Development of HLA-A, -B and -DR Typing Method Using Next-Generation Sequencing / 대한수혈학회지

BACKGROUND: Research on next-generation sequencing (NGS)-based HLA typing is active. To resolve the phase ambiguity and long turn-around-time of conventional high resolution HLA typing, this study developed a NGS-based high resolution HLA typing method that can handle large-scale samples within an efficient testing time. METHODS: For HLA NGS, the condition of nucleic acid extraction, library construction, PCR mechanism, and HLA typing with bioinformatics were developed. To confirm the accuracy of the NGS-based HLA typing method, the results of 192 samples HLA typed by SSOP and 28 samples typed by SBT compared to NGS-based HLA-A, -B and -DR typing. RESULTS: DNA library construction through two-step PCR, NGS sequencing with MiSeq (Illumina Inc., San Diego, USA), and the data analysis platform were established. NGS-based HLA typing results were compatible with known HLA types from 220 blood samples. CONCLUSION: The NSG-based HLA typing method could handle large volume samples with high-throughput. Therefore, it would be useful for HLA typing of bone marrow donation volunteers.

Evaluating the results of the Momguard noninvasive prenatal test

PURPOSE: To evaluate the performance of the Momguard noninvasive prenatal test by tracing the 'screen positive' results based on preliminary samples from Korean cohorts. MATERIALS AND METHODS: This preliminary study is based on data collected by the LabGenomics Clinical Laboratory (Seongnam, Korea) with informed consent. Only pregnant women who underwent both the Momguard test and karyotyping were included in this study. Momguard test results were compared with those of the karyotyping analysis. RESULTS: Among the 38 cases with 'screen positive' results by Momguard, 30 cases also had karyotyping results available. In three trisomy (T) 18 and three T13 cases, the Momguard results were concordant with the karyotyping results. For the T21 cases, except for one case belonging to the mid-risk zone, Momguard results from 23 out of 24 cases matched the karyotyping results. CONCLUSION: Momguard is a highly reliable screening tool for detecting T13, T18, and T21 cases in independent Korean cohort samples.

Genome-Wide Association Study of Lung Cancer in Korean Non-Smoking Women

Lung cancer in never-smokers ranks as the seventh most common cause of cancer death worldwide, and the incidence of lung cancer in non-smoking Korean women appears to be steadily increasing. To identify the effect of genetic polymorphisms on lung cancer risk in non-smoking Korean women, we conducted a genome-wide association study of Korean female non-smokers with lung cancer. We analyzed 440,794 genotype data of 285 cases and 1,455 controls, and nineteen SNPs were associated with lung cancer development (P < 0.001). For external validation, nineteen SNPs were replicated in another sample set composed of 293 cases and 495 controls, and only rs10187911 on 2p16.3 was significantly associated with lung cancer development (dominant model, OR of TG or GG, 1.58, P = 0.025). We confirmed this SNP again in another replication set composed of 546 cases and 744 controls (recessive model, OR of GG, 1.32, P = 0.027). OR and P value in combined set were 1.37 and < 0.001 in additive model, 1.51 and < 0.001 in dominant model, and 1.54 and < 0.001 in recessive model. The effect of this SNP was found to be consistent only in adenocarcinoma patients (1.36 and < 0.001 in additive model, 1.49 and < 0.001 in dominant model, and 1.54 and < 0.001 in recessive model). Furthermore, after imputation with HapMap data, we found regional significance near rs10187911, and five SNPs showed P value less than that of rs10187911 (rs12478012, rs4377361, rs13005521, rs12475464, and rs7564130). Therefore, we concluded that a region on chromosome 2 is significantly associated with lung cancer risk in Korean non-smoking women.

Identifying Copy Number Variants under Selection in Geographically Structured Populations Based on F-statistics

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional FST measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the FST estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.

Identifying Copy Number Variants under Selection in Geographically Structured Populations Based on F-statistics

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional FST measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the FST estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.

Web-Based Database and Viewer of East Asian Copy Number Variations

We have discovered copy number variations (CNVs) in 3,578 Korean individuals with the Affymetrix Genome-Wide SNP array 5.0, and 4,003 copy number variation regions (CNVRs) were defined in a previous study. To explore the details of the variants easily in related studies, we built a database, cataloging the CNVs and related information. This system helps researchers browsing these variants with gene and structure variant annotations. Users can easily find specific regions with search options and verify them from system-integrated genome browsers with annotations.

Common variants at the promoter region of the APOM confer a risk of rheumatoid arthritis

Although the genetic component in the etiology of rheumatoid arthritis (RA) has been consistently suggested, many novel genetic loci remain to uncover. To identify RA risk loci, we performed a genome-wide association study (GWAS) with 100 RA cases and 600 controls using Affymetrix SNP array 5.0. The candidate risk locus (APOM gene) was re-sequenced to discover novel promoter and coding variants in a group of the subjects. Replication was performed with the independent case-control set comprising of 578 RAs and 711 controls. Through GWAS, we identified a novel SNP associated with RA at the APOM gene in the MHC class III region on 6p21.33 (rs805297, odds ratio (OR) = 2.28, P = 5.20 x 10(-7)). Three more polymorphisms were identified at the promoter region of the APOM by the re-sequencing. For the replication, we genotyped the four SNP loci in the independent case-control set. The association of rs805297 identified by GWAS was successfully replicated (OR = 1.40, P = 6.65 x 10(-5)). The association became more significant in the combined analysis of discovery and replication sets (OR = 1.56, P = 2.73 +/- 10(-10)). The individuals with the rs805297 risk allele (A) at the promoter region showed a significantly lower level of APOM expression compared with those with the protective allele (C) homozygote. In the logistic regressions by the phenotype status, the homozygote risk genotype (A/A) consistently showed higher ORs than the heterozygote one (A/C) for the phenotype-positive RAs. These results indicate that APOM promoter polymorphisms are significantly associated with the susceptibility to RA.

Comparison of the Affymetrix SNP Array 5.0 and Oligoarray Platforms for Defining CNV

Together with single nucleotide polymorphism (SNP), copy number variations (CNV) are recognized to be the major component of human genetic diversity and used as a genetic marker in many disease association studies. Affymetrix Genome-wide SNP 5.0 is one of the commonly used SNP array platforms for SNP-GWAS as well as CNV analysis. However, there has been no report that validated the accuracy and reproducibility of CNVs identified by Affymetrix SNP array 5.0. In this study, we compared the characteristics of CNVs from the same set of genomic DNAs detected by three different array platforms; Affymetrix SNP array 5.0, Agilent 2X244K CNV array and NimbleGen 2.1M CNV array. In our analysis, Affymetrix SNP array 5.0 seems to detect CNVs in a reliable manner, which can be applied for association studies. However, for the purpose of defining CNVs in detail, Affymetrix Genome-wide SNP 5.0 might be relatively less ideal than NimbleGen 2.1M CNV array and Agilent 2X244K CNV array, which outperform Affymetrix array for defining the small-sized single copy variants. This result will help researchers to select a suitable array platform for CNV analysis.

No Association between Copy Number Variation of the TCRB Gene and the Risk of Autism Spectrum Disorder in the Korean Population

Although autism spectrum disorder (ASD) has been thought to have a substantial genetic background, major contributing genes have yet to be identified or successfully replicated. Immunological dysfunction has been suggested to be associated with ASD, and T cell-mediated immunity was considered important for the development of ASD. In this study, we analyzed 163 ASD subjects and 97 normal controls by genomic quantitative PCR to evaluate the association between the copy number variation of the 7q34 locus, harboring the TCRB gene, and ASDs. As a result, there was no significant difference of the frequency distribution of TCRB copy numbers between ASD cases and normal controls. TCRB gene copy numbers ranged from 0 to 5 copies, and the frequency distribution of each copy number was similar between the two groups. The proportion of the individuals with 2 copies of TCRB was 11.7% (19/163) in ASD cases and 12.1% (11/91) in the control group (p=0.68). After the effects of sex were adjusted by logistic regression, ORs for individuals with 2 copies showed no significant difference compared with the diploid copy number as reference (n=2). Although we could not see the positive association, our results will be valuable information for mining ASD-associated genes and for exploring the role of T cell immunity further in the pathogenesis of ASD.

Replication of the Association between Copy Number Variation on 8p23.1 and Autism by Using ASD-specific BAC Array

To discover genetic markers for autism spectrum disorder (ASD), we previously applied genome-wide BAC array comparative genomic hybridization (array-CGH) to 28 autistic patients and 62 normal controls in Korean population, and identified that chromosomal losses on 8p23.1 and on 17p11.2 are significantly associated with autism. In this study, we developed an 8.5K ASD-specific BAC array covering 27 previously reported ASD-associated CNV loci including ours and examined whether the associations would be replicated in 8 ASD patient cell lines of four different ethnic groups and 10 Korean normal controls. As a result, a CNV-loss on 8p23.1 was found to be significantly more frequent in patients regardless of ethnicity (p<0.0001). This CNV region contains two coding genes, DEFA1 and DEFA3, which are members of DEFENSIN gene family. Two other CNVs on 17p11.2 and Xp22.31 were also distributed differently between ASDs and controls, but not significant (p=0.069 and 0.092, respectively). All the other loci did not show significant association. When these evidences are considered, the association between ASD and CNV of DEFENSIN gene seems worthy of further exploration to elucidate the pathogenesis of ASD. Validation studies with a larger sample size will be required to verify its biological implication.