Human Gene Module / Chromosome 5 / UIMC1

UIMC1ubiquitin interaction motif containing 1

SFARI Gene Score
2
Strong Candidate Criteria 2.1
Autism Reports / Total Reports
5 / 6
Rare Variants / Common Variants
25 / 0
Aliases
UIMC1, RAP80,  X2HRIP110
Associated Syndromes
-
Chromosome Band
5q35.2
Associated Disorders
-
Relevance to Autism

De novo missense variants and transmitted frameshift variants in the UIMC1 gene have been observed in ASD probands in multiple studies (Iossifov et al., 2014; Yuen et al., 2017; Ruzzo et al., 2019). TADA analysis of de novo and transmitted variants from iHART, the Simons Simplex Collection, the Autism Sequencing Consortium, and the Autism Genome Project in Ruzzo et al., 2019 identified UIMC1 as an ASD candidate gene with a false discovery rate (FDR) < 0.1.

Molecular Function

This gene encodes a nuclear protein that interacts with Brca1 (breast cancer 1) in a complex to recognize and repair DNA lesions. This protein binds ubiquitinated lysine 63 of histone H2A and H2AX. This protein may also function as a repressor of transcription.

External Links
Gene CardOpen Targets PlatformgnomAD browserPubMed
Human
Entrez GeneOMIMUniProtHumanBaseVariCarta
SFARI Genomic Platforms
GPF browser SFARI genome browser
Reports related to UIMC1 (6 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Primary The contribution of de novo coding mutations to autism spectrum disorder Iossifov I et al. (2014) Yes -
2 Support Prevalence and architecture of de novo mutations in developmental disorders et al. (2017) No -
3 Support Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder C Yuen RK et al. (2017) Yes -
4 Recent Recommendation Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks Ruzzo EK , et al. (2019) Yes -
5 Recent Recommendation Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders Wang T et al. (2020) Yes -
6 Support - Zhou X et al. (2022) Yes -
Rare Variants   (25)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.1045A>G p.Ile349Val missense_variant De novo - - 28135719 et al. (2017)
c.1555C>T p.Arg519Ter stop_gained Unknown - - 33004838 Wang T et al. (2020)
c.1870C>T p.Arg624Ter stop_gained Unknown - - 33004838 Wang T et al. (2020)
c.1996C>T p.Gln666Ter stop_gained Unknown - - 33004838 Wang T et al. (2020)
c.-8-20_-3del - splice_site_variant Unknown - - 33004838 Wang T et al. (2020)
c.793A>G p.Lys265Glu missense_variant De novo - - 33004838 Wang T et al. (2020)
c.1724A>G p.Tyr575Cys missense_variant De novo - - 33004838 Wang T et al. (2020)
c.132C>T p.Ser44%3D synonymous_variant De novo - - 35982159 Zhou X et al. (2022)
c.2T>C p.Met1? initiator_codon_variant Unknown - - 33004838 Wang T et al. (2020)
c.233-2A>G - splice_site_variant Familial Maternal - 33004838 Wang T et al. (2020)
c.1870C>T p.Arg624Ter stop_gained De novo - Simplex 33004838 Wang T et al. (2020)
c.1870C>T p.Arg624Ter stop_gained Familial Maternal - 33004838 Wang T et al. (2020)
c.1344_1345delinsAT p.Gln449Ter stop_gained Unknown - - 33004838 Wang T et al. (2020)
c.228_232delinsTGCAT p.Gln78Ter stop_gained Unknown - - 33004838 Wang T et al. (2020)
c.1732del p.His578MetfsTer35 frameshift_variant Unknown - - 33004838 Wang T et al. (2020)
c.61G>A p.Asp21Asn missense_variant De novo - Multiplex 28263302 C Yuen RK et al. (2017)
c.101G>A p.Arg34His missense_variant De novo - Simplex 25363768 Iossifov I et al. (2014)
c.1996C>T p.Gln666Ter stop_gained Familial Paternal Simplex 33004838 Wang T et al. (2020)
c.1891C>G p.Gln631Glu missense_variant De novo - Simplex 25363768 Iossifov I et al. (2014)
c.1288A>G p.Ser430Gly missense_variant De novo - Multiplex 31398340 Ruzzo EK , et al. (2019)
c.70del p.Thr24LeufsTer7 frameshift_variant Familial Maternal - 33004838 Wang T et al. (2020)
c.954dup p.Gly319ArgfsTer9 frameshift_variant Familial Maternal - 33004838 Wang T et al. (2020)
c.1368dup p.Asp457Ter frameshift_variant Familial Maternal Multiplex 31398340 Ruzzo EK , et al. (2019)
c.820_826del p.Val274IlefsTer12 frameshift_variant Unknown Not paternal - 33004838 Wang T et al. (2020)
c.954dup p.Gly319ArgfsTer9 frameshift_variant Familial Maternal Multiplex 31398340 Ruzzo EK , et al. (2019)
Common Variants  

No common variants reported.

SFARI Gene score
2

Strong Candidate

De novo missense variants and transmitted frameshift variants in the UIMC1 gene have been observed in ASD probands in multiple studies (Iossifov et al., 2014; Yuen et al., 2017; Ruzzo et al., 2019). TADA analysis of de novo and transmitted variants from iHART, the Simons Simplex Collection, the Autism Sequencing Consortium, and the Autism Genome Project in Ruzzo et al., 2019 identified UIMC1 as an ASD candidate gene with a false discovery rate (FDR) < 0.1.

Score Delta: Score remained at 2

criteria met
See SFARI Gene'scoring criteria
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.

4/1/2022
3
icon
2

Decreased from 3 to 2

Description

De novo missense variants and transmitted frameshift variants in the UIMC1 gene have been observed in ASD probands in multiple studies (Iossifov et al., 2014; Yuen et al., 2017; Ruzzo et al., 2019). TADA analysis of de novo and transmitted variants from iHART, the Simons Simplex Collection, the Autism Sequencing Consortium, and the Autism Genome Project in Ruzzo et al., 2019 identified UIMC1 as an ASD candidate gene with a false discovery rate (FDR) < 0.1.

10/1/2020
3
icon
3

Decreased from 3 to 3

Description

De novo missense variants and transmitted frameshift variants in the UIMC1 gene have been observed in ASD probands in multiple studies (Iossifov et al., 2014; Yuen et al., 2017; Ruzzo et al., 2019). TADA analysis of de novo and transmitted variants from iHART, the Simons Simplex Collection, the Autism Sequencing Consortium, and the Autism Genome Project in Ruzzo et al., 2019 identified UIMC1 as an ASD candidate gene with a false discovery rate (FDR) < 0.1.

Reports Added
[Prevalence and architecture of de novo mutations in developmental disorders2017] [Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders2020]
10/1/2019
4
icon
3

Decreased from 4 to 3

New Scoring Scheme
Description

De novo missense variants and transmitted frameshift variants in the UIMC1 gene have been observed in ASD probands in multiple studies (Iossifov et al., 2014; Yuen et al., 2017; Ruzzo et al., 2019). TADA analysis of de novo and transmitted variants from iHART, the Simons Simplex Collection, the Autism Sequencing Consortium, and the Autism Genome Project in Ruzzo et al., 2019 identified UIMC1 as an ASD candidate gene with a false discovery rate (FDR) < 0.1.

Reports Added
[New Scoring Scheme]
7/1/2019
icon
4

Increased from to 4

Description

De novo missense variants and transmitted frameshift variants in the UIMC1 gene have been observed in ASD probands in multiple studies (Iossifov et al., 2014; Yuen et al., 2017; Ruzzo et al., 2019). TADA analysis of de novo and transmitted variants from iHART, the Simons Simplex Collection, the Autism Sequencing Consortium, and the Autism Genome Project in Ruzzo et al., 2019 identified UIMC1 as an ASD candidate gene with a false discovery rate (FDR) < 0.1.

Krishnan Probability Score

Score 0.44747721112294

Ranking 12322/25841 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 0.032645862569223

Ranking 8970/18225 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 0.73730662252529

Ranking 1436/18665 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 -0.24611101221161

Ranking 16311/20870 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
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