Development of bioinformatics resources for display and analysis of copy number and other structural variants in the human genome

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

Multiclass Cancer Prediction Based on Copy Number Variation Using Deep Learning

DNA copy number variation (CNV) is the type of DNA variation which is associated with various human diseases. CNV ranges in size from 1 kilobase to several megabases on a chromosome. Most of the computational research for cancer classification is traditional machine learning based, which relies on handcrafted extraction and selection of features. To the best of our knowledge, the deep learning-based research also uses the step of feature extraction and selection. To understand the difference between multiple human cancers, we developed three end-to-end deep learning models, i.e., DNN (fully connected), CNN (convolution neural network), and RNN (recurrent neural network), to classify six cancer types using the CNV data of 24,174 genes. The strength of an end-to-end deep learning model lies in representation learning (automatic feature extraction). The purpose of proposing more than one model is to find which architecture among them performs better for CNV data. Our best model achieved 92% accuracy with an ROC of 0.99, and we compared the performances of our proposed models with state-of-the-art techniques. Our models have outperformed the state-of-the-art techniques in terms of accuracy, precision, and ROC. In the future, we aim to work on other types of cancers as well.

Chromosomal microarray analysis, including constitutional and neoplastic disease applications, 2021 revision: a technical standard of the American College of Medical Genetics and Genomics (ACMG)

Chromosomal microarray technologies, including array comparative genomic hybridization and single-nucleotide polymorphism array, are widely applied in the diagnostic evaluation for both constitutional and neoplastic disorders. In a constitutional setting, this technology is accepted as the first-tier test for the evaluation of chromosomal imbalances associated with intellectual disability, autism, and/or multiple congenital anomalies. Furthermore, chromosomal microarray analysis is recommended for patients undergoing invasive prenatal diagnosis with one or more major fetal structural abnormalities identified by ultrasonographic examination, and in the evaluation of intrauterine fetal demise or stillbirth when further cytogenetic analysis is desired. This technology also provides important genomic data in the diagnosis, prognosis, and therapy of neoplastic disorders, including both hematologic malignancies and solid tumors. To assist clinical laboratories in the validation of chromosomal microarray methodologies for constitutional and neoplastic applications, the American College of Medical Genetics and Genomics (ACMG) Laboratory Quality Assurance Committee has developed these updated technical laboratory standards, which replace the ACMG technical standards and guidelines for microarray analysis in constitutional and neoplastic disorders previously published in 2013.

A snapshot neural ensemble method for cancer-type prediction based on copy number variations

An accurate diagnosis and prognosis for cancer are specific to patients with particular cancer types and molecular traits, which needs to address carefully. The discovery of important biomarkers is becoming an important step toward understanding the molecular mechanisms of carcinogenesis in which genomics data and clinical outcomes need to be analyzed before making any clinical decision. Copy number variations (CNVs) are found to be associated with the risk of individual cancers and hence can be used to reveal genetic predispositions before cancer develops. In this paper, we collect the CNVs data about 8000 cancer patients covering 14 different cancer types from The Cancer Genome Atlas. Then, two different sparse representations of CNVs based on 578 oncogenes and 20,308 protein-coding genes, including genomic deletions and duplication across the samples, are prepared. Then, we train Conv-LSTM and convolutional autoencoder (CAE) networks using both representations and create snapshot models. While the Conv-LSTM can capture locally and globally important features, CAE can utilize unsupervised pretraining to initialize the weights in the subsequent convolutional layers against the sparsity. Model averaging ensemble (MAE) is then applied to combine the snapshot models in order to make a single prediction. Finally, we identify most significant CNVs biomarkers using guided-gradient class activation map plus (GradCAM++) and rank top genes for different cancer types. Results covering several experiments show fairly high prediction accuracies for the majority of cancer types. In particular, using protein-coding genes, Conv-LSTM and CAE networks can predict cancer types correctly at least 72.96% and 76.77% of the cases, respectively. Contrarily, using oncogenes gives moderately higher accuracies of 74.25% and 78.32%, whereas the snapshot model based on MAE shows overall 2.5% of accuracy improvement.

Ximmer: a system for improving accuracy and consistency of CNV calling from exome data

Background

While exome and targeted next-generation DNA sequencing are primarily used for detecting single nucleotide changes and small indels, detection of copy number variants (CNVs) can provide highly valuable additional information from the data. Although there are dozens of exome CNV detection methods available, these are often difficult to use, and accuracy varies unpredictably between and within datasets.

Findings

We present Ximmer, a tool that supports an end-to-end process for evaluating, tuning, and running analysis methods for detection of CNVs in germline samples. Ximmer includes a simulation framework, implementations of several commonly used CNV detection methods, and a visualization and curation tool that together enable interactive exploration and quality control of CNV results. Using Ximmer, we comprehensively evaluate CNV detection on four datasets using five different detection methods. We show that application of Ximmer can improve accuracy and aid in quality control of CNV detection results. In addition, Ximmer can be used to run analyses and explore CNV results in exome data.

Conclusions

Ximmer offers a comprehensive tool and method for applying and improving accuracy of CNV detection methods for exome data.

Learning causal networks with latent variables from multivariate information in genomic data

Learning causal networks from large-scale genomic data remains challenging in absence of time series or controlled perturbation experiments. We report an information- theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many genomic datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. The approach and associated algorithm, miic, outperform earlier methods on a broad range of benchmark networks. Causal network reconstructions are presented at different biological size and time scales, from gene regulation in single cells to whole genome duplication in tumor development as well as long term evolution of vertebrates. Miic is publicly available at https://github.com/miicTeam/MIIC.

The reconstruction of causal networks from genomic data is an important but challenging problem. Predicting key regulatory interactions or genomic alterations at the origin of human diseases can guide experimental investigation and ultimately inspire innovative therapy. However, causal relationships are difficult to establish without the possibility to directly perturb the organisms’ genome for ethical or practical reasons. Besides, unmeasured (latent) variables may be hidden in many genomic datasets and lead to spurious causal relationships between observed variables. We propose in this paper an efficient computational approach, miic, that overcomes these limitations and learns causal networks from non-perturbative (observational) data in the presence of latent variables. In addition, we assess the confidence of each predicted interaction and demonstrate the enhanced robustness and accuracy of miic compared to alternative existing methods. This approach can be applied on a wide range of datasets and provide new biological insights on regulatory networks from single cell expression data or genomic alterations during tumor development. Miic is implemented in an R package freely available to the scientific community under a General Public License.

Association between genome-wide copy number variation and arsenic-induced skin lesions: a prospective study

BACKGROUND

Exposure to arsenic in drinking water is a global health problem and arsenic-induced skin lesions are hallmark of chronic arsenic toxicity. We and others have reported germline genetic variations as risk factors for such skin lesions. The role of copy number variation (CNV) in the germline DNA in this regard is unknown.

METHODS

From a large prospectively followed-up cohort, exposed to arsenic, we randomly selected 2171 subjects without arsenic-induced skin lesions at enrollment and genotyped their whole blood DNA samples on Illumina Cyto12v2.1 SNP chips to generate DNA copy number. Participants were followed up every 2 years for a total of 8 years, especially for the development of skin lesions. In Cox regression models, each CNV segment was used as a predictor, accounting for other potential covariates, for incidence of skin lesions.

RESULT

The presence of genomic deletion(s) in a number of genes (OR5J2, GOLGA6L7P, APBA2, GALNTL5, VN1R31P, PHKG1P2, SGCZ, ZNF658) and lincRNA genes (RP11-76I14.1, CTC-535 M15.2, RP11-73B2.2) were associated with higher risk [HR between 1.67 (CI 1.3-2.1) and 2.15 (CI 1.5-2.9) for different CNVs] for development of skin lesions independent of gender, age, and arsenic exposure. Some deletions had stronger effect in a specific gender (ZNF658 in males, SGCZ in females) and some had stronger effect in higher arsenic exposure (lincRNA CTD-3179P9.1) suggesting a possible gene-environment interaction.

CONCLUSION

This first genome-wide CNV study in a prospectively followed-up large cohort, exposed to arsenic, suggests that DNA deletion in several genes and lincRNA genes may predispose an individual to a higher risk of development of arsenic-induced skin lesions.

Novel recurrent chromosomal aberrations detected in clonal plasma cells of light chain amyloidosis patients show potential adverse prognostic effect: first results from a genome-wide copy number array analysis

Immunoglobulin light chain (AL) amyloidosis is a rare plasma cell dyscrasia characterized by the deposition of abnormal amyloid fibrils in multiple organs, thus impairing their function. In the largest cohort studied up to now of 118 CD138-purified plasma cell samples from previously untreated immunoglobulin light chain amyloidosis patients, we assessed in parallel copy number alterations using high-density copy number arrays and interphase fluorescence in situ hybridization (iFISH). We used fluorescence in situ hybridization probes for the IgH translocations t(11;14), t(4;14), and t(14;16) or any other IgH rearrangement as well as numerical aberrations of the chromosome loci 1q21, 8p21, 5p15/5q35, 11q22.3 or 11q23, 13q14, 15q22, 17p13, and 19q13. Recurrent gains included chromosomes 1q (36%), 9 (24%), 11q (24%), as well as 19 (15%). Recurrent losses affected chromosome 13 (29% monosomy) and partial losses of 14q (19%), 16q (14%) and 13q (12%), respectively. In 88% of patients with translocation t(11;14), the hallmark chromosomal aberration in AL amyloidosis, a concomitant gain of 11q22.3/11q23 detected by iFISH was part of the unbalanced translocation der(14)t(11;14)(q13;q32) with the breakpoint in the CCND1/MYEOV gene region. Partial loss of chromosome regions 14q and 16q were significantly associated to gain 1q. Gain 1q21 detected by iFISH almost always resulted from a gain of the long arm of chromosome 1 and not from trisomy 1, whereas deletions on chromosome 1p were rarely found. Overall and event-free survival analysis found a potential adverse prognostic effect of concomitant gain 1q and deletion 14q as well as of deletion 1p. In conclusion, in the first whole genome report of clonal plasma cells in AL amyloidosis, novel aberrations and hitherto unknown potential adverse prognostic effects were uncovered.

Analysis of tissue from products of conception and perinatal losses using QF-PCR and microarray: A three-year retrospective study resulting in an efficient protocol

OBJECTIVE

To evaluate the performance of a laboratory protocol for direct genetic analysis performed on tissues obtained from miscarriages, stillbirth and postnatal death.

METHODS

Samples were collected between July 1st, 2011 and June 30th, 2014. QF-PCR analysis was the initial test followed by aCGH analysis performed on the normal QF-PCR specimens.

RESULTS

Of the 1195 submitted specimens, a total of 1071 samples were confirmed as true fetal. The failure rate was 1.4%. Of those, 30.8% yielded abnormal results. Of the latter, 57.6% had abnormal QF-PCR and 42.4% had abnormal microarray result. Autosomal trisomies were detected in 61.2%, triploidy in 7.6%, monosomy X in 9.1%, sex-chromosome aneuploidy (apart from monosomy X) in 1.5%, molar pregnancies in 5.8% and copy number variants in 14.2% including microdeletions/microduplications and cryptic unbalanced rearrangements. The highest diagnostic yield was observed in the 1st trimester specimens at 67.6%. We confirmed that maternal age correlates with the likelihood of autosomal trisomies but not with triploidy, sex chromosome aneuploidies, molar pregnancy, or CNVs.

CONCLUSION

An efficient laboratory protocol, based on QF-PCR and aCGH of uncultured cells has replaced standard cytogenetic analysis in testing of tissue from all pregnancy losses in our center and resulted in reduced test failure rate and increased diagnostic yield.

Phenotypic and genomic analysis of multiple myeloma minimal residual disease tumor cells: a new model to understand chemoresistance

We report for the first time the biological features of MRD cells in MM and unravel that clonal selection is already present at the MRD stage. MRD cells show a singular phenotypic signature that may result from persisting clones with different genetic and gene expression profiles.

Diagnostic interpretation of array data using public databases and internet sources

The range of commercially available array platforms and analysis software packages is expanding and their utility is improving, making reliable detection of copy-number variants (CNVs) relatively straightforward. Reliable interpretation of CNV data, however, is often difficult and requires expertise. With our knowledge of the human genome growing rapidly, applications for array testing continuously broadening, and the resolution of CNV detection increasing, this leads to great complexity in interpreting what can be daunting data. Correct CNV interpretation and optimal use of the genotype information provided by single-nucleotide polymorphism probes on an array depends largely on knowledge present in various resources. In addition to the availability of host laboratories' own datasets and national registries, there are several public databases and Internet resources with genotype and phenotype information that can be used for array data interpretation. With so many resources now available, it is important to know which are fit-for-purpose in a diagnostic setting. We summarize the characteristics of the most commonly used Internet databases and resources, and propose a general data interpretation strategy that can be used for comparative hybridization, comparative intensity, and genotype-based array data.

Repeat- and error-aware comparison of deletions

MOTIVATION

The number of reported genetic variants is rapidly growing, empowered by ever faster accumulation of next-generation sequencing data. A major issue is comparability. Standards that address the combined problem of inaccurately predicted breakpoints and repeat-induced ambiguities are missing. This decisively lowers the quality of 'consensus' callsets and hampers the removal of duplicate entries in variant databases, which can have deleterious effects in downstream analyses.

RESULTS

We introduce a sound framework for comparison of deletions that captures both tool-induced inaccuracies and repeat-induced ambiguities. We present a maximum matching algorithm that outputs virtual duplicates among two sets of predictions/annotations. We demonstrate that our approach is clearly superior over ad hoc criteria, like overlap, and that it can reduce the redundancy among callsets substantially. We also identify large amounts of duplicate entries in the Database of Genomic Variants, which points out the immediate relevance of our approach.

AVAILABILITY AND IMPLEMENTATION

Implementation is open source and available from https://bitbucket.org/readdi/readdi

CONTACT

roland.wittler@uni-bielefeld.de or t.marschall@mpi-inf.mpg.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The cellular origin and malignant transformation of Waldenström macroglobulinemia

Benign (ie, IgM MGUS and smoldering WM) clonal B cells already harbor the phenotypic and molecular signatures of the malignant WM clone. Multistep transformation from benign (ie, IgM MGUS and smoldering WM) to malignant WM may require specific copy number abnormalities.

A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations

We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.

Genome-wide analysis of human populations is useful in shedding light on the evolutionary history of the human genome, with a wide range of applications from reconstructing past associations between different population histories to disease mapping. In this manuscript we report on the application of genome-wide data to southern African populations and the identification of genome-wide signatures of selection pre- and post-admixture. Several signals of selection, before and after admixture, were identified, some of which involved loci associated with human diseases, including malaria, influenza, tuberculosis and HIV/AIDS. These results may reflect adaptations of southern African populations to infectious diseases. Consistent with previous studies, this study highlights the significance of the San in the genetics of human populations, as they are distinct from the other populations in many respects i.e. haplotype structure, locations of recombination hotspots, copy number and population structure. Furthermore, our study demonstrates the admixture of the San, Bantu-speaking populations and populations of Eurasian ancestry in some of the southern and eastern African populations. It illustrates the value in correcting for this stratification in future genome-wide association studies, and suggests that a future admixture mapping in these populations would likely be warranted and successful.

Usefulness of the SNP microarray technology to identify rare mutations in the case of perinatal death

Background: The single nucleotide polymorphism (SNP) microarray technology has emerged as a powerful tool to screen the whole genome for sub-microscopic duplications and deletions that are not detectable by traditional cytogenetic analysis.

Case: We report a case of a female twin born at 27th week of gestation who died 1 day after birth whereas the co-twin survived without complications. The case twin was referred to our unit for autopsy, and in addition we performed an SNP microarray analysis.

Results: Three copy number variants (CNVs) were identified by the SNP microarray analysis. The most interesting CNV in relation to the clinical phenotype (pulmonary immaturity) was a disruption in the gene ST6GALNAC3 (1p31.1) that is involved in the biosynthesis of gangliosides.

Conclusions: It is unknown from this case report whether the CNV at 1p31.1 contributes to a genetic predisposition that is related to maturation of the lungs or the perinatal death of one of the twins. However, disruptions in the biosynthesis of gangliosides have been previously associated with premature death in mice.

Molecular characterization of an intact p53 pathway subtype in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is the most aggressive histological type of epithelial ovarian cancer, which is characterized by a high frequency of somatic TP53 mutations. We performed exome analyses of tumors and matched normal tissues of 34 Japanese patients with HGSOC and observed a substantial number of patients without TP53 mutation (24%, 8/34). Combined with the results of copy number variation analyses, we subdivided the 34 patients with HGSOC into subtypes designated ST1 and ST2. ST1 showed intact p53 pathway and was characterized by fewer somatic mutations and copy number alterations. In contrast, the p53 pathway was impaired in ST2, which is characterized by abundant somatic mutations and copy number alterations. Gene expression profiles combined with analyses using the Gene Ontology resource indicate the involvement of specific biological processes (mitosis and DNA helicase) that are relevant to genomic stability and cancer etiology. In particular we demonstrate the presence of a novel subtype of patients with HGSOC that is characterized by an intact p53 pathway, with limited genomic alterations and specific gene expression profiles.

Trisomy 1q41-qter and monosomy 3p26.3-pter in a family with a translocation (1;3): further delineation of the syndromes

Background

Trisomy 1q and monosomy 3p deriving from a t(1;3) is an infrequent event. The clinical characteristics of trisomy 1q41-qter have been described but there is not a delineation of the syndrome. The 3p25.3-pter monosomy syndrome (MIM 613792) characteristics include low birth weight, microcephaly, psychomotor and growth retardation and abnormal facies.

Case presentation

A 2 years 8 months Mexican mestizo male patient was evaluated due to a trisomy 1q and monosomy 3p derived from a familial t(1;3)(q41;q26.3). Four female carriers of the balanced translocation and one relative that may have been similarly affected as the proband were identified. The implicated chromosomal regions were defined by microarray analysis, the patient had a trisomy 1q41-qter of 30.3 Mb in extension comprising about 240 protein coding genes and a monosomy 3p26.3-pter of 1.7 Mb including only the genes CNTN6 (MIM 607220) and CHL1 (MIM 607416), which have been implicated in dendrite development. Their contribution to the phenotype, regarding the definition of trisomy 1q41-qter and monosomy 3p26.3-pter syndromes are discussed.

Conclusion

We propose that a trisomy 1q41-qter syndrome should be considered in particular when the following characteristics are present: postnatal growth delay, macrocephaly, wide fontanelle, triangular facies, frontal bossing, thick eye brows, down slanting palpebral fissures, hypertelorism, flat nasal bridge, hypoplasic nostrils, long filtrum, high palate, microretrognathia, ear abnormalities, neural abnormalities (in particular ventricular dilatation), psychomotor developmental delay and mental retardation. Our patient showed most of these clinical characteristics with exception of macrocephaly, possibly due to a compensatory effect by haploinsufficiency of the two genes lost from 3p. The identification of carriers has important implications for genetic counseling as the risk of a new born with either a der(3) or der(1) resulting from an adjacent-1 segregation is of 25% for each of them, as the products of adjacent-2 or 3:1 segregations are not expected to be viable.

In vivo murine model of acquired resistance in myeloma reveals differential mechanisms for lenalidomide and pomalidomide in combination with dexamethasone

The development of resistance to therapy is unavoidable in the history of multiple myeloma patients. Therefore, the study of its characteristics and mechanisms is critical in the search for novel therapeutic approaches to overcome it. This effort is hampered by the absence of appropriate preclinical models, especially those mimicking acquired resistance. Here we present an in vivo model of acquired resistance based on the continuous treatment of mice bearing subcutaneous MM1S plasmacytomas. Xenografts acquired resistance to two generations of immunomodulatory drugs (IMiDs; lenalidomide and pomalidomide) in combination with dexamethasone, that was reversible after a wash-out period. Furthermore, lenalidomide-dexamethasone (LD) or pomalidomide-dexamethasone (PD) did not display cross-resistance, which could be due to the differential requirements of the key target Cereblon and its substrates Aiolos and Ikaros observed in cells resistant to each combination. Differential gene expression profiles of LD and PD could also explain the absence of cross-resistance. Onset of resistance to both combinations was accompanied by upregulation of the mitogen-activated protein kinase/extracellular signal-regulated kinase (ERK) kinase (MEK)/ERK pathway and addition of selumetinib, a small-molecule MEK inhibitor, could resensitize resistant cells. Our results provide insights into the mechanisms of acquired resistance to LD and PD combinations and offer possible therapeutic approaches to addressing IMiD resistance in the clinic.

MBASED: allele-specific expression detection in cancer tissues and cell lines

Allele-specific gene expression, ASE, is an important aspect of gene regulation. We developed a novel method MBASED, meta-analysis based allele-specific expression detection for ASE detection using RNA-seq data that aggregates information across multiple single nucleotide variation loci to obtain a gene-level measure of ASE, even when prior phasing information is unavailable. MBASED is capable of one-sample and two-sample analyses and performs well in simulations. We applied MBASED to a panel of cancer cell lines and paired tumor-normal tissue samples, and observed extensive ASE in cancer, but not normal, samples, mainly driven by genomic copy number alterations.

De novo missense mutations in the NAA10 gene cause severe non-syndromic developmental delay in males and females

Recent studies revealed the power of whole-exome sequencing to identify mutations in sporadic cases with non-syndromic intellectual disability. We now identified de novo missense variants in NAA10 in two unrelated individuals, a boy and a girl, with severe global developmental delay but without any major dysmorphism by trio whole-exome sequencing. Both de novo variants were predicted to be deleterious, and we excluded other variants in this gene. This X-linked gene encodes N-alpha-acetyltransferase 10, the catalytic subunit of the NatA complex involved in multiple cellular processes. A single hypomorphic missense variant p.(Ser37Pro) was previously associated with Ogden syndrome in eight affected males from two different families. This rare disorder is characterized by a highly recognizable phenotype, global developmental delay and results in death during infancy. In an attempt to explain the discrepant phenotype, we used in vitro N-terminal acetylation assays which suggested that the severity of the phenotype correlates with the remaining catalytic activity. The variant in the Ogden syndrome patients exhibited a lower activity than the one seen in the boy with intellectual disability, while the variant in the girl was the most severe exhibiting only residual activity in the acetylation assays used. We propose that N-terminal acetyltransferase deficiency is clinically heterogeneous with the overall catalytic activity determining the phenotypic severity.

Coherent somatic mutation in autoimmune disease

BACKGROUND

Many aspects of autoimmune disease are not well understood, including the specificities of autoimmune targets, and patterns of co-morbidity and cross-heritability across diseases. Prior work has provided evidence that somatic mutation caused by gene conversion and deletion at segmentally duplicated loci is relevant to several diseases. Simple tandem repeat (STR) sequence is highly mutable, both somatically and in the germ-line, and somatic STR mutations are observed under inflammation.

RESULTS

Protein-coding genes spanning STRs having markers of mutability, including germ-line variability, high total length, repeat count and/or repeat similarity, are evaluated in the context of autoimmunity. For the initiation of autoimmune disease, antigens whose autoantibodies are the first observed in a disease, termed primary autoantigens, are informative. Three primary autoantigens, thyroid peroxidase (TPO), phogrin (PTPRN2) and filaggrin (FLG), include STRs that are among the eleven longest STRs spanned by protein-coding genes. This association of primary autoantigens with long STR sequence is highly significant (p<3.0x10(-7)). Long STRs occur within twenty genes that are associated with sixteen common autoimmune diseases and atherosclerosis. The repeat within the TTC34 gene is an outlier in terms of length and a link with systemic lupus erythematosus is proposed.

CONCLUSIONS

The results support the hypothesis that many autoimmune diseases are triggered by immune responses to proteins whose DNA sequence mutates somatically in a coherent, consistent fashion. Other autoimmune diseases may be caused by coherent somatic mutations in immune cells. The coherent somatic mutation hypothesis has the potential to be a comprehensive explanation for the initiation of many autoimmune diseases.

Definition and refinement of the 7q36.3 duplication region associated with schizophrenia

Using a very high-resolution oligonucleotide array for copy number variant (CNV) screening of samples comprising schizophrenic patients, we detected a novel CNV within the critical region (NCBI36/hg18, Chr7: 158,630,410-158,719,410) previously shown to be associated with schizophrenia. We investigated the association between the novel CNV identified in the current study and schizophrenia. Three independent samples were used: (1) Screening set, 300 Japanese schizophrenic patients (53.28 ± 14.66 years); (2) Confirmation set, 531 schizophrenic patients (46.03 ± 12.15 years); and (3) 711 healthy controls (47.12 ± 11.03 years). All subjects enrolled in the study were Japanese. Chromosomal position was determined using fluorescence in situ hybridization. We identified a novel duplication within the region associated with schizophrenia identified on 7q36.3 that is adjacent to VIPR2 and is not associated with schizophrenia. In the Japanese population, the 35-kb region that harbors the common, novel CNV should be excluded from the region associated with schizophrenia on 7q36.3.

Rare autosomal copy number variations in early-onset familial Alzheimer's disease

Over 200 rare and fully penetrant pathogenic mutations in amyloid precursor protein (APP), presenilin 1 and 2 (PSEN1 and PSEN2) cause a subset of early-onset familial Alzheimer's disease (EO-FAD). Of these, 21 cases of EO-FAD families carrying unique APP locus duplications remain the only pathogenic copy number variations (CNVs) identified to date in Alzheimer's disease (AD). Using high-density DNA microarrays, we performed a comprehensive genome-wide analysis for the presence of rare CNVs in 261 EO-FAD and early/mixed-onset pedigrees. Our analysis revealed 10 novel private CNVs in 10 EO-FAD families overlapping a set of genes that includes: A2BP1, ABAT, CDH2, CRMP1, DMRT1, EPHA5, EPHA6, ERMP1, EVC, EVC2, FLJ35024 and VLDLR. In addition, CNVs encompassing two known frontotemporal dementia genes, CHMP2B and MAPT were found. To our knowledge, this is the first study reporting rare gene-rich CNVs in EO-FAD and early/mixed-onset AD that are likely to underlie pathogenicity in familial AD and perhaps related dementias.

The Potential Role of Insulin on the Shank-Postsynaptic Platform in Neurodegenerative Diseases Involving Cognition

Loss of synaptic function is critical in the pathogenesis of Alzheimer's disease (AD) and other central nervous system (CNS) degenerations. A promising candidate in the regulation of synaptic function is Shank, a protein that serves as a scaffold for excitatory synaptic receptors and proteins. Loss of Shank alters structure and function of the postsynaptic density (PSD). Shank proteins are associated with N-methyl-d-aspartate and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor loss at the PSD in AD; mutations in Shank also lead to autism spectrum disorders (ASDs) and schizophrenia, both of which affect cognition, suggesting that Shank may play a common pathologic role in AD, ASD, and schizophrenia. Shank protein directly associates with insulin receptor substrate protein p53 in PSD. Insulin and insulin sensitizers have been used in clinical trials for these diseases; this suggests that insulin signals may alter protein homeostasis at the shank-postsynaptic platform in PSDs; insulin could improve the function of synapses in these diseases.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis

BACKGROUND

Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan.

RESULTS

We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations.

CONCLUSIONS

We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Assessing the impact of copy number variants on miRNA genes in autism by Monte Carlo simulation

Autism Spectrum Disorders (ASDs) are childhood neurodevelopmental disorders with complex genetic origins. Previous studies have investigated the role of de novo Copy Number Variants (CNVs) and microRNAs as important but distinct etiological factors in ASD. We developed a novel computational procedure to assess the potential pathogenic role of microRNA genes overlapping de novo CNVs in ASD patients. Here we show that for chromosomes # 1, 2 and 22 the actual number of miRNA loci affected by de novo CNVs in patients was found significantly higher than that estimated by Monte Carlo simulation of random CNV events. Out of 24 miRNA genes over-represented in CNVs from these three chromosomes only hsa-mir-4436b-1 and hsa-mir-4436b-2 have not been detected in CNVs from non-autistic subjects as reported in the Database of Genomic Variants. Altogether the results reported in this study represent a first step towards a full understanding of how a dysregulated expression of the 24 miRNAs genes affect neurodevelopment in autism. We also propose that the procedure used in this study can be effectively applied to CNVs/miRNA genes association data in other genomic disorders beyond autism.

The impact of chromosomal microarray on clinical management: a retrospective analysis

PURPOSE

Chromosomal microarray has been widely adopted as the first-tier clinical test for individuals with multiple congenital anomalies, developmental delay, intellectual disability, and autism spectrum disorders. Although chromosomal microarray has been extensively shown to provide a higher diagnostic yield than conventional cytogenetic methods, some health insurers refuse to provide coverage for this test, claiming that it is experimental and does not affect patients' clinical management.

METHODS

We retrospectively reviewed the electronic medical records of all patients who had abnormal chromosomal microarray findings reported by our laboratory over a 3-year period and quantified the management recommendations made in response to these results.

RESULTS

Abnormal chromosomal microarray findings were reported for 12.7% of patients (227/1,780). For patients with clinical follow-up notes available, these results had management implications for 54.5% of patients in the entire abnormal cohort (102/187) and for 42.1% of patients referred for isolated neurodevelopmental disorders (16/38). Recommendations included pharmacological treatment, cancer-related screening or exclusion of screening, contraindications, and referrals for further evaluation.

CONCLUSION

These results empirically demonstrate the clinical utility of chromosomal microarray by providing evidence that management was directly affected for the majority of patients in our cohort with abnormal chromosomal microarray findings.

Human transporter database: comprehensive knowledge and discovery tools in the human transporter genes

Transporters are essential in homeostatic exchange of endogenous and exogenous substances at the systematic, organic, cellular, and subcellular levels. Gene mutations of transporters are often related to pharmacogenetics traits. Recent developments in high throughput technologies on genomics, transcriptomics and proteomics allow in depth studies of transporter genes in normal cellular processes and diverse disease conditions. The flood of high throughput data have resulted in urgent need for an updated knowledgebase with curated, organized, and annotated human transporters in an easily accessible way. Using a pipeline with the combination of automated keywords query, sequence similarity search and manual curation on transporters, we collected 1,555 human non-redundant transporter genes to develop the Human Transporter Database (HTD) (http://htd.cbi.pku.edu.cn). Based on the extensive annotations, global properties of the transporter genes were illustrated, such as expression patterns and polymorphisms in relationships with their ligands. We noted that the human transporters were enriched in many fundamental biological processes such as oxidative phosphorylation and cardiac muscle contraction, and significantly associated with Mendelian and complex diseases such as epilepsy and sudden infant death syndrome. Overall, HTD provides a well-organized interface to facilitate research communities to search detailed molecular and genetic information of transporters for development of personalized medicine.

Genome-wide analysis of the role of copy-number variation in pancreatic cancer risk

Although family history is a risk factor for pancreatic adenocarcinoma, much of the genetic etiology of this disease remains unknown. While genome-wide association studies have identified some common single nucleotide polymorphisms (SNPs) associated with pancreatic cancer risk, these SNPs do not explain all the heritability of this disease. We hypothesized that copy number variation (CNVs) in the genome may play a role in genetic predisposition to pancreatic adenocarcinoma. Here, we report a genome-wide analysis of CNVs in a small hospital-based, European ancestry cohort of pancreatic cancer cases and controls. Germline CNV discovery was performed using the Illumina Human CNV370 platform in 223 pancreatic cancer cases (both sporadic and familial) and 169 controls. Following stringent quality control, we asked if global CNV burden was a risk factor for pancreatic cancer. Finally, we performed in silico CNV genotyping and association testing to discover novel CNV risk loci. When we examined the global CNV burden, we found no strong evidence that CNV burden plays a role in pancreatic cancer risk either overall or specifically in individuals with a family history of the disease. Similarly, we saw no significant evidence that any particular CNV is associated with pancreatic cancer risk. Taken together, these data suggest that CNVs do not contribute substantially to the genetic etiology of pancreatic cancer, though the results are tempered by small sample size and large experimental variability inherent in array-based CNV studies.

Homozygous microdeletion of exon 5 in ZNF277 in a girl with specific language impairment

Specific language impairment (SLI), an unexpected failure to develop appropriate language skills despite adequate non-verbal intelligence, is a heterogeneous multifactorial disorder with a complex genetic basis. We identified a homozygous microdeletion of 21,379 bp in the ZNF277 gene (NM_021994.2), encompassing exon 5, in an individual with severe receptive and expressive language impairment. The microdeletion was not found in the proband's affected sister or her brother who had mild language impairment. However, it was inherited from both parents, each of whom carries a heterozygous microdeletion and has a history of language problems. The microdeletion falls within the AUTS1 locus, a region linked to autistic spectrum disorders (ASDs). Moreover, ZNF277 is adjacent to the DOCK4 and IMMP2L genes, which have been implicated in ASD. We screened for the presence of ZNF277 microdeletions in cohorts of children with SLI or ASD and panels of control subjects. ZNF277 microdeletions were at an increased allelic frequency in SLI probands (1.1%) compared with both ASD family members (0.3%) and independent controls (0.4%). We performed quantitative RT-PCR analyses of the expression of IMMP2L, DOCK4 and ZNF277 in individuals carrying either an IMMP2L_DOCK4 microdeletion or a ZNF277 microdeletion. Although ZNF277 microdeletions reduce the expression of ZNF277, they do not alter the levels of DOCK4 or IMMP2L transcripts. Conversely, IMMP2L_DOCK4 microdeletions do not affect the expression levels of ZNF277. We postulate that ZNF277 microdeletions may contribute to the risk of language impairments in a manner that is independent of the autism risk loci previously described in this region.

Copy number variations of HLA-DRB5 is associated with systemic lupus erythematosus risk in Chinese Han population

Systemic lupus erythematosus (SLE) is a polygenic, systemic, autoimmune disease. Copy number variants (CNVS) have been discovered to be associated with a number of complex disorders. We undertook the current study to explore the potential associations between genomic CNVS and SLE in Chinese Han population. In the discovery stage, seven SLE patients were examined with the high-density comparative genomic hybridization microarrays in the screening test for SLE associated CNVS. Then, in the validation stage, 135 SLE patients and 219 matched healthy subjects were investigated for the CNVS of gene HLA-DRB5 by AccuCopy™ technology. Quantitative polymerase chain reaction was carried out to determine the copy number (CN) and mRNA level of HLA-DRB5 in SLE patients. Although the mRNA level of HLA-DRB5 between the CN deletion group and the CN normal group in SLE patients was not statistically positive (P = 0.46), our results still showed more CN of HLA-DRB5 in SLE patients than in healthy controls (P = 3.98 × 10(-6)). Odds ratio for CN deletion was 0.38 (95% confidence interval (CI), 0.23-0.61, P = 7.79 × 10(-5)) and for CN duplication was 1.89 (95% CI, 0.56-7.66, P = 0.37), respectively. These findings indicated that CNVS of HLA-DRB5 was associated with the risk of SLE, and CN deletion appeared to be protective for SLE.

Molecular cytogenetics: making it safe for human embryonic stem cells to enter the clinic

Regenerative therapies based on transplantation of cells derived from human embryonic stem cells (hESC) are currently being prepared for clinical trials. Unfortunately, recent evidence indicates that many kinds of changes can occur to hESC during expansion in culture, and alterations to the growth control mechanisms may be required to establish hESC lines at all. Changes in the genome and epigenome can affect the validity of in vitro and animal studies, and put transplant recipients at increased risk of cancer. New molecular cytogenetic technologies enable us to examine the whole human genome with ever-finer resolution. This review describes several techniques for whole-genome analysis and the information they can provide about hESC lines. Adoption of high-resolution genotyping into routine characterization may prevent highly discouraging clinical outcomes.

Changing interpretation of chromosomal microarray over time in a community cohort with intellectual disability

Chromosomal microarray (CMA) is the first-line diagnostic test for individuals with intellectual disability, autism, or multiple congenital anomalies, with a 10-20% diagnostic yield. An ongoing challenge for the clinician and laboratory scientist is the interpretation of variants of uncertain significance (VOUS)-usually rare, unreported genetic variants. Laboratories differ in their threshold for reporting VOUS, and clinical practice varies in how this information is conveyed to the family and what follow-up is arranged. Workflows, websites, and databases are constantly being updated to aid the interpretation of VOUS. There is a growing literature reporting new microdeletion and duplication syndromes, susceptibility, and modifier copy number variants (CNVs). Diagnostic methods are also evolving with new array platforms and genome builds. In 2010, high-resolution arrays (Affymetrix 2.7 M Oligo and SNP, 50 kB resolution) were performed on a community cohort of 67 individuals with intellectual disability of unknown aetiology. Three hundred and one CNVs were detected and analyzed using contemporary resources and a simple scoring system. Thirteen (19%) of the arrays were assessed as potentially pathogenic, 4 (6%) as benign and 50 (75%) of uncertain clinical significance. The CNV data were re-analyzed in 2012 using the contemporary interpretative resources. There was a statistically significant difference in the assessment of individual CNVs (P < 0.0001). An additional eight patients were reassessed as having a potentially pathogenic array (n = 21, 31%) and several additional susceptibility or modifier CNVs were identified. This study highlights the complexity involved in the interpretation of CMA and uniquely demonstrates how, even on the same array platform, it can be subject to change over time.

CNVs-microRNAs interactions demonstrate unique characteristics in the human genome. An interspecies in silico analysis

MicroRNAs (miRNAs) and copy number variations (CNVs) represent two classes of newly discovered genomic elements that were shown to contribute to genome plasticity and evolution. Recent studies demonstrated that miRNAs and CNVs must have co-evolved and interacted in an attempt to maintain the balance of the dosage sensitive genes and at the same time increase the diversity of dosage non-sensitive genes, contributing to species evolution. It has been previously demonstrated that both the number of miRNAs that target genes found in CNV regions as well as the number of miRNA binding sites are significantly higher than those of genes found in non-CNV regions. These findings raise the possibility that miRNAs may have been created under evolutionary pressure, as a mechanism for increasing the tolerance to genome plasticity. In the current study, we aimed in exploring the differences of miRNAs-CNV functional interactions between human and seven others species. By performing in silico whole genome analysis in eight different species (human, chimpanzee, macaque, mouse, rat, chicken, dog and cow), we demonstrate that miRNAs targeting genes located within CNV regions in humans have special functional characteristics that provide an insight into the differences between humans and other species.

HAMR: high-throughput annotation of modified ribonucleotides

RNA is often altered post-transcriptionally by the covalent modification of particular nucleotides; these modifications are known to modulate the structure and activity of their host RNAs. The recent discovery that an RNA methyl-6 adenosine demethylase (FTO) is a risk gene in obesity has brought to light the significance of RNA modifications to human biology. These noncanonical nucleotides, when converted to cDNA in the course of RNA sequencing, can produce sequence patterns that are distinguishable from simple base-calling errors. To determine whether these modifications can be detected in RNA sequencing data, we developed a method that can not only locate these modifications transcriptome-wide with single nucleotide resolution, but can also differentiate between different classes of modifications. Using small RNA-seq data we were able to detect 92% of all known human tRNA modification sites that are predicted to affect RT activity. We also found that different modifications produce distinct patterns of cDNA sequence, allowing us to differentiate between two classes of adenosine and two classes of guanine modifications with 98% and 79% accuracy, respectively. To show the robustness of this method to sample preparation and sequencing methods, as well as to organismal diversity, we applied it to a publicly available yeast data set and achieved similar levels of accuracy. We also experimentally validated two novel and one known 3-methylcytosine (3mC) sites predicted by HAMR in human tRNAs. Researchers can now use our method to identify and characterize RNA modifications using only RNA-seq data, both retrospectively and when asking questions specifically about modified RNA.

A genome wide survey supports the involvement of large copy number variants in schizophrenia with and without intellectual disability

BACKGROUND

Copy number variants (CNVs) have been shown to play a role in schizophrenia and intellectual disability.

METHODS

We compared the CNV burden in 66 patients with intellectual disability and no symptoms of psychosis (ID-only) with the burden in 64 patients with intellectual disability and schizophrenia (ID + SCZ). Samples were genotyped on three plates by the Broad Institute using the Affymetrix 6.0 array.

RESULTS

For CNVs larger than 100 kb, there was no difference in the CNV burden of ID-only and ID + SCZ. In contrast, the number of duplications larger than 1 Mb was increased in ID + SCZ compared to ID-only. We detected seven large duplications and two large deletions at chromosome 15q11.2 (18.5-20.1 Mb) which were all present in patients with ID + SCZ. The involvement of this region in schizophrenia was confirmed in Scottish samples from the ISC study (N = 2,114; 1,130 cases and 984 controls). Finally, one of the patients with schizophrenia and low IQ carrying a duplication at 15q11.2, is a member of a previously described pedigree with multiple cases of mild intellectual disability, schizophrenia, hearing impairment, retinitis pigmentosa and cataracts. DNA samples were available for 11 members of this family and the duplication was present in all 10 affected individuals and was absent in an unaffected individual.

CONCLUSIONS

Duplications at 15q11.2 (18.5-20.1 Mb) are highly prevalent in a severe group of patients characterized by intellectual disability and comorbid schizophrenia. It is also associated with a phenotype that includes schizophrenia, low IQ, hearing and visual impairments resembling the spectrum of symptoms described in "ciliopathies."

CNVannotator: a comprehensive annotation server for copy number variation in the human genome

Copy number variation (CNV) is one of the most prevalent genetic variations in the genome, leading to an abnormal number of copies of moderate to large genomic regions. High-throughput technologies such as next-generation sequencing often identify thousands of CNVs involved in biological or pathological processes. Despite the growing demand to filter and classify CNVs by factors such as frequency in population, biological features, and function, surprisingly, no online web server for CNV annotations has been made available to the research community. Here, we present CNVannotator, a web server that accepts an input set of human genomic positions in a user-friendly tabular format. CNVannotator can perform genomic overlaps of the input coordinates using various functional features, including a list of the reported 356,817 common CNVs, 181,261 disease CNVs, as well as, 140,342 SNPs from genome-wide association studies. In addition, CNVannotator incorporates 2,211,468 genomic features, including ENCODE regulatory elements, cytoband, segmental duplication, genome fragile site, pseudogene, promoter, enhancer, CpG island, and methylation site. For cancer research community users, CNVannotator can apply various filters to retrieve a subgroup of CNVs pinpointed in hundreds of tumor suppressor genes and oncogenes. In total, 5,277,234 unique genomic coordinates with functional features are available to generate an output in a plain text format that is free to download. In summary, we provide a comprehensive web resource for human CNVs. The annotated results along with the server can be accessed at http://bioinfo.mc.vanderbilt.edu/CNVannotator/.

The Database of Genomic Variants: a curated collection of structural variation in the human genome

Over the past decade, the Database of Genomic Variants (DGV; http://dgv.tcag.ca/) has provided a publicly accessible, comprehensive curated catalogue of structural variation (SV) found in the genomes of control individuals from worldwide populations. Here, we describe updates and new features, which have expanded the utility of DGV for both the basic research and clinical diagnostic communities. The current version of DGV consists of 55 published studies, comprising >2.5 million entries identified in >22,300 genomes. Studies included in DGV are selected from the accessioned data sets in the archival SV databases dbVar (NCBI) and DGVa (EBI), and then further curated for accuracy and validity. The core visualization tool (gbrowse) has been upgraded with additional functions to facilitate data analysis and comparison, and a new query tool has been developed to provide flexible and interactive access to the data. The content from DGV is regularly incorporated into other large-scale genome reference databases and represents a standard data resource for new product and database development, in particular for copy number variation testing in clinical labs. The accurate cataloguing of variants in DGV will continue to enable medical genetics and genome sequencing research.

Disruption of the ATE1 and SLC12A1 Genes by Balanced Translocation in a Boy with Non-Syndromic Hearing Loss

We report on a boy with non-syndromic hearing loss and an apparently balanced translocation t(10;15)(q26.13;q21.1). The same translocation was found in the normally hearing brother, father and paternal grandfather; however, this does not exclude its involvement in disease pathogenesis, for example, by unmasking a second mutation. Breakpoint analysis via FISH with BAC clones and long-range PCR products revealed a disruption of the arginyltransferase 1 (ATE1) gene on translocation chromosome 10 and the solute carrier family 12, member 1 gene (SLC12A1) on translocation chromosome 15. SNP array analysis revealed neither loss nor gain of chromosomal regions in the affected child, and a targeted gene enrichment panel consisting of 130 known deafness genes was negative for pathogenic mutations. The expression patterns in zebrafish and humans did not provide evidence for ear-specific functions of the ATE1 and SLC12A1 genes. Sanger sequencing of the 2 genes in the boy and 180 GJB2 mutation-negative hearing-impaired individuals did not detect homozygous or compound heterozygous pathogenic mutations. Our study demonstrates the many difficulties in unraveling the molecular causes of a heterogeneous phenotype. We cannot directly implicate disruption of ATE1 and/or SLC12A1 to the abnormal hearing phenotype; however, mutations in these genes may have a role in polygenic or multifactorial forms of hearing impairment. On the other hand, it is conceivable that our patient carries a disease-causing mutation in a so far unidentified deafness gene. Evidently, disruption of ATE1 and/or SLC12A1 gene function alone does not have adverse effects.

ACMG Standards and Guidelines for constitutional cytogenomic microarray analysis, including postnatal and prenatal applications: revision 2013

Microarray methodologies, including array comparative genomic hybridization and single-nucleotide polymorphism-detecting arrays, are accepted as an appropriate first-tier test for the evaluation of imbalances associated with intellectual disability, autism, and multiple congenital anomalies. This technology also has applicability in prenatal specimens. To assist clinical laboratories in validation of microarray methodologies for constitutional applications, the American College of Medical Genetics and Genomics has produced the following revised professional standards and guidelines.

Association between copy number variations of HLA-DQA1 and ankylosing spondylitis in the Chinese Han population

Ankylosing spondylitis (AS) is a chronic inflammatory disease with complex genetic traits. Multiple sequence variations have been associated with AS, but explained only a proportion of heritability. The studies herein aimed to explore potential associations between genomic copy number variation (CNV) and AS of Han Chinese. Five AS patients were examined with the high-density comparative genomic hybridization (CGH) microarrays in the first screen test for AS associated CNVs. A total of 533 AS patients and 792 unrelated controls were examined in confirmation studies with the AccuCopy assays. A significant association was observed between the CNV of the HLA-DQA1 and AS. Comparing with controls, AS patients showed an aberrant copy number (CN), and significantly increased number of patients had more than 2 copies of the HLA-DQA1. Therefore, CNV of the HLA-DQA1 may play an important role in susceptibility to AS in Han Chinese population.

Follow-up of a major psychosis linkage site in 13q13-q14 reveals significant association in both case-control and family samples

BACKGROUND

We previously reported a genome-wide significant linkage for major psychosis in chromosome 13q13-q14.

METHODS

An association analysis was conducted in 247 unrelated DSM-IV schizophrenia (SZ) patients and 250 unrelated control subjects from the Eastern Quebec population genotyped with 2150 single nucleotide polymorphisms in 13q13-q14. We also used the kindred sample where linkage was detected (125 SZ, 120 bipolar disorder [BD] and 36 schizoaffective disorder patients vs. 467 unaffected adult relatives) for replication.

RESULTS

An association of the T allele of rs1156026 found in the case-control sample (odds ratio [OR] = 1.81, p = 4 × 10(-6), false discovery rate = .01) was replicated in the kindred sample (OR = 1.54, p = .01), strengthening the overall association evidence (p = 8 × 10(-7)). The effect size increased in the subset of unrelated patients with a family history (OR = 2.28) and in the 15 families where SZ was predominant (OR = 2.03). In the kindred sample, onset of either SZ or BD was, on average, 5 years earlier for T/T compared with C/C homozygotes, leading to stronger association in patients with onset before 26 years of age (SZ: OR = 2.40, p = 1.3 × 10(-4); SZ, BD, and schizoaffective disorder combined: OR = 1.87, p = 8 × 10(-5)).

CONCLUSIONS

Case-control and family-based association provided evidence of a locus at 13q13-q14 related to SZ. The proximity of the associated single nucleotide polymorphism with the linkage signal and the extension of the associated phenotype to major psychosis with younger age of onset indicate congruence between the linkage and association signals. The rs1156026 association is novel and factors explaining its nondetection in previous studies are discussed.

Mapping the human reference genome's missing sequence by three-way admixture in Latino genomes

A principal obstacle to completing maps and analyses of the human genome involves the genome's "inaccessible" regions: sequences (often euchromatic and containing genes) that are isolated from the rest of the euchromatic genome by heterochromatin and other repeat-rich sequence. We describe a way to localize these sequences by using ancestry linkage disequilibrium in populations that derive ancestry from at least three continents, as is the case for Latinos. We used this approach to map the genomic locations of almost 20 megabases of sequence unlocalized or missing from the current human genome reference (NCBI Genome GRCh37)-a substantial fraction of the human genome's remaining unmapped sequence. We show that the genomic locations of most sequences that originated from fosmids and larger clones can be admixture mapped in this way, by using publicly available whole-genome sequence data. Genome assembly efforts and future builds of the human genome reference will be strongly informed by this localization of genes and other euchromatic sequences that are embedded within highly repetitive pericentromeric regions.

Systematic pharmacogenomics analysis of a Malay whole genome: proof of concept for personalized medicine

BACKGROUND

With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to patient variability in pharmacokinetics and pharmacodynamics responses towards drugs would be the next step in future medicine in line with the vision of personalizing medicine.

METHODS

Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences.

PRINCIPAL FINDINGS

Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings.

CONCLUSIONS

The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis.

Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.

Prioritization of Copy Number Variation Loci Associated with Autism from AutDB-An Integrative Multi-Study Genetic Database

Copy number variants (CNVs) are thought to play an important role in the predisposition to autism spectrum disorder (ASD). However, their relatively low frequency and widespread genomic distribution complicates their accurate characterization and utilization for clinical genetics purposes. Here we present a comprehensive analysis of multi-study, genome-wide CNV data from AutDB (http://mindspec.org/autdb.html), a genetic database that accommodates detailed annotations of published scientific reports of CNVs identified in ASD individuals. Overall, we evaluated 4,926 CNVs in 2,373 ASD subjects from 48 scientific reports, encompassing ∼2.12×10⁹ bp of genomic data. Remarkable variation was seen in CNV size, with duplications being significantly larger than deletions, (P  =  3×10⁻¹⁰⁵; Wilcoxon rank sum test). Examination of the CNV burden across the genome revealed 11 loci with a significant excess of CNVs among ASD subjects (P<7×10⁻⁷). Altogether, these loci covered 15,610 kb of the genome and contained 166 genes. Remarkable variation was seen both in locus size (20 - 4950 kb), and gene content, with seven multigenic (≥3 genes) and four monogenic loci. CNV data from control populations was used to further refine the boundaries of these ASD susceptibility loci. Interestingly, our analysis indicates that 15q11.2-13.3, a genomic region prone to chromosomal rearrangements of various sizes, contains three distinct ASD susceptibility CNV loci that vary in their genomic boundaries, CNV types, inheritance patterns, and overlap with CNVs from control populations. In summary, our analysis of AutDB CNV data provides valuable insights into the genomic characteristics of ASD susceptibility CNV loci and could therefore be utilized in various clinical settings and facilitate future genetic research of this disorder.