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Guiblet, W.

Publications and source records attributed to Guiblet, W..

3 recordsLinked to original sources

The integrated stress response regulates 18S nonfunctional rRNA decay in mammals

18S nonfunctional rRNA decay (NRD) detects and eliminates translationally nonfunctional 18S rRNA. While this process is critical for ribosome quality control, the mechanisms underlying nonfunctional 18S rRNA turnover remain elusive. NRD was originally identified and has exclusively been studied in Saccharomyces cerevisiae. Here, we show that 18S NRD is conserved in mammals. Using genome-wide CRISPR genetic interaction screens, we find that mammalian NRD acts through the integrated stress response (ISR) via GCN2 and ribosomal protein ubiquitination by RNF10. Selective ribosome profiling reveals nonfunctional 18S rRNA induces translational arrest at start sites. Indeed, biochemical analyses demonstrate that ISR activation limits translation initiation and attenuates collisions between scanning 43S preinitiation complexes and nonfunctional 80S ribosomes arrested at start sites. Overall, the ISR promotes nonfunctional 18S rRNA and 40S ribosomal protein turnover by RNF10-mediated ubiquitination. These findings establish a dynamic feedback mechanism by which the GCN2-RNF10 axis surveils ribosome functionality at translation initiation.

molecular biology↗

Quadrupia: Derivation of G-quadruplexes for organismal genomes across the tree of life

G-quadruplex DNA structures exhibit a profound influence on essential biological processes, including transcription, replication, telomere maintenance, and genomic stability. These structures have demonstrably shaped organismal evolution. However, a comprehensive, organism-wide G-quadruplex map encompassing the diversity of life has remained elusive. Here, we introduce Quadrupia, the most extensive and well-characterized G-quadruplex database to date, facilitating the exploration of G-quadruplex structures across the evolutionary spectrum. Quadrupia has identified G-quadruplex sequences in 108,449 reference genomes, with a total of 140,181,277 G-quadruplexes. The database also hosts a collection of 319,784 G-quadruplex clusters of 20 or more members, annotated by taxonomic distributions, multiple sequence alignments, profile Hidden Markov Models and cross-references to G-quadruplex 3D structures. Examination of G-quadruplexes across functional genomic elements in different taxa indicates preferential orientation and positioning, with significant differences between individual taxonomic groups. For example, we find that G-quadruplexes in bacteria with a single replication origin display profound preference for the leading orientation. Finally, we experimentally validate the most frequently observed G-quadruplexes using CD-spectroscopy, UV melting, and fluorescent-based approaches. Quadrupia is publicly available through https://www.pavlopoulos-lab.org/quadrupia.

genomics↗

Altered sequencing success at non-B-DNA motifs

Modern sequencing technologies are not error-free, and might have elevated error rates at some locations of the genome. A potential cause for such elevated error rates is the formation of alternative DNA structures (non-B DNA), such as G-quadruplexes (G4s), Z-DNA, or cruciform structures, during sequencing. Approximately 13% of the human genome has the potential to form such structures, which have been previously shown to affect the activity of DNA polymerases and helicases. Here we tested whether motifs with the potential to form non-B DNA (non-B motifs) influence the sequencing success of three major sequencing technologies--Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT). We estimated sequencing success by computing the rates of single-nucleotide, insertion, and deletion errors, as well as by evaluating mean read depth and mean base quality. Overall, all technologies exhibited altered sequencing success for most non-B motif types. Single-nucleotide error rates were generally increased for G-quadruplexes (G4s) and Z-DNA motifs in all three technologies. Illumina and PacBio HiFi deletion error rates were also increased for all non-B types except for Z-DNA motifs, while in ONT they were increased substantially only for G4 motifs. Insertion error rates for non-B motifs were highly elevated in Illumina, moderately elevated in PacBio HiFi, and only slightly elevated in ONT. Using Poisson regression modeling, we evaluated how non-B DNA motifs and other factors influence sequencing error profiles. Using the error rates at non-B motifs, we developed a probabilistic approach to determine the number of false-positive single-nucleotide variants (SNVs) in different sample size and variant frequency cutoff scenarios, as well as in previously generated sequencing data sets (1000Genomes, Simons Genome Diversity Project, and gnomAD). Overall, the effect of non-B DNA on sequencing should be considered in downstream analyses, particularly in studies with limited read depth--e.g., single-cell and ancient DNA sequencing, as well as sequencing of pooled population samples--and when scoring variants with low frequency (e.g., singletons). Because each sequencing technology analyzed has a unique error profile at non-B motifs, a combination of different technologies should be considered in future sequencing studies of such motifs, to maximize accuracy.

genomics↗