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. 2014 Oct 28;9(10):e109186. doi: 10.1371/journal.pone.0109186

Table 5. Computer Simulation of SNP Accrual in the Setting of a Transition Bias Leads to Enhancement of Conservative Mutations.

Imposed Substitution Bias Sequence No. Runs Muts/Run Resulting Ncon∶Con P-Value vs. Corresponding unbiased substitution
Unbiased Artificial Sequence 10 50 2.95 ----
CFTR 10 50 1.93 ----
CFTR GC-RICH 10 10 1.75 ----
CFTR Mutation Database Derived Transition Bias (See Table 2) Artificial Sequence 10 50 2.8 2.46 E-15
CFTR 10 50 2.04 ----
CFTR GC-RICH 10 10 1.56 2.89 E-19
Exon Derived Transition Bias (See Table 1) Artificial Sequence 10 50 2.52 5.96 E-58
CFTR 10 50 1.53 4.31 E-85
CFTR GC-RICH 10 10 1.57 3.45 E-29
Intron Derived Transition Bias (See Table 1) Artificial Sequence 10 50 2.25 8.40 E-32
CFTR 10 50 1.99 ----
CFTR GC-RICH 10 10 1.17 6.49 E-18

SNPs were stochastically placed in 1) an artificial, assembled gene containing 1480 codons arranged randomly (i.e. random codons were used to generate a 4440 bp sequence), 2) the CFTR coding sequence (1480 codons), or 3) a GC-rich region of CFTR. The computer-generated positions to be mutated were selected randomly, and the choice of base replacement (e.g. with or without a particular transition bias) derived as above, according to the CFTR mutation database (Table 2), or rates observed for exonic or intronic SNPs (Table 1). The ratios for non-conservative (Ncon) to conservative (Con) SNPs are shown. Table 5 is the result of 10 simulation runs per sequence, indicating significant differences even after small numbers of SNP incorporation.