Identification of copy number variants in whole-genome data using Reference Coverage Profiles

Contribution of Spontaneous Mutations to Quantitative and Molecular Variation at the Highly Repetitive rDNA Locus in Yeast

The ribosomal DNA array in Saccharomyces cerevisiae consists of many tandem repeats whose copy number is believed to be functionally important but highly labile. Regulatory mechanisms have evolved to maintain copy number by directed mutation, but how spontaneous variation at this locus is generated and selected has not been well characterized. We applied a mutation accumulation approach to quantify the impacts of mutation and selection on this unique genomic feature across hundreds of mutant strains. We find that mutational variance for this trait is relatively high, and that unselected mutations elsewhere in the genome can disrupt copy number maintenance. In consequence, copy number generally declines gradually, consistent with a previously proposed model of rDNA maintenance where a downward mutational bias is normally compensated by mechanisms that increase copy number when it is low. This pattern holds across ploidy levels and strains in the standard lab environment but differs under some stressful conditions. We identify several alleles, gene categories, and genomic features that likely affect copy number, including aneuploidy for chromosome XII. Copy number change is associated with reduced growth in diploids, consistent with stabilizing selection. Levels of standing variation in copy number are well predicted by a balance between mutation and stabilizing selection, suggesting this trait is not subject to strong diversifying selection in the wild. The rate and spectrum of point mutations within the rDNA locus itself are distinct from the rest of the genome and predictive of polymorphism locations. Our findings help differentiate the roles of mutation and selection and indicate that spontaneous mutation patterns shape several aspects of ribosomal DNA evolution.

Identification, Evaluation, and Management of Children With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with reported prevalence in the United States of 1 in 59 children (approximately 1.7%). Core deficits are identified in 2 domains: social communication/interaction and restrictive, repetitive patterns of behavior. Children and youth with ASD have service needs in behavioral, educational, health, leisure, family support, and other areas. Standardized screening for ASD at 18 and 24 months of age with ongoing developmental surveillance continues to be recommended in primary care (although it may be performed in other settings), because ASD is common, can be diagnosed as young as 18 months of age, and has evidenced-based interventions that may improve function. More accurate and culturally sensitive screening approaches are needed. Primary care providers should be familiar with the diagnostic criteria for ASD, appropriate etiologic evaluation, and co-occurring medical and behavioral conditions (such as disorders of sleep and feeding, gastrointestinal tract symptoms, obesity, seizures, attention-deficit/hyperactivity disorder, anxiety, and wandering) that affect the child's function and quality of life. There is an increasing evidence base to support behavioral and other interventions to address specific skills and symptoms. Shared decision making calls for collaboration with families in evaluation and choice of interventions.  This single clinical report updates the 2007 American Academy of Pediatrics clinical reports on the evaluation and treatment of ASD in one publication with an online table of contents and section view available through the American Academy of Pediatrics Gateway to help the reader identify topic areas within the report.

Major changes of cell function and toxicant sensitivity in cultured cells undergoing mild, quasi-natural genetic drift

Genomic drift affects the functional properties of cell lines, and the reproducibility of data from in vitro studies. While chromosomal aberrations and mutations in single pivotal genes are well explored, little is known about effects of minor, possibly pleiotropic, genome changes. We addressed this question for the human dopaminergic neuronal precursor cell line LUHMES by comparing two subpopulations (SP) maintained either at the American-Type-Culture-Collection (ATCC) or by the original provider (UKN). Drastic differences in susceptibility towards the specific dopaminergic toxicant 1-methyl-4-phenylpyridinium (MPP+) were observed. Whole-genome sequencing was performed to identify underlying genetic differences. While both SP had normal chromosome structures, they displayed about 70 differences on the level of amino acid changing events. Some of these differences were confirmed biochemically, but none offered a direct explanation for the altered toxicant sensitivity pattern. As second approach, markers known to be relevant for the intended use of the cells were specifically tested. The “ATCC” cells rapidly down-regulated the dopamine-transporter and tyrosine-hydroxylase after differentiation, while “UKN” cells maintained functional levels. As the respective genes were not altered themselves, we conclude that polygenic complex upstream changes can have drastic effects on biochemical features and toxicological responses of relatively similar SP of cells.

Holoprosencephaly: A clinical genomics perspective

New and rapidly evolving technologies have dramatically impacted the practice of clinical genetics as well as broader areas of medicine. To illustrate this trend from the perspective of a clinical molecular laboratory, we briefly summarize our general experience conducting exome testing for patients with holoprosencephaly (HPE). Though these cases are not representative of HPE more generally (i.e., cases undergoing exome sequencing represent a skewed sample), results include a 22% positive rate from exome testing. Of interest, 29% of reported results involved genes not considered to be classic HPE genes, indicating more evidence that HPE may fall within the severe spectrum of many other genetic conditions.

Mutation in an alternative transcript of CDKL5 in a boy with early-onset seizures

Infantile-onset epilepsies are a set of severe, heterogeneous disorders for which clinical genetic testing yields causative mutations in ∼20%–50% of affected individuals. We report the case of a boy presenting with intractable seizures at 2 wk of age, for whom gene panel testing was unrevealing. Research-based whole-genome sequencing of the proband and four unaffected family members identified a de novo mutation, NM_001323289.1:c.2828_2829delGA in CDKL5, a gene associated with X-linked early infantile epileptic encephalopathy 2. CDKL5 has multiple alternative transcripts, and the mutation lies in an exon in the brain-expressed forms. The mutation was undetected by gene panel sequencing because of its intronic location in the CDKL5 transcript typically used to define the exons of this gene for clinical exon-based tests (NM_003159). This is the first report of a patient with a mutation in an alternative transcript of CDKL5. This finding suggests that incorporating alternative transcripts into the design and variant interpretation of exon-based tests, including gene panel and exome sequencing, could improve the diagnostic yield.

Global characterization of copy number variants in epilepsy patients from whole genome sequencing

Epilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.

Experience with genomic sequencing in pediatric patients with congenital cardiac defects in a large community hospital

BACKGROUND

Congenital cardiac defects, whether isolated or as part of a larger syndrome, are the most common type of human birth defect occurring on average in about 1% of live births depending on the malformation. As there is an expanding understanding of the underlying molecular mechanisms by which a cardiac defect may occur, there is a need to assess the current rates of diagnosis of cardiac defects by molecular sequencing in a clinical setting.

METHODS AND RESULTS

In this report, we evaluated 34 neonatal and pediatric patients born with a cardiac defect and their parents using exomized preexisting whole genome sequencing (WGS) data to model clinically available exon-based tests. Overall, we identified candidate variants in previously reported cardiac-related genes in 35% (12/34) of the probands. These include clearly pathogenic variants in two of 34 patients (6%) and variants of uncertain significance in relevant genes in 10 patients (26%), of these latter 10, 2 segregated with clinically apparent findings in the family trios.

CONCLUSIONS

These findings suggest that with current knowledge of the proteins underlying CHD, genomic sequencing can identify the underlying genetic etiology in certain patients; however, this technology currently does not have a high enough yield to be of routine clinical use in the screening of pediatric congenital cardiac defects.

Genomic analysis of an infant with intractable diarrhea and dilated cardiomyopathy

We describe a case of an infant presenting with intractable diarrhea who subsequently developed dilated cardiomyopathy, for whom a diagnosis was not initially achieved despite extensive clinical testing, including panel-based genetic testing. Research-based whole-genome sequences of the proband and both parents were analyzed by the SAVANNA pipeline, a variant prioritization strategy integrating features of variants, genes, and phenotypes, which was implemented using publicly available tools. Although the intestinal morphological abnormalities characteristic of congenital tufting enteropathy (CTE) were not observed in the initial clinical gastrointestinal tract biopsies of the proband, an intronic variant, EPCAM c.556-14A>G, previously identified as pathogenic for CTE, was found in the homozygous state. A newborn cousin of the proband also presenting with intractable diarrhea was found to carry the same homozygous EPCAM variant, and clinical testing revealed intestinal tufting and loss of EPCAM staining. This variant, however, was considered nonexplanatory for the proband's dilated cardiomyopathy, which could be a sequela of the child's condition and/or related to other genetic variants, which include de novo mutations in the genes NEDD4L and GSK3A and a maternally inherited SCN5A variant. This study illustrates three ways in which genomic sequencing can aid in the diagnosis of clinically challenging patients: differential diagnosis despite atypical clinical presentation, distinguishing the possibilities of a syndromic condition versus multiple conditions, and generating hypotheses for novel contributory genes.

Leveraging network analytics to infer patient syndrome and identify causal genes in rare disease cases

BACKGROUND

Next-generation sequencing is widely used to identify disease-causing variants in patients with rare genetic disorders. Identifying those variants from whole-genome or exome data can be both scientifically challenging and time consuming. A significant amount of time is spent on variant annotation, and interpretation. Fully or partly automated solutions are therefore needed to streamline and scale this process.

RESULTS

We describe Phenotype Driven Ranking (PDR), an algorithm integrated into Ingenuity Variant Analysis, that uses observed patient phenotypes to prioritize diseases and genes in order to expedite causal-variant discovery. Our method is based on a network of phenotype-disease-gene relationships derived from the QIAGEN Knowledge Base, which allows for efficient computational association of phenotypes to implicated diseases, and also enables scoring and ranking.

CONCLUSIONS

We have demonstrated the utility and performance of PDR by applying it to a number of clinical rare-disease cases, where the true causal gene was known beforehand. It is also shown that PDR compares favorably to a representative alternative tool.

A wellness study of 108 individuals using personal, dense, dynamic data clouds

Personal data for 108 individuals were collected during a 9-month period, including whole genome sequences; clinical tests, metabolomes, proteomes, and microbiomes at three time points; and daily activity tracking. Using all of these data, we generated a correlation network that revealed communities of related analytes associated with physiology and disease. Connectivity within analyte communities enabled the identification of known and candidate biomarkers (e.g., gamma-glutamyltyrosine was densely interconnected with clinical analytes for cardiometabolic disease). We calculated polygenic scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to discover molecular correlates of polygenic risk (e.g., genetic risk for inflammatory bowel disease was negatively correlated with plasma cystine). Finally, behavioral coaching informed by personal data helped participants to improve clinical biomarkers. Our results show that measurement of personal data clouds over time can improve our understanding of health and disease, including early transitions to disease states.

Detection of active transposable elements in Arabidopsis thaliana using Oxford Nanopore Sequencing technology

BACKGROUND

Transposables elements (TEs) contribute to both structural and functional dynamics of most eukaryotic genomes. Because of their propensity to densely populate plant and animal genomes, the precise estimation of the impact of transposition on genomic diversity has been considered as one of the main challenges of today's genomics. The recent development of NGS (next generation sequencing) technologies has open new perspectives in population genomics by providing new methods for high throughput detection of Transposable Elements-associated Structural Variants (TEASV). However, these have relied on Illumina platform that generates short reads (up to 350 nucleotides). This limitation in size of sequence reads can cause high false discovery rate (FDR) and therefore limit the power of detection of TEASVs, especially in the case of large, complex genomes. The newest sequencing technologies, such as Oxford Nanopore Technologies (ONT) can generate kilobases-long reads thus representing a promising tool for TEASV detection in plant and animals.

RESULTS

We present the results of a pilot experiment for TEASV detection on the model plant species Arabidopsis thaliana using ONT sequencing and show that it can be used efficiently to detect TE movements. We generated a ~0.8X genome coverage of a met1-derived epigenetic recombinant inbred line (epiRIL) using a MinIon device with R7 chemistry. We were able to detect nine new copies of the LTR-retrotransposon Evadé (EVD). We also evidenced the activity of the DNA transposon CACTA, CAC1.

CONCLUSIONS

Even at a low sequence coverage (0.8X), ONT sequencing allowed us to reliably detect several TE insertions in Arabidopsis thaliana genome. The long read length allowed a precise and un-ambiguous mapping of the structural variations caused by the activity of TEs. This suggests that the trade-off between read length and genome coverage for TEASV detection may be in favor of the former. Should the technology be further improved both in terms of lower error rate and operation costs, it could be efficiently used in diversity studies at population level.

Utilization of genomic sequencing for population screening of immunodeficiencies in the newborn

PurposeImmunodeficiency screening has been added to many state-directed newborn screening programs. The current methodology is limited to screening for severe T-cell lymphopenia disorders. We evaluated the potential of genomic sequencing to augment current newborn screening for immunodeficiency, including identification of non-T cell disorders.MethodsWe analyzed whole-genome sequencing (WGS) and clinical data from a cohort of 1,349 newborn-parent trios by genotype-first and phenotype-first approaches. For the genotype-first approach, we analyzed predicted protein-impacting variants in 329 immunodeficiency-related genes in the WGS data. As a phenotype-first approach, electronic health records were used to identify children with clinical features suggestive of immunodeficiency. Genomes of these children and their parents were analyzed using a separate pipeline for identification of candidate pathogenic variants for rare Mendelian disorders.ResultsWGS provides adequate coverage for most known immunodeficiency-related genes. 13,476 distinct variants and 8,502 distinct predicted protein-impacting variants were identified in this cohort; five individuals carried potentially pathogenic variants requiring expert clinical correlation. One clinically asymptomatic individual was found genomically to have complement component 9 deficiency. Of the symptomatic children, one was molecularly identified as having an immunodeficiency condition and two were found to have other molecular diagnoses.ConclusionNeonatal genomic sequencing can potentially augment newborn screening for immunodeficiency.

Differences between the genomes of lymphoblastoid cell lines and blood-derived samples

Lymphoblastoid cell lines (LCLs) represent a convenient research tool for expanding the amount of biologic material available from an individual. LCLs are commonly used as reference materials, most notably from the Genome in a Bottle Consortium. However, the question remains how faithfully LCL-derived genome assemblies represent the germline genome of the donor individual as compared to the genome assemblies derived from peripheral blood mononuclear cells. We present an in-depth comparison of a large collection of LCL- and peripheral blood mononuclear cell-derived genomes in terms of distributions of coverage and copy number alterations. We found significant differences in the depth of coverage and copy number calls, which may be driven by differential replication timing. Importantly, these copy number changes preferentially affect regions closer to genes and with higher GC content. This suggests that genomic studies based on LCLs may display locus-specific biases, and that conclusions based on analysis of depth of coverage and copy number variation may require further scrutiny.

Next-Generation Sequencing-Based Approaches for Mutation Mapping and Identification in Caenorhabditis elegans

The use of next-generation sequencing (NGS) has revolutionized the way phenotypic traits are assigned to genes. In this review, we describe NGS-based methods for mapping a mutation and identifying its molecular identity, with an emphasis on applications in Caenorhabditis elegans In addition to an overview of the general principles and concepts, we discuss the main methods, provide practical and conceptual pointers, and guide the reader in the types of bioinformatics analyses that are required. Owing to the speed and the plummeting costs of NGS-based methods, mapping and cloning a mutation of interest has become straightforward, quick, and relatively easy. Removing this bottleneck previously associated with forward genetic screens has significantly advanced the use of genetics to probe fundamental biological processes in an unbiased manner.

Big biomedical data as the key resource for discovery science

Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's.