Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations.

The major histocompatibility complex (MHC) containing the classical human leukocyte antigen (HLA) Class I and Class II genes is among the most polymorphic and diverse regions in the human genome. Despite the clinical importance of identifying the HLA types, very few databases jointly characterize densely genotyped single nucleotide polymorphisms (SNPs) and HLA alleles in the same samples. To date, the HapMap presents the only public resource that provides a SNP reference panel for predicting HLA alleles, constructed with four collections of individuals of north-western European, northern Han Chinese, cosmopolitan Japanese and Yoruba Nigerian ancestry. Owing to complex patterns of linkage disequilibrium in this region, it is unclear whether the HapMap reference panels can be appropriately utilized for other populations. Here, we describe a public resource for the Singapore Genome Variation Project with: (i) dense genotyping across ∼ 9000 SNPs in the MHC; (ii) four-digit HLA typing for eight Class I and Class II loci, in 96 southern Han Chinese, 89 Southeast Asian Malays and 83 Tamil Indians. This resource provides population estimates of the frequencies of HLA alleles at these eight loci in the three population groups, particularly for HLA-DPA1 and HLA-DPB1 that were not assayed in HapMap. Comparing between population-specific reference panels and a cosmopolitan panel created from all four HapMap populations, we demonstrate that more accurate imputation is obtained with population-specific panels than with the cosmopolitan panel, especially for the Malays and Indians but even when imputing between northern and southern Han Chinese. As with SNP imputation, common HLA alleles were imputed with greater accuracy than low-frequency variants.

Deep whole-genome sequencing of 100 southeast Asian Malays.

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies.

Comprehensive long-span paired-end-tag mapping reveals characteristic patterns of structural variations in epithelial cancer genomes.

Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long-span paired-end-tag (PET) sequencing approach using 10-Kb genomic DNA inserts to study human genome structural variations (SVs). The use of a 10-Kb insert size allows the identification of breakpoints within repetitive or homology-containing regions of a few kilobases in size and results in a higher physical coverage compared with small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and two noncancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germ-line SVs, whereas tandem duplications, unpaired inversions, interchromosomal translocations, and complex rearrangements are over-represented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA-PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures that are compatible with breakage-fusion-bridge cycles, and we discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers.

Viral quasispecies inference from 454 pyrosequencing.

BACKGROUND: Many potentially life-threatening infectious viruses are highly mutable in nature. Characterizing the fittest variants within a quasispecies from infected patients is expected to allow unprecedented opportunities to investigate the relationship between quasispecies diversity and disease epidemiology. The advent of next-generation sequencing technologies has allowed the study of virus diversity with high-throughput sequencing, although these methods come with higher rates of errors which can artificially increase diversity. RESULTS: Here we introduce a novel computational approach that incorporates base quality scores from next-generation sequencers for reconstructing viral genome sequences that simultaneously infers the number of variants within a quasispecies that are present. Comparisons on simulated and clinical data on dengue virus suggest that the novel approach provides a more accurate inference of the underlying number of variants within the quasispecies, which is vital for clinical efforts in mapping the within-host viral diversity. Sequence alignments generated by our approach are also found to exhibit lower rates of error. CONCLUSIONS: The ability to infer the viral quasispecies colony that is present within a human host provides the potential for a more accurate classification of the viral phenotype. Understanding the genomics of viruses will be relevant not just to studying how to control or even eradicate these viral infectious diseases, but also in learning about the innate protection in the human host against the viruses.

Singapore Pharmacogenomics Portal: a web resource for evaluating human genetic variations of genes responsible for drug responses.

The Singapore Pharmacogenomics Portal is the first genomics web platform that links public resources from PharmGKB and DrugBank with population genetics data from the International HapMap Project and the Singapore Genome Variation Project. The web portal provides the opportunity to survey genetic differences across populations for all autosomal genes in the genome, and serves as an integrated platform for linking these data with drugs and genetic variants that affect drug responses, adverse reactions, and dosage requirements. We envisage that the information provided by the portal will be useful to drug regulators and clinical researchers when evaluating the transferability of results from clinical trials conducted in one population to other populations for which no direct clinical testing has been conducted. The utility of this resource may extend to other countries in the region that also have significant populations of Chinese, Malay, or Indian ancestry.

A method for identifying haplotypes carrying the causative allele in positive natural selection and genome-wide association studies.

MOTIVATION: Methods for detecting positive selection relied on finding evidence of long haplotypes to identify candidate regions under selection. However, these methods generally do not identify the length and form of the selected haplotype. RESULTS: We present HapFinder, a method which can find the common longest haplotype under three different settings from a database, which is relevant in the analysis of positive selection in population genetics and also in medical genetics for finding the likely haplotype form carrying the causal allele at the functional polymorphism. AVAILABILITY: A java program, implementing the methods described in HapFinder, together with R scripts and datasets for producing the figures presented in this article are publicly available at http://www.nus-cme.org.sg/sgvp/software/hapfinder.html. The site also hosts an online browser for finding haplotypes from the International HapMap Project and the Singapore Genome Variation Project.

SgD-CNV, a database for common and rare copy number variants in three Asian populations.

Copy number variants (CNVs) extend our understanding of the genetic diversity in humans. However, the distribution and characteristics of CNVs in Asian populations remain largely unexplored, especially for rare CNVs that have emerged as important genetic factors for complex traits. In the present study, we performed an in-depth investigation of common and rare CNVs across 8,148 individuals from the three major Asian ethnic groups: Chinese (n = 1,945), Malays (n = 2,399), and Indians (n = 2,217) in Singapore, making this investigation the most comprehensive genome-wide survey of CNVs outside the European-ancestry populations to date. We detected about 16 CNVs per individual and the ratio of loss to gain events is ∼2:1. The majority of the CNVs are of low frequency (<10%), and 40% are rare (<1%). In each population, ∼20% of the CNVs are not previously catalogued in the Database of Genomic Variants (DGV). Contrary to findings from European studies, the common CNVs (>5%) in our populations are not well tagged by SNPs in Illumina 1M and 610K arrays, and most disease-associated common CNVs previously reported in Caucasians are rare in our populations. We also report noticeable population differentiation in the CNV landscape of these Asian populations, with the greatest diversity seen between the Indians and the Chinese.

Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity.

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed.

A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations.

Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium.

Long span DNA paired-end-tag (DNA-PET) sequencing strategy for the interrogation of genomic structural mutations and fusion-point-guided reconstruction of amplicons.

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10-20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.

A common BIM deletion polymorphism mediates intrinsic resistance and inferior responses to tyrosine kinase inhibitors in cancer.

Tyrosine kinase inhibitors (TKIs) elicit high response rates among individuals with kinase-driven malignancies, including chronic myeloid leukemia (CML) and epidermal growth factor receptor-mutated non-small-cell lung cancer (EGFR NSCLC). However, the extent and duration of these responses are heterogeneous, suggesting the existence of genetic modifiers affecting an individual's response to TKIs. Using paired-end DNA sequencing, we discovered a common intronic deletion polymorphism in the gene encoding BCL2-like 11 (BIM). BIM is a pro-apoptotic member of the B-cell CLL/lymphoma 2 (BCL2) family of proteins, and its upregulation is required for TKIs to induce apoptosis in kinase-driven cancers. The polymorphism switched BIM splicing from exon 4 to exon 3, which resulted in expression of BIM isoforms lacking the pro-apoptotic BCL2-homology domain 3 (BH3). The polymorphism was sufficient to confer intrinsic TKI resistance in CML and EGFR NSCLC cell lines, but this resistance could be overcome with BH3-mimetic drugs. Notably, individuals with CML and EGFR NSCLC harboring the polymorphism experienced significantly inferior responses to TKIs than did individuals without the polymorphism (P = 0.02 for CML and P = 0.027 for EGFR NSCLC). Our results offer an explanation for the heterogeneity of TKI responses across individuals and suggest the possibility of personalizing therapy with BH3 mimetics to overcome BIM-polymorphism-associated TKI resistance.