follicles, the oocytes were arrested at the first prophase. To maintain meiotic arrest in fully grown oocytes, the phosphodies- terase inhibitor, isobutylmethylxantine (IBMX) (0.2 mM, Sigma), that prevents cAMP degradation was included in the medium of incubation [38]. The follicles were punctured under a stereoscopic microscope in order to release the cumulus–oocyte complexes that were then placed into acidic L-15 medium (pH 6.0) to obtain cumulus-free oocytes. Each oocyte was placed in a 0.2 mL tube (ABgene) in a volume of 5 mL medium. Oocytes were frozen in liquid nitrogen and kept in 280uC until analyzed. Whole Genome Amplification of single cells was performed using the GenomePlex Single Cell Whole Genome Amplification Kit (Sigma #WGA4) and the GenomiPhi DNA amplification kit (GE Healthcare, UK). The GenomePlex kit was used according to the manufacturer’s instructions. Prior to the GenomiPhi protocol, cell denaturation was performed as follows: one part (2 ml) of lysis solution (400 mM KOH, 100 mM DTT and 10 mM EDTA) was added to 0.5 ml tubes, each containing a single cell in 2 ml double distilled water. Cells were lysed for 10 min on ice followed by addition of one part (2 ml) of neutralization solution (400 mM HCl, 600 mM Tris HCl, pH 6–prepared by mixing 4 ml of 1 M HCl and 6 ml of 1 M Tris HCl, pH 7.5). At this point each cell was in 6 ml solution (instead of 1 ml according to the protocol). The GenomiPhi protocol was carried out according to the manufacturer’s instructions, except that amounts of all the ingredients were multiplied by six. Cell identifiers Because analysis of multiple loci from single cells requires a minimal amount of DNA (typically ,1 mg in our case) we first amplified genomic DNA either by ex vivo culturing of single cells or by WGA (as described above), or a combination of these. DNA was extracted from cell clones using the Wizard SV Genomic DNA Purification System (Promega). All Primers were obtained from Applied Biosystems. Some were part of the ABI PRISMH Mouse Mapping Primers v.1.0, and others were designed by us using Primer3 (http://frodo.wi.mit.edu/). In each amplification reaction 4 MS loci were amplified together in 25 ml including DNA (25–50 ng when extracted from cell clones, or about 1% of WGA products), 0.2 mM of each primer, 0.2 mM of each dNTP (BIOLINE), and 0.625U of Thermo-Start DNA Polymerase (ABgene). Thermal cycling conditions were: (i) 15’ 95uc, (ii) 35 cycles: 1’ 95uc, 1’ 58uc, 1’ 72uc, (iii) 15’ 72uc. Amplified products from three PCR reactions were combined and run on an ABI prism 3130xl Genetic Analyzer machine (Applied Biosystems). Fragment analysis was performed using the GeneMapper v3.7 software accompanying the machine. We used a programmable laboratory robot (TECAN Genesis) augmented with a PCR machine (Biometra TRobot) to perform the liquid handling for PCR, the PCR itself, and the sample preparation for the capillary machine. Capillary signals were analyzed using an automatic signal analysis program that we designed (see Text S1). Manual override was used in about 1.5% of the signals that were defined by the algorithm as problematic, as well as all signals of samples which were amplified using Genome-Plex, due to their high stutter patterns. Analysis assigns to each MS allele in every sample a relative allelic value–a whole number equal to the difference between the number of repeats of that allele and the number of repeat units of the corresponding allele in the zygote (MS slippage mutations tend to insert or delete repeated units). All relative allelic values together compose the identifier ascribed to each cell. Cell Lineage Trees in Mice Evaluation of whole genome amplification fidelity RMA cells (kindly donated by Lea Eisenbach, The Weizmann Institute of Science) were maintained in RPM1640 medium (GIBCO, Invitrogen, UK) supplemented with 10% heat inactivated (65uC, 30 minutes) FBS (GIBCO) and 1% Penicillin/Streptomycin (GIBCO). Single RMA cells were obtained as described above, and were allowed to grow for a few days, until clones with about 10–20 cells were obtained. These clones were then separated to single cells, whose identifiers were obtained as described above. Mutations in two loci were overridden as problematic signals (see shaded ‘PS’ signals in Tables S4a–b, discussed in Text S1). Separate experiments were performed for each WGA kit (GenomiPhi and GenomePlex). In the GenomiPhi experiment two clones were created and five progeny cell were analyzed from each clone. This experiment showed 0.9% mutations. In the GenomePlex experiment three clones were created and eight progeny cells were analyzed from one clone, and one progeny cell was analyzed from each of the other two clones. This experiment showed 1.2% mutations. Bulk of RMA DNA was used as a reference against which mutations were assigned. Lineage reconstruction Lineage tree reconstruction was performed with the NJ algorithm (implemented in MATLAB). We used the distance function ‘‘Absolute-distance’’, in which the distance between two samples is the average distance between their allelic values in all alleles which were analyzed in both samples. The un-rooted output tree was rooted from the node corresponding to the root, yielding the reconstructed rooted tree. Lineage analysis of reconstructed trees Our general scheme for lineage analysis is as follows: (i) a set of cells for which we would like to check their correlation to lineage is chosen, (ii) a lineage measure is chosen, (iii) the ratio between the average lineage measure for all pairs of cells in the set and the average lineage measure for all pairs of cells is calculated. If this ratio is larger (or smaller, depending on the measure) than 95% of the ratios in 10,000 randomizations of the samples, we define the correlation between lineage and this set to be significant. In the analysis of myofibers and muscles we used the same scheme, but compared all pairs of cells within a myofiber/muscle to all pairs of cells in the experiment. We calculated the average lineage measure within all pairs of satellite cells which are on the same myofiber (or muscle), and proceeded as above. Analysis of lineage vs. physical proximity in satellite cells For each analyzed muscle we calculated a lineage matrix and a physical matrix between all satellite cells within the muscle. Each entry in the lineage matrix is the lineage measure between the pair of corresponding cells. Each entry in the physical matrix is the physical distance between the pair of corresponding cells, as defined in the paper (difference between myofiber indices). An anti-correlation coefficient (equal to minus the correlation coefficient) was obtained for each lineage and physical matrix, and was compared to 10,000 randomizations of the lineage matrix. Lineage and physical proximity within a muscle were defined as significantly anti-correlated if the anti-correlation coefficient for the actual data was larger than 95% of the anti- correlation coefficients in the randomizations. Supporting Information Figure S1 Examples of MS mutations and signal analysis issues Found at: doi:10.1371/journal.pone.0001939.s001 (0.04 MB DOC) PLoS ONE | www.plosone.org 10 April 2008 | Volume 3 | Issue 4 | e1939