BACKGROUND: Circular RNAs (CircRNAs) are a newly appreciated class of RNAs that lack free 5' and 3' ends, are expressed by the thousands in diverse forms of life, and are mostly of enigmatic function. Ostensibly due to their resistance to exonucleases, circRNAs are known to be exceptionally stable. Previous work in Drosophila and mice have shown that circRNAs increase during aging in neural tissues. RESULTS: Here, we examined the global profile of circRNAs in C. elegans during aging by performing ribo-depleted total RNA-seq from the fourth larval stage (L4) through 10-day old adults. Using stringent bioinformatic criteria and experimental validation, we annotated a high-confidence set of 1166 circRNAs, including 575 newly discovered circRNAs. These circRNAs were derived from 797 genes with diverse functions, including genes involved in the determination of lifespan. A massive accumulation of circRNAs during aging was uncovered. Many hundreds of circRNAs were significantly increased among the aging time-points and increases of select circRNAs by over 40-fold during aging were quantified by RT-qPCR. The expression of 459 circRNAs was determined to be distinct from the expression of linear RNAs from the same host genes, demonstrating host gene independence of circRNA age-accumulation. CONCLUSIONS: We attribute the global scale of circRNA age-accumulation to the high composition of post-mitotic cells in adult C. elegans, coupled with the high resistance of circRNAs to decay. These findings suggest that the exceptional stability of circRNAs might explain age-accumulation trends observed from neural tissues of other organisms, which also have a high composition of post-mitotic cells. Given the suitability of C. elegans for aging research, it is now poised as an excellent model system to determine whether there are functional consequences of circRNA accumulation during aging.
Age-accumulation, Aging, C. elegans, Gene expression, RNA-seq, Splicing, circRNA, Aging, Animals, Caenorhabditis elegans, Gene Expression Profiling, Genomics, High-Throughput Nucleotide Sequencing, RNA, Sequence Analysis, RNA