Human Gene Module / Chromosome 6 / SENP6

SENP6SUMO specific peptidase 6

SFARI Gene Score
3
Suggestive Evidence Criteria 3.1
Autism Reports / Total Reports
4 / 4
Rare Variants / Common Variants
3 / 0
Aliases
-
Associated Syndromes
-
Chromosome Band
6q14.1
Associated Disorders
-
Relevance to Autism

Li et al., 2023 determined that a de novo splice-region variant in the SENP6 gene originally identified in an ASD proband from the Autism Sequencing Consortium in Satterstrom et al., 2020 was a non-canonical splicing variant; subsequent functional analysis by minigene splicing assays demonstrated that this variant resulted in skipping of exon 18. Additional de novo variants in the SENP6 gene, including a de novo frameshift variant, have been identified in ASD probands (Zhou et al., 2022; Trost et al., 2022).

Molecular Function

Ubiquitin-like molecules (UBLs), such as SUMO1, are structurally related to ubiquitin and can be ligated to target proteins in a similar manner as ubiquitin. However, covalent attachment of UBLs does not result in degradation of the modified proteins. SUMO1 modification is implicated in the targeting of RANGAP1 to the nuclear pore complex, as well as in stabilization of I-kappa-B-alpha (NFKBIA) from degradation by the 26S proteasome. Like ubiquitin, UBLs are synthesized as precursor proteins, with 1 or more amino acids following the C-terminal glycine-glycine residues of the mature UBL protein. Thus, the tail sequences of the UBL precursors need to be removed by UBL-specific proteases, such as SENP6, prior to their conjugation to target proteins. SENPs also display isopeptidase activity for deconjugation of SUMO-conjugated substrates

External Links
Gene CardOpen Targets PlatformgnomAD browserPubMed
Human
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SFARI Genomic Platforms
GPF browser SFARI genome browser
Reports related to SENP6 (4 Reports)
# Type Title Author, Year Autism Report Associated Disorders
1 Support Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism Satterstrom FK et al. (2020) Yes -
2 Support - Zhou X et al. (2022) Yes -
3 Support - Trost B et al. (2022) Yes -
4 Primary - Kuokuo Li et al. (2024) Yes -
Rare Variants   (3)
Status Allele Change Residue Change Variant Type Inheritance Pattern Parental Transmission Family Type PubMed ID Author, Year
c.1896G>A p.Gln632= synonymous_variant De novo - - 35982159 Zhou X et al. (2022)
c.2196-3C>A - splice_region_variant De novo - - 31981491 Satterstrom FK et al. (2020)
c.605del p.Lys202ArgfsTer27 frameshift_variant De novo - - 36368308 Trost B et al. (2022)
Common Variants  

No common variants reported.

SFARI Gene score
3

Suggestive Evidence

Score Delta: Score remained at 3

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.

4/1/2024
icon
3

Increased from to 3

Krishnan Probability Score

Score 0.49169553478504

Ranking 5219/25841 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 0.99987682159665

Ranking 712/18225 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 0.94263831747867

Ranking 15382/18665 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 0.25722287821323

Ranking 3375/20870 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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