Literature DB >> 34076780

Whole-genome sequencing identifies functional noncoding variation in SEMA3C that cosegregates with dyslexia in a multigenerational family.

Amaia Carrion-Castillo1,2, Sara B Estruch1, Ben Maassen3,4, Barbara Franke5,6, Clyde Francks1,6, Simon E Fisher7,8.   

Abstract

Dyslexia is a common heritable developmental disorder involving impaired reading abilities. Its genetic underpinnings are thought to be complex and heterogeneous, involving common and rare genetic variation. Multigenerational families segregating apparent monogenic forms of language-related disorders can provide useful entrypoints into biological pathways. In the present study, we performed a genome-wide linkage scan in a three-generational family in which dyslexia affects 14 of its 30 members and seems to be transmitted with an autosomal dominant pattern of inheritance. We identified a locus on chromosome 7q21.11 which cosegregated with dyslexia status, with the exception of two cases of phenocopy (LOD = 2.83). Whole-genome sequencing of key individuals enabled the assessment of coding and noncoding variation in the family. Two rare single-nucleotide variants (rs144517871 and rs143835534) within the first intron of the SEMA3C gene cosegregated with the 7q21.11 risk haplotype. In silico characterization of these two variants predicted effects on gene regulation, which we functionally validated for rs144517871 in human cell lines using luciferase reporter assays. SEMA3C encodes a secreted protein that acts as a guidance cue in several processes, including cortical neuronal migration and cellular polarization. We hypothesize that these intronic variants could have a cis-regulatory effect on SEMA3C expression, making a contribution to dyslexia susceptibility in this family.

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Year:  2021        PMID: 34076780     DOI: 10.1007/s00439-021-02289-w

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


  78 in total

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Authors:  M Bahlo; C J Bromhead
Journal:  Bioinformatics       Date:  2009-05-12       Impact factor: 6.937

2.  Exact trait-model-free tests for linkage detection in pedigrees.

Authors:  S Basu; Y Di; E A Thompson
Journal:  Ann Hum Genet       Date:  2008-05-28       Impact factor: 1.670

3.  CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.

Authors:  Alexej Abyzov; Alexander E Urban; Michael Snyder; Mark Gerstein
Journal:  Genome Res       Date:  2011-02-07       Impact factor: 9.043

Review 4.  Exome sequencing as a tool for Mendelian disease gene discovery.

Authors:  Michael J Bamshad; Sarah B Ng; Abigail W Bigham; Holly K Tabor; Mary J Emond; Deborah A Nickerson; Jay Shendure
Journal:  Nat Rev Genet       Date:  2011-09-27       Impact factor: 53.242

5.  Evaluation of results from genome-wide studies of language and reading in a novel independent dataset.

Authors:  A Carrion-Castillo; E van Bergen; A Vino; T van Zuijen; P F de Jong; C Francks; S E Fisher
Journal:  Genes Brain Behav       Date:  2016-07       Impact factor: 3.449

Review 6.  The interface between genetics and psychology: lessons from developmental dyslexia.

Authors:  D V M Bishop
Journal:  Proc Biol Sci       Date:  2015-05-07       Impact factor: 5.349

Review 7.  Molecular genetics of dyslexia: an overview.

Authors:  Amaia Carrion-Castillo; Barbara Franke; Simon E Fisher
Journal:  Dyslexia       Date:  2013-11

8.  Semaphorin-3A guides radial migration of cortical neurons during development.

Authors:  Gang Chen; Jian Sima; Ming Jin; Kai-Yu Wang; Xiao-Jing Xue; Wang Zheng; Yu-Qiang Ding; Xiao-Bing Yuan
Journal:  Nat Neurosci       Date:  2007-12-02       Impact factor: 24.884

9.  Annotation of functional variation in personal genomes using RegulomeDB.

Authors:  Alan P Boyle; Eurie L Hong; Manoj Hariharan; Yong Cheng; Marc A Schaub; Maya Kasowski; Konrad J Karczewski; Julie Park; Benjamin C Hitz; Shuai Weng; J Michael Cherry; Michael Snyder
Journal:  Genome Res       Date:  2012-09       Impact factor: 9.043

10.  The UK Biobank resource with deep phenotyping and genomic data.

Authors:  Clare Bycroft; Colin Freeman; Desislava Petkova; Gavin Band; Lloyd T Elliott; Kevin Sharp; Allan Motyer; Damjan Vukcevic; Olivier Delaneau; Jared O'Connell; Adrian Cortes; Samantha Welsh; Alan Young; Mark Effingham; Gil McVean; Stephen Leslie; Naomi Allen; Peter Donnelly; Jonathan Marchini
Journal:  Nature       Date:  2018-10-10       Impact factor: 49.962

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