From the periphery to centre stage: de novo single nucleotide variants play a key role in human genetic disease.

Human germline mutations arise anew during meiosis in every generation. Such spontaneously occurring genetic variants are termed de novo mutations. Although the introduction of microarray based approaches led to the discovery of numerous de novo copy number variants underlying a range of human genetic conditions, de novo single nucleotide variants (SNVs) remained refractory to analysis at the whole genome level until the advent of next generation sequencing technologies such as whole genome sequencing and whole exome sequencing. These approaches have recently allowed the estimation of the mutation rate of de novo SNVs and greatly increased our understanding of their contribution to human genetic disease. Indeed, de novo SNVs have been found to underlie various common human neurodevelopmental conditions such as schizophrenia, autism and intellectual disability, as well as sporadic cases of rare Mendelian disorders. In many cases, however, confirmation of the pathogenicity of identified de novo SNVs remains a major challenge.

Statistical challenges associated with detecting copy number variations with next-generation sequencing.

MOTIVATION: Analysing next-generation sequencing (NGS) data for copy number variations (CNVs) detection is a relatively new and challenging field, with no accepted standard protocols or quality control measures so far. There are by now several algorithms developed for each of the four broad methods for CNV detection using NGS, namely the depth of coverage (DOC), read-pair, split-read and assembly-based methods. However, because of the complexity of the genome and the short read lengths from NGS technology, there are still many challenges associated with the analysis of NGS data for CNVs, no matter which method or algorithm is used. RESULTS: In this review, we describe and discuss areas of potential biases in CNV detection for each of the four methods. In particular, we focus on issues pertaining to (i) mappability, (ii) GC-content bias, (iii) quality control measures of reads and (iv) difficulty in identifying duplications. To gain insights to some of the issues discussed, we also download real data from the 1000 Genomes Project and analyse its DOC data. We show examples of how reads in repeated regions can affect CNV detection, demonstrate current GC-correction algorithms, investigate sensitivity of DOC algorithm before and after quality control of reads and discuss reasons for which duplications are harder to detect than deletions.

Exome sequencing: dual role as a discovery and diagnostic tool.

Recent developments in high-throughput sequence capture methods and next-generation sequencing technologies have now made exome sequencing a viable approach to elucidate the genetic basis of Mendelian disorders with hitherto unknown etiology. In addition, exome sequencing is increasingly being employed as a diagnostic tool for specific genetic diseases, particularly in the context of those disorders characterized by significant genetic and phenotypic heterogeneity, for example, Charcot-Marie-Tooth disease and congenital disorders of glycosylation. Such disorders are challenging to interrogate with conventional polymerase chain reaction-Sanger sequencing methods, because of the inherent difficulty in prioritizing candidate genes for diagnostic testing. Here, we explore the value of exome sequencing as a diagnostic tool and discuss whether exome sequencing can come to serve a dual role in diagnosis and discovery. We summarize the current status of exome sequencing, the technical challenges facing it, and its adaptation to diagnostics, and make recommendations for the use of exome sequencing as a routine diagnostic tool. Finally, we discuss pertinent ethical concerns, such as the use of exome sequencing data, originally generated in a diagnostic context, in research investigations.

Singapore Genome Variation Project: a haplotype map of three Southeast Asian populations.

The Singapore Genome Variation Project (SGVP) provides a publicly available resource of 1.6 million single nucleotide polymorphisms (SNPs) genotyped in 268 individuals from the Chinese, Malay, and Indian population groups in Southeast Asia. This online database catalogs information and summaries on genotype and phased haplotype data, including allele frequencies, assessment of linkage disequilibrium (LD), and recombination rates in a format similar to the International HapMap Project. Here, we introduce this resource and describe the analysis of human genomic variation upon agglomerating data from the HapMap and the Human Genome Diversity Project, providing useful insights into the population structure of the three major population groups in Asia. In addition, this resource also surveyed across the genome for variation in regional patterns of LD between the HapMap and SGVP populations, and for signatures of positive natural selection using two well-established metrics: iHS and XP-EHH. The raw and processed genetic data, together with all population genetic summaries, are publicly available for download and browsing through a web browser modeled with the Generic Genome Browser.

Gene discovery in familial cancer syndromes by exome sequencing: prospects for the elucidation of familial colorectal cancer type X.

Recent advances in genotyping and sequencing technologies have provided powerful tools with which to explore the genetic basis of both Mendelian (monogenic) and sporadic (polygenic) diseases. Several hundred genome-wide association studies have so far been performed to explore the genetics of various polygenic or complex diseases including those cancers with a genetic predisposition. Exome sequencing has also proven very successful in elucidating the etiology of a range of hitherto poorly understood Mendelian disorders caused by high-penetrance mutations. Despite such progress, the genetic etiology of several familial cancers, such as familial colorectal cancer type X, has remained elusive. Familial colorectal cancer type X and Lynch syndrome are similar in terms of their fulfilling certain clinical criteria, but the former group is not characterized by germline mutations in DNA mismatch-repair genes. On the other hand, the genetics of sporadic colorectal cancer have been investigated by genome-wide association studies, leading to the identification of multiple new susceptibility loci. In addition, there is increasing evidence to suggest that familial and sporadic cancers exhibit similarities in terms of their genetic etiologies. In this review, we have summarized our current knowledge of familial colorectal cancer type X, discussed current approaches to probing its genetic etiology through the application of new sequencing technologies and the recruitment of the results of colorectal cancer genome-wide association studies, and explore the challenges that remain to be overcome given the uncertainty of the current genetic model (ie, monogenic vs polygenic) of familial colorectal cancer type X.

Regions of homozygosity in three Southeast Asian populations.

The genomes of outbred populations were first shown in 2006 to contain regions of homozygosity (ROHs) of several megabases. Further studies have also investigated the characteristics of ROHs in healthy individuals in various populations but there are no studies on Singapore populations to date. This study aims to identify and investigate the characteristics of ROHs in three Singapore populations. A total of 268 samples (96 Chinese, 89 Malays and 83 Indians) are genotyped on Illumina Human 1 M Beadchip and Affymetrix Genome-Wide Human SNP Array 6.0. We use the PennCNV algorithm to detect ROHs. We report an abundance of ROHs (≥500 kb), with an average of more than one hundred regions per individual. On average, the Indian population has the lowest number of ROHs and smallest total length of ROHs per individual compared with the Chinese and Malay populations. We further investigate the relationship between the occurrence of ROHs and haplotype frequency, regional linkage disequilibrium (LD) and positive selection. Based on the results of this data set, we find that the frequency of occurrence of ROHs is positively associated with haplotype frequency and regional LD. The majority of regions detected for recent positive selection and regions with differential LD between populations overlap with the ROH loci. When we consider both the location of the ROHs and the allelic form of the ROHs, we are able to separate the populations by principal component analysis, demonstrating that ROHs contain information on population structure and the demographic history of a population.

Clinical cancer genome and precision medicine.

Revolutionary sequencing technologies have changed biomedical research and life science exponentially. Revealing the whole landscape of causal somatic and inherited mutations underlying individual patient's cancer sample by whole-genome sequencing (WGS) and whole-exome sequencing (WES) can lead to not only a new mutations-based taxonomy of solid tumors (Stratton, Science 331:1553-1558, 2011). But also shapes a roadmap for precision medicine (Roychowdhury et al., Sci Transl Med 3:111ra121, 2011; Roukos, Expert Rev Mol Diagn 12:215-218, 2012; Mirnezami et al., N Engl J Med 366:489-491, 2012). This inevitable approach for personalized diagnostics in concert with free-falling genome sequencing costs raises now the question of applying next-generation sequencing (NGS) technology in the clinic. In the pragmatic clinical world and in contrast to innovative research, is NGS-based clinical evidence sufficient for decision-making on tailoring the best available treatment to the individual cancer patient?

Human genetics and genomics a decade after the release of the draft sequence of the human genome.

Substantial progress has been made in human genetics and genomics research over the past ten years since the publication of the draft sequence of the human genome in 2001. Findings emanating directly from the Human Genome Project, together with those from follow-on studies, have had an enormous impact on our understanding of the architecture and function of the human genome. Major developments have been made in cataloguing genetic variation, the International HapMap Project, and with respect to advances in genotyping technologies. These developments are vital for the emergence of genome-wide association studies in the investigation of complex diseases and traits. In parallel, the advent of high-throughput sequencing technologies has ushered in the 'personal genome sequencing' era for both normal and cancer genomes, and made possible large-scale genome sequencing studies such as the 1000 Genomes Project and the International Cancer Genome Consortium. The high-throughput sequencing and sequence-capture technologies are also providing new opportunities to study Mendelian disorders through exome sequencing and whole-genome sequencing. This paper reviews these major developments in human genetics and genomics over the past decade.

Studying the epigenome using next generation sequencing.

The advances in next generation sequencing (NGS) technologies have had a significant impact on epigenomic research. The arrival of NGS technologies has enabled a more powerful sequencing based method--that is, ChIP-Seq--to interrogate whole genome histone modifications, improving on the conventional microarray based method (ChIP-chip). Similarly, the first human DNA methylome was mapped using NGS technologies. More importantly, studies of DNA methylation and histone modification using NGS technologies have yielded new discoveries and improved our knowledge of human biology and diseases. The concept that cytosine methylation was restricted to CpG dinucleotides has only been recently challenged by new data generated from sequencing the DNA methylome. Approximately 25% of all cytosine methylation identified in stem cells was in a non-CG context. The non-CG methylation was more enriched in gene bodies and depleted in protein binding sites and enhancers. The recent developments of third generation sequencing technologies have shown promising results of directly sequencing methylated nucleotides and having the ability to differentiate between 5-methylcytosine and 5-hydroxymethylcytosine. The importance of 5-hydroxymethylcytosine remains largely unknown, but it has been found in various tissues. 5-hydroxymethylcytosine was particularly enriched at promoters and in intragenic regions (gene bodies) but was largely absent from non-gene regions in DNA from human brain frontal lobe tissue. The presence of 5-hydroxymethylcytosine in gene bodies was more positively correlated with gene expression levels. The importance of studying 5-methylcytosine and 5-hydroxymethylcytosine separately for their biological roles will become clearer when more efficient methods to distinguish them are available.

Revisiting Mendelian disorders through exome sequencing.

Over the past several years, more focus has been placed on dissecting the genetic basis of complex diseases and traits through genome-wide association studies. In contrast, Mendelian disorders have received little attention mainly due to the lack of newer and more powerful methods to study these disorders. Linkage studies have previously been the main tool to elucidate the genetics of Mendelian disorders; however, extremely rare disorders or sporadic cases caused by de novo variants are not amendable to this study design. Exome sequencing has now become technically feasible and more cost-effective due to the recent advances in high-throughput sequence capture methods and next-generation sequencing technologies which have offered new opportunities for Mendelian disorder research. Exome sequencing has been swiftly applied to the discovery of new causal variants and candidate genes for a number of Mendelian disorders such as Kabuki syndrome, Miller syndrome and Fowler syndrome. In addition, de novo variants were also identified for sporadic cases, which would have not been possible without exome sequencing. Although exome sequencing has been proven to be a promising approach to study Mendelian disorders, several shortcomings of this method must be noted, such as the inability to capture regulatory or evolutionary conserved sequences in non-coding regions and the incomplete capturing of all exons.

Regions of homozygosity and their impact on complex diseases and traits.

Regions of homozygosity (ROHs) are more abundant in the human genome than previously thought. These regions are without heterozygosity, i.e. all the genetic variations within the regions have two identical alleles. At present there are no standardized criteria for defining the ROHs resulting in the different studies using their own criteria in the analysis of homozygosity. Compared to the era of genotyping microsatellite markers, the advent of high-density single nucleotide polymorphism genotyping arrays has provided an unparalleled opportunity to comprehensively detect these regions in the whole genome in different populations. Several studies have identified ROHs which were associated with complex phenotypes such as schizophrenia, late-onset of Alzheimer's disease and height. Collectively, these studies have conclusively shown the abundance of ROHs larger than 1 Mb in outbred populations. The homozygosity association approach holds great promise in identifying genetic susceptibility loci harboring recessive variants for complex diseases and traits.

A population-based study of copy number variants and regions of homozygosity in healthy Swedish individuals.

The abundance of copy number variants (CNVs) and regions of homozygosity (ROHs) have been well documented in previous studies. In addition, their roles in complex diseases and traits have since been increasingly appreciated. However, only a limited amount of CNV and ROH data is currently available for the Swedish population. We conducted a population-based study to detect and characterize CNVs and ROHs in 87 randomly selected healthy Swedish individuals using the Affymetrix SNP Array 6.0. More than 600 CNV loci were detected in the population using two different CNV-detection algorithms (PennCNV and Birdsuite). A total of 196 loci were consistently identified by both algorithms, suggesting their reliability. Numerous disease-associated and pharmacogenetics-related genes were found to be overlapping with common CNV loci such as CFHR1/R3, LCE3B/3C, UGT2B17 and GSTT1. Correlation analysis between copy number polymorphisms (CNPs) and genome-wide association studies-identified single-nucleotide polymorphisms also indicates the potential roles of several CNPs as causal variants for diseases and traits such as body mass index, Crohn's disease and multiple sclerosis. In addition, we also identified a total of 14 815 ROHs 500 kb or 2814 ROHs 1M in the Swedish individuals with an average of 170 and 32 regions detected per individual respectively. Approximately 141 Mb or 4.92% of the genome is homozygous in each individual of the Swedish population. This is the first population-based study to investigate the population characteristics of CNVs and ROHs in the Swedish population. This study found many CNV loci that warrant further investigation, and also highlighted the abundance and importance of investigating ROHs for their associations with complex diseases and traits.

Copy number polymorphisms in new HapMap III and Singapore populations.

Copy number variations can be identified using newer genotyping arrays with higher single nucleotide polymorphisms (SNPs) density and copy number probes accompanied by newer algorithms. McCarroll et al. (2008) applied these to the HapMap II samples and identified 1316 copy number polymorphisms (CNPs). In our study, we applied the same approach to 859 samples from three Singapore populations and seven HapMap III populations. Approximately 50% of the 1291 autosomal CNPs were found to be polymorphic only in populations of non-African ancestry. Pairwise comparisons among the 10 populations showed substantial differences in the CNPs frequencies. Additionally, 698 CNPs showed significant differences with false discovery rate (FDR)<0.01 among the 10 populations and these loci overlap with known disease-associated or pharmacogenetic-related genes such as CFHR3 and CFHR1 (age related macular degeneration), GSTTI (metabolism of various carcinogenic compounds and cancers) and UGT2B17 (prostate cancer and graft-versus-host disease). The correlations between CNPs and genome-wide association studies-SNPs were investigated and several loci, which were previously unreported, that may potentially be implicated in complex diseases and traits were found; for example, childhood acute lymphoblastic leukaemia, age-related macular degeneration, breast cancer, response to antipsychotic treatment, rheumatoid arthritis and type-1 diabetes. Additionally, we also found 5014 novel copy number loci that have not been reported previously by McCarroll et al. (2008) in the 10 populations.

Molecular epidemiology and its current clinical use in cancer management.

The revelation of the entire human DNA sequence in 2001, and the launching of the international haplotype map (HapMap) project, made the identification of common markers of disease possible, dramatically transforming molecular epidemiology. In recent years, the development of, and discoveries within, human genome research have been rapid, highlighted by the current explosion of genome-wide association studies (GWAS). GWAS aim at finding germline changes that increase cancer risk. An equally important and rapid development had been seen in cancer genomics, with great strides being made in our understanding of somatic mutations that allow and accompany cancer development. In this review we discuss whether it is currently possible to use these new discoveries to aid the reduction of cancer mortality by reducing risk of disease, improving prognosis, and keeping complications due to treatment to a minimum. Findings from GWAS have mostly been used to predict risk, but there is the potential to use them for prognostication and even treatment prediction. Expression arrays have identified prognostic patterns for breast cancer, but few reliable patterns are available for treatment prediction. More importantly, virtually no genetic signatures are available to predict morbidity from treatment. Thus, there is a need to bring different biological techniques together and integrate them with existing clinical oncological care for a simultaneous risk and outcome assessment.

Genomic copy number variations in three Southeast Asian populations.

Research on the role of copy number variations (CNVs) in the genetic risk of diseases in Asian populations has been hampered by a relative lack of reference CNV maps for Asian populations outside the East Asians. In this article, we report the population characteristics of CNVs in Chinese, Malay, and Asian Indian populations in Singapore. Using the Illumina Human 1M Beadchip array, we identify 1,174 CNV loci in these populations that corroborated with findings when the same samples were typed on the Affymetrix 6.0 platform. We identify 441 novel loci not previously reported in the Database of Genomic Variations (DGV). We observe a considerable number of loci that span all three populations and were previously unreported, as well as population-specific loci that are quite common in the respective populations. From this we observe the distribution of CNVs in the Asian Indian population to be considerably different from the Chinese and Malay populations. About half of the deletion loci and three-quarters of duplication loci overlap UCSC genes. Tens of loci show population differentiation and overlap with genes previously known to be associated with genetic risk of diseases. One of these loci is the CYP2A6 deletion, previously linked to reduced susceptibility to lung cancer.

The pursuit of genome-wide association studies: where are we now?

It is now 5 years since the first genome-wide association studies (GWAS), published in 2005, identified a common risk allele with large effect size for age-related macular degeneration in a small sample set. Following this exciting finding, researchers have become optimistic about the prospect of the genome-wide association approach. However, most of the risk alleles identified in the subsequent GWAS for various complex diseases are common with small effect sizes (odds ratio <1.5). So far, more than 450 GWAS have been published and the associations of greater than 2000 single nucleotide polymorphisms (SNPs) or genetic loci were reported. The aim of this review paper is to give an overview of the evolving field of GWAS, discuss the progress that has been made by GWAS and some of the interesting findings, and summarize what we have learned over the past 5 years about the genetic basis of human complex diseases. This review will focus on GWAS of SNPs association for complex diseases but not studies of copy number variations.

The discovery of human genetic variations and their use as disease markers: past, present and future.

The field of human genetic variations has progressed rapidly over the past few years. It has added much information and deepened our knowledge and understanding of the diversity of genetic variations in the human genome. This significant progress has been driven mainly by the developments of microarray and next generation sequencing technologies. The array-based methods have been widely used for large-scale copy number variation (CNV) detection in the human genome. The arrival of next generation sequencing technologies, which enabled the completion of several whole genome resequencing studies, has also resulted in a massive discovery of genetic variations. These studies have identified several hundred thousand short indels and a total of thousands of CNVs and other structural variations in the human genome. The discovery of these 'newer' types of genetic variations, indels, CNVs and copy neutral variations (inversions and translocations) has also widened the scope of genetic markers in human genetic and disease gene mapping studies. The aim of this review article is to summarize the latest developments in the discovery of human genetic variations and address the issue of inadequate coverage of genetic variations in the current genome-wide association studies, which mainly focuses on common SNPs. Finally, we also discuss the future directions in the field and their impacts on next generation genome-wide association studies.