proposed trait‐associated variant is introduced into the germline of the organism and the resulting offspring are examined for evidence of the abnormal phenotype. With knockout models, the action of the gene in question is eliminated and the offspring are examined for evidence of an abnormal phenotype. Similar experiments can be performed in cultured cells, where the introduction of the variant (or gene knockout) is easier. However, finding the appropriate cell line and determining the appropriate cellular phenotype corresponding to the trait may be difficult. Recent advances in generating relevant cellular models have utilized inducible pluripotent stem cell (iPSC) technology, by which cells (blood, fibroblast) from an individual with a phenotype and genotype of interest can be reprogrammed and differentiated to a cell type of interest (such as neuron or retinal pigment epithelium). Such cells might be closer to the affected tissue type and have more recognizable phenotypes due to the genetic variant under study. A further advance incorporates gene editing technology (e.g. CRISPR/Cas9) into the approach, whereby an established iPSC line can be edited to introduce (or correct) a variant of interest. Such an approach eliminates the need to draw a sample from a person known to carry a variant of interest and allows examination of isogenic cell lines with and without the variant for phenotypic changes. These approaches are rapidly evolving, and frequently revised sources, such as Current Protocols in Human Genetics, should be consulted for the latest details on functional studies using these approaches.
Keys to a Successful Study
Foster Interaction of Necessary Expertise
To appropriately carry out any disease gene discovery study, one must use techniques from five different areas of expertise (Figure 1.3). These areas are clinical evaluation, molecular genetics, statistical genetics, bioinformatics, and epidemiology. The first provides the necessary diagnostic and participant recruitment skills needed to define the phenotype and help collect samples and data. The second provides genotyping, sequencing, and functional analysis skills necessary to help locate and identify the genes and variants of interest and evaluate their functional consequences. The third provides the statistical and analytical framework for the proper design of the study and the analysis of the generated data. The fourth provides computational and algorithmic expertise for the processing, storage, and dissemination of large‐scale datasets. And the fifth provides expertise to incorporate environmental variables and apply results at the population level.
The initial focus of gene discovery on single‐gene disorders resulted in a linear approach (Figure 1.1) that could be implemented by a single investigator with expertise in one of these areas, with periodic consultation with colleagues from other disciplines as needed. Complex traits require a multidisciplinary approach that is not easily implemented by a single investigator, and given differences in genetic architecture, available samples, and research questions, different approaches (and thus different teams) may need to be formed for each trait. Thus, experts in each of these fields must be intimately involved in all aspects of the study. Even with all this expertise in place, it is essential that the study not be divided into separate components with little interaction. For example, statistical geneticists and epidemiologists should be involved in the discussion of the clinical phenotype to determine the effect of potential changes to the phenotype definition on the genetic study design, screening approach, and statistical power.
Figure 1.3 Components of a complex disease study and expertise needed to contribute.
Develop Careful Study Design
It may seem self‐evident that a careful study design is necessary for a successful study. However, it is not enough to decide on a general design of “collect cases and controls, genotype on a genome‐wide chip, do GWAS analysis.” Each step in the study requires substantial thought, and the decisions made at one step will have implications for each of the others. Much as a team of engineers and architects must project unintended side effects from a change in a structural design, lest a catastrophic failure ensue, researchers must consider carefully all aspects of the experimental design lest they doom themselves to making inappropriate conclusions based on inadequately obtained and interpreted results.
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