Exploring the genetic basis of complex diseases
What is a Complex Disease?
Complex diseases are among the most pressing challenges in present day healthcare. These conditions are influenced by the interaction between a genetic predisposition and environmental or lifestyle factors that can impact the severity and progression of the disease. As opposed to rare diseases, which are often caused by the dysfunction of a single gene, most diseases are complex and are influenced by thousands of common genetic variants. For instance, conditions like heart disease, diabetes, and mental disorders are considered complex diseases due to their multifactorial nature.
Due to their inherent complexity, researching these medical conditions has proven extremely challenging in the past. However, progress in genomics technologies has accelerated the study of the human genome at the level of both its sequence — revealing the genetic diversity across populations — and of its expression at the various functional levels, including the transcriptome, the proteome, and the regulome. Using these advances, Genome Wide Association Studies (GWAS) have successfully mapped thousands of loci associated with complex traits. These associations could reveal the molecular mechanisms altered in common complex diseases and result in the identification of novel treatments.
In this blog, we discuss how novel sequencing technologies are revolutionizing the study of complex diseases, with a particular focus on cancer genomics.
The Complexity of Cancer Genomics
Cancer is a particularly complex disease, with genetic mutations arising from both environmental and hereditary influences. This variability means that each patient’s cancer is characterized by a unique constellation of mutations.
Increasingly, studies are finding that most somatic variants in cancer genomes occur in non-coding regions, including promoters, enhancers, insulators, silencers, and non-coding RNAs. However, these regions can be difficult to identify and study due to extensive repeats and staggering complexity.
The advent of long-read sequencing (LRS) means that non-coding regions can be sequenced and analyzed much more easily than with previous technology. Notably, in 2022, this technological leap culminated in the achievement of a complete, gapless sequence of the human genome, showing the immense potential of LRS to detect novel and complex variants that elude detection by conventional short-read sequencing methods [1].
Several studies have now used LRS to genotype large genome aberrations, such as copy number variant (CNVs) and structural variants (SVs) [2-5]. In addition to looking at these genomic variations, LRS can also be used to analyze the transcriptome of cancer cells.
Long reads can completely cover full-length transcript sequences, allowing scientists to analyze the structures and variety of transcript isoforms. Fusion transcripts are known to be major driver events of carcinogenesis in several types of cancers, playing critical roles in tumorigenesis and progression [6].
The PacBio Iso-Seq® method utilizes highly accurate HiFi sequencing to capture full-length transcripts to detect cancer-specific splicing isoforms and fusion transcripts (Fig 1). This was demonstrated in SK-BR-3, the most studied cancer cell line as a model of breast cancer [7]. Comprehensive genome and transcriptome sequencing revealed tens of thousands of novel isoforms and characterized several novel gene fusions, including some that required the fusion of three separate chromosome regions. An invaluable resource, LRS was able to capture the complexity of structural variations on both the genomic and transcriptomic levels. This type of information is essential for helping to enable both the potential diagnosis and treatment stratification of cancer.
Figure 1. Comparison of short-read and HiFi sequencing for resolving a gene with several transcript isoforms. Transcript isoforms (black) have multiple junctions. Few short-reads span these junctions (blue), and so cannot resolve complex isoforms. HiFi reads cover full length, spanning all junctions (pink), requiring no computational assembly.
The Role of Methylation in Complex Disease
When studying complex diseases, it is important to analyze a range of factors, including the genome, transcriptome, and the epigenome. In cancer cells, aberrant DNA methylation can have profound effects on transcriptomics, from causing chromosomal instability due to global hypomethylation [8] to the silencing of genes like cell cycle regulators and mismatch repair factors due to hypermethylation [9].
Because of their crucial role in cancer development and progression, DNA methylation markers hold immense potential as predictive factors for disease outcomes and individual responses to chemotherapy [10]. Many of the epigenetic changes associated with cancer occur early in tumorigenesis and are highly prevalent across various tumor types. This universality renders methylation cancer biomarkers invaluable for early detection, offering clinical insight into treatment resistance, tumor characterization, and the tissue of origin. Crucially, cancer-associated methylation changes can also be detected with precision in cell-free DNA found in blood, stool, urine, and other biosamples, presenting a promising approach in non-invasive cancer diagnosis and monitoring [10].
Analyzing epigenetic changes associated with cancer also offers another tantalizing opportunity. Unlike genetic mutations, epigenetic alterations are reversible, meaning that we can target these changes to reverse the cancer phenotype. Using methylation inhibitors such as 5′-azacytidine and decitabine, scientists have been able to treat specific subtypes of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) [11].
Read how reversing epigenetic changes could also reverse the symptoms of aging
Work with Eremid to Study Complex Disease
Genomics is crucial to the understanding and treatment of complex diseases such as cancer. By using LRS to identify novel variants and bisulfite sequencing to identify specific methylation markers, scientists can redefine our approach to combating cancer, developing new methods for diagnosis in addition to tailored and effective treatments.
As experts in sequencing and analysis, Eremid’s world-class scientific team offers state-of-the-art solutions in genomics, transcriptomics, and epigenetics. Our PacBio Revio system is the latest generation of LRS systems employing PacBio’s HiFi sequencing technology. With its remarkable capabilities, combined with our in-house expertise, we are poised to help you propel clinical research to new heights, harnessing techniques like Iso-Seq to push the boundaries of what genomics can achieve.
References
1. Nurk, S., Koren, S., Rhie, A., Rautiainen, M., Bzikadze, A.V., et al., 2022. The complete sequence of a human genome. Science 376, 44–53. https://doi.org/10.1126/science.abj6987
2. Suzuki, A., Suzuki, M., Mizushima-Sugano, J., Frith, M.C., Makałowski, W., et al., 2017. Sequencing and phasing cancer mutations in lung cancers using a long-read portable sequencer. DNA Research 24, 585. https://doi.org/10.1093/dnares/dsx027
3. Fujimoto, A., Wong, J.H., Yoshii, Y., Akiyama, S., Tanaka, A., et al., 2021. Whole-genome sequencing with long reads reveals complex structure and origin of structural variation in human genetic variations and somatic mutations in cancer. Genome Medicine 13, 65. https://doi.org/10.1186/s13073-021-00883-1
4. Euskirchen, P., Bielle, F., Labreche, K., Kloosterman, W.P., Rosenberg, S., et al., 2017. Same-day genomic and epigenomic diagnosis of brain tumors using real-time nanopore sequencing. Acta Neuropathol 134, 691–703. https://doi.org/10.1007/s00401-017-1743-5
5. Sakamoto, Y., Xu, L., Seki, M., Yokoyama, T.T., Kasahara, M., et al., 2020. Long-read sequencing for non-small-cell lung cancer genomes. Genome Res. 30, 1243–1257. https://doi.org/10.1101/gr.261941.120
6. Edwards, P.A.W., 2010. Fusion genes and chromosome translocations in the common epithelial cancers. J Pathol 220, 244–254. https://doi.org/10.1002/path.2632
7. Nattestad, M., Goodwin, S., Ng, K., Baslan, T., Sedlazeck, F.J., et al., 2018. Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line. Genome Res 28, 1126–1135. https://doi.org/10.1101/gr.231100.117
8. Rodriguez, J., Frigola, J., Vendrell, E., Risques, R.-A., Fraga, M.F., et al., 2006. Chromosomal instability correlates with genome-wide DNA demethylation in human primary colorectal cancers. Cancer Res 66, 8462–9468. https://doi.org/10.1158/0008-5472.CAN-06-0293
9. Herman, J.G., Baylin, S.B., 2003. Gene silencing in cancer in association with promoter hypermethylation. N Engl J Med 349, 2042–2054. https://doi.org/10.1056/NEJMra023075
10. Locke, W.J., Guanzon, D., Ma, C., Liew, Y.J., Duesing, K.R., et al., 2019. DNA Methylation Cancer Biomarkers: Translation to the Clinic. Frontiers in Genetics 10. https://doi.org/10.3389/fgene.2019.01150
11. Aumer, T., Gremmelmaier, C.B., Runtsch, L.S., Pforr, J.C., Yeşiltaç, G.N., et al., 2022. Comprehensive comparison between azacytidine and decitabine treatment in an acute myeloid leukemia cell line. Clinical Epigenetics 14, 113. https://doi.org/10.1186/s13148-022-01329-0
