Role of Long-Read Sequencing in Genomic Medicine

The latest advances in next-generation sequencing technologies have revolutionized the field of medical genetics. Genomic medicine and medical genetics are relatively new fields that involve using genomic technologies for diagnostics and therapeutic decision-making. These genomics-based approaches are becoming increasingly feasible in clinical settings as the cost of whole-genome sequencing data continues to fall.

Medical Genetics

Image Credit: PopTika/Shutterstock.com

Long-read sequencing is an emerging approach capable of capturing the complexity of the genome by identifying structural variations at the whole genome level. This strategy exhibits a series of advantages compared to short-read sequencing methods, which are not only associated with the sequence length but also speed and fragmentation bias.

Long-Read Sequencing vs. Short-Read Sequencing

Long-read sequencing -often referred to as third-generation sequencing- is a DNA sequencing technique that can determine the nucleotide sequence of long pieces of DNA that range in size from tens to hundreds of kilobases (kb) simultaneously at the same time. This technique enables efficient sequencing of long sequences of DNA over 10 kb in one single read, whereas short-read sequencing methods yield much smaller pieces of a few hundred base pairs in size (often ranging from 150 bp to 300 bp).

But the advantages of the long-read sequencing technologies do not end in fewer reads. This approach can be readily applied to a real-time environment to sequence long pieces of DNA without the need for amplification, making it faster than traditional short-read sequencing methods.

Short read sequencing methods pose some technical hurdles that are especially heightened for large and complex genomes like the human genome. A single set of human chromosomes, i.e., the haploid human genome, is approximately 2.9 billion base pairs (2,900 Mb) long, of which more than one-half consists of repetitive sequences. This highly redundant nature of the human genome makes more difficult the assemblage and annotation of nucleotide sequences obtained from short-read sequencing.

Read Next: Types of Gene Editing

The Importance of the Long-Read Sequencing Technology in Genomic Medicine

Whole-exome sequencing is a technique focused on targeted sequencing of all the protein-coding regions of the genome (i.e., exome analysis). This technique is considered a simple, cost-effective, and efficient approach for diagnosing many genetic disorders. However, whole-exome sequencing cannot detect different diseases since pathogenic mutations may also fall in the genome's non-coding (regulatory) regions.

Over the past decade, high-throughput whole-genome sequencing methods have revealed that the human genome contains over 20,000 structurally variable genomic regions. Many of these genomic regions include several thousands of insertions and deletions (collectively referred to as indels) that are on the order of dozens of megabase pairs in size. Genetic polymorphisms located in such variable regions can often represent a challenge for detection using short-read sequencing platforms.

In addition to the misidentification of structurally variable genomic regions, short-read sequencing methods also have problems assembling and determining which alleles are on the same chromosome, a technical hurdle known as allele phasing. Moreover, long-read sequencing technology is one of the most promising approaches for the characterization of genetic variation in large and complex genomes and entire genomic regions. This sequencing technology also identifies single nucleotide polymorphisms (SNPs) in loci associated with an increased risk of developing genetic and multifactorial diseases.

Genetic Disorders

Image Credit: Vitalii Vodolazskyi/Shutterstock.com

The Future of Long-read Sequencing in Genomic Medicine

It is important to highlight that long-read sequencing still faces technical challenges for full application in genomic medicine. The most important problem may be the construction of suitable genomic libraries. Nonetheless, it is expected that such technical issues hampering the adoption of the long-read sequencing technology from lab bench to clinic can be solved in the next few years.

Personalized genomic medicine is an emerging concept involving the utilization of data from a patient's genome for treating genetic diseases in a personalized manner, associating a particular genotype with a given phenotype or health outcome. Long read sequencing has come to convert personalized genomics into something easier and more efficient for clinical settings. The development of more accurate and inexpensive long-read sequencing data will allow better access to this technology while delivering a modern concept of treatment that better fits patients' needs.

Sources:

  • De Coster, W., Weissensteiner, M. H., & Sedlazeck, F. J. (2021). Towards population-scale long-read sequencing. Nature Reviews Genetics, 22(9), 572-587.
  • Glusman, G., Cox, H. C., & Roach, J. C. (2014). Whole-genome haplotyping approaches and genomic medicine. Genome medicine, 6(9), 1-16.
  • Mantere, T., Kersten, S., & Hoischen, A. (2019). Long-read sequencing emerging in medical genetics. Frontiers in genetics, 10, 426.
  • Wang, Y., Li, X., Wang, C., Gao, L., Wu, Y., Ni, X., ... & Jiang, J. (2021). Unveiling the transcriptomic complexity of Miscanthus sinensis using a combination of PacBio long read-and Illumina short read sequencing platforms. BMC genomics, 22(1), 1-16.
  • Wei, P. L., Hung, C. S., Kao, Y. W., Lin, Y. C., Lee, C. Y., Chang, T. H., ... & Lin, J. C. (2020). Characterization of fecal microbiota with clinical specimen using long-read and short-read sequencing platform. International journal of molecular sciences, 21(19), 7110.
  • Zhuo, Z., Rong, W., Li, H., Li, Y., Luo, X., Liu, Y., ... & Xiao, F. (2021). Long-read sequencing reveals the structural complexity of genomic integration of HBV DNA in hepatocellular carcinoma. NPJ genomic medicine, 6(1), 1-8.

Further Reading

Last Updated: Jun 30, 2022

Dr. Luis Vaschetto

Written by

Dr. Luis Vaschetto

After completing his Bachelor of Science in Genetics in 2011, Luis continued his studies to complete his Ph.D. in Biological Sciences in March of 2016. During his Ph.D., Luis explored how the last glaciations might have affected the population genetic structure of Geraecormobious Sylvarum (Opiliones-Arachnida), a subtropical harvestman inhabiting the Parana Forest and the Yungas Forest, two completely disjunct areas in northern Argentina.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Vaschetto, Luis. (2022, June 30). Role of Long-Read Sequencing in Genomic Medicine. AZoLifeSciences. Retrieved on April 27, 2024 from https://www.azolifesciences.com/article/Role-of-Long-Read-Sequencing-in-Genomic-Medicine.aspx.

  • MLA

    Vaschetto, Luis. "Role of Long-Read Sequencing in Genomic Medicine". AZoLifeSciences. 27 April 2024. <https://www.azolifesciences.com/article/Role-of-Long-Read-Sequencing-in-Genomic-Medicine.aspx>.

  • Chicago

    Vaschetto, Luis. "Role of Long-Read Sequencing in Genomic Medicine". AZoLifeSciences. https://www.azolifesciences.com/article/Role-of-Long-Read-Sequencing-in-Genomic-Medicine.aspx. (accessed April 27, 2024).

  • Harvard

    Vaschetto, Luis. 2022. Role of Long-Read Sequencing in Genomic Medicine. AZoLifeSciences, viewed 27 April 2024, https://www.azolifesciences.com/article/Role-of-Long-Read-Sequencing-in-Genomic-Medicine.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.