Central resources of variant discovery and annotation and its role in precision medicine.

Rapid technological advancement in high-throughput genomics, microarray, and deep sequencing technologies has accelerated the possibility of more complex precision medicine research using large amounts of heterogeneous health-related data from patients, including genomic variants. Genomic variants can be identified and annotated based on the reference human genome either within the sequence as a whole or in a putative functional genomic element. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) mutually created standards and guidelines for the appraisal of proof to expand consistency and straightforwardness in clinical variation interpretations. Various efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation. In the present study, several resources are highlighted with recognition and data spreading of clinically important genetic variations.

Enzymatic inhibitory activity of Ficus deltoidea leaf extract on matrix metalloproteinase-2, 8 and 9.

Dysregulation of matrix metalloproteinases (MMPs) activity is known in many pathological conditions with which most of the conditions are related to elevate MMPs activities. Ficus deltoidea (FD) is a plant known for its therapeutic properties. In order to evaluate the therapeutic potential of FD leaf extract, we study the enzymatic inhibition properties of FD leaf extract and its major bioactive compounds (vitexin and isovitexin) on a panel of MMPs (MMP-2, MMP-8 and MMP-9) using experimental and computational approaches. FD leaf extract and its major bioactive compounds showed pronounced inhibition activity towards the MMPs tested. Computational docking analysis revealed that vitexin and isovitexin bind to the active site of the three tested MMPs. We also evaluated the cytotoxicity and cell migration inhibition activity of FD leaf extract in the endothelial EA.hy 926 cell line. Conclusively, this study provided additional information on the potential of FD leaf extract for therapeutical application.

Transcriptogenomics identification and characterization of RNA editing sites in human primary monocytes using high-depth next generation sequencing data.

High-depth next generation sequencing data provide valuable insights into the number and distribution of RNA editing events. Here, we report the RNA editing events at cellular level of human primary monocyte using high-depth whole genomic and transcriptomic sequencing data. We identified over a ten thousand putative RNA editing sites and 69% of the sites were A-to-I editing sites. The sites enriched in repetitive sequences and intronic regions. High-depth sequencing datasets revealed that 90% of the canonical sites were edited at lower frequencies (<0.7). Single and multiple human monocytes and brain tissues samples were analyzed through genome sequence independent approach. The later approach was observed to identify more editing sites. Monocytes was observed to contain more C-to-U editing sites compared to brain tissues. Our results establish comparable pipeline that can address current limitations as well as demonstrate the potential for highly sensitive detection of RNA editing events in single cell type.

Experimental and computational approaches to reveal the potential of Ficus deltoidea leaves extract as α-amylase inhibitor.

Ficus deltoidea leaves extract are known to have good therapeutic properties such as antioxidant, anti-inflammatory and anti-diabetic. We showed that 50% ethanol-water extract of F. deltoidea leaves and its pungent compounds vitexin and isovitexin exhibited significant (p < 0.05) α-amylase inhibition with IC50 (vitexin: 4.6 µM [0.02 µg/mL]; isovitexin: 0.06 µg/mL [13.8 µM] and DPPH scavenging with IC50 (vitexin: 92.5 µM [0.4 µg/mL]; isovitexin: 0.5 µg/mL [115.4 µM]). Additionally, molecular docking analysis confirmed that vitexin has a higher binding affinity (-7.54 kcal/mol) towards α-amylase compared to isovitexin (-5.61 kcal/mol). On the other hand, the molecular dynamics findings showed that vitexin-α-amylase complex is more stable during the simulation of 20 ns when compared to the isovitexin-α-amylase complex. Our results suggest that vitexin is more potent and stable against α-amylase enzyme, thus it could develop as a therapeutic drug for the treatment of diabetes.

Transcriptome landscape of human primary monocytes at different sequencing depth.

Differential gene and transcript expression pattern of human primary monocytes from healthy young subjects were profiled under different sequencing depths (50M, 100M, and 200M reads). The raw data consisted of 1.3 billion reads generated from RNA sequencing (RNA-Seq) experiments. A total of 17,657 genes and 75,392 transcripts were obtained at sequencing depth of 200M. Total splice junction reads showed an even more significant increase. Comparative analysis of the expression patterns of immune-related genes revealed a total of 217 differentially expressed (DE) protein-coding genes and 50 DE novel transcripts, in which 40 DE protein-coding genes were related to the immune system. At higher sequencing depth, more genes, known and novel transcripts were identified and larger proportion of reads were allowed to map across splice junctions. The results also showed that increase in sequencing depth has no effect on the sequence alignment.

Transcriptome profiling of monocytes from XLA patients revealed the innate immune function dysregulation due to the BTK gene expression deficiency.

X-linked agammaglobulinemia (XLA) is a rare genetic disorder, caused by mutations in BTK (Bruton's Tyrosine Kinase) gene. Deep high-throughput RNA sequencing (RNA-Seq) approach was utilized to explore the possible differences in transcriptome profiles of primary monocytes in XLA patients compared with healthy subjects. Our analysis revealed the differences in expression of 1,827 protein-coding genes, 95 annotated long non-coding RNAs (lncRNAs) and 20 novel lincRNAs between XLA patients and healthy subjects. GO and KEGG pathway analysis of differentially expressed (DE) protein-coding genes showed downregulation of several innate immune-related genes and upregulation of oxidative phosphorylation and apoptosis-related genes in XLA patients compared to the healthy subjects. Moreover, the functional prediction analysis of DE lncRNAs revealed their potential role in regulating the monocytes cell cycle and apoptosis in XLA patients. Our results suggested that BTK mutations may contribute to the dysregulation of innate immune system and increase susceptibility to apoptosis in monocytes of XLA patients. This study provides significant finding on the regulation of BTK gene in monocytes and the potential for development of innovative biomarkers and therapeutic monitoring strategies to increase the quality of life in XLA patients.

Draft Genome Sequence of a Biosurfactant-Producing Bacillus subtilis UMX-103 Isolated from Hydrocarbon-Contaminated Soil in Terengganu, Malaysia.

The draft genome here presents the sequence of Bacillus subtilis UMX-103. The bacterial strain was isolated from hydrocarbon-contaminated soil from Terengganu, Malaysia. The whole genome of the bacterium was sequenced using Illumina HiSeq 2000 sequencing platform. The genome was assembled using de novo approach. The genome size of UMX-103 is 4,234,627 bp with 4399 genes comprising 4301 protein-coding genes and 98 RNA genes. The analysis of assembled genes revealed the presence of 25 genes involved in biosurfactant production, where 14 of the genes are related to biosynthesis and 11 of the genes are in the regulation of biosurfactant productions. This draft genome will provide insights into the genetic bases of its biosurfactant-producing capabilities.

Toward a Reference Gene Catalog of Human Primary Monocytes.

Transcriptome analyses based on high-throughput RNA sequencing (RNA-Seq) provide powerful and quantitative characterization of cell types and in-depth understanding of biological systems in health and disease. In this study, we present a comprehensive transcriptome profile of human primary monocytes, a crucial component of the innate immune system. We performed deep RNA-Seq of monocytes from six healthy subjects and integrated our data with 10 other publicly available RNA-Seq datasets of human monocytes. A total of 1.9 billion reads were generated, which allowed us to capture most of the genes transcribed in human monocytes, including 11,994 protein-coding genes, 5558 noncoding genes (including long noncoding RNAs, precursor miRNAs, and others), 2819 pseudogenes, and 7034 putative novel transcripts. In addition, we profiled the expression pattern of 1155 transcription factors (TFs) in human monocytes, which are the main molecules in controlling the gene transcription. An interaction network was constructed among the top expressed TFs and their targeted genes, which revealed the potential key regulatory genes in biological function of human monocytes. The gene catalog of human primary monocytes provided in this study offers significant promise and future potential clinical applications in the fields of precision medicine, systems diagnostics, immunogenomics, and the development of innovative biomarkers and therapeutic monitoring strategies.

Long non-coding RNA expression in primary human monocytes.

Long non-coding RNAs (lncRNAs) have been shown to possess a wide range of functions in both cellular and developmental processes including cancers. Although some of the lncRNAs have been implicated in the regulation of the immune response, the exact function of the large majority of lncRNAs still remains unknown. In this study, we characterized the lncRNAs in human primary monocytes, an essential component of the innate immune system. We performed RNA sequencing of monocytes from four individuals and combined our data with eleven other publicly available datasets. Our analysis led to identification of ~8000 lncRNAs of which >1000 have not been previously reported in monocytes. PCR-based validation of a subset of the identified novel long intergenic noncoding RNAs (lincRNAs) revealed distinct expression patterns. Our study provides a landscape of lncRNAs in monocytes, which could facilitate future experimental studies to characterize the functions of these molecules in the innate immune system.

The first Malay database toward the ethnic-specific target molecular variation.

BACKGROUND: The Malaysian Node of the Human Variome Project (MyHVP) is one of the eighteen official Human Variome Project (HVP) country-specific nodes. Since its inception in 9(th) October 2010, MyHVP has attracted the significant number of Malaysian clinicians and researchers to participate and contribute their data to this project. MyHVP also act as the center of coordination for genotypic and phenotypic variation studies of the Malaysian population. A specialized database was developed to store and manage the data based on genetic variations which also associated with health and disease of Malaysian ethnic groups. This ethnic-specific database is called the Malaysian Node of the Human Variome Project database (MyHVPDb). FINDINGS: Currently, MyHVPDb provides only information about the genetic variations and mutations found in the Malays. In the near future, it will expand for the other Malaysian ethnics as well. The data sets are specified based on diseases or genetic mutation types which have three main subcategories: Single Nucleotide Polymorphism (SNP), Copy Number Variation (CNV) followed by the mutations which code for the common diseases among Malaysians. MyHVPDb has been open to the local researchers, academicians and students through the registration at the portal of MyHVP ( http://hvpmalaysia.kk.usm.my/mhgvc/index.php?id=register ). CONCLUSIONS: This database would be useful for clinicians and researchers who are interested in doing a study on genomics population and genetic diseases in order to obtain up-to-date and accurate information regarding the population-specific variations and also useful for those in countries with similar ethnic background.

Growth curves for school children from Kuching, Sarawak: a methodological development.

In this article, the authors propose reference curves for height and weight for school children in the Kuching area, Sarawak. The school children were from primary to secondary schools (aged 6.5 to 17 years old) and comprised both genders. Anthropometric measurements and demographic information for 3081 school-aged children were collected (1440 boys and 1641 girls). Fitted line plots and percentiles for height and weight (3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles) were obtained. The height of school boys and school girls were almost similar at the start of their school-going age. For school girls, height and weight values stabilized when they reached 16 or 17 years old but kept increasing for school boys. School boys were taller than school girls as they entered adolescence. Height differences between school boys and school girls became significantly wider as they grew older. Chinese school children were taller and heavier than those of other ethnic groups.

Malaysian growth centiles for children under six years old.

BACKGROUND: Growth references are useful for the screening, assessment and monitoring of individual children as well as for evaluating various growth promoting interventions that could possibly affect a child in early life. AIM: To determine the growth centiles of Malaysian children and to establish contemporary cross-sectional growth reference charts for height and weight from birth to 6 years of age based on a representative sample of children from Malaysia. METHODS: Gender- and age-specific centile curves for height and weight were derived using the Cole's LMS method. Data for this study were retrieved from Malaysian government health clinics using a two-stage stratified random sampling technique. Assessment of nutritional status was done with the SD scores (Z-scores) of WHO 2006 standards. RESULTS: Boys were found to be taller and heavier than girls in this study. The median length of Malaysian children was higher than the WHO 2006 standards and CDC 2000 reference. The overall prevalence of stunting and underweight were 8.3% and 9.3%, respectively. CONCLUSIONS: This study presents the first large-scale initiative for local reference charts. The growth reference would enable the growth assessment of a Malaysian child compared to the average growth of children in the country. It is suggested that the use of WHO 2006 Child Growth Standards should be complemented with local reference charts for a more wholesome growth assessment.

Amino acid sequence and structural comparison of BACE1 and BACE2 using evolutionary trace method.

Beta-amyloid precursor protein cleavage enzyme 1 (BACE1) and beta-amyloid precursor protein cleavage enzyme 2 (BACE2), members of aspartyl protease family, are close homologues and have high similarity in their protein crystal structures. However, their enzymatic properties differ leading to disparate clinical consequences. In order to identify the residues that are responsible for such differences, we used evolutionary trace (ET) method to compare the amino acid conservation patterns of BACE1 and BACE2 in several mammalian species. We found that, in BACE1 and BACE2 structures, most of the ligand binding sites are conserved which indicate their enzymatic property of aspartyl protease family members. The other conserved residues are more or less randomly localized in other parts of the structures. Four group-specific residues were identified at the ligand binding site of BACE1 and BACE2. We postulated that these residues would be essential for selectivity of BACE1 and BACE2 biological functions and could be sites of interest for the design of selective inhibitors targeting either BACE1 or BACE2.

A comparative analysis of synonymous codon usage bias pattern in human albumin superfamily.

Synonymous codon usage bias is an inevitable phenomenon in organismic taxa across the three domains of life. Though the frequency of codon usage is not equal across species and within genome in the same species, the phenomenon is non random and is tissue-specific. Several factors such as GC content, nucleotide distribution, protein hydropathy, protein secondary structure, and translational selection are reported to contribute to codon usage preference. The synonymous codon usage patterns can be helpful in revealing the expression pattern of genes as well as the evolutionary relationship between the sequences. In this study, synonymous codon usage bias patterns were determined for the evolutionarily close proteins of albumin superfamily, namely, albumin, α-fetoprotein, afamin, and vitamin D-binding protein. Our study demonstrated that the genes of the four albumin superfamily members have low GC content and high values of effective number of codons (ENC) suggesting high expressivity of these genes and less bias in codon usage preferences. This study also provided evidence that the albumin superfamily members are not subjected to mutational selection pressure.

First comprehensive in silico analysis of the functional and structural consequences of SNPs in human GalNAc-T1 gene.

GalNAc-T1, a key candidate of GalNac-transferases genes family that is involved in mucin-type O-linked glycosylation pathway, is expressed in most biological tissues and cell types. Despite the reported association of GalNAc-T1 gene mutations with human disease susceptibility, the comprehensive computational analysis of coding, noncoding and regulatory SNPs, and their functional impacts on protein level, still remains unknown. Therefore, sequence- and structure-based computational tools were employed to screen the entire listed coding SNPs of GalNAc-T1 gene in order to identify and characterize them. Our concordant in silico analysis by SIFT, PolyPhen-2, PANTHER-cSNP, and SNPeffect tools, identified the potential nsSNPs (S143P, G258V, and Y414D variants) from 18 nsSNPs of GalNAc-T1. Additionally, 2 regulatory SNPs (rs72964406 and #x26; rs34304568) were also identified in GalNAc-T1 by using FastSNP tool. Using multiple computational approaches, we have systematically classified the functional mutations in regulatory and coding regions that can modify expression and function of GalNAc-T1 enzyme. These genetic variants can further assist in better understanding the wide range of disease susceptibility associated with the mucin-based cell signalling and pathogenic binding, and may help to develop novel therapeutic elements for associated diseases.

A whole genome analyses of genetic variants in two Kelantan Malay individuals.

BACKGROUND: The sequencing of two members of the Royal Kelantan Malay family genomes will provide insights on the Kelantan Malay whole genome sequences. The two Kelantan Malay genomes were analyzed for the SNP markers associated with thalassemia and Helicobacter pylori infection. Helicobacter pylori infection was reported to be low prevalence in the north-east as compared to the west coast of the Peninsular Malaysia and beta-thalassemia was known to be one of the most common inherited and genetic disorder in Malaysia. RESULT: By combining SNP information from literatures, GWAS study and NCBI ClinVar, 18 unique SNPs were selected for further analysis. From these 18 SNPs, 10 SNPs came from previous study of Helicobacter pylori infection among Malay patients, 6 SNPs were from NCBI ClinVar and 2 SNPs from GWAS studies. The analysis reveals that both Royal Kelantan Malay genomes shared all the 10 SNPs identified by Maran (Single Nucleotide Polymorphims (SNPs) genotypic profiling of Malay patients with and without Helicobacter pylori infection in Kelantan, 2011) and one SNP from GWAS study. In addition, the analysis also reveals that both Royal Kelantan Malay genomes shared 3 SNP markers; HBG1 (rs1061234), HBB (rs1609812) and BCL11A (rs766432) where all three markers were associated with beta-thalassemia. CONCLUSIONS: Our findings suggest that the Royal Kelantan Malays carry the SNPs which are associated with protection to Helicobacter pylori infection. In addition they also carry SNPs which are associated with beta-thalassemia. These findings are in line with the findings by other researchers who conducted studies on thalassemia and Helicobacter pylori infection in the non-royal Malay population.

Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods.

BACKGROUND: Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. RESULTS: In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. CONCLUSIONS: The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies.

Feature selection methods for optimizing clinicopathologic input variables in oral cancer prognosis.

The incidence of oral cancer is high for those of Indian ethnic origin in Malaysia. Various clinical and pathological data are usually used in oral cancer prognosis. However, due to time, cost and tissue limitations, the number of prognosis variables need to be reduced. In this research, we demonstrated the use of feature selection methods to select a subset of variables that is highly predictive of oral cancer prognosis. The objective is to reduce the number of input variables, thus to identify the key clinicopathologic (input) variables of oral cancer prognosis based on the data collected in the Malaysian scenario. Two feature selection methods, genetic algorithm (wrapper approach) and Pearson's correlation coefficient (filter approach) were implemented and compared with single-input models and a full-input model. The results showed that the reduced models with feature selection method are able to produce more accurate prognosis results than the full-input model and single-input model, with the Pearson's correlation coefficient achieving the most promising results.

Computational docking of L-arginine and its structural analogues to C-terminal domain of Escherichia coli arginine repressor protein (ArgRc).

The arginine repressor (ArgR) of Escherichia coli binds to six L-arginine molecules that act as its co-repressor in order to bind to DNA. The binding of L-arginine molecules as well as its structural analogues is compared by means of computational docking. A grid-based energy evaluation method combined with a Monte Carlo simulated annealing process was used in the automated docking. For all ligands, the docking procedure proposed more than one binding site in the C-terminal domain of ArgR (ArgRc). Interaction patterns of ArgRc with L-arginine were also observed for L-canavanine and L-citrulline. L-lysine and L-homoarginine, on the other hand, were shown to bind poorly at the binding site. Figure A general overview of the sites found from docking the various ligands into ArgRc ( grey ribbons). Red coloured sticks: residues in binding site H that was selected for docking