Towards a complete resolution of the genetic architecture of disease

Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to Sclerotinia sclerotiorum

Sclerotinia sclerotiorum (Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor genes. Genome-wide identification of genes involved in QDR to Ss is yet to be conducted. In this study, we integrated several assays including genome-wide association study (GWAS), multi-omics co-localization, and machine learning prediction to identify, on a genome-wide scale, genes involved in the oilseed rape QDR to Ss. Employing GWAS and multi-omics co-localization, we identified seven resistance-associated loci (RALs) associated with oilseed rape resistance to Ss. Furthermore, we developed a machine learning algorithm and named it Integrative Multi-Omics Analysis and Machine Learning for Target Gene Prediction (iMAP), which integrates multi-omics data to rapidly predict disease resistance-related genes within a broad chromosomal region. Through iMAP based on the identified RALs, we revealed multiple calcium signaling genes related to the QDR to Ss. Population-level analysis of selective sweeps and haplotypes of variants confirmed the positive selection of the predicted calcium signaling genes during evolution. Overall, this study has developed an algorithm that integrates multi-omics data and machine learning methods, providing a powerful tool for predicting target genes associated with specific traits. Furthermore, it makes a basis for further understanding the role and mechanisms of calcium signaling genes in the QDR to Ss.

The Road so Far in Colorectal Cancer Pharmacogenomics: Are We Closer to Individualised Treatment?

In recent decades, survival rates in colorectal cancer have improved greatly due to pharmacological treatment. However, many patients end up developing adverse drug reactions that can be severe or even life threatening, and that affect their quality of life. These remain a limitation, as they may force dose reduction or treatment discontinuation, diminishing treatment efficacy. From candidate gene approaches to genome-wide analysis, pharmacogenomic knowledge has advanced greatly, yet there is still huge and unexploited potential in the use of novel technologies such as next-generation sequencing strategies. This review summarises the road of colorectal cancer pharmacogenomics so far, presents considerations and directions to be taken for further works and discusses the path towards implementation into clinical practice.

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice

Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine mapping process to find the causal gene controlling the trait. With the availability of a rich assortment of genomic and functional genomic data, it is possible to develop a computational method to facilitate faster identification of causal genes. We developed QTG-Finder, a machine learning based algorithm to prioritize causal genes by ranking genes within a quantitative trait locus (QTL). Two predictive models were trained separately based on known causal genes in Arabidopsis and rice. An independent validation analysis showed that the models could recall about 64% of Arabidopsis and 79% of rice causal genes when the top 20% ranked genes were considered. The top 20% ranked genes can range from 10 to 100 genes, depending on the size of a QTL. The models can prioritize different types of traits though at different efficiency. We also identified several important features of causal genes including paralog copy number, being a transporter, being a transcription factor, and containing SNPs that cause premature stop codon. This work lays the foundation for systematically understanding characteristics of causal genes and establishes a pipeline to predict causal genes based on public data.

Genomic Regions Associated with IgE Levels against Culicoides spp. Antigens in Three Horse Breeds

Insect bite hypersensitivity (IBH), which is a cutaneous allergic reaction to antigens from Culicoides spp., is the most prevalent skin disorder in horses. Misdiagnosis is possible, as IBH is usually diagnosed based on clinical signs. Our study is the first to employ IgE levels against several recombinant Culicoides spp. allergens as an objective, independent, and quantitative phenotype to improve the power to detect genetic variants that underlie IBH. Genotypes of 200 Shetland ponies, 127 Icelandic horses, and 223 Belgian Warmblood horses were analyzed while using a mixed model approach. No single-nucleotide polymorphism (SNP) passed the Bonferroni corrected significance threshold, but several regions were identified within and across breeds, which confirmed previously identified regions of interest and, in addition, identifying new regions of interest. Allergen-specific IgE levels are a continuous and objective phenotype that allow for more powerful analyses when compared to a case-control set-up, as more significant associations were obtained. However, the use of a higher density array seems necessary to fully employ the use of IgE levels as a phenotype. While these results still require validation in a large independent dataset, the use of allergen-specific IgE levels showed value as an objective and continuous phenotype that can deepen our understanding of the biology underlying IBH.

Genetic and epigenetic influences on the loss of tolerance in autoimmunity

Immunological tolerance loss is fundamental to the development of autoimmunity; however, the underlying mechanisms remain elusive. Immune tolerance consists of central and peripheral tolerance. Central tolerance, which occurs in the thymus for T cells and bone marrow for B cells, is the primary way that the immune system discriminates self from non-self. Peripheral tolerance, which occurs in tissues and lymph nodes after lymphocyte maturation, controls self-reactive immune cells and prevents over-reactive immune responses to various environment factors. Loss of tolerance results in autoimmune disorders, such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), type 1 diabetes (T1D) and primary biliary cirrhosis (PBC). The etiology and pathogenesis of autoimmune diseases are highly complicated. Both genetic predisposition and epigenetic modifications are implicated in the loss of tolerance and autoimmunity. In this review, we will discuss the genetic and epigenetic influences on tolerance breakdown in autoimmunity. Genetic and epigenetic influences on autoimmune diseases, such as SLE, RA, T1D and PBC, will also be briefly discussed.

Multiple system atrophy: genetic risks and alpha-synuclein mutations

Multiple system atrophy (MSA) is one of the few neurodegenerative disorders where we have a significant understanding of the clinical and pathological manifestations but where the aetiology remains almost completely unknown. Research to overcome this hurdle is gaining momentum through international research collaboration and a series of genetic and molecular discoveries in the last few years, which have advanced our knowledge of this rare synucleinopathy. In MSA, the discovery of α-synuclein pathology and glial cytoplasmic inclusions remain the most significant findings. Families with certain types of α-synuclein mutations develop diseases that mimic MSA, and the spectrum of clinical and pathological features in these families suggests a spectrum of severity, from late-onset Parkinson's disease to MSA. Nonetheless, controversies persist, such as the role of common α-synuclein variants in MSA and whether this disorder shares a common mechanism of spreading pathology with other protein misfolding neurodegenerative diseases. Here, we review these issues, specifically focusing on α-synuclein mutations.

Exome sequencing identifies targets in the treatment-resistant ophthalmoplegic subphenotype of myasthenia gravis

Treatment-resistant ophthalmoplegia (OP-MG) is not uncommon in individuals with African genetic ancestry and myasthenia gravis (MG). To identify OP-MG susceptibility genes, extended whole exome sequencing was performed using extreme phenotype sampling (11 OP-MG vs 4 control-MG) all with acetylcholine receptor-antibody positive MG. This approach identified 356 variants that were twice as frequent in OP-MG compared to control-MG individuals. After performing probability test estimates and filtering variants according to those 'suggestive' of association with OP-MG (p < 0.05), only three variants remained which were expressed in extraocular muscles. Validation in 25 OP-MG and 50 control-MG cases supported the association of DDX17_delG (p = 0.014) and SPTLC3_insACAC (p = 0.055) with OP-MG, but ST8SIA1_delCCC could not be verified by Sanger sequencing. A parallel approach, using a semantic model informed by current knowledge of MG-pathways, identified an African-specific interleukin-6 receptor (IL6R) variant, IL6R c.*3043 T>C, that was more frequent in OP-MG compared to control-MG cases (p = 0.069) and population controls (p = 0.043). A weighted genetic risk score, derived from the odds ratios of association of these variants with OP-MG, correlated with the OP-MG phenotype as opposed to control MG. This unbiased approach implicates several potentially functional gene variants in the gangliosphingolipid and myogenesis pathways in the development of the OP-MG subphenotype.

Severe axonal neuropathy is a late manifestation of SPG11

Complex hereditary spastic paraplegia (HSP) is a clinically heterogeneous group of disorders usually inherited in an autosomal recessive manner. In the past, complex recessive spastic paraplegias have been frequently associated with SPG11 mutations but also with defects in SPG15, SPG7 and a handful of other rare genes. Pleiotropy exists in HSP genes, exemplified in the recent association of SPG11 mutations with CMT2. In this study, we performed whole exome sequence analysis and identified two siblings with novel compound heterozygous frameshift SPG11 mutations. The mutations segregated with disease were not present in control databases and analysis of skin fibroblast derived mRNA indicated that the SPG11 truncated mRNA species were not degraded significantly by non-sense mediated mRNA decay. These siblings had severe early-onset spastic paraplegia but later in their disease developed severe axonal neuropathy, neuropathic pain and blue/black foot discolouration likely caused by a combination of the severe neuropathy with autonomic dysfunction and peripheral oedema. We also identified a similar late-onset axonal neuropathy in a Cypriot SPG11 family. Although neuropathy is occasionally present in SPG11, in our SPG11 patients reported here it was particularly severe, highlighting the association of axonal neuropathy with SPG11 and the late manifestation of axonal peripheral nerve damage.

Analysis of the prion protein gene in multiple system atrophy

Neurodegenerative diseases are a very diverse group of disorders but they share some common mechanisms such as abnormally misfolded proteins with prion-like propagation and aggregation. Creutzfeldt-Jakob disease (CJD) is the most prevalent prion disease in humans. In the sporadic form of CJD the only known risk factor is the codon 129 polymorphism. Recent reports suggested that α-synuclein in multiple system atrophy (MSA) has similar pathogenic mechanisms as the prion protein. Here we present 1 Italian family with MSA and prion disease. Also, cases of concurrent MSA and prion pathology in the same individual or family suggest the possibility of molecular interaction between prion protein and α-synuclein in the process of protein accumulation and neurodegeneration, warranting further investigations. We assessed the PRNP gene by whole-exome sequencing in 264 pathologically confirmed MSA cases and 462 healthy controls to determine whether the 2 diseases share similar risk factors. We then analyzed codon 129 polymorphism by Sanger sequencing and compared with previously published results in sporadic CJD. Homozygosity at codon 129 was present in 50% of pathologically confirmed MSA cases and in 58% of normal controls (odds ratio, 0.7 (95% confidence interval of 0.5–0.9)) compared with 88.2% in sporadic CJD. Our data show that the homozygous state of position 129 in the PRNP is not a risk factor for MSA. No other variants in the PRNP gene were associated with increased risk for MSA.

Next-generation sequencing in neuromuscular diseases

PURPOSE OF REVIEW

Neuromuscular diseases are clinically and genetically heterogeneous and probably contain the greatest proportion of causative Mendelian defects than any other group of conditions. These disorders affect muscle and/or nerves with neonatal, childhood or adulthood onset, with significant disability and early mortality. Along with heterogeneity, unidentified and often very large genes require complementary and comprehensive methods in routine molecular diagnosis. Inevitably, this leads to increased diagnostic delays and challenges in the interpretation of genetic variants.

RECENT FINDINGS

The application of next-generation sequencing, as a research and diagnostic strategy, has made significant progress into solving many of these problems. The analysis of these data is by no means simple, and the clinical input is essential to interpret results.

SUMMARY

In this review, we describe using examples the recent advances in the genetic diagnosis of neuromuscular disorders, in research and clinical practice and the latest developments that are underway in next-generation sequencing. We also discuss the latest collaborative initiatives such as the Genomics England (Department of Health, UK) genome sequencing project that combine rare disease clinical phenotyping with genomics, with the aim of defining the vast majority of rare disease genes in patients as well as modifying risks and pharmacogenomics factors.

Clinical Trial Simulations Based on Genetic Stratification and the Natural History of a Functional Outcome Measure in Creutzfeldt-Jakob Disease

IMPORTANCE

A major challenge for drug development in neurodegenerative diseases is that adequately powered efficacy studies with meaningful end points typically require several hundred participants and long durations. Prion diseases represent the archetype of brain diseases caused by protein misfolding, the most common subtype being sporadic Creutzfeldt-Jakob disease (sCJD), a rapidly progressive dementia. There is no well-established trial method in prion disease.

OBJECTIVE

To establish a more powerful and meaningful clinical trial method in sCJD.

DESIGN, SETTING, AND PARTICIPANTS

A stratified medicine and simulation approach based on a prospective interval-cohort study conducted from October 2008 to June 2014. This study involved 598 participants with probable or definite sCJD followed up over 470 patient-years at a specialist national referral service in the United Kingdom with domiciliary, care home, and hospital patient visits. We fitted linear mixed models to the outcome measurements, and simulated clinical trials involving 10 to 120 patients (no dropouts) with early to moderately advanced prion disease using model parameters to compare the power of various designs.

MAIN OUTCOMES AND MEASURES

A total of 2681 assessments were done using a functionally orientated composite end point (Medical Research Council Scale) and associated with clinical investigations (brain magnetic resonance imaging, electroencephalography, and cerebrospinal fluid analysis) and molecular data (prion protein [PrP] gene sequencing, PrPSc type).

RESULTS

Of the 598 participants, 273 were men. The PrP gene sequence was significantly associated with decline relative to any other demographic or investigation factors. Patients with sCJD and polymorphic codon 129 genotypes MM, VV, and MV lost 10% of their function in 5.3 (95% CI, 4.2-6.9), 13.2 (95% CI, 10.9-16.6), and 27.8 (95% CI, 21.9-37.8) days, respectively (P < .001). Simulations indicate that an adequately powered (80%; 2-sided α = .05) open-label randomized trial using 50% reduction in Medical Research Council Scale decline as the primary outcome could be conducted with only 120 participants assessed every 10 days and only 90 participants assessed daily, providing considerably more power than using survival as the primary outcome. Restricting to VV or MV codon 129 genotypes increased power even further. Alternatively, single-arm intervention studies (half the total sample size) could provide similar power in comparison to the natural history cohort.

CONCLUSIONS AND RELEVANCE

Functional end points in neurodegeneration need not require long and very large clinical studies to be adequately powered for efficacy. Patients with sCJD may be an efficient and cost-effective group for testing disease-modifying therapeutics. Stratified medicine and natural history cohort approaches may transform the feasibility of clinical trials in orphan diseases.

Genome-wide assessment of Parkinson's disease in a Southern Spanish population

Here, we set out to study the genetic architecture of Parkinson's disease (PD) through a Genome-Wide Association Study in a Southern Spanish population. About 240 PD cases and 192 controls were genotyped on the NeuroX array. We estimated genetic variation associated with PD risk and age at onset (AAO). Risk profile analyses for PD and AAO were performed using a weighted genetic risk score. Total heritability was estimated by genome-wide complex trait analysis. Rare variants were screened with single-variant and burden tests. We also screened for variation in known PD genes. Finally, we explored runs of homozygosity and structural genomic variations. We replicate PD association (uncorrected p-value < 0.05) at the following loci: ACMSD/TMEM163, MAPT, STK39, MIR4697, and SREBF/RAI1. Subjects in the highest genetic risk score quintile showed significantly increased risk of PD versus the lowest quintile (odds ratio = 3.6, p-value < 4e(-7)), but no significant difference in AAO. We found evidence of runs of homozygosity in 2 PD-associated regions: one intersecting the HLA-DQB1 gene in 6 patients and 1 control; and another intersecting the GBA-SYT11 gene in PD case. The GBA N370S and the LRRK2 G2019S variants were found in 8 and 7 cases, respectively, replicating previous work. A structural variant was found in 1 case in the PARK2 gene locus. This current work represents a comprehensive assessment at a genome-wide level characterizing a novel population in PD genetics.

What we have learned from the next-generation sequencing: Contributions to the genetic diagnoses and understanding of pathomechanisms of neurodegenerative diseases

Since its first availability in 2009, the next-generation sequencing (NGS) has been proved to be a powerful tool in identifying disease-associated variants in many neurological diseases, such as spinocerebellar ataxias, Charcot-Marie-Tooth disease, hereditary spastic paraplegia, and amyotrophic lateral sclerosis. Whole exome sequencing and whole genome sequencing are efficient for identifying variants in novel or unexpected genes responsible for inherited diseases, whereas targeted sequencing is useful in detecting variants in previously known disease-associated genes. The trove of genetic data yielded by NGS has made a significant impact on the clinical diagnoses while contributing hugely on the discovery of molecular pathomechanisms underlying these diseases. Nonetheless, elucidation of the pathogenic roles of the variants identified by NGS is challenging. Establishment of consensus guidelines and development of public genomic/phenotypic databases are thus vital to facilitate data sharing and validation.

Genetic causes of amyotrophic lateral sclerosis: new genetic analysis methodologies entailing new opportunities and challenges

The genetic architecture of amyotrophic lateral sclerosis (ALS) is being increasingly understood. In this far-reaching review, we examine what is currently known about ALS genetics and how these genes were initially identified. We also discuss the various types of mutations that might underlie this fatal neurodegenerative condition and outline some of the strategies that might be useful in untangling them. These include expansions of short repeat sequences, common and low-frequency genetic variations, de novo mutations, epigenetic changes, somatic mutations, epistasis, oligogenic and polygenic hypotheses. This article is part of a Special Issue entitled ALS complex pathogenesis.

Next-generation sequencing of nine atrial fibrillation candidate genes identified novel de novo mutations in patients with extreme trait of atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Genome-wide association studies (GWAS) have identified common variants in nine genomic regions associated with AF (KCNN3, PRRX1, PITX2, WNT8A, CAV1, C9orf3, SYNE2, HCN4 and ZFHX3 genes); however, the genetic variability of these risk variants does not explain the entire genetic susceptibility to AF. Rare variants missed by GWAS may also contribute to genetic risk of AF.

METHODS

We used an extreme trait design to sequence carefully selected probands with extreme phenotypes and their unaffected parents to identify rare de novo variants or mutations. Based on the hypothesis that common and rare variants may colocate in the same disease susceptibility gene, we used next-generation sequencing to sequence these nine published AF susceptibility genes identified by GWAS (a total of 179 exons) in 20 trios, 200 unrelated patients with AF and 200 non-AF controls.

RESULTS

We identified a novel mutation in the 5' untranslated region of the PITX2 gene, which localised in the transcriptionally active enhancer region. We also identified one missense exon mutation in KCNN3, two in ZFHX3 and one in SYNE2. None of these mutations were present in other unrelated patients with AF, healthy controls, unaffected parents and are thus novel and de novo (p<10(-4)). Functional study showed that the mutation in the 5' untranslated region of the PITX2 gene significantly downregulated PITX2 expression in atrial myocytes, either in basal condition or during rapid pacing. In silico analysis showed that the missense mutation in ZFHX3 results in damage of the ZFHX3 protein structure.

CONCLUSIONS

The genetic architecture of subjects with extreme phenotypes of AF is similar to that of rare or Mendelian diseases, and mutations may be the underlying cause.

Human knockout research: new horizons and opportunities

Although numerous approaches have been pursued to understand the function of human genes, Mendelian genetics has by far provided the most compelling and medically actionable dataset. Biallelic loss-of-function (LOF) mutations are observed in the majority of autosomal recessive Mendelian disorders, representing natural human knockouts and offering a unique opportunity to study the physiological and developmental context of these genes. The restriction of such context to 'disease' states is artificial, however, and the recent ability to survey entire human genomes for biallelic LOF mutations has revealed a surprising landscape of knockout events in 'healthy' individuals, sparking interest in their role in phenotypic diversity beyond disease causation. As I discuss in this review, the potentially wide implications of human knockout research warrant increased investment and multidisciplinary collaborations to overcome existing challenges and reap its benefits.

Alzheimer's disease genetics: from the bench to the clinic

Alzheimer's disease (AD) is a clinically heterogeneous neurodegenerative disease with a strong genetic component. Several genes have been associated with AD risk for nearly 20 years. However, it was not until the recent technological advances that allow for the analysis of millions of polymorphisms in thousands of subjects that we have been able to advance our understanding of the genetic complexity of AD susceptibility. Genome-wide association studies and whole-exome and whole-genome sequencing have revealed more than 20 loci associated with AD risk. These studies have provided insights into the molecular pathways that are altered in AD pathogenesis, which have, in turn, provided insight into novel therapeutic targets.

Next generation sequencing techniques in neurological diseases: redefining clinical and molecular associations

The development of next-generation sequencing technologies has allowed for the identification of several new genes and genetic factors in human genetics. Common results from the application of these technologies have revealed unexpected presentations for mutations in known disease genes. In this review, we summarize the major contributions of exome sequencing to the study of neurodegenerative disorders and other neurological conditions and discuss the interface between Mendelian and complex neurological diseases with a particular focus on pleiotropic events.

The contribution of genetic and environmental factors to the duration of pregnancy

This review describes how improvements in biometric-genetic studies of twin kinships, half-sibships, and cousinships have now demonstrated a sizeable fetal genetic and maternal genetic contribution to the spontaneous onset of labor. This is an important development because previous literature for the most part reports only an influence of the maternal genome. Current estimates of the percent of variation that is attributable to fetal genetic factors range from 11-35%; the range for the maternal genetic contribution is 13-20%. These same studies demonstrate an even larger influence of environmental sources over and above the influence of genetic sources and previously identified environmental risk factors. With these estimates in hand, a major goal for research on pregnancy duration is to identify specific allelic variation and environmental risk to account for this estimated genetic and environmental variation. A review of the current literature can serve as a guide for future research efforts.

Epigenetics of multiple sclerosis: an updated review

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized with autoimmune response against myelin proteins and progressive axonal loss. The heterogeneity of the clinical course and low concordance rates in monozygotic twins have indicated the involvement of complex heritable and environmental factors in MS pathogenesis. MS is more often transmitted to the next generation by mothers than fathers suggesting an epigenetic influence. One of the possible reasons of this parent-of-origin effect might be the human leukocyte antigen-DRB1*15 allele, which is the major risk factor for MS and regulated by epigenetic mechanisms such as DNA methylation and histone deacetylation. Moreover, major environmental risk factors for MS, vitamin D deficiency, smoking and Ebstein-Barr virus are all known to exert epigenetic changes. In the last few decades, compelling evidence implicating the role of epigenetics in MS has accumulated. Increased or decreased acetylation, methylation and citrullination of genes regulating the expression of inflammation and myelination factors appear to be particularly involved in the epigenetics of MS. Although much less is known about epigenetic factors causing neurodegeneration, epigenetic mechanisms regulating axonal loss, apoptosis and mitochondrial dysfunction in MS are in the process of identification. Additionally, expression levels of several microRNAs (miRNAs) (e.g., miR-155 and miR-326) are increased in MS brains and potential mechanisms by which these factors might influence MS pathogenesis have been described. Certain miRNAs may also be potentially used as diagnostic biomarkers in MS. Several reagents, especially histone deacetylase inhibitors have been shown to ameliorate the symptoms of experimental allergic encephalomyelitis. Ongoing efforts in this field are expected to result in characterization of epigenetic factors that can be used in prediction of treatment responsive MS patients, diagnostic screening panels and treatment methods with specific mechanism of action.

Functional interpretation of non-coding sequence variation: concepts and challenges

Understanding the functional mechanisms underlying genetic signals associated with complex traits and common diseases, such as cancer, diabetes and Alzheimer's disease, is a formidable challenge. Many genetic signals discovered through genome-wide association studies map to non-protein coding sequences, where their molecular consequences are difficult to evaluate. This article summarizes concepts for the systematic interpretation of non-coding genetic signals using genome annotation data sets in different cellular systems. We outline strategies for the global analysis of multiple association intervals and the in-depth molecular investigation of individual intervals. We highlight experimental techniques to validate candidate (potential causal) regulatory variants, with a focus on novel genome-editing techniques including CRISPR/Cas9. These approaches are also applicable to low-frequency and rare variants, which have become increasingly important in genomic studies of complex traits and diseases. There is a pressing need to translate genetic signals into biological mechanisms, leading to prognostic, diagnostic and therapeutic advances.

Genotype to phenotype via network analysis

A prime objective of genomic medicine is the identification of disease-causing mutations and the mechanisms by which such events result in disease. As most disease phenotypes arise not from single genes and proteins but from a complex network of molecular interactions, a priori knowledge about the molecular network serves as a framework for biological inference and data mining. Here we review recent developments at the interface of biological networks and mutation analysis. We examine how mutations may be treated as a perturbation of the molecular interaction network and what insights may be gained from taking this perspective. We review work that aims to transform static networks into rich context-dependent networks and recent attempts to integrate non-coding RNAs into such analysis. Finally, we conclude with an overview of the many challenges and opportunities that lie ahead.

Next-Generation Sequencing in the Genetics of Human Atrial Fibrillation

The International Human Genome Sequencing Consortium published the first draft of the human genome in the journal Nature in February 2001, providing the sequence of the entire genome's three billion base pairs. The Human Genome Project involves a concerted effort to better understand the human DNA sequence through identification of all the genes. The knowledge that can be derived from the genome could result in the development of novel diagnostic assays, targeted therapies and the improved ability to predict the onset, severity and progression of diseases. This has been made possible by many parallelized, high-throughput technologies such as next-generation sequencing. In this review, we discuss the possible application of next-generation sequencing in finding the susceptibility gene(s) or disease mechanism of an important human arrhythmia called atrial fibrillation.

KEY WORDS

Arrhythmia; Atrial fibrillation; Genetics, Next-generation sequencing.

The epilepsy phenome/genome project

BACKGROUND

Epilepsy is a common neurological disorder that affects approximately 50 million people worldwide. Both risk of epilepsy and response to treatment partly depend on genetic factors, and gene identification is a promising approach to target new prediction, treatment, and prevention strategies. However, despite significant progress in the identification of genes causing epilepsy in families with a Mendelian inheritance pattern, there is relatively little known about the genetic factors responsible for common forms of epilepsy and so-called epileptic encephalopathies. Study design The Epilepsy Phenome/Genome Project (EPGP) is a multi-institutional, retrospective phenotype-genotype study designed to gather and analyze detailed phenotypic information and DNA samples on 5250 participants, including probands with specific forms of epilepsy and, in a subset, parents of probands who do not have epilepsy.

RESULTS

EPGP is being executed in four phases: study initiation, pilot, study expansion/establishment, and close-out. This article discusses a number of key challenges and solutions encountered during the first three phases of the project, including those related to (1) study initiation and management, (2) recruitment and phenotyping, and (3) data validation. The study has now enrolled 4223 participants.

CONCLUSIONS

EPGP has demonstrated the value of organizing a large network into cores with specific roles, managed by a strong Administrative Core that utilizes frequent communication and a collaborative model with tools such as study timelines and performance-payment models. The study also highlights the critical importance of an effective informatics system, highly structured recruitment methods, and expert data review.

TREM2 variants in Alzheimer's disease

BACKGROUND

Homozygous loss-of-function mutations in TREM2, encoding the triggering receptor expressed on myeloid cells 2 protein, have previously been associated with an autosomal recessive form of early-onset dementia.

METHODS

We used genome, exome, and Sanger sequencing to analyze the genetic variability in TREM2 in a series of 1092 patients with Alzheimer's disease and 1107 controls (the discovery set). We then performed a meta-analysis on imputed data for the TREM2 variant rs75932628 (predicted to cause a R47H substitution) from three genomewide association studies of Alzheimer's disease and tested for the association of the variant with disease. We genotyped the R47H variant in an additional 1887 cases and 4061 controls. We then assayed the expression of TREM2 across different regions of the human brain and identified genes that are differentially expressed in a mouse model of Alzheimer's disease and in control mice.

RESULTS

We found significantly more variants in exon 2 of TREM2 in patients with Alzheimer's disease than in controls in the discovery set (P=0.02). There were 22 variant alleles in 1092 patients with Alzheimer's disease and 5 variant alleles in 1107 controls (P<0.001). The most commonly associated variant, rs75932628 (encoding R47H), showed highly significant association with Alzheimer's disease (P<0.001). Meta-analysis of rs75932628 genotypes imputed from genomewide association studies confirmed this association (P=0.002), as did direct genotyping of an additional series of 1887 patients with Alzheimer's disease and 4061 controls (P<0.001). Trem2 expression differed between control mice and a mouse model of Alzheimer's disease.

CONCLUSIONS

Heterozygous rare variants in TREM2 are associated with a significant increase in the risk of Alzheimer's disease. (Funded by Alzheimer's Research UK and others.).

Understanding the Dynamics of Gene Regulatory Systems; Characterisation and Clinical Relevance of cis-Regulatory Polymorphisms

Modern genetic analysis has shown that most polymorphisms associated with human disease are non-coding. Much of the functional information contained in the non-coding genome consists of cis-regulatory sequences (CRSs) that are required to respond to signal transduction cues that direct cell specific gene expression. It has been hypothesised that many diseases may be due to polymorphisms within CRSs that alter their responses to signal transduction cues. However, identification of CRSs, and the effects of allelic variation on their ability to respond to signal transduction cues, is still at an early stage. In the current review we describe the use of comparative genomics and experimental techniques that allow for the identification of CRSs building on recent advances by the ENCODE consortium. In addition we describe techniques that allow for the analysis of the effects of allelic variation and epigenetic modification on CRS responses to signal transduction cues. Using specific examples we show that the interactions driving these elements are highly complex and the effects of disease associated polymorphisms often subtle. It is clear that gaining an understanding of the functions of CRSs, and how they are affected by SNPs and epigenetic modification, is essential to understanding the genetic basis of human disease and stratification whilst providing novel directions for the development of personalised medicine.

Exploring the effects of polymorphisms on cis-regulatory signal transduction response

cis-Regulatory sequences (CRSs) direct cell-specific and inducible gene expression in response to signal transduction networks, and it is becoming apparent that many cases of disease susceptibility and drug response stratification are due to polymorphisms that alter CRS responses in a context-dependent manner. In the current review, we describe successful methods for identifying CRSs and analyzing the effects of allelic variation on their responses to signal transduction. The technologies described build on the successes of ENCODE (ENCyclopedia Of DNA Elements) by exploring the effects of polymorphisms on CRS context dependency. This understanding is essential to uncover the genomic basis of disease susceptibility and will play a major role in delivering on the promise of personalized medicine.

Use of support vector machines for disease risk prediction in genome-wide association studies: concerns and opportunities

The success of genome-wide association studies (GWAS) in deciphering the genetic architecture of complex diseases has fueled the expectations whether the individual risk can also be quantified based on the genetic architecture. So far, disease risk prediction based on top-validated single-nucleotide polymorphisms (SNPs) showed little predictive value. Here, we applied a support vector machine (SVM) to Parkinson disease (PD) and type 1 diabetes (T1D), to show that apart from magnitude of effect size of risk variants, heritability of the disease also plays an important role in disease risk prediction. Furthermore, we performed a simulation study to show the role of uncommon (frequency 1-5%) as well as rare variants (frequency <1%) in disease etiology of complex diseases. Using a cross-validation model, we were able to achieve predictions with an area under the receiver operating characteristic curve (AUC) of ~0.88 for T1D, highlighting the strong heritable component (∼90%). This is in contrast to PD, where we were unable to achieve a satisfactory prediction (AUC ~0.56; heritability ~38%). Our simulations showed that simultaneous inclusion of uncommon and rare variants in GWAS would eventually lead to feasible disease risk prediction for complex diseases such as PD. The used software is available at http://www.ra.cs.uni-tuebingen.de/software/MACLEAPS/.

Insights from genome-wide association studies of drug response

Early genome-wide association studies (GWAS) using relatively small samples have identified both rare and common genetic variants with large impact on severe adverse drug reactions, dosing, and efficacy. Here we outline the challenges and recent successes of the GWAS approach in disease genetics and the ways in which these can be applied to pharmacogenomics for biological discovery, determination of heritability, and personalized treatment. We highlight that the genetic architecture of drug efficacy reflects a complex trait yet that of adverse drug reactions more closely mirrors the architecture of Mendelian diseases and how this difference affects future study design. Given that multiple layers of biological data are increasingly available on large samples from biorepositories linked to electronic medical records, GWAS will remain a key component of the systems biology approach to uncovering small to moderate genetic determinants of drug response; these discoveries should move us closer to a personalized approach to health care.

Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered.

Cancer heterogeneity: origins and implications for genetic association studies

Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders difficult the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goals of identifying targetable disease pathways and successfully treating individual patients.

Genic and nongenic contributions to natural variation of quantitative traits in maize

The complex genomes of many economically important crops present tremendous challenges to understand the genetic control of many quantitative traits with great importance in crop production, adaptation, and evolution. Advances in genomic technology need to be integrated with strategic genetic design and novel perspectives to break new ground. Complementary to individual-gene–targeted research, which remains challenging, a global assessment of the genomic distribution of trait-associated SNPs (TASs) discovered from genome scans of quantitative traits can provide insights into the genetic architecture and contribute to the design of future studies. Here we report the first systematic tabulation of the relative contribution of different genomic regions to quantitative trait variation in maize. We found that TASs were enriched in the nongenic regions, particularly within a 5-kb window upstream of genes, which highlights the importance of polymorphisms regulating gene expression in shaping the natural variation. Consistent with these findings, TASs collectively explained 44%–59% of the total phenotypic variation across maize quantitative traits, and on average, 79% of the explained variation could be attributed to TASs located in genes or within 5 kb upstream of genes, which together comprise only 13% of the genome. Our findings suggest that efficient, cost-effective genome-wide association studies (GWAS) in species with complex genomes can focus on genic and promoter regions.

From genome-wide association studies to disease mechanisms: celiac disease as a model for autoimmune diseases

Celiac disease is characterized by a chronic inflammatory reaction in the intestine and is triggered by gluten, a constituent derived from grains which is present in the common daily diet in the Western world. Despite decades of research, the mechanisms behind celiac disease etiology are still not fully understood, although it is clear that both genetic and environmental factors are involved. To improve the understanding of the disease, the genetic component has been extensively studied by genome-wide association studies. These have uncovered a wealth of information that still needs further investigation to clarify its importance. In this review, we summarize and discuss the results of the genetic studies in celiac disease, focusing on the "non-HLA" genes. We also present novel approaches to identifying the causal variants in complex susceptibility loci and disease mechanisms.

From genome-wide association studies to disease mechanisms: celiac disease as a model for autoimmune diseases

Celiac disease is characterized by a chronic inflammatory reaction in the intestine and is triggered by gluten, a constituent derived from grains which is present in the common daily diet in the Western world. Despite decades of research, the mechanisms behind celiac disease etiology are still not fully understood, although it is clear that both genetic and environmental factors are involved. To improve the understanding of the disease, the genetic component has been extensively studied by genome-wide association studies. These have uncovered a wealth of information that still needs further investigation to clarify its importance. In this review, we summarize and discuss the results of the genetic studies in celiac disease, focusing on the “non-HLA” genes. We also present novel approaches to identifying the causal variants in complex susceptibility loci and disease mechanisms.

Detecting low frequent loss-of-function alleles in genome wide association studies with red hair color as example

Multiple loss-of-function (LOF) alleles at the same gene may influence a phenotype not only in the homozygote state when alleles are considered individually, but also in the compound heterozygote (CH) state. Such LOF alleles typically have low frequencies and moderate to large effects. Detecting such variants is of interest to the genetics community, and relevant statistical methods for detecting and quantifying their effects are sorely needed. We present a collapsed double heterozygosity (CDH) test to detect the presence of multiple LOF alleles at a gene. When causal SNPs are available, which may be the case in next generation genome sequencing studies, this CDH test has overwhelmingly higher power than single SNP analysis. When causal SNPs are not directly available such as in current GWA settings, we show the CDH test has higher power than standard single SNP analysis if tagging SNPs are in linkage disequilibrium with the underlying causal SNPs to at least a moderate degree (r²>0.1). The test is implemented for genome-wide analysis in the publically available software package GenABEL which is based on a sliding window approach. We provide the proof of principle by conducting a genome-wide CDH analysis of red hair color, a trait known to be influenced by multiple loss-of-function alleles, in a total of 7,732 Dutch individuals with hair color ascertained. The association signals at the MC1R gene locus from CDH were uniformly more significant than traditional GWA analyses (the most significant P for CDH = 3.11×10⁻¹⁴² vs. P for rs258322 = 1.33×10⁻⁶⁶). The CDH test will contribute towards finding rare LOF variants in GWAS and sequencing studies.

Genetic linkage analysis of a large family with photoparoxysmal response

In this study, we report the results of a genetic linkage analysis of a large family with photoparoxysmal response, defined by the presence of a photoparoxysmal response (PPR) on EEG. The participants were genotyped using an 8 cM whole genome wide scan, and both parametric and non-parametric linkage analysis were carried out. The parametric analysis by MLINK did not identify any definite conclusion but a region of interest on chromosome 1 near marker D1S2865; and non-parametric linkage analysis found a locus of interest on chromosome 16, near marker D16S2621. The possible confounding factors for, and pathogenic implication of, and the results are discussed.

Sequencing technologies and genome sequencing

The high-throughput - next generation sequencing (HT-NGS) technologies are currently the hottest topic in the field of human and animals genomics researches, which can produce over 100 times more data compared to the most sophisticated capillary sequencers based on the Sanger method. With the ongoing developments of high throughput sequencing machines and advancement of modern bioinformatics tools at unprecedented pace, the target goal of sequencing individual genomes of living organism at a cost of $1,000 each is seemed to be realistically feasible in the near future. In the relatively short time frame since 2005, the HT-NGS technologies are revolutionizing the human and animal genome researches by analysis of chromatin immunoprecipitation coupled to DNA microarray (ChIP-chip) or sequencing (ChIP-seq), RNA sequencing (RNA-seq), whole genome genotyping, genome wide structural variation, de novo assembling and re-assembling of genome, mutation detection and carrier screening, detection of inherited disorders and complex human diseases, DNA library preparation, paired ends and genomic captures, sequencing of mitochondrial genome and personal genomics. In this review, we addressed the important features of HT-NGS like, first generation DNA sequencers, birth of HT-NGS, second generation HT-NGS platforms, third generation HT-NGS platforms: including single molecule Heliscope™, SMRT™ and RNAP sequencers, Nanopore, Archon Genomics X PRIZE foundation, comparison of second and third HT-NGS platforms, applications, advances and future perspectives of sequencing technologies on human and animal genome research.

Differential activity by polymorphic variants of a remote enhancer that supports galanin expression in the hypothalamus and amygdala: implications for obesity, depression and alcoholism

The expression of the galanin gene (GAL) in the paraventricular nucleus (PVN) and in the amygdala of higher vertebrates suggests the requirement for highly conserved, but unidentified, regulatory sequences that are critical to allow the galanin gene to control alcohol and fat intake and modulate mood. We used comparative genomics to identify a highly conserved sequence that lay 42 kb 5' of the human GAL transcriptional start site that we called GAL5.1. GAL5.1 activated promoter activity in neurones of the PVN, arcuate nucleus and amygdala that also expressed the galanin peptide. Analysis in neuroblastoma cells demonstrated that GAL5.1 acted as an enhancer of promoter activity after PKC activation. GAL5.1 contained two polymorphisms; rs2513280(C/G) and rs2513281(A/G), that occurred in two allelic combinations (GG or CA) where the dominant GG alelle occurred in 70-83 % of the human population. Intriguingly, both SNPs were found to be in LD (R(2) of 0.687) with another SNP (rs2156464) previously associated with major depressive disorder (MDD). Recreation of these alleles in reporter constructs and subsequent magnetofection into primary rat hypothalamic neurones showed that the CA allele was 40 % less active than the GG allele. This is consistent with the hypothesis that the weaker allele may affect food and alcohol preference. The linkage of the SNPs analysed in this study with a SNP previously associated with MDD together with the functioning of GAL5.1 as a PVN and amygdala specific enhancer represent a significant advance in our ability to understand alcoholism, obesity and major depressive disorder.

Milestones in PD genetics

Over the last 25 years, genetic findings have profoundly changed our views on the etiology of Parkinson's disease. Linkage studies and positional cloning strategies have identified mutations in a number of genes that cause several monogenic autosomal-dominant or autosomal-recessive forms of the disorder. Although most of these Mendelian forms of Parkinson's disease are rare, whole-genome association studies have more recently provided convincing evidence that low-penetrance variants in at least some of these, but also in several other genes, play a direct role in the etiology of the common sporadic disease as well. In addition, rare variants with intermediate-effect strengths in genes such as Gaucher's disease-associated glucocerebrosidase A have been discovered as important risk factors. "Next-generation" sequencing technologies are expected by some to identify many more of these variants. Thus, an increasingly complex network of genes contributing in different ways to disease risk and progression is emerging. These findings may provide the "genetic entry points" to identify molecular targets and readouts necessary to design rational disease-modifying treatments.