Abstract
Computational inference of mutation effects is necessary for genetic studies in which many mutations must be considered as etiologic candidates. Programs such as PolyPhen-2 predict the relative severity of damage caused by missense mutations, but not the actual probability that a mutation will reduce/eliminate protein function. Based on genotype and phenotype data for 116,330 ENU-induced mutations in the Mutagenetix database, we calculate that putative null mutations, and PolyPhen-2-classified "probably damaging", "possibly damaging", or "probably benign" mutations have, respectively, 61%, 17%, 9.8%, and 4.5% probabilities of causing phenotypically detectable damage in the homozygous state. We use these probabilities in the estimation of genome saturation and the probability that individual proteins have been adequately tested for function in specific genetic screens. We estimate the proportion of essential autosomal genes in Mus musculus (C57BL/6J) and show that viable mutations in essential genes are more likely to induce phenotype than mutations in non-essential genes.
| Original language | English (US) |
|---|---|
| Article number | 441 |
| Journal | Nature Communications |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 1 2018 |
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ASJC Scopus subject areas
- Chemistry(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Physics and Astronomy(all)
Cite this
Probability of phenotypically detectable protein damage by ENU-induced mutations in the Mutagenetix database. / Wang, Tao; Bu, Chun Hui; Hildebrand, Sara; Jia, Gaoxiang; Siggs, Owen M.; Lyon, Stephen; Pratt, David; Scott, Lindsay; Russell, Jamie; Ludwig, Sara; Murray, Anne R.; Moresco, Eva Marie Y.; Beutler, Bruce.
In: Nature Communications, Vol. 9, No. 1, 441, 01.12.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Probability of phenotypically detectable protein damage by ENU-induced mutations in the Mutagenetix database
AU - Wang, Tao
AU - Bu, Chun Hui
AU - Hildebrand, Sara
AU - Jia, Gaoxiang
AU - Siggs, Owen M.
AU - Lyon, Stephen
AU - Pratt, David
AU - Scott, Lindsay
AU - Russell, Jamie
AU - Ludwig, Sara
AU - Murray, Anne R.
AU - Moresco, Eva Marie Y.
AU - Beutler, Bruce
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Computational inference of mutation effects is necessary for genetic studies in which many mutations must be considered as etiologic candidates. Programs such as PolyPhen-2 predict the relative severity of damage caused by missense mutations, but not the actual probability that a mutation will reduce/eliminate protein function. Based on genotype and phenotype data for 116,330 ENU-induced mutations in the Mutagenetix database, we calculate that putative null mutations, and PolyPhen-2-classified "probably damaging", "possibly damaging", or "probably benign" mutations have, respectively, 61%, 17%, 9.8%, and 4.5% probabilities of causing phenotypically detectable damage in the homozygous state. We use these probabilities in the estimation of genome saturation and the probability that individual proteins have been adequately tested for function in specific genetic screens. We estimate the proportion of essential autosomal genes in Mus musculus (C57BL/6J) and show that viable mutations in essential genes are more likely to induce phenotype than mutations in non-essential genes.
AB - Computational inference of mutation effects is necessary for genetic studies in which many mutations must be considered as etiologic candidates. Programs such as PolyPhen-2 predict the relative severity of damage caused by missense mutations, but not the actual probability that a mutation will reduce/eliminate protein function. Based on genotype and phenotype data for 116,330 ENU-induced mutations in the Mutagenetix database, we calculate that putative null mutations, and PolyPhen-2-classified "probably damaging", "possibly damaging", or "probably benign" mutations have, respectively, 61%, 17%, 9.8%, and 4.5% probabilities of causing phenotypically detectable damage in the homozygous state. We use these probabilities in the estimation of genome saturation and the probability that individual proteins have been adequately tested for function in specific genetic screens. We estimate the proportion of essential autosomal genes in Mus musculus (C57BL/6J) and show that viable mutations in essential genes are more likely to induce phenotype than mutations in non-essential genes.
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UR - http://www.scopus.com/inward/citedby.url?scp=85041325943&partnerID=8YFLogxK
U2 - 10.1038/s41467-017-02806-4
DO - 10.1038/s41467-017-02806-4
M3 - Article
VL - 9
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
IS - 1
M1 - 441
ER -