Challenges and Approaches to Genotyping Repetitive DNA

Author:

Morton Elizabeth A1,Hall Ashley N12,Kwan Elizabeth1,Mok Calvin3ORCID,Queitsch Konstantin4,Nandakumar Vivek4,Stamatoyannopoulos John4,Brewer Bonita J1,Waterston Robert1,Queitsch Christine1

Affiliation:

1. Department of Genome Sciences

2. Molecular and Cellular Biology Program, University of Washington, Seattle, 98195

3. Department of Molecular Genetics, University of Toronto, Ontario M5S 1A8, Canada, and

4. Altius Institute for Biomedical Sciences, Seattle, Washington 98121

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.

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology

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