A mutation spectra database for bacterial and mammalian genes: 1998

Transcription-induced mutational strand bias and its effect on substitution rates in human genes

If substitution rates are not the same on the two complementary DNA strands, a substitution is considered strand asymmetric. Such substitutional strand asymmetries are determined here for the three most frequent types of substitution on the human genome (C --> T, A --> G, and G --> T). Substitution rate differences between both strands are estimated for 4,590 human genes by aligning all repeats occurring within the introns with their ancestral consensus sequences. For 1,630 of these genes, both coding strand and noncoding strand rates could be compared with rates in gene-flanking regions. All three rates considered are found to be on average higher on the coding strand and lower on the transcribed strand in comparison to their values in the gene-flanking regions. This finding points to the simultaneous action of rate-increasing effects on the coding strand--such as increased adenine and cytosine deamination--and transcription-coupled repair as a rate-reducing effect on the transcribed strand. The common behavior of the three rates leads to strong correlations of the rate asymmetries: Whenever one rate is strand biased, the other two rates are likely to show the same bias. Furthermore, we determine all three rate asymmetries as a function of time: the A --> G and G --> T rate asymmetries are both found to be constant in time, whereas the C --> T rate asymmetry shows a pronounced time dependence, an observation that explains the difference between our results and those of an earlier work by Green et al. (2003. Transcription-associated mutational asymmetry in mammalian evolution. Nat Genet. 33:514-517.). Finally, we show that in addition to transcription also the replication process biases the substitution rates in genes.

Mutations induced by bacteriophage T7 RNA polymerase and their effects on the composition of the T7 genome

We show here that transcription by the bacteriophage T7 RNA polymerase increases the deamination of cytosine bases in the non-transcribed strand to uracil, causing C to T mutations in that strand. Under optimal conditions, the mutation frequency increases about fivefold over background, and is similar to that seen with the Escherichia coli RNA polymerase. Further, we found that a mutant T7 RNA polymerase with a slower rate of elongation caused more cytosine deaminations than its wild-type parent. These results suggest that promoting cytosine deamination in the non-transcribed strand is a general property of transcription in E. coli and is dependent on the length of time the transcription bubble stays open during elongation. To see if transcription-induced mutations have influenced the evolution of bacteriophage T7, we analyzed its genome for a bias in base composition. Our analysis showed a significant excess of thymine over cytosine bases in the highly transcribed regions of the genome. Moreover, the average value of this bias correlated well with the levels of transcription of different genomic regions. Our results indicate that transcription-induced mutations have altered the composition of bacteriophage T7 genome and suggest that this may be a significant force in genome evolution.

Similarity pattern analysis in mutational distributions

The validity and applicability of the statistical procedure - similarity pattern analysis (SPAN) - to the study of mutational distributions (MDs) was demonstrated with two sets of data. The first was mutational spectra (MS) for 697 GC to AT transitions produced with eight alkylating agents (AAs) in the lacI gene of Escherichia coli. The second was a recently summarized data on the distributions of 11562 spontaneous, radiation- and chemical-induced forward mutations in the ad-3 region of heterokaryon 12 of Neurospora crassa. They were analyzed as large two-way contingency tables (CTs) where two kinds of profiles were compared: site (or genotypic class) profiles and origin (or mutagen) profiles. To measure similarity (homogeneity) between any pair of profiles, the relevant sufficient statistics, Kastenbaum-Hirotsu squared distance (KHi(2)), was used. Collapsing the similar profiles into distinct internally homogeneous clusters named 'collapsets' revealed their similarity pattern. To facilitate the procedure, the computer program, COLLAPSE, was elaborated. The results of SPAN for the lacI spectra were found comparable with the results of their previous analysis with two multivariate statistical methods, the factor and cluster analyses. In the ad-3 data set, five collapsets were revealed among origin profiles (OPs): (I) ENU = 4NQO = 4HAQO = FANFT = SQ18506; (II) AF-2 = EI = MMS = DEP; (III) ETO = UV; (IV) AHA = PROCARB; and (V) He ions = protons. Moreover, the previous observation that MDs are dose-dependent was confirmed for X-ray-induced MDs. Profiles induced with the low doses of X-rays are similar to that induced with 85Sr, and profiles induced with the medium X-ray doses to those induced with protons and He ions. Evaluated similarities appear to be rather reasonable: mutagens with similar mode of action induce similar MDs. Similarity pattern revealed among genotypic class profiles (GCPs) seems to be also interpretable. When supplemented with descriptive cluster analysis, SPAN appears to be a fruitful methodology in MS analysis.