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Chapter 10
MUTANT MOUSE: Biosimulator
for the Functional Annotation of Gene
and Genome Networks
bona fide
Yoichi Gondo
RIKEN Genomic Sciences Center, Functional Genomics Research Group, Population and
Quantitative Genomics Team, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045,
Japan, gondo@gsc.riken.jp
Abstract. The advancements of genomics and genome projects led to the current paradigm
that the blueprint of life is depicted in the genome sequences. To decipher the life system,
deductive methods have been applied from genome sequences to genes, transcripts, proteins,
organelles, cells, tissues, organs, organisms, and populations. As a result we encountered an
astronomical scale of complicated molecular and cellular networks in the life system. There is
a way, however, to directly connect the function of a single base pair (bp) in genome
sequences to the life system by bypassing all the molecular and cellular labyrinths.
“MUTANT” provides the ultimate tool as a bona fide biosimulator for the functional annota-
tion of gene and genome networks. Genetics, with mutations and mutants, is revealing the life
system. Mendel deduced the concept of “gene” from a large dataset of the pea phenome. Snell
discovered the mouse H2 locus by graft rejection that led to the identification and understand-
ing of the major histocompatibility complex. Many other mouse mutants (i.e., nu , scid , lpr , gld ,
Sl , and W) provided model systems for the functional characterization of key genes in immu-
nological networks. In this context, “reverse genetics” methods have been developed since the
1980s to systematically produce mutant mice carrying a particular gene of interest, for exam-
ple, transgenic mice, knockout mice, and gene targeting. Recently, more versatile, large-scale,
and high-throughput methods such as ENU mutagenesis and insertional mutagenesis are being
used to generate mutant mice. This chapter offers a review of the history and current status of
mouse mutagenesis and discusses the value of mouse model systems.
10.1 Introduction
Theoretical modeling and computer simulation are two powerful tools to elucidate
the mechanism of complex systems. Testable modeling, parameter setting, and em-
pirical input of initial parameter values are some of the key requirements for simula-
tion. The efficacy of simulations is finally evaluated by how closely the simulation
output reflects the complex system. The calculation power of computer hardware is
another key factor that determines whether the results are obtained within a reason-
able period of time.
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