PHF7PHD finger protein 7
Autism Reports / Total Reports
3 / 4Rare Variants / Common Variants
15 / 0Aliases
PHF7, HSPC045, HSPC226, NYD-SP6Associated Syndromes
-Chromosome Band
3p21.1Associated Disorders
DD/NDD, IDRelevance to Autism
A de novo likely gene-disruptive (LGD) variant in PHF7 was identified in an ASD proband from the Simons Simplex Collection (Iossifov et al., 2014). Single-molecular molecular inversion probe (smMIP) sequencing of 3,363 probands from cohorts with a primary diagnosis of ASD in Wang et al., 2020 identified 5 ASD-associated LGD variants and one ASD-associated missense variant with a CADD score 30 in the PHF7 gene.
Molecular Function
Spermatogenesis is a complex process regulated by extracellular and intracellular factors as well as cellular interactions among interstitial cells of the testis, Sertoli cells, and germ cells. This gene is expressed in the testis in Sertoli cells but not germ cells. The protein encoded by this gene contains plant homeodomain (PHD) finger domains, also known as leukemia associated protein (LAP) domains, believed to be involved in transcriptional regulation. The protein, which localizes to the nucleus of transfected cells, has been implicated in the transcriptional regulation of spermatogenesis.
External Links
SFARI Genomic Platforms
Reports related to PHF7 (4 Reports)
| # | Type | Title | Author, Year | Autism Report | Associated Disorders |
|---|---|---|---|---|---|
| 1 | Support | 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 | Primary | Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders | Wang T et al. (2020) | Yes | DD, ID |
| 4 | Support | - | Cirnigliaro M et al. (2023) | Yes | - |
Rare Variants (15)
| Status | Allele Change | Residue Change | Variant Type | Inheritance Pattern | Parental Transmission | Family Type | PubMed ID | Author, Year |
|---|---|---|---|---|---|---|---|---|
| c.112C>T | p.Arg38Ter | stop_gained | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.803-1G>C | - | splice_site_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.920-1G>C | - | splice_site_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.1040C>T | p.Pro347Leu | missense_variant | De novo | - | - | 28135719 | et al. (2017) | |
| c.275G>A | p.Arg92Gln | missense_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.686C>T | p.Ala229Val | missense_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.829G>A | p.Gly277Arg | missense_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.41+1G>A | - | splice_site_variant | Unknown | Not maternal | - | 33004838 | Wang T et al. (2020) | |
| c.587dup | p.Ser197IlefsTer12 | frameshift_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.1137dup | p.Ser380IlefsTer8 | frameshift_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.111_120del | p.Arg38GlyfsTer6 | frameshift_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.939_940del | p.Asp315HisfsTer11 | frameshift_variant | Unknown | - | - | 33004838 | Wang T et al. (2020) | |
| c.388del | p.Leu130PhefsTer89 | frameshift_variant | De novo | - | - | 25363768 | Iossifov I et al. (2014) | |
| c.356dup | p.His120ProfsTer23 | frameshift_variant | Familial | Maternal | - | 33004838 | Wang T et al. (2020) | |
| c.112C>T | p.Arg38Ter | stop_gained | Familial | Maternal | Multiplex | 37506195 | Cirnigliaro M et al. (2023) |
Common Variants
No common variants reported.
SFARI Gene score
2
Strong Candidate
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
Krishnan Probability Score
Score 0.49114975384063
Ranking 5756/25841 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 0.064913882316604
Ranking 8290/18225 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 0.33754027421519
Ranking 211/18665 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 -0.52955341150098
Ranking 19480/20870 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.