Generating mouse models for biomedical research


Early mouse genetics research relied on mice having visible physical defects and readily measurable phenotypes, such as those caused by random spontaneous or induced mutations This ‘forward genetics’ approach depends on the presence of a phenotype to guide the search for the underlying genetic mutation. With the advent of techniques that enabled molecular cloning and the use of recombinant DNA to efficiently manipulate mouse genomes, researchers no longer needed to search for a relevant phenotype. Instead, they could engineer a pre-determined specific mutation into the mouse genome in real time in pluripotent mouse embryonic stem (ES) cells this ‘reverse genetics’ approach enabled scientists to study the phenotypic consequences of a known specific genetic mutation. This approach can generate ‘knockout’ mice by genetically manipulating the genome of ES cells, and then injecting the targeted cells into morulae or blastocysts which are then implanted into pseudopregnant female mice. The resulting chimeric embryos develop into offspring that bear the desired gene deletion. After backcrossing to test for germline transmission of the knockout allele and subsequent intercrossing to achieve homozygosity, the phenotypic consequences of the mutation can be assessed. Phenotypes can also be assessed in transgenic mice which are generated by introducing an exogenous gene via microinjection into the one-cell-stage zygote. When successful, these genetic manipulations can also undergo germline transmission to the next generation.

With the sequencing of the mouse and human genomes attention soon turned to determining the function of protein-coding genes. A growing number further motivated efforts to functionally annotate every human gene and to determine the genetic basis of rare, simple and common complex human diseases using mouse models. Mouse models are thus vitally important for elucidating gene function. Those that express the pathophysiology of human disease are an essential resource for understanding disease mechanisms, improving diagnostic strategies and for testing therapeutic interventions. Even mouse models that only partially recapitulate the human phenotype, such as mutations in individual paralogs, can still provide important insights into disease mechanisms. In this At a Glance article, we review recent technological advances for generating new and improved mouse models for biomedical research. This article aims to update a previous poster published in this journal several years ago. This earlier article discussed the role of natural variation, random transgenesis, reverse genetics via ES-cell-derived knockouts, forward genetics via ethylnitrosurea (ENU)-induced chemical mutagenesis, and genetic manipulation using transposons in the generation of mouse models. Many technological advances have since emerged, leading to refinements and improvements in the generation of more precise mouse models. These new technologies overcome some of the limitations of earlier mouse models by adding specificity, reproducibility and efficiency to the generation of alleles that can expand our knowledge of disease pathogenesis. For example, the ability to generate mouse models that recapitulate the single-nucleotide variants (SNVs) found in humans will enable us to differentiate between disease-causing and disease-associated mechanisms.

In the poster accompanying this article, we feature four areas of advancement:

(1) Conditional mutagenesis strategies in mouse ES cells;

(2) Gene function knockdown using RNA interference (RNAi);

These technologies represent a new paradigm in our ability to manipulate the mouse genome. However, as we discuss, these approaches are not without limitations. For example, the success of conditional mutagenesis can be hampered by poor gene-targeting efficiency in ES cells and by the limited production of germline-competent chimeras that can transmit the mutant allele to subsequent generations in their germline. Furthermore, protein expression can be highly variable following mRNA knockdown by RNAi, which can make experimental reproducibility a challenge. The major limitations of programmable endonucleases, the latest genome-editing tools, is mosaicism and their potential, albeit addressable, problem of inducing off-target mutations. Nonetheless, such pitfalls do not detract from the versatility that these newer technologies afford for manipulating the mouse genome.

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