Long read sequencing of retinal RNA improves killifish transcriptome annotation
- 1Washington University School of Medicine
Abstract
Purpose The African Turquoise Killifish has recently emerged as a powerful model for aging and age-related disease research studies. However, molecular based investigations have been limited by preliminary genome and transcriptome builds with incomplete reference genome sequence, fragmented chromosome assembly, and missing gene annotations. These issues make primary (alignment and quantification) and secondary (Gene Ontology, Gene Set Enrichment Analysis, cross-species comparisons) analyses difficult to reliably implement and interpret. This study seeks to generate a complete retinal reference transcriptome to facilitate future killifish transcriptomic, epigenetic, and proteomic studies of the visual system. Methods We generated an enhanced retina transcriptome using long-read PacBio RNAseq data that was processed using a robust computational pipeline to merge reads, classify genes, and annotate with nearest orthologous gene names from other species. This new annotation was compared to available references and validated using bulk and single cell RNAseq datasets. Results Comparison of the widely used Nfu_20140520 and the newly released NfurGRZ-RIMD1 genome builds identified NfurGRZ-RIMD1 to be more contiguous and complete. However, we identified limitations with both transcriptomes, including the lack of annotation of certain retina specific genes and many uninformative gene names. Using long-read PacBio sequencing of RNA collected from young and old Killifish retinas, we annotated a deep retinal transcriptome onto the NfurGRZ-RIMD1 reference genome. This analysis identified thousands of previously unannotated transcripts from retinas of young and old killifish. By matching each translated protein sequence to its nearest ortholog, we increased the number and proportion of genes with meaningful gene names. Mapping of bulk and single-cell RNAseq data showed substantial increase in mapping rate and identified hundreds of genes and transcripts with age-dependent expression dynamics. Conclusions Assembly of an enhanced retinal transcriptome for the killifish improved both primary and secondary analyses of bulk and single cell RNAseq data. Improvements will benefit future studies investigating the mechanisms of aging in the killifish and to best utilize this powerful model to understand human disease.
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BibTeX
@misc{rebba2026long,
title = {{Long read sequencing of retinal RNA improves killifish transcriptome annotation}},
author = {S. Rebba and L. van Schalkwyk and A. M. Krzywanska and R. B. MacDonald and B. B. Clark and P. A. Ruzycki},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.02.748420},
url = {https://www.biorxiv.org/content/10.64898/2026.09.02.748420v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Long read sequencing of retinal RNA improves killifish transcriptome annotation
AU - S. Rebba
AU - L. van Schalkwyk
AU - A. M. Krzywanska
AU - R. B. MacDonald
AU - B. B. Clark
AU - P. A. Ruzycki
PY - 2026
DA - 2026/09/02
PB - bioRxiv
DO - 10.64898/2026.09.02.748420
UR - https://www.biorxiv.org/content/10.64898/2026.09.02.748420v1
AB - Purpose The African Turquoise Killifish has recently emerged as a powerful model for aging and age-related disease research studies. However, molecular based investigations have been limited by preliminary genome and transcriptome builds with incomplete reference genome sequence, fragmented chromosome assembly, and missing gene annotations. These issues make primary (alignment and quantification) and secondary (Gene Ontology, Gene Set Enrichment Analysis, cross-species comparisons) analyses difficult to reliably implement and interpret. This study seeks to generate a complete retinal reference transcriptome to facilitate future killifish transcriptomic, epigenetic, and proteomic studies of the visual system. Methods We generated an enhanced retina transcriptome using long-read PacBio RNAseq data that was processed using a robust computational pipeline to merge reads, classify genes, and annotate with nearest orthologous gene names from other species. This new annotation was compared to available references and validated using bulk and single cell RNAseq datasets. Results Comparison of the widely used Nfu_20140520 and the newly released NfurGRZ-RIMD1 genome builds identified NfurGRZ-RIMD1 to be more contiguous and complete. However, we identified limitations with both transcriptomes, including the lack of annotation of certain retina specific genes and many uninformative gene names. Using long-read PacBio sequencing of RNA collected from young and old Killifish retinas, we annotated a deep retinal transcriptome onto the NfurGRZ-RIMD1 reference genome. This analysis identified thousands of previously unannotated transcripts from retinas of young and old killifish. By matching each translated protein sequence to its nearest ortholog, we increased the number and proportion of genes with meaningful gene names. Mapping of bulk and single-cell RNAseq data showed substantial increase in mapping rate and identified hundreds of genes and transcripts with age-dependent expression dynamics. Conclusions Assembly of an enhanced retinal transcriptome for the killifish improved both primary and secondary analyses of bulk and single cell RNAseq data. Improvements will benefit future studies investigating the mechanisms of aging in the killifish and to best utilize this powerful model to understand human disease.
ER -