Human Genetics

Genetic variations and their association with disease

The Human Genome Project, which mapped the human genome in 2001 and completed the euchromatic sequence in 2004, rapidly accelerated the field of human genetics. The ~3 billion base pairs and 20-25 thousand protein-encoding genes that were published in this project established a solid foundation for biomedical research. At the time, the most advanced technology used by researchers was Sanger sequencing. It was time-consuming and expensive, costing approximately $10 million per human genome in 2006.1

Next-generation sequencing (NGS; also known as second-generation sequencing) techniques were introduced in 2007 and their subsequent advancements have reshaped and expanded human genetics research. The ability to analyze whole genomes at a fraction of the time and cost has been instrumental to the widespread clinical applicability of NGS.2

 

Advantages of NGS over Sanger Sequencing

NGS allows researchers to efficiently compare genomes among individuals to identify genetic causes of diseases. NGS also identifies a broad spectrum of DNA mutations, including large genomic deletions of exons or whole genes and rearrangements (e.g., inversions and translocations). By contrast, Sanger sequencing is generally limited to the detection of substitutions and small insertions and deletions. In addition, NGS can evaluate entire genomes or exomes to identify novel mutations and genes associated with disease in an unbiased manner. By contrast, Sanger sequencing requires prior knowledge about the gene or locus of interest. The higher sensitivity of NGS allows for detection of variants present in a small percentage of cells (such as mosaic variants), which are undetectable by Sanger sequencing.

 

Types of NGS: Whole Genome, Whole Exome, and Targeted Sequencing

The three main types of NGS are whole genome sequencing, whole exome sequencing and targeted sequencing.

  • Whole genome sequencing: studies the sequence of an entire genome
  • Whole exome sequencing: studies the sequence of just the coding regions which is approximately 2% of the whole genome
  • Targeted sequencing: focuses on specific genomic regions based on the research area of interest. These areas include genes for a variety of inherited diseases such as somatic oncology, cardiac and neurological diseases.

Because most disease-causing mutations are located in the coding region, whole exome sequencing is thought to be more efficient for identifying clinically relevant gene mutations than whole genome sequencing. However, DNA variations outside of the coding regions have been shown to affect gene activity and protein synthesis, thus indicating a potential role for utilizing whole genome sequencing.

 

Advancing Diagnostics and Therapeutics with NGS

NGS has revolutionized risk assessment for diseases and the development of personalized treatment options. In the oncology field, NGS has allowed rapid and cost-effective identification and characterization of genetic variants associate with tumorigenesis, tumor progression and tumor metastases, as well as the complexity, heterogeneity and evolution of different types of tumors. This information has been instrumental for identifying prognostic markers and developing diagnostic tests and molecularly-targeted therapies, which have improved personalized approaches to cancer management. For example, identification of mutations in EGFR and HER2 have revolutionized development of drugs targeting these mutations, which have in turn improved prognosis for cancers with these mutations.

NGS also helps with the identification of multiple genes involved in complex diseases by making it economically feasible to perform genome­ wide association studies. Genetic predispositions to most disease phenotypes are complex and require large numbers of samples to differentiate signals of association from noise. The ability to rapidly sequence whole human genomes has allowed for identification of genetic variants associated with a wide range of traits and disease phenotypes, including high altitude adaptation, drug metabolism and age-related macular degeneration.3

NGS techniques are capable of generating immense quantities of genetic data, and ongoing collaborative projects are instrumental for translating this information into diagnostic tools that shape clinical decision-making. Recent efforts focused on the classification and clinical interpretation of sequence variants include joint criteria published by the American College of Medical Genetics and Genomics/Association for Molecular Pathology4 and databases such as the Exome Aggregation Consortium5 and Human Gene Mutation Database.6

With the innovation of NGS technologies, researchers have the ability to map whole genomes, exomes and targeted sequences with a higher throughput and at lower costs than previous methods. This has enabled scientists to perform complex genetic testing for more accurate diagnosis of diseases and develop more effective therapeutics for patients.

Roche Sequencing Solutions offers a broad portfolio of target enrichment and library preparation products for NGS research applications.

  1. Wetterstrand KA. DNA Sequencing Costs: Data from the NHGRI Genome Sequencing Program (GSP) Available at: www.genome.gov/sequencingcostsdata. Accessed February 11, 2020.

  2. https://www.yourgenome.org/stories/next-generation-sequencing

  3. Koboldt DC, Steinberg KM, Larson DE, Wilson RK, Mardis ER. The next-generation sequencing revolution and its impact on genomics. Cell. 2013 Sep 26;155(1):27-38. doi: 10.1016/j.cell.2013.09.006.

  4. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17: 405–424. doi:10.1038/gim.2015.30

  5. Song W, Gardner SA, Hovhannisyan H, Natalizio A, Weymouth KS, Chen W, et al. Exploring the landscape of pathogenic genetic variation in the ExAC population database: insights of relevance to variant classification. Genet Med. 2016;18: 850–854. doi:10.1038/gim.2015.180

  6. Stenson PD, Mort M, Ball E V, Howells K, Phillips AD, Thomas NS, et al. The Human Gene Mutation Database: 2008 update. Genome Med. 2009;1: 13. doi:10.1186/gm13