Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA Microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design microarray probes with high specificities and sensitivities. Highly specific probes correspond to probes having unique DNA sequences; whereas highly sensitive probes correspond to those with melting temperature within a desired range and having no secondary structure. The selection of these probes from a set of functional DNA sequences (exons) constitutes a computationally expensive discrete non-linear search problem. We delegate the search task to a simple yet effective Evolution Strategy algorithm. The computational efficiency is also greatly improved by making use of an available bioinformatics tool.

Lack of association between genetic markers on chromosome 16q22-Q24 and type 1 diabetes in Russian affected families

Aim To evaluate whether the T1D susceptibility locus on chromosome 16q contributes to the genetic susceptibility to T1D in Russian patients. Method Thirteen microsatellite markers, spanning a 47-centimorgan genomic region on 16q22-q24 were evaluated for linkage to T1D in 98 Russian multiplex families. Multipoint logarithm of odds (LOD) ratio (MLS) and nonparametric LOD (NPL) values were computed for each marker, using GENEHUNTER 2.1 software. Four microsatellites (D16S422, D16S504, D16S3037, and D16S3098) and 6 biallelic markers in 2 positional candidate genes, ICSBP1 and NQO1, were additionally tested for association with T1D in 114 simplex families, using transmission disequilibrium test (TDT). Results A peak of linkage (MLS = 1.35, NPL = 0.91) was shown for marker D16S750, but this was not significant (P = 0.18). The subsequent linkage analysis in the subset of 46 multiplex families carrying a common risk HLA-DR4 haplotype increased peak MLS and NPL values to 1.77 and 1.22, respectively, but showed no significant linkage (P = 0.11) to T1D in the 16q22-q24 genomic region. TDT analysis failed to find significant association between these markers and disease, even after the conditioning for the predisposing HLA-DR4 haplotype. Conclusion Our results did not support the evidence for the susceptibility locus to T1D on chromosome 16q22-24 in the Russian family data set. The lack of association could reflect genetic heterogeneity of type 1 diabetes in diverse ethnic groups.

Evaluation of IDDM8 susceptibility locus in a Russian simplex family data set

Type 1 diabetes (TID) susceptibility locus, IDDM8, has been accurately mapped to 200 kilobases at the terminal end of chromosome 6q27. This is within the region which harbours a cluster of three genes encoding proteasome subunit beta 1 (PMSB1), TATA-box binding protein (TBP) and a homologue of mouse programming cell death activator 2 (PDCD2). In this study, we evaluated whether these genes contribute to TID susceptibility using the transmission disequilibrium test of the data set from 114 affected Russian simplex families. The A allele of the G/A1180 single nucleotide polymorphism (SNP) at the PDCD2 gene, which was significant in its preferential transfer from parents to diabetic children (75 transmissions vs. 47 non-transmissionS, x(2) = 12.85, P corrected = 0.0038), was found to be associated with T1D. G/A1180 dimorphism and two other SNPs, C/T771 TBP and G/T(-271) PDCD2, were shown to share three common haplotypes, two of which (A-T-G and A-T-T) have been associated with higher development risk of TID. The third haplotype (G-T-G) was related to having a lower risk of disease. These findings suggest that the PDCD2 gene is a likely susceptibility gene for TID within IDDM8. However, it was not possible to exclude the TBP gene from being another putative susceptibility gene in this region. (c) 2005 Elsevier Ltd. All rights reserved.

Methicillin-resistant Staphylococcus aureus genotyping using a small set of polymorphisms

The aim of this study was to identify a set of genetic polymorphisms that efficiently divides methicillin-resistant Staphylococcus aureus (MRSA) strains into groups consistent with the population structure. The rationale was that such polymorphisms could underpin rapid real-time PCR or low-density array-based methods for monitoring MRSA dissemination in a cost-effective manner. Previously, the authors devised a computerized method for identifying sets of single nucleoticle polymorphisms (SNPs) with high resolving power that are defined by multilocus sequence typing (MLST) databases, and also developed a real-time PCR method for interrogating a seven-member SNP set for genotyping S. aureus. Here, it is shown that these seven SNPs efficiently resolve the major MRSA lineages and define 27 genotypes. The SNP-based genotypes are consistent with the MRSA population structure as defined by eBURST analysis. The capacity of binary markers to improve resolution was tested using 107 diverse MRSA isolates of Australian origin that encompass nine SNP-based genotypes. The addition of the virulence-associated genes cna, pvl and bbplsdrE, and the integrated plasmids pT181, p1258 and pUB110, resolved the nine SNP-based genotypes into 21 combinatorial genotypes. Subtyping of the SCCmec locus revealed new SCCmec types and increased the number of combinatorial genotypes to 24. It was concluded that these polymorphisms provide a facile means of assigning MRSA isolates into well-recognized lineages.