5. MARCO CONCEPTUAL
5.1 Cultura y Psicología Cultural
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Large multipage figure available at https://shiek-‐db.wistar.upenn.edu/riethman/suppfig48.pdf
Figure 4.8 − Snapshots of Annotated Mouse Subtelomeres. Screenshots of the mouse subtelomere browser showing static versions of tracks specifically discussed in this paper are shown. See the live browser (http://vader.wistar.upenn.edu/mousesubtel) for custom track selection, zooming, and track organization.Figure 4.7 − Telomeric BAC Isolation. The CH25 BAC library was prepared using sheared DNA from
strain c57bl/6j and cloning into the vector pTARBAC6 (Osoegawa et al., 2007). The library was screened using labeled overgo probes (Vollrath, 1999) specific for the junction of vector and telomere repeat
sequence in order to specifically identify clones which contain an insert fragment with the telomere repeat at one end. BAC clones thus identified were colony-purified, end-sequenced, and localized to metaphase chromosomes using FISH. The non-telomere BAC end sequences were mapped to the assembled mouse genome using BLAST (Altschul et al., 1990). The combination of FISH localizations (or multi-site
localization) and end sequence match were used to select candidate telomere BACs for full sequencing. The telomeric BACs thus identified and the sequenced clones incorporated into Build38/mm10 are listed in Supplementary Table 1.
Figure 4.9 − Mouse 18q Subtelomere Annotated using additional datasets. Screenshots of the mouse subtelomere browser showing static versions of tracks specifically discussed in this paper are shown. See the live browser (http://vader.wistar.upenn.edu/mou sesubtel) for custom track selection, zooming, and track organization.
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Figure 4.10 − Mouse 9q
Subtelomere Annotated using additional datasets. The same tracks as in Supplementary Figure 3, as shown for 9q.
Table 4.2 − Mouse Subtelomeric Clones. Telomeric BACs were identified as described in the legend to
Supplemenary Figure 4.7, and are highlighted in Supplementary Table 4.2. Fosmid End Sequence (FES) mapping: An end-sequenced fosmid library derived from sheared mouse genomic DNA (WI-2; Church et al., 2009) was screened for clones containing the telomere terminal repeat sequence (TTAGGG)n. Because of the orientation of this repeat at all terminal repeat tracts, the distal end-sequence from a telomere-terminal fosmid will always contain a (CCCTAA)n pattern. As for a similar computational screen of human fosmid libraries (Stong et al., 2014), requiring a perfect (CCCTAA)4 match reliably identified authentic telomere- containing fosmid clones. The mate pairs of (CCCTAA)-containing fosmid end sequences from the WI-2 library were mapped back to reference subtelomere assemblies; all but a few mapped either uniquely to a known subtelomere assembly or to a known SRE. These mappings identified fosmids that should bridge existing subterminal gaps in the reference sequence, and are identified in Supplementary Table 4.2.
Excel spreadsheet available from https://shiek-‐db.wistar.upenn.edu/riethman/supptab3.xls
Table 4.3 − Datasets used in this study and quality metrics. Table includes all data set tracks andinformation on data set origins, their matched control, and the specific companies and product numbers for antibodies used. The abbreviations for the antibody-providing companies are: MIL, Millipore; sc, Santa Cruz Biotechnology; ab, Abcam; and BL, Bethyl Laboratories. Metrics include number of peaks called in hybrid genome using all reads, and only uniquely mapping reads. FRiP (Fraction of Reads in Peak), for all reads: partial reads (mapping likelihood) was counted in peaks called using all reads. FRiP for only unique reads is reads in peaks called using only uniquely mapping reads. PBC (PCR Bottleneck Coefficient) is the number of genomic positions with one read mapping to it (uniquely mapping or partial mapping), divided by the total number of genomic positions with at least one read mapping (uniquely mapping or partial mapping). NSC (Normalized Strand Cross-correlation coefficient) is the ratio of maximal cross-correlation value over the background cross-correlation. RSC (Relative Strand Cross-correlation coefficient) is the maximal cross correlation value minus the background cross-correlation, divided by the cross-correlation at the read length minus the background cross-correlation. Fordetail see (Landt et al., 2012) and
http://genome.ucsc.edu/ENCODE/qualityMetrics.html.
Excel spreadsheet available from https://shiek-‐db.wistar.upenn.edu/riethman/supptab4.xls
Table 4.4 − SRE boundary enrichment statistics. Raw Peak Counts of Subtelomere BoundaryEnrichments. All Tables have columns corresponding to different boundary categories, and total for all boundaries in the SRE region. Boundary categories are 1copy/SRE (duplicon ends at unique subtelomere sequence), Gap (duplicon ends at most terminal complete sequence but not telomere), SRE/SRE (duplicon ends within SRE region), SRE/SD (duplicon ends at genomic duplicon), Terminal (duplicon ends at telomere), All_Bndries (all boundaries). Rows correspond to datasets. A. Raw Counts - Counts of peaks in association with different boundary categories and total. Additional row, Sequence, is the amount of sequence within the window of the boundary type, or the total SRE region. B. Percent – This table shows the percent of total peaks associated with a boundary type, for the total column this is always 100%. The additional row still corresponds to the amount of sequence within the window for the boundary type, the percent of sequence within the window of the boundary type out of the total SRE. This is the expected percentage of peaks in association, if the peaks are distributed randomly in the SRE. C. Enrichment – The ratio of percentage for a category and dataset over the expected percentage for that category. D. P Value – The p value calculated using a binomial test with the expected percentage as the probability of success, and the associated number of peaks and total number of peaks as success and trials.