Elaine Ostrander, Ph.D.

Fido's Closet: Canine Bones and the Stories They Tell

The 165 domestic US dogs breeds display tremendous morphologic variation, making them an appealing model for the identification of genetic regulators of vertebrate shape and development. We have genotyped over 1000 dogs representing 85 domestic breeds to generate data on over 60,000 informative SNPs per dog. This, combined with morphometric data has allowed us to map and sequence loci that control various features of breed-specific traits related to shape and size. In this seminar, we will summarize our work on body size and skull shape, providing new insights into the ways in which genes work together to create a continuum of variation across dog breeds.

Differences between breeds in terms of both skull shape and body size are large and striking, resulting from selective breeding that isolated and propagated heritable traits to create breeds of purpose and fancy. Previous studies suggest that cranioskeletal modularity exists among dogs, particularly between bones that articulate the face and neurocranium. The result is a repertoire of forms, including those superficially reminiscent to human brachycephaly (face-shortening), dolichocephaly (face-lengthening), and hydrocephalus (neurocranium enlargement). While these cephalic disorders are associated with human morbidity, their canine analogs appear benign, suggesting that novel developmental mechanisms are responsible for canine cranioskeletal shapes. Using craniometric data collected from museum specimens, we mapped quantitative cranioskeletal traits, revealing the genetic basis of dogs’ rostrum-neurocranium modularity. Fine mapping isolated a missense mutation in BMP3 that falls within a selective sweep and is associated with canine brachycephaly. Using functional genetic assays in zebrafish, we demonstrate that the putative mutation strongly reduces human BMP3 activity in vivo, and that BMP3 is required for normal cranioskeletal development. At least three additional loci play contributory roles.

Similar studies are underway with regard to body size; the IGF1 gene, together with at least four other loci are shown to play major roles in determining the gradient of skeletal size observed between giant and small domestic dog breeds. Fine mapping of these four loci validated the scan associations and revealed critical intervals that include excellent candidate genes. For each locus, the most highly associated SNP was genotyped in over 500 dogs belonging to 100 dog breeds (covering the entire range of weight and height) to determine the effects of the different alleles on canine body size. The results show that dogs carrying the large allele at all loci have a weight above 55 pounds. Most dogs < 50 lbs are carriers of the small IGF1 allele and dogs which carry the small allele at all loci have an average weight of 10 lbs. Most alleles appear to contribute to dog size in a manner expected of additive effect QTLs.

Julian Parkhill, Ph.D.

Tracking transmission and evolution of bacterial pathogens with high-throughput genomics

High-throughput sequencing technologies allow us to perform rapid draft whole-genome sequencing for hundreds of bacterial strains simultaneously. Using these techniques, we can perform genome sequencing at the population level in order to identify genetic variation for epidemiology, and to look for the signatures of selective pressure and evolutionary change. Data from population-level studies on human pathogens including Staphyloccus aureus, Streptococcus pneumoniae and Vibrio cholerae will be presented showing how we can track transmission, and identify different population structures and evolutionary pressures acting on these organisms.

John Quackenbush, Ph.D.

Network and State Space Models: Science and Science Fiction Approaches to Cell Fate Predictions

Two trends are driving innovation and discovery in biological sciences: technologies that allow holistic surveys of genes, proteins, and metabolites and a realization that biological processes are driven by complex networks of interacting biological molecules. However, there is a gap between the gene lists emerging from genome sequencing projects and the network diagrams that are essential if we are to understand the link between genotype and phenotype. ‘Omic technologies were once heralded as providing a window into those networks, but so far their success has been limited, in large part because the high-dimensional they produce cannot be fully constrained by the limited number of measurements and in part because the data themselves represent only a small part of the complete story. To circumvent these limitations, we have developed methods that combine ‘omic data with other sources of information in an effort to leverage, more completely, the compendium of information that we have been able to amass. Here we will present a number of approaches we have developed, with an emphasis on the how those methods have provided into the role that particular cellular pathways play in driving differentiation, and the role that variation in gene expression patterns influences the development of disease states. Looking forward, we will examine more abstract state-space models that may have potential to lead us to a more general predictive, theoretical biology.

Michael Snyder, Ph.D.

Adventures in Personal Genomics and Whole Omics Profiling

Personalized medicine is expected to benefit from the combination of genomic information with the global monitoring of molecular components and physiological states. To ascertain whether this can be achieved, we determined the whole genome sequence of an individual at high accuracy and performed an integrated Personal Omics Profiling (iPOP) analysis, combining genomic, transcriptomic, proteomic, metabolomic, and autoantibodyomic information, over a 21-month period that included healthy and two virally infected states. Our iPOP analysis of blood components revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways across healthy and disease conditions. Importantly, genomic information was also used to estimate medical risks, including Type 2 Diabetes, whose onset was observed during the course of our study. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states.