.2017 Apr;20(4):602-611.

doi: 10.1038/nn.4524. Epub 2017 Mar 6.

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder

Ryan K C Yuen¹, Daniele Merico^{1 2}, Matt Bookman^{3 4}, Jennifer L Howe¹, Bhooma Thiruvahindrapuram¹, Rohan V Patel¹, Joe Whitney¹, Nicole Deflaux^{3 4}, Jonathan Bingham^{3 4}, Zhuozhi Wang¹, Giovanna Pellecchia¹, Janet A Buchanan¹, Susan Walker¹, Christian R Marshall^{1 5}, Mohammed Uddin¹, Mehdi Zarrei¹, Eric Deneault¹, Lia D'Abate^{1 6}, Ada J S Chan^{1 6}, Stephanie Koyanagi¹, Tara Paton¹, Sergio L Pereira¹, Ny Hoang^{1 7}, Worrawat Engchuan¹, Edward J Higginbotham¹, Karen Ho¹, Sylvia Lamoureux¹, Weili Li¹, Jeffrey R MacDonald¹, Thomas Nalpathamkalam¹, Wilson W L Sung¹, Fiona J Tsoi¹, John Wei¹, Lizhen Xu¹, Anne-Marie Tasse⁸, Emily Kirby⁸, William Van Etten⁹, Simon Twigger⁹, Wendy Roberts⁷, Irene Drmic^{1 7}, Sanne Jilderda^{1 7}, Bonnie MacKinnon Modi^{1 7}, Barbara Kellam¹, Michael Szego^{1 10}, Cheryl Cytrynbaum^{6 10 11 12}, Rosanna Weksberg^{6 11 12}, Lonnie Zwaigenbaum¹³, Marc Woodbury-Smith^{1 14}, Jessica Brian¹⁵, Lili Senman¹⁵, Alana Iaboni¹⁵, Krissy Doyle-Thomas¹⁵, Ann Thompson¹⁴, Christina Chrysler¹⁴, Jonathan Leef¹⁵, Tal Savion-Lemieux¹⁶, Isabel M Smith¹⁷, Xudong Liu¹⁸, Rob Nicolson^{19 20}, Vicki Seifer²¹, Angie Fedele²¹, Edwin H Cook²², Stephen Dager²³, Annette Estes²⁴, Louise Gallagher²⁵, Beth A Malow²⁶, Jeremy R Parr²⁷, Sarah J Spence²⁸, Jacob Vorstman²⁹, Brendan J Frey^{2 30}, James T Robinson³¹, Lisa J Strug^{1 32}, Bridget A Fernandez³³, Mayada Elsabbagh¹⁶, Melissa T Carter^{12 34}, Joachim Hallmayer³⁵, Bartha M Knoppers³⁶, Evdokia Anagnostou¹⁵, Peter Szatmari^{37 38 39}, Robert H Ring⁴⁰, David Glazer^{3 4}, Mathew T Pletcher²¹, Stephen W Scherer^{1 6 41}

Affiliations

¹ The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada.
² Deep Genomics Inc., Toronto, Canada.
³ Google, Mountain View, California, USA.
⁴ Verily Life Sciences, South San Francisco, California, USA.
⁵ Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Canada.
⁶ Department of Molecular Genetics, University of Toronto, Toronto, Canada.
⁷ Autism Research Unit, The Hospital for Sick Children, Toronto, Canada.
⁸ Public Population Project in Genomics and Society, McGill University, Montreal, Canada.
⁹ BioTeam Inc., Middleton, Massachusetts, USA.
¹⁰ Dalla Lana School of Public Health and the Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
¹¹ Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada.
¹² Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Canada.
¹³ Department of Pediatrics, University of Alberta, Edmonton, Canada.
¹⁴ Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.
¹⁵ Bloorview Research Institute, University of Toronto, Toronto, Canada. .
¹⁶ Department of Psychiatry, McGill University, Montreal, Canada.
¹⁷ Departments of Pediatrics and of Psychology &Neuroscience, Dalhousie University and Autism Research Centre, IWK Health Centre, Halifax, Canada.
¹⁸ Department of Psychiatry, Queen's University, Kinston, Canada.
¹⁹ Children's Health Research Institute, London, Ontario, Canada.
²⁰ Western University, London, Ontario, Canada.
²¹ Autism Speaks, New York, New York, USA.
²² Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
²³ Department of Radiology, University of Washington, Seattle, Washington, USA.
²⁴ Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington, USA.
²⁵ Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.
²⁶ Sleep Disorders Division, Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
²⁷ Institute of Neuroscience, Newcastle University, Newcastle Upon Tyne, UK.
²⁸ Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, USA.
²⁹ Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
³⁰ Department of Electrical and Computer Engineering and Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada.
³¹ Department of Medicine, University of California San Diego, La Jolla, California, USA.
³² Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Canada.
³³ Disciplines of Genetics and Medicine, Memorial University of Newfoundland and Provincial Medical Genetic Program, Eastern Health, St. John's, Canada.
³⁴ Regional Genetics Program, The Children's Hospital of Eastern Ontario, Ottawa, Canada.
³⁵ Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA.
³⁶ Centre of Genomics and Policy, McGill University, Montreal, Canada.
³⁷ Child Youth and Family Services, Centre for Addiction and Mental Health, Toronto, Canada.
³⁸ Department of Psychiatry, University of Toronto, Toronto, Canada.
³⁹ Department of Psychiatry, The Hospital for Sick Children, Toronto, Canada.
⁴⁰ Department of Pharmacology &Physiology, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA.
⁴¹ McLaughlin Centre, University of Toronto, Toronto, Canada.

PMID:28263302
PMCID: PMC5501701
DOI: 10.1038/nn.4524

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder

Ryan K C Yuen et al. Nat Neurosci.2017 Apr.

.2017 Apr;20(4):602-611.

doi: 10.1038/nn.4524. Epub 2017 Mar 6.

Authors

Affiliations

¹ The Centre for Applied Genomics, Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada.
² Deep Genomics Inc., Toronto, Canada.
³ Google, Mountain View, California, USA.
⁴ Verily Life Sciences, South San Francisco, California, USA.
⁵ Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Canada.
⁶ Department of Molecular Genetics, University of Toronto, Toronto, Canada.
⁷ Autism Research Unit, The Hospital for Sick Children, Toronto, Canada.
⁸ Public Population Project in Genomics and Society, McGill University, Montreal, Canada.
⁹ BioTeam Inc., Middleton, Massachusetts, USA.
¹⁰ Dalla Lana School of Public Health and the Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
¹¹ Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada.
¹² Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Canada.
¹³ Department of Pediatrics, University of Alberta, Edmonton, Canada.
¹⁴ Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.
¹⁵ Bloorview Research Institute, University of Toronto, Toronto, Canada. .
¹⁶ Department of Psychiatry, McGill University, Montreal, Canada.
¹⁷ Departments of Pediatrics and of Psychology &Neuroscience, Dalhousie University and Autism Research Centre, IWK Health Centre, Halifax, Canada.
¹⁸ Department of Psychiatry, Queen's University, Kinston, Canada.
¹⁹ Children's Health Research Institute, London, Ontario, Canada.
²⁰ Western University, London, Ontario, Canada.
²¹ Autism Speaks, New York, New York, USA.
²² Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
²³ Department of Radiology, University of Washington, Seattle, Washington, USA.
²⁴ Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington, USA.
²⁵ Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.
²⁶ Sleep Disorders Division, Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
²⁷ Institute of Neuroscience, Newcastle University, Newcastle Upon Tyne, UK.
²⁸ Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, USA.
²⁹ Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
³⁰ Department of Electrical and Computer Engineering and Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada.
³¹ Department of Medicine, University of California San Diego, La Jolla, California, USA.
³² Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Canada.
³³ Disciplines of Genetics and Medicine, Memorial University of Newfoundland and Provincial Medical Genetic Program, Eastern Health, St. John's, Canada.
³⁴ Regional Genetics Program, The Children's Hospital of Eastern Ontario, Ottawa, Canada.
³⁵ Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA.
³⁶ Centre of Genomics and Policy, McGill University, Montreal, Canada.
³⁷ Child Youth and Family Services, Centre for Addiction and Mental Health, Toronto, Canada.
³⁸ Department of Psychiatry, University of Toronto, Toronto, Canada.
³⁹ Department of Psychiatry, The Hospital for Sick Children, Toronto, Canada.
⁴⁰ Department of Pharmacology &Physiology, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA.
⁴¹ McLaughlin Centre, University of Toronto, Toronto, Canada.

PMID:28263302
PMCID: PMC5501701
DOI: 10.1038/nn.4524

Abstract

We are performing whole-genome sequencing of families with autism spectrum disorder (ASD) to build a resource (MSSNG) for subcategorizing the phenotypes and underlying genetic factors involved. Here we report sequencing of 5,205 samples from families with ASD, accompanied by clinical information, creating a database accessible on a cloud platform and through a controlled-access internet portal. We found an average of 73.8 de novo single nucleotide variants and 12.6 de novo insertions and deletions or copy number variations per ASD subject. We identified 18 new candidate ASD-risk genes and found that participants bearing mutations in susceptibility genes had significantly lower adaptive ability (P = 6 × 10^-4). In 294 of 2,620 (11.2%) of ASD cases, a molecular basis could be determined and 7.2% of these carried copy number variations and/or chromosomal abnormalities, emphasizing the importance of detecting all forms of genetic variation as diagnostic and therapeutic targets in ASD.

PubMed Disclaimer

Conflict of interest statement

Competing Financial Interests: The authors declare no competing financial interests.

Figures

**Figure 1. Schematic of sample and data processing in MSSNG**
An executive committee oversees the project. The parameters for DNA sample selection and (genetic and phenotypic) data are managed by the committee, including consenting and ethics protocols. Coded identifiers’ for samples selected for WGS are posted as they are identified at MSSNG portal (http://mss.ng/research), so the ASD research community can monitor progress. Phenome data include subject information (identity number, year of birth, sex), family code (proband, parent, sibling), results of diagnostic tests (e.g. ADOS, ADI-R, age at diagnosis, functional assessments, intelligence tests, body measurements and dysmorphic features). The database accommodates as much of this information as is available for each sample, but that varies widely. Future plans include incorporation of fields for co-morbidities, related conditions, exposures, extended family history, interventions, and other parameters that become apparent. WGS technologies were Complete Genomics and Illumina HiSeq (2000 and X). WGS data are transferred to Google Genomics for data processing through the Google Cloud. Ref-blocked gVCFs were generated and stored in Google Cloud Storage, which were also processed forde novo mutation detection in the local cluster (for Complete Genomics data using filtering method) and Google Compute Engine (for Illumina data using DenovoGear). The Ref-blocked gVCFs and thede novo mutations were annotated through the Google Compute Engine (using Annovar), which can be accessed through the BigQuery tables. Quality controls of the genomic data were performed in the local cluster and the Google Cloud. The processed genetic data and the phenotypic data are accessible through the MSSNG Portal interface. The MSSNG database is designed to support incremental addition of data without changes in architecture, scaling to at least tens of thousands. New WGS and phenotype data are continually added to MSSNG as new batches of 1,000 samples are processed. DACO: Data access committee; UPD: Uniparental disomy; Ti/Tv: Transition to transversion ratio; IBS: Identity by state.

**Figure 2. Characteristics and quality of WGS from different sequencing platforms**
(a) Number of SNVs detected per genome. (b) Number of indels detected per genome. (c) Number of rare coding SNVs detected per genome after quality filtering. (d) Number of rare coding indels detected per genome after quality filtering. Genomes sequenced by Complete Genomics with 2.0 pipeline version are colored in orange, by Complete Genomics with 2.4 pipeline version are colored in brown, by Complete Genomics with 2.5 pipeline version are colored in green, by Illumina HiSeq 2000 are colored in blue, and by Illumina HiSeq X are colored in purple. Details of quality for individual samples can be found in Supplementary Table 1.

**Figure 3. ASD-susceptibility genes/loci**
(a) ASD-risk genes with higher than expected mutation rate from MSSNG integrated with other large-scale high-throughput sequencing projects. ASD-risk genes are ranked in descending order of the number of mutations found for each gene. Other LOF mutations, including inherited LOF mutations and LOF mutations with unknown inheritance (where parents are unavailable for testing), and CNVs found in the MSSNG cohort are indicated (except for genes found by higher than expectedde novo missense mutation rate). MSSNG data are in green and published data are in yellow. Novel putative ASD-risk genes identified in this study carry an asterisk.Δ indicate genes with druggable protein domains identified (Supplementary Table 6). (b) Pathogenic chromosomal abnormalities and CNVs identified falling into one of four categories: Chromosomal abnormalities; DECIPHER loci and other genomic disorders associated with ASD; large rare CNVs between 3–10Mb and CNVs disrupting ASD candidate genes not described above in Figure 3a. Deletions are in red, duplications are in blue and complex variants are in purple. # indicate CNVs shared between affected siblings; ‡ indicates a CNV carried by an individual with a second pathogenic CNV; † indicates a CNV shared between individuals within an extended pedigree. Details can be found in Supplementary Table 8. Examples of CNVs affecting theNRXN1 andCHD8 genes, and thePTCHD1-AS non-coding gene identified from the WGS are shown in Figure 4.

**Figure 4. CNV characterization via WGS reads in the MSSNG Portal**
(a–c) Visualization of CNVs in WGS data. (a) A heterozygous 246kb deletion of three exons ofNRXN1 at chromosome 2p16.3 in subject 2-1428-003 (average 50% decrease in sequence read-depth); (b) a 31.1kb duplication withinCHD8 at chromosome 14q11.2 in subject 2-1375-003 (average of 50% increase in sequence read-depth) and (c) 125kb deletion of exon 3 of the non-coding genePTCHD1-AS at Xp22.11 in male subject 1-0277-003 (no reads apparent, other than a small stretch of likely mis-aligned repetitive sequences). Left and right panels show the proximal and distal breakpoints of the CNVs respectively. Aligned reads viewed from the BAM files in the MSSNG browser are shown indicating the read depth. Genome co-ordinates are shown above and impacted genes below. The predicted CNVs visible from the WGS data and high-resolution microarray are shown by the red (deletion) and blue (duplication) bars. For 32 CNVs described in Figure 3b plus 17 additional CNVs, we derived a more accurate estimate of the breakpoints by visual inspection of read depth from the BAM file in the MSSNG browser. On average, the size difference between the CNV predicted by microarray data and the estimated size from WGS data was 6.9kb and for 31/49 (63%) CNVs, the size of the CNV was smaller in the microarray data than WGS. For four CNVs, the WGS-resolved breakpoints altered the exons of genes being annotated as deleted or duplicated. In another case, this resulted in a CNV from microarray no longer being classified as pathogenic as the revised breakpoints no longer included coding sequence.

**Figure 5. Phenotype comparison for the samples with and without identified mutations**
Standard score of (a) IQ Full scale and (b) Vineland Adaptive Behavior were compared between samples with pathogenic CNVs,*de novo* LOF mutations, mutations in ASD-risk genes and other samples without any of these mutations.

**Figure 6. Interaction similarity network of ASD-risk genes**
Connections represent gene similarity based on physical protein interactions and pathway interactions. Connection thickness is proportional to the fraction of interaction partners shared by the connected genes. The size of the node for each gene is proportional to the total mutation count (Figure 3). Genes associated with LOF mutations are in circle shape, while genes associated with missense mutations are in diamond shape. The node color corresponds to the BrainSpan brain expression Principal Component 1 (prenatal in yellow, postnatal in blue, balanced in light blue, undetermined in grey). The labels of novel ASD-risk genes are displayed in red. The network was visualized using Cytoscape.

See this image and copyright information in PMC

Cited by

MTSplice predicts effects of genetic variants on tissue-specific splicing.
Cheng J, Çelik MH, Kundaje A, Gagneur J.Cheng J, et al.Genome Biol. 2021 Mar 31;22(1):94. doi: 10.1186/s13059-021-02273-7.Genome Biol. 2021.PMID:33789710Free PMC article.
Identification of two novel autism genes,TRPC4 andSCFD2, in Qatar simplex families through exome sequencing.
Gupta V, Ben-Mahmoud A, Ku B, Velayutham D, Jan Z, Yousef Aden A, Kubbar A, Alshaban F, Stanton LW, Jithesh PV, Layman LC, Kim HG.Gupta V, et al.Front Psychiatry. 2023 Oct 31;14:1251884. doi: 10.3389/fpsyt.2023.1251884. eCollection 2023.Front Psychiatry. 2023.PMID:38025430Free PMC article.
The ANC-1 (Nesprin-1/2) organelle-anchoring protein functions through mitochondria to polarize axon growth in response to SLT-1.
Fischer NC, Friedman V, Martinez-Reyes MA, Hao H, Chowdhury TA, Starr DA, Quinn CC.Fischer NC, et al.PLoS Genet. 2022 Nov 21;18(11):e1010521. doi: 10.1371/journal.pgen.1010521. eCollection 2022 Nov.PLoS Genet. 2022.PMID:36409768Free PMC article.
Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders.
Iannuccelli M, Vitriolo A, Licata L, Lo Surdo P, Contino S, Cheroni C, Capocefalo D, Castagnoli L, Testa G, Cesareni G, Perfetto L.Iannuccelli M, et al.Mol Psychiatry. 2024 Jan;29(1):186-196. doi: 10.1038/s41380-023-02317-3. Epub 2023 Dec 15.Mol Psychiatry. 2024.PMID:38102483Free PMC article.
Genome Sequencing as a Diagnostic Test in Children With Unexplained Medical Complexity.
Costain G, Walker S, Marano M, Veenma D, Snell M, Curtis M, Luca S, Buera J, Arje D, Reuter MS, Thiruvahindrapuram B, Trost B, Sung WWL, Yuen RKC, Chitayat D, Mendoza-Londono R, Stavropoulos DJ, Scherer SW, Marshall CR, Cohn RD, Cohen E, Orkin J, Meyn MS, Hayeems RZ.Costain G, et al.JAMA Netw Open. 2020 Sep 1;3(9):e2018109. doi: 10.1001/jamanetworkopen.2020.18109.JAMA Netw Open. 2020.PMID:32960281Free PMC article.

See all "Cited by" articles

References

1. Lai MC, Lombardo MV, Baron-Cohen S. Autism. Lancet. 2014;383:896–910. - PubMed
1. Robinson EB, et al. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat Genet. 2016;48:552–555. - PMC - PubMed
1. Anagnostou E, et al. Autism spectrum disorder: advances in evidence-based practice. CMAJ. 2014;186:509–519. - PMC - PubMed
1. Carter MT, Scherer SW. Autism spectrum disorder in the genetics clinic: a review. Clin Genet. 2013;83:399–407. - PubMed
1. Miles JH. Complex Autism Spectrum Disorders and Cutting-Edge Molecular Diagnostic Tests. JAMA. 2015;314:879–880. - PubMed

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Related information

Grants and funding

U24 CA210004/CA/NCI NIH HHS/United States

LinkOut - more resources

Full Text Sources
Other Literature Sources
- The Lens - Patent Citations Database
- scite Smart Citations
Medical
- MedlinePlus Consumer Health Information
- MedlinePlus Health Information

Movatterモバイル変換

Account

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Full text links

Actions

Share

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder

Affiliations

Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Similar articles

Cited by

References

MeSH terms

Related information

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical