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Genome-wide Level (genome-wide + level)
Selected AbstractsGenome-wide association analyses of quantitative traits: the GAW16 experienceGENETIC EPIDEMIOLOGY, Issue S1 2009Saurabh GhoshArticle first published online: 18 NOV 200 Abstract The group that formed on the theme of genome-wide association analyses of quantitative traits (Group 2) in the Genetic Analysis Workshop 16 comprised eight sets of investigators. Three data sets were available: one on autoantibodies related to rheumatoid arthritis provided by the North American Rheumatoid Arthritis Consortium; the second on anthropometric, lipid, and biochemical measures provided by the Framingham Heart Study (FHS); and the third a simulated data set modeled after FHS. The different investigators in the group addressed a large set of statistical challenges and applied a wide spectrum of association methods in analyzing quantitative traits at the genome-wide level. While some previously reported genes were validated, some novel chromosomal regions provided significant evidence of association in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect association. Genet. Epidemiol. 33 (Suppl. 1):S13,S18, 2009. © 2009 Wiley-Liss, Inc. [source] From sextant to GPS: Twenty-five years of mapping the genome with ChIPJOURNAL OF CELLULAR BIOCHEMISTRY, Issue 1 2009David A. Wacker Abstract Since its inception, ChIP technology has evolved immensely. Technological advances have improved its specificity and sensitivity, its scale has expanded to a genome-wide level, and its relative ease of use has made it a virtually ubiquitous tool. This year marks the 25th anniversary of the development of ChIP. In honor of this milestone, we briefly revisit its history, offer a review of recent articles employing ChIP on a genome-wide scale, and lay out our views for the future of ChIP. J. Cell. Biochem. 107: 6,10, 2009. © 2009 Wiley-Liss, Inc. [source] Heritabilities and quantitative trait loci for blood gases and blood pH in swineANIMAL GENETICS, Issue 2 2009G. Reiner Summary Maintaining pH and blood gases in a narrow range is essential to sustain normal biochemical reactions. Decreased oxygenation, poor tissue perfusion, disturbance to CO2 expiration, and shortage of HCO3, can lead to metabolic acidosis. This is a common situation in swine, and originates from a broad range of medical conditions. pH and blood gases appear to be under genetic control, and populations with physiological traits closer to the pathological thresholds may be more susceptible to developing pathological conditions. However, little is known about the genetic basis of such traits. We have therefore estimated phenotypic and genetic variability and identified quantitative trait loci (QTL) for pH and blood gases in blood samples from 139 F2 pigs from the Meishan/Pietrain family. Samples were taken before and after challenge with Sarcocystis miescheriana, a protozoan parasite of muscle. Twenty-seven QTL influencing pH and blood gases were identified on nine chromosomes. Five of the QTL were significant on a genome-wide level; 22 QTL were significant on a chromosome-wide level. QTL for pH-associated traits have been mapped to SSC3, 18 and X. QTL associated with CO2 have been detected on SSC6, 7, 8 and 9, and QTL associated with O2 on SSC2 and SSC8. QTL showed specific health/disease patterns that were related to the physiological state of the pigs from day 0, to acute disease (day 14), convalescence (day 28) and chronic disease (day 42). The results demonstrate that pH and blood gases are influenced by multiple chromosomal areas, each with relatively small effects. [source] Mapping of quantitative trait loci for clinical,chemical traits in swineANIMAL GENETICS, Issue 1 2009G. Reiner Summary Clinical,chemical traits are diagnostic parameters essential for characterization of health and disease in veterinary practice. The traits show significant variability and are under genetic control, but little is known about the fundamental genetic architecture of this variability, especially in swine. We have identified QTL for alkaline phosphatase (ALP), lactate (LAC), bilirubin (BIL), creatinine (CRE) and ionized sodium (Na+), potassium (K+) and calcium (Ca++) from the serum of 139 F2 pigs from a Meishan/Pietrain family before and after challenge with Sarcocystis miescheriana, a protozoan parasite of muscle. After infection, the pigs passed through three stages representing acute disease, subclinical disease and chronic disease. Forty-two QTL influencing clinical,chemical traits during these different stages were identified on 15 chromosomes. Eleven of the QTL were significant on a genome-wide level; 31 QTL were chromosome-wide significant. QTL showed specific health/disease patterns with respect to the baseline values of the traits as well as the values obtained through the different stages of disease. QTL influencing different traits at different times were found primarily on chromosomes 1, 3, 7 and 14. The most prominent QTL for the investigated clinical,chemical traits mapped to SSC3 and 7. Baseline traits of ALP, LAC, BIL, Ca++ and K+ were influenced by QTL regions on SSC3, 6, 7, 8 and 13. Single QTL explained up to 21.7% of F2 phenotypic variance. Our analysis confirms that variation of clinical,chemical traits is associated with multiple chromosomal regions. [source] Genome-wide genetic diversity of Holstein Friesian cattle reveals new insights into Australian and global population variability, including impact of selectionANIMAL GENETICS, Issue 1 2007K. R. Zenger Summary Past breeding strategies for dairy cattle have been very effective in producing rapid genetic gain to achieve industry targets and raise profitability. Such gains have been largely facilitated by intense selection of sires combined with the use of artificial insemination. However, this practice can potentially limit the level of genetic diversity through inbreeding and selection plateaus. The rate of inbreeding in Australia is increasing, primarily as a result of semen importation from a small number of prominent bulls from the USA. The effect of this genetic influx in the Australian dairy cattle population is poorly understood both in terms of diversity and local adaptation/divergence. This study uses 845 genome-wide SNP genetic markers and 431 bulls to characterize the level of genetic diversity and genetic divergence within the Australian and international Holstein Friesian dairy population. No significant differences in genetic diversity (as measured by heterozygosity [Ho] and allelic richness [A]) were observed over the 25-year time period (1975,1999) for bulls used in Australia. The importation of foreign semen into Australia has increased the effective population size until it was in effect a sub-sample of the global population. Our data indicate that most individuals are equally closely related to one another, regardless of country of origin and year of birth. In effect, the global population can be considered as one single population unit. These results indicate that inbreeding, genetic drift and selection has had little effect at reducing genetic diversity and differentiating the Australian Holstein Friesian population at a genome-wide level. [source] Identifying Modifier Loci in Existing Genome Scan DataANNALS OF HUMAN GENETICS, Issue 5 2008E. W. Daw Summary In many genetic disorders in which a primary disease-causing locus has been identified, evidence exists for additional trait variation due to genetic factors. These findings have led to studies seeking secondary ,modifier' loci. Identification of modifier loci provides insight into disease mechanisms and may provide additional screening and treatment targets. We believe that modifier loci can be identified by re-analysis of genome screen data while controlling for primary locus effects. To test this hypothesis, we simulated multiple replicates of typical genome screening data on to two real family structures from a study of hypertrophic cardiomyopathy. With this marker data, we simulated two trait models with characteristics similar to one measure of hypertrophic cardiomyopathy. Both trait models included 3 genes. In the first, the trait was influenced by a primary gene, a secondary ,modifier' gene, and a third very small effect gene. In the second, we modeled an interaction between the first two genes. We examined power and false positive rates to map the secondary locus while controlling for the effect of the primary locus with two types of analyses. First, we examined Monte Carlo Markov chain (MCMC) simultaneous segregation and linkage analysis as implemented in Loki, for which we calculated two scoring statistics. Second, we calculated LOD scores using an individual-specific liability class based on the quantitative trait value. We found that both methods produced scores that are significant on a genome-wide level in some replicates. We conclude that mapping of modifier loci in existing samples is possible with these methods. [source] Searching for the regulators of human gene expressionBIOESSAYS, Issue 10 2006Julian T. Forton Many common human traits are believed to be a composite reflection of multiple genetic and non-genetic factors and the genetic contribution is consequently often difficult to characterise. Recent advances suggest that subtle variation in the regulation of gene expression may contribute to complex human traits. In two reports,1,2 Cheung and colleagues scale up human genetics analysis to an impressive level in a genome-wide search for the regulators of gene expression. They perform linkage analysis on expression profiles for over 3,500 genes and then employ the HapMap resource3 to take positive findings through to association studies at the genome-wide level. This work gives new insights into the complexities of gene regulation and the plausibility of genome-wide study design. BioEssays 28: 968,972, 2006. © 2006 Wiley Periodicals, Inc. [source] | ||||||||||