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Review
. 2018 Aug 1;50(8):563-579.
doi: 10.1152/physiolgenomics.00046.2018. Epub 2018 May 4.

Genome sequencing in the clinic: the past, present, and future of genomic medicine

Jeremy W Prokop  1   2   3 , Thomas May  1   4   5 , Kim Strong  1 , Stephanie M Bilinovich  2 , Caleb Bupp  2   6 , Surender Rajasekaran  2   7 , Elizabeth A Worthey  1 , Jozef Lazar  1
Affiliations
Review

Genome sequencing in the clinic: the past, present, and future of genomic medicine

Jeremy W Prokop et al. Physiol Genomics. .

Abstract

Genomic sequencing has undergone massive expansion in the past 10 yr, from a rarely used research tool into an approach that has broad applications in a clinical setting. From rare disease to cancer, genomics is transforming our knowledge of biology. The transition from targeted gene sequencing, to whole exome sequencing, to whole genome sequencing has only been made possible due to rapid advancements in technologies and informatics that have plummeted the cost per base of DNA sequencing and analysis. The tools of genomics have resolved the etiology of disease for previously undiagnosable conditions, identified cancer driver gene variants, and have impacted the understanding of pathophysiology for many diseases. However, this expansion of use has also highlighted research's current voids in knowledge. The lack of precise animal models for gene-to-function association, lack of tools for analysis of genomic structural changes, skew in populations used for genetic studies, publication biases, and the "Unknown Proteome" all contribute to voids needing filled for genomics to work in a fast-paced clinical setting. The future will hold the tools to fill in these voids, with new data sets and the continual development of new technologies allowing for expansion of genomic medicine, ushering in the days to come for precision medicine. In this review we highlight these and other points in hopes of advancing and guiding precision medicine into the future for optimal success.

Keywords: GWAS; VUS; clinical sequencing; ethics; whole genome sequencing.

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Figures

Fig. 1.
Fig. 1.
Timeline for the discovery of DNA/genes into the genomic era for medicine.
Fig. 2.
Fig. 2.
Current statistics from the National Human Genome Research Institute-European Bioinformatics Institute (EBI/NHGRI) database. The EBI/NHGRI genome-wide association study (GWAS) catalog (https://www.ebi.ac.uk/gwas/docs/file-downloads, downloaded 3/23/2018) was assessed for publications per year (A), traits with the most associations (B), most associations per chromosome Mb (C), and associations per ethnicity (D).
Fig. 3.
Fig. 3.
Population structure in current GWAS studies. Each search term was queried against the GWAS studies on November 1, 2016 from the EBI/NHGRI GWAS catalog. Populations were extracted and plotted as box and whisker plots. Caucasian/European = cyan, African American = red, Hispanic = gray, South American = yellow, Middle Eastern = Blue, Asian = green, African = dark blue.
Fig. 4.
Fig. 4.
Sample workflow for clinical sequencing and interpretation of variants.
Fig. 5.
Fig. 5.
Curated protein publication bias with the UniProt database. A: number of genes binned into various number of publications as a percent of total publications. Shown in black are the values for all 20,120 validated human proteins of UniProt and in red are the values for 2,030 proteins annotated in UniProt as transcription factors. B: the same data from A but plotted as the total number of publications represented by each group.
See this image and copyright information in PMC

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