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Whole-genome sequencing in an autism multiplex family
BACKGROUND: Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental disorders that affect 1 in 88 children in the US. Previous exome sequencing studies on family trios have implicated a role for rare, de-novo mutations in the pathogenesis of autism. METHODS: To examine the...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642023/ https://www.ncbi.nlm.nih.gov/pubmed/23597238 http://dx.doi.org/10.1186/2040-2392-4-8 |
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author | Shi, Lingling Zhang, Xu Golhar, Ryan Otieno, Frederick G He, Mingze Hou, Cuiping Kim, Cecilia Keating, Brendan Lyon, Gholson J Wang, Kai Hakonarson, Hakon |
author_facet | Shi, Lingling Zhang, Xu Golhar, Ryan Otieno, Frederick G He, Mingze Hou, Cuiping Kim, Cecilia Keating, Brendan Lyon, Gholson J Wang, Kai Hakonarson, Hakon |
author_sort | Shi, Lingling |
collection | PubMed |
description | BACKGROUND: Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental disorders that affect 1 in 88 children in the US. Previous exome sequencing studies on family trios have implicated a role for rare, de-novo mutations in the pathogenesis of autism. METHODS: To examine the utility of whole-genome sequencing to identify inherited disease candidate variants and genes, we sequenced two probands from a large pedigree, including two parents and eight children. We evaluated multiple analytical strategies to identify a prioritized list of candidate genes. RESULTS: By assuming a recessive model of inheritance, we identified seven candidate genes shared by the two probands. We also evaluated a different analytical strategy that does not require the assumption of disease model, and identified a list of 59 candidate variants that may increase susceptibility to autism. Manual examination of this list identified ANK3 as the most likely candidate gene. Finally, we identified 33 prioritized non-coding variants such as those near SMG6 and COQ5, based on evolutionary constraint and experimental evidence from ENCODE. Although we were unable to confirm rigorously whether any of these genes indeed contribute to the disease, our analysis provides a prioritized shortlist for further validation studies. CONCLUSIONS: Our study represents one of the first whole-genome sequencing studies in autism leveraging a large family-based pedigree. These results provide for a discussion on the relative merits of finding de-novo mutations in sporadic cases versus finding inherited mutations in large pedigrees, in the context of neuropsychiatric and neurodevelopmental diseases. |
format | Online Article Text |
id | pubmed-3642023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36420232013-05-03 Whole-genome sequencing in an autism multiplex family Shi, Lingling Zhang, Xu Golhar, Ryan Otieno, Frederick G He, Mingze Hou, Cuiping Kim, Cecilia Keating, Brendan Lyon, Gholson J Wang, Kai Hakonarson, Hakon Mol Autism Research BACKGROUND: Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental disorders that affect 1 in 88 children in the US. Previous exome sequencing studies on family trios have implicated a role for rare, de-novo mutations in the pathogenesis of autism. METHODS: To examine the utility of whole-genome sequencing to identify inherited disease candidate variants and genes, we sequenced two probands from a large pedigree, including two parents and eight children. We evaluated multiple analytical strategies to identify a prioritized list of candidate genes. RESULTS: By assuming a recessive model of inheritance, we identified seven candidate genes shared by the two probands. We also evaluated a different analytical strategy that does not require the assumption of disease model, and identified a list of 59 candidate variants that may increase susceptibility to autism. Manual examination of this list identified ANK3 as the most likely candidate gene. Finally, we identified 33 prioritized non-coding variants such as those near SMG6 and COQ5, based on evolutionary constraint and experimental evidence from ENCODE. Although we were unable to confirm rigorously whether any of these genes indeed contribute to the disease, our analysis provides a prioritized shortlist for further validation studies. CONCLUSIONS: Our study represents one of the first whole-genome sequencing studies in autism leveraging a large family-based pedigree. These results provide for a discussion on the relative merits of finding de-novo mutations in sporadic cases versus finding inherited mutations in large pedigrees, in the context of neuropsychiatric and neurodevelopmental diseases. BioMed Central 2013-04-18 /pmc/articles/PMC3642023/ /pubmed/23597238 http://dx.doi.org/10.1186/2040-2392-4-8 Text en Copyright © 2013 Shi et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Shi, Lingling Zhang, Xu Golhar, Ryan Otieno, Frederick G He, Mingze Hou, Cuiping Kim, Cecilia Keating, Brendan Lyon, Gholson J Wang, Kai Hakonarson, Hakon Whole-genome sequencing in an autism multiplex family |
title | Whole-genome sequencing in an autism multiplex family |
title_full | Whole-genome sequencing in an autism multiplex family |
title_fullStr | Whole-genome sequencing in an autism multiplex family |
title_full_unstemmed | Whole-genome sequencing in an autism multiplex family |
title_short | Whole-genome sequencing in an autism multiplex family |
title_sort | whole-genome sequencing in an autism multiplex family |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3642023/ https://www.ncbi.nlm.nih.gov/pubmed/23597238 http://dx.doi.org/10.1186/2040-2392-4-8 |
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