David Geffen School of Medicine at UCLA
Department of Human Genetics

Speaker Series - Winter Quarter 2012

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

Mon, Jan 09
Regulation and Dynamics of Endocytic Vesicle Formation
Sandra K. Lemmon, Ph.D., Professor of Molecular & Cellular Pharmacology and Director, MD/PhD Program, University of Miami
Contact & Intro: Esteban Dell'Angelica, x63749
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ABSTRACT: My laboratory studies endocytosis, a process by which extracellular materials and plasma membrane proteins are engulfed into membrane vesicles at the cell surface and taken up into the cell interior for delivery to other parts of the cell or for degradation. Many important nutrients and key regulatory molecules enter the cell by endocytosis, so this process is critical for normal cell and tissue function, cell growth and development. There are a large number of diseases that are caused by perturbation of endocytosis, including familial and autosomal recessive hypercholesterolemias, which lead to high circulating cholesterol and poor cardiovascular health, or cancer, caused by disruption of the number and activity of growth signaling receptors at the cell surface. There are multiple pathways of endocytosis in cells, but our lab studies that mediated by the vesicle coat protein clathrin in budding yeast. Many yeast endocytic factors are homologues of those found in animal cells, so this has been a powerful system for studying clathrin-mediated internalization. Over 70 proteins and the actin cytoskeleton are involved in clathrin-mediated endocytosis, but only recently have we begun to understand how these components dynamically participate in the endocytic process and how the process is regulated. We tag factors involved in endocytosis with variants of GFP and visualize their assembly and disassembly by live cell imaging, which combined with molecular genetics of yeast, have provided a remarkable way to understand the dynamic formation of endocytic vesicles.

Mon, Feb 06
Coancestry in pedigrees and populations
Elizabeth Thompson, Ph.D., Professor of Statistics, University of Washington
Contact & Intro: Kate Wheeler, kwheeler@mednet.ucla.edu
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ABSTRACT: Coancestry or gene identity by descent (ibd) underlies all genetically mediated similarities among relatives. If pedigree relationships among individuals are known, relatively sparse genetic marker data serve to estimate latent ibd. The ibd graph, defined among observed individuals and across the genome, specifies the segments of genome shared ibd among individuals. In pedigrees, the descent of genome, and hence the ibd graph, may be realized by MCMC. For each realized ibd graph, analyses of trait data may be carried out conditionally on the ibd graph, and the pedigree relationships and genetic marker data are no longer relevant. Methods to recognize when different patterns of descent provide the same ibd graph, across realizations and across the genome, are key to efficient trait analyses. More remote relationships are usually not known, but segments of genome shared ibd in remote cousins are rare rather than short. Thus the ibd resulting from these remote relationships can be estimated using denser genetic marker data and a population-genetic based ibd model. Specifically, use an HMM model to estimate the ibd graphs among the four genomes of pairs of individuals. Algorithms to merge the ibd graphs inferred within and among pedigrees provide a combined ibd graph. Using this combined graph for subsequent trait-data analysis has the potential to increase both the power and the resolution of mapping of genes contributing to complex traits.

Mon, Feb 27
Note Location Change: NRB Auditorium
Interpreting personal genomes
Kai Wang, Ph.D., Assistant Professor, Department of Psychiatry & Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
Contact & Intro: Kate Wheeler, kwheeler@mednet.ucla.edu
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ABSTRACT: High-throughput sequencing data are being generated at an unprecedented rate, but the development of bioinformatics tools for handling these data lags behind. For example, there is a paucity of methods that can simultaneously handle a large number of genetic variants (typically >3 million variants for a given human genome) and annotate their functional impacts, despite the fact that this is an important task in many sequencing applications. Functional interpretation of genetic variants therefore becomes one of the major obstacles to connect sequencing data with biomedical researchers. We have recently developed the ANNOVAR software for functional interpretation of genetic variants, and we are developing automated pipelines for personal genome annotation. In my talk, I will share three stories on using high-throughput sequencing (chromosome X sequencing, whole-exome sequencing and whole-genome sequencing) and variant annotation to identify genetic basis of several human diseases. I will discuss the lessons that we have learned from these studies and how to improve personal genome annotation to facilitate human genetics research as well as clinical applications.

Mon, Mar 12
Note Location Change: CHS 13-105
Next-generation genotyping for next-generation sequencing
Eric Stone, Ph.D., Associate Professor of Genetics, North Carolina State University
Contact & Intro: Kate Wheeler, kwheeler@mednet.ucla.edu
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ABSTRACT: High-throughput sequencing is enabling remarkably deep surveys of population genomic variation. It is now possible to completely re-sequence a sample of individuals from a common population, yet the identification of segregating SNP variants remains an evolving computational challenge. Mitigating the degree to which experimental and bioinformatic sources of error influence sequencing data is critical to high-quality genotyping. In this talk I present an approach that attempts to do so by borrowing strength across multiple sequenced individuals. I discuss how strength can be borrowed at two levels: first, at the population level, to structure the joint distribution on population genotypes; and second, at the sequencing level, to identify systematic errors in the sequencing reads. I emphasize that the genotyping approach is general and show how it applies both to human pedigree data and to a panel of inbred Drosophila melanogaster lines.

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