Research Article

Related GMR Articles

02/02/2010
Gallus; Gene expression; Skeletal muscle; Tissue-specific expression

Macro- and microarrays are well-established technologies to determine gene functions through repeated measurements of transcript abundance. We constructed a chicken skeletal muscle-associated array based on a muscle-specific EST database, which was used to generate a tissue expression dataset of ~4500 chicken genes across 5 adult tissues (skeletal muscle, heart, liver, brain, and skin). ... more

E.C. Jorge; C.M.R. Melo; M.F. Rosário; J.R.S. Rossi; M.C. Ledur; A.S.A.M.T. Moura; L.L. Coutinho
04/03/2012
Gene expression; Hemi-nested PCR; Indirect immunofluorescence; Sheep

The CD44 family belongs to a larger group of hyaluronic acid-binding proteins and plays important roles in oocyte maturation, fertilization and preimplantational embryo development. We analyzed the CD44 receptor in sheep oocytes and embryos. Immature oocytes (N = 66) were obtained from a local abattoir; mature oocytes (N = 35) and embryos (N = 41) were obtained by laparotomy from adult ... more

J.V. Luz; A.S. Alcântara-Neto; R.I.T.P. Batista; J.M.G. Souza; D.I.A. Teixeira; L.M. Melo; V.J.F. Freitas
10/31/2014
Apis cerana; Gene expression; Transcriptome; Varroa destructor

Varroa destructor is the greatest threat to the honeybee Apis mellifera worldwide, while it rarely causes serious harm to its native host, the Eastern honeybee Apis cerana. The genetic mechanisms underlying the resistance of A. cerana to Varroa remain unclear. Thus, understanding the molecular mechanism of resistance to Varroa may ... more

T. Ji; L. Yin; Z. Liu; F. Shen; J. Shen
10/31/2014
Apis cerana; Gene expression; Transcriptome; Varroa destructor

The Varroa destructor mite has become the greatest threat to Apis mellifera health worldwide, but rarely causes serious damage to its native host Apis cerana. Understanding the resistance mechanisms of eastern bees against Varroa mites will help researchers determine how to protect other species from this organism. The A. cerana genome has not ... more

T. Ji; L. Yin; Z. Liu; Q. Liang; Y. Luo; J. Shen; F. Shen
05/11/2015
Arabidopsis; Gene expression; Glucose; Transcriptome

Sugars acting as fuel energy or as signaling molecules play important roles in plant growth and development. Although sugars associated with early seedling development have been analyzed in detail, few studies have examined the effect of sugar on genome-wide gene transcription. To analyze the role of glucose on the genomic level, we examined the response of seedlings to 5% glucose using ... more

L. Han; J.L. Li; M. Jin; Y.H. Su
03/01/2004
Chromobacterium violaceum; Gene expression; Gene regulation; RNA processing; Transcription; Translation

The repertoire of 4,431 open reading frames (ORFs), eight rRNA operons and 98 tRNA genes of Chromobacterium violaceum must be expressed in a regulated manner for successful adaptation to a wide variety of environmental conditions. To accomplish this feat, the organism relies on protein machineries involved in transcription, RNA processing and translation. Analysis of the C. violaceum ... more

R. Silva; J.R. Araripe; E. Rondinelli; T.P. Ürményi
03/31/2003
Double-stranded RNA (dsRNA); Gene expression; RNA interference; Trypanosoma

Mechanisms controlling gene expression in trypanosomatids depend on several layers of regulation, with most regulatory pathways acting at a post-transcriptional level. Consequently, these parasites can follow the rapid changes associated with transitions between the insect vector and the mammalian host, with instant reprogramming of genetic expression. Using primarily Trypanosoma ... more

S.M.R. Teixeira; W.D. da Rocha
10/04/2007
Clustering; Gene expression; Gene-gene interactions; Supervised learning

We show here an example of the application of a novel method, MUTIC (model utilization-based clustering), used for identifying complex interactions between genes or gene categories based on gene expression data. The method deals with binary categorical data which consist of a set of gene expression profiles divided into two biologically meaningful categories. It does not require data ... more

L.S. Coelho; M.A. Mudado; B. Goertzel; C. Pennachin
10/04/2007
Bioinformatics tool; Comparative genomic hybridization; DNA microarray; Gene expression; Genomic shotgun libraries; Optimal clones

In DNA microarray experiments, the gene fragments that are spotted on the slides are usually obtained by the synthesis of specific oligonucleotides that are able to amplify genes through PCR. Shotgun library sequences are an alternative to synthesis of primers for the study of each gene in the genome. The possibility of putting thousands of gene sequences into a single slide allows the ... more

M.E. Cantão; J.E. Ferreira; E.G.M. Lemos
10/04/2007
Co-regulation; Escherichia coli; Gene expression; Microarray analysis; Partial correlation; Transcriptional regulation

Transcriptional control is an essential regulatory mechanism employed by bacteria. Much about transcriptional regulation remains to be discovered, even for the most widely studied bacterium, Escherichia coli. In the present study, we made a genome-wide low-order partial correlation analysis of E. coli microarray data with the purpose of recovering regulatory ... more

D.F.T. Veiga; F.F.R. Vicente; M. Grivet; A. de la Fuente; A.T.R. Vasconcelos

Pages