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Highest Significance (highest + significance)
Selected AbstractsQuantitative trait loci associated with AutoFOM grading characteristics, carcass cuts and chemical body composition during growth of Sus scrofaANIMAL GENETICS, Issue 5 2006M. Mohrmann Summary A three-generation full-sib resource family was constructed by crossing two commercial pig lines. Genotypes for 37 molecular markers covering chromosomes SSC1, SSC6, SSC7 and SSC13 were obtained for 315 F2 animals of 49 families and their parents and grandparents. Phenotypic records of traits including carcass characteristics measured by the AutoFOM grading system, dissected carcass cuts and meat quality characteristics were recorded at 140 kg slaughter weight. Furthermore, phenotypic records on live animals were obtained for chemical composition of the empty body, protein and lipid accretion (determined by the deuterium dilution technique), daily gain and feed intake during the course of growth from 30 to 140 kg body weight. Quantitative trait loci (QTL) detection was conducted using least-squares regression interval mapping. Highest significance at the 0.1% chromosome-wise level was obtained for five QTL: AutoFOM belly weight on SSC1; ham lean-meat weight, percentage of fat of primal cuts and daily feed intake between 60 and 90 kg live weight on SSC6; and loin lean-meat weight on SSC13. QTL affecting daily gain and protein accretion were found on SSC1 in the same region. QTL for protein and lipid content of empty body at 60 kg liveweight were located close to the ryanodine receptor 1 (RYR1) locus on SSC6. On SSC13, significant QTL for protein accretion and feed conversion ratio were detected during growth from 60 to 90 kg. In general, additive genetic effects of alleles originating from the Piétrain line were associated with lower fatness and larger muscularity as well as lower daily gain and lower protein accretion rates. Most of the QTL for carcass characteristics were found on SSC6 and were estimated after adjustment for the RYR1 gene. QTL for carcass traits, fatness and growth on SSC7 reported in the literature, mainly detected in crosses of commercial lines × obese breeds, were not obtained in the present study using crosses of only commercial lines, suggesting that these QTL are not segregating in the analysed commercial lines. [source] Association of Molecular Variants, Haplotypes, and Linkage Disequilibrium Within the Human Vitamin D-Binding Protein (DBP) Gene With Postmenopausal Bone Mineral Density,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 9 2003Yoichi Ezura Abstract Possible contribution of vitamin D-binding protein (DBP) gene for determination of BMD was tested by characterizing 13 SNPs in 384 adult Japanese women. When the effect of a specific single SNP was tested, five SNPs (,39C>T, IVS1+827C>T, IVS1+1916C>T, IVS1-1154A>G, and IVS11+1097G>C) correlated with BMD significantly at various levels. The chromosomal dosage of one haplotype (T-C-C-G-T-C in ,39C>T, IVS1+827C>T, IVS1+1916C>T, IVS1-1154A>G, D432E, and IVS11+1097G>C) displayed significant correlation with adjusted radial BMD (r = 0.15, p = 0.008; n = 331). Multiple regression analyses revealed a most significant correlation with the combination of IVS1+827C>T and D432E (r2 = 0.029, p = 0.005). These results indicate a complex combined effect of several SNPs within the DBP gene that might underlie susceptibility to low radial BMD and osteoporosis. Introduction: Osteoporosis results from the interplay of multiple environmental and genetic determinants. The gene encoding vitamin D-binding protein (DBP), a key factor for regulating calcium homeostasis through the vitamin D endocrine system, is a probable candidate for conferring susceptibility to osteoporosis. Methods: To test a possible contribution of the DBP gene for determination of bone mineral density (BMD) of adult women, we have characterized 13 single nucleotide polymorphisms (SNPs) within the DBP gene in DNA from 384 adult Japanese women and attempted to correlate specific SNPs with BMD. Results and Conclusions: Sixteen major haplotypes accounted for 80% of the variations, indicating allelic complexity in this genomic region. Pairwise linkage disequilibrium (LD), measured by the D, and r2 statistics, demonstrated a general pattern of decline with increasing distance, but individual LD values within small genomic segments were diverse. Regression analysis for adjusted BMD revealed significant correlation with respect to five of them (,39C>T, IVS1+827C>T, IVS1+1916C>T, IVS1-1154A>G, and IVS11+1097G>C) at various levels. An intronic SNP (IVS11+1097G>C) with the highest significance of association (p = 0.006) showed significant LD with four SNPs located around the first exon (r2 values >0.18, D, > 0.5). A non-synonymous coding SNP, D432E, showed a comparable level of correlation, but it was in a moderate LD only with IVS11+1097G>C. The chromosomal dosage of one haplotype (T-C-C-G-T-C in ,39C>T, IVS1+827C>T, IVS1+1916C>T, IVS1-1154A>G, D432E and IVS11+1097G>C) estimated in each subject displayed significant correlation with adjusted radial BMD (r = 0.15, p = 0.008; n = 331). Furthermore, multiple regression analyses revealed that the most significant correlation was achieved for the combination of IVS1+827C>T and D432E (r2 = 0.029, p = 0.005). These results indicate a complex combined effect of several SNPs within the DBP gene that might underlie susceptibility to low radial BMD and osteoporosis. [source] A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humansPROTEOMICS - CLINICAL APPLICATIONS, Issue 8 2009Joshua Boateng Abstract An integrated MS-based proteomic approach is described that combines MALDI-MS and LC-MS with artificial neural networks for the identification of protein and peptide biomarkers associated with recombinant human growth hormone (rhGH) administration. Serum from exercised males administered with rhGH or placebo was analysed using ELISA to determine insulin-like growth factor-I concentrations. Diluted serum from rhGH- and placebo-treated subjects was analysed for protein biomarkers by MALDI-MS, whereas LC-MS was used to analyse tryptically digested ACN-depleted serum extracts for peptide biomarkers. Ion intensities and m/z values were used as inputs to artificial neural networks to classify samples into rhGH- and placebo-treated groups. Six protein ions (MALDI-MS) correctly classified 96% of samples into their respective groups, with a sensitivity of 91% (20 of 22 rhGH treated) and specificity of 100% (24 of 24 controls). Six peptide ions (LC-MS) were also identified and correctly classified 93% of samples with a sensitivity of 90% (19 of 21 rhGH treated) and a specificity of 95% (20 of 21 controls). The peptide biomarker ion with the highest significance was sequenced using LC-MS/MS and database searching and found to be associated with leucine-rich ,-2-glycoprotein. [source] Gene profiling and pathway analysis of neuroendocrine transdifferentiated prostate cancer cellsTHE PROSTATE, Issue 1 2009Ryutaro Mori Abstract BACKGROUND Neuroendocrine (NE) cells are present in both normal prostate and prostate cancer. In addition, NE differentiation can be induced by various factors, such as IL-6, in vitro and in vivo. However, the mechanism of this differentiation and the role of NE cells in prostate cancer are not well understood. In this study, we evaluated the gene expression and analyzed the pathways in prostate cancer cells exposed to various NE differentiation inducing factors in vitro. METHODS Gene expression signatures between control LNCaP cells and each treatment induced NE cell line were compared using Affymetrix GeneChip with network and pathway analysis. RESULTS All treatments were able to transdifferentiate LNCaP cells into NE phenotype as shown by morphology changes and NE marker measurements. Of the 54,675 oligonucleotide-based probe sets in microarray, 44,975 were mapped into the Ingenuity Pathway Analysis database and were filtered according to the t -test P value. At P,<,0.002, the number of genes that were differentially expressed included 302 of the IL-6 treated cells, 201 of genistein, 233 of epinephrine, and 191 of the charcoal stripped serum ones. A pooled data approach also showed 346 differentially expressed genes at the same P value. Gene ontology analysis showed that cancer-related function had the highest significance. CONCLUSIONS Despite some overlap, each NE transdifferentiation inducing treatment was associated with a changed expression of a unique set of genes, and such gene profiling may help to elucidate the molecular mechanisms involved in NE transdifferentiation of prostate cancer cells. Prostate 69: 12,23, 2009. © 2008 Wiley,Liss, Inc. [source] A genome-wide scan for signatures of recent selection in Holstein cattleANIMAL GENETICS, Issue 4 2010S. Qanbari Summary The data from the newly available 50 K SNP chip was used for tagging the genome-wide footprints of positive selection in Holstein,Friesian cattle. For this purpose, we employed the recently described Extended Haplotype Homozygosity test, which detects selection by measuring the characteristics of haplotypes within a single population. To assess formally the significance of these results, we compared the combination of frequency and the Relative Extended Haplotype Homozygosity value of each core haplotype with equally frequent haplotypes across the genome. A subset of the putative regions showing the highest significance in the genome-wide EHH tests was mapped. We annotated genes to identify possible influence they have in beneficial traits by using the Gene Ontology database. A panel of genes, including FABP3, CLPN3, SPERT, HTR2A5, ABCE1, BMP4 and PTGER2, was detected, which overlapped with the most extreme P -values. This panel comprises some interesting candidate genes and QTL, representing a broad range of economically important traits such as milk yield and composition, as well as reproductive and behavioural traits. We also report high values of linkage disequilibrium and a slower decay of haplotype homozygosity for some candidate regions harbouring major genes related to dairy quality. The results of this study provide a genome-wide map of selection footprints in the Holstein genome, and can be used to better understand the mechanisms of selection in dairy cattle breeding. [source] | |||||||||||||