High-resolution mapping of DNA copy alterations in human chromosome 22 using high-density tiling oligonucleotide arrays

Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints

We developed a generally applicable method, CRISPR/Cas9-targeted long-read sequencing (CTLR-Seq), to resolve, haplotype-specifically, the large and complex regions in the human genome that had been previously impenetrable to sequencing analysis, such as large segmental duplications (SegDups) and their associated genome rearrangements. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to isolate intact large (i.e., up to 2,000 kb) genomic regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) at high on-target coverage using long-read sequencing, allowing for their complete sequence assembly. We applied CTLR-Seq to the SegDup-mediated rearrangements that constitute the boundaries of, and give rise to, the 22q11.2 Deletion Syndrome (22q11DS), the most common human microdeletion disorder. We then performed de novo assembly to resolve, at base-pair resolution, the full sequence rearrangements and exact chromosomal breakpoints of 22q11.2DS (including all common subtypes). Across multiple patients, we found a high degree of variability for both the rearranged SegDup sequences and the exact chromosomal breakpoint locations, which coincide with various transposons within the 22q11.2 SegDups, suggesting that 22q11DS can be driven by transposon-mediated genome recombination. Guided by CTLR-Seq results from two 22q11DS patients, we performed three-dimensional chromosomal folding analysis for the 22q11.2 SegDups from patient-derived neurons and astrocytes and found chromosome interactions anchored within the SegDups to be both cell type-specific and patient-specific. Lastly, we demonstrated that CTLR-Seq enables cell-type specific analysis of DNA methylation patterns within the deletion haplotype of 22q11DS.

Screening of 22q11.2DS Using Multiplex Ligation-Dependent Probe Amplification as an Alternative Diagnostic Method

Background

The 22q11.2 deletion syndrome (22q11.2DS) is the most common form of deletion disorder in humans. Low copy repeats flanking the 22q11.2 region confers a substrate for nonallelic homologous recombination (NAHR) events leading to rearrangements which have been reported to be associated with highly variable and expansive phenotypes. The 22q11.2DS is reported as the most common genetic cause of congenital heart defects (CHDs).

Methods

A total of 42 patients with congenital heart defects, as confirmed by echocardiography, were recruited. Genetic molecular analysis using a fluorescence in situ hybridization (FISH) technique was conducted as part of routine 22q11.2DS screening, followed by multiplex ligation-dependent probe amplification (MLPA), which serves as a confirmatory test.

Results

Two of the 42 CHD cases (4.76%) indicated the presence of 22q11.2DS, and interestingly, both cases have conotruncal heart defects. In terms of concordance of techniques used, MLPA is superior since it can detect deletions within the 22q11.2 locus and outside of the typically deleted region (TDR) as well as duplications.

Conclusion

The incidence of 22q11.2DS among patients with CHD in the east coast of Malaysia is 0.047. MLPA is a scalable and affordable alternative molecular diagnostic method in the screening of 22q11.2DS and can be routinely applied for the diagnosis of deletion syndromes.

Emerging roles of non-coding RNAs in vector-borne infections

Non-coding RNAs (ncRNAs) are nucleotide sequences that are known to assume regulatory roles previously thought to be reserved for proteins. Their functions include the regulation of protein activity and localization and the organization of subcellular structures. Sequencing studies have now identified thousands of ncRNAs encoded within the prokaryotic and eukaryotic genomes, leading to advances in several fields including parasitology. ncRNAs play major roles in several aspects of vector-host-pathogen interactions. Arthropod vector ncRNAs are secreted through extracellular vesicles into vertebrate hosts to counteract host defense systems and ensure arthropod survival. Conversely, hosts can use specific ncRNAs as one of several strategies to overcome arthropod vector invasion. In addition, pathogens transmitted through vector saliva into vertebrate hosts also possess ncRNAs thought to contribute to their pathogenicity. Recent studies have addressed ncRNAs in vectors or vertebrate hosts, with relatively few studies investigating the role of ncRNAs derived from pathogens and their involvement in establishing infections, especially in the context of vector-borne diseases. This Review summarizes recent data focusing on pathogen-derived ncRNAs and their role in modulating the cellular responses that favor pathogen survival in the vertebrate host and the arthropod vector, as well as host ncRNAs that interact with vector-borne pathogens.

Downregulation of genes outside the deleted region in individuals with 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11.2DS) is caused by recurrent hemizygous deletions of chromosome 22q11.2. The phenotype of the syndrome is complex and varies widely among individuals. Little is known about the role of the different genes located in 22q11.2, and we hypothesized that genetic risk factors lying elsewhere in the genome might contribute to the phenotype. Here, we present the whole-genome gene expression data of 11 patients with approximately 3 Mb deletions. Apart from the hemizygous genes mapped to the 22q11.2 region, the TUBA8 and GNAZ genes, neighboring the deleted interval but in normal copy number, showed altered expression. When genes mapped to other chromosomes were considered in the gene expression analysis, a genome-wide dysregulation was observed, with increased or decreased expression levels. The enriched pathways of these genes were related to immune response, a deficiency that is frequently observed in 22q11.2DS patients. We also used the hypothesis-free weighted gene co-expression network analysis (WGCNA), which revealed the co-expression gene network modules with clear connection to mechanisms associated with 22q11.2DS such as immune response and schizophrenia. These findings, combined with the traditional gene expression profile, can be used for the identification of potential pathways and genes not previously considered to be related to the 22q11.2 deletion syndrome.

Local and global chromatin interactions are altered by large genomic deletions associated with human brain development

Large copy number variants (CNVs) in the human genome are strongly associated with common neurodevelopmental, neuropsychiatric disorders such as schizophrenia and autism. Here we report on the epigenomic effects of the prominent large deletion CNVs on chromosome 22q11.2 and on chromosome 1q21.1. We use Hi-C analysis of long-range chromosome interactions, including haplotype-specific Hi-C analysis, ChIP-Seq analysis of regulatory histone marks, and RNA-Seq analysis of gene expression patterns. We observe changes on all the levels of analysis, within the deletion boundaries, in the deletion flanking regions, along chromosome 22q, and genome wide. We detect gene expression changes as well as pronounced and multilayered effects on chromatin states, chromosome folding and on the topological domains of the chromatin, that emanate from the large CNV locus. These findings suggest basic principles of how such large genomic deletions can alter nuclear organization and affect genomic molecular activity.

Copy number variants in the human genome (CNVs) are associated with neurodevelopmental and psychiatric disorders such as schizophrenia and autism. Here the authors investigate how  the large deletion CNV on chromosome 22q11.2 alters chromatin organization.

History and evolution of cytogenetic techniques: Current and future applications in basic and clinical research

Chromosomes are the vehicles of genes, which are the functional units of a cell's nucleus. In humans, there are more than 20,000 genes that are distributed among 46 chromosomes in somatic cells. The study of chromosome structure and function is known as cytogenetics which is historically a field of hybrid science encompassing cytology and genetics. The field of cytogenetics has undergone rapid developments over the last several decades from classical Giemsa staining of chromosomes to 3-dimensional spatial organization of chromosomes with a high resolution mapping of gene structure at the nucleotide level. Improved molecular cytogenetic techniques have opened up exciting possibilities for understanding the chromosomal/molecular basis of various human diseases including cancer and tissue degeneration. This review summaries the history and evolution of various cytogenetic techniques and their current and future applications in diverse areas of basic research and medical diagnostics.

Differential DNA methylation at birth associated with mental disorder in individuals with 22q11.2 deletion syndrome

Individuals with 22q11.2 deletion syndrome (DS) have an increased risk of comorbid mental disorders including schizophrenia, attention deficit hyperactivity disorder, depression, as well as intellectual disability. Although most 22q11.2 deletion carriers have the long 3-Mb form of the hemizygous deletion, there remains a large variation in the development and progression of psychiatric disorders, which suggests that alternative factors contribute to the pathogenesis. In this study we investigated whether neonatal DNA methylation signatures in individuals with the 22q11.2 deletion associate with mental disorder later in life. DNA methylation was measured genome-wide from neonatal dried blood spots in a cohort of 164 individuals with 22q11.2DS, including 48 individuals diagnosed with a psychiatric disorder. Among several CpG sites with P-value<10-6, we identified cg23546855 (P-value=2.15 × 10-7) mapping to STK32C to be associated with a later psychiatric diagnosis. Pathway analysis of the top findings resulted in the identification of several Gene Ontology pathways to be significantly enriched (P-value<0.05 after Benjamini-Hochberg correction); among them are the following: neurogenesis, neuron development, neuron projection development, astrocyte development, axonogenesis and axon guidance. In addition, we identified differentially methylated CpG sites in LRP2BP (P-value=5.37 × 10-8) to be associated with intellectual disability (F70-79), in TOP1 (P-value=1.86 × 10-7) with behavioral disorders (F90-98), in NOSIP (P-value=5.12 × 10-8) with disorders of psychological development (F80-89) and in SEMA4B (P-value=4.02 × 10-7) with schizophrenia spectrum disorders (F20-29). In conclusion, our study suggests an association of DNA methylation differences at birth with development of mental disorder later in life in 22q11.2DS individuals.

A Linear-Time Algorithm for the Copy Number Transformation Problem

Problems of genome rearrangement are central in both evolution and cancer. Most evolutionary scenarios have been studied under the assumption that the genome contains a single copy of each gene. In contrast, tumor genomes undergo deletions and duplications, and thus, the number of copies of genes varies. The number of copies of each segment along a chromosome is called its copy number profile (CNP). Understanding CNP changes can assist in predicting disease progression and treatment. To date, questions related to distances between CNPs gained little scientific attention. Here we focus on the following fundamental problem, introduced by Schwarz et al.: given two CNPs, u and v, compute the minimum number of operations transforming u into v, where the edit operations are segmental deletions and amplifications. We establish the computational complexity of this problem, showing that it is solvable in linear time and constant space.

Deletion Extents Are Not the Cause of Clinical Variability in 22q11.2 Deletion Syndrome: Does the Interaction between DGCR8 and miRNA-CNVs Play a Major Role?

In humans, the most common genomic disorder is the hemizygous deletion of the chromosome 22q11.2 region, that results in the “22q11.2 deletion syndrome” (22q11.2DS). A peculiarity of 22q11.2DS is its great phenotypic variability that makes this pathology a classic example of a syndrome with variable expressivity and incomplete penetrance. The reasons for this variability have not been elucidated yet, and the molecular substrates underlying the different clinical features of 22q11.2DS are still debated. A cohort of 21 patients has been analyzed by array CGH in order to detect some of the genetic differences that may influence this variability. Two aspects have been investigated: (1) the precise localization of the deletion breakpoints within the low copy repeats (LCRs), (2) the additional Copy Number Variations (CNVs) elsewhere in the genome, by analyzing their gene content. Both protein-coding genes and miRNAs were considered, in order to discover possible epistatic interactions between genes of the 22q11.2 region and the rest of the genome. Eighteen out of twenty-one patients had a deletion of ~3 Mb mediated by LCR22-A and D, whereas 3/21 had a smaller deletion. The breakpoints within the LCR22-A and D do not have a major role in the phenotypic variability since they are rather clustered and the small differences concern genes that are not directly related to clinical signs of 22q11.2DS. A detailed analysis of the gene content of 22q11.2 deleted region indicates that this syndrome could be a bioenergetic disorder or consequence of an altered post-transcriptional gene regulation, due to the presence of DGCR8, a major player of the microRNA (miRNA) biogenesis. Only four genes with mitochondrial function are harbored in the additional CNVs, whereas 11 miRNA, all related to biological pathways present in the 22q11.2DS, have been detected in 19/21 patients. CNVs and miRNAs are new entities that have changed the order of complexity at the level of gene expression and regulation, thus CNV-miRNAs (miRNA harbored in the CNVs) are potential functional variants that should be considered high priority candidate variants in genotype-phenotype association studies. Deletion of DGCR8, the main actor in miRNA biogenesis, amplifies this variability. To our knowledge, this is the first report that focus on the miRNA-CNVs in 22q11.2DS, with the aim of trying to better understand their role in the variable expressivity and incomplete penetrance.

Schizophrenia Spectrum Disorders in a Danish 22q11.2 Deletion Syndrome Cohort Compared to the Total Danish Population--A Nationwide Register Study

OBJECTIVE

Cross-sectional studies have shown associations between 22q11.2 deletion syndrome and schizophrenia. However, large-scale prospective studies have been lacking. We, therefore, conducted the first large-scale population based study on the risk of being diagnosed with schizophrenia in persons identified with 22q11.2 deletion syndrome.

METHODS

Danish nationwide registers were linked to establish a cohort consisting of all Danish citizens born during 1955-2004 and the cohort was followed from January 1, 1994 until December 31, 2013. Data were analyzed using survival analyses and adjusted for calendar year, age, sex, and parental mental health history.

RESULTS

A total of 156 individuals with 22q11.2 deletion syndrome were identified, out of which 6 individuals were diagnosed with schizophrenia spectrum disorders following identification with 22q11 deletion syndrome. Identified carriers of 22q11.2 deletion had an 8.13(95% CI: 3.65-18.09) fold increased risk of schizophrenia spectrum disorder.

CONCLUSIONS

Carriers of a 22q11.2 deletion who had been clinically identified had a highly increased risk of schizophrenia spectrum disorders.

The Danish 22q11 research initiative

BACKGROUND

Neurodevelopmental brain disorders such as schizophrenia, autism and attention deficit hyperactivity disorder are complex disorders with heterogeneous etiologies. Schizophrenia and autism are difficult to treat and often cause major individual suffering largely owing to our limited understanding of the disease biology. Thus our understanding of the biological pathogenesis needs to be substantiated to enable development of more targeted treatment options with improved efficacy. Insights into the pre-morbid disease dynamics, the morbid condition and the underlying biological disease mechanisms may come from studies of subjects with homogenous etiologies. Breakthroughs in psychiatric genetics have shown that several genetic anomalies predispose for neurodevelopmental brain disorders. We have established a Danish research initiative to study the common microdeletion at chromosome 22q11.2, which is one of the genetic anomalies that confer high risk of schizophrenia, autism and attention deficit hyperactivity disorder.

METHODS/DESIGN

The study applies a "cause-to-outcome" strategy to identify pre-morbid pathogenesis and underlying biological disease mechanisms of psychosis and secondarily the morbid condition of autism and attention deficit hyperactivity disorder. We use a population based epidemiological design to inform on disease prevalence, environmental risk factors and familial disposition for mental health disorders and a case control study design to map the functional effects across behavioral and neurophysiological traits of the 22q11 deletion in a recruited sample of Danish individuals.

DISCUSSION

Identification of predictive pre-morbid clinical, cognitive, functional and structural brain alterations in 22q11 deletion carriers may alter current clinical practice from symptomatic therapy of manifest mental illness into early intervention strategies, which may also be applicable to at risk subjects without known etiology. Hopefully new insights into the biological disease mechanisms, which are mandatory for novel drug developments, can improve the outcome of the pharmacological interventions in psychiatry.

Applying Genomics and Proteomics in Translational Surgical Oncology Research

BACKGROUND

Translational surgical research can range from investigating clinically oriented basic pathophysiological research via the correlation of molecular findings with a patient's clinical outcome to conducting treatment response studies. Herein, the specialist's opinion as a 'surgeon scientist' plays a pivotal role, e.g. in planning experimental setups focusing on the clinically most relevant needs. SUMMARY AND KEY MESSAGES: This review provides a survey of genomic and proteomic technologies and gives an up-to-date overview of those studies applying these technologies exemplarily in colorectal cancer-based biomarker research. Although current results are promising, future validation studies within multicenter networks are required to promote the translation of 'omics' from bench to bedside. In this endeavor, departments of surgery and institutes of experimental surgery together should play a fundamental role. The program for 'clinician scientists' recently launched by the German Research Society (DFG) could be one tool to promote interdisciplinary networks and surgeons' impact on translational research.

Transcriptome Profiling of Peripheral Blood in 22q11.2 Deletion Syndrome Reveals Functional Pathways Related to Psychosis and Autism Spectrum Disorder

Background

22q11.2 Deletion Syndrome (22q11DS) represents one of the greatest known genetic risk factors for the development of psychotic illness, and is also associated with high rates of autistic spectrum disorders (ASD) in childhood. We performed integrated genomic analyses of 22q11DS to identify genes and pathways related to specific phenotypes.

Methods

We used a high-resolution aCGH array to precisely characterize deletion breakpoints. Using peripheral blood, we examined differential expression (DE) and networks of co-expressed genes related to phenotypic variation within 22q11DS patients. Whole-genome transcriptional profiling was performed using Illumina Human HT-12 microarrays. Data mining techniques were used to validate our results against independent samples of both peripheral blood and brain tissue from idiopathic psychosis and ASD cases.

Results

Eighty-five percent of 22q11DS individuals (N = 39) carried the typical 3 Mb deletion, with significant variability in deletion characteristics in the remainder of the sample (N = 7). DE analysis and weighted gene co-expression network analysis (WGCNA) identified expression changes related to psychotic symptoms in patients, including a module of co-expressed genes which was associated with psychosis in 22q11DS and involved in pathways associated with transcriptional regulation. This module was enriched for brain-expressed genes, was not related to antipsychotic medication use, and significantly overlapped with transcriptional changes in idiopathic schizophrenia. In 22q11DS-ASD, both DE and WGCNA analyses implicated dysregulation of immune response pathways. The ASD-associated module showed significant overlap with genes previously associated with idiopathic ASD.

Conclusion

These findings further support the use of peripheral tissue in the study of major mutational models of diseases affecting the brain, and point towards specific pathways dysregulated in 22q11DS carriers with psychosis and ASD.

Tetralogy of Fallot and Hypoplastic Left Heart Syndrome - Complex Clinical Phenotypes Meet Complex Genetic Networks

In many cases congenital heart disease (CHD) is represented by a complex phenotype and an array of several functional and morphological cardiac disorders. These malformations will be briefly summarized in the first part focusing on two severe CHD phenotypes, hypoplastic left heart syndrome (HLHS) and tetralogy of Fallot (TOF). In most cases of CHD the genetic origin remains largely unknown, though the complexity of the clinical picture strongly argues against a dysregulation which can be attributed to a single candidate gene but rather suggests a multifaceted polygenetic origin with elaborate interactions. Consistent with this idea, genome-wide approaches using whole exome sequencing, comparative sequence analysis of multiplex families to identify de novo mutations and global technologies to identify single nucleotide polymorphisms, copy number variants, dysregulation of the transcriptome and epigenetic variations have been conducted to obtain information about genetic alterations and potential predispositions possibly linked to the occurrence of a CHD phenotype. In the second part of this review we will summarize and discuss the available literature on identified genetic alterations linked to TOF and HLHS.

[22q11.2DS Syndrome as a Genetic Subtype of Schizophrenia]

INTRODUCTION

The 22q11.2 deletion syndrome (22q11.2DS) is associated with the microdeletion of this chromosomal region, and represents the second most common genetic syndrome after Down's syndrome. In patients with schizophrenia, 22q11.2DS has a prevalence of 2%, and in selected groups can be increased to between 32-53%.

OBJECTIVE

To describe the generalities of 22q11.2DS syndrome as a genetic subtype of schizophrenia, its clinical characteristics, molecular genetic aspects, and frequency in different populations.

METHODS

A review was performed from 1967 to 2013 in scientific databases, compiling articles about 22q11.2DS syndrome and its association with schizophrenia.

RESULTS

The 22q11.2 DS syndrome has a variable phenotype associated with other genetic syndromes, birth defects in many tissues and organs, and a high rate of psychiatric disorders, particularly schizophrenia. Likewise, it has been identified in clinical populations with schizophrenia selected by the presence of common syndromic characteristics. FISH, qPCR and MLPA techniques, and recently, aCGH and NGS technologies, are being used to diagnose this microdeletion.

CONCLUSIONS

It is important in clinical practice to remember that people suffering the 22q11.2DS have a high genetic risk for developing schizophrenia, and it is considered that the simultaneous presence of this disease and 22q11.2DS represents a genetic subtype of schizophrenia. There are clear phenotypic criteria, molecular and cytogenetic methods to diagnose this group of patients, and to optimize a multidisciplinary approach in their monitoring.

The 22q11.2 deletion syndrome as a window into complex neuropsychiatric disorders over the lifespan

Evidence is rapidly accumulating that rare, recurrent copy number variants represent large effect risk factors for neuropsychiatric disorders. 22q11.2 deletion syndrome (22q11DS) (velocardiofacial syndrome or DiGeorge syndrome) is the most common known contiguous gene deletion syndrome and is associated with diverse neuropsychiatric disorders across the life span. One of the most intriguing aspects of the syndrome is the variability in clinical and cognitive presentation: children with 22q11DS have high prevalence of autism spectrum, attention deficit, and anxiety disorders, as well as psychotic-like features, and up to 30% of adolescents and adults develop schizophrenia-like psychosis. Recently, cases of early-onset Parkinson's disease in adults have been reported, collectively suggesting a role for disrupted dopaminergic neurotransmission in the observed neuropsychiatric phenotypes. There is also some evidence that 22q11DS-associated autism spectrum disorder and schizophrenia represent two unrelated phenotypic manifestations, consistent with a neuropsychiatric pleiotropy model. This genetic lesion thus provides a unique model for the discovery of specific genomic risk and (potentially) protective factors for neuropsychiatric disease. Here, we provide an overview of neuropsychiatric findings to date, which highlight the value of this syndrome in mapping the developmental trajectory of dimensional phenotypes that traverse multiple diagnostic categories. Potential sources of genetic variability that may contribute to the disorder's heterogeneous presentation are reviewed. Because of its known genetic etiology, animal models can readily be developed that recapitulate specific aspects of the syndrome. Future research directions involve translational models and potential for drug screenable targets in the context of this human model system.

Common copy number variation detection from multiple sequenced samples

Common copy number variations (CNVs) are small regions of genomic variations at the same loci across multiple samples, which can be detected with high resolution from next-generation sequencing (NGS) technique. Multiple sequencing data samples are often available from genomic studies; examples include sequences from multiple platforms and sequences from multiple individuals. By integrating complementary information from multiple data samples, detection power can be potentially improved. However, most of current CNV detection methods often process an individual sequence sample, or two samples in an abnormal versus matched normal study; researches on detecting common CNVs across multiple samples have been very limited but are much needed. In this paper, we propose a novel method to detect common CNVs from multiple sequencing samples by exploiting the concurrency of genomic variations in read depth signals derived from multiple NGS data. We use a penalized sparse regression model to fit multiple read depth profiles, based on which common CNV identification is formulated as a change-point detection problem. Finally, we validate the proposed method on both simulation and real data, showing that it can give both higher detection power and better break point estimation over several published CNV detection methods.

Parametric modeling of whole-genome sequencing data for CNV identification

Copy number variants (CNVs) constitute an important class of genetic variants in human genome and are shown to be associated with complex diseases. Whole-genome sequencing provides an unbiased way of identifying all the CNVs that an individual carries. In this paper, we consider parametric modeling of the read depth (RD) data from whole-genome sequencing with the aim of identifying the CNVs, including both Poisson and negative-binomial modeling of such count data. We propose a unified approach of using a mean-matching variance stabilizing transformation to turn the relatively complicated problem of sparse segment identification for count data into a sparse segment identification problem for a sequence of Gaussian data. We apply the optimal sparse segment identification procedure to the transformed data in order to identify the CNV segments. This provides a computationally efficient approach for RD-based CNV identification. Simulation results show that this approach often results in a small number of false identifications of the CNVs and has similar or better performances in identifying the true CNVs when compared with other RD-based approaches. We demonstrate the methods using the trio data from the 1000 Genomes Project.

Phenotypic impact of genomic structural variation: insights from and for human disease

Genomic structural variants have long been implicated in phenotypic diversity and human disease, but dissecting the mechanisms by which they exert their functional impact has proven elusive. Recently however, developments in high-throughput DNA sequencing and chromosomal engineering technology have facilitated the analysis of structural variants in human populations and model systems in unprecedented detail. In this Review, we describe how structural variants can affect molecular and cellular processes, leading to complex organismal phenotypes, including human disease. We further present advances in delineating disease-causing elements that are affected by structural variants, and we discuss future directions for research on the functional consequences of structural variants.

Child development and structural variation in the human genome

Structural variation of the human genome sequence is the insertion, deletion, or rearrangement of stretches of DNA sequence sized from around 1,000 to millions of base pairs. Over the past few years, structural variation has been shown to be far more common in human genomes than previously thought. Very little is currently known about the effects of structural variation on normal child development, but such effects could be of considerable significance. This review provides an overview of the phenomenon of structural variation in the human genome sequence, describing the novel genomics technologies that are revolutionizing the way structural variation is studied and giving examples of genomic structural variations that affect child development.

Genotype-phenotype correlation in 22q11.2 deletion syndrome

BACKGROUND

The 22q11.2 deletion syndrome (22q11.2DS) is caused by hemizygous microdeletions on chromosome 22q11.2 with highly variable physical and neuropsychiatric manifestations. We explored the genotype-phenotype relationship in a relatively large 22q11.2DS cohort treated and monitored in our clinic using comprehensive clinical evaluation and detailed molecular characterization of the deletion.

METHODS

Molecular analyses in 142 subjects with 22q11.2DS features were performed by FISH and MLPA methods. Participants underwent clinical assessment of physical symptoms and structured psychiatric and cognitive evaluation.

RESULTS

Deletions were found in 110 individuals including one with an atypical nested distal deletion which was missed by the FISH test. Most subjects (88.2%) carried the 3Mb typically deleted region and 11.8% carried 4 types of deletions differing in size and location. No statistically significant genotype-phenotype correlations were found between deletion type and clinical data although some differences in hypocalcemia and cardiovascular anomalies were noted.Analysis of the patient with the distal nested deletion suggested a redundancy of genes causing the physical and neuropsychiatric phenotype in 22q11.2DS and indicating that the psychiatric and cognitive trajectories may be governed by different genes.

CONCLUSIONS

MLPA is a useful and affordable molecular method combining accurate diagnosis and detailed deletion characterization. Variations in deletion type and clinical manifestations impede the detection of significant differences in samples of moderate size, but analysis of individuals with unique deletions may provide insight into the underlying biological mechanisms.Future genotype-phenotype studies should involve large multicenter collaborations employing uniform clinical standards and high-resolution molecular methods.

Robust Detection and Identification of Sparse Segments in Ultra-High Dimensional Data Analysis

Copy number variants (CNVs) are alternations of DNA of a genome that results in the cell having a less or more than two copies of segments of the DNA. CNVs correspond to relatively large regions of the genome, ranging from about one kilobase to several megabases, that are deleted or duplicated. Motivated by CNV analysis based on next generation sequencing data, we consider the problem of detecting and identifying sparse short segments hidden in a long linear sequence of data with an unspecified noise distribution. We propose a computationally efficient method that provides a robust and near-optimal solution for segment identification over a wide range of noise distributions. We theoretically quantify the conditions for detecting the segment signals and show that the method near-optimally estimates the signal segments whenever it is possible to detect their existence. Simulation studies are carried out to demonstrate the efficiency of the method under different noise distributions. We present results from a CNV analysis of a HapMap Yoruban sample to further illustrate the theory and the methods.

Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV

MOTIVATION

The ability to detect copy-number variation (CNV) and loss of heterozygosity (LOH) from exome sequencing data extends the utility of this powerful approach that has mainly been used for point or small insertion/deletion detection.

RESULTS

We present ExomeCNV, a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies, from mapped short sequence reads, and we assess both the method's power and the effects of confounding variables. We apply our method to a cancer exome resequencing dataset. As expected, accuracy and resolution are dependent on depth-of-coverage and capture probe design.

AVAILABILITY

CRAN package 'ExomeCNV'.

CONTACT

fsathira@fas.harvard.edu; snelson@ucla.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of genomic indels and structural variations using split reads

Background

Recent studies have demonstrated the genetic significance of insertions, deletions, and other more complex structural variants (SVs) in the human population. With the development of the next-generation sequencing technologies, high-throughput surveys of SVs on the whole-genome level have become possible. Here we present split-read identification, calibrated (SRiC), a sequence-based method for SV detection.

Results

We start by mapping each read to the reference genome in standard fashion using gapped alignment. Then to identify SVs, we score each of the many initial mappings with an assessment strategy designed to take into account both sequencing and alignment errors (e.g. scoring more highly events gapped in the center of a read). All current SV calling methods have multilevel biases in their identifications due to both experimental and computational limitations (e.g. calling more deletions than insertions). A key aspect of our approach is that we calibrate all our calls against synthetic data sets generated from simulations of high-throughput sequencing (with realistic error models). This allows us to calculate sensitivity and the positive predictive value under different parameter-value scenarios and for different classes of events (e.g. long deletions vs. short insertions). We run our calculations on representative data from the 1000 Genomes Project. Coupling the observed numbers of events on chromosome 1 with the calibrations gleaned from the simulations (for different length events) allows us to construct a relatively unbiased estimate for the total number of SVs in the human genome across a wide range of length scales. We estimate in particular that an individual genome contains ~670,000 indels/SVs.

Conclusions

Compared with the existing read-depth and read-pair approaches for SV identification, our method can pinpoint the exact breakpoints of SV events, reveal the actual sequence content of insertions, and cover the whole size spectrum for deletions. Moreover, with the advent of the third-generation sequencing technologies that produce longer reads, we expect our method to be even more useful.

Molecular Diagnostics of Soft Tissue Tumors

Context.—Soft tissue pathology encompasses a remarkably diverse assortment of benign and malignant soft tissue tumors. Rendering a definitive diagnosis is complicated not only by the large volume of existing histologic subtypes (&gt;100) but also frequently by the presence of overlapping clinical, histologic, immunohistochemical, and/or radiographic features. During the past 3 decades, mesenchymal tumor–specific, cytogenetic and molecular genetic abnormalities have demonstrated an increasingly important, ancillary role in mesenchymal tumor diagnostics.

Objectives.—To review molecular diagnostic tools available to the pathologist to further classify specific soft tissue tumor types and recurrent aberrations frequently examined. Advantages and limitations of individual approaches will also be highlighted.

Data Sources.—Previously published review articles, peer-reviewed research publications, and the extensive cytogenetic and molecular diagnostic experience of the authors to include case files of The University of Nebraska Medical Center.

Conclusions.—Cytogenetic and molecular genetic assays are used routinely for diagnostic purposes in soft tissue pathology and represent a powerful adjunct to complement conventional microscopy and clinicoradiographic evaluation in the formulation of an accurate diagnosis. Care should be taken, however, to recognize the limitations of these approaches. Ideally, more than one technical approach should be available to a diagnostic laboratory to compensate for the shortcomings of each approach in the assessment of individual specimens.

The 22q11.2 microdeletion: fifteen years of insights into the genetic and neural complexity of psychiatric disorders

Over the last fifteen years it has become established that 22q11.2 deletion syndrome (22q11DS) is a true genetic risk factor for schizophrenia. Carriers of deletions in chromosome 22q11.2 develop schizophrenia at rate of 25-30% and such deletions account for as many as 1-2% of cases of sporadic schizophrenia in the general population. Access to a relatively homogeneous population of individuals that suffer from schizophrenia as the result of a shared etiological factor and the potential to generate etiologically valid mouse models provides an immense opportunity to better understand the pathobiology of this disease. In this review we survey the clinical literature associated with the 22q11.2 microdeletions with a focus on neuroanatomical changes. Then, we highlight results from work modeling this structural mutation in animals. The key biological pathways disrupted by the mutation are discussed and how these changes impact the structure and function of neural circuits is described.

Identification of genes and genomic islands correlated with high pathogenicity in Streptococcus suis using whole genome tiling microarrays

Streptococcus suis is an important zoonotic pathogen that can cause meningitis and sepsis in both pigs and humans. Infections in humans have been sporadic worldwide but two severe outbreaks occurred in China in recent years, while infections in pigs are a major problem in the swine industry. Some S. suis strains are more pathogenic than others with 2 sequence types (ST), ST1 and ST7, being well recognized as highly pathogenic. We analyzed 31 isolates from 23 serotypes and 25 STs by NimbleGen tiling microarray using the genome of a high pathogenicity (HP) ST1 strain, GZ1, as reference and a new algorithm to detect gene content difference. The number of genes absent in a strain ranged from 49 to 225 with a total of 632 genes absent in at least one strain, while 1346 genes were found to be invariably present in all strains as the core genome of S. suis, accounting for 68% of the GZ1 genome. The majority of genes are located in chromosomal blocks with two or more contiguous genes. Sixty two blocks are absent in two or more strains and defined as regions of difference (RDs), among which 26 are putative genomic islands (GIs). Clustering and statistical analyses revealed that 8 RDs including 6 putative GIs and 21 genes within these RDs are significantly associated with HP. Three RDs encode known virulence related factors including the extracellular factor, the capsular polysaccharide and a SrtF pilus. The strains were divided into 5 groups based on population genetic analysis of multilocus sequence typing data and the distribution of the RDs among the groups revealed gain and loss of RDs in different groups. Our study elucidated the gene content diversity of S. suis and identified genes that potentially promote HP.

Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity

Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95–99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ∼15% and ∼20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.

Human individual genome sequencing has recently become affordable, enabling highly detailed genetic sequence comparisons. While the identification and genotyping of single-nucleotide polymorphisms has already been successfully established for different sequencing platforms, the detection, quantification and genotyping of large-scale copy-number variants (CNVs), i.e., losses or gains of long genomic segments, has remained challenging. We present a computational approach that enables detecting CNVs in sequencing data and accurately identifies the actual copy-number at which DNA segments of interest occur in an individual genome. This approach enabled us to obtain novel insights into the largest human gene family – the olfactory receptors (ORs) – involved in smell perception. While previous studies reported an abundance of CNVs in ORs, our approach enabled us to globally identify absolute differences in OR gene counts that exist between humans. While several OR genes have very high gene counts, other ORs are found only once or are missing entirely in some individuals. The latter have a particularly high probability of influencing individual differences in the perception of smell, a question that future experimental efforts can now address. Furthermore, we observed differences in OR gene counts between populations, pointing at ORs that might contribute to population-specific differences in smell.

Detection of copy number variation from array intensity and sequencing read depth using a stepwise Bayesian model

Background

Copy number variants (CNVs) have been demonstrated to occur at a high frequency and are now widely believed to make a significant contribution to the phenotypic variation in human populations. Array-based comparative genomic hybridization (array-CGH) and newly developed read-depth approach through ultrahigh throughput genomic sequencing both provide rapid, robust, and comprehensive methods to identify CNVs on a whole-genome scale.

Results

We developed a Bayesian statistical analysis algorithm for the detection of CNVs from both types of genomic data. The algorithm can analyze such data obtained from PCR-based bacterial artificial chromosome arrays, high-density oligonucleotide arrays, and more recently developed high-throughput DNA sequencing. Treating parameters--e.g., the number of CNVs, the position of each CNV, and the data noise level--that define the underlying data generating process as random variables, our approach derives the posterior distribution of the genomic CNV structure given the observed data. Sampling from the posterior distribution using a Markov chain Monte Carlo method, we get not only best estimates for these unknown parameters but also Bayesian credible intervals for the estimates. We illustrate the characteristics of our algorithm by applying it to both synthetic and experimental data sets in comparison to other segmentation algorithms.

Conclusions

In particular, the synthetic data comparison shows that our method is more sensitive than other approaches at low false positive rates. Furthermore, given its Bayesian origin, our method can also be seen as a technique to refine CNVs identified by fast point-estimate methods and also as a framework to integrate array-CGH and sequencing data with other CNV-related biological knowledge, all through informative priors.

Sperm rates of 7q11.23, 15q11q13 and 22q11.2 deletions and duplications: a FISH approach

Genomic disorders are human diseases caused by meiotic chromosomal rearrangements of unstable regions flanked by Low Copy Repeats (LCRs). LCRs act as substrates for Non-Allelic Homologous Recombination (NAHR) leading to deletions and duplications. The aim of this study was to assess the basal frequency of deletions and duplications of the 7q11.23, 15q11-q13 and 22q11.2 regions in spermatozoa from control donors to check differences in the susceptibility to generate anomalies and to assess the contribution of intra- and inter-chromatid NAHR events. Semen samples from ten control donors were processed by FISH. A customized combination of probes was used to discriminate among normal, deleted and duplicated sperm genotypes. A minimum of 10,000 sperm were assessed per sample and region. There were no differences in the mean frequency of deletions and duplications (del + dup) among the 7q11.23, 15q11-q13 and 22q11.2 regions (frequency ± SEM, 0.37 ± 0.02; 0.46 ± 0.07 and 0.27 ± 0.07%, respectively) (P = 0.122). Nevertheless, hierarchical cluster analysis reveals interindividual differences suggesting that particular haplotypes could be the main source of variability in NAHR rates. The mean frequency of deletions was not different from the mean frequency of duplications in the 7q11.23 (P = 0.202) and 15q11-q13 (P = 0.609) regions, indicating a predominant inter-chromatid NAHR. By contrast, in the 22q11.2 region the frequency of deletions slightly exceed duplications (P = 0.032), although at the individual level any donor showed differences. Altogether, our results support the inter-chromatid NAHR as the predominant mechanism involved in the generation of sperm deletions and duplications.

A robust penalized method for the analysis of noisy DNA copy number data

Background

Deletions and amplifications of the human genomic DNA copy number are the causes of numerous diseases, such as, various forms of cancer. Therefore, the detection of DNA copy number variations (CNV) is important in understanding the genetic basis of many diseases. Various techniques and platforms have been developed for genome-wide analysis of DNA copy number, such as, array-based comparative genomic hybridization (aCGH) and high-resolution mapping with high-density tiling oligonucleotide arrays. Since complicated biological and experimental processes are often associated with these platforms, data can be potentially contaminated by outliers.

Results

We propose a penalized LAD regression model with the adaptive fused lasso penalty for detecting CNV. This method contains robust properties and incorporates both the spatial dependence and sparsity of CNV into the analysis. Our simulation studies and real data analysis indicate that the proposed method can correctly detect the numbers and locations of the true breakpoints while appropriately controlling the false positives.

Conclusions

The proposed method has three advantages for detecting CNV change points: it contains robustness properties; incorporates both spatial dependence and sparsity; and estimates the true values at each marker accurately.

Behavior, brain, and genome in genomic disorders: finding the correspondences

OBJECTIVE

Within the last decade or so, there has been an acceleration of research attempting to connect specific genetic lesions to the patterns of brain structure and activation. This article comments on observations that have been made based on these recent data and discusses their importance for the field of investigations into developmental disorders.

METHODS

In making these observations, the authors focus on one specific genomic lesion, the well-studied, yet still incompletely understood, 22q11.2 deletion syndrome.

RESULTS

The authors demonstrate the degree of variability in the phenotype that occurs at both the brain and behavioral levels of genomic disorders and describe how this variability is, on close inspection, represented at the genomic level.

CONCLUSION

The authors emphasize the importance of combining genetic/genomic analyses and neuroimaging for research and for future clinical diagnostic purposes and for the purposes of developing individualized, patient-tailored treatment and remediation approaches.

22q11.2 microdeletions: linking DNA structural variation to brain dysfunction and schizophrenia

Recent studies are beginning to paint a clear and consistent picture of the impairments in psychological and cognitive competencies that are associated with microdeletions in chromosome 22q11.2. These studies have highlighted a strong link between this genetic lesion and schizophrenia. Parallel studies in humans and animal models are starting to uncover the complex genetic and neural substrates altered by the microdeletion. In addition to offering a deeper understanding of the effects of this genetic lesion, these findings may guide analysis of other copy-number variants associated with cognitive dysfunction and psychiatric disorders.

What have the genomics ever done for the psychoses?

BACKGROUND

Despite the substantial heritability of the psychoses and their genuine public health burden, the applicability of the genomic approach in psychiatry has been strongly questioned or prematurely dismissed.

METHODS

selective review of the recent literature on molecular genetic and genomic approaches to the psychoses including the early output from genome-wide association studies and the genomic analysis of DNA structural variation.

RESULTS

Susceptibility variants at strong candidate genes have been identified including neuregulin, dysbindin, DISC1 and neurexin 1. Rare but highly penetrant copy number variants and new mutations affecting genes involved in neurodevelopment, cell signalling and synaptic function have been described showing some overlapping genetic architecture with other developmental disorders including autism. The de-novo mutations described offer an explanation for the familial sporadic divide and the persistence of schizophrenia in the population. The functional effects of risk variants at the level of cognition and connectivity has been described and recently, ZNF804A has been identified, and the MHC re-identified as risk loci, and it has been shown that at least a third of the variation in liability is due to multiple common risk variants of small effect with a substantial shared genetic liability between schizophrenia and bipolar affective disorder.

CONCLUSIONS

The genomics have done much for the psychoses to date and more is anticipated.

Personal genome sequencing: current approaches and challenges

The revolution in DNA sequencing technologies has now made it feasible to determine the genome sequences of many individuals; i.e., "personal genomes." Genome sequences of cells and tissues from both normal and disease states have been determined. Using current approaches, whole human genome sequences are not typically assembled and determined de novo, but, instead, variations relative to a reference sequence are identified. We discuss the current state of personal genome sequencing, the main steps involved in determining a genome sequence (i.e., identifying single-nucleotide polymorphisms [SNPs] and structural variations [SVs], assembling new sequences, and phasing haplotypes), and the challenges and performance metrics for evaluating the accuracy of the reconstruction. Finally, we consider the possible individual and societal benefits of personal genome sequences.

Quality of Cell Products: Authenticity, Identity, Genomic Stability and Status of Differentiation

Cellular therapies that either use modifications of a patient's own cells or allogeneic cell lines are becoming in vogue. Besides the technical issues of optimal isolation, cultivation and modification, quality control of the generated cellular products are increasingly being considered to be more important. This is not only relevant for the cell's therapeutic application but also for cell science in general. Recent changes in editorial policies of respected journals, which now require proof of authenticity when cell lines are used, demonstrate that the subject of the present paper is not a virtual problem at all. In this article we provide 2 examples of contaminated cell lines followed by a review of the recent developments used to verify cell lines, stem cells and modifications of autologous cells. With relative simple techniques one can now prove the authenticity and the quality of the cellular material of interest and therefore improve the scientific basis for the development of cells for therapeutic applications. The future of advanced cellular therapies will require production and characterization of cells under GMP and GLP conditions, which include proof of identity, safety and functionality and absence of contamination.

Validation of rearrangement break points identified by paired-end sequencing in natural populations of Drosophila melanogaster

Several recent studies have focused on the evolution of recently duplicated genes in Drosophila. Currently, however, little is known about the evolutionary forces acting upon duplications that are segregating in natural populations. We used a high-throughput, paired-end sequencing platform (Illumina) to identify structural variants in a population sample of African D. melanogaster. Polymerase chain reaction and sequencing confirmation of duplications detected by multiple, independent paired-ends showed that paired-end sequencing reliably uncovered the break points of structural rearrangements and allowed us to identify a number of tandem duplications segregating within a natural population. Our confirmation experiments show that rates of confirmation are very high, even at modest coverage. Our results also compare well with previous studies using microarrays (Emerson J, Cardoso-Moreira M, Borevitz JO, Long M. 2008. Natural selection shapes genome wide patterns of copy-number polymorphism in Drosophila melanogaster. Science. 320:1629-1631. and Dopman EB, Hartl DL. 2007. A portrait of copy-number polymorphism in Drosophila melanogaster. Proc Natl Acad Sci U S A. 104:19920-19925.), which both gives us confidence in the results of this study as well as confirms previous microarray results.We were also able to identify whole-gene duplications, such as a novel duplication of Or22a, an olfactory receptor, and identify copy-number differences in genes previously known to be under positive selection, like Cyp6g1, which confers resistance to dichlorodiphenyltrichloroethane. Several "hot spots" of duplications were detected in this study, which indicate that particular regions of the genome may be more prone to generating duplications. Finally, population frequency analysis of confirmed events also showed an excess of rare variants in our population, which indicates that duplications segregating in the population may be deleterious and ultimately destined to be lost from the population.

Genome variation discovery with high-throughput sequencing data

The advent of high-throughput sequencing (HTS) technologies is enabling sequencing of human genomes at a significantly lower cost. The availability of these genomes is hoped to enable novel medical diagnostics and treatment, specific to the individual, thus launching the era of personalized medicine. The data currently generated by HTS machines require extensive computational analysis in order to identify genomic variants present in the sequenced individual. In this paper, we overview HTS technologies and discuss several of the plethora of algorithms and tools designed to analyze HTS data, including algorithms for read mapping, as well as methods for identification of single-nucleotide polymorphisms, insertions/deletions and large-scale structural variants and copy-number variants from these mappings.

The role of DNA copy number variation in schizophrenia

Schizophrenia is a major psychiatric disease with strong evidence of genetic risk factors. Recent studies based on genome-wide study of copy number variations (CNVs) have detected novel recurrent submicroscopic copy number changes, including recurrent deletions at 1q21.11, 15q11.3, 15q13.3, and the recurrent CNV at the 2p16.3 neurexin 1 locus. These schizophrenia susceptibility CNV loci demonstrate that schizophrenia is, at least in part, genetic in origin and provide the basis for further investigation of mutations associated with the disease. The studies combined have also established the role of rare and-in sporadic cases-de novo variants in schizophrenia. Furthermore, neuronal-related genes and genetic pathways are starting to emerge from the CNV loci associated with schizophrenia. Here, we review the major findings in the recent literature, which begin to unravel the genetic and biological architecture of this complex human neuropsychiatric disorder.

Chromosome aberrations involving 10q22: report of three overlapping interstitial deletions and a balanced translocation disrupting C10orf11

Interstitial deletions of chromosome band 10q22 are rare. We report on the characterization of three overlapping de novo 10q22 deletions by high-resolution array comparative genomic hybridization in three unrelated patients. Patient 1 had a 7.9 Mb deletion in 10q21.3-q22.2 and suffered from severe feeding problems, facial dysmorphisms and profound mental retardation. Patients 2 and 3 had nearly identical deletions of 3.2 and 3.6 Mb, the proximal breakpoints of which were located at an identical low-copy repeat. Both patients were mentally retarded; patient 3 also suffered from growth retardation and hypotonia. We also report on the results of breakpoint analysis by array painting in a mentally retarded patient with a balanced chromosome translocation 46,XY,t(10;13)(q22;p13)dn. The breakpoint in 10q22 was found to disrupt C10orf11, a brain-expressed gene in the common deleted interval of patients 1-3. This finding suggests that haploinsufficiency of C10orf11 contributes to the cognitive defects in 10q22 deletion patients.

BreakDancer: an algorithm for high-resolution mapping of genomic structural variation

Detection and characterization of genomic structural variation are important for understanding the landscape of genetic variation in human populations and in complex diseases such as cancer. Recent studies demonstrate the feasibility of detecting structural variation using next-generation, short-insert, paired-end sequencing reads. However, the utility of these reads is not entirely clear, nor are the analysis methods with which accurate detection can be achieved. The algorithm BreakDancer predicts a wide variety of structural variants including insertion-deletions (indels), inversions and translocations. We examined BreakDancer's performance in simulation, in comparison with other methods and in analyses of a sample from an individual with acute myeloid leukemia and of samples from the 1,000 Genomes trio individuals. BreakDancer sensitively and accurately detected indels ranging from 10 base pairs to 1 megabase pair that are difficult to detect via a single conventional approach.

The genetic architecture of Down syndrome phenotypes revealed by high-resolution analysis of human segmental trisomies

Down syndrome (DS), or trisomy 21, is a common disorder associated with several complex clinical phenotypes. Although several hypotheses have been put forward, it is unclear as to whether particular gene loci on chromosome 21 (HSA21) are sufficient to cause DS and its associated features. Here we present a high-resolution genetic map of DS phenotypes based on an analysis of 30 subjects carrying rare segmental trisomies of various regions of HSA21. By using state-of-the-art genomics technologies we mapped segmental trisomies at exon-level resolution and identified discrete regions of 1.8-16.3 Mb likely to be involved in the development of 8 DS phenotypes, 4 of which are congenital malformations, including acute megakaryocytic leukemia, transient myeloproliferative disorder, Hirschsprung disease, duodenal stenosis, imperforate anus, severe mental retardation, DS-Alzheimer Disease, and DS-specific congenital heart disease (DSCHD). Our DS-phenotypic maps located DSCHD to a <2-Mb interval. Furthermore, the map enabled us to present evidence against the necessary involvement of other loci as well as specific hypotheses that have been put forward in relation to the etiology of DS-i.e., the presence of a single DS consensus region and the sufficiency of DSCR1 and DYRK1A, or APP, in causing several severe DS phenotypes. Our study demonstrates the value of combining advanced genomics with cohorts of rare patients for studying DS, a prototype for the role of copy-number variation in complex disease.

Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants

The goal of human genome re-sequencing is obtaining an accurate assembly of an individual's genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen), with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs). SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome.) To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of human genomes at maximum accuracy and low cost.

In recent years, the development of high throughput sequencing and array technologies has enabled the accurate re-sequencing of individual genomes, especially in identifying and reconstructing the variants in an individual's genome compared to a “reference”. The costs and sensitivities of these technologies differ considerably from each other, and even more technologies are expected to appear in the near future. To both reduce the total cost of re-sequencing to an affordable point and be adaptive to these constantly evolving bio-technologies, we propose to build a computationally efficient simulation framework that can help us optimize the combination of different technologies to perform low cost comparative genome re-sequencing, especially in reconstructing large structural variants, which is considered in many respects the most challenging step in genome re-sequencing. Our simulation results quantitatively show how much improvement one can gain in reconstructing large structural variants by integrating different technologies in optimal ways. We envision that in the future, more experimental technologies will be incorporated into this simulation framework and its results can provide informative guidelines for the actual experimental design to achieve optimal genome re-sequencing output at low costs.

TileProbe: modeling tiling array probe effects using publicly available data

Motivation: Individual probes on an Affymetrix tiling array usually behave differently. Modeling and removing these probe effects are critical for detecting signals from the array data. Current data processing techniques either require control samples or use probe sequences to model probe-specific variability, such as with MAT. Although the MAT approach can be applied without control samples, residual probe effects continue to distort the true biological signals.

Results: We propose TileProbe, a new technique that builds upon the MAT algorithm by incorporating publicly available data sets to remove tiling array probe effects. By using a large number of these readily available arrays, TileProbe robustly models the residual probe effects that MAT model cannot explain. When applied to analyzing ChIP-chip data, TileProbe performs consistently better than MAT across a variety of analytical conditions. This shows that TileProbe resolves the issue of probe-specific effects more completely.

Availability:http://www.biostat.jhsph.edu/∼hji/cisgenome/index_files/tileprobe.htm

Contact:hji@jhsph.edu

Supplementary information:Supplementary data are available at Bioinformatics online.