Systematic analysis of dark and camouflaged genes: disease-relevant genes hiding in plain sight
Mark EbbertiD, Tanner D. JenseniD, Karen R. Jansen‐WestiD, Jonathon P. SensiD, Joseph S. ReddyiD, Perry G. RidgeiD, John S. K. KauweiD, Véronique BelziliD, Luc PregentiD, Minerva M. CarrasquilloiD, Dirk Keene, Eric Berg LarsoniD, Paul K. CraneiD, Yan W. AsmanniD, Nilüfer Ertekin‐TaneriD, Steven G. YounkiniD, Owen A. RossiD, Rosa RademakersiD, Leonard PetrucelliiD, John Denis FryeriD
Abstract
BackgroundThe human genome contains dark gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions that are dark by depth (few mappable reads) and others that are camouflaged (ambiguous alignment), and we assess how well long-read technologies resolve these regions. We further present an algorithm to resolve most camouflaged regions (including in short-read data) and apply it to the Alzheimers Disease Sequencing Project (ADSP; 13142 samples), as a proof of principle.\n\nResultsBased on standard whole-genome lllumina sequencing data, we identified 37873 dark regions in 5857 gene bodies (3635 protein-coding) from pathways important to human health, development, and reproduction. Of the 5857 gene bodies, 494 (8.4%) were 100% dark (142 protein-coding) and 2046 (34.9%) were [≥]5% dark (628 protein-coding). Exactly 2757 dark regions were in protein-coding exons (CDS) across 744 genes. Long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduced dark CDS regions to approximately 45.1%, 33.3%, and 18.2% respectively. Applying our algorithm to the ADSP, we rescued 4622 exonic variants from 501 camouflaged genes, including a rare, ten-nucleotide frameshift deletion in CR1, a top Alzheimers disease gene, found in only five ADSP cases and zero controls.\n\nConclusionsWhile we could not formally assess the CR1 frameshift mutation in Alzheimers disease (insufficient sample-size), we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 196
- FWCI
- 8.68
- Field percentile
- top 1%
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Sequencing the gaps: dark genomic regions persist in CHM13 despite long-read advances
Mark E. Wadsworth, Madeline L. Page, … Mark Ebbert·bioRxiv·May 23, 2025
- Nanopore Long-Read Sequencing Unveils Genomic Disruptions in Alzheimer's Disease
Paulino Ramirez, Wenyan Sun, … Bess E Frost·Alzheimer s & DementiaPeer-reviewed·Nov 1, 2025
- Using deep long-read RNAseq in Alzheimer's disease brain to assess medical relevance of RNA isoform diversity
Bernardo Aguzzoli Heberle, J. Anthony Brandon, … Mark Ebbert·Nature BiotechnologyPeer-reviewed·May 22, 2024
- HiFi long-read genomes for difficult-to-detect clinically relevant variants
Wolfram Höps, Marjan M. Weiss, … Lisenka E.L.M. Vissers·The American Journal of Human GeneticsPeer-reviewed·Jan 13, 2025
- Alzheimer's Disease Sequencing Project Release 4 Whole Genome Sequencing Dataset
Yuk Yee Leung, Wan‐Ping Lee, … Li‐San Wang·Alzheimer s & DementiaPeer-reviewed·May 1, 2025
- Long-read sequencing across the C9orf72 ‘GGGGCC’ repeat expansion: implications for clinical use and genetic discovery efforts in human disease
Mark Ebbert, Stefan L. Farrugia, … John Denis Fryer·Molecular NeurodegenerationPeer-reviewed·Aug 20, 2018