Physiological Profiling (26 pages)

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Physiological Profiling



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Physiological Profiling Mathematical Integration of Genotypes Phenotypes Peter J Tonellato Ph D Director Bioinformatics Research Center Medical College of Wisconsin Physiological Profiling A methodology to discover data mining and apply stratification empirical or mechanistic based relationships within or between phenotypes and genetic data Can be equally applied to model organism and human clinical data Acquired Data PostProcess Math Models Genotypes Phenotypes Multivariate Analysis Genome Phenotypes Linked to Genome Derived Phenotype Analysis Physiological Information Physiology Linked to Genome Physiological Profiling Four Steps 1 Collect and maintain functional measures especially for well described genomic backgrounds PhysGen 2 Analyze physiological relationships both empirical and model based approaches 3 Analyze phenotype genetic relationships s a linkage analysis or other predictive modeling 4 Apply stratification cluster identification cluster grouping to detect primary and secondary relationships between measures Physiological Profiling Four Steps 1 Collect and maintain functional measures especially for well described genomic backgrounds PhysGen 2 Analyze physiological relationships both empirical and model based approaches 3 Analyze phenotype genetic relationships s a linkage analysis or other predictive modeling 4 Apply stratification cluster identification cluster grouping to detect primary and secondary relationships between measures Aquired and Derived Phenotypes PUT A RAT PICTURE HERE Acquired Data Phenotype Kidney Weight Kidney Weight ABP 10 15 min MABP 2 min RBF 10 15 min MRBF 2 min MABP RVR RBF BP Recording 4 hr 2 Analyze physiological relationships both empirical and model based approaches Capture first order physiological phenomena e g correlation of paired measures Model development can provide framework for hypothesis development and testing e g first order biochemical network MM Create mechanistic as opposed to empirical relationships between phenotypes e g Model of BP variation 2 Analyze physiological relationships both empirical and model based approaches Capture first order physiological phenomena e g correlation of paired measures GET ONE OF THE SPECIFIC DATA SETS TWO PHENOTYPES Between BN and BN SS 18 and discuss relationship 2 Analyze physiological relationships both empirical and model based approaches Capture first order physiological phenomena e g correlation of paired measures Model development can provide framework for hypothesis development and testing e g first order biochemical network MM Create mechanistic as opposed to empirical relationships between phenotypes e g Model of BP variation 2 Analyze physiological relationships both empirical and model based approaches Capture first order physiological phenomena e g correlation of paired measures Model development can provide framework for hypothesis development and testing e g first order biochemical network MM Create mechanistic as opposed to empirical relationships between phenotypes e g Model of BP variation MAP mmHg MAP from Hypertensive Normal and Subtype seconds Physiological Profiling Four Steps 1 Collect and maintain functional measures especially for well described genomic backgrounds PhysGen 2 Analyze physiological relationships both empirical and model based approaches 3 Analyze phenotype genetic relationships s a linkage analysis or other predictive modeling 4 Apply stratification cluster identification cluster grouping to detect primary and secondary relationships between measures High Salt Blood Pressure BN SS 8 6 mmHg mmHg freq 4 2 seconds 0 25 100 150 200 250 200 250 seconds F2 20 freq 15 mmHg mmHg 10 5 0 seconds 100 150 systolic blood pressure mmHg seconds Rat to Human Model Discovery RAT UniGenes Human QTLs RH G G RH 0 20 13 40 130 60 168 75 4 48 8 155 81 6 159 87 7 248 123 9 189 80 100 152 2 741 251 0 750 272 0 440 120 140 12 116 360 312 619 cM cR GLUE cR cM Human to Rat Model Creation RAT UniGenes Human QTLs G RH G RH 0 20 13 40 130 60 168 75 4 48 8 155 81 6 159 87 7 248 123 9 189 80 100 152 2 741 251 0 750 272 0 440 120 140 12 116 360 312 619 cM cR GLUE cR cM Physiological Profiling Four Steps 1 Collect and maintain functional measures especially for well described genomic backgrounds PhysGen 2 Analyze physiological relationships both empirical and model based approaches 3 Analyze phenotype genetic relationships s a linkage analysis or other predictive modeling 4 Apply stratification cluster identification cluster grouping to detect primary and secondary relationships between measures Brown Norway Colorized correlation matrix of 86 phenotypes Linearly ordered and grouped by prescribed physiological relationships F2 vs Segregated F2 Low responders to salt loading F2 lt 1 1 0 F2 vs Segregated F2 Allele for Salt Sensitive trait Data Mining Interrogate the population to identify subpopulations of interests 1 1 0 F2 vs Segregated F2 heterozygotes Colorized correlation matrix of 86 phenotypes Linearly ordered and grouped by prescribed physiological relationships Data Mining Interrogate the population to identify subpopulations of interests 1 1 0 A B C D E Clusters of BN correlation F G F2 F2 BN SS Phenotypes grouped by BN clusters Conclusions Functional relationships should be fully explored Modeling Empirical Testing and Mapping Combination of analysis to develop integrated perspective Function Structure and interaction Physiological profiling is a discovery process that should lead to hypothesis concerning physiological function and the corresponding genetic basis Acknowledgements Bioinformatics Research Center Simon Twigger Mary Shimoyama Dan Chen Haiping Xia Sam Cheng Roumyana Kirova Zhitao Wang Jed Mathis Dean Pasko Jessica Ginster Peter Long Mike Thomas Wiehong Jin Hai Yu Nan Jiang Nancy Sobczek Dept of Physiology Allen W Cowley Andrew S Greene and A cast of dozens Human and Molecular Genetics Howard Jacob Anne Kwitek Black Yashiro Kita Masahide Shiozawa Ulrich Broeckel Rebecca Majewski Li Guo Marcelo Nobrega Pierre Dumas Sheri Jene Christian Albrechts Universit t Kiel Institut f r Pharmakologie Monika Stoll


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