Human Gene Module / Chromosome 1 / SKI


SFARI Gene Score
High Confidence Criteria 1.1
Autism Reports / Total Reports
6 / 7
Rare Variants / Common Variants
10 / 0
Limited Learn More
Associated Syndromes
Chromosome Band
Associated Disorders
Genetic Category
Rare Single Gene Mutation
Relevance to Autism

Two de novo protein-truncating variants in the SKI gene were identified in ASD probands from the Autism Sequencing Consortium (De Rubeis et al., 2014; Satterstrom et al., 2020), while additional protein-truncating variants in this gene were observed in case and control samples from the Danish iPSYCH study (Satterstrom et al., 2020). TADA analysis of de novo variants from the Simons Simplex Collection and the Autism Sequencing Consortium and protein-truncating variants from iPSYCH in Satterstrom et al., 2020 identified SKI as a candidate gene with a false discovery rate (FDR) between 0.01 and 0.05 (0.01 < FDR 0.05). A de novo missense variant in the SKI gene was also observed in an ASD proband in Yuen et al., 2017.

Molecular Function

This gene encodes the nuclear protooncogene protein homolog of avian sarcoma viral (v-ski) oncogene. It functions as a repressor of TGF-beta signaling, and may play a role in neural tube development and muscle differentiation. Heterozygous variants in this gene are associated with Shprintzen-Goldberg syndrome (OMIM 182212), a disorder comprising craniosynostosis, a marfanoid habitus, and skeletal, neurologic, cardiovascular, and connective tissue anomalies.

SFARI Genomic Platforms
Reports related to SKI (7 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Primary Synaptic, transcriptional and chromatin genes disrupted in autism De Rubeis S , et al. (2014) Yes -
2 Support Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder C Yuen RK et al. (2017) Yes -
3 Recent recommendation Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism Satterstrom FK et al. (2020) Yes -
4 Support - Hu C et al. (2022) Yes -
5 Support - Zhou X et al. (2022) Yes -
6 Support - Hu C et al. (2023) Yes -
7 Support - et al. () No -
Rare Variants   (10)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.101G>T p.Gly34Val missense_variant Unknown - - 38177409 et al. ()
c.969+5G>C - splice_site_variant De novo - - 35741772 Hu C et al. (2022)
c.1322G>C p.Arg441Pro missense_variant De novo - - 35982159 Zhou X et al. (2022)
c.1886A>C p.Glu629Ala missense_variant De novo - - 35982159 Zhou X et al. (2022)
c.1845G>T p.Glu615Asp missense_variant Familial Paternal - 37007974 Hu C et al. (2023)
c.1138C>T p.Arg380Ter stop_gained De novo - Simplex 25363760 De Rubeis S , et al. (2014)
c.1868dup p.Asn623LysfsTer206 frameshift_variant De novo - - 35982159 Zhou X et al. (2022)
c.1124G>A p.Arg375His missense_variant De novo - Multiplex 28263302 C Yuen RK et al. (2017)
c.1327_1334del p.Pro443SerfsTer42 frameshift_variant De novo - - 35982159 Zhou X et al. (2022)
c.2180_2184del p.Glu727ValfsTer100 frameshift_variant De novo - Simplex 31981491 Satterstrom FK et al. (2020)
Common Variants  

No common variants reported.

SFARI Gene score

High Confidence

Score Delta: Score remained at 1


High Confidence

See all Category 1 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.


Increased from to 1

Krishnan Probability Score

Score 0.49323051256769

Ranking 4231/25841 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: A searchable browser, with the ability to view networks of associated ASD risk genes, can be found at
ExAC Score

Score 0.98140209983332

Ranking 2094/18225 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 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: aned_exac_nonTCGA_z_pli_rec_null_data.txt
Sanders TADA Score

Score 0.50595858015774

Ranking 461/18665 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
Zhang D Score

Score 0.51754593260398

Ranking 392/20870 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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