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With the advent of long-read sequencing, previously unresolvable genomic elements are being revisited in an effort to generate fully complete reference genomes. One such element is ribosomal DNA (rDNA), the highly conserved genomic region that encodes rRNAs. Genomic structure and content of the rDNA are variable in both prokarya and eukarya, posing interesting questions about the biology of rDNA. Here, we consider the types of variation observed in rDNA – including locus structure and number, copy number, and sequence variation – and their known phenotypic consequences. With recent advances in long-read sequencing technology, incorporating the full rDNA sequence into reference genomes is within reach. This knowledge will have important implications for understanding rDNA biology within the context of cell physiology and whole-organism phenotypes. Ribosomal (r)DNA has historically been excluded from reference genomes because of its repetitive nature and large size. Advances in long-read sequencing may be the key to fully integrated assessment of variation at the rDNA, including sequence, structural, and copy number variation. rDNA variation may impact human health with possible roles in cancer and aging. [ABSTRACT FROM AUTHOR]

The ribosomal RNA genes (rDNA) are tandemly arrayed in most eukaryotes and exhibit vast copy number variation. There is growing interest in integrating this variation into genotype–phenotype associations. Here, we explored a possible association of rDNA copy number variation with autism spectrum disorder and found no difference between probands and unaffected siblings. Because short-read sequencing estimates of rDNA copy number are error prone, we sought to validate our 45S estimates. Previous studies reported tightly correlated, concerted copy number variation between the 45S and 5S arrays, which should enable the validation of 45S copy number estimates with pulsed-field gel-verified 5S copy numbers. Here, we show that the previously reported strong concerted copy number variation may be an artifact of variable data quality in the earlier published 1000 Genomes Project sequences. We failed to detect a meaningful correlation between 45S and 5S copy numbers in thousands of samples from the high-coverage Simons Simplex Collection dataset as well as in the recent high-coverage 1000 Genomes Project sequences. Our findings illustrate the challenge of genotyping repetitive DNA regions accurately and call into question the accuracy of recently published studies of rDNA copy number variation in cancer that relied on diverse publicly available resources for sequence data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]