Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese.

Personalized medical care focuses on prediction of disease risk and response to medications. To build the risk models, access to both large-scale genomic resources and human genetic studies is required. The Taiwan Biobank (TWB) has generated high-coverage, whole-genome sequencing data from 1492 individuals and genome-wide SNP data from 103,106 individuals of Han Chinese ancestry using custom SNP arrays. Principal components analysis of the genotyping data showed that the full range of Han Chinese genetic variation was found in the cohort. The arrays also include thousands of known functional variants, allowing for simultaneous ascertainment of Mendelian disease-causing mutations and variants that affect drug metabolism. We found that 21.2% of the population are mutation carriers of autosomal recessive diseases, 3.1% have mutations in cancer-predisposing genes, and 87.3% carry variants that affect drug response. We highlight how TWB data provide insight into both population history and disease burden, while showing how widespread genetic testing can be used to improve clinical care.

Genome-wide analysis of copy number variations identifies PARK2 as a candidate gene for autism spectrum disorder.

BACKGROUND: Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder with complex genetic underpinning in its etiology. Copy number variations (CNVs) as one of the genetic factors associated with ASD have been addressed in recent genome-wide association studies (GWAS). However, the significance of CNV has not been well investigated in non-Caucasian ASD population. METHODS: To identify the pathogenic CNVs responsible for ASD in Han Chinese, we performed a segment-based GWAS of CNV in 335 ASD cases and 1093 healthy controls using Affymetrix single nucleotide polymorphism (SNP) array by focusing on case-specific CNVs. PARK2 was one of the important genes with several case-specific regions overlapped on it. The findings were validated in the initial screen sample set and replicated in another sample set by real-time quantitative PCR (qPCR). RESULTS: A total of six CNVs at 6q26 that spanned different exons of PARK2 were identified. The PARK2 expression level was down-regulated at exon-dependent manner in cases with either deletion or duplication. The result revealed that the gene function might be disrupted by exonic deletion and duplication. We also observed that the ASD case with exonic duplication demonstrated a more severe interference of PARK2 expression and the clinical feature than the ones with deletion at the exons 2-4 of the PARK2 gene. CONCLUSIONS: Our finding provides evidence to support that CNVs affecting PARK2 function might contribute to genetic etiology of a proportion of cases with ASD. The intriguing results of this work warrant further study on characterizing the functional impact of various exonic CNVs on the PARK2 gene. TRIAL REGISTRATION: ClinicalTrials.gov NCT00494754.

UPS 2.0: unique probe selector for probe design and oligonucleotide microarrays at the pangenomic/genomic level.

BACKGROUND: Nucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets. RESULTS: Algorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,Unique probe within a group,Unique probe in a specific Unigene set,Unique probe based on the pangenomic level, and Unique Probe in the user-defined genome/transcriptome, are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments. CONCLUSIONS: The UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at http://array.iis.sinica.edu.tw/ups/. Screen cast: http://array.iis.sinica.edu.tw/ups/demo/demo.htm.

PALM: a paralleled and integrated framework for phylogenetic inference with automatic likelihood model selectors.

BACKGROUND: Selecting an appropriate substitution model and deriving a tree topology for a given sequence set are essential in phylogenetic analysis. However, such time consuming, computationally intensive tasks rely on knowledge of substitution model theories and related expertise to run through all possible combinations of several separate programs. To ensure a thorough and efficient analysis and avert tedious manipulations of various programs, this work presents an intuitive framework, the phylogenetic reconstruction with automatic likelihood model selectors (PALM), with convincing, updated algorithms and a best-fit model selection mechanism for seamless phylogenetic analysis. METHODOLOGY: As an integrated framework of ClustalW, PhyML, MODELTEST, ProtTest, and several in-house programs, PALM evaluates the fitness of 56 substitution models for nucleotide sequences and 112 substitution models for protein sequences with scores in various criteria. The input for PALM can be either sequences in FASTA format or a sequence alignment file in PHYLIP format. To accelerate the computing of maximum likelihood and bootstrapping, this work integrates MPICH2/PhyML, PalmMonitor and Palm job controller across several machines with multiple processors and adopts the task parallelism approach. Moreover, an intuitive and interactive web component, PalmTree, is developed for displaying and operating the output tree with options of tree rooting, branches swapping, viewing the branch length values, and viewing bootstrapping score, as well as removing nodes to restart analysis iteratively. SIGNIFICANCE: The workflow of PALM is straightforward and coherent. Via a succinct, user-friendly interface, researchers unfamiliar with phylogenetic analysis can easily use this server to submit sequences, retrieve the output, and re-submit a job based on a previous result if some sequences are to be deleted or added for phylogenetic reconstruction. PALM results in an inference of phylogenetic relationship not only by vanquishing the computation difficulty of ML methods but also providing statistic methods for model selection and bootstrapping. The proposed approach can reduce calculation time, which is particularly relevant when querying a large data set. PALM can be accessed online at http://palm.iis.sinica.edu.tw.

The unique probe selector: a comprehensive web service for probe design and oligonucleotide arrays.

BACKGROUND: Nucleic acid hybridization, a fundamental technique in molecular biology, can be modified into very effective and sensitive methods for detecting particular targets mixed with millions of non-target sequences. Therefore, avoiding cross-hybridization is the most crucial issue for developing diagnostic methods based on hybridization. RESULTS: To develop a probe with a high discriminating power, this study constructed a web service, the Unique Probe Selector (UPS), for customized probe design. The UPS service integrates a probe design mechanism and a scoring system for evaluating the performance of probe annealing and the uniqueness of a probe in a user-defined genetic background. Starting from an intuitive web interface, the UPS accepts a query with single or multiple sequences in fasta format. The best probe(s) for each sequence can be downloaded from result pages in a fasta or .csv format with a summary of probe characteristics. The option "Unique probe within group" selects the most unique probe for each target sequence with low probability to hybridize to the other sequences in the same submitted query. The option "Unique probe in the specific organism" devises probes for each submitted sequence to identify its target among selected genetic backgrounds based on Unigene. CONCLUSION: The UPS evaluates probe-to-target hybridization under a user-defined condition in silico to ensure high-performance hybridization and minimizes the possibility of non-specific reactions. UPS has been applied to design human arrays for gene expression studies and to develop several small arrays of gene families that were inferred as molecular signatures of cancer typing/staging or pathogen signatures. Notably, UPS is freely accessible at http://array.iis.sinica.edu.tw/ups/.

Fly-DPI: database of protein interactomes for D. melanogaster in the approach of systems biology.

BACKGROUND: Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions. RESULTS: Three high-throughput yeast two-hybrid experiments and the collection in FlyBase were used as our starting datasets. The co-occurrences of domains in these interactive events are converted into a probability score of domain-domain interaction. These scores are used to infer putative interaction among all available open reading frames (ORFs) of fruit fly. Additionally, the likelihood function is used to estimate all potential protein-protein interactions. All parameters are successfully iterated and MLE is obtained for each pair of domains. Additionally, the maximized likelihood reaches its converged criteria and maintains the probability stable. The hybrid model achieves a high specificity with a loss of sensitivity, suggesting that the model may possess major features of protein-protein interactions. Several putative interactions predicted by the proposed hybrid model are supported by literatures, while experimental data with a low probability score indicate an uncertain reliability and require further proof of interaction.Fly-DPI is the online database used to present this work. It is an integrated proteomics tool with comprehensive protein annotation information from major databases as well as an effective means of predicting protein-protein interactions. As a novel search strategy, the ping-pong search is a naïve path map between two chosen proteins based on pre-computed shortest paths. Adopting effective filtering strategies will facilitate researchers in depicting the bird's eye view of the network of interest. Fly-DPI can be accessed at http://flydpi.nhri.org.tw. CONCLUSION: This work provides two reference systems, statistical and biological, to evaluate the reliability of protein interaction. First, the hybrid model statistically estimates both experimental and predicted protein interaction relationships. Second, the biological information for filtering and annotation itself is a strong indicator for the reliability of protein-protein interaction. The space-temporal or stage-specific expression patterns of genes are also critical for identifying proteins involved in a particular situation.

hp-DPI: Helicobacter pylori database of protein interactomes--embracing experimental and inferred interactions.

We implemented a statistical model into our protein interaction database for validation of two-hybrid assays of Helicobacter pylori, and prediction of putative protein interactions not yet discovered experimentally. To present the enormous amount of experimental and inferred protein interaction networking maps, the H.pylori Database of Protein Interactomes (hp-DPI) is developed with a succinct yet comprehensive visualization tool integrated with annotation from Genbank, GO, and KEGG. hp-DPI is first built with, but not limited to, H.pylori protein interactions and is expected to naturally include other organisms' protein interacting relationships in the future.