David Geffen School of Medicine at UCLA
Department of Human Genetics

Speaker Series - Spring Quarter 2011

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

Mon, Apr 04
Ancient DNA Reveals Frequent Hybridization Between Brown Bears and Polar Bears Throughout the Last 100,000 Years
Beth Shapiro, Ph.D., Shaffer Assistant Professor of Biology, Department of Biology, The Pennsylvania State University
Contact & Intro: Marc Suchard, x57442 & msuchard@ucla.edu
Mon, Apr 11
Massively Parallel Sequencing as a Clinical Research Tool: Hypothesis Testing and Hypothesis Generating Approaches to Clinical Genomics
Les G. Biesecker , M.D., Senior Investigator and Chief, Genetic Disease Research Branch and Director of the Physician Scientist Development Program, National Human Genome Research Institute
Contact & Intro: Julian Martinez, x42405
Mon, Apr 18
Correction for Hidden Confounders in Genetic Analyses Using Graphical/Generative Models
David Heckerman, Ph.D., Director, eScience Group at Microsoft Research
Contact & Intro: Kate Wheeler, x72487
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ABSTRACT: Hidden confounders often plague genetic analyses. For example, in genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) analyses, confounding from population structure, family relatedness, and cryptic relatedness and from expression heterogeneity, respectively, can be seen. I will present a class of models that successfully correct for a wide variety of multiple hidden confounders. The models are conveniently expressed in the graphical/generative model framework and are related to mixed models. I will describe applications of the approach to GWAS, eQTL analyses, and the identification of the effects of the human immune system on HIV evolution.

Mon, Apr 25
PIPs and the Biogenesis of Secretory Granules and Lysosome-Related Organelles
Julie Brill, Ph.D., Associate Professor, Department of Molecular Genetics, University of Toronto
Contact & Intro: Esteban Dell'Angelica, x63749
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ABSTRACT: Human physiology requires formation of secretory granules and lysosome-related organelles (LROs). Professional secretory cells store bioactive molecules such as mucus, hormones, enzymes and neuropeptides in regulated secretory granules until their release in response to an appropriate signal. Melanocytes and T-cells produce LROs required for pigmentation and immune system function. Hence, understanding mechanisms involved in formation of these organelles will have far-reaching implications for human health. Phosphatidylinositol (PI) phosphates (PIPs) are key regulators of membrane trafficking, yet their roles in secretory granule biogenesis and LRO formation are not well understood. Using the fruit fly Drosophila melanogaster as a model system, we generated loss-of-function mutations in the enzymes that regulate levels of PI 4-phosphate (PI4P). We discovered that the type II PI 4-kinase PI4KII is required in the larval salivary gland for proper sorting of secretory cargo and SNAREs during formation of mucin-type secretory granules . Moreover, we found that the PI 4-phosphatase Sac1 and PI4KII act together to regulate formation of pigment granules, which are LROs found in the adult eye. Our studies reveal novel functions for PI4P regulators in secretory granule and LRO biogenesis, and suggest that homologs of these enzymes may play critical roles in human development and disease.

Mon, May 02
A Unified Framework for Association Analysis of Multiple Related Phenotypes
Matthew Stephens, Ph.D., Professor, Department of Human Genetics and Department of Statistics, The University of Chicago
Contact & Intro: Marc Suchard, x57442
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ABSTRACT: In many ongoing genome-wide association studies, multiple related phenotypes are available for testing for association with genetic variants. In most cases, however, these related phenotypes are analyzed independently from one another. For example, several studies have measured multiple lipid-related phenotypes, such as LDL-cholesterol, HDL-cholesterol, and Triglycerides, but in most cases the primary analysis has been a simple univariate scan for each phenotype. This type of univariate analysis fails to make full use of potentially rich phenotypic data.

While this observation is in some sense obvious, much less obvious is the right way to go about examining associations with multiple phenotypes. Common existing approaches include the use of methods such as MANOVA, canonical correlations, or Principal Components Analysis, to identify linear combinations of outcome that are associated with genetic variants. However, if such methods give a significant result, these associations are not always easy to interpret.

Indeed the usual approach to explaining observed multivariate associations is to revert to univariate tests, which seems far from ideal.

In this work we outline an approach to dealing with multiple phenotypes based on Bayesian model averaging. The method attempts to identify which subset of phenotypes is associated with a given genotype. In this way it incorporates the null model (no phenotypes associated with genotype); the simple univariate alternative (only one phenotype associated with genotype) and the general alternative (all phenotypes associated with genotype) into a single unified framework. In particular our approach both tests for and explains multivariate associations within a single model, avoiding the need to resort to univariate tests when explaining and interpreting significant multivariate findings. We illustrate the approach on examples, and show how, when combined with multiple phenotype data, the method can improve both power and interpretation of association analysis.

Mon, May 09
When the Glass is Half Empty: Monoallelic Expression and Susceptibility to Autism
Sagiv Shifman, Ph.D., Department of Genetics, The Alexander Silberman Inst. of Life Sciences, The Hebrew University of Jerusalem
Contact & Intro: Eleazar Eskin, x51322
Mon, May 16
Systems Approaches to Studying the Mammalian Circadian Clock
John Hogenesch, Ph.D., Associate Professor of Pharmacology, Director of the Penn Center for Bioinformatics, Associate Director of the Penn Genome Frontiers Institute, University of Pennsylvania School of Medicine
Contact & Intro: Jake Lusis, x51359
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ABSTRACT: Systems approaches offer a path to understand complex biological systems. We are studying the mammalian circadian clock, a complex system that acts to anticipate regular changes in the environment and alter physiology and behavior accordingly. In this talk, I will discuss how we are using large scale experimental and systems approaches to i) find new clock components, ii) discover network properties of the clock, and iii) defining the output pathways that are clock-regulated. These approaches include perturbation modeling with endogenous gene expression as a read-out, whole genome cell based screening, and high throughput sequencing. Because the clock is a dynamic system, we are developing experimental and informatics methods to conduct these studies over time.

Mon, May 23
Regulation of Signaling Receptors by Endocytosis (and vice versa)
Mark von Zastrow, Ph.D., Professor; Friends of LPPI Endowed Chair for Research in Schizophrenia and Depression, Department of Psychiatry, University of California, San Francisco
Contact & Intro: Esteban Dell'Angelica, x63749
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ABSTRACT: Endocytosis is a fundamental means by which the number and functional activity of signaling receptors are regulated. Our laboratory is focused on signaling in vertebrates and, in particular, in the mammalian nervous system. In past work our laboratory discovered regulated endocytosis of ionotropic glutamate receptors, and helped to define roles of endocytosis in mediating activity-dependent plasticity of rapid synaptic neurotransmission. We have a long-standing interest in understanding how endocytosis controls the number and functional activity of seven-transmembrane signaling receptors, and established in previous work that endocytosis can discriminate the receptor-mediated effects of clinically relevant drugs from native neuromodulators. Our current efforts focus on elucidating the molecular basis for sorting of signaling receptors in the endocytic pathway, in unraveling the intimate relationships between the signaling and endocytic machineries, and in developing new chemical approaches for elucidating receptor regulation in individual neurons and within intact neural circuits.

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