Trisomy

Primers spanning the translocation breakpoint were designed using Primer3 software (Broad Institute). The breakpoint primer sequences were Chr17fwd_5′-GTGGCAAGAGACTCAAATTCAAC-3′ and Chr16rev_5′-TGGCTTATTATTATCAGGGCATTT-3′. These primers amplify a ~275 bp product from junction site of the 17¹⁶ translocation product. Positive control primers were IMR8545_5′-AAAGTCGCTCTGAGTTGTTAT-3′ and IMR8546_5′-GGAGCGGGAGAAATGGATATG-3′, which amplify a 600 bp product from the Rosa locus. In a 50 μl total reaction, all 4 primers were used at a final concentration of 0.4 μM each. PCR cycling conditions were 94°C – 2min, 94°C – 45sec, 55°C – 45sec, 72°C –1min for 40 cycles, followed by a final 7 min. extension at 72°C – 7min. PCR products were separated on a 1.5% agarose gel. For the purposes of validation, 209 samples that were previously genotyped by either by quantitative PCR (Liu et al. 2003 ) or DNA FISH as being either positive, negative or inconclusive for the segmental trisomy were genotyped by breakpoint PCR. Among this set of samples were samples from Ts65Dn mice and 2 derivative strains, B6EiC3Sn.BLiA-Ts(17¹⁶)65Dn/DnJ (The Jackson Laboratory, stock #5252) and B6EiC3Sn-Rb(12.Ts17¹⁶65Dn)2Cje/CjeDn (The Jackson Laboratory, stock #4850). Additionally, 113 samples derived from Ts65Dn mice and genotyped using the SNP based genotyping prescreen (Lorenzi et al 2010) and FISH confirmation (Moore et al. 1999 (link)).

Indexed paired-end .qseq files were aligned to the mouse reference genome (mm9) using bwa^{31 (link)}, and custom scripts were used to split the resulting .bam files by index and to add the chastity flag. The resulting .bam files were sorted and filtered for duplicates (which removes both single-end and dual-end duplicates) and low-quality alignments (q < 20) using Samtools Version 0.1.10 (ref. 32 (link)). We developed a pipeline, BAIT (bioinformatic analysis of inherited templates), that parsed the bam files on the basis of the strand directionality assigned to each read. Reads that mapped to the ‘+’ strand from the first PET (paired-end tag) and the ‘−’ strand reads from the second PET were classified as Watson reads, and reads that mapped to the – strand from the first PET and the + strand from the second PET were classified as Crick reads. These data were plotted as separate histograms against ideograms of mouse chromosomes, with reads counted in 200-kb bins across each chromosome. Additional files in .bed format were plotted over the ideograms to represent sequence gaps and contig orientations. The number of reads mapping to Watson or Crick for each chromosome were summed, and the number of reads per megabase for each chromosome was calculated and printed below the ideograms. Normalized counts per megabase were determined by calculating the sum of both Watson and Crick reads for all autosomes and dividing by the length of the autosomes (in megabases). Any chromosomes in which read counts were 0.66× lower or 1.33× higher than the normalized count were classified as monosomies or trisomies, respectively. SCE events were defined as the interval in which there was a switch from reads mapping to both Watson and Crick strands to reads mapping to just one of the strands, without a corresponding change in the total number of reads such that the sum of Watson and Crick reads remained constant. Our criteria further stipulated that there must be ten consecutive Watson-only or Crick-only reads after the interval switch to count the switch as an SCE or to confirm fragment or contig orientation. To verify SCE and misorientation events, the SCE and misoriented contig interval coordinates were also converted to .bed files using BEDtools^{33 (link)} and uploaded to the UCSC genome browser to identify genomic features and genome build features, such as contigs, and to determine suitable BACs for FISH probes.