Back

The RNA Atlas, a single nucleotide resolution map of the human transcriptome

Lorenzi, L.; Chiu, H.-S.; Avila Cobos, F.; Gross, S.; Volders, P.-J.; Cannoodt, R.; Nuytens, J.; Vanderheyden, K.; Anckaert, J.; Lefever, S.; Goovaerts, T.; Hansen, T. B.; Kuersten, S.; Nijs, N.; Taghon, T.; Vermaelen, K.; Bracke, K. R.; Saeys, Y.; De Meyer, T.; Deshpande, N.; Anande, G.; Chen, T.-W.; Wilkins, M. R.; Unnikrishnan, A.; De Preter, K.; Kjems, J.; Koster, J.; Schroth, G. P.; Vandesompele, J.; Sumazin, P.; Mestdagh, P.

2019-10-17 genetics
10.1101/807529 bioRxiv
Show abstract

The human transcriptome consists of various RNA biotypes including multiple types of non-coding RNAs (ncRNAs). Current ncRNA compendia remain incomplete partially because they are almost exclusively derived from the interrogation of small- and polyadenylated RNAs. Here, we present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogeneous collection of nearly 300 human tissues and cell lines. We report on thousands of novel RNA species across all major RNA biotypes, including a hitherto poorly-cataloged class of non-polyadenylated single-exon long non-coding RNAs. In addition, we exploit intron abundance estimates from total RNA-sequencing to test and verify functional regulation by novel non-coding RNAs. Our study represents a substantial expansion of the current catalogue of human ncRNAs and their regulatory interactions. All data, analyses, and results are available in the R2 web portal and serve as a basis to further explore RNA biology and function.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.