Table 1.

Genetic Techniques for Testing CKD

Technique	Description	Benefits	Drawbacks
Sanger Sequencing	• PCR-based, single nucleotide sequencing of a targeted locus, less than 1 kB; or of multiple loci simultaneously • Used for confirmatory testing of NGS results • Used for testing when a specific disease associated when a known locus, or loci are suspected	• Capable of detecting SNVs and short indels • Capable of testing for a microdeletions smaller than limit of CMA testing by using primers flanking a CNV hotspot • Rapid testing and analysis possible • Near perfect accuracy for variants within tested loci • Avoids secondary and incidental findings	• Scope of testing limited to less than 1 kB per sequence • Low throughput limits ability to test multiple variants • Cannot detect most structural variation
CMA	• Genome-wide survey of copy number capable of CNVs greater than 200–400 kb • Used when a genomic disorder is clinically suspected, often in combination with karyotype	• High resolution for CNVs • Unbiased, genome-wide assay	• Cannot detect SNVs and indels28 • Decreased sensitivity within repetitive regions and pseudogenes28 • Cannot detect balanced structural changes
MPS targeted panel	• Massive parallel sequencing in which DNA from many loci is isolated and sequenced • Panels tailored to sequence portions of genes known to be associated with specific diagnoses	• High sensitivity to a variation within a broad region of coverage • Significant reduction in data storage and annotation requirements compared to ES and GS • Useful when secondary and incidental findings are not desired	• Panel excludes novel and rare variants outside of region of coverage • Limited potential for future reclassification of variants
ES	• Massive parallel sequencing of nearly all protein-coding portions of genes • Provides unbiased survey that can detect most known disease-causing SNVs	• High sensitivity screen for exonic SNVs • Data can be reanalyzed periodically as new sequence information becomes available	• Limited detection of indels and CNVs • May not target all CKD genes29 • Highly resource intensive requiring expensive equipment, time consuming data interpretation and expert analysis30 • Can produce undesired incidental and secondary findings31 • Limited detection within repetitive and CG-rich regions32,33 • Platform-specific artifacts can be introduced into sequence data • Not uniformly covered and reimbursed by health insurance34
GS	• Massive parallel sequencing of near entirety of a genome • Provides unbiased survey that can detect most known disease-causing SNVs	• Sensitive to SNVs, including indels and intronic variants • Capable of sequencing genes with high homology to other loci • Capable of detecting genomic disorders • Decreased artifact in sequence data compared to ES • Data can be reanalyzed periodically as new sequence information becomes available	• Unclear significance of non-coding variants35 • Limited detection within repetitive and CG-rich regions32 • Highly resource intensive, particularly regarding longterm data storage • Can produce undesired incidental and secondary findings • Not uniformly covered and reimbursed by health insurance34