John Wei
The Centre for Applied Genomics
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Featured researches published by John Wei.
Genome Biology | 2010
Andy Wing Chun Pang; Jeffrey R. MacDonald; Dalila Pinto; John Wei; Muhammad A Rafiq; Donald F. Conrad; Hansoo Park; Charles Lee; J. Craig Venter; Ewen F. Kirkness; Samuel Levy; Lars Feuk; Stephen W. Scherer
BackgroundSeveral genomes have now been sequenced, with millions of genetic variants annotated. While significant progress has been made in mapping single nucleotide polymorphisms (SNPs) and small (<10 bp) insertion/deletions (indels), the annotation of larger structural variants has been less comprehensive. It is still unclear to what extent a typical genome differs from the reference assembly, and the analysis of the genomes sequenced to date have shown varying results for copy number variation (CNV) and inversions.ResultsWe have combined computational re-analysis of existing whole genome sequence data with novel microarray-based analysis, and detect 12,178 structural variants covering 40.6 Mb that were not reported in the initial sequencing of the first published personal genome. We estimate a total non-SNP variation content of 48.8 Mb in a single genome. Our results indicate that this genome differs from the consensus reference sequence by approximately 1.2% when considering indels/CNVs, 0.1% by SNPs and approximately 0.3% by inversions. The structural variants impact 4,867 genes, and >24% of structural variants would not be imputed by SNP-association.ConclusionsOur results indicate that a large number of structural variants have been unreported in the individual genomes published to date. This significant extent and complexity of structural variants, as well as the growing recognition of their medical relevance, necessitate they be actively studied in health-related analyses of personal genomes. The new catalogue of structural variants generated for this genome provides a crucial resource for future comparison studies.
Nature Genetics | 2006
Razi Khaja; Junjun Zhang; Jeffrey R. MacDonald; Yongshu He; Ann M Joseph-George; John Wei; Muhammad A Rafiq; Cheng Qian; Mary Shago; Lorena Pantano; Hiroyuki Aburatani; Keith W. Jones; Richard Redon; Lluís Armengol; Xavier Estivill; Richard J. Mural; Charles Lee; Stephen W. Scherer; Lars Feuk
Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs and intermediate-sized variants (ISVs). However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized (<50 kb) variants. Here we show that genome assembly comparison is a robust approach for identification of all classes of genetic variation. Through comparison of two human assemblies (Celeras R27c compilation and the Build 35 reference sequence), we identified megabases of sequence (in the form of 13,534 putative non-SNP events) that were absent, inverted or polymorphic in one assembly. Database comparison and laboratory experimentation further demonstrated overlap or validation for 240 variable regions and confirmed >1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.
JAMA | 2015
Kristiina Tammimies; Christian R. Marshall; Susan Walker; Gaganjot Kaur; Bhooma Thiruvahindrapuram; Anath C. Lionel; Ryan K. C. Yuen; Mohammed Uddin; Wendy Roberts; Rosanna Weksberg; Marc Woodbury-Smith; Lonnie Zwaigenbaum; Evdokia Anagnostou; Z. B. Wang; John Wei; Jennifer L. Howe; Matthew J. Gazzellone; Lynette Lau; Wilson W L Sung; Kathy Whitten; Cathy Vardy; Victoria Crosbie; Brian Tsang; Lia D’Abate; Winnie W. L. Tong; Sandra Luscombe; Tyna Doyle; Melissa T. Carter; Peter Szatmari; Susan Stuckless
IMPORTANCEnThe use of genome-wide tests to provide molecular diagnosis for individuals with autism spectrum disorder (ASD) requires more study.nnnOBJECTIVEnTo perform chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) in a heterogeneous group of children with ASD to determine the molecular diagnostic yield of these tests in a sample typical of a developmental pediatric clinic.nnnDESIGN, SETTING, AND PARTICIPANTSnThe sample consisted of 258 consecutively ascertained unrelated children with ASD who underwent detailed assessments to define morphology scores based on the presence of major congenital abnormalities and minor physical anomalies. The children were recruited between 2008 and 2013 in Newfoundland and Labrador, Canada. The probands were stratified into 3 groups of increasing morphological severity: essential, equivocal, and complex (scores of 0-3, 4-5, and ≥6).nnnEXPOSURESnAll probands underwent CMA, with WES performed for 95 proband-parent trios.nnnMAIN OUTCOMES AND MEASURESnThe overall molecular diagnostic yield for CMA and WES in a population-based ASD sample stratified in 3 phenotypic groups.nnnRESULTSnOf 258 probands, 24 (9.3%, 95%CI, 6.1%-13.5%) received a molecular diagnosis from CMA and 8 of 95 (8.4%, 95%CI, 3.7%-15.9%) from WES. The yields were statistically different between the morphological groups. Among the children who underwent both CMA and WES testing, the estimated proportion with an identifiable genetic etiology was 15.8% (95%CI, 9.1%-24.7%; 15/95 children). This included 2 children who received molecular diagnoses from both tests. The combined yield was significantly higher in the complex group when compared with the essential group (pairwise comparison, P = .002). [table: see text].nnnCONCLUSIONS AND RELEVANCEnAmong a heterogeneous sample of children with ASD, the molecular diagnostic yields of CMA and WES were comparable, and the combined molecular diagnostic yield was higher in children with more complex morphological phenotypes in comparison with the children in the essential category. If replicated in additional populations, these findings may inform appropriate selection of molecular diagnostic testing for children affected by ASD.
G3: Genes, Genomes, Genetics | 2012
Aparna Prasad; Daniele Merico; Bhooma Thiruvahindrapuram; John Wei; Anath C. Lionel; Daisuke Sato; Jessica Rickaby; Chao Lu; Peter Szatmari; Wendy Roberts; Bridget A. Fernandez; Christian R. Marshall; Eli Hatchwell; Peggy S. Eis; Stephen W. Scherer
The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection.
American Journal of Medical Genetics | 2014
Abdul Noor; Anath C. Lionel; Sarah Cohen-Woods; Narges Moghimi; Alanna Fennell; Bhooma Thiruvahindrapuram; Liana Kaufman; Bryan Degagne; John Wei; Sagar V. Parikh; Pierandrea Muglia; Julia Forte; Stephen W. Scherer; James L. Kennedy; Wei Xu; Peter McGuffin; Anne Farmer; John S. Strauss; John B. Vincent
Genome‐wide single nucleotide polymorphism (SNP) data from 936 bipolar disorder (BD) individuals and 940 psychiatrically healthy comparison individuals of North European descent were analyzed for copy number variation (CNV). Using multiple CNV calling algorithms, and validating using in vitro molecular analyses, we identified CNVs implicating several candidate genes that encode synaptic proteins, such as DLG1, DLG2, DPP6, NRXN1, NRXN2, NRXN3, SHANK2, and EPHA5, as well as the neuronal splicing regulator RBFOX1 (A2BP1), and neuronal cell adhesion molecule CHL1. We have also identified recurrent CNVs on 15q13.3 and 16p11.2‐regions previously reported as risk loci for neuropsychiatric disorders. In addition, we performed CNV analysis of individuals from 215 BD trios and identified de novo CNVs involving the NRXN1 and DRD5 genes. Our study provides further evidence of the occasional involvement of genomic mutations in the etiology of BD, however, there is no evidence of an increased burden of CNVs in BD. Further, the identification of CNVs at multiple members of the neurexin gene family in BD individuals, supports the role of synaptic disruption in the etiology of BD.
Biological Psychiatry | 2015
William Warnica; Daniele Merico; Gregory Costain; Simon E. Alfred; John Wei; Christian R. Marshall; Stephen W. Scherer; Anne S. Bassett
BACKGROUNDnMicroRNAs (miRNAs) are key regulators of gene expression in the human genome and may contribute to risk for neuropsychiatric disorders. miRNAs play an acknowledged role in the strongest of genetic risk factors for schizophrenia, 22q11.2 deletions. We hypothesized that in schizophrenia there would be an enrichment of other rare copy number variants (CNVs) that overlap miRNAs.nnnMETHODSnUsing high-resolution genome-wide microarrays and rigorous methods, we compared the miRNA content of rare CNVs in well-characterized cohorts of schizophrenia cases (n = 420) and comparison subjects, excluding 22q11.2 CNVs. We also performed a gene-set enrichment analysis of the predicted miRNA target genes.nnnRESULTSnThe schizophrenia group was enriched for the proportion of individuals with a rare CNV overlapping a miRNA (3.29-fold increase over comparison subjects, p < .0001). The presence of a rare CNV overlapping a miRNA remained a significant predictor of schizophrenia case status (p = .0072) in a multivariate logistic regression model correcting for total CNV size. In contrast, comparable analyses correcting for CNV size showed no enrichment of rare CNVs overlapping protein-coding genes. A gene-set enrichment analysis indicated that predicted target genes of recurrent CNV-overlapped miRNAs in schizophrenia may be functionally enriched for neurodevelopmental processes, including axonogenesis and neuron projection development. Predicted gene targets driving these results included CAPRIN1, NEDD4, NTRK2, PAK2, RHOA, and SYNGAP1.nnnCONCLUSIONSnThese data are the first to demonstrate a genome-wide role for CNVs overlapping miRNAs in the genetic risk for schizophrenia. The results provide support for an expanded multihit model of causation, with potential implications for miRNA-based therapeutics.
Journal of Neurodevelopmental Disorders | 2014
Matthew J. Gazzellone; Xue Zhou; Anath C. Lionel; Mohammed Uddin; Bhooma Thiruvahindrapuram; Shuang Liang; Caihong Sun; Jia Wang; Mingyang Zou; Kristiina Tammimies; Susan Walker; Thanuja Selvanayagam; John Wei; Z. B. Wang; Lijie Wu; Stephen W. Scherer
BackgroundAutism spectrum disorders (ASDs) are a group of neurodevelopmental conditions with a demonstrated genetic etiology. Rare (<1% frequency) copy number variations (CNVs) account for a proportion of the genetic events involved, but the contribution of these events in non-European ASD populations has not been well studied. Here, we report on rare CNVs detected in a cohort of individuals with ASD of Han Chinese background.MethodsDNA samples were obtained from 104 ASD probands and their parents who were recruited from Harbin, China. Samples were genotyped on the Affymetrix CytoScan HD platform. Rare CNVs were identified by comparing data with 873 technology-matched controls from Ontario and 1,235 additional population controls of Han Chinese ethnicity.ResultsOf the probands, 8.6% had at least 1 de novo CNV (overlapping the GIGYF2, SPRY1, 16p13.3, 16p11.2, 17p13.3-17p13.2, DMD, and NAP1L6 genes/loci). Rare inherited CNVs affected other plausible neurodevelopmental candidate genes including GRID2, LINGO2, and SLC39A12. A 24-kb duplication was also identified at YWHAE, a gene previously implicated in ASD and other developmental disorders. This duplication is observed at a similar frequency in cases and in population controls and is likely a benign Asian-specific copy number polymorphism.ConclusionsOur findings help define genomic features relevant to ASD in the Han Chinese and emphasize the importance of using ancestry-matched controls in medical genetic interpretations.
BMC Genomics | 2007
Kohji Okamura; John Wei; Stephen W. Scherer
BackgroundChargaffs rule of DNA base composition, stating that DNA comprises equal amounts of adenine and thymine (%A = %T) and of guanine and cytosine (%C = %G), is well known because it was fundamental to the conception of the Watson-Crick model of DNA structure. His second parity rule stating that the base proportions of double-stranded DNA are also reflected in single-stranded DNA (%A = %T, %C = %G) is more obscure, likely because its biological basis and significance are still unresolved. Within each strand, the symmetry of single nucleotide composition extends even further, being demonstrated in the balance of di-, tri-, and multi-nucleotides with their respective complementary oligonucleotides.ResultsHere, we propose that inversions are sufficient to account for the symmetry within each single-stranded DNA. Human mitochondrial DNA does not demonstrate such intra-strand parity, and we consider how its different functional drivers may relate to our theory. This concept is supported by the recent observation that inversions occur frequently.ConclusionAlong with chromosomal duplications, inversions must have been shaping the architecture of genomes since the origin of life.
American Journal of Human Genetics | 2018
Mohammed Uddin; Brianna K. Unda; Vickie Kwan; Nicholas Holzapfel; Sean H. White; Leon Chalil; Marc Woodbury-Smith; Karen S. Ho; Erin Harward; Nadeem Murtaza; Biren M. Dave; Giovanna Pellecchia; Lia D’Abate; Thomas Nalpathamkalam; Sylvia Lamoureux; John Wei; Marsha Speevak; James Stavropoulos; Kristin J. Hope; Jacob Nielsen; E. Robert Wassman; Stephen W. Scherer; Karun K. Singh
Copy-number variations (CNVs) are strong risk factors for neurodevelopmental and psychiatric disorders. The 15q13.3 microdeletion syndrome region contains up to ten genes and is associated with numerous conditions, including autism spectrum disorder (ASD), epilepsy, schizophrenia, and intellectual disability; however, the mechanisms underlying the pathogenesis of 15q13.3 microdeletion syndrome remain unknown. We combined whole-genome sequencing, human brain gene expression (proteome and transcriptome), and a mouse model with a syntenic heterozygous deletion (Df(h15q13)/+ mice) and determined that the microdeletion results in abnormal development of cortical dendritic spines and dendrite outgrowth. Analysis of large-scale genomic, transcriptomic, and proteomic data identified OTUD7A as a critical gene for brain function. OTUD7A was found to localize to dendritic and spine compartments in cortical neurons, and its reduced levels in Df(h15q13)/+ cortical neurons contributed to the dendritic spine and dendrite outgrowth deficits. Our results reveal OTUD7A as a major regulatory gene for 15q13.3 microdeletion syndrome phenotypes that contribute to the disease mechanism through abnormal cortical neuron morphological development.
Genome Medicine | 2017
Chelsea Lowther; Daniele Merico; Gregory Costain; Jack Waserman; Kerry Boyd; Abdul Noor; Marsha Speevak; Dimitri J. Stavropoulos; John Wei; Anath C. Lionel; Christian R. Marshall; Stephen W. Scherer; Anne S. Bassett
BackgroundSchizophrenia is a severe psychiatric disorder associated with IQ deficits. Rare copy number variations (CNVs) have been established to play an important role in the etiology of schizophrenia. Several of the large rare CNVs associated with schizophrenia have been shown to negatively affect IQ in population-based controls where no major neuropsychiatric disorder is reported. The aim of this study was to examine the diagnostic yield of microarray testing and the functional impact of genome-wide rare CNVs in a community ascertained cohort of adults with schizophrenia and low (<u200985) or average (≥u200985) IQ.MethodsWe recruited 546 adults of European ancestry with schizophrenia from six community psychiatric clinics in Canada. Each individual was assigned to the low or average IQ group based on standardized tests and/or educational attainment. We used rigorous methods to detect genome-wide rare CNVs from high-resolution microarray data. We compared the burden of rare CNVs classified as pathogenic or as a variant of unknown significance (VUS) between each of the IQ groups and the genome-wide burden and functional impact of rare CNVs after excluding individuals with a pathogenic CNV.ResultsThere were 39/546 (7.1%; 95% confidence interval [CI]u2009=u20095.2–9.7%) schizophrenia participants with at least one pathogenic CNV detected, significantly more of whom were from the low IQ group (odds ratio [OR]u2009=u20095.01 [2.28–11.03], pu2009=u20090.0001). Secondary analyses revealed that individuals with schizophrenia and average IQ had the lowest yield of pathogenic CNVs (nu2009=u20099/325; 2.8%), followed by those with borderline intellectual functioning (nu2009=u20099/130; 6.9%), non-verbal learning disability (nu2009=u20096/29; 20.7%), and co-morbid intellectual disability (nu2009=u200915/62; 24.2%). There was no significant difference in the burden of rare CNVs classified as a VUS between any of the IQ subgroups. There was a significantly (p=0.002) increased burden of rare genic duplications in individuals with schizophrenia and low IQ that persisted after excluding individuals with a pathogenic CNV.ConclusionsUsing high-resolution microarrays we were able to demonstrate for the first time that the burden of pathogenic CNVs in schizophrenia differs significantly between IQ subgroups. The results of this study have implications for clinical practice and may help inform future rare variant studies of schizophrenia using next-generation sequencing technologies.