Cargando…

ENU-induced phenovariance in mice: inferences from 587 mutations

BACKGROUND: We present a compendium of N-ethyl-N-nitrosourea (ENU)-induced mouse mutations, identified in our laboratory over a period of 10 years either on the basis of phenotype or whole genome and/or whole exome sequencing, and archived in the Mutagenetix database. Our purpose is threefold: 1) to...

Descripción completa

Detalles Bibliográficos
Autores principales: Arnold, Carrie N, Barnes, Michael J, Berger, Michael, Blasius, Amanda L, Brandl, Katharina, Croker, Ben, Crozat, Karine, Du, Xin, Eidenschenk, Celine, Georgel, Philippe, Hoebe, Kasper, Huang, Hua, Jiang, Zhengfan, Krebs, Philippe, La Vine, Diantha, Li, Xiaohong, Lyon, Stephen, Moresco, Eva Marie Y, Murray, Anne R, Popkin, Daniel L, Rutschmann, Sophie, Siggs, Owen M, Smart, Nora G, Sun, Lei, Tabeta, Koichi, Webster, Victoria, Tomisato, Wataru, Won, Sungyong, Xia, Yu, Xiao, Nengming, Beutler, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3532239/
https://www.ncbi.nlm.nih.gov/pubmed/23095377
http://dx.doi.org/10.1186/1756-0500-5-577
_version_ 1782254280235810816
author Arnold, Carrie N
Barnes, Michael J
Berger, Michael
Blasius, Amanda L
Brandl, Katharina
Croker, Ben
Crozat, Karine
Du, Xin
Eidenschenk, Celine
Georgel, Philippe
Hoebe, Kasper
Huang, Hua
Jiang, Zhengfan
Krebs, Philippe
La Vine, Diantha
Li, Xiaohong
Lyon, Stephen
Moresco, Eva Marie Y
Murray, Anne R
Popkin, Daniel L
Rutschmann, Sophie
Siggs, Owen M
Smart, Nora G
Sun, Lei
Tabeta, Koichi
Webster, Victoria
Tomisato, Wataru
Won, Sungyong
Xia, Yu
Xiao, Nengming
Beutler, Bruce
author_facet Arnold, Carrie N
Barnes, Michael J
Berger, Michael
Blasius, Amanda L
Brandl, Katharina
Croker, Ben
Crozat, Karine
Du, Xin
Eidenschenk, Celine
Georgel, Philippe
Hoebe, Kasper
Huang, Hua
Jiang, Zhengfan
Krebs, Philippe
La Vine, Diantha
Li, Xiaohong
Lyon, Stephen
Moresco, Eva Marie Y
Murray, Anne R
Popkin, Daniel L
Rutschmann, Sophie
Siggs, Owen M
Smart, Nora G
Sun, Lei
Tabeta, Koichi
Webster, Victoria
Tomisato, Wataru
Won, Sungyong
Xia, Yu
Xiao, Nengming
Beutler, Bruce
author_sort Arnold, Carrie N
collection PubMed
description BACKGROUND: We present a compendium of N-ethyl-N-nitrosourea (ENU)-induced mouse mutations, identified in our laboratory over a period of 10 years either on the basis of phenotype or whole genome and/or whole exome sequencing, and archived in the Mutagenetix database. Our purpose is threefold: 1) to formally describe many point mutations, including those that were not previously disclosed in peer-reviewed publications; 2) to assess the characteristics of these mutations; and 3) to estimate the likelihood that a missense mutation induced by ENU will create a detectable phenotype. FINDINGS: In the context of an ENU mutagenesis program for C57BL/6J mice, a total of 185 phenotypes were tracked to mutations in 129 genes. In addition, 402 incidental mutations were identified and predicted to affect 390 genes. As previously reported, ENU shows strand asymmetry in its induction of mutations, particularly favoring T to A rather than A to T in the sense strand of coding regions and splice junctions. Some amino acid substitutions are far more likely to be damaging than others, and some are far more likely to be observed. Indeed, from among a total of 494 non-synonymous coding mutations, ENU was observed to create only 114 of the 182 possible amino acid substitutions that single base changes can achieve. Based on differences in overt null allele frequencies observed in phenotypic vs. non-phenotypic mutation sets, we infer that ENU-induced missense mutations create detectable phenotype only about 1 in 4.7 times. While the remaining mutations may not be functionally neutral, they are, on average, beneath the limits of detection of the phenotypic assays we applied. CONCLUSIONS: Collectively, these mutations add to our understanding of the chemical specificity of ENU, the types of amino acid substitutions it creates, and its efficiency in causing phenovariance. Our data support the validity of computational algorithms for the prediction of damage caused by amino acid substitutions, and may lead to refined predictions as to whether specific amino acid changes are responsible for observed phenotypes. These data form the basis for closer in silico estimations of the number of genes mutated to a state of phenovariance by ENU within a population of G3 mice.
format Online
Article
Text
id pubmed-3532239
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-35322392013-01-03 ENU-induced phenovariance in mice: inferences from 587 mutations Arnold, Carrie N Barnes, Michael J Berger, Michael Blasius, Amanda L Brandl, Katharina Croker, Ben Crozat, Karine Du, Xin Eidenschenk, Celine Georgel, Philippe Hoebe, Kasper Huang, Hua Jiang, Zhengfan Krebs, Philippe La Vine, Diantha Li, Xiaohong Lyon, Stephen Moresco, Eva Marie Y Murray, Anne R Popkin, Daniel L Rutschmann, Sophie Siggs, Owen M Smart, Nora G Sun, Lei Tabeta, Koichi Webster, Victoria Tomisato, Wataru Won, Sungyong Xia, Yu Xiao, Nengming Beutler, Bruce BMC Res Notes Data Note BACKGROUND: We present a compendium of N-ethyl-N-nitrosourea (ENU)-induced mouse mutations, identified in our laboratory over a period of 10 years either on the basis of phenotype or whole genome and/or whole exome sequencing, and archived in the Mutagenetix database. Our purpose is threefold: 1) to formally describe many point mutations, including those that were not previously disclosed in peer-reviewed publications; 2) to assess the characteristics of these mutations; and 3) to estimate the likelihood that a missense mutation induced by ENU will create a detectable phenotype. FINDINGS: In the context of an ENU mutagenesis program for C57BL/6J mice, a total of 185 phenotypes were tracked to mutations in 129 genes. In addition, 402 incidental mutations were identified and predicted to affect 390 genes. As previously reported, ENU shows strand asymmetry in its induction of mutations, particularly favoring T to A rather than A to T in the sense strand of coding regions and splice junctions. Some amino acid substitutions are far more likely to be damaging than others, and some are far more likely to be observed. Indeed, from among a total of 494 non-synonymous coding mutations, ENU was observed to create only 114 of the 182 possible amino acid substitutions that single base changes can achieve. Based on differences in overt null allele frequencies observed in phenotypic vs. non-phenotypic mutation sets, we infer that ENU-induced missense mutations create detectable phenotype only about 1 in 4.7 times. While the remaining mutations may not be functionally neutral, they are, on average, beneath the limits of detection of the phenotypic assays we applied. CONCLUSIONS: Collectively, these mutations add to our understanding of the chemical specificity of ENU, the types of amino acid substitutions it creates, and its efficiency in causing phenovariance. Our data support the validity of computational algorithms for the prediction of damage caused by amino acid substitutions, and may lead to refined predictions as to whether specific amino acid changes are responsible for observed phenotypes. These data form the basis for closer in silico estimations of the number of genes mutated to a state of phenovariance by ENU within a population of G3 mice. BioMed Central 2012-10-24 /pmc/articles/PMC3532239/ /pubmed/23095377 http://dx.doi.org/10.1186/1756-0500-5-577 Text en Copyright ©2012 Arnold et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Data Note
Arnold, Carrie N
Barnes, Michael J
Berger, Michael
Blasius, Amanda L
Brandl, Katharina
Croker, Ben
Crozat, Karine
Du, Xin
Eidenschenk, Celine
Georgel, Philippe
Hoebe, Kasper
Huang, Hua
Jiang, Zhengfan
Krebs, Philippe
La Vine, Diantha
Li, Xiaohong
Lyon, Stephen
Moresco, Eva Marie Y
Murray, Anne R
Popkin, Daniel L
Rutschmann, Sophie
Siggs, Owen M
Smart, Nora G
Sun, Lei
Tabeta, Koichi
Webster, Victoria
Tomisato, Wataru
Won, Sungyong
Xia, Yu
Xiao, Nengming
Beutler, Bruce
ENU-induced phenovariance in mice: inferences from 587 mutations
title ENU-induced phenovariance in mice: inferences from 587 mutations
title_full ENU-induced phenovariance in mice: inferences from 587 mutations
title_fullStr ENU-induced phenovariance in mice: inferences from 587 mutations
title_full_unstemmed ENU-induced phenovariance in mice: inferences from 587 mutations
title_short ENU-induced phenovariance in mice: inferences from 587 mutations
title_sort enu-induced phenovariance in mice: inferences from 587 mutations
topic Data Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3532239/
https://www.ncbi.nlm.nih.gov/pubmed/23095377
http://dx.doi.org/10.1186/1756-0500-5-577
work_keys_str_mv AT arnoldcarrien enuinducedphenovarianceinmiceinferencesfrom587mutations
AT barnesmichaelj enuinducedphenovarianceinmiceinferencesfrom587mutations
AT bergermichael enuinducedphenovarianceinmiceinferencesfrom587mutations
AT blasiusamandal enuinducedphenovarianceinmiceinferencesfrom587mutations
AT brandlkatharina enuinducedphenovarianceinmiceinferencesfrom587mutations
AT crokerben enuinducedphenovarianceinmiceinferencesfrom587mutations
AT crozatkarine enuinducedphenovarianceinmiceinferencesfrom587mutations
AT duxin enuinducedphenovarianceinmiceinferencesfrom587mutations
AT eidenschenkceline enuinducedphenovarianceinmiceinferencesfrom587mutations
AT georgelphilippe enuinducedphenovarianceinmiceinferencesfrom587mutations
AT hoebekasper enuinducedphenovarianceinmiceinferencesfrom587mutations
AT huanghua enuinducedphenovarianceinmiceinferencesfrom587mutations
AT jiangzhengfan enuinducedphenovarianceinmiceinferencesfrom587mutations
AT krebsphilippe enuinducedphenovarianceinmiceinferencesfrom587mutations
AT lavinediantha enuinducedphenovarianceinmiceinferencesfrom587mutations
AT lixiaohong enuinducedphenovarianceinmiceinferencesfrom587mutations
AT lyonstephen enuinducedphenovarianceinmiceinferencesfrom587mutations
AT morescoevamariey enuinducedphenovarianceinmiceinferencesfrom587mutations
AT murrayanner enuinducedphenovarianceinmiceinferencesfrom587mutations
AT popkindaniell enuinducedphenovarianceinmiceinferencesfrom587mutations
AT rutschmannsophie enuinducedphenovarianceinmiceinferencesfrom587mutations
AT siggsowenm enuinducedphenovarianceinmiceinferencesfrom587mutations
AT smartnorag enuinducedphenovarianceinmiceinferencesfrom587mutations
AT sunlei enuinducedphenovarianceinmiceinferencesfrom587mutations
AT tabetakoichi enuinducedphenovarianceinmiceinferencesfrom587mutations
AT webstervictoria enuinducedphenovarianceinmiceinferencesfrom587mutations
AT tomisatowataru enuinducedphenovarianceinmiceinferencesfrom587mutations
AT wonsungyong enuinducedphenovarianceinmiceinferencesfrom587mutations
AT xiayu enuinducedphenovarianceinmiceinferencesfrom587mutations
AT xiaonengming enuinducedphenovarianceinmiceinferencesfrom587mutations
AT beutlerbruce enuinducedphenovarianceinmiceinferencesfrom587mutations