Challenges and Approaches to Genotyping Repetitive DNA. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Morton, Elizabeth A; Hall, Ashley N; Kwan, Elizabeth; Mok, Calvin; Queitsch, Konstantin; Nandakumar, Vivek; Stamatoyannopoulos, John; Brewer, Bonita J; Waterston, Robert; Queitsch, Christine
• Is Part Of: G3. Volume 10:Issue 1(2020)
• Page Start: 417
• Page End: 430
• Publication Date: 2020-01-01
• Subjects: Ribosomal DNA -- Repetitive DNA -- Whole Genome Sequencing -- Copy Number Variation; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.119.400771
• Languages: English
• ISSNs: 2160-1836

Abstract

Abstract: Individuals within a species can exhibit vast variation in copy number of repetitive DNA elements. This variation may contribute to complex traits such as lifespan and disease, yet it is only infrequently considered in genotype-phenotype associations. Although the possible importance of copy number variation is widely recognized, accurate copy number quantification remains challenging. Here, we assess the technical reproducibility of several major methods for copy number estimation as they apply to the large repetitive ribosomal DNA array (rDNA). rDNA encodes the ribosomal RNAs and exists as a tandem gene array in all eukaryotes. Repeat units of rDNA are kilobases in size, often with several hundred units comprising the array, making rDNA particularly intractable to common quantification techniques. We evaluate pulsed-field gel electrophoresis, droplet digital PCR, and Nextera-based whole genome sequencing as approaches to copy number estimation, comparing techniques across model organisms and spanning wide ranges of copy numbers. Nextera-based whole genome sequencing, though commonly used in recent literature, produced high error. We explore possible causes for this error and provide recommendations for best practices in rDNA copy number estimation. We present a resource of high-confidence rDNA copy number estimates for a set of S. cerevisiae and C. elegans strains for future use. We furthermore explore the possibility for FISH-based copy number estimation, an alternative that could potentially characterize copy number on a cellular level.