According to the prion hypothesis, atypical phenotypes arise when a prion protein adopts an alternative conformation and persist when that form assembles into self-replicating aggregates. Amyloid formation in vitro provides a model for this protein-misfolding pathway, but the mechanism by which this process interacts with the cellular environment to produce transmissible phenotypes is poorly understood. Using the yeast prion Sup35/[PSI + ], we found that protein conformation determined the size distribution of aggregates through its interactions with a molecular chaperone. Shifts in this range created variations in aggregate abundance among cells due to a size threshold for transmission, and this heterogeneity, along with aggregate growth and fragmentation, induced age-dependent fluctuations in phenotype. Thus, prion conformations may specify phenotypes as population averages in a dynamic system. Prion proteins adopt a spectrum of conformations or strains, which create phenotypes of distinct severity and stability in vivo (1-3). These phenotypes are linked to the assembly of the protein into aggregates that, at unique rates, template the conversion of newly-made prion protein to a similar state and are fragmented (4). But, how do these biochemical events translate into distinct phenotypes? One possibility is an "abundance-based" model, in which phenotypes are linked to an equilibrium between aggregated and soluble prion protein that determines protein activity and the number of heritable prions (propagons) (5,6). However, the conversion and fragmentation reactions also create heterogeneity in aggregate size, raising the possibility of a second, "size-based" model in which a subpopulation of aggregates establishes and propagates phenotypes (7).To distinguish between these models, we focused on the [PSI + ] Weak and [PSI + ] Strong conformations of the yeast prion protein Sup35, which create phenotypes of different stabilities in vivo (8). To sustain these phenotypes in a dividing culture, Sup35 protein in the prion conformation must be inherited (7). To test whether conformational differences impact phenotypic stability by altering protein transmissibility, we monitored Sup35-GFP transfer to daughter cells. Using fluorescence loss in photobleaching (FLIP), a [PSI + ] Weak strain transferred half as much Sup35-GFP (~15% vs. ~30%; Fig. 1A) and contained ~50% fewer ** This manuscript has been accepted for publication in Science. This version has not undergone final editing. Please refer to the complete version of record at http://www.sciencemag.org/. The manuscript may not be reproduced or used in any manner that does not fall within the fair use provisions of the

Motivation: Structural variants, including duplications, insertions, deletions and inversions of large blocks of DNA sequence, are an important contributor to human genome variation. Measuring structural variants in a genome sequence is typically more challenging than measuring single nucleotide changes. Current approaches for structural variant identification, including paired-end DNA sequencing/mapping and array comparative genomic hybridization (aCGH), do not identify the boundaries of variants precisely. Consequently, most reported human structural variants are poorly defined and not readily compared across different studies and measurement techniques.Results: We introduce Geometric Analysis of Structural Variants (GASV), a geometric approach for identification, classification and comparison of structural variants. This approach represents the uncertainty in measurement of a structural variant as a polygon in the plane, and identifies measurements supporting the same variant by computing intersections of polygons. We derive a computational geometry algorithm to efficiently identify all such intersections. We apply GASV to sequencing data from nine individual human genomes and several cancer genomes. We obtain better localization of the boundaries of structural variants, distinguish genetic from putative somatic structural variants in cancer genomes, and integrate aCGH and paired-end sequencing measurements of structural variants. This work presents the first general framework for comparing structural variants across multiple samples and measurement techniques, and will be useful for studies of both genetic structural variants and somatic rearrangements in cancer.Availability: http://cs.brown.edu/people/braphael/software.htmlContact: braphael@brown.edu