Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling. Issue 13 (12th June 2020)

• Record Type: Journal Article
• Authors: Cheung, Peter Pak-Hang; Jiang, Biaobin; Booth, Gregory T.; Chong, Tin Hang; Unarta, Ilona Christy; Wang, Yuqing; Suarez, Gianmarco D.; Wang, Jiguang; Lis, John T.; Huang, Xuhui
• Is Part Of: Journal of molecular biology. Volume 432:Issue 13(2020)
• Page Start: 3933
• Page End: 3949
• Publication Date: 2020-06-12
• Subjects: transcription fidelity -- RNA polymerase I -- Ribosomal RNA -- RNA sequencing; TEEL transcription error-enriched genomic loci -- NET-seq native elongating transcript sequencing -- Cir-seq circular sequencing -- EmPC-seq error model-coupled precision nuclear run-on circular-sequencing -- Pol I polymerase I -- rDNA ribosomal DNA -- biotin-NTP biotin-labeled ribonucleotide triphosphate -- rRNA ribosomal RNA -- TEF transcription error frequency -- SNP single-nucleotide polymorphism; Molecular biology -- Periodicals; Biology -- Periodicals; Biochemistry -- Periodicals; Bacteriology -- Periodicals; Molecular Biology -- Periodicals; Biochemistry -- Periodicals; Biologie moléculaire -- Périodiques; Biologie -- Périodiques; Biochimie -- Périodiques; Moleculaire biologie; Biochemistry; Biology; Molecular biology; Periodicals; 572.805
• DOI: 10.1016/j.jmb.2020.04.011
• Languages: English
• ISSNs: 0022-2836

Abstract

Abstract: RNA polymerase transcribes certain genomic loci with higher errors rates. These transcription error-enriched genomic loci (TEELs) have implications in disease. Current deep-sequencing methods cannot distinguish TEELs from post-transcriptional modifications, stochastic transcription errors, and technical noise, impeding efforts to elucidate the mechanisms linking TEELs to disease. Here, we describe background error model-coupled precision nuclear run-on circular-sequencing (EmPC-seq) to discern genomic regions enriched for transcription misincorporations. EmPC-seq innovatively combines a nuclear run-on assay for capturing nascent RNA before post-transcriptional modifications, a circular-sequencing step that sequences the same nascent RNA molecules multiple times to improve accuracy, and a statistical model for distinguishing error-enriched regions among stochastic polymerase errors. Applying EmPC-seq to the ribosomal RNA transcriptome, we show that TEELs of RNA polymerase I are not randomly distributed but clustered together, with higher error frequencies at nascent transcript 3′ ends. Our study establishes a reliable method of identifying TEELs with nucleotide precision, which can help elucidate their molecular origins. Graphical abstract: Unlabelled Image Highlights: EmPC-seq combines experimental, bioinformatics, and statistical methods to identify a high confidence set of transcriptional mutation-prone positions within genes, eliminating typically confounding factors arising from coverage biases, sequencing noise, alignment artifacts, and background mutations, EmPC-seq affirmatively shows that transcriptional mutation-prone regions cluster together. EmPC-seq allows single transcript analyses to investigate of the molecular origin of transcriptional errors, and we show that transcriptional mutations are enriched at the active site. EmPC-seq can be widely applicable for the study of transcription mutations in various model systems including virus, bacteria, and mammalian cells.