Identification of SNP markers for common CNV regions and association analysis of risk of subarachnoid aneurysmal hemorrhage in Japanese population

Evolutionary History of the Risk of SNPs for Diffuse-Type Gastric Cancer in the Japanese Population

A genome wide association study reported that the T allele of rs2294008 in a cancer-related gene, PSCA, is a risk allele for diffuse-type gastric cancer. This allele has the highest frequency (0.63) in Japanese in Tokyo (JPT) among 26 populations in the 1000 Genomes Project database. F_ST ≈ 0.26 at this single nucleotide polymorphism is one of the highest between JPT and the genetically close Han Chinese in Beijing (CHB). To understand the evolutionary history of the alleles in PSCA, we addressed: (i) whether the C non-risk allele at rs2294008 is under positive selection, and (ii) why the mainland Japanese population has a higher T allele frequency than other populations. We found that haplotypes harboring the C allele are composed of two subhaplotypes. We detected that positive selection on both subhaplotypes has occurred in the East Asian lineage. However, the selection on one of the subhaplotypes in JPT seems to have been relaxed or ceased after divergence from the continental population; this may have caused the elevation of T allele frequency. Based on simulations under the dual structure model (a specific demography for the Japanese) and phylogenetic analysis with ancient DNA, the T allele at rs2294008 might have had high frequency in the Jomon people (one of the ancestral populations of the modern Japanese); this may explain the high T allele frequency in the extant Japanese.

Association Analysis to Copy Number Variation (CNV) of Opn4 Gene with Growth Traits of Goats

Simple Summary

Copy number variation is a common genetic polymorphism and is mainly represented by submicroscopic levels of deletion and duplication which are caused by rearrangement of the genome. It is well known that copy number variations of genes are associated with growth traits of livestock. In this study, we detected the correlation between the copy number variation of the Opn4 gene and growth traits of Guizhou goats. We found that the copy number variation of the Opn4 gene had a significant influence on the body length and body weight of Guizhou goats. The results may provide preliminary suggestions into Guizhou goat breeding and new insights into the future of CNV as a new promising molecular marker in animal breeding.

Abstract

Extensive research has been carried out regarding the correlation between the growth traits of livestock and genetic polymorphisms, including single nucleotide polymorphisms and copy number variations (CNV). The purpose of this study was to analyze the CNV and its genetic effects of the Opn4 gene in 284 Guizhou goats (Guizhou black goat: n = 186, Guizhou white goat: n = 98). We used qPCR to detect the CNV of the Opn4 gene in Guizhou goats, and the classification results were correlated with the corresponding individual growth traits by SPSS software. The results showed that the Opn4 gene had a superior effect on growth traits with multiple copy variants in Guizhou black goats, and there was a significant correlation between copy number variation sites and body length traits. Contrary to the former conclusion, in Guizhou white goats, individuals with the Normal copy number type showed superior growth traits and copy number variant sites were significantly associated with body weight traits. Therefore, the CNV of the Opn4 gene can be used as a candidate molecular genetic marker to improve goat growth traits, speeding up the breeding process of goat elite varieties.

Red Cell Distribution Width After Subarachnoid Hemorrhage

BACKGROUND

High red cell distribution width (RDW) values have been associated with increased hospital mortality in critically ill patients, but few data are available for subarachnoid hemorrhage (SAH).

METHODS

We analyzed an institutional database of adult (>18 y) patients admitted to the Department of Intensive Care after nontraumatic SAH between January 2011 and May 2016. RDW (normal value, 10.9% to 13.4%) was obtained daily from admission for a maximum of 7 days, from routine blood analysis. We recorded the occurrence of delayed cerebral ischemia (DCI), and neurological outcome (assessed using the Glasgow Outcome Scale [GOS]) at 3 months.

RESULTS

A total of 270 patients were included (median age 54 y-121/270 male [45%]), of whom 96 (36%) developed DCI and 109 (40%) had an unfavorable neurological outcome (GOS, 1 to 3). The median RDW on admission was 13.8 [13.3 to 14.5]% and the highest value during the intensive care unit (ICU) stay 14.2 [13.6 to 14.8]%. The RDW was high (>13.4%) in 177 patients (66%) on admission and in 217 (80%) at any time during the ICU stay. Patients with a high RDW on admission were more likely to have an unfavorable neurological outcome. In multivariable regression analysis, older age, a high WFNS grade on admission, presence of DCI or intracranial hypertension, previous neurological disease, vasopressor therapy and a high RDW (OR, 1.1618 [95% CI, 1.213-2.158]; P=0.001) during the ICU stay were independent predictors of unfavorable neurological outcome.

CONCLUSIONS

High RDW values were more likely to result in an unfavorable outcome after SAH. This information could help in the stratification of SAH patients already on ICU admission.

Copy number variations and stroke

Stroke is the third leading cause of death worldwide after heart disease and all forms of cancers. Monogenic disorders, genetic, and environmental risk factors contribute to damaging cerebral blood vessels and, consequently, cause stroke. Developments in genomic research led to the discovery of numerous copy number variants (CNVs) that have been recently identified as a new tool for understanding the genetic basis of many diseases. This review discusses the current understanding of the types of stroke, the existing knowledge on the involvement of specific CNVs in stroke as well as the limitations of the methods used for detecting CNVs like SNP-microarray. To confirm an unequivocally association between CNVs and stroke and extend the current findings, it would be desirable to use another methodology to detect smaller CNVs or CNVs in genomic regions poorly covered by this technique, for instance, CGH-array.

Detection of CAPN10 copy number variation in Thai patients with type 2 diabetes by denaturing high performance liquid chromatography and real-time quantitative polymerase chain reaction

Aims/Introduction

A combination of multiple genetic and environmental factors contribute to the pathogenesis of type 2 diabetes. Copy number variations (CNVs) are associated with complex human diseases. However, CNVs can cause genotype deviation from the Hardy–Weinberg equilibrium (HWE). A genetic case–control association study in 216 Thai diabetic patients and 192 non-diabetic controls found that, after excluding genotyping errors, genotype distribution of calpain 10 (CAPN10) SNP44 (rs2975760) deviated from HWE. Here, we aimed to detect CNV within the CAPN10 SNP44 region.

Materials and Methods

CNV within the CAPN10 SNP44 region was detected using denaturing high-performance liquid chromatography, and the results confirmed by real-time quantitative polymerase chain reaction with SYBR Green I.

Results

Both methods successfully identified CNV in the CAPN10 SNP44 region, obtaining concordant results. Correction of genotype calling based on the status of identified CNVs showed that the CAPN10 SNP44 genotype is in good agreement with HWE (P > 0.05). However, no association between CNV genotypes and risk of type 2 diabetes was observed.

Conclusions

Identified CNVs for CAPN10 SNP44 genotypes lead to deviation from HWE. Furthermore, both denaturing high-performance liquid chromatography and real-time quantitative polymerase chain reaction are useful for detecting CNVs.

Advantage of using allele-specific copy numbers when testing for association in regions with common copy number variants

Copy number variants (CNV) can be called from SNP-arrays; however, few studies have attempted to combine both CNV and SNP calls to test for association with complex diseases. Even when SNPs are located within CNVs, two separate association analyses are necessary, to compare the distribution of bi-allelic genotypes in cases and controls (referred to as SNP-only strategy) and the number of copies of a region (referred to as CNV-only strategy). However, when disease susceptibility is actually associated with allele specific copy-number states, the two strategies may not yield comparable results, raising a series of questions about the optimal analytical approach. We performed simulations of the performance of association testing under different scenarios that varied genotype frequencies and inheritance models. We show that the SNP-only strategy lacks power under most scenarios when the SNP is located within a CNV; frequently it is excluded from analysis as it does not pass quality control metrics either because of an increased rate of missing calls or a departure from fitness for Hardy-Weinberg proportion. The CNV-only strategy also lacks power because the association testing depends on the allele which copy number varies. The combined strategy performs well in most of the scenarios. Hence, we advocate the use of this combined strategy when testing for association with SNPs located within CNVs.

Cutting-edge issues in primary biliary cirrhosis

Several crucial issues remain open in our understanding of primary biliary cirrhosis (PBC), an autoimmune liver disease targeting the small- and medium-sized intrahepatic bile ducts. These issues include the high tissue specificity of the autoimmune injury despite the nontraditional autoantigens found in all mitochondria recognized by PBC-associated autoantibodies, the causes of the commonly observed pruritus, and the disease etiology per se. In all these fields, there has been recent interest secondary to the use of large-scale efforts (such as genome-wide association studies) that were previously considered poorly feasible in a rare disease such as PBC as well as other intuitions. Accordingly, there are now fascinating theories to explain the onset and severity of pruritus due to elevated autotaxin levels, the peculiar apoptotic features of bile duct cells to explain the tissue specificity, and genomic and epigenetic associations contributing to disease susceptibility. We have arbitrarily chosen these four aspects as the most promising in the PBC recent literature and will provide herein a discussion of the recent data and their potential implications.

Frequent amplification of CENPF, GMNN and CDK13 genes in hepatocellular carcinomas

Genomic changes frequently occur in cancer cells during tumorigenesis from normal cells. Using the Illumina Human NS-12 single-nucleotide polymorphism (SNP) chip to screen for gene copy number changes in primary hepatocellular carcinomas (HCCs), we initially detected amplification of 35 genes from four genomic regions (1q21–41, 6p21.2–24.1, 7p13 and 8q13–23). By integrated screening of these genes for both DNA copy number and gene expression in HCC and colorectal cancer, we selected CENPF (centromere protein F/mitosin), GMNN (geminin, DNA replication inhibitor), CDK13 (cyclin-dependent kinase 13), and FAM82B (family with sequence similarity 82, member B) as common cancer genes. Each gene exhibited an amplification frequency of ∼30% (range, 20–50%) in primary HCC (n = 57) and colorectal cancer (n = 12), as well as in a panel of human cancer cell lines (n = 70). Clonogenic and invasion assays of NIH3T3 cells transfected with each of the four amplified genes showed that CENPF, GMNN, and CDK13 were highly oncogenic whereas FAM82B was not. Interestingly, the oncogenic activity of these genes (excluding FAM82B) was highly correlated with gene-copy numbers in tumor samples (correlation coefficient, r>0.423), indicating that amplifications of CENPF, GMNN, and CDK13 genes are tightly linked and coincident in tumors. Furthermore, we confirmed that CDK13 gene copy number was significantly associated with clinical onset age in patients with HCC (P = 0.0037). Taken together, our results suggest that coincidently amplified CDK13, GMNN, and CENPF genes can play a role as common cancer-driver genes in human cancers.

Identification of copy number variation of CAPN10 in Thais with type 2 diabetes by multiplex PCR and denaturing high performance liquid chromatography (DHPLC)

Copy number variations (CNVs) have been shown to be associated with several diseases. They can cause deviation of genotypes from Hardy-Weinberg Equilibrium (HWE). Genetic case-control association studies in Thais revealed that genotype distribution of CAPN10 Indel19 was deviated from HWE after correction of genotyping error. Therefore, we aim to identify CNVs within CAPN10 Indel19 region. The semi-quantitative denaturating high performance liquid chromatography (DHPLC) method was used to detect CNVs in the region of CAPN10 Indel19 marker in cohort of 305 patients with type 2 diabetes and 250 control subjects without diabetes. CNVs in the region of CAPN10 Indel19 was successfully detected by DHPLC. After correction of genotype calling based on the status of identified CNVs, CAPN10 Indel19 genotypes were well-fitted for HWE (p>0.05). However, we did not find association between CNV genotypes and risk of type 2 diabetes in our population. CNVs in CAPN10 have been identified in Thais. These CNVs lead to deviation from HWE of CAPN10 Indel19 genotypes. After excluding identified CNVs from the analysis, CAPN10 Indel19 was associated with type 2 diabetes. The information obtained from our study would be helpful for genotyping accuracies of SNPs residing in the CNVs region.

Copy number variation in the genomes of domestic animals

Copy number variation (CNV) might be one of the main contributors to phenotypic diversity and evolutionary adaptation in animals and plants, employing a wide variety of mechanisms, such as gene dosage and transcript structure alterations, to modulate organismal plasticity. In the past 4 years, considerable advances have been made in the characterization of the genomic architecture of CNV in domestic species. First, low-resolution CNV maps were produced for cattle, goat, sheep, pig, dog, chicken, duck and turkey, showing that these structural polymorphisms comprise a significant part of these genomes. Furthermore, CNVs have been associated with several pigmentation (white coat in horse, pig and sheep) and morphological (late feathering and pea comb in chicken) traits, as well as with susceptibility to a wide array of diseases and developmental disorders, for example osteopetrosis, anhidrotic ectodermal dysplasia, copper toxicosis, intersexuality, cone degeneration, periodic fever and dermoid sinus, among others. In the future, development of high-resolution tools for CNV detection and typing combined with the implementation of databases integrating CNV, QTL and gene expression data will be essential to identify and measure the impact of this source of structural variation on the many phenotypes that are relevant to animal breeders and veterinary practitioners.

The genetic effect of copy number variations on the risk of type 2 diabetes in a Korean population

Background

Unlike Caucasian populations, genetic factors contributing to the risk of type 2 diabetes mellitus (T2DM) are not well studied in Asian populations. In light of this, and the fact that copy number variation (CNV) is emerging as a new way to understand human genomic variation, the objective of this study was to identify type 2 diabetes–associated CNV in a Korean cohort.

Methodology/Principal Findings

Using the Illumina HumanHap300 BeadChip (317,503 markers), genome-wide genotyping was performed to obtain signal and allelic intensities from 275 patients with type 2 diabetes mellitus (T2DM) and 496 nondiabetic subjects (Total n = 771). To increase the sensitivity of CNV identification, we incorporated multiple factors using PennCNV, a program that is based on the hidden Markov model (HMM). To assess the genetic effect of CNV on T2DM, a multivariate logistic regression model controlling for age and gender was used. We identified a total of 7,478 CNVs (average of 9.7 CNVs per individual) and 2,554 CNV regions (CNVRs; 164 common CNVRs for frequency>1%) in this study. Although we failed to demonstrate robust associations between CNVs and the risk of T2DM, our results revealed a putative association between several CNVRs including chr15:45994758–45999227 (P = 8.6E-04, P^corr = 0.01) and the risk of T2DM. The identified CNVs in this study were validated using overlapping analysis with the Database of Genomic Variants (DGV; 71.7% overlap), and quantitative PCR (qPCR). The identified variations, which encompassed functional genes, were significantly enriched in the cellular part, in the membrane-bound organelle, in the development process, in cell communication, in signal transduction, and in biological regulation.

Conclusion/Significance

We expect that the methods and findings in this study will contribute in particular to genome studies of Asian populations.

Copy number variation

Recent genetic epidemiology studies have been dominated by genome-wide association (GWA) studies using single nucleotide polymorphisms (SNPs). However, a form of structural genomic variation, termed copy number variation (CNV), is also widespread throughout the human genome, and can be highly polymorphic between individuals. Such variation has long been shown, through candidate gene studies using low-throughput molecular biology techniques, to have direct consequences on human health and variation. Many studies have now sought to extensively characterise this variation on a genome-wide scale and, increasingly, attempts are being made to identify associations between CNV and human disease. Although many of the study design issues that have been described for SNP GWA studies are also relevant for CNV GWA studies, CNV studies also present their own unique set of challenges and considerations. New microarray-based technologies are enabling more accurate mapping of CNVs, and CNV maps of the human genome are being regularly refined with increasing resolution. The study of CNV and its effects on human health and disease therefore present a dynamic and exciting challenge for researchers in the field of genetic epidemiology.

Assessment of copy number variation using the Illumina Infinium 1M SNP-array: a comparison of methodological approaches in the Spanish Bladder Cancer/EPICURO study

High-throughput single nucleotide polymorphism (SNP)-array technologies allow to investigate copy number variants (CNVs) in genome-wide scans and specific calling algorithms have been developed to determine CNV location and copy number. We report the results of a reliability analysis comparing data from 96 pairs of samples processed with CNVpartition, PennCNV, and QuantiSNP for Infinium Illumina Human 1Million probe chip data. We also performed a validity assessment with multiplex ligation-dependent probe amplification (MLPA) as a reference standard. The number of CNVs per individual varied according to the calling algorithm. Higher numbers of CNVs were detected in saliva than in blood DNA samples regardless of the algorithm used. All algorithms presented low agreement with mean Kappa Index (KI) <66. PennCNV was the most reliable algorithm (KI(w=) 98.96) when assessing the number of copies. The agreement observed in detecting CNV was higher in blood than in saliva samples. When comparing to MLPA, all algorithms identified poorly known copy aberrations (sensitivity = 0.19-0.28). In contrast, specificity was very high (0.97-0.99). Once a CNV was detected, the number of copies was truly assessed (sensitivity >0.62). Our results indicate that the current calling algorithms should be improved for high performance CNV analysis in genome-wide scans. Further refinement is required to assess CNVs as risk factors in complex diseases.

VnD: a structure-centric database of disease-related SNPs and drugs

Numerous genetic variations have been found to be related to human diseases. Significant portion of those affect the drug response as well by changing the protein structure and function. Therefore, it is crucial to understand the trilateral relationship among genomic variations, diseases and drugs. We present the variations and drugs (VnD), a consolidated database containing information on diseases, related genes and genetic variations, protein structures and drug information. VnD was built in three steps. First, we integrated various resources systematically to deduce catalogs of disease-related genes, single nucleotide polymorphisms (SNPs), protein mutations and relevant drugs. VnD contains 137,195 disease-related gene records (13,940 distinct genes) and 16,586 genetic variation records (1790 distinct variations). Next, we carried out structure modeling and docking simulation for wild-type and mutant proteins to examine the structural and functional consequences of non-synonymous SNPs in the drug-related genes. Conformational changes in 590 wild-type and 4437 mutant proteins from drug-related genes were included in our database. Finally, we investigated the structural and biochemical properties relevant to drug binding such as the distribution of SNPs in proximal protein pockets, thermo-chemical stability, interactions with drugs and physico-chemical properties. The VnD database, available at http://vnd.kobic.re.kr:8080/VnD/ or vandd.org, would be a useful platform for researchers studying the underlying mechanism for association among genetic variations, diseases and drugs.

Genome-wide association analysis of copy number variations in subarachnoid aneurysmal hemorrhage

Subarachnoid aneurysmal hemorrhage (SAH) due to cerebral aneurysm rupture is a very serious disease resulting in high mortality rate. It has been known that genetic factors are involved in the risk of SAH. A recent breakthrough in genomic variation called copy number variation (CNV) has been revealed to be involved in risks of human diseases. In this study, we hypothesized that CNVs can predict the risk of SAH. We used the Illumina HumanHap300 BeadChip (317 503 markers) to genotype 497 individuals in a Japanese population. Furthermore, individual CNVs were identified using signal and allelic intensities. The genetic effect of CNV on the risk of SAH was evaluated using multivariate logistic regression controlling for age and gender in 187 common CNV regions (frequency >1%). From a total of 4574 individual CNVs identified in this study (9.7 CNVs per individual), we were able to discover 1644 unique CNV regions containing 1232 genes. The identified variations were validated using visual examination of the genoplot image, overlapping analysis with the Database of Genomic Variants (73.2%), CNVpartition (72.4%) and quantitative PCR. Interestingly, two CNV regions, chr4:153210505-153212191 (deletion, 4q31.3, P=0.0005, P(corr) (corrected P-value)=0.04) and chr10:6265006-6267388 (duplication, 10p15.1, P=0.0006, P(corr)=0.05), were significantly associated with the risk of SAH after multiple testing corrections. Our results suggest that the newly identified CNV regions may contribute to SAH disease susceptibility.

Genome-wide profiling of structural genomic variations in Korean HapMap individuals

Background

Structural genomic variation study, along with microarray technology development has provided many genomic resources related with architecture of human genome, and led to the fact that human genome structure is a lot more complicated than previously thought.

Methodology/Principal Findings

In the case of International HapMap Project, Epstein-Barr various immortalized cell lines were preferably used over blood in order to get a larger number of genomic DNA. However, genomic aberration stemming from immortalization process, biased representation of the donor tissue, and culture process may influence the accuracy of SNP genotypes. In order to identify chromosome aberrations including loss of heterozygosity (LOH), large-scale and small-scale copy number variations, we used Illumina HumanHap500 BeadChip (555,352 markers) on Korean HapMap individuals (n = 90) to obtain Log R ratio and B allele frequency information, and then utilized the data with various programs including Illumina ChromoZone, cnvParition and PennCNV. As a result, we identified 28 LOHs (>3 mb) and 35 large-scale CNVs (>1 mb), with 4 samples having completely duplicated chromosome. In addition, after checking the sample quality (standard deviation of log R ratio <0.30), we selected 79 samples and used both signal intensity and B allele frequency simultaneously for identification of small-scale CNVs (<1 mb) to discover 4,989 small-scale CNVs. Identified CNVs in this study were successfully validated using visual examination of the genoplot images, overlapping analysis with previously reported CNVs in DGV, and quantitative PCR.

Conclusion/Significance

In this study, we describe the result of the identified chromosome aberrations in Korean HapMap individuals, and expect that these findings will provide more meaningful information on the human genome.

Identification of copy number variations and common deletion polymorphisms in cattle

BACKGROUND

Recently, the discovery of copy number variation (CNV) led researchers to think that there are more variations of genomic DNA than initially believed. Moreover, a certain CNV region has been found to be associated with the onset of diseases. Therefore, CNV is now known as an important genomic variation in biological mechanisms. However, most CNV studies have only involved the human genome. The study of CNV involving other animals, including cattle, is severely lacking.

RESULTS

In our study of cattle, we used Illumina BovineSNP50 BeadChip (54,001 markers) to obtain each marker's signal intensity (Log R ratio) and allelic intensity (B allele frequency), which led to our discovery of 855 bovine CNVs from 265 cows. For these animals, the average number of CNVs was 3.2, average size was 149.8 kb, and median size was 171.5 kb. Taking into consideration some overlapping regions among the identified bovine CNVs, 368 unique CNV regions were detected. Among them, there were 76 common CNVRs with > 1% CNV frequency. Together, these CNVRs contained 538 genes. Heritability errors of 156 bovine pedigrees and comparative pairwise analyses were analyzed to detect 448 common deletion polymorphisms. Identified variations in this study were successfully validated using visual examination of the genoplot image, Mendelian inconsistency, another CNV identification program, and quantitative PCR.

CONCLUSIONS

In this study, we describe a map of bovine CNVs and provide important resources for future bovine genome research. This result will contribute to animal breeding and protection from diseases with the aid of genomic information.

Identification of genome-wide copy number variations and a family-based association study of Avellino corneal dystrophy

OBJECTIVE

To determine the association of identified copy number variations (CNVs) in whole genome with the risk of Avellino corneal dystrophy (ACD) in a Korean population.

DESIGN

Case-control study.

PARTICIPANTS

A total of 146 patients with ACD and 226 control subjects.

METHODS

A total of 193 trios were genotyped by the Illumina HumanHapCNV370-Duo BeadChip (370,404 markers) (Illumina, Inc., San Diego, CA). The intensity signal (log R ratio) and allelic intensity ratio (B allele frequency) of each marker in all individuals were obtained by Illumina BeadStudio software (Illumina, Inc.). To obtain authentic CNVs in this study, we performed a family-based CNV validation and family-based boundary mapping using the PennCNV algorithm, which incorporates multiple factors, including total log R ratio, B allele frequency, and family information, based on an integrated hidden Markov model.

MAIN OUTCOME MEASURES

Statistical comparison and identification of CNVs between case and control using family information.

RESULTS

We identified 27,267 individual trio CNVs with a median size of 16.2 kb, aggregated in 2245 CNV regions. Most of the identified trio CNVs in this study showed well-defined CNV boundaries and overlapped with those in the Database of Genomic Variants (DGV) (83.4% in number and 79.2% in length). With the common CNV regions (264 CNV regions >5%), we performed a family-based association test with the risk of ACD.

CONCLUSIONS

Two CNV regions (chr6:29978470-29987783 and chr14:59896944-59916129) were significantly associated with the risk of ACD (P=0.05-0.003 and P=0.008, respectively). This study describes the first results of a genome-wide association analysis of individual CNVs with the risk of ACD and shows that 2 novel CNV loci may be involved in the risk of ACD.

FINANCIAL DISCLOSURE(S)

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Genome-wide association studies: a powerful tool for neurogenomics

As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.

Genome-wide association studies and the genetic dissection of complex traits

The availability of affordable high throughput technology for parallel genotyping has opened the field of genetics to genome-wide association studies (GWAS), and in the last few years hundreds of articles reporting results of GWAS for a variety of heritable traits have been published. What do these results tell us? Although GWAS have discovered a few hundred reproducible associations, this number is underwhelming in relation to the huge amount of data produced, and challenges the conjecture that common variants may be the genetic causes of common diseases. We argue that the massive amount of genetic data that result from these studies remains largely unexplored and unexploited because of the challenge of mining and modeling enormous data sets, the difficulty of using nontraditional computational techniques and the focus of accepted statistical analyses on controlling the false positive rate rather than limiting the false negative rate. In this article, we will review the common approach to analysis of GWAS data and then discuss options to learn more from these data. We will use examples from our ongoing studies of sickle cell anemia and also GWAS in multigenic traits.

Copy number variants (CNVs) in primate species using array-based comparative genomic hybridization

A substantial amount of genomic variation is now known to exist in humans and other primate species. Single nucleotide polymorphisms (SNPs) are thought to represent the vast majority of genomic differences among individuals in a given primate species and comprise about 0.1% of the genomes of two humans. However, recent studies have now shown that structural variation msay account for as much as 0.7% of the genomic differences in humans, of which copy number variants (CNVs) are the largest component. CNVs are segments of DNA that can range in size from hundreds of bases to millions of base pairs in length and have different number of copies between individuals. Recent technological advancements in array technologies led to genome-wide identification of CNVs and consequently revealed thousands of variable loci in humans, comprising as much as 12% of the human genome [A.J. Iafrate, L. Feuk, M.N. Rivera, M.L. Listewnik, P.K. Donahoe, Y. Qi, S.W. Scherer, C. Lee, Nat. Genet. 36 (2004) 949-951, [3]]. CNVs in humans have already been associated with susceptibility to certain complex diseases, dietary adaptation, and several neurological conditions. In addition, recent studies have shown that CNVs can be successfully implemented in population genetics research, providing important insights into human genetic variation. Nevertheless, the important role of CNVs in primate evolution and genetic diversity is still largely unknown. This article aims to outline the strengths and weaknesses of current comparative genomic hybridization array technologies that have been employed to detect CNV variation and the applications of these techniques to primate genetic research.

High-throughput methods for SNP genotyping

Single nucleotide polymorphisms (SNPs) are ideal markers for identifying genes associated with complex diseases for two main reasons. Firstly, SNPs are densely located on the human genome at about one SNP per approximately 500-1,000 base pairs. Secondly, a large number of commercial platforms are available for semiautomated or fully automated SNP genotyping. These SNP genotyping platforms serve different purposes since they differ in SNP selection, reaction chemistry, signal detection, throughput, cost, and assay flexibility. This chapter aims to give an overview of some of these platforms by explaining the technologies behind each platform and identifying the best application scenarios for each platform through cross-comparison. The readers may delve into more technical details in the following chapters.

An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases

BACKGROUND

Studies on the relationship between disease and genetic variations such as single nucleotide polymorphisms (SNPs) are important. Genetic variations can cause disease by influencing important biological regulation processes. Despite the needs for analyzing SNP and disease correlation, most existing databases provide information only on functional variants at specific locations on the genome, or deal with only a few genes associated with disease. There is no combined resource to widely support gene-, SNP-, and disease-related information, and to capture relationships among such data. Therefore, we developed an integrated database-pipeline system for studying SNPs and diseases.

RESULTS

To implement the pipeline system for the integrated database, we first unified complicated and redundant disease terms and gene names using the Unified Medical Language System (UMLS) for classification and noun modification, and the HUGO Gene Nomenclature Committee (HGNC) and NCBI gene databases. Next, we collected and integrated representative databases for three categories of information. For genes and proteins, we examined the NCBI mRNA, UniProt, UCSC Table Track and MitoDat databases. For genetic variants we used the dbSNP, JSNP, ALFRED, and HGVbase databases. For disease, we employed OMIM, GAD, and HGMD databases. The database-pipeline system provides a disease thesaurus, including genes and SNPs associated with disease. The search results for these categories are available on the web page http://diseasome.kobic.re.kr/, and a genome browser is also available to highlight findings, as well as to permit the convenient review of potentially deleterious SNPs among genes strongly associated with specific diseases and clinical phenotypes.

CONCLUSION

Our system is designed to capture the relationships between SNPs associated with disease and disease-causing genes. The integrated database-pipeline provides a list of candidate genes and SNP markers for evaluation in both epidemiological and molecular biological approaches to diseases-gene association studies. Furthermore, researchers then can decide semi-automatically the data set for association studies while considering the relationships between genetic variation and diseases. The database can also be economical for disease-association studies, as well as to facilitate an understanding of the processes which cause disease. Currently, the database contains 14,674 SNP records and 109,715 gene records associated with human diseases and it is updated at regular intervals.