This study aims to identify Acinetobacter of clinical isolates from the University of Malaya Medical Centre (UMMC), Kuala Lumpur, to the species level by 16S rDNA sequencing.
There is a need for country/population-specific databases because the existence of population-specific mutations for single gene disorders is well documented, and there is also good evidence for ethnic differences in the frequencies of genetic variations involved in complex disorders. Thus the Singapore Human Mutation/Polymorphism Database (SHMPD) was created to provide clinicians and scientists access to a central genetic database for the Singapore population. The data catalogued in the database include mutations identified in Singapore for Mendelian diseases, and frequencies of polymorphisms that have been investigated in either healthy controls or samples associated with specific phenotypes. Data from journal articles identified by searches in PubMed and other online resources, and via personal communications with researchers were compiled and assembled into a single database. Genes are categorized alphabetically and are also searchable by name and disease. The information provided for each variant of the gene includes the protein encoded, phenotype association, gender, size, and ethnic origin of the sample, as well as the reported genotype and allele frequencies, and direct links to the corresponding abstracts on PubMed. Our database will facilitate molecular diagnosis of Mendelian disorders and improve study designs for complex traits. It will be useful not only for researchers in Singapore, but also for those in countries with similar ethnic backgrounds, such as China, Taiwan, Hong Kong, Indonesia, and Malaysia.
The genetically polymorphic cytochrome P450 (CYP) 2A6 is the major nicotine-oxidase in humans that may contribute to nicotine dependence and cancer susceptibility. The authors investigated the types and frequencies of CYP2A6 alleles in the three major ethnic groups in Malaysia and CYP2A6*1A, CYP2A6*1B, CYP2A6*1x2, CYP2A6*2, CYP2A6*3, CYP2A6*4, CYP2A6*5, CYP2A6*7, CYP2A6*8 and CYP2A6*10 were determined by allele-specific polymerase chain reaction (PCR) in 270 Malays, 172 Chinese and 174 Indians. Except for CYP2A6*2 and *3 that were not detected in the Malays and Chinese, all the other alleles were detected. Frequencies for the CYP2A6*4 allele were 7, 5 and 2%, respectively, in Malays, Chinese and Indians. A statistically significant high frequency of the duplicated CYP2A6*1x2 allele occurred among Chinese. Among Malays and Chinese, the most common allele was CYP2A6*1B, but it was CYP2A6*1A among Indians. These ethnic difference in frequencies suggested that further studies are required to investigate the implications on diseases such as cancer and smoking behaviour among these major ethnic groups in Malaysia.
Recent advances in DNA sequencing technology have enabled elucidation of whole genome information from a plethora of organisms. In parallel with this technology, various bioinformatics tools have driven the comparative analysis of the genome sequences between species and within isolates. While drawing meaningful conclusions from a large amount of raw material, computer-aided identification of suitable targets for further experimental analysis and characterization, has also led to the prediction of non-human homologous essential genes in bacteria as promising candidates for novel drug discovery. Here, we present a comparative genomic analysis to identify essential genes in Burkholderia pseudomallei. Our in silico prediction has identified 312 essential genes which could also be potential drug candidates. These genes encode essential proteins to support the survival of B. pseudomallei including outer-inner membrane and surface structures, regulators, proteins involved in pathogenenicity, adaptation, chaperones as well as degradation of small and macromolecules, energy metabolism, information transfer, central/intermediate/miscellaneous metabolism pathways and some conserved hypothetical proteins of unknown function. Therefore, our in silico approach has enabled rapid screening and identification of potential drug targets for further characterization in the laboratory.
The Internet has been an integral part of the Information and Communication
Technology (ICT) community in recent years. New internet users have been
growing steadily over the years. This has lead to the depletion of new Internet
Protocol (IP) addresses worldwide. To overcome this predicament, the new
Internet Protocol version 6 (IPv6) had been introduced. The existing Internet
Protocol version 4 (IPv4) is expected to be eventually replaced by this IPv6.
The changeover from IPv4 to IPv6 is expected to be implemented progressively.
During this transition period, these two protocols are expected to coexist for
a number of years. IPv4-to-IPv6 transition tools have been designed to facilitate
a smooth transition from IPv4 to IPv6. The two most basic IPv4-to-IPv6
transition tools available are the hybrid stack mechanism and tunneling.
Tunneling is the encapsulation of IPv6 traffic within IPv4 packets so they can
be sent over an IPv4 infrastructure. This project was initiated to set up an
experimental IPv6 testbed, in order to study the performance as well as
transition and migration issues of IPv6 networks under controlled conditions.
This paper looks at how tunneling can be performed over existing internetwork
infrastructure at Fakulti Kejuruteraan Elektrik (FKE), UiTM.
For a given DNA sequence, it is well known that pair wise alignment schemes are used to determine the similarity with the DNA sequences available in the databanks. The efficiency of the alignment decides the type of amino acids and its corresponding proteins. In order to evaluate the given DNA sequence for its proteomic identity, a pattern matching approach is proposed in this paper. A block based semi-global alignment scheme is introduced to determine the similarity between the DNA sequences (known and given). The two DNA sequences are divided into blocks of equal length and alignment is performed which minimizes the computational complexity. The efficiency of the alignment scheme is evaluated using the parameter, percentage of similarity (POS). Four essential DNA version of the amino acids that emphasize the importance of proteomic functionalities are chosen as patterns and matching is performed with the known and given DNA sequences to determine the similarity between them. The ratio of amino acid counts between the two sequences is estimated and the results are compared with that of the POS value. It is found from the experimental results that higher the POS value and the pattern matching higher are the similarity between the two DNA sequences. The optimal block is also identified based on the POS value and amino acids count.
Oil palm is the second largest source of edible oil which contributes to approximately 20% of the world's production of oils and fats. In order to understand the molecular biology involved in in vitro propagation, flowering, efficient utilization of nitrogen sources and root diseases, we have initiated an expressed sequence tag (EST) analysis on oil palm.
The Singapore Genome Variation Project (SGVP) provides a publicly available resource of 1.6 million single nucleotide polymorphisms (SNPs) genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia. This online database catalogs information and summaries on genotype and phased haplotype data, including allele frequencies, assessment of linkage disequilibrium (LD), and recombination rates in a format similar to the International HapMap Project. Here, we introduce this resource and describe the analysis of human genomic variation upon agglomerating data from the HapMap and the Human Genome Diversity Project, providing useful insights into the population structure of the three major population groups in Asia. In addition, this resource also surveyed across the genome for variation in regional patterns of LD between the HapMap and SGVP populations, and for signatures of positive natural selection using two well-established metrics: iHS and XP-EHH. The raw and processed genetic data, together with all population genetic summaries, are publicly available for download and browsing through a web browser modeled with the Generic Genome Browser.
Protein-protein interactions (PPIs) play a significant role in many crucial cellular operations such as metabolism, signaling and regulations. The computational methods for predicting PPIs have shown tremendous growth in recent years, but problem such as huge false positive rates has contributed to the lack of solid PPI information. We aimed at enhancing the overlap between computational predictions and experimental results in an effort to partially remove PPIs falsely predicted. The use of protein function predictor named PFP() that are based on shared interacting domain patterns is introduced in this study with the purpose of aiding the Gene Ontology Annotations (GOA). We used GOA and PFP() as agents in a filtering process to reduce false positive pairs in the computationally predicted PPI datasets. The functions predicted by PFP() were extracted from cross-species PPI data in order to assign novel functional annotations for the uncharacterized proteins and also as additional functions for those that are already characterized by the GO (Gene Ontology). The implementation of PFP() managed to increase the chances of finding matching function annotation for the first rule in the filtration process as much as 20%. To assess the capability of the proposed framework in filtering false PPIs, we applied it on the available S. cerevisiae PPIs and measured the performance in two aspects, the improvement made indicated as Signal-to-Noise Ratio (SNR) and the strength of improvement, respectively. The proposed filtering framework significantly achieved better performance than without it in both metrics.
The frequencies of alleles implicated in drug-response variability provide vital information for public health management. Differences in frequencies between genetically diverse groups of individuals can hamper drug assessments, particularly in populations where clinical data are not readily available.
Signal transduction through protein-protein interactions and protein modifications are the main mechanisms controlling many biological processes. Here we described the implementation of MedScan information extraction technology and Pathway Studio software (Ariadne Genomics Inc.) to create a Salmonella specific molecular interaction database. Using the database, we have constructed several signal transduction pathways in Salmonella enterica serovar Typhi which causes Typhoid Fever, a major health threat especially in developing countries. S. Typhi has several pathogenicity islands that control rapid switching between different phenotypes including adhesion and colonization, invasion, intracellular survival, proliferation, and biofilm formation in response to environmental changes. Understanding of the detailed mechanism for S. Typhi survival in host cells is necessary for development of efficient detection and treatment of this pathogen. The constructed pathways were validated using publically available gene expression microarray data for Salmonella.
Genetic diseases are a pressing global health problem that requires comprehensive access to basic clinical and genetic data to counter. The creation of regional and international databases that can be easily accessed by clinicians and diagnostic labs will greatly improve our ability to accurately diagnose and treat patients with genetic disorders. The Human Variome Project is currently working in conjunction with human genetics societies to achieve this by establishing systems to collect every mutation reported by a diagnostic laboratory, clinic, or research laboratory in a country and store these within a national repository, or HVP Country Node. Nodes have already been initiated in Australia, Belgium, China, Egypt, Malaysia, and Kuwait. Each is examining how to systematically collect and share genetic, clinical, and biochemical information in a country-specific manner that is sensitive to local ethical and cultural issues. This article gathers cases of genetic data collection within countries and takes recommendations from the global community to develop a procedure for countries wishing to establish their own collection system as part of the Human Variome Project. We hope this may lead to standard practices to facilitate global collection of data and allow efficient use in clinical practice, research and therapy.
Vanda Mimi Palmer (VMP) is a highly sought as fragrant-orchid hybrid in Malaysia. It is economically important in cosmetic and beauty industries and also a famous potted ornamental plant. To date, no work on fragrance-related genes of vandaceous orchids has been reported from other research groups although the analysis of floral fragrance or volatiles have been extensively studied. An expressed sequence tag (EST) resource was developed for VMP principally to mine any potential fragrance-related expressed sequence tag-simple sequence repeat (EST-SSR) for future development as markers in the identification of fragrant vandaceous orchids endemic to Malaysia. Clustering, annotation and assembling of the ESTs identified 1,196 unigenes which defined 966 singletons and 230 contigs. The VMP dbEST was functionally classified by gene ontology (GO) into three groups: molecular functions (51.2%), cellular components (16.4%) and biological processes (24.6%) while the remaining 7.8% showed no hits with GO identifier. A total of 112 EST-SSR (9.4%) was mined on which at least five units of di-, tri-, tetra-, penta-, or hexa-nucleotide repeats were predicted. The di-nucleotide motif repeats appeared to be the most frequent repeats among the detected SSRs with the AT/TA types as the most abundant among the dimerics, while AAG/TTC, AGA/TCT-type were the most frequent trimerics. The mined EST-SSR is believed to be useful in the development of EST-SSR markers that is applicable in the screening and characterization of fragrance-related transcripts in closely related species.
We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 × 10(-7)). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci.
Gene expression data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. In order to select a small subset of informative genes from the data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence methods. However, due to the small number of samples compared to the huge number of genes (high dimension), irrelevant genes, and noisy genes, many of the computational methods face difficulties to select the small subset. Thus, we propose an improved (modified) binary particle swarm optimization to select the small subset of informative genes that is relevant for the cancer classification. In this proposed method, we introduce particles' speed for giving the rate at which a particle changes its position, and we propose a rule for updating particle's positions. By performing experiments on ten different gene expression datasets, we have found that the performance of the proposed method is superior to other previous related works, including the conventional version of binary particle swarm optimization (BPSO) in terms of classification accuracy and the number of selected genes. The proposed method also produces lower running times compared to BPSO.
Functional genomics has proven to be an efficient tool in identifying genes involved in various biological functions. However the availability of commercially important seaweed Eucheuma denticulatum functional resources is still limited. EuDBase is the first seaweed online repository that provides integrated access to ESTs of Eucheuma denticulatum generated from samples collected from Kudat and Semporna in Sabah, Malaysia. The database stored 10,031 ESTs that are clustered and assembled into 2,275 unique transcripts (UT) and 955 singletons. Raw data were automatically processed using ESTFrontier, an in-house automated EST analysis pipeline. Data was collected in MySQL database. Web interface is implemented using PHP and it allows browsing and querying EuDBase through search engine. Data is searchable via BLAST hit, domain search, Gene Ontology or KEGG Pathway. A user-friendly interface allows the identification of sequences either using a simple text query or similarity search. The development of EuDBase is initiated to store, manage and analyze the E. denticulatum ESTs and to provide accumulative digital resources for the use of global scientific community. EuDBase is freely available from http://www.inbiosis.ukm.my/eudbase/.
The HUGO Pan-Asian SNP consortium conducted the largest survey to date of human genetic diversity among Asians by sampling 1,719 unrelated individuals among 71 populations from China, India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, and Thailand. We have constructed a database (PanSNPdb), which contains these data and various new analyses of them. PanSNPdb is a research resource in the analysis of the population structure of Asian peoples, including linkage disequilibrium patterns, haplotype distributions, and copy number variations. Furthermore, PanSNPdb provides an interactive comparison with other SNP and CNV databases, including HapMap3, JSNP, dbSNP and DGV and thus provides a comprehensive resource of human genetic diversity. The information is accessible via a widely accepted graphical interface used in many genetic variation databases. Unrestricted access to PanSNPdb and any associated files is available at: http://www4a.biotec.or.th/PASNP.
Improving the quality of the non-climacteric fruit, pineapple, is possible with information on the expression of genes that occur during the process of fruit ripening. This can be made known though the generation of partial mRNA transcript sequences known as expressed sequence tags (ESTs). ESTs are useful not only for gene discovery but also function as a resource for the identification of molecular markers, such as simple sequence repeats (SSRs). This paper reports on firstly, the construction of a normalized library of the mature green pineapple fruit and secondly, the mining of EST-SSRs markers using the newly obtained pineapple ESTs as well as publically available pineapple ESTs deposited in GenBank. Sequencing of the clones from the EST library resulted in 282 good sequences. Assembly of sequences generated 168 unique transcripts (UTs) consisting of 34 contigs and 134 singletons with an average length of ≈500 bp. Annotation of the UTs categorized the known proteins transcripts into the three ontologies as: molecular function (34.88%), biological process (38.43%), and cellular component (26.69%). Approximately 7% (416) of the pineapple ESTs contained SSRs with an abundance of trinucleotide SSRs (48.3%) being identified. This was followed by dinucleotide and tetranucleotide SSRs with frequency of 46 and 57%, respectively. From these EST-containing SSRs, 355 (85.3%) matched to known proteins while 133 contained flanking regions for primer design. Both the ESTs were sequenced and the mined EST-SSRs will be useful in the understanding of non-climacteric ripening and the screening of biomarkers linked to fruit quality traits.
Y-Short Tandem Repeats (Y-STR) data consist of many similar and almost similar objects. This characteristic of Y-STR data causes two problems with partitioning: non-unique centroids and local minima problems. As a result, the existing partitioning algorithms produce poor clustering results.