Coding and noncoding variants in EBF3 are involved in HADDS and simplex autism.
Autistic Disorder
/ epidemiology
Enhancer Elements, Genetic
/ genetics
Exome
/ genetics
Female
Gene Regulatory Networks
/ genetics
Genetic Predisposition to Disease
Humans
Male
Muscle Hypotonia
/ epidemiology
Mutation
/ genetics
Neurodevelopmental Disorders
/ epidemiology
Neurons
/ metabolism
Transcription Factors
/ genetics
Autism
De novo
EBF3
Enhancer
Gene regulatory network
Genome
Neurodevelopmental disorder
Variant
hs737
Journal
Human genomics
ISSN: 1479-7364
Titre abrégé: Hum Genomics
Pays: England
ID NLM: 101202210
Informations de publication
Date de publication:
13 07 2021
13 07 2021
Historique:
received:
03
05
2021
accepted:
17
06
2021
entrez:
14
7
2021
pubmed:
15
7
2021
medline:
5
2
2022
Statut:
epublish
Résumé
Previous research in autism and other neurodevelopmental disorders (NDDs) has indicated an important contribution of protein-coding (coding) de novo variants (DNVs) within specific genes. The role of de novo noncoding variation has been observable as a general increase in genetic burden but has yet to be resolved to individual functional elements. In this study, we assessed whole-genome sequencing data in 2671 families with autism (discovery cohort of 516 families, replication cohort of 2155 families). We focused on DNVs in enhancers with characterized in vivo activity in the brain and identified an excess of DNVs in an enhancer named hs737. We adapted the fitDNM statistical model to work in noncoding regions and tested enhancers for excess of DNVs in families with autism. We found only one enhancer (hs737) with nominal significance in the discovery (p = 0.0172), replication (p = 2.5 × 10 In this study, we identify DNVs in the hs737 enhancer in individuals with autism. Through multiple approaches, we find hs737 targets the gene EBF3 that is genome-wide significant in NDDs. By assessment of noncoding variation and the genes they affect, we are beginning to understand their impact on gene regulatory networks in NDDs.
Sections du résumé
BACKGROUND
Previous research in autism and other neurodevelopmental disorders (NDDs) has indicated an important contribution of protein-coding (coding) de novo variants (DNVs) within specific genes. The role of de novo noncoding variation has been observable as a general increase in genetic burden but has yet to be resolved to individual functional elements. In this study, we assessed whole-genome sequencing data in 2671 families with autism (discovery cohort of 516 families, replication cohort of 2155 families). We focused on DNVs in enhancers with characterized in vivo activity in the brain and identified an excess of DNVs in an enhancer named hs737.
RESULTS
We adapted the fitDNM statistical model to work in noncoding regions and tested enhancers for excess of DNVs in families with autism. We found only one enhancer (hs737) with nominal significance in the discovery (p = 0.0172), replication (p = 2.5 × 10
CONCLUSIONS
In this study, we identify DNVs in the hs737 enhancer in individuals with autism. Through multiple approaches, we find hs737 targets the gene EBF3 that is genome-wide significant in NDDs. By assessment of noncoding variation and the genes they affect, we are beginning to understand their impact on gene regulatory networks in NDDs.
Identifiants
pubmed: 34256850
doi: 10.1186/s40246-021-00342-3
pii: 10.1186/s40246-021-00342-3
pmc: PMC8278787
doi:
Substances chimiques
EBF3 protein, human
0
Transcription Factors
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
44Subventions
Organisme : NHGRI NIH HHS
ID : R01 HG003988
Pays : United States
Organisme : NHGRI NIH HHS
ID : UM1 HG008901
Pays : United States
Organisme : NHGRI NIH HHS
ID : K01 HG010498
Pays : United States
Organisme : NHGRI NIH HHS
ID : U24 HG008956
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM139774
Pays : United States
Organisme : NIMH NIH HHS
ID : R00 MH117165
Pays : United States
Informations de copyright
© 2021. The Author(s).
Références
Nature. 2012 Apr 04;485(7397):242-5
pubmed: 22495311
Genes (Basel). 2020 Jan 29;11(2):
pubmed: 32013076
Nat Genet. 2021 Aug;53(8):1125-1134
pubmed: 34312540
Nature. 2020 May;581(7809):434-443
pubmed: 32461654
Nature. 2020 May;581(7809):444-451
pubmed: 32461652
Nat Genet. 2013 Jun;45(6):580-5
pubmed: 23715323
Neuron. 2015 Sep 23;87(6):1215-1233
pubmed: 26402605
Nature. 2014 Nov 13;515(7526):209-15
pubmed: 25363760
Science. 2018 Apr 20;360(6386):327-331
pubmed: 29674594
Science. 2018 Dec 14;362(6420):
pubmed: 30545852
Nature. 2012 Apr 04;485(7397):246-50
pubmed: 22495309
Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W273-9
pubmed: 15215394
Nat Genet. 2014 Aug;46(8):881-5
pubmed: 25038753
Cancer Res. 2016 Jul 1;76(13):3719-31
pubmed: 27197156
Nat Genet. 2019 Jan;51(1):106-116
pubmed: 30559488
Cell. 2022 Sep 1;185(18):3426-3440.e19
pubmed: 36055201
Neuron. 2010 Oct 21;68(2):192-5
pubmed: 20955926
Neuron. 2011 Jun 9;70(5):863-85
pubmed: 21658581
Nat Genet. 2019 Mar;51(3):431-444
pubmed: 30804558
Am J Hum Genet. 2017 Jan 5;100(1):128-137
pubmed: 28017372
Nat Protoc. 2009;4(1):44-57
pubmed: 19131956
Am J Hum Genet. 2015 Aug 6;97(2):272-83
pubmed: 26235986
Cell Syst. 2016 Jul;3(1):95-8
pubmed: 27467249
Cell. 2017 Oct 19;171(3):710-722.e12
pubmed: 28965761
Nature. 2020 Jul;583(7818):744-751
pubmed: 32728240
Cell. 2014 Jul 17;158(2):263-276
pubmed: 24998929
Res Comput Mol Biol. 2017 May;10229:336-352
pubmed: 28691125
Curr Protoc Hum Genet. 2015 Oct 06;87:7.25.1-7.25.15
pubmed: 26439716
Cell. 2020 Mar 19;180(6):1262-1271.e15
pubmed: 32169219
Neuron. 2011 Jun 9;70(5):886-97
pubmed: 21658582
Mol Autism. 2017 Oct 5;8:54
pubmed: 29034068
Hum Mol Genet. 2011 Nov 15;20(22):4360-70
pubmed: 21865298
Am J Hum Genet. 2017 Jan 5;100(1):138-150
pubmed: 28017370
Nucleic Acids Res. 2019 Jul 2;47(W1):W127-W135
pubmed: 31114870
Nat Genet. 2017 Jul;49(7):978-985
pubmed: 28504703
Nature. 2020 Jul;583(7818):699-710
pubmed: 32728249
Nat Genet. 2011 Jun;43(6):519-25
pubmed: 21552263
Nucleic Acids Res. 2007 Jan;35(Database issue):D88-92
pubmed: 17130149
Nat Genet. 2011 Aug 14;43(9):838-46
pubmed: 21841781
Am J Hum Genet. 2016 Jan 7;98(1):58-74
pubmed: 26749308
Genome Res. 2002 Jun;12(6):996-1006
pubmed: 12045153
Nat Genet. 2011 Jun;43(6):585-9
pubmed: 21572417
Nature. 2020 Oct;586(7831):757-762
pubmed: 33057194
Nat Methods. 2012 Feb 28;9(3):215-6
pubmed: 22373907
JAMA. 2017 Sep 26;318(12):1182-1184
pubmed: 28973605
Genome Res. 2015 Jan;25(1):142-54
pubmed: 25378250
Hum Genet. 2013 Nov;132(11):1235-43
pubmed: 23793516
Am J Hum Genet. 2013 Feb 7;92(2):221-37
pubmed: 23375656
Nature. 2014 Nov 13;515(7526):216-21
pubmed: 25363768
Science. 2012 Sep 7;337(6099):1190-5
pubmed: 22955828
Neuron. 2012 Apr 26;74(2):285-99
pubmed: 22542183
Nature. 2016 Oct 27;538(7626):523-527
pubmed: 27760116
Nature. 2012 Apr 11;485(7398):376-80
pubmed: 22495300
Am J Hum Genet. 2017 Jan 5;100(1):117-127
pubmed: 28017373
Cell. 2016 Oct 6;167(2):355-368.e10
pubmed: 27693352
Science. 2015 Mar 6;347(6226):1155-9
pubmed: 25745175
Nat Genet. 2014 Oct;46(10):1063-71
pubmed: 25217958
Nature. 2009 Oct 8;461(7265):747-53
pubmed: 19812666
Cell. 2020 Aug 6;182(3):754-769.e18
pubmed: 32610082
Cell Res. 2009 Feb;19(2):271-3
pubmed: 19153597
Cell. 2017 Oct 19;171(3):557-572.e24
pubmed: 29053968
Nucleic Acids Res. 2016 Jan 4;44(D1):D726-32
pubmed: 26527727
Nature. 2012 Apr 04;485(7397):237-41
pubmed: 22495306
Bioinformatics. 2010 Mar 15;26(6):841-2
pubmed: 20110278
Am J Hum Genet. 2019 Dec 5;105(6):1274-1285
pubmed: 31785789
Cell. 2020 Feb 6;180(3):568-584.e23
pubmed: 31981491
Science. 2007 Apr 20;316(5823):445-9
pubmed: 17363630
Genome Res. 2010 Jan;20(1):110-21
pubmed: 19858363