Revealing missing isoforms encoded in the human genome by integrating genomic, transcriptomic and proteomic data

Abstract

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing and is much larger than the number of human genes.\n\nIn this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.\n\nAuthor summaryThe identification of all human proteins is an important and open problem. In this report we first develop an ab initio predictor to collect candidate gene models as many as possible. Next, comprehensive sets of RNA-seq data from diverse tissues and cell lines are used to select confident transcripts. Experimental validation of a subset of predictions confirms a high accuracy for the predicted coding transcript set and has added about 30,000 new protein-coding transcripts to the existing corpus of knowledge in this area. This is significant progress given that the existing protein-coding transcript number in public databases is about 60,000. Our newly found transcripts are more tissue specific. Based on our results, we show that L1's high impact on gene origin and genes with high number of transcripts are enriched in specific functions. At last, we estimate that the total number of human protein-coding transcripts is in excess of 200,000.