Bacterial communities on facial skin of teenage and elderly Thai females.

The Human Microbiome Project was first established to understand the roles of human-associated microbes to human health and disease. This study presents preliminary findings of Thai female facial skin microbiome using three pooled samples from groups of skin microbiome profiles, namely (1) healthy and (2) acne-prone young adults (teenage.hea and teenage.acn) and (3) healthy elderly adults (elderly.hea) based on standard dermatological criteria. These samples were sequenced using 454-pyrosequencing targeting 16S rRNA (V3-V4 regions). Good's coverage index of greater than 92% shows sufficient sampling of our data for each group. Three unique OTUs for each microbiome profile (43, 258 and 59 for teenage.hea, teenage.acn and ederly.hea, respectively) were obtained with 134 shared OTUs among the three datasets. Based on Morisita-Horn similarity coefficient, age is the major factor that brings the community relationship factor closer. The comparison among the three datasets reveal majority of Gemmatimonadetes, Planctomycetes and Nitrospirae in the teenage.hea, whereas Firmicutes are more prevalent in teenage.acn and elderly.hea skin types. In addition, when comparing Thai facial microbial diversity with the 16S data from U.S. forehead female database, significant differences were found among orders of bacteria, pointing to possible differences in human ecto-flora.

Structural and functional diversity of free-living microorganisms in reef surface, Kra island, Thailand.

BACKGROUND: Coral reefs worldwide are being harmed through anthropogenic activities. Some coral reefs in Thailand remain well-preserved, including the shallow coral reefs along Kra island, Nakhon Si Thammarat province. Interestingly, the microbial community in this environment remains unknown. The present study identified biodiversity of prokaryotes and eukaryotes of 0.22-30 µm in sizes and their metabolic potentials in this coral reef surface in summer and winter seasons, using 16S and 18S rRNA genes pyrosequencing. RESULTS: The marine microbial profiles in summer and winter seasons comprised mainly of bacteria, in phylum, particular the Proteobacteria. Yet, different bacterial and eukaryotic structures existed between summer and winter seasons, supported by low Lennon and Yue & Clayton theta similarity indices (8.48-10.43% for 16S rRNA, 0.32-7.81% for 18S rRNA ). The topmost prokaryotic phylum for the summer was Proteobacteria (99.68%), while for the winter Proteobacteria (62.49%) and Bacteroidetes (35.88%) were the most prevalent. Uncultured bacteria in phyla Cyanobacteria, Planctomycetes, SAR406 and SBR1093 were absent in the summer. For eukaryotic profiles, species belonging to animals predominated in the summer, correlating with high animal activities in the summer, whereas dormancy and sporulation predominated in the winter. For the winter, eukaryotic plant species predominated and several diverse species were detected. Moreover, comparison of our prokaryotic databases in summer and winter of Kra reef surface against worldwide marine culture-independent prokaryotic databases indicated our databases to most resemblance those of coastal Sichang island, Chonburi province, Thailand, and the 3 tropical GOS sites close to Galapagos island (GS039, GS040 and GS045), in orderly. CONCLUSIONS: The study investigated and obtained culture-independent databases for marine prokaryotes and eukaryotes in summer and winter seasons of Kra reef surface. The data helped understand seasonal dynamics of microbial structures and metabolic potentials of this tropical ecosystem, supporting the knowledge of the world marine microbial biodiversity.

Population structure of four Thai indigenous chicken breeds.

BACKGROUND: In recent years, Thai indigenous chickens have increasingly been bred as an alternative in Thailand poultry market. Due to their popularity, there is a clear need to improve the underlying quality and productivity of these chickens. Studying chicken genetic variation can improve the chicken meat quality as well as conserving rare chicken species. To begin with, a minimal set of molecular markers that can characterize the Thai indigenous chicken breeds is required. RESULTS: Using AFLP-PCR, 30 single nucleotide polymorphisms (SNPs) from Thai indigenous chickens were obtained by DNA sequencing. From these SNPs, we genotyped 465 chickens from 7 chicken breeds, comprising four Thai indigenous chicken breeds--Pradhuhangdum (PD), Luenghangkhao (LK), Dang (DA) and Chee (CH), one wild chicken--the red jungle fowls (RJF), and two commercial chicken breeds--the brown egg layer (BL) and commercial broiler (CB). The chicken genotypes reveal unique genetic structures of the four Thai indigenous chicken breeds. The average expected heterozygosities of PD=0.341, LK=0.357, DA=0.349 and CH=0.373, while the references RJF= 0.327, CB=0.324 and BL= 0.285. The F(ST) values among Thai indigenous chicken breeds vary from 0.051 to 0.096. The F(ST) values between the pairs of Thai indigenous chickens and RJF vary from 0.083 to 0.105 and the FST values between the Thai indigenous chickens and the two commercial chicken breeds vary from 0.116 to 0.221. A neighbour-joining tree of all individual chickens showed that the Thai indigenous chickens were clustered into four groups which were closely related to the wild RJF but far from the commercial breeds. Such commercial breeds were split into two closely groups. Using genetic admixture analysis, we observed that the Thai indigenous chicken breeds are likely to share common ancestors with the RJF, while both commercial chicken breeds share the same admixture pattern. CONCLUSION: These results indicated that the Thai indigenous chicken breeds may descend from the same ancestors. These indigenous chicken breeds were more closely related to red jungle fowls than those of the commercial breeds. These findings showed that the proposed SNP panel can effectively be used to characterize the four Thai indigenous chickens.

How bio-questionable are the different recombinant human erythropoietin copy products in Thailand?

PURPOSE: The high prevalence of pure red cell aplasia in Thailand has been associated with the sharp increase in number of recombinant human erythropoietin (rhEPO) copy products, based on a classical generic regulatory pathway, which have entered the market. This study aims to assess the quality of rhEPO copy products being used in Thailand. METHODS: Twelve rhEPO copy products were purchased from pharmacies in Thailand, shipped under controlled cold chain conditions to the Netherlands and characterized using (1) high performance size-exclusion chromatography, (2) asymmetrical flow field-flow fractionation, (3) sodium dodecyl sulfate polyacrylamide gel electrophoresis in combination with (4) Western blotting and additionally tested for (5) host cell protein impurities as well as (6) endotoxin contamination. RESULTS: Some of the tested rhEPO copy products showed high aggregate levels and contained a substantial amount of protein fragments. Also, one of rhEPO copy products had a high endotoxin level, exceeding the FDA limit. CONCLUSIONS: Our observations show that some of the tested copy products on the Thai market differ significantly from the originator rhEPO product, Epogen®. This comparison study supports a link between the quality attributes of copy rhEPO products and their immunogenicity.

MetaSel: a metaphase selection tool using a Gaussian-based classification technique.

BACKGROUND: Identification of good metaphase spreads is an important step in chromosome analysis for identifying individuals with genetic disorders. The process of finding suitable metaphase chromosomes for accurate clinical analysis is, however, very time consuming since they are selected manually. The selection of suitable metaphase chromosome spreads thus represents a major bottleneck for conventional cytogenetic analysis. Although many algorithms have been developed for karyotyping, none have adequately addressed the critical bottleneck of selecting suitable chromosome spreads. In this paper, we present a software tool that uses a simple rule-based system to efficiently identify metaphase spreads suitable for karyotyping. RESULTS: The chromosome shapes can be classified by the software into four main classes. The first and the second classes refer to individual chromosomes with straight and skewed shapes, respectively. The third class is characterized as those chromosomes with overlapping bodies and the fourth class is for the non-chromosome objects. Good metaphase spreads should largely contain chromosomes of the first and the second classes, while the third class should be kept minimal. Several image parameters were examined and used for creating rule-based classification. The threshold value for each parameter is determined using a statistical model. We observed that the Gaussian model can represent the empirical probability density function of the parameters and, hence, the threshold value can be easily determined. The proposed rules can efficiently and accurately classify the individual chromosome with > 90% accuracy. CONCLUSIONS: The software tool, termed MetaSel, was developed. Using the Gaussian-based rules, the tool can be used to quickly rank hundreds of chromosome spread images so as to assist cytogeneticists to perform karyotyping effectively. Furthermore, MetaSel offers an intuitive, yet comprehensive, workflow to assist karyotyping, including tools for editing chromosome (split, merge and fix) and a karyotyping editor (moving, rotating, and pairing homologous chromosomes). The program can be freely downloaded from "http://www4a.biotec.or.th/GI/tools/metasel".

Metagenomic profiles of free-living archaea, bacteria and small eukaryotes in coastal areas of Sichang island, Thailand.

BACKGROUND: Tha Wang and Tham Phang coasts, though situated at similar oceanographic positions on Sichang island, Chonburi province, Thailand, are different in bay geography and amount of municipal disturbances. These affect the marine ecosystems. The study used metagenomics combined with 16S and 18S rDNA pyrosequencing to identify types and distributions of archaea, bacteria, fungi and small eukaryotes of sizes ranges 0.45 and ~30 µm. RESULTS: Following the open bay geography and minimal municipal sewages, Tham Phang coast showed the cleaner water properties, described by color, salinity, pH, conductivity and percent dissolved oxygen. The 16S and 18S rDNA metagenomic profiles for Tha Wang and Tham Phang coasts revealed many differences, highlighting by low Lennon and Yue & Clayton theta similarity indices (66.03-73.03% for 16S rDNA profiles, 2.85-25.38% for 18S rDNA profiles). For 16S rDNA, the percent compositions of species belonging to Proteobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, Verrucomicrobia, Gammatimonadetes, Tenericutes, Acidobacteria, Spirochaetes, Chlamydiae, Euryarchaeota, Nitrospirae, Planctomycetes, Thermotogae and Aquificae were higher or distinctly present in Tha Wang. In Tham Phang, except Actinobacteria, the fewer number of prokaryotic species existed. For 18S rDNA, fungi represented 74.745% of the species in Tha Wang, whereas only 6.728% in Tham Phang. Basidiomycota (71.157%) and Ascomycota (3.060%) were the major phyla in Tha Wang. Indeed, Tha Wang-to-Tham Phang percent composition ratios for fungi Basidiomycota and Chytridiomycota were 1264.701 and 25.422, respectively. In Tham Phang, Brachiopoda (lamp shells) and Mollusca (snails) accounted for 80.380% of the 18S rDNA species detected, and their proportions were approximately tenfold greater than those in Tha Wang. Overall, coastal Tham Phang comprised abundant animal species. CONCLUSIONS: Tha Wang contained numerous archaea, bacteria and fungi, many of which could synthesize useful biotechnology gas and enzymes that could also function in high-saline and high-temperature conditions. Tham Phang contained less abundant archaea, bacteria and fungi, and the majority of the extracted metagenomes belonged to animal kingdom. Many microorganisms in Tham Phang were essential for nutrient-recycling and pharmaceuticals, for instances, Streptomyces, Pennicilium and Saccharomyces. Together, the study provided metagenomic profiles of free-living prokaryotes and eukaryotes in coastal areas of Sichang island.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies.

BACKGROUND: Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD). RESULTS: In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. CONCLUSION: iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci.

A novel maternally-derived insertional translocation resulting in partial trisomy 4q13.2-q22.1 with complex translocation t(8;20) in a family with intellectual disability.

We characterized the chromosomal aberration in family with intellectual disability, including two affected children and their affected mother. Initial standard karyotypes of the three individuals showed an apparently balanced translocation of chromosomes 8 and 20. Using molecular cytogenetic techniques, we observed complex structural chromosomal aberration comprising of reciprocal translocation between chromosomes 8 and 20 with pericentric inversion (8p11.12q22.3) and insertion of chromosome 4 segments into both der(8) and der(20). In particular, the insertion of chromosome 4 was complex. Two segments (4q13.2-q13.3 and 4q21.21-q22.1) were inserted into the der(8)t(8;20) breakpoint and one segment (4q13.3-q21.21) into the der(20)t(8;20) breakpoint. Both children inherited two normal chromosomes 4 from their parents and the der(8) and der(20) from the mother, resulting in partial trisomy of 4q13.2-q22.1. Interestingly, the mother, in addition to the same complex insertions and inversion, was founded to have a deletion of 4q13.2-q22.1 in one of her chromosomes 4, yielding no genetic imbalance but with potential disruption of intellectual dysfunction-related gene(s) at the breakpoints as the cause of her intellectual impairment. This family is the third case report of an insertional translocation mechanism causing partial trisomy 4q syndrome. Our study demonstrates that an insertion of an extra chromosomal segment, not primarily involving in translocation breakpoints, which results in partial trisomy, can be an unapparent cause of the abnormal phenotypes.

In-House Validation of Multiplex PCR for Simultaneous Detection of Shiga Toxin-Producing Escherichia coli, Listeria monocytogenes and Salmonella spp. in Raw Meats.

The aim of the study was to perform in-house validation of the developed multiplex PCR (mPCR)-based alternative method to detect Shiga toxin-producing Escherichia coli (STEC), Listeria monocytogenes (L. monocytogenes) and Salmonella spp. in raw meats following the ISO 16140-2: 2016. A comparative study of the developed mPCR against the Bacteriological Analytical Manual (BAM) method was evaluated for inclusivity and exclusivity, sensitivity and the relative level of detection (RLOD). Inclusivity levels for each target bacterium were all 100%, while exclusivity for non-target bacteria was 100%. The sensitivity of the developed mPCR was calculated based on the analysis of 72 samples of raw meat. The sensitivity of the developed mPCR was 100%. The RLOD values of the developed mPCR for STEC, L. monocytogenes and Salmonella spp. were 0.756, 1.170 and 1.000, respectively. The developed mPCR showed potential as a tool for the fast, specific and sensitive detection of the three bacteria in the raw meat industry.

Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure.

BACKGROUND: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis. RESULTS: A new heuristic called EigenDev for detecting population structure is presented. When tested on simulated data, this heuristic is robust to sample size. In contrast, the TW statistic was found to be susceptible to type I error, especially for large population samples. EigenDev is thus better-suited for analysis of large datasets containing many individuals, in which spurious patterns are likely to exist and could be incorrectly interpreted as population stratification. EigenDev was applied to the iterative pruning PCA (ipPCA) method, which resolves the underlying subpopulations. This subpopulation information was used to supervise STRUCTURE analysis to infer patterns of ancestry at an unprecedented level of resolution. To validate the new approach, a bovine and a large human genetic dataset (3945 individuals) were analyzed. We found new ancestry patterns consistent with the subpopulations resolved by ipPCA. CONCLUSIONS: The EigenDev heuristic is robust to sampling and is thus superior for detecting structure in large datasets. The application of EigenDev to the ipPCA algorithm improves the estimation of the number of subpopulations and the individual assignment accuracy, especially for very large and complex datasets. Furthermore, we have demonstrated that the structure resolved by this approach complements parametric analysis, allowing a much more comprehensive account of population structure. The new version of the ipPCA software with EigenDev incorporated can be downloaded from http://www4a.biotec.or.th/GI/tools/ippca.

An Implementation Framework for Telemedicine to Address Noncommunicable Diseases in Thailand.

To maintain the continuity of noncommunicable disease (NCD) services and ascertain the health outcomes of patients with NCDs during the COVID-19 (coronavirus disease 2019) outbreak in Thailand, various telemedicine services have been developed. To achieve this determination, the implementation framework has been constructed based on recommendations from multidisciplinary experts (Thai NCD Collaboration Group). Within the framework, all key elements are illustrated with their priority and expected collaborations. Ultimately, active collaborations from multi-stakeholders are vitally important to ensure that telemedicine services for NCDs will finally become practical, successful, and sustainable.

Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.

BACKGROUND: Purely epistatic multi-locus interactions cannot generally be detected via single-locus analysis in case-control studies of complex diseases. Recently, many two-locus and multi-locus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data. Furthermore, there is no explicit proof that a combination of multiple two-locus analyses can lead to the correct identification of multi-locus interactions. RESULTS: The proposed 2LOmb algorithm performs an omnibus permutation test on ensembles of two-locus analyses. The algorithm consists of four main steps: two-locus analysis, a permutation test, global p-value determination and a progressive search for the best ensemble. 2LOmb is benchmarked against an exhaustive two-locus analysis technique, a set association approach, a correlation-based feature selection (CFS) technique and a tuned ReliefF (TuRF) technique. The simulation results indicate that 2LOmb produces a low false-positive error. Moreover, 2LOmb has the best performance in terms of an ability to identify all causative single nucleotide polymorphisms (SNPs) and a low number of output SNPs in purely epistatic two-, three- and four-locus interaction problems. The interaction models constructed from the 2LOmb outputs via a multifactor dimensionality reduction (MDR) method are also included for the confirmation of epistasis detection. 2LOmb is subsequently applied to a type 2 diabetes mellitus (T2D) data set, which is obtained as a part of the UK genome-wide genetic epidemiology study by the Wellcome Trust Case Control Consortium (WTCCC). After primarily screening for SNPs that locate within or near 372 candidate genes and exhibit no marginal single-locus effects, the T2D data set is reduced to 7,065 SNPs from 370 genes. The 2LOmb search in the reduced T2D data reveals that four intronic SNPs in PGM1 (phosphoglucomutase 1), two intronic SNPs in LMX1A (LIM homeobox transcription factor 1, alpha), two intronic SNPs in PARK2 (Parkinson disease (autosomal recessive, juvenile) 2, parkin) and three intronic SNPs in GYS2 (glycogen synthase 2 (liver)) are associated with the disease. The 2LOmb result suggests that there is no interaction between each pair of the identified genes that can be described by purely epistatic two-locus interaction models. Moreover, there are no interactions between these four genes that can be described by purely epistatic multi-locus interaction models with marginal two-locus effects. The findings provide an alternative explanation for the aetiology of T2D in a UK population. CONCLUSION: An omnibus permutation test on ensembles of two-locus analyses can detect purely epistatic multi-locus interactions with marginal two-locus effects. The study also reveals that SNPs from large-scale or genome-wide case-control data which are discarded after single-locus analysis detects no association can still be useful for genetic epidemiology studies.

Iterative pruning PCA improves resolution of highly structured populations.

BACKGROUND: Non-random patterns of genetic variation exist among individuals in a population owing to a variety of evolutionary factors. Therefore, populations are structured into genetically distinct subpopulations. As genotypic datasets become ever larger, it is increasingly difficult to correctly estimate the number of subpopulations and assign individuals to them. The computationally efficient non-parametric, chiefly Principal Components Analysis (PCA)-based methods are thus becoming increasingly relied upon for population structure analysis. Current PCA-based methods can accurately detect structure; however, the accuracy in resolving subpopulations and assigning individuals to them is wanting. When subpopulations are closely related to one another, they overlap in PCA space and appear as a conglomerate. This problem is exacerbated when some subpopulations in the dataset are genetically far removed from others. We propose a novel PCA-based framework which addresses this shortcoming. RESULTS: A novel population structure analysis algorithm called iterative pruning PCA (ipPCA) was developed which assigns individuals to subpopulations and infers the total number of subpopulations present. Genotypic data from simulated and real population datasets with different degrees of structure were analyzed. For datasets with simple structures, the subpopulation assignments of individuals made by ipPCA were largely consistent with the STRUCTURE, BAPS and AWclust algorithms. On the other hand, highly structured populations containing many closely related subpopulations could be accurately resolved only by ipPCA, and not by other methods. CONCLUSION: The algorithm is computationally efficient and not constrained by the dataset complexity. This systematic subpopulation assignment approach removes the need for prior population labels, which could be advantageous when cryptic stratification is encountered in datasets containing individuals otherwise assumed to belong to a homogenous population.

RExPrimer: an integrated primer designing tool increases PCR effectiveness by avoiding 3' SNP-in-primer and mis-priming from structural variation.

BACKGROUND: Polymerase chain reaction (PCR) is very useful in many areas of molecular biology research. It is commonly observed that PCR success is critically dependent on design of an effective primer pair. Current tools for primer design do not adequately address the problem of PCR failure due to mis-priming on target-related sequences and structural variations in the genome. METHODS: We have developed an integrated graphical web-based application for primer design, called RExPrimer, which was written in Python language. The software uses Primer3 as the primer designing core algorithm. Locally stored sequence information and genomic variant information were hosted on MySQLv5.0 and were incorporated into RExPrimer. RESULTS: RExPrimer provides many functionalities for improved PCR primer design. Several databases, namely annotated human SNP databases, insertion/deletion (indel) polymorphisms database, pseudogene database, and structural genomic variation databases were integrated into RExPrimer, enabling an effective without-leaving-the-website validation of the resulting primers. By incorporating these databases, the primers reported by RExPrimer avoid mis-priming to related sequences (e.g. pseudogene, segmental duplication) as well as possible PCR failure because of structural polymorphisms (SNP, indel, and copy number variation (CNV)). To prevent mismatching caused by unexpected SNPs in the designed primers, in particular the 3' end (SNP-in-Primer), several SNP databases covering the broad range of population-specific SNP information are utilized to report SNPs present in the primer sequences. Population-specific SNP information also helps customize primer design for a specific population. Furthermore, RExPrimer offers a graphical user-friendly interface through the use of scalable vector graphic image that intuitively presents resulting primers along with the corresponding gene structure. In this study, we demonstrated the program effectiveness in successfully generating primers for strong homologous sequences. CONCLUSION: The improvements for primer design incorporated into RExPrimer were demonstrated to be effective in designing primers for challenging PCR experiments. Integration of SNP and structural variation databases allows for robust primer design for a variety of PCR applications, irrespective of the sequence complexity in the region of interest. This software is freely available at http://www4a.biotec.or.th/rexprimer.

pHCR: a parallel haplotype configuration reduction algorithm for haplotype interaction analysis.

Finding gene interaction models is one of the most important issues in genotype-phenotype association studies. This paper presents a model-free nonparametric statistical interaction analysis known as Parallel Haplotype Configuration Reduction (pHCR). This technique extends the original Multifactor Dimensionality Reduction (MDR) algorithm by using haplotype contribution values (c-values) and a haplotype interaction scheme instead of analyzing interactions among single-nucleotide polymorphisms. The proposed algorithm uses the statistical power of haplotypes to obtain a gene-gene interaction model. pHCR computes a statistical value for each haplotype, which contributes to the phenotype, and then performs haplotype interaction analysis on the basis of the cumulative c-value of each individual haplotype. To address the high computational complexity of pHCR, this paper also presents a scalable parallel computing solution. Nine common two-locus disease models were used to evaluate the algorithm performance under different scenarios. The results from all cases showed that pHCR shows higher power to detect gene-gene interaction in comparison with the results obtained from running MDR on the same data set. We also compared pHCR with FAMHAP, which mainly considers haplotype in the association analysis. For every experiment on the simulated data set, pHCR correctly produced haplotype interactions with much fewer false positives. We also challenged pHCR with a real data set input of beta-thalassemia/Hemoglobin E (HbE) disease. The result suggested the interaction between two previously reported quantitative trait loci of the fetal hemoglobin level, which is a major modifying factor, and disease severity of beta-thalassemia/HbE disease.

VarDetect: a nucleotide sequence variation exploratory tool.

BACKGROUND: Single nucleotide polymorphisms (SNPs) are the most commonly studied units of genetic variation. The discovery of such variation may help to identify causative gene mutations in monogenic diseases and SNPs associated with predisposing genes in complex diseases. Accurate detection of SNPs requires software that can correctly interpret chromatogram signals to nucleotides. RESULTS: We present VarDetect, a stand-alone nucleotide variation exploratory tool that automatically detects nucleotide variation from fluorescence based chromatogram traces. Accurate SNP base-calling is achieved using pre-calculated peak content ratios, and is enhanced by rules which account for common sequence reading artifacts. The proposed software tool is benchmarked against four other well-known SNP discovery software tools (PolyPhred, novoSNP, Genalys and Mutation Surveyor) using fluorescence based chromatograms from 15 human genes. These chromatograms were obtained from sequencing 16 two-pooled DNA samples; a total of 32 individual DNA samples. In this comparison of automatic SNP detection tools, VarDetect achieved the highest detection efficiency. AVAILABILITY: VarDetect is compatible with most major operating systems such as Microsoft Windows, Linux, and Mac OSX. The current version of VarDetect is freely available at http://www.biotec.or.th/GI/tools/vardetect.

Thailand mutation and variation database (ThaiMUT).

With the completion of the human genome project, novel sequencing and genotyping technologies had been utilized to detect mutations. Such mutations have continually been produced at exponential rate by researchers in various communities. Based on the population's mutation spectra, occurrences of Mendelian diseases are different across ethnic groups. A proportion of Mendelian diseases can be observed in some countries at higher rates than others. Recognizing the importance of mutation effects in Thailand, we established a National and Ethnic Mutation Database (NEMDB) for Thai people. This database, named Thailand Mutation and Variation database (ThaiMUT), offers a web-based access to genetic mutation and variation information in Thai population. This NEMDB initiative is an important informatics tool for both research and clinical purposes to retrieve and deposit human variation data. The mutation data cataloged in ThaiMUT database were derived from journal articles available in PubMed and local publications. In addition to collected mutation data, ThaiMUT also records genetic polymorphisms located in drug related genes. ThaiMUT could then provide useful information for clinical mutation screening services for Mendelian diseases and pharmacogenomic researches. ThaiMUT can be publicly accessed from http://gi.biotec.or.th/thaimut.

Association between ADAM33 polymorphisms and asthma in a Thai population.

ADAM33 (A Disintegrin And Metalloprotease 33) is an asthma susceptibility gene found across several human populations. However, no information on ADAM33 exists for Thai population. The objective of this study was to determine the association, if any, between ADAM33 polymorphisms and asthma in Thai subjects. Genotyping revealed 8 single nucleotide polymorphisms (SNPs) within the 3' region of the ADAM33 gene among 200 asthmatics and 100 control subjects. Asthmatic subjects were further sub-categorized into high and low severity groups. Multiple genetic model statistic tests for single-marker and haplotype association were carried out. Differences in allele frequencies at the SNPs rs528557/S2, rs598418 and rs44707/ST+4 in asthmatics were statistically significant compared to controls. The SNP rs528557/S2 could also be linked to the low severity group and the SNPs rs598418 and rs44707/ST+4 with the high severity group. Two-SNP haplotype analysis at the SNPs rs528557/S2 and rs598418 revealed a significant association with asthma. This study in a Thai population confirmed a positive association between ADAM33 polymorphisms and asthma susceptibility.

WASP: a Web-based Allele-Specific PCR assay designing tool for detecting SNPs and mutations.

BACKGROUND: Allele-specific (AS) Polymerase Chain Reaction is a convenient and inexpensive method for genotyping Single Nucleotide Polymorphisms (SNPs) and mutations. It is applied in many recent studies including population genetics, molecular genetics and pharmacogenomics. Using known AS primer design tools to create primers leads to cumbersome process to inexperience users since information about SNP/mutation must be acquired from public databases prior to the design. Furthermore, most of these tools do not offer the mismatch enhancement to designed primers. The available web applications do not provide user-friendly graphical input interface and intuitive visualization of their primer results. RESULTS: This work presents a web-based AS primer design application called WASP. This tool can efficiently design AS primers for human SNPs as well as mutations. To assist scientists with collecting necessary information about target polymorphisms, this tool provides a local SNP database containing over 10 million SNPs of various populations from public domain databases, namely NCBI dbSNP, HapMap and JSNP respectively. This database is tightly integrated with the tool so that users can perform the design for existing SNPs without going off the site. To guarantee specificity of AS primers, the proposed system incorporates a primer specificity enhancement technique widely used in experiment protocol. In particular, WASP makes use of different destabilizing effects by introducing one deliberate 'mismatch' at the penultimate (second to last of the 3'-end) base of AS primers to improve the resulting AS primers. Furthermore, WASP offers graphical user interface through scalable vector graphic (SVG) draw that allow users to select SNPs and graphically visualize designed primers and their conditions. CONCLUSION: WASP offers a tool for designing AS primers for both SNPs and mutations. By integrating the database for known SNPs (using gene ID or rs number), this tool facilitates the awkward process of getting flanking sequences and other related information from public SNP databases. It takes into account the underlying destabilizing effect to ensure the effectiveness of designed primers. With user-friendly SVG interface, WASP intuitively presents resulting designed primers, which assist users to export or to make further adjustment to the design. This software can be freely accessed at http://bioinfo.biotec.or.th/WASP.