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A perceived disadvantage of transgenic rodent mutation assays is that spontaneous mutant frequencies are high compared to those of endogenous genes and may consequently reduce sensitivity to induced mutation. We have previously argued that unrepaired G:T mismatches from spontaneous deamination of 5-methylcytosine at CpG sites could be converted to apparent in vivo mutations in the bacterial recovery systems because of rapid, random, mismatch repair in Escherichia coli. In this study, we have measured mutation frequencies in spleen of male mice induced by N-ethyl-N-nitrosourea (ENU) using the PhiX174 transgene, which is not subject to mismatch repair in E.coli, using single-burst analysis, a unique method to identify in vivo mutation. In order to compare our results to those using the lacI and cII transgenes, we converted all mutant frequencies to base pair substitution (bps) mutation frequencies per nucleotide based on mutant spectra from this study and published literature. We found this frequency in control spleen to be similar for lacI (3.8 +/- 0.7 x 10(-8)) and PhiX174 (3.1 +/- 1.2 x 10(-8)) at 6 weeks of age. We found a strong age dependence for spontaneous lacI mutation that extrapolated to a value at conception (1.8 +/- 0.9 x 10(-8)) that was not significantly different from the human germ line bps mutation frequency per nucleotide of 1.7 +/- 0.2 x 10(-8). These two transgenes provided similar mutational responses to 40 mg/kg ENU, 7- to 9-fold. In contrast, the cII target gene in the same tissue produces both spontaneous and induced mutation frequencies approximately 10 times higher, for unknown reasons. We conclude that the spontaneous mutant frequencies measured by the lacI and PhiX174 transgenes in this moderately dividing tissue accurately measure in vivo mutation frequencies at early ages. For these two transgenes, seemingly high mutant frequencies may reflect the expected accumulation of somatic mutation with age.

Motivation: Gene class testing (GCT) is a statistical approach to determine whether some functionally predefined classes of genes express differently under two experimental conditions. GCT computes the P-value of each gene class based on the null distribution and the gene classes are ranked for importance in accordance with their P-values. Currently, two null hypotheses have been considered: the Q1 hypothesis tests the relative strength of association with the phenotypes among the gene classes, and the Q2 hypothesis assesses the statistical significance. These two hypotheses are related but not equivalent., Method: We investigate three one-sided and two two-sided test statistics under Q1 and Q2. The null distributions of gene classes under Q1 are generated by permuting gene labels and the null distributions under Q2 are generated by permuting samples., Results: We applied the five statistics to a diabetes dataset with 143 gene classes and to a breast cancer dataset with 508 GO (Gene Ontology) terms. In each statistic, the null distributions of the gene classes under Q1 are different from those under Q2 in both datasets, and their rankings can be different too. We clarify the one-sided and two-sided hypotheses, and discuss some issues regarding the Q1 and Q2 hypotheses for gene class ranking in the GCT. Because Q1 does not deal with correlations among genes, we prefer test based on Q2., Supplementary Information: Supplementary data are available at Bioinformatics online.

K-ras codon 12 GGT-->GAT and GGT-->GTT mutations are the most frequently observed K-ras point mutations in human and rodent tumors and therefore are implicated in carcinogenesis for many tissues. Measurement of these mutations in rat models and human tissue could facilitate a more logical extrapolation of rodent tumorigenesis data to human disease. We have developed allele-specific competitive blocker PCR (ACB-PCR) assays for rat K-ras codon 12 GGT-->GTT and GGT-->GAT mutations that parallel the already published assays for human K-ras codon 12 mutations. Liver K-ras codon 12 mutant allele fractions were measured in vehicle-treated and N-hydroxy-2-acetylaminofluorene (N-OH-AAF)-treated Big Blue rats. The average K-ras codon 12 GGT-->GTT mutant fraction (MF) for four control rats was 50 x 10(-6) (95% CI: 27 x 10(-6), 95 x 10(-6)) and for four treated rats was 165 x 10(-6) (95% CI: 87 x 10(-6), 312 x 10(-6)), indicating a 3.3-fold increase with treatment (95% CI: 1.3-8.1). The average MF of K-ras codon 12 GGT-->GAT for control rats was 1320 x 10(-6) (95% CI: 498 x 10(-6), 3500 x 10(-6)) and for treated rats was 8450 x 10(-6) (95% CI: 3180 x 10(-6), 22 400 x 10(-6)), indicating a 6.4-fold increase with treatment (95% CI: 1.6-25.4). These transgenic rats were part of a study that included analysis of liver lacI mutations. Although data from lacI determinations show that this compound induces mostly G-->T mutations, using the ACB-PCR method both K-ras codon 12 GGT-->GTT and GGT-->GAT MFs were significantly increased in treated rats versus control rats. This data raises the possibility that N-OH-AAF may not only induce mutations by a genotoxic mechanism, but also by amplification of both de novo and pre-existing K-ras mutation.

DNA mismatch repair (MMR) deficiencies result in increased frequencies of spontaneous mutation and tumor formation. In the present study, we tested the hypothesis that a chemically-induced mutational response would be greater in a mouse with an MMR-deficiency than in the MMR-proficient mouse models commonly used to assay for chemical carcinogenicity. To accomplish this, the induction of H-ras codon 61 CAA-->AAA mutation was examined in Pms2 knockout mice (Pms2-/-, C57BL/6 background) and sibling wild-type mice (Pms2+/+). Groups of five or six neonatal male mice were treated with 0.3 micromol 4-aminobiphenyl (4-ABP) or the vehicle control, dimethylsulfoxide. Eight months after treatment, liver DNAs were isolated and analysed for levels of H-ras codon 61 CAA-->AAA mutation using allele-specific competitive blocker-PCR. In Pms2-proficient and Pms2-deficient mice, 4-ABP treatment caused an increase in mutant fraction (MF) from 1.65x10(-5) to 2.91x10(-5) and from 3.40x10(-5) to 4.70x10(-5), respectively. Pooling data from 4-ABP-treated and control mice, the approximately 2-fold increase in MF observed in Pms2-deficient as compared with Pms2-proficient mice was statistically significant (P=0.0207) and consistent with what has been reported previously in terms of induction of G:C-->T:A mutation in a Pms2-deficient background. Pooling data from both genotypes, the increase in H-ras MF in 4-ABP-treated mice, as compared with control mice, did not reach the 95% confidence level of statistical significance (P=0.0606). The 4-ABP treatment caused a 1.76-fold and 1.38-fold increase in average H-ras MF in Pms2-proficient and Pms2-deficient mice, respectively. Furthermore, the levels of induced mutation in Pms2-proficient and Pms2-deficient mice were nearly identical (1.26x10(-5) and 1.30x10(-5), respectively). We conclude that Pms2-deficiency does not result in an amplification of the H-ras codon 61 CAA-->AAA mutational response induced by 4-ABP.

Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and technical variation. This study presents a variance-components approach to investigating animal-to-animal, between-array, within-array and day-to-day variations for two data sets. The first data set involved estimation of technical variances for pooled control and pooled treated RNA samples. The variance components included between-array, and two nested within-array variances: between-section (the upper- and lower-sections of the array are replicates) and within-section (two adjacent spots of the same gene are printed within each section). The second experiment was conducted on four different weeks. Each week there were reference and test samples with a dye-flip replicate in two hybridization days. The variance components included week-to-week, animal-to-animal and between-array and within-array variances., Results: We applied the linear mixed-effects model to quantify different sources of variation. In the first data set, we found that the between-array variance is greater than the between-section variance, which, in turn, is greater than the within-section variance. In the second data set, for the reference samples, the week-to-week variance is larger than the between-array variance, which, in turn, is slightly larger than the within-array variance. For the test samples, the week-to-week variance has the largest variation. The animal-to-animal variance is slightly larger than the between-array and within-array variances. However, in a gene-by-gene analysis, the animal-to-animal variance is smaller than the between-array variance in four out of five housekeeping genes. In summary, the largest variation observed is the week-to-week effect. Another important source of variability is the animal-to-animal variation. Finally, we describe the use of variance-component estimates to determine optimal numbers of animals, arrays per animal and sections per array in planning microarray experiments.

Male C57BL/6N mice were administered a single ip injection of 30 mg of N-methyl-N-nitrosourea (MNU)/kg of body weight. Additional groups were treated similarly every 3 hours for the next 24 hours. Adenocarcinomas of the small intestine were the major treatment-related tumors, with the total incidence being 38% at 250 days after injection. There was a significant circadian variation for tumor induction; the maximum number of intestinal tumors (approximately equal to 55%) tended to occur when the MNU was administered during the middle of the light period (6:00 to 18:00), while the tumor incidence was at a minimum (approximately equal to 10%) when the MNU was given in the middle of the dark phase (18:00 to 6:00). These data are discussed in relation to DNA synthesis and repair and MNU-induced cellular toxicity.