David Geffen School of Medicine at UCLA
Department of Human Genetics

Speaker Series - Spring Quarter 2010

Mondays, 11am - 12pm, Gonda Building First Floor Conference Room, 1357

Mon, Apr 05
Gene-Environment Interactions in Heart Disease
James Engert, Ph.D., Associate Professor, McGill University Departments of Medicine & Human Genetics, Division of Cardiology
Contact & Intro: Paivi Pajukanta, ext. 72011
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ABSTRACT:

LITERATURE:
  1. Invited Commentary: From Genome-Wide Association Studies to Gene-Environment-Wide Interaction Studies—Challenges and Opportunities. Muin J. Khoury, Sholom Wacholder. American Journal of Epidemiology. Vol. 169, No. 2. November 20, 2008.

  2. Genetic Polymorphisms and the Cardiovascular Risk of Non-Steroidal Anti-Inflammatory Drugs. Christine G. St. Germaine, MSc, Peter Bogaty, MD, Luce Boyer, RN, James Hanley, PhD, James C. Engert, PhD, and James M. Brophy, MD, PhD. The American Journal of Cardiology.

Mon, Apr 12
Human Evolution: Revelations from Next-Generation Sequencing
Rasmus Nielsen, Ph.D., University of Copenhagen and UC Berkeley
Contact & Intro: Marc Suchard, ext 57442
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ABSTRACT: Next-generation sequencing is revolutionizing human genetics by allowing affordable and fast analyses of human genomic variation - but it is also providing new computational and statistical challenges. We have developed a number of tools for analyzing next-generation sequencing data, that takes into account the special nature of this data, including high error rates, missing data, varying coverage, etc. These include tools for statistically valid population genetic analyses of low-coverage data, that explicitly take into account the uncertainty in genotype calling, and new methods for association mapping based on pooled and un-pooled genomes. We have applied the methods in a number of different projects, including the analyses of 200 exomes from a European population, analyses of ancient DNA from 4000 year old human remains from Greenland, and a comparative analysis of exomes of individuals of Tibetan and Han Chinese descent.

Mon, Apr 19
The Mitochondrial Proteome and Human Disease
Vamsi Mootha, M.D., Harvard Medical School, Department of Systems Biology
Contact & Intro: Marc Suchard, ext 57442
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ABSTRACT:

LITERATURE:
  1. Systematic identification of human mitochondrial disease genes through integrative genomics. Sarah Calvo, Mohit Jain, Xiaohui Xie, Sunil A Sheth, Betty Chang, Olga A Goldberger, Antonella Spinazzola, Massimo Zeviani, Steven A Carr, Vamsi K Mootha. Nature Genetics. Vol 38. Number 5. May 2006.

  2. A Mitochondrial Protein Compendium Elucidates Complex I Disease Biology. David J. Pagliarini, Sarah E. Calvo, Betty Chang, Sunil A. Sheth, Scott B. Vafai, Shao-En Ong, Geoffrey A. Walford, Canny Sugiana, Avihu Boneh, William K. Chen, David E. Hill, Marc Vidal, James G. Evans, David R. Thorburn, Steven A. Carr, Vamsi K. Mootha1. Cell. 134. 112–123. July 11, 2008.

Mon, Apr 26
An Enhanced Matching Procedure to Correct for Population Stratification in Case-Control Association Studies
Michael P. Epstein, Ph.D., Associate Professor, Department of Human Genetics, Emory University School of Medicine
Contact & Intro: Paivi Pajukanta, ext. 72011
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ABSTRACT:

LITERATURE:
  1. A Simple and Improved Correction for Population Stratification in Case-Control Studies Michael P. Epstein,* Andrew S. Allen,* and Glen A. Satten. The American Journal of Human Genetics Volume 80 May 2007.

  2. On the Use of General Control Samples for Genome-wide Association Studies: Genetic Matching Highlights Causal Variants. Diana Luca, Steven Ringquist, Lambertus Klei, Ann B. Lee, Christian Gieger, H.-Erich Wichmann, Stefan Schreiber, Michael Krawczak, Ying Lu, Alexis Styche, Bernie Devlin, Kathryn Roeder, and Massimo Trucco. The American Journal of Human Genetics 82, 453–463, February 2008.

Mon, May 03
Population genetics in the personal genome era: implications for personal ancestry reconstruction and multi-ethnic medical genomics
Carlos Bustamante, Stanford University
Contact & Intro: Marc Suchard, ext 57442
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ABSTRACT: Understanding the contribution of rare and common genetic genetic variants to disease susceptibility will likely require multi- and trans-ethnic sequencing studies that compare the genomes of many individuals with and without a particular disease. Of particular importance will be accounting for the role of population stratification at fine scales both in terms of genomic and geographic location. Here, we present results from sequencing, assembly, and genomic analysis of two diploid genomes from Phase 3 HapMap sequenced to ~20X coverage using SoLiD technology. The donor individuals are of Mexican-American and African-American ancestry and represent the first "admixed" genomes to be sequenced to high coverage. We demonstrate that genomic sequencing provides finer resolution of "admixture breakpoints" based on allele frequency estimates from HapMap and TGP. For each admixed genome, we use the distribution of admixture breakpoints to infer the personal admixture history of the sample and patterns of genomic diversity to reconstruct the demographic history of European, African, and Native American continental populations. Furthermore, we compare the distribution of functional and putatively neutral genetic variation among 12 sequenced genomes and find that difference in demographic history may account for statistically significant, differences in distributions of synonymous vs. benign, possibly damaging, and probably damaging non-synonymous coding variants. Finally, we use the SoLiD comparative personal genomic data sets and TGP data to quantify the relative proportions of private, rare, and common functional and neutral genetic within and among populations.

LITERATURE:
  1. Genome-wide patterns of population structure and admixture in West Africans and African Americans. Bryc K, Auton A, Nelson MR, Oksenberg JR, Hauser SL, Williams S, Froment A, Bodo JM, Wambebe C, Tishkoff SA, Bustamante CD. Proc Natl Acad Sci U S A. 2010; 107 (2): 786-91

  2. Global distribution of genomic diversity underscores rich complex history of continental human populations. Auton A, Bryc K, Boyko AR, Lohmueller KE, Novembre J, Reynolds A, Indap A, Wright MH, Degenhardt JD, Gutenkunst RN, King KS, Nelson MR, Bustamante CD. Genome Res. 2009; 19 (5): 795-803

  3. Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data. Gutenkunst RN, Hernandez RD, Williamson SH, Bustamante CD. PLoS Genet. 2009; 5 (10): e1000695

  4. Genes mirror geography within Europe. Novembre J, Johnson T, Bryc K, Kutalik Z, Boyko AR, Auton A, Indap A, King KS, Bergmann S, Nelson MR, Stephens M, Bustamante CD. Nature. 2008; 456 (7218): 98-101

Link to Carlos Bustamante at Stanford

Mon, May 10
Charting the Fate of the 'Good Cholesterol' - Characterization of the HDL receptor SR-BI and its influence on Coronary Heart Disease
Monty Krieger, Ph.D., Whitehead Professor of Biology, Department of Biology, Massachusetts Institute of Technology
Contact & Intro: Paivi Pajukanta, ext. 72011 and Jake Lusis, ext. 51359
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ABSTRACT: Lipoproteins play a critical role in controlling the transport and metabolism of lipids, such as cholesterol. The metabolism of plasma lipoproteins, especially LDL ('bad' cholesterol) and HDL ('good' cholesterol), can profoundly influence atherosclerosis, which is a major cause of coronary heart disease and stroke. The LDL receptor-mediated control of plasma LDL levels has been well-defined by the seminal work of Brown and Goldstein. More recently investigations have established that a distinct receptor for HDL, the scavenger receptor class B type I (SR-BI), plays an important role in controlling HDL metabolism. SR-BI binds HDL tightly and mediates the selective uptake of its lipids into cells. The mechanism of selective lipid uptake is fundamentally different from that of classic receptor-mediated uptake via coated pits and vesicles (e.g., the LDL receptor pathway). Results of analyses of the in vitro mechanism of action and in vivo function of SR-BI will be reviewed.

LITERATURE:
  1. Goldstein JL, Brown MS. The LDL receptor. Arteriosclerosis, Thrombosis, and Vascular Biology. 2009;29:431-438

  2. Krieger M. Scavenger receptor class B type I is a multiligand HDL receptor that influences diverse physiologic systems. J Clin Invest. 2001 Sep;108(6):793-7.

  3. Krieger M, Stern DM. Series introduction: multiligand receptors and human disease. J Clin Invest. 2001 Sep;108(5):645-7.

  4. Kocher O, Krieger M. Role of the adaptor protein PDZK1 in controlling the HDL receptor SR-BI. Curr Opin Lipidol. 2009 Jun;20(3):236-41.

Mon, May 17
Imputation estimators in population genetics partially correct for model misspecification
Vladimir Minin, Assistant Professor, Department of Statistics, University of Washington
Contact & Intro: Marc Suchard, ext 57442
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ABSTRACT: Inference problems with incomplete observations often aim at estimating population properties of

unobserved quantities. For example, when analyzing multilocus genotype data, one is often

interested in estimating frequencies of unobserved phased multilocus genotypes. One simple way to

estimate population properties of missing data is to impute the unobserved

quantities of interest at the individual level and then take an empirical average of the imputed

values. We show that this simple imputation estimator can provide partial protection against model

misspecification. We illustrate imputation estimators' robustness to model specification on

two examples: phasing multilocus genotypes and mixture model-based clustering.

LITERATURE:
  1. V.N. Minin, J.D. O'Brien, and A. Seregin. Empirically corrected estimation of complete-data population summaries under model misspecification, arXiv:0911.0930, 2009. (http://arxiv.org/abs/0911.0930)

  2. J.D. O’Brien, V.N. Minin, and M.A. Suchard. Learning to count: Robust estimates for labeled distances between molecular sequences. Molecular Biology and Evolution, 26:801–814, 2009.

  3. W. Zhai, M. Slatkin, and R. Nielsen. Exploring variation in the dN/dS ratio among sites and lineages using mutational mappings: applications to the influenza virus. Journal of Molecular Evolution, 65:340–348, 2007.

Mon, May 24
Cell Biology of the Lowe Syndrome
R. Claudio Aguilar, Department of Biological Sciences, Purdue University
Contact & Intro: Dell'Angelica, ext 63749
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ABSTRACT: The Lowe syndrome is an X-linked, life-threatening, developmental disease characterized by mental retardation, cataracts and renal failure. Although this human illness has been linked to defective function of the phosphatidylinositol 5-phosphatase, Ocrl1 (Oculo-Cerebro-Renal syndrome of Lowe protein 1), the mechanism by which this enzyme deficiency triggers disease is not clear. Ocrl1 is known to mainly localize to the Golgi apparatus and endosomes, however it translocates to plasma membrane ruffles upon cell stimulation with growth factors. The functional implications of this inducible translocation to the plasma membrane are also unknown. We have recently found that Ocrl1 is required for proper cell migration, spreading and fluid-phase uptake. In agreement with these results, we found that primary fibroblasts from two patients diagnosed with Lowe syndrome displayed similar cellular defects. Importantly, these abnormalities were suppressed by expressing wild-type Ocrl1 but not by a phosphatase-deficient patient mutant. Interestingly, the homologous human PI-5-phosphatase, Inpp5b, considered to be redundant with Ocrl1, was also unable to complement the Ocrl1-dependent cell migration defect. Further, Ocrl1 variants that, like Inpp5b, cannot bind the endocytic adaptor AP2 or clathrin, were less apt to rescue the migration phenotype. However, no defect in membrane recruitment of AP2/clathrin or in transferrin endocytosis by patient cells was detected. As a whole, our results indicate that Ocrl1 deficiency affects cellular processes involving ruffle-mediated membrane remodeling. Because cell movements play a crucial role during embryogenesis, our results provide a novel framework to understand how Ocrl1 defects lead to developmental abnormalities associated with the Lowe syndrome.

LITERATURE:

Coon et al., (2009). Hum. Mol. Gen. 18(23):4478-91.

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