The role and challenges of exome sequencing in studies of human diseases

Rare and low-frequency variants in human common diseases and other complex traits

In humans, most of the genetic variation is rare and often population-specific. Whereas the role of rare genetic variants in familial monogenic diseases is firmly established, we are only now starting to explore the contribution of this class of genetic variation to human common diseases and other complex traits. Such large-scale experiments are possible due to the development of next-generation DNA sequencing. Early findings suggested that rare and low-frequency coding variation might have a large effect on human phenotypes (eg, PCSK9 missense variants on low-density lipoprotein-cholesterol and coronary heart diseases). This observation sparked excitement in prognostic and diagnostic medicine, as well as in genetics-driven strategies to develop new drugs. In this review, I describe results and present initial conclusions regarding some of the recent rare and low-frequency variant discoveries. We can already assume that most phenotype-associated rare and low-frequency variants have modest-to-weak phenotypical effect. Thus, we will need large cohorts to identify them, as for common variants in genome-wide association studies. As we expand the list of associated rare and low-frequency variants, we can also better recognise the current limitations: we need to develop better statistical methods to optimally test association with rare variants, including non-coding variation, and to account for potential confounders such as population stratification.

Genetics of diabetic retinopathy

Diabetic retinopathy (DR) is a polygenic disorder. Twin studies and familial aggregation studies have documented clear familial clustering. Heritability has been estimated to be as high as 27 % for any DR and 52 % for proliferative diabetic retinopathy (PDR), an advanced form of the disease. Linkage analyses, candidate gene association studies and genome-wide association studies (GWAS) performed to date have not identified any widely reproducible risk loci for DR. Combined analysis of the data from multiple GWAS is emerging as an important next step to explain the unaccounted heritability. Key factors to future discovery of the genetic underpinnings of DR are precise DR ascertainment, a focus on the more heritable disease forms such as PDR, stringent selection of control participants with regards to duration of diabetes, and methods that allow combination of existing datasets from different ethnicities to achieve sufficient sample sizes to detect variants with modest effect sizes.

Validation and assessment of variant calling pipelines for next-generation sequencing

Background

The processing and analysis of the large scale data generated by next-generation sequencing (NGS) experiments is challenging and is a burgeoning area of new methods development. Several new bioinformatics tools have been developed for calling sequence variants from NGS data. Here, we validate the variant calling of these tools and compare their relative accuracy to determine which data processing pipeline is optimal.

Results

We developed a unified pipeline for processing NGS data that encompasses four modules: mapping, filtering, realignment and recalibration, and variant calling. We processed 130 subjects from an ongoing whole exome sequencing study through this pipeline. To evaluate the accuracy of each module, we conducted a series of comparisons between the single nucleotide variant (SNV) calls from the NGS data and either gold-standard Sanger sequencing on a total of 700 variants or array genotyping data on a total of 9,935 single-nucleotide polymorphisms. A head to head comparison showed that Genome Analysis Toolkit (GATK) provided more accurate calls than SAMtools (positive predictive value of 92.55% vs. 80.35%, respectively). Realignment of mapped reads and recalibration of base quality scores before SNV calling proved to be crucial to accurate variant calling. GATK HaplotypeCaller algorithm for variant calling outperformed the UnifiedGenotype algorithm. We also showed a relationship between mapping quality, read depth and allele balance, and SNV call accuracy. However, if best practices are used in data processing, then additional filtering based on these metrics provides little gains and accuracies of >99% are achievable.

Conclusions

Our findings will help to determine the best approach for processing NGS data to confidently call variants for downstream analyses. To enable others to implement and replicate our results, all of our codes are freely available at http://metamoodics.org/wes.

Exome Sequencing in Fetuses with Structural Malformations

Prenatal diagnostic testing is a rapidly advancing field. An accurate diagnosis of structural anomalies and additional abnormalities in fetuses with structural anomalies is important to allow “triage” and designation of prognosis. This will allow parents to make an informed decision relating to the pregnancy. This review outlines the current tests used in prenatal diagnosis, focusing particularly on “new technologies” such as exome sequencing. We demonstrate the utility of exome sequencing above that of conventional karyotyping and Chromosomal Microarray (CMA) alone by outlining a recent proof of concept study investigating 30 parent-fetus trios where the fetus is known to have a structural anomaly. This may allow the identification of pathological gene anomalies and consequently improved prognostic profiling, as well as excluding anomalies and distinguishing between de novo and inherited mutations, in order to estimate the recurrence risk in future pregnancies. The potential ethical dilemmas surrounding exome sequencing are also considered, and the future of prenatal genetic diagnosis is discussed.

The neurogenetics of atypical parkinsonian disorders

Although classic Parkinson disease is the disorder most commonly associated with the clinical feature of parkinsonism, there is in fact a broader spectrum of disease represented by a collection of phenotypically similar neurodegenerative conditions that mimic many of its core features. These atypical parkinsonian disorders most commonly include progressive supranuclear palsy and corticobasal degeneration, disorders both associated with frontotemporal dementia, as well as multiple system atrophy and dementia with Lewy bodies. Although the clinical distinction of these disorders still remains a challenge to physicians, recent advances in genetics are poised to tease apart the differences. Insights into the molecular etiologies underlying these conditions will improve diagnosis, yield a better understanding of the underlying disease pathology, and ultimately lend stimulation to the development of potential treatments. At the same time, the wide range of phenotypes observed from mutations in a single gene warrants broad testing facilitated by advances in DNA sequencing. These expanding genomic approaches, ranging from the use of next-generation sequencing to identify causative or risk-associated gene variations to the study of epigenetic modification linking human genetics to environmental factors, are poised to lead the field into a new age of discovery.

TBX1 mutation identified by exome sequencing in a Japanese family with 22q11.2 deletion syndrome-like craniofacial features and hypocalcemia

Background

Although TBX1 mutations have been identified in patients with 22q11.2 deletion syndrome (22q11.2DS)-like phenotypes including characteristic craniofacial features, cardiovascular anomalies, hypoparathyroidism, and thymic hypoplasia, the frequency of TBX1 mutations remains rare in deletion-negative patients. Thus, it would be reasonable to perform a comprehensive genetic analysis in deletion-negative patients with 22q11.2DS-like phenotypes.

Methodology/Principal Findings

We studied three subjects with craniofacial features and hypocalcemia (group 1), two subjects with craniofacial features alone (group 2), and three subjects with normal phenotype within a single Japanese family. Fluorescence in situ hybridization analysis excluded chromosome 22q11.2 deletion, and genomewide array comparative genomic hybridization analysis revealed no copy number change specific to group 1 or groups 1+2. However, exome sequencing identified a heterozygous TBX1 frameshift mutation (c.1253delA, p.Y418fsX459) specific to groups 1+2, as well as six missense variants and two in-frame microdeletions specific to groups 1+2 and two missense variants specific to group 1. The TBX1 mutation resided at exon 9C and was predicted to produce a non-functional truncated protein missing the nuclear localization signal and most of the transactivation domain.

Conclusions/Significance

Clinical features in groups 1+2 are well explained by the TBX1 mutation, while the clinical effects of the remaining variants are largely unknown. Thus, the results exemplify the usefulness of exome sequencing in the identification of disease-causing mutations in familial disorders. Furthermore, the results, in conjunction with the previous data, imply that TBX1 isoform C is the biologically essential variant and that TBX1 mutations are associated with a wide phenotypic spectrum, including most of 22q11.2DS phenotypes.

Epigenetics and depression: return of the repressed

INTRODUCTION

Epigenetics has recently emerged as a potential mechanism by which adverse environmental stimuli can result in persistent changes in gene expression. Epigenetic mechanisms function alongside the DNA sequence to modulate gene expression and ultimately influence protein production. The current review provides an introduction and overview of epigenetics with a particular focus on preclinical and clinical studies relevant to major depressive disorder (MDD).

METHODS

PubMed and Web of Science databases were interrogated from January 1995 up to December 2012 using combinations of search terms, including "epigenetic", "microRNA" and "DNA methylation" cross referenced with "depression", "early life stress" and "antidepressant".

RESULTS

There is an association between adverse environmental stimuli, such as early life stress, and epigenetic modification of gene expression. Epigenetic changes have been reported in humans with MDD and may serve as biomarkers to improve diagnosis. Antidepressant treatments appear to reverse or initiate compensatory epigenetic alterations that may be relevant to their mechanism of action.

LIMITATIONS

As a narrative review, the current report was interpretive and qualitative in nature.

CONCLUSION

Epigenetic modification of gene expression provides a mechanism for understanding the link between long-term effects of adverse life events and the changes in gene expression that are associated with depression. Although still a developing field, in the future, epigenetic modifications of gene expression may provide novel biomarkers to predict future susceptibility and/or onset of MDD, improve diagnosis, and aid in the development of epigenetics-based therapies for depression.

Genetics of proteasome diseases

The proteasome is a large, multiple subunit complex that is capable of degrading most intracellular proteins. Polymorphisms in proteasome subunits are associated with cardiovascular diseases, diabetes, neurological diseases, and cancer. One polymorphism in the proteasome gene PSMA6 (-8C/G) is associated with three different diseases: type 2 diabetes, myocardial infarction, and coronary artery disease. One type of proteasome, the immunoproteasome, which contains inducible catalytic subunits, is adapted to generate peptides for antigen presentation. It has recently been shown that mutations and polymorphisms in the immunoproteasome catalytic subunit PSMB8 are associated with several inflammatory and autoinflammatory diseases including Nakajo-Nishimura syndrome, CANDLE syndrome, and intestinal M. tuberculosis infection. This comprehensive review describes the disease-related polymorphisms in proteasome genes associated with human diseases and the physiological modulation of proteasome function by these polymorphisms. Given the large number of subunits and the central importance of the proteasome in human physiology as well as the fast pace of detection of proteasome polymorphisms associated with human diseases, it is likely that other polymorphisms in proteasome genes associated with diseases will be detected in the near future. While disease-associated polymorphisms are now readily discovered, the challenge will be to use this genetic information for clinical benefit.

Profiling, Bioinformatic, and Functional Data on the Developing Olfactory/GnRH System Reveal Cellular and Molecular Pathways Essential for This Process and Potentially Relevant for the Kallmann Syndrome

During embryonic development, immature neurons in the olfactory epithelium (OE) extend axons through the nasal mesenchyme, to contact projection neurons in the olfactory bulb. Axon navigation is accompanied by migration of the GnRH+ neurons, which enter the anterior forebrain and home in the septo-hypothalamic area. This process can be interrupted at various points and lead to the onset of the Kallmann syndrome (KS), a disorder characterized by anosmia and central hypogonadotropic hypogonadism. Several genes has been identified in human and mice that cause KS or a KS-like phenotype. In mice a set of transcription factors appears to be required for olfactory connectivity and GnRH neuron migration; thus we explored the transcriptional network underlying this developmental process by profiling the OE and the adjacent mesenchyme at three embryonic ages. We also profiled the OE from embryos null for Dlx5, a homeogene that causes a KS-like phenotype when deleted. We identified 20 interesting genes belonging to the following categories: (1) transmembrane adhesion/receptor, (2) axon-glia interaction, (3) scaffold/adapter for signaling, (4) synaptic proteins. We tested some of them in zebrafish embryos: the depletion of five (of six) Dlx5 targets affected axonal extension and targeting, while three (of three) affected GnRH neuron position and neurite organization. Thus, we confirmed the importance of cell-cell and cell-matrix interactions and identified new molecules needed for olfactory connection and GnRH neuron migration. Using available and newly generated data, we predicted/prioritized putative KS-disease genes, by building conserved co-expression networks with all known disease genes in human and mouse. The results show the overall validity of approaches based on high-throughput data and predictive bioinformatics to identify genes potentially relevant for the molecular pathogenesis of KS. A number of candidate will be discussed, that should be tested in future mutation screens.