Identification of mRNA 5' cap-associated proteins in the human malaria parasite Plasmodium falciparum.

Eukaryotic messenger RNA is translated via a 5' cap-dependent initiation mechanism. Experimental evidence for proteins involved with translation initiation among eukaryotic parasites is lacking, including Plasmodium falciparum, the human malaria parasite. Native P. falciparum proteins from asexual stage parasites were enriched using a 5' cap affinity matrix. Proteomic analysis of enriched protein eluates revealed proteins putatively associated with the 5' cap. The canonical 5' cap-binding protein eIF4E (PF3D7_0315100) was the most reproducibly enriched protein. The eIF4A and eIF4G proteins hypothesized to form the eIF4F initiation complex with eIF4E were also detected as 5' cap enriched, albeit with low reproducibility. Surprisingly, enolase (ENO) was the second most enriched protein after eIF4E. Recombinant ENO protein did not demonstrate 5' cap activity, suggesting an indirect association of the native ENO with the 5' cap.

The Thai reference exome (T-REx) variant database.

To maximize the potential of genomics in medicine, it is essential to establish databases of genomic variants for ethno-geographic groups that can be used for filtering and prioritizing candidate pathogenic variants. Populations with non-European ancestry are poorly represented among current genomic variant databases. Here, we report the first high-density survey of genomic variants for the Thai population, the Thai Reference Exome (T-REx) variant database. T-REx comprises exome sequencing data of 1092 unrelated Thai individuals. The targeted exome regions common among four capture platforms cover 30.04 Mbp on autosomes and chromosome X. 345 681 short variants (18.27% of which are novel) and 34 907 copy number variations were found. Principal component analysis on 38 469 single nucleotide variants present worldwide showed that the Thai population is most genetically similar to East and Southeast Asian populations. Moreover, unsupervised clustering revealed six Thai subpopulations consistent with the evidence of gene flow from neighboring populations. The prevalence of common pathogenic variants in T-REx was investigated in detail, which revealed subpopulation-specific patterns, in particular variants associated with erythrocyte disorders such as the HbE variant in HBB and the Viangchan variant in G6PD. T-REx serves as a pivotal addition to the current databases for genomic medicine.

A cell-based ribozyme reporter system employing a chromosomally-integrated 5' exonuclease gene.

BACKGROUND: Bioinformatic genome surveys indicate that self-cleaving ribonucleic acids (ribozymes) appear to be widespread among all domains of life, although the functions of only a small number have been validated by biochemical methods. Alternatively, cell-based reporter gene assays can be used to validate ribozyme function. However, reporter activity can be confounded by phenomena unrelated to ribozyme-mediated cleavage of RNA. RESULTS: We established a ribozyme reporter system in Escherichia coli in which a significant reduction of reporter activity is manifest when an active ribozyme sequence is fused to the reporter gene and the expression of a foreign Bacillus subtilis RNaseJ1 5' exonuclease is induced from a chromosomally-integrated gene in the same cell. CONCLUSIONS: The reporter system could be useful for validating ribozyme function in candidate sequences identified from bioinformatics.

IPCAPS: an R package for iterative pruning to capture population structure.

BACKGROUND: Resolving population genetic structure is challenging, especially when dealing with closely related or geographically confined populations. Although Principal Component Analysis (PCA)-based methods and genomic variation with single nucleotide polymorphisms (SNPs) are widely used to describe shared genetic ancestry, improvements can be made especially when fine-scale population structure is the target. RESULTS: This work presents an R package called IPCAPS, which uses SNP information for resolving possibly fine-scale population structure. The IPCAPS routines are built on the iterative pruning Principal Component Analysis (ipPCA) framework that systematically assigns individuals to genetically similar subgroups. In each iteration, our tool is able to detect and eliminate outliers, hereby avoiding severe misclassification errors. CONCLUSIONS: IPCAPS supports different measurement scales for variables used to identify substructure. Hence, panels of gene expression and methylation data can be accommodated as well. The tool can also be applied in patient sub-phenotyping contexts. IPCAPS is developed in R and is freely available from http://bio3.giga.ulg.ac.be/ipcaps.

Insight into the peopling of Mainland Southeast Asia from Thai population genetic structure.

There is considerable ethno-linguistic and genetic variation among human populations in Asia, although tracing the origins of this diversity is complicated by migration events. Thailand is at the center of Mainland Southeast Asia (MSEA), a region within Asia that has not been extensively studied. Genetic substructure may exist in the Thai population, since waves of migration from southern China throughout its recent history may have contributed to substantial gene flow. Autosomal SNP data were collated for 438,503 markers from 992 Thai individuals. Using the available self-reported regional origin, four Thai subpopulations genetically distinct from each other and from other Asian populations were resolved by Neighbor-Joining analysis using a 41,569 marker subset. Using an independent Principal Components-based unsupervised clustering approach, four major MSEA subpopulations were resolved in which regional bias was apparent. A major ancestry component was common to these MSEA subpopulations and distinguishes them from other Asian subpopulations. On the other hand, these MSEA subpopulations were admixed with other ancestries, in particular one shared with Chinese. Subpopulation clustering using only Thai individuals and the complete marker set resolved four subpopulations, which are distributed differently across Thailand. A Sino-Thai subpopulation was concentrated in the Central region of Thailand, although this constituted a minority in an otherwise diverse region. Among the most highly differentiated markers which distinguish the Thai subpopulations, several map to regions known to affect phenotypic traits such as skin pigmentation and susceptibility to common diseases. The subpopulation patterns elucidated have important implications for evolutionary and medical genetics. The subpopulation structure within Thailand may reflect the contributions of different migrants throughout the history of MSEA. The information will also be important for genetic association studies to account for population-structure confounding effects.

Biomarker selection and classification of "-omics" data using a two-step bayes classification framework.

Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel two-step machine-learning framework is presented to address this need. First, a Naïve Bayes estimator is used to rank features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are then used in a Hidden Naïve Bayes classifier to construct a classification prediction model from these filtered attributes. In order to obtain the minimum set of the most informative biomarkers, the bottom-ranked features are successively removed from the Naïve Bayes-filtered feature list one at a time, and the classification accuracy of the Hidden Naïve Bayes classifier is checked for each pruned feature set. The performance of the proposed two-step Bayes classification framework was tested on different types of -omics datasets including gene expression microarray, single nucleotide polymorphism microarray (SNParray), and surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) proteomic data. The proposed two-step Bayes classification framework was equal to and, in some cases, outperformed other classification methods in terms of prediction accuracy, minimum number of classification markers, and computational time.