Comparative study of the genetic variability in thymidine kinase and glycoprotein B genes of herpes simplex viruses by the RNase A mismatch cleavage method

Genotypic characterization of UL23 thymidine kinase and UL30 DNA polymerase of clinical isolates of herpes simplex virus: natural polymorphism and mutations associated with resistance to antivirals

The molecular mechanisms of herpes simplex virus (HSV) resistance to antiviral drugs interfering with viral DNA synthesis reported so far rely on the presence of mutations within UL23 (thymidine kinase [TK]) and UL30 (DNA polymerase) genes. The interpretation of genotypic antiviral resistance assay results requires the clear distinction between resistance mutations and natural interstrain sequence variations. The objectives of this work were to describe extensively the natural polymorphism of UL23 TK and UL30 DNA polymerase among HSV-1 and HSV-2 strains and the amino acid changes potentially associated with HSV resistance to antivirals. The sequence analysis of the full-length UL23 and UL30 genes was performed. Ninety-four drug-sensitive clinical isolates (43 HSV-1 and 51 HSV-2) and 3 laboratory strains (KOS, gHSV-2, and MS2) were studied for natural polymorphism, and 25 clinical isolates exhibiting phenotypic traits of resistance to antivirals were analyzed for drug resistance mutations. Our results showed that TK and DNA polymerase are highly conserved among HSV strains, with a weaker variability for HSV-2 strains. This study provided a precise map of the natural polymorphism of both viral enzymes among HSV-1 and HSV-2 isolates, with the identification of 15 and 51 polymorphisms never previously described for TK and DNA polymerase, respectively, which will facilitate the interpretation of genotypic antiviral-resistant testing. Moreover, the genotypic characterization of 25 drug-resistant HSV isolates revealed 8 new amino acid changes located in TK and potentially accounting for acyclovir (ACV) resistance.

Assessing dissimilarity of genes by comparing their RNAse A mismatch cleavage patterns

We propose a simple algorithm for estimating the number of nucleotide differences between a pair of RNA or DNA sequences through comparison of their RNAse A mismatch cleavage patterns. In the RNAse A mismatch cleavage technique two or more sample sequences are hybridized to the same RNA probe, the hybrids are partially digested with RNAse A, and the digestion products are compared on an electrophoretic gel. Here we provide an algorithm for converting the numbers of unique and matching electrophoretic bands into an estimate of the number of nucleotide differences between the sequences. Computer simulation indicates that the proposed method yields a robust estimate of the genetic distance despite stochastic errors and occasional violation of certain assumptions. Our study suggests that the method performs best when the distance between the sequences is < 15 differences. When the sequences under analysis are likely to have larger distances, we advise to substitute one long riboprobe with a set of shorter nonoverlapping probes. The new algorithm is applied to infer the proximity of several strains of pseudorabies virus.

Selection response in finite populations

Formulae were derived to predict genetic response under various selection schemes assuming an infinitesimal model. Account was taken of genetic drift, gametic (linkage) disequilibrium (Bulmer effect), inbreeding depression, common environmental variance, and both initial segregating variance within families (sigma AW02) and mutational (sigma M2) variance. The cumulative response to selection until generation t(CRt) can be approximated as [equation: see text] where Ne is the effective population size, sigma AW infinity 2 = Ne sigma M2 is the genetic variance within families at the steady state (or one-half the genic variance, which is unaffected by selection), and D is the inbreeding depression per unit of inbreeding. R0 is the selection response at generation 0 assuming preselection so that the linkage disequilibrium effect has stabilized. beta is the derivative of the logarithm of the asymptotic response with respect to the logarithm of the within-family genetic variance, i.e., their relative rate of change. R0 is the major determinant of the short term selection response, but sigma Me2 Ne and beta are also important for the long term. A selection method of high accuracy using family information gives a small Ne and will lead to a larger response in the short term and a smaller response in the long term, utilizing mutation less efficiently.