Long read sequencing of retinal RNA improves killifish transcriptome annotation

An African Turquoise Killifish, a promising model for aging and age-related disease research, has faced limitations due to preliminary genome and transcriptome builds. These issues caused problems in primary and secondary analyses of RNAseq data. Researchers aimed to generate a comprehensive retinal transcriptome to improve future studies of the visual system.

Using long-read PacBio RNAseq data processed through a robust computational pipeline, the study created a new annotation for the NfurGRZ-RIMD1 reference genome. This new build was more contiguous and complete than the widely-used Nfu_20140520. However, both transcriptomes had limitations, such as missing annotation of retina-specific genes and many uninformative gene names.

By conducting long-read PacBio sequencing on RNA from retinas of young and old Killifish, the researchers annotated a deep retinal transcriptome onto the improved reference genome. This analysis revealed thousands of previously unannotated transcripts from the retinas of killifish at different ages. Matching each protein sequence to its closest ortholog increased the number of genes with meaningful gene names.

Mapping bulk and single-cell RNAseq data showed a substantial increase in mapping rate, identifying hundreds of genes and transcripts with age-dependent expression dynamics. The enhanced retinal transcriptome improved both primary and secondary analyses of RNAseq data, benefiting future studies investigating aging mechanisms in the Killifish. This advancement will help researchers better utilize this model to understand human disease.