Design of tag SNP whole genome genotyping arrays

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs). The genetic variants in XMET genes are critical to predicate inter-individual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.

The dichotomy between disease phenotype databases and the implications for understanding complex diseases involving the major histocompatibility complex

Many genes related to innate and adaptive immunity reside within the major histocompatibility complex (MHC) and have been associated with a multitude of complex, immune-related disorders. Despite years of genetic study, this region has seen few causative determinants discovered for immune-mediated diseases. Reported associations have been curated in various databases including the Genetic Association Database, NCBI database of clinically relevant variants (ClinVar) and the Human Gene Mutation Database and together capture genetic associations and annotated pathogenic loci within the MHC and across the genome for a variety of complex, immune-mediated diseases. A review of these three distinct databases reveals disparate annotations between associated genes and pathogenic loci, alluding to the polygenic, multifactorial nature of immune-mediated diseases and the pleiotropic character of genes within the MHC. The technical limitations and inherent biases imposed by current approaches and technologies in studying the MHC create a strong case for the need to perform targeted deep sequencing of the MHC and other immunologically relevant loci in order to fully elucidate and study the causative elements of complex immune-mediated diseases.

Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies

Background

In addition to HLA genetic incompatibility, non-HLA difference between donor and recipients of transplantation leading to allograft rejection are now becoming evident. We aimed to create a unique genome-wide platform to facilitate genomic research studies in transplant-related studies. We designed a genome-wide genotyping tool based on the most recent human genomic reference datasets, and included customization for known and potentially relevant metabolic and pharmacological loci relevant to transplantation.

Methods

We describe here the design and implementation of a customized genome-wide genotyping array, the ‘TxArray’, comprising approximately 782,000 markers with tailored content for deeper capture of variants across HLA, KIR, pharmacogenomic, and metabolic loci important in transplantation. To test concordance and genotyping quality, we genotyped 85 HapMap samples on the array, including eight trios.

Results

We show low Mendelian error rates and high concordance rates for HapMap samples (average parent-parent-child heritability of 0.997, and concordance of 0.996). We performed genotype imputation across autosomal regions, masking directly genotyped SNPs to assess imputation accuracy and report an accuracy of >0.962 for directly genotyped SNPs. We demonstrate much higher capture of the natural killer cell immunoglobulin-like receptor (KIR) region versus comparable platforms. Overall, we show that the genotyping quality and coverage of the TxArray is very high when compared to reference samples and to other genome-wide genotyping platforms.

Conclusions

We have designed a comprehensive genome-wide genotyping tool which enables accurate association testing and imputation of ungenotyped SNPs, facilitating powerful and cost-effective large-scale genotyping of transplant-related studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0211-x) contains supplementary material, which is available to authorized users.

Development of a broad-based ADME panel for use in pharmacogenomic studies

Aim: To optimally address the interindividual variability observed in pharmacokinetic drug response, we have created a custom genotyping panel that interrogates most of the key genetic variations present in a set of 181 prioritized genes responsible for the absorption, distribution, metabolism and excretion (ADME) of many therapeutic agents. This consensus list of genes and variants was based on the ADME core and extended gene lists compiled by a group of pharmaceutical companies as having relevance. Although these pharmacokinetic genes and pathways are well known, tools that can interrogate a large number of these genes simultaneously within a single experiment are not currently available. Methods: Using novel design strategies, we have developed an optimized and validated ADME genotyping panel, encompassing approximately 3000 variants, that has broad applicability to any study or clinical trial that would benefit from the evaluation of an extensive list of ADME genes. Results & conclusion: Over the course of three design iterations, overall assay conversion rates were improved from 83 to 97% resulting in a panel that fills in many of the gaps in coverage present on currently available commercial genotyping assays. The utility of the assay has been demonstrated by the screening of more than 1000 samples resulting in the discovery of novel pharmacogenomic associations. The assay, and the underlying methods, will continue to be a valuable tool for use in future pharmacogenomic studies.

Original submitted 28 November 2013; Revision submitted 13 May 2014

Large SNP arrays for genotyping in crop plants

Genotyping with large numbers of molecular markers is now an indispensable tool within plant genetics and breeding. Especially through the identification of large numbers of single nucleotide polymorphism (SNP) markers using the novel high-throughput sequencing technologies, it is now possible to reliably identify many thousands of SNPs at many different loci in a given plant genome. For a number of important crop plants, SNP markers are now being used to design genotyping arrays containing thousands of markers spread over the entire genome and to analyse large numbers of samples. In this article, we discuss aspects that should be considered during the design of such large genotyping arrays and the analysis of individuals. The fact that crop plants are also often autopolyploid or allopolyploid is given due consideration. Furthermore, we outline some potential applications of large genotyping arrays including high-density genetic mapping, characterization (fingerprinting) of genetic material and breeding-related aspects such as association studies and genomic selection.

The relationship of haplotype in lactotransferrin and its expression levels in Chinese Han ovarian cancer

Chromosomal DNA sequence polymorphisms may contribute to individuality, confer risk for diseases, and most commonly are used as genetic markers in association study. The iron-binding protein lactoferrin inhibits bacterial growth by sequestering essential iron and also exhibits antitumor, anti-inflammatory, and immunoregulatory activities. The gene coding for lactotransferrin (LTF) is polymorphic, with the occurrence of several common alleles in the general population. This genetically determined variation can affect LTF functions. In this study, we determined the distribution of LTF gene polymorphisms (rs1126477, rs1126478, rs2073495, and rs9110) in the Chinese Han population and investigated whether these polymorphisms were associated with increased risk of ovarian carcinoma in the Chinese. It was found that the rs1126477 was correlated significantly with ovarian cancer. The frequency of A allele of rs1126477 was significantly higher in 700 ovarian cancer patients compared with that in the control group of 700 cases (P< 0.01, χ(2)= 6.79). The frequency of AA genotype was significantly higher in ovarian cancer patients compared with that in the control group (P< 0.05, χ(2)= 6.49). AA genotype is the risk factor of ovarian cancer. The odds ratio (OR) was 2.24 and the 95% confidence interval (CI) was 1.08-4.59, respectively. The 'A-G-C-C' haplotype constructed with rs1126477, rs1126478, rs2073495, and rs9110 was the risk factor to be ovarian cancer. The expression of LTF gene was lower in individuals with 'A-G-C-C' haplotype compared with that in individuals without 'A-G-C-C' haplotype. These findings suggested that rs1126477 could play important roles in ovarian carcinoma physiological processes in the Chinese.

Tag SNP polymorphism of CCL2 and its role in clinical tuberculosis in Han Chinese pediatric population

BACKGROUND

Chemokine (C-C motif) ligand 2 CCL2/MCP-1 is among the key signaling molecules of innate immunity; in particular, it is involved in recruitment of mononuclear and other cells in response to infection, including tuberculosis (TB) and is essential for granuloma formation.

METHODOLOGY/PRINCIPAL FINDINGS

We identified a tag SNP for the CCL2/MCP-1 gene (rs4586 C/T). In order to understand whether this SNP may serve to evaluate the contribution of the CCL2 gene to the expression of TB disease, we further analysed distribution of its alleles and genotypes in 301 TB cases versus 338 non-infected controls (all BCG vaccinated) representing a high-risk pediatric population of North China. In the male TB subgroup, the C allele was identified in a higher rate (P = 0.045), and, acting dominantly, was found to be a risk factor for clinical TB (P = 0.029). Homozygous TT genotype was significantly associated with lower CSF mononuclear leukocyte (ML) counts in patients with tuberculous meningitis (TBM) (P = 0.001).

CONCLUSIONS/SIGNIFICANCE

The present study found an association of the CCL2 tag SNP rs4586 C allele and pediatric TB disease in males, suggesting that gender may affect the susceptibility to TB even in children. The association of homozygous TT genotype with decreased CSF mononuclear leukocyte (ML) count not only suggests a clinical significance of this SNP, but indicates its potential to assist in the clinical assessment of suspected TBM, where delay is critical and diagnosis is difficult.

A short primer on the functional analysis of copy number variation for biomedical scientists

Recent studies have highlighted the potential prevalence of copy number variation (CNV) in mammalian genomes, including the human genome. These studies suggest that CNVs may play a potentially important role in human phenotypic diversity and disease susceptibility. Here, we consider some of the in silico challenges of characterizing genomic structural variants. While the phenotypic impact of the vast majority of CNVs is likely to be neutral, some CNVs will clearly impact phenotype. Here, we review some of the key databases hosting CNV data and discuss some of the caveats in the analysis of CNV data. The task is now to translate some of the initial associations between CNVs and disease into causal variants.