TNRC6Ctrinucleotide repeat containing adaptor 6C
Autism Reports / Total Reports
6 / 6Rare Variants / Common Variants
16 / 0Aliases
-Associated Syndromes
-Chromosome Band
17q25.3Associated Disorders
-Relevance to Autism
A de novo coding-synonymous variant in the TNRC6C gene was identified in an ASD proband from the Simons Simplex Collection in Iossifov et al., 2014; functional assessment of this variant by a high throughput Massively Parallel Splicing Assay (MaPSY) in Rhine et al., 2022 demonstrated that this variant disrupted splicing, and this functional effect was further validated by RT-PCR. Additional rare de novo non-coding variation in this gene has also been observed in ASD probands (Yuen et al., 2017; Turner et al., 2017).
Molecular Function
Predicted to enable RNA binding activity. Involved in gene silencing by miRNA; positive regulation of nuclear-transcribed mRNA catabolic process, deadenylation-dependent decay; and positive regulation of nuclear-transcribed mRNA poly(A) tail shortening. Predicted to be located in cytosol. Predicted to be active in P-body and nucleoplasm.
External Links
SFARI Genomic Platforms
Reports related to TNRC6C (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 | Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder | C Yuen RK et al. (2017) | Yes | - |
| 3 | Support | Genomic Patterns of De Novo Mutation in Simplex Autism | Turner TN et al. (2017) | Yes | - |
| 4 | Recent Recommendation | - | Rhine CL et al. (2022) | Yes | - |
| 5 | Support | - | Woodbury-Smith M et al. (2022) | Yes | - |
| 6 | Support | - | Zhou X et al. (2022) | Yes | - |
Rare Variants (16)
| Status | Allele Change | Residue Change | Variant Type | Inheritance Pattern | Parental Transmission | Family Type | PubMed ID | Author, Year |
|---|---|---|---|---|---|---|---|---|
| c.3696G>C | p.Met1232Ile | missense_variant | De novo | - | - | 35982159 | Zhou X et al. (2022) | |
| c.2386+5722G>C | - | intron_variant | De novo | - | Simplex | 28263302 | C Yuen RK et al. (2017) | |
| c.-218-4369A>G | - | intron_variant | De novo | - | Simplex | 28965761 | Turner TN et al. (2017) | |
| c.2386+1730C>A | - | intron_variant | De novo | - | Simplex | 28965761 | Turner TN et al. (2017) | |
| c.2387-3933A>C | - | intron_variant | De novo | - | Simplex | 28965761 | Turner TN et al. (2017) | |
| c.3148C>T | p.Leu1050%3D | synonymous_variant | De novo | - | - | 35982159 | Zhou X et al. (2022) | |
| c.3793+514C>T | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.4610-600G>A | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.-218-2389G>A | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.-546+3970del | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.-546+8930A>G | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.2386+5064A>G | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.2386+5085A>G | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.3469-1629del | - | intron_variant | De novo | - | Multiplex | 28263302 | C Yuen RK et al. (2017) | |
| c.1121C>A | p.Thr374Asn | missense_variant | Unknown | - | - | 35205252 | Woodbury-Smith M et al. (2022) | |
| c.2850G>A | p.Pro950= | synonymous_variant | De novo | - | Simplex | 25363768 | Iossifov I et al. (2014) |
Common Variants
No common variants reported.
SFARI Gene score
2
Strong Candidate
Functional assessment of ASD-associated variant
Score Delta: Score remained at 2
criteria met
See SFARI Gene'scoring criteriaWe 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
2
Increased from to 2
Description
Functional assessment of ASD-associated variant
Krishnan Probability Score
Score 0.4923975293856
Ranking 4553/25841 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 0.99999782398435
Ranking 350/18225 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
Sanders TADA Score
Score 0.94646245735066
Ranking 16880/18665 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 0.546168355426
Ranking 259/20870 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.