Optimizing screening and mating strategies for phenotype-driven recessive N-ethyl-N-nitrosourea screens in mice

Ivana Barbaric, T. Neil Dear

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Phenotype-driven N-ethyl-N-nitrosourea (ENU) mutagenesis screens in the mouse are being used to elucidate gene function and develop disease models. Many of the earlier screens focused on identifying dominant mutations, whereas many newer mutagenesis programs have arisen that focus on identifying recessive mutations. Recessive screens require more complex breeding and phenotyping procedures, yet little information is available on the optimal breeding and phenotyping strategies for identifying recessive mutations. Optimization involves minimizing the numbers of mice that must be bred and subjected to phenotypic screens while maximizing the number of mutant phenotypes that can be identified. Analysis of expected frequencies of mutants has been used to determine which of the typically used mating and screening strategies will produce the best returns in terms of identifying recessive phenotypes. As a general guideline, to minimize the number of mice to be screened, the optimal strategy is to mate a single generation 2 (G2) female and G 1 male and screen either 11 or 17 G3 offspring to obtain at least 1 or 2 homozygous mutants, respectively. When the expense of producing and housing the mice is the greatest cost factor and the phenotype is so robust that a single outlier will suffice, then the optimal strategy is to mate 2 G2 sisters with the G1 male parent and screen a single litter from each. Intercrossing of G2 brothers and sisters is not an efficient method for maximizing returns from ENU screens.

Original languageEnglish
Pages (from-to)44-49
Number of pages6
JournalJournal of the American Association for Laboratory Animal Science
Volume46
Issue number6
Publication statusPublished or Issued - Nov 2007
Externally publishedYes

ASJC Scopus subject areas

  • Animal Science and Zoology

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