Keynote Speakers

Prof. Jennifer A. Marshall Graves
ARC Center for Kangaroo Genomics, Research school of Biological Sciences
Australian National University

Title: Exploring Genomes of Distantly Related Mammals

There are three groups of extant mammals, two of which abound in Australia. Marsupials (kangaroos and their relatives) and monotremes (echidna and the fabulous platypus) have been evolving independently for most of mammalian history. The genomes of marsupial and monotreme mammals are particularly valuable because these "alternative mammals" fill a phylogenetic gap in vertebrate species lined up for exhaustive genomic study. Human and mice (~70MY) are too close to distinguish signal, whereas mammal/bird comparisons (~310MY) are too distant to allow alignment. Kangaroos (180 MY) and platypus (210 MY) are just right. Sequence has diverged sufficiently for stringent detection of homologies that can reveal coding regions and regulatory signals. Importantly, marsupials and monotremes share with humans many mammal-specific developmental pathways and regulatory systems such as sex determination, lactation and X chromosome inactivation. The ARC Centre for Kangaroo Genomics is characterizing the genome of the model Australian kangaroo Macropus eugenii (the tammar wallaby), which is being sequenced by AGRF in Australia, and Baylor (funded by NIH) in the US. We are developing detailed physical and linkage maps of the genome to complement sequencing, and will prepare and array cDNAs for functional studies, especially of reproduction and development. Complete sequencing of the distantly related Brazilian short-tailed opossum Monodelphis domestica by the NIH allows us to compare distantly related marsupials. Sequencing of the genome of the platypus, Ornithorhynchus anatinus by Washington University (funded by the NIH) is complete, and our lab is anchoring contigs to the physical map. We have isolated and completely characterized many BACs and cDNAs containing kangaroo and platypus genes of interest, and demonstrate the value of comparisons to reveal conserved genome organization and function, and new insights in the evolution of the mammalian genome, particularly sex chromosomes.

Prof. Joe Nadeau
Department of Genetics
School of Medicine
Case Western Reserve University

Title: Bugs, Guts and Fat - a Systems Approach to the Metabolic 'Axis of Evil'

Rapidly growing evidence suggests that complex and variable interactions between host genetic and systems factors, diet, activity and lifestyle choices, and intestinal microbes control the incidence, severity and complexity of metabolic diseases. The dramatic increase in the world-wide incidence of these diseases, including obesity, diabetes, hypertension, heart disease, and fatty liver disease, raises the need for new ways to maintain health despite inherited and environmental risks. We are pursuing a comprehensive approach based on diet-induced models of metabolic disease. During the course of these studies, new and challenging statistical, analytical and computational problems were discovered. We pioneered a new paradigm for genetic studies based on chromosome substitution strains of laboratory mice. These strains involve systematically substituting each chromosome in a host strain with the corresponding chromosome from a donor strain. A genome survey with these strains therefore involves testing a panel of individual, distinct and non-overlapping genotypes, in contrast to conventional studies of heterogeneous populations. Studies of diet-induced metabolic disease with these strains have already led to striking observations. We discovered that most traits are controlled by a many genetic variants each of which has unexpectedly large phenotypic effects and that act in a highly non-additive manner. The non-additive nature of these variants challenges conventional models of the architecture of complex traits. At every level of resolution from the entire genome to very small genetic intervals, we discovered comparable levels of genetic complexity, suggesting a fractal property of complex traits. Another remarkable property of these large-effect variants is their ability to switch complex systems between alternative phenotypic states such as obese to lean and high to low cholesterol, suggesting that biological traits might be organized in a small number of stable states rather than continuous variability. Moreover, by studying correlations between non-genetic variation in pairs of traits (the genetic control of non-genetic variation), we discovered a new way to dissect the functional architecture of biological systems. Finally, a neglected aspect of these studies of metabolic disease involves the intestingal microbes. Early studies suggest that diet and host physiology affect the numbers and kinds of microbes, and that these microbes in turn affect host metabolism. These interactions between 'bugs, guts and fat' extend systems studies from conventional aspects of genetics and biology to population considerations of the functional interactions between hosts, diet and our microbial passengers. With these models of diet-induced metabolic disease in chromosome substitution strains, we are now positioned find ways to tip complex systems from disease to health.

Prof. Pavel Pevzner
Ronald R. Taylor Professor of Computer Science
Department of Computer Science & Engineering
University of California, San Diego

Title: Protein Identification via Spectral Networks Analysis

Advances in tandem mass-spectrometry (MS/MS) steadily increase the rate of generation of MS/MS spectra. As a result, the existing approaches that compare spectra against databases are already facing a bottleneck, particularly when interpreting spectra of modified peptides. We introduce a new idea that allows one to perform MS/MS database search without ever comparing a spectrum against a database. We propose to slightly change the experimental protocol to intentionally generate spectral pairs - pairs of spectra obtained from overlapping (often non-tryptic) peptides or from unmodified and modified versions of the same peptide. While seemingly redundant, spectral pairs open up computational avenues that were never explored before. Having a spectrum of a modified peptide paired with a spectrum of an unmodified peptide, allows one to separate the prefix and suffix ladders, to greatly reduce the number of noise peaks, and to generate a small number of peptide reconstructions that are likely to contain the correct one. The MS/MS database search is thus reduced to extremely fast pattern matching (rather than time-consuming matching of spectra against databases). In addition to speed, our approach provides a new paradigm for identifying post-translational modifications and shotgun protein sequencing via spectral networks analysis.

This is a joint work with Nuno Bandeira, Karl Clauser, Ari Frank and Dekel Tsur.