Comparison of predicted and actual consequences of missense mutations.
Each person's genome sequence has thousands of missense variants. Practical interpretation of their functional significance must rely on computational inferences in the absence of exhaustive experimental measurements. Here we analyzed the efficacy of these inferences in 33 de novo missense mutations revealed by sequencing in first-generation progeny of N-ethyl-N-nitrosourea-treated mice, involving 23 essential immune system genes. PolyPhen2, SIFT, MutationAssessor, Panther, CADD, and Condel were used to predict each mutation's functional importance, whereas the actual effect was measured by breeding and testing homozygotes for the expected in vivo loss-of-function phenotype. Only 20% of mutations predicted to be deleterious by PolyPhen2 (and 15% by CADD) showed a discernible phenotype in individual homozygotes. Half of all possible missense mutations in the same 23 immune genes were predicted to be deleterious, and most of these appear to become subject to purifying selection because few persist between separate mouse substrains, rodents, or primates. Because defects in immune genes could be phenotypically masked in vivo by compensation and environment, we compared inferences by the same tools with the in vitro phenotype of all 2,314 possible missense variants in TP53; 42% of mutations predicted by PolyPhen2 to be deleterious (and 45% by CADD) had little measurable consequence for TP53-promoted transcription. We conclude that for de novo or low-frequency missense mutations found by genome sequencing, half those inferred as deleterious correspond to nearly neutral mutations that have little impact on the clinical phenotype of individual cases but will nevertheless become subject to purifying selection.
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Lisa A
LA
Miosge
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Matthew A
MA
Field
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Yovina
Y
Sontani
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia; Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Vicky
V
Cho
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia; Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Simon
S
Johnson
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia; Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Anna
A
Palkova
Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Bhavani
B
Balakishnan
Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Rong
R
Liang
Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Yafei
Y
Zhang
Center for Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390;
Stephen
S
Lyon
Center for Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390;
Bruce
B
Beutler
Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Belinda
B
Whittle
Australian Phenomics Facility, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Edward M
EM
Bertram
Ramaciotti Immunisation Genomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia;
Anselm
A
Enders
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia; Immunogenomics Laboratory, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia c.goodnow@garvan.org.au dan.andrews@anu.edu.au.
Christopher C
CC
Goodnow
Immunogenomics Laboratory, John Curtin School of Medical Research, Australian National University, Canberra City, ACT 2601, Australia; c.goodnow@garvan.org.au dan.andrews@anu.edu.au.
T Daniel
TD
Andrews
D000818:Animals; D003062:Codon; D019295:Computational Biology; D003198:Computer Simulation; D059472:Exome; D014644:Genetic Variation; D016678:Genome; D015894:Genome, Human; D005838:Genotype; D006801:Humans; D007107:Immune System; D007153:Immunologic Deficiency Syndromes / Q000235:genetics; D051379:Mice; D008810:Mice, Inbred C57BL; D008957:Models, Genetic; D020125:Mutation, Missense; D009369:Neoplasms / Q000235:genetics; D010641:Phenotype; D012984:Software; D016159:Tumor Suppressor Protein p53 / Q000235:genetics
D003062:Codon; C495901:TP53 protein, human; D016159:Tumor Suppressor Protein p53
cancer; de novo mutation; evolution; immunodeficiency; nearly neutral