Genome sequencing (GS) has proven to be revolutionary in the diagnosis of Genetics and Rare Genetic Diseases. Despite the ability of GS to identify most non-coding variation, determining which non-coding variants are disease-causing is challenging. To tackle this issue, RNA sequencing (RNA-seq) has emerged as a valuable tool, providing valuable insights and support in identifying disease-causing non-coding variants.
DNA-based tests, like genome sequencing, capture a snapshot of a person’s genetic code. RNA sequencing provides a different way of looking at the genes, by looking at how DNA is being translated and utilized to produce proteins in our body. A combine RNA-seq and whole genome sequencing approach provides distinct advantages in the diagnosis of genetic and rare diseases.
Let’s explore each aspect:
a. Genetic Variation Identification: DNA sequences contain the genetic information of an individual, and analyzing them can help identify variations or mutations in specific genes associated with certain diseases. This is especially important for rare diseases, which are often caused by specific genetic alterations.
b. Inherited Disease Detection: Many genetic diseases are inherited from parents, and by DNA sequencing, clinicians can identify potential risk factors or carriers of such diseases in families. This allows for early detection and intervention.
c. Precision Medicine: Understanding the patient’s DNA sequence can help in personalized treatment approaches. Some rare diseases have specific genetic subtypes that respond differently to treatments. By knowing the patient’s DNA, doctors can tailor treatments to their unique genetic makeup.
d. Prenatal Diagnosis: In cases where a rare disease is known to be associated with certain genetic mutations, prenatal screening of DNA sequences can help identify potential health issues in the unborn child, enabling parents to make informed decisions about the pregnancy.
a. Gene Expression Analysis:
There are different types of gene expression profiling. Some measure coding region mRNA, showing the pattern of genes expressed by a cell at the transcription level. Others, like RNA sequencing, measure the entire set of RNA including pre-mRNA, mRNA and several types of noncoding RNA such as tRNA, miRNA and long ncRNA.
By studying RNA expression profiles, researchers can gain insights into the underlying molecular processes and dysregulations contributing to the disease.
b. Splicing Abnormalities: Some genetic diseases are caused by abnormalities in RNA splicing, leading to non-functional or altered proteins. Analyzing RNA sequences helps detect such splicing errors, which may not be apparent from DNA sequences alone.
c. Temporal and Tissue-Specific Expression: RNA sequences can vary between tissues and change over time. For some rare diseases, understanding the specific RNA expression pattern in affected tissues can help diagnose and classify the disease more accurately.
d. Identifying Novel Disease-Causing Variants: In some cases, disease-causing mutations may not be apparent in the DNA sequence due to the complexity of genetic interactions. Studying RNA sequences together with DNA sequences can help identify novel or previously undetected disease-causing variants.
In a study conducted by SickKids hospital, Canada, RNA-seq was an effective adjunct test when paired with GS in identifying non-coding variant in children with unexplained medical complexity. In another study a novel pathogenic non-coding variant in single families with Inherited retinal degenerations (IRDs) was identified by combining WGS and RNA-seq technology.
In summary, integrating both DNA and RNA sequence analysis provides a comprehensive view of the genetic and molecular landscape of an individual’s health. This multi-level approach improves the accuracy of diagnosis for genetic and rare diseases, leading to better patient management and potential advancements in therapeutic strategies.
- Bronstein, R., Capowski, E. E., Mehrotra, S., Jansen, A. D., Navarro-Gomez, D., Maher, M., Place, E., Sangermano, R., Bujakowska, K. M., Gamm, D. M., & Pierce, E. A. (2020). A combined RNA-seq and whole genome sequencing approach for identification of non-coding pathogenic variants in single families. 29(6), 967–979. https://doi.org/10.1093/hmg/ddaa016
- Deshwar, A. R., Yuki, K. E., Hou, H., Liang, Y., Khan, T., Celik, A., Ramani, A., Mendoza, R. L., Marshall, C. R., Brudno, M., Shlien, A., Meyn, M. S., Hayeems, R. Z., McKinlay, B. J., Klentrou, P., Wilson, M. D., Kyriakopoulou, L., Costain, G., & Dowling, J. J. (2023). Trio RNA sequencing in a cohort of medically complex children. American Journal of Human Genetics, 110(5). https://doi.org/10.1016/j.ajhg.2023.03.006
- Hrdlickova, R., Toloue, M., & Tian, B. (2016). RNA-Seq methods for transcriptome analysis. Wiley Interdisciplinary Reviews: RNA, 8(1), e1364. https://doi.org/10.1002/wrna.1364
- Scotti, M. M., & Swanson, M. S. (2015). RNA mis-splicing in disease. Nature Reviews Genetics, 17(1), 19–32. https://doi.org/10.1038/nrg.2015.3