Human Gene Module / Chromosome 1 / SPEN

SPENspenfamily transcriptional repressor

Score
2
Strong Candidate Criteria 2.1
Autism Reports / Total Reports
4 / 7
Rare Variants / Common Variants
9 / 0
Aliases
SPEN, HIAA0929,  MINT,  RBM15C,  SHARP
Associated Syndromes
-
Genetic Category
Rare Single Gene Mutation
Chromosome Band
1p36.21-p36.13
Associated Disorders
ASD
Relevance to Autism

De novo likely gene-disruptive (LGD) variants in the SPEN gene have been identified in two probands with ASD (Iossifov et al., 2014; Yuen et al., 2016) and two probands with unspecified developmental disorders (Deciphering Developmental Disorders Study 2017). An integrated meta-analysis of de novo mutation data from a combined dataset of 10,927 individuals with neurodevelopmental disorders identified SPEN as a gene with an excess of LGD variants (false discovery rata < 5%, count >1) (Coe et al., 2018). De novo missense variants in SPEN have also been observed in ASD probands (De Rubeis et al., 2014; Iossifov et al., 2014; Krumm et al., 2015).

Molecular Function

his gene encodes a hormone inducible transcriptional repressor. Repression of transcription by this gene product can occur through interactions with other repressors, by the recruitment of proteins involved in histone deacetylation, or through sequestration of transcriptional activators. The product of this gene contains a carboxy-terminal domain that permits binding to other corepressor proteins. This domain also permits interaction with members of the NuRD complex, a nucleosome remodeling protein complex that contains deacetylase activity. In addition, this repressor contains several RNA recognition motifs that confer binding to a steroid receptor RNA coactivator; this binding can modulate the activity of both liganded and nonliganded steroid receptors.

Reports related to SPEN (7 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Support Synaptic, transcriptional and chromatin genes disrupted in autism. De Rubeis S , et al. (2014) Yes -
2 Primary The contribution of de novo coding mutations to autism spectrum disorder. Iossifov I , et al. (2014) Yes -
3 Support Excess of rare, inherited truncating mutations in autism. Krumm N , et al. (2015) Yes -
4 Support Genome-wide characteristics of de novo mutations in autism. Yuen RK , et al. (2016) Yes -
5 Support Prevalence and architecture of de novo mutations in developmental disorders. Deciphering Developmental Disorders Study (2017) No -
6 Recent Recommendation Neurodevelopmental disease genes implicated by de novo mutation and copy number variation morbidity. Coe BP , et al. (2018) No -
7 Support Lessons Learned from Large-Scale, First-Tier Clinical Exome Sequencing in a Highly Consanguineous Population. Monies D , et al. (2019) No Autistic features
Rare Variants   (9)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.5392C>T p.Gln1798Ter stop_gained De novo - Simplex 27525107 Yuen RK , et al. (2016)
c.986A>C p.Asp329Ala missense_variant De novo - - 25363760 De Rubeis S , et al. (2014)
c.4651G>A p.Glu1551Lys missense_variant De novo - Simplex 25961944 Krumm N , et al. (2015)
c.4054G>A p.Asp1352Asn missense_variant Unknown - Unknown 31130284 Monies D , et al. (2019)
c.8492G>C p.Ser2831Thr missense_variant De novo - Simplex 25363768 Iossifov I , et al. (2014)
c.7503G>A p.Trp2501Ter stop_gained De novo - - 28135719 Deciphering Developmental Disorders Study (2017)
c.461G>A p.Arg154Gln missense_variant De novo - - 28135719 Deciphering Developmental Disorders Study (2017)
c.3028_3029insA p.Asp1011GlyfsTer11 frameshift_variant De novo - Simplex 25363768 Iossifov I , et al. (2014)
c.6958_6962del p.Lys2320GlyfsTer37 frameshift_variant De novo - - 28135719 Deciphering Developmental Disorders Study (2017)
Common Variants  

No common variants reported.

SFARI Gene score
2

Strong Candidate

De novo likely gene-disruptive (LGD) variants in the SPEN gene have been identified in two probands with ASD (Iossifov et al., 2014; Yuen et al., 2016) and two probands with unspecified developmental disorders (Deciphering Developmental Disorders Study 2017). An integrated meta-analysis of de novo mutation data from a combined dataset of 10,927 individuals with neurodevelopmental disorders identified SPEN as a gene with an excess of LGD variants (false discovery rata < 5%, count >1) (Coe et al., 2018). De novo missense variants in SPEN have also been observed in ASD probands (De Rubeis et al., 2014; Iossifov et al., 2014; Krumm et al., 2015).

Score Delta: Score remained at 3

2

Strong Candidate

See all Category 2 Genes

We considered a rigorous statistical comparison between cases and controls, yielding genome-wide statistical significance, with independent replication, to be the strongest possible evidence for a gene. These criteria were relaxed slightly for category 2.

7/1/2019
3
icon
3

Score remained at 3

Description

De novo likely gene-disruptive (LGD) variants in the SPEN gene have been identified in two probands with ASD (Iossifov et al., 2014; Yuen et al., 2016) and two probands with unspecified developmental disorders (Deciphering Developmental Disorders Study 2017). An integrated meta-analysis of de novo mutation data from a combined dataset of 10,927 individuals with neurodevelopmental disorders identified SPEN as a gene with an excess of LGD variants (false discovery rata < 5%, count >1) (Coe et al., 2018). De novo missense variants in SPEN have also been observed in ASD probands (De Rubeis et al., 2014; Iossifov et al., 2014; Krumm et al., 2015).

1/1/2019
icon
3

Increased from to 3

Description

De novo likely gene-disruptive (LGD) variants in the SPEN gene have been identified in two probands with ASD (Iossifov et al., 2014; Yuen et al., 2016) and two probands with unspecified developmental disorders (Deciphering Developmental Disorders Study 2017). An integrated meta-analysis of de novo mutation data from a combined dataset of 10,927 individuals with neurodevelopmental disorders identified SPEN as a gene with an excess of LGD variants (false discovery rata < 5%, count >1) (Coe et al., 2018). De novo missense variants in SPEN have also been observed in ASD probands (De Rubeis et al., 2014; Iossifov et al., 2014; Krumm et al., 2015).

Krishnan Probability Score

Score 0.6124481364197

Ranking 170/25841 scored genes


[Show Scoring Methodology]
Krishnan and colleagues generated probability scores genome-wide by using a machine learning approach on a human brain-specific gene network. The method was first presented in Nat Neurosci 19, 1454-1462 (2016), and scores for more than 25,000 RefSeq genes can be accessed in column G of supplementary table 3 (see: http://www.nature.com/neuro/journal/v19/n11/extref/nn.4353-S5.xlsx). A searchable browser, with the ability to view networks of associated ASD risk genes, can be found at asd.princeton.edu.
ExAC Score

Score 0.99999999999996

Ranking 22/18225 scored genes


[Show Scoring Methodology]
The Exome Aggregation Consortium (ExAC) is a summary database of 60,706 exomes that has been widely used to estimate 'constraint' on mutation for individual genes. It was introduced by Lek et al. Nature 536, 285-291 (2016), and the ExAC browser can be found at exac.broadinstitute.org. The pLI score was developed as measure of intolerance to loss-of- function mutation. A pLI > 0.9 is generally viewed as highly constrained, and thus any loss-of- function mutations in autism in such a gene would be more likely to confer risk. For a full list of pLI scores see: ftp://ftp.broadinstitute.org/pub/ExAC_release/release0.3.1/functional_gene_constraint/fordist_cle aned_exac_nonTCGA_z_pli_rec_null_data.txt
Iossifov Probability Score

Score 0.93

Ranking 110/239 scored genes


[Show Scoring Methodology]
Supplementary dataset S2 in the paper by Iossifov et al. (PNAS 112, E5600-E5607 (2015)) lists 239 genes with a probability of at least 0.8 of being associated with autism risk (column I). This probability metric combines the evidence from de novo likely-gene- disrupting and missense mutations and assesses it against the background mutation rate in unaffected individuals from the University of Washington’s Exome Variant Sequence database (evs.gs.washington.edu/EVS/). The list of probability scores can be found here: www.pnas.org/lookup/suppl/doi:10.1073/pnas.1516376112/- /DCSupplemental/pnas.1516376112.sd02.xlsx
Sanders TADA Score

Score 0.58853014493696

Ranking 672/18665 scored genes


[Show Scoring Methodology]
The TADA score ('Transmission and De novo Association') was introduced by He et al. PLoS Genet 9(8):e1003671 (2013), and is a statistic that integrates evidence from both de novo and transmitted mutations. It forms the basis for the claim of 65 individual genes being strongly associated with autism risk at a false discovery rate of 0.1 (Sanders et al. Neuron 87, 1215-1233 (2015)). The calculated TADA score for 18,665 RefSeq genes can be found in column P of Supplementary Table 6 in the Sanders et al. paper (the column headed 'tadaFdrAscSscExomeSscAgpSmallDel'), which represents a combined analysis of exome data and small de novo deletions (see www.cell.com/cms/attachment/2038545319/2052606711/mmc7.xlsx).
Zhang D Score

Score 0.31851542272344

Ranking 2464/20870 scored genes


[Show Scoring Methodology]
The DAMAGES score (disease-associated mutation analysis using gene expression signatures), or D score, was developed to combine evidence from de novo loss-of- function mutation with evidence from cell-type- specific gene expression in the mouse brain (specifically translational profiles of 24 specific mouse CNS cell types isolated from 6 different brain regions). Genes with positive D scores are more likely to be associated with autism risk, with higher-confidence genes having higher D scores. This statistic was first presented by Zhang & Shen (Hum Mutat 38, 204- 215 (2017), and D scores for more than 20,000 RefSeq genes can be found in column M in supplementary table 2 from that paper.
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