Human Gene Module / Chromosome 6 / RANBP9

RANBP9RAN binding protein 9

SFARI Gene Score
3
Suggestive Evidence Criteria 3.1
Autism Reports / Total Reports
6 / 7
Rare Variants / Common Variants
6 / 0
Aliases
-
Associated Syndromes
-
Chromosome Band
6p23
Associated Disorders
-
Relevance to Autism

Whole-exome sequencing of 115 ASD trios from three countries with a high frequency of consanguineous populations (Pakistan, Iran, and Saudi Arabia) in Harripaul et al., 2026 identified a homozygous missense variant in the RANBP9 gene (NM_005493.3:c.1735G>C;p.Gly579Arg) in a female ASD proband from Pakistan. De novo variants in this gene, including a de novo loss-of-function variant, have been previously identified in ASD probands from the Simons Simplex Collection, the SPARK cohort, the Autism Sequencing Consortium, and a Japanese ASD cohort (Iossifov et al., 2014; Lim et al., 2017; Takata et al., 2018; Zhou et al., 2022; Fu et al., 2022). RANBP9 has been shown to interact with the ASD candidate gene MET and enhance HGF-MET signaling by recruiting Sos and activating the Ras pathway (Wang et al., 2022).

Molecular Function

his gene encodes a protein that binds RAN, a small GTP binding protein belonging to the RAS superfamily that is essential for the translocation of RNA and proteins through the nuclear pore complex. The protein encoded by this gene has also been shown to interact with several other proteins, including met proto-oncogene, homeodomain interacting protein kinase 2, androgen receptor, and cyclin-dependent kinase 11.

External Links
Gene CardOpen Targets PlatformgnomAD browserPubMed
Human
Entrez GeneOMIMUniProtHumanBaseVariCarta
SFARI Genomic Platforms
GPF browser SFARI genome browser
Reports related to RANBP9 (7 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Support - Wang D , et al. (2002) No -
2 Support The contribution of de novo coding mutations to autism spectrum disorder Iossifov I et al. (2014) Yes -
3 Support Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder Lim ET , et al. (2017) Yes -
4 Support Integrative Analyses of De Novo Mutations Provide Deeper Biological Insights into Autism Spectrum Disorder Takata A , et al. (2018) Yes -
5 Support - Zhou X et al. (2022) Yes -
6 Support - Fu JM et al. (2022) Yes -
7 Primary - Harripaul, Ricardo et al. (2026) Yes -
Rare Variants   (6)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.1967C>T p.Ala656Val missense_variant De novo - - 28714951 Lim ET , et al. (2017)
c.2059+2T>C p.? splice_site_variant De novo - Simplex 35982160 Fu JM et al. (2022)
c.540C>G p.Leu180= synonymous_variant De novo - Multiplex 35982159 Zhou X et al. (2022)
c.1967C>T p.Ala656Val missense_variant De novo - Simplex 29346770 Takata A , et al. (2018)
c.417C>T p.Ala139= synonymous_variant De novo - Simplex 25363768 Iossifov I et al. (2014)
c.1735G>C p.Gly579Arg missense_variant Familial Both parents Simplex 41865132 Harripaul, Ricardo et al. (2026)
Common Variants  

No common variants reported.

SFARI Gene score
3

Suggestive Evidence

criteria met
See SFARI Gene'scoring criteria
3

Suggestive Evidence

See all Category 3 Genes

The literature is replete with relatively small studies of candidate genes, using either common or rare variant approaches, which do not reach the criteria set out for categories 1 and 2. Genes that had two such lines of supporting evidence were placed in category 3, and those with one line of evidence were placed in category 4. Some additional lines of "accessory evidence" (indicated as "acc" in the score cards) could also boost a gene from category 4 to 3.

4/1/2026
3

Initial score established: 3

Krishnan Probability Score

Score 0.56932591270403

Ranking 1046/25841 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.
Original Source
ExAC Score

Score 0.99995849555959

Ranking 570/18225 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
Original Source
Sanders TADA Score

Score 0.93326326632702

Ranking 12218/18665 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).
Original Source
Zhang D Score

Score -0.01296812288372

Ranking 9089/20870 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.
Original Source
Submit New Gene

Report an Error