterization and classification of new genomes. A new measure has been proposed to compute sequence complexity in protein sequences based on linguistic complexity. The algorithm requires a single parameter, is computationally simple and provides a framework for comparative genomic analysis. Protein sequences were classified into groups of high or low complexity based on a quantitative measure termed F(c), which is proportional to the fraction of low complexity sequence present in the protein. The algorithm was tested on sequences of 196 non-homologous proteins whose crystal structures are available at </=2.0 A resolution. Protein sequences of high complexity had 'globular' structures (95% agreement), whereas those of low complexity had non-globular structures (80% agreement). Application of this measure to proteins of unknown structure/function from different genomes revealed that the sequences of high complexity constitute the majority in all genomes (about 90% in Archaea, about 93% in Eubacteria, 89% in Saccharomyces cerevisiae and 90% in Caenorhabditis elegans). Aeropyrum pernix among Archaeae and Deinococcus radiodurans among Eubacteria have the lowest fraction of high complexity proteins (75% and 80% respectively). Further, it was observed that a few bacterial pathogens (Mycobacterium tuberculosis, Pseudomonas aeruginosa) have high fraction of low complexity proteins. The program ScanCom is available from the authors as a PERL script (UNIX system).

Algorithms↗
PubMed2006

Osteoarthritis susceptibility loci defined by genome scan meta-analysis.

Genome scans for osteoarthritis (OA) have yielded inconsistent results. The absence of replication of linkage might be due to the lack of power of individual studies. A meta-analysis of published data was performed to assess evidence for linkage of OA across genome scan studies. Three OA whole-genome scans including 893 families with 3,000 affected individuals were used for genome scan meta-analysis (GSMA). A total of five bins lie above 95% confidence level (P=0.05) and one bin is above 99% confidence level (P=0.01) in OA GSMA; bins 7.6 (7q34-7q36.3, P (sumrnk) =0.0035), 11.3 (11p12-11q13.4), 6.3 (6p21.1-6q15), 2.8 (2q31.1-2q34) and 15.3 (15q21.3-15q26.1). The highest summed bin was bins 7.6. In conclusion, the OA GSMA has shown that chromosome 7q34-7q36.3 have the highest summed rank and four additional loci with significant summed ranks across studies.

Chromosomes, Human, Pair 7↗
PubMed2006

Osteoarthritis susceptibility loci defined by genome scan meta-analysis.

Genome scans for osteoarthritis (OA) have yielded inconsistent results. The absence of replication of linkage might be due to lack of power of individual studies. A meta-analysis of the published data was performed to assess evidence for linkage of OA across genome scan studies. Three OA whole-genome scans including 893 families with 3,000 affected individuals were used for genome scan meta-analysis (GSMA). A total of 5 bins lie above 95% confidence level (P = 0.05) and 1 bin is above 99% confidence level (P = 0.01) in OA GSMA; bins 7.6 (7q34-7q36.3, Psumrnk = 0.0035), 11.3 (11p12-11q13.4), 6.3 (6p21.1-6q15), 2.8 (2q31.1-2q34) and 15.3 (15q21.3-15q26.1). The highest summed rank was observed at bin 7.6. In conclusion, the OA GSMA has shown chromosome 7q34-7q36.3 with the highest summed rank and four additional loci with significant summed ranks across studies.

Chromosomes, Human, Pair 7↗
PubMed2004

The complete nucleotide sequence and multipartite organization of the tobacco mitochondrial genome: comparative analysis of mitochondrial genomes in higher plants.

Tobacco is a valuable model system for investigating the origin of mitochondrial DNA (mtDNA) in amphidiploid plants and studying the genetic interaction between mitochondria and chloroplasts in the various functions of the plant cell. As a first step, we have determined the complete mtDNA sequence of Nicotiana tabacum. The mtDNA of N. tabacum can be assumed to be a master circle (MC) of 430,597 bp. Sequence comparison of a large number of clones revealed that there are four classes of boundaries derived from homologous recombination, which leads to a multipartite organization with two MCs and six subgenomic circles. The mtDNA of N. tabacum contains 36 protein-coding genes, three ribosomal RNA genes and 21 tRNA genes. Among the first class, we identified the genes rps1 and psirps14, which had previously been thought to be absent in tobacco mtDNA on the basis of Southern analysis. Tobacco mtDNA was compared with those of Arabidopsis thaliana, Beta vulgaris, Oryza sativa and Brassica napus. Since repeated sequences show no homology to each other among the five angiosperms, it can be supposed that these were independently acquired by each species during the evolution of angiosperms. The gene order and the sequences of intergenic spacers in mtDNA also differ widely among the five angiosperms, indicating multiple reorganizations of genome structure during the evolution of higher plants. Among the conserved genes, the same potential conserved nonanucleotide-motif-type promoter could only be postulated for rrn18-rrn5 in four of the dicotyledonous plants, suggesting that a coding sequence does not necessarily move with the promoter upon reorganization of the mitochondrial genome.

Base Sequence↗
PubMed2006

GRAST: a new way of genome reduction analysis using comparative genomics.

MOTIVATION: Establishment of intra-cellular life involved a profound re-configuration of the genetic characteristics of bacteria, including genome reduction and rearrangements. Understanding the mechanisms underlying these phenomena will shed light on the genome rearrangements essential for the development of an intra-cellular lifestyle. Comparison of genomes with differences in their sizes poses statistical as well as computational problems. Little efforts have been made to develop flexible computational tools with which to analyse genome reduction and rearrangements. RESULTS: Investigation of genome reduction and rearrangements in endosymbionts using a novel computational tool (GRAST) identified gathering of genes with similar functions. Conserved clusters of functionally related genes (CGSCs) were detected. Heterogeneous gene and gene cluster non-functionalization/loss are identified between genome regions, functional gene categories and during evolution. Results show that gene non-functionalisation has accelerated during the last 50 MY of Buchnera's evolution while CGSCs have been static.

Algorithms↗
PubMed2004

Mapping DNA-protein interactions in large genomes by sequence tag analysis of genomic enrichment.

Identifying the chromosomal targets of transcription factors is important for reconstructing the transcriptional regulatory networks underlying global gene expression programs. We have developed an unbiased genomic method called sequence tag analysis of genomic enrichment (STAGE) to identify the direct binding targets of transcription factors in vivo. STAGE is based on high-throughput sequencing of concatemerized tags derived from target DNA enriched by chromatin immunoprecipitation. We first used STAGE in yeast to confirm that RNA polymerase III genes are the most prominent targets of the TATA-box binding protein. We optimized the STAGE protocol and developed analysis methods to allow the identification of transcription factor targets in human cells. We used STAGE to identify several previously unknown binding targets of human transcription factor E2F4 that we independently validated by promoter-specific PCR and microarray hybridization. STAGE provides a means of identifying the chromosomal targets of DNA-associated proteins in any sequenced genome.

Cells, Cultured↗
PubMed2006

Development of computations in bioscience and bioinformatics and its application: review of the Symposium of Computations in Bioinformatics and Bioscience (SCBB06).

The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21-22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.

Biological Science Disciplines↗
PubMed1996

Anoxygenic phototrophy across the phylogenetic spectrum: current understanding and future perspectives

The phylogenetic heterogeneity of anoxygenic phototrophic bacteria has been revealed by 16S rRNA sequence analysis, the results of which have led to extensive taxonomic rearrangements within previously defined taxa of phototrophs and stimulated interest in this group of organisms. Anoxygenic photosynthetic bacteria can be found within 4 of the 12 phylogenetic lineages, and in some cases are highly related to non-photosynthetic members of these groups. The largest number of phototrophs are found in the class Proteobacteria. Comparative phylogenetic analysis using 23S rDNA sequences generally supports the topology obtained from 16S rDNA sequences. The photosynthetic reaction centers are conserved in all photosynthetic bacteria, and are of two types. One is shared by the Proteobacteria and Chloroflexus aurantiacus and is similar to Photosystem II of cyanobacteria, while heliobacteria and Chlorobium and relatives possess a reaction center similar to the cyanobacterial Photosystem I. These similarities are supported by sequence analysis of core reaction center peptides, but contradict phylogenies reconstructed from rRNA sequence analysis. Genome analysis by means of physical mapping has been performed for only three species of anoxygenic phototrophs. Some conservation of operon structure and gene sequence has been found within the Proteobacteria, but does not extend to other phototrophs.

Journal Article↗