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1.  The GENOTEND chip: a new tool to analyse gene expression in muscles of beef cattle for beef quality prediction 
Previous research programmes have described muscle biochemical traits and gene expression levels associated with beef tenderness. One of our results concerning the DNAJA1 gene (an Hsp40) was patented. This study aims to confirm the relationships previously identified between two gene families (heat shock proteins and energy metabolism) and beef quality.
We developed an Agilent chip with specific probes for bovine muscular genes. More than 3000 genes involved in muscle biology or meat quality were selected from genetic, proteomic or transcriptomic studies, or from scientific publications. As far as possible, several probes were used for each gene (e.g. 17 probes for DNAJA1). RNA from Longissimus thoracis muscle samples was hybridised on the chips. Muscles samples were from four groups of Charolais cattle: two groups of young bulls and two groups of steers slaughtered in two different years. Principal component analysis, simple correlation of gene expression levels with tenderness scores, and then multiple regression analysis provided the means to detect the genes within two families (heat shock proteins and energy metabolism) which were the most associated with beef tenderness. For the 25 Charolais young bulls slaughtered in year 1, expression levels of DNAJA1 and other genes of the HSP family were related to the initial or overall beef tenderness. Similarly, expression levels of genes involved in fat or energy metabolism were related with the initial or overall beef tenderness but in the year 1 and year 2 groups of young bulls only. Generally, the genes individually correlated with tenderness are not consistent across genders and years indicating the strong influence of rearing conditions on muscle characteristics related to beef quality. However, a group of HSP genes, which explained about 40% of the variability in tenderness in the group of 25 young bulls slaughtered in year 1 (considered as the reference group), was validated in the groups of 30 Charolais young bulls slaughtered in year 2, and in the 21 Charolais steers slaughtered in year 1, but not in the group of 19 steers slaughtered in year 2 which differ from the reference group by two factors (gender and year). When the first three groups of animals were analysed together, this subset of genes explained a 4-fold higher proportion of the variability in tenderness than muscle biochemical traits.
This study underlined the relevance of the GENOTEND chip to identify markers of beef quality, mainly by confirming previous results and by detecting other genes of the heat shock family as potential markers of beef quality. However, it was not always possible to extrapolate the relevance of these markers to all animal groups which differ by several factors (such as gender or environmental conditions of production) from the initial population of reference in which these markers were identified.
PMCID: PMC3438070  PMID: 22894653
Predictors; Beef; Tenderness; Array; Gene expression
2.  Use of Gene Expression Profiles of Peripheral Blood Lymphocytes to Distinguish BRCA1 Mutation Carriers in High Risk Breast Cancer Families 
Cancer Informatics  2009;7:41-56.
Mutations in two major genes, BRCA1 and BRCA2, account for up to 30% of families with hereditary breast cancer. Unfortunately, in most families there is little to indicate which gene should be targeted first for mutation screening, which is labor intensive, time consuming and often prohibitively expensive. As BRCA1 is a tumor suppressor gene involved in various cellular processes, heterozygous mutations could deregulate dependent pathways, such as DNA damage response, and disturb transcriptional activity of genes involved in the downstream signaling cascade. We investigated gene expression profiling in peripheral blood lymphocytes to evaluate this strategy for distinguishing BRCA1 mutation carriers from non-carriers. RNA from whole blood samples of 15 BRCA1 mutation carriers and 15 non-carriers from BRCA1 or BRCA2 families were hybridized to Agilent Technologies Whole Human Genome OligoMicroarrays (4 × 44 K multiplex format) containing 41,000 unique human genes and transcripts. Gene expression data were analyzed with Welch’s t-tests and submitted to hierarchical clustering (GeneSpring GX software, Agilent Technologies). Statistical analysis revealed a slight tendency for 133 genes to be differentially expressed between BRCA1 mutation carriers and non-carriers. However, hierarchical clustering of these genes did not accurately discriminate BRCA1 mutation carriers from non-carriers. Expression variation for these genes according to BRCA1 mutation status was weak. In summary, microarray profiling of untreated whole blood does not appear to be informative in identifying breast cancer risk due to BRCA1 mutation.
PMCID: PMC2664702  PMID: 19352458
microarray; gene expression profile; peripheral blood mononuclear cells; hereditary breast cancer; BRCA1; molecular genetic diagnostics

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