Chee-Seng Ku

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.

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.

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. Ann Neurol 2012;71:5–14

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.

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.

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.

A new paradigm emerges from the study of de novo mutations in the context of neurodevelopmental disease.

The study of de novo point mutations (new germline mutations arising from the gametes of the parents) remained largely static until the arrival of next-generation sequencing technologies, which made both whole-exome sequencing (WES) and whole-genome sequencing (WGS) feasible in practical terms. Single nucleotide polymorphism genotyping arrays have been used to identify de novo copy-number variants in a number of common neurodevelopmental conditions such as schizophrenia and autism. By contrast, as point mutations and microlesions occurring de novo are refractory to analysis by these microarray-based methods, little was known about either their frequency or impact upon neurodevelopmental disease, until the advent of WES. De novo point mutations have recently been implicated in schizophrenia, autism and mental retardation through the WES of case-parent trios. Taken together, these findings strengthen the hypothesis that the occurrence of de novo mutations could account for the high prevalence of such diseases that are associated with a marked reduction in fecundity. De novo point mutations are also known to be responsible for many sporadic cases of rare dominant Mendelian disorders such as Kabuki syndrome, Schinzel–Giedion syndrome and Bohring–Opitz syndrome. These disorders share a common feature in that they are all characterized by intellectual disability. In summary, recent WES studies of neurodevelopmental and neuropsychiatric disease have provided new insights into the role of de novo mutations in these disorders. Our knowledge of de novo mutations is likely to be further accelerated by WGS. However, the collection of case-parent trios will be a prerequisite for such studies. This review aims to discuss recent developments in the study of de novo mutations made possible by technological advances in DNA sequencing.

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.

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.

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.