Nowadays sequencing is getting more affordable and commonplace for genetic screening and scientific research, but it uncovers genes with unknown function and many mutations with unknown functional effect. Research of rare human diseases using model organisms is important, because patients suffering from diseases caused by genetic defects need to find out what’s causing their disease and how it can be treated. A review article in Genetics by Wangler et. al gives examples of how model organisms are being used to discover the cause of diseases and the function of genes. The authors also show how scientists are putting human genes and gene variants in model organisms, particularly the fruit fly, Drosophila, and zebrafish, and also describe new efforts and organizations that bring scientists and clinicians together to help diagnose rare undiagnosed diseases of patients.
Genetic research using model organisms is important, because many diseases have a genetic origin. Research of genes with conserved sequence or function in model organisms reveals similarities between proteins and disease pathways which are not obvious. Even when the phenotypes between species are different, often the molecular pathways or mechanisms are the same. (Wangler 2017) For example, the study of development of the Drosophila wing identified genetic machinery which causes skeletal and craniofacial defects in humans. As shown by pathogenic variants of genes in the Wnt pathway catalogued in Mendelian Inheritance in Man database (www.omim.org), these mutations cause disease in humans, specifically Robinow Syndrome. There are many evolutionarily conserved genes which are involved in important biological processes. Homologous genes which are essential in Drosophila and have more than one homologue in humans are eight times more likely to be associated with Mendelian disease. (Wangler 2017, Yamamoto 2014) This demonstrates that research in model organisms has a predictive power, because genes associated with disease are identified and prioritized for further research.
Figure 2 shows the workflow of the collaboration of The Undiagnosed Disease Network (UDN) and the Model Organism Screening Center. First patients apply at the UDN website (UDN Gateway) hosted by the Undiagnosed Diseases Network coordinating center. This organization has 7 clinical sites in the US. Then after they are accepted, they have sequencing done at their two sequencing cores and sometimes metabolomics at their Metabolomics core. If they can’t figure out the disease by combining genotype and phenotype, the patient’s gene/variant information and a description of their condition is sent to the Model Organism Screening Center (MOSC). First the MOSC does a MARRVEL (Model Organism Aggregated Resources for Rare Variant ExpLoration) search of human and model organism online databases at www.marrvel.org. They search for other patients who have similar gene variants. Then when a candidate gene variant is prioritized, it is studied in the Drosophila and zebrafish core. Study of genetic variants in the genome is complicated, and gene variants involved in disease need to be functionally evaluated in vivo in a model organism so that clinicians can correctly identify the problem and understand why it is happening.
Whole exome sequencing (WES) is used as a diagnostic tool to find mutations in the exons, or parts of genes coding for proteins. There are 180,000 exons which total about 30 million basepairs or 1% of the genome. (Ng et. al 2009 Nature) The DNA in these sections are transcribed to mRNA, and the mRNA is later translated into protein. The paper describes an example of a young child patient of the UDN whose mutation was identified by the UDN by whole exome sequencing, and then whose data was shared with other genomic scientists using the online GeneMatcher tool (genematcher.org) and emphasizes the importance of the prescreening step.
But what about the noncoding DNA, found outside the exons, within the genes in introns, and outside the genes, that makes up the other 99% of the human genome? Next generation sequencing of the whole genome shows all these other sequences too, but there is a lot more information to analyze. Whole genome sequencing (WGS) has resulted in the discovery that there are even RNA’s produced from enhancer regions and the act of transcription there may be important. Noncoding regulatory regions, such as enhancers, silencers, or promoters can also cause disease when mutated, but it depends on the mutation. Single nucleotide polymorphisms (SNP’s) identified by GWAS (genome-wide association studies) are often in noncoding regions, and through systematic genomic studies such as this one, (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651703/), the authors identified and linked regulatory variants to human cancers.
As stated in the paper, teamwork is paramount for helping the patient. The work of scientists who research model organisms is vital for understanding how the disease is caused, and the work of clinicians directly helps the patient when they are provided with the information. The patients are identifying their own symptoms and trying to figure out what disease they have, and it is through teamwork of all these groups (scientists, clinicians, and patients) that diseases can be cured.
References
Wangler, M. F., Yamamoto, S., Chao, H.-T., Posey, J. E., Westerfield, M., Postlethwait, J., … Bellen. (2017). Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research. Genetics, 207(1), 9–27. http://doi.org/10.1534/genetics.117.203067
Yamamoto, S., Jaiswal, M., Charng, W.-L., Gambin, T., Karaca, E., Mirzaa, G., … Bellen, H. J. (2014). A Drosophila genetic resource of mutants to study mechanisms underlying human genetic diseases. Cell, 159(1), 200–214. http://doi.org/10.1016/j.cell.2014.09.002
Ng, S. B., Turner, E. H., Robertson, P. D., Flygare, S. D., Bigham, A. W., Lee, C., … Shendure, J. (2009). Targeted capture and massively parallel sequencing of 12 human exomes. Nature, 461(7261), 272–276. JOUR. Retrieved from http://dx.doi.org/10.1038/nature08250
Liu, S., Liu, Y., Zhang, Q., Wu, J., Liang, J., Yu, S., … Wang, X. (2017). Systematic identification of regulatory variants associated with cancer risk. Genome Biology, 18(1), 194. article. http://doi.org/10.1186/s13059-017-1322-z