henhaobio
Sign in

bioRxivGeneticsPreprint

Pushing the limits of single molecule transcript sequencing to uncover the largest disease-associated transcript isoforms in the human neural retina

Merel StemerdinkiD, Tabea RiepeiD, Nick ZomeriD, Renee SalziD, Michael P. KwintiD, Raoul Timmermans, Barbara FerrariiD, Stefano FerrariiD, Alfredo Dueñas ReyiD, Emma Delanote, Suzanne E. de BruijniD, Hannie KremeriD, Susanne RoosingiD, Frauke CoppietersiD, Alexander HoischeniD, Frans P.M. CremersiD, Peter A.C. ’t HoeniD, Erwin van WijkiD, Erik de VriezeiD

PDFDOI

Abstract

Sequencing technologies have long limited the comprehensive investigation of large transcripts associated with inherited retinal diseases (IRDs) like Usher syndrome, which involves 11 associated genes with transcripts up to 19.6 kb. To address this, we used PacBio long-read mRNA isoform sequencing (Iso-Seq) following standard library preparation and an optimized workflow to enrich for long transcripts in the human neural retina. While our workflow achieved sequencing of transcripts up to 15 kb, this was insufficient for Usher syndrome-associated genes USH2A and ADGRV1, with transcripts of 18.9 kb and 19.6 kb, respectively. To overcome this, we employed the Samplix Xdrop System for indirect target enrichment of cDNA, a technique typically used for genomic DNA capture. This method facilitated the successful capture and sequencing of ADGRV1 transcripts as well as the full-length 18.9 kb USH2A transcripts. By combining algorithmic analysis with detailed manual curation of sequenced reads, we identified novel isoforms and alternative splicing events across the 11 Usher syndrome-associated genes, with implications for diagnostics and therapy development. Our findings demonstrate the Xdrop systems adaptability for cDNA capture and the advantages of integrating computational and manual transcript analyses. The full neural retina sequencing dataset is available via EGA under identifier EGAD50000000720.

Citations
0

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.

Similarity Map
SelectedSame fieldCross-field
THISWang '24Riepe '24Swamy '20Wang '25Fabian-Mora '25Kaplan '26
63% semantic matchGenomics
Luozixian Wang, Daniel Urrutia-Cabrera, Sandy S. C. Hung+6 more·bioRxiv·Aug 8, 2024· 3 citations