Genotyping Mice Cancer Models
Analysis of the genomic DNA constitution for an organism is called genotyping. The official reference sequence for the mouse genome from the C57BL/6J strain can be used as a comparison to the model mice or the diseased tissue samples. Sequencing information on other strains is being generated as well. Large scale projects to identify SNPs and CNVs have provided additional crucial information. Genotyping can also be performed on any control animals and their modified counterparts for comparison. Primary or secondary metastatic tumors can also be evaluated, and can prove to be rather disparate. The specific technique used to assess the genotype will vary by tissue, experimental design or available technology. The complexities of chromosomal instability in cancer situations require special attention for analytical techniques. For example, loss of heterozygosity (LOH) has been implicated in many cancers. Tissue and tumor heterogeneity, or mixtures of different cells types and stages, can be a factor in analysis. Improvements in genotyping methods and software over time will increase the rate, quality, and volume of these processes. Described below are some established methods. Some of these methods will be applied together to obtain complementary data about the genomic sequences under investigation.
Complex chromosomal rearrangements and aberrations have long been studied as a mechanism or as a consequence of cancer, and cytological examination of chromosome structure by employing cytogenetics was an important and early diagnostic for genomic changes. This method of analysis has been especially common in myeloproliferative cancers such leukemias. More recently the technique of fluorescence in situ hybridization (FISH) to identify duplications, deletions, or rearrangements has been used for chromosomal structural analyses. Multiplex or multi-fluor FISH with multiple probes and spectral karyotyping (SKY) strategies are increasingly refining these types of studies and improving detection of aberrations. These techniques may be complementary to microarray or resequencing strategies to identify duplications or deletions of genomic regions.
Array-based hybridization platforms, now with significant history and literature in cancer research, generally use nucleotide sequences tethered to a platform, to which experimental sequences are applied, and the presence or absence of nucleotides or segments in the experimental situation can be determined. These tools allow simultaneous genotyping of many single-nucleotide polymorphisms (SNPs) for the detection of
small nucleotide variations between samples. In the case of comparative genomic hybridization (CGH) larger segment analysis can also be performed to evaluate structural variation in the genome, including copy-number variation (CNV) situations. Among these platforms, whole-genome sampling analysis has been used to genotype large human cohorts to conduct genome-wide association studies for a variety of human diseases. These studies have been highly successful at identifying loci associated with certain diseases.
Initial microarray-based genotyping platforms were limited to a few thousand markers. To overcome these limitations and to enable the potential for genome-wide association studies (GWAS) in the mouse, there are now high-density arrays. Mouse diversity arrays may capture the genetic diversity present in classical and wild-derived inbred strains. Classical inbred strains are most often used, and have contributed disproportionately to the genotypes stored in databases. Increasingly high-throughput tools will increase the diversity of information obtained from mouse strains and a wealth of data is becoming available from comparative analyses.
As technologies for rapid and large-scale genomic sequencing continue to progress (sometimes referred to as next-generation sequencing), increasingly there will be efforts to fully sequence normal and tumor samples as a means to identify mutations and to understand the mechanisms and pathologies of cancer. These strategies can be of use for genetically modified mouse models or for xenograft situations. Sometimes the choice is made to sequence only exons of genes (exome sequencing) for rapid analysis and cost savings. It is also possible to focus on certain pathways for sequencing analysis. These strategies are easily applied to mouse model cancer analysis as well.
A variety of other techniques may be used for determining genomic content of cells. Many types of PCR strategies, fragment length polymorphism analysis, and other methods are performed in some laboratory settings. The amount of sequence to be studied, the locally available equipment and tools, and the volume of the analysis to be performed will determine the choice of the appropriate method. Additionally, new strategies are being developed continually to improve the sensitivity and speed of these investigations.
Once genotyping data is obtained, it will need to be processed, analyzed, and compared with other data sets to draw conclusions. Although many bioinformatics resources with a focus on cancer will emphasize human genomics and human cancer (such as The Cancer Genome Atlas TCGA and the International Cancer Genome Consortium ICGC project) and may assist in the explorations of comparisons with model animals, many of them will also provide data for other species. Array-based hybridization data can be searched via the GEO and ArrayExpress repositories, which will offer links to relevant research publications and array providers. Other resources may be more focused on mouse tumor biology specifically, such as the Mouse Tumor Biology Database (MTB). Sequence repositories like the NCBIâ??s Sequence Read Archive are storing data from large-scale sequencing projects, with links to submitting labs and literature that can guide researchers to useful techniques and technologies. The CaBIGÂ® project of the NCI is also providing extensive protocols and informatics tools support with cross-species utility. Explore many resources associated with CaBIGÂ® to find resources such as CaArray, CaGWAS, geWorkbench for integrated genomics strategies, and tools for managing samples such as caTissue Suite.