and Sli15 [33,34]. It is conceivable that these chromosome passenger complex components need to be balanced in dosage to ensure proper chromosome segregation. The flip side of the above finding is that relatively stable karyotypes may result from fortuitous but possibly complex balancing of certain key modules of the mitotic machinery. In an adaptive landscape, such metastable karyotypes may correlate with relatively stable, thus selectable, phenotypic states. This is consistent with the observation in mouse models or cancer cells that whereas moderate levels of CIN promote tumor formation or emergence of drug resistance, extremely high CIN could abate both processes [35,36]. A recent large-scale analysis of aneuploid karyotypes in cancer cells revealed a high rate of co-occurrence of specific chromosome gains or losses [37]. While this may be explained by a requirement for balanced gene function to maintain fitness, chromosome co-gain or co-loss may also be important for achieving relatively stable cancer karyotypes in order for persistent expression of cancer phenotypes given a certain tissue microenvironment. Further, the existence of relatively stable karyotypic and phenotypic states may explain why certain chromosome aberrations in cancer are clonal [38,39]. Finally, the observation of both global and chromosome-specific determinants of CIN may help to reconcile the chromosome/ genome-centric theory vs. gene-centric theory in cancer evolution. First, our model of discrete and genome-dependent scaling of accurate chromosome segregation is consistent with the notion that complex cellular behaviors are non-linearly related to the sum of the function encoded by individual genes or even chromosomes. At the same time, the observation of different degrees of CIN associated with different aneuploid karyotypes, and more impor- tantly with specific chromosome imbalances, highlights the exceptional impact of certain molecular components, such as Mad1 and Mad2, on the function and stability of the genome. However, even in this latter scenario, the impact of specific gene dosage is context-dependent, i.e. dependent on the dosage or activity of its partners in a manner that is potentially difficult to decode without a better knowledge of the entire cancer genome. Materials and Methods Strain generation and media Aneuploid strains were generated as meiotic products of a homozygous triploid yeast strain as previously described [15]. All strains were cultured in either liquid or solid YEPD (Yeast Extract Peptone +2% Dextrose) media at 23uC. A list of all analyzed aneuploid strains with their karyotype information is provided in Table S1. Collection of population and colony samples from aneuploid cultures Aneuploid spores were grown into colonies of ,106 cells based on preliminary experiments correlating colony size with cell number. Then the spore-derived colonies were entirely picked and resuspended into 2 mL of YEPD media. The actual cell concentration was measured using a hemocytometer and ,200 cells were plated onto 15 cm YEPD plates. 600 mL of the culture was immediately fixed with 70% Ethanol for DNA content analysis by FACS (see below). Concomitantly a biomass corre- sponding to an OD600 = 0.3 in 300 mL was immediately frozen at 280uC for qPCR assays (see below). A part of the culture was used to prepare glycerol stocks. The remaining culture was diluted 2006 with YEPD media and grown at 23uC. Cell numbers in the growing cultures were regularly monitored using the hemocytom- eter and ,200 cells were spread on to YEPD plates once the Karyotypic Determinants of Chromosome Instability cultures reached ,25 and ,30 cell divisions after germination. After 3–6 days incubation at 23uC, 11 colonies from each YEPD plate were randomly picked as previously described [15]. The picked colonies were inoculated into a 96-well deep-well block containing 1.5 mL YEPD media and grown overnight at 200 rpm. Each culture was harvested for FACS and qPCR analysis as described above. High-throughput karyotyping method The DNA content analysis and qPCR-based karyotyping were performed essentially as previously described [15] with the only exception that FACS samples from to MAD2:MAD1 ratio experiment were acquired using a MACSquant Analyzer (Miltenyi) and 6,000 events were collected for each sample. The data were analyzed using FlowJo 7.6.1. Ploidy variation analysis was performed by extracting the mode of the G1 peak position from the DNA profile of original spore and from the correspond- ing 11 colonies. The CV (Coefficient of Variation) was calculated between these 12 G1 peak positions and compared to the CV of 12 randomly-picked haploid colonies processed in parallel. MAD2:MAD1 gene copy number ratio and apparent ploidy variation A new set of aneuploid strains was generated as described above. When the spore colony reached ,106 cells, the colony was picked, partially harvested for FACS analysis and for MAD2:- MAD1 ratio determination (see below), its cell number was determined at the hemocytometer and ,200 cells were plated into fresh YEPD plates. Once colonies became visible, 11 randomly selected colonies were picked and processed for FACS analysis as described above. When aligning the DNA profile of the original spore to the DNA profiles of the corresponding 11 colonies, the following criteria were applied: (i) those strains with obvious heterogeneous and noisy DNA profiles were classified as unstable; (ii) strains with clean DNA profiles and similar ploidy were subjected to ploidy variation analysis as described above. A strain was classified as ‘ploidy stable’ only if it showed similar or smaller CV compared to that of a haploid control strain processed in parallel. Samples harvested for MAD2:MAD1 copy number ratio determination were resuspended in 20 mL PBS (pH = 7.4) containing 50 mg/ml Zymolyase 100T (US Biological) and incubated at 37uC for 30 min. These samples were diluted 1:200. To prepare qPCR reactions, 2 ml of these dilutions were combined with 8 ml 16 Perfecta SYBR Green Mix (Quanta) at 500 nM for forward and reverse primers in technical triplicates on a CAS-4200 robot (Corbett) and run on an ABI 7900HT cycler with the following cycling conditions: 95uC for 5 min, then 40 cycles of 95uC for 15 s followed by 60uC for 1 min. Ct values were obtained using SDS 2.4 software (ABI). The ratio of MAD2:MAD1 copy number presented in Figure 5C and 5D were calculated using the NRQ method in qbasePLUS version 2.0 software (Biogazelle) by setting either MAD1 or ChrVII as the endogenous control and scaling all samples to wild type haploid. All primers used in this study are listed in Table S2. Statistical analysis and computer simulations All statistical analyses and computer simulations were performed in the R environment for statistical computing. Difference in means was evaluated by means of two-sided unpaired Welch’s t-test, association between categorical data by Fisher’s Exact Test for count data, overlap between subsets by Hypergeometric test and difference between empirical cumulative distribution functions by Kolmo- gorov-Smirnov test. Results were considered significant if P,0.05. PLoS Genetics | www.plosgenetics.org 11 May 2012 | Volume 8 | Issue 5 | e1002719