Science & Technology, Canada (Commonwealth Union) – Researchers from the University of Toronto, (U of T), Donnelly Centre for Cellular and Biomolecular Research have made a significant discovery, identifying nearly one million new exons within the human genome. Exons are specific DNA segments that are expressed in mature RNA.
Despite the human genome containing approximately 20,000 protein-coding genes with around 180,000 known internal exons, these protein-coding regions represent only one percent of the total genome. The remainder, often referred to as the “dark genome,” remains largely unexplored.
Lead investigator Timothy Hughes, who is also a professor and chair of the Department of Molecular Genetics in the U of T’s Temerty Faculty of Medicine, explained that they have begun to unveil the mysteries of the dark genome by employing a technique called exon trapping, which has led to the discovery of these previously unknown exons.
“The technique involves an assay with plasmids to find exons in DNA fragments of unknown composition,” explained Hughes, the holder of the Canada Research Chair in decoding gene regulation and the John W. Billes Chair of Medical Research for the U of T. “While exon trapping is not widely used anymore, it proved to be effective when used in combination with high-throughput sequencing to scan the entire human genome.”
The researchers published their findings in the journal Genome Research. Exons are parts of the genome that can produce proteins to guide tissue growth and biological functions in the body. When exons can splice themselves into mature RNA transcripts without external help, they are considered autonomous. The study’s authors were motivated to test the exon definition model, which is crucial for molecular genetics research, after doubting one of its presumptions – that the precise excision of non-protein-coding intron regions of the genome is facilitated by clear and consistent signs of where exons commence and end. This assumption does not appear to be universally valid since the splicing of exons does not always proceed flawlessly, occasionally yielding mature RNA transcripts containing non-functional segments, as indicated by the researchers.
“Almost none of the newly discovered exons are found consistently across genomes of different species,” explained Hughes. “They seem to appear in the human genome mainly due to random mutation and are unlikely to play a significant role in our biology. This is evidence that evolution in humans involves a lot of trial and error – most likely enabled by the vast size of our genome.”
Researchers of the study pointed out that documenting randomly mutated exons within the human genome is crucial due to the potential harm their translation could inflict. Long non-coding RNA exons, although autonomous and often lacking defined function, have been linked to cancer development. Among approximately 1.25 million identified exons, both known and unknown, identified through exon trapping, nearly four percent were classified as long non-coding RNA exons.
Moreover, exons located within non-coding introns, termed pseudoexons, possess the ability to mutate, thereby strengthening weak splice sites. This alteration can result in the inclusion of the exon in mature RNA transcripts, potentially leading to disease.
Professor Benjamin Blencowe, from the University of Toronto’s Temerty Faculty of Medicine, who was not part of the study, indicated that the study is intriguing as it expands our understanding of sequences within the human genome that may function as exons in transcribed RNA. Professor Blencowe further pointed out that while the significance of many newly discovered exons remains uncertain, some could become active under specific circumstances, such as through disease-related mutations, underscoring the importance of cataloging them. This research serves as a valuable asset in ongoing endeavors aimed at unraveling the intricacies of the splicing code.
Enhancing our comprehension of the variables influencing exon inclusion in mature RNA holds significant promise for enhancing tools like SpliceAI, a widely utilized program for splice site prediction and detection of aberrant splicing patterns. By incorporating newly generated data from studies such as this one, SpliceAI can undergo refinement, thereby augmenting its predictive accuracy, according to the researchers.
Hughes pointed out that, “SpliceAI often lacks specificity regarding exon characteristics and exhibits limited efficacy in predicting splicing events within uncharted exons.” Hughes further indicated that the exon trapping data they have gathered offers biologically relevant insights that can enrich SpliceAI and similar splicing prediction algorithms, paving the way for deeper exploration of the enigmatic regions of the genome.
