Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 57,294 bioRxiv papers from 263,837 authors.

mRNA-like long non-coding RNAs (lncRNA) are a significant component of mammalian transcriptomes, although most are expressed only at low levels, with high tissue-specificity and/or at specific developmental stages. In many cases, therefore, lncRNA detection by RNA-sequencing (RNA-seq) is compromised by stochastic sampling. To account for this and create a catalogue of ruminant lncRNA, we compared de novo assembled lncRNA derived from large RNA-seq datasets in transcriptional atlas projects for sheep and goats with previous lncRNA assembled in cattle and human. Few lncRNA could be reproducibly assembled from a single dataset, even with deep sequencing of the same tissues from multiple animals. Furthermore, there was little sequence overlap between lncRNA assembled from pooled RNA-seq data. We combined positional conservation (synteny) with cross-species mapping of candidate lncRNA to identify a consensus set of ruminant lncRNA and then used the RNA-seq data to demonstrate detectable and reproducible expression in each species. The majority of lncRNA were encoded by single exons, and expressed at < 1 TPM. In sheep, 20-30% of lncRNA had expression profiles significantly correlated with neighbouring protein-coding genes, suggesting association with enhancers. Alongside substantially expanding the ruminant lncRNA repertoire, the outcomes of our analysis demonstrate that stochastic sampling can be partly overcome by combining RNA-seq datasets from related species. This has practical implications for the future discovery of lncRNA in other species.

Download data

• Downloaded 453 times
• Download rankings, all-time:
  • Site-wide: 19,509 out of 57,294
  • In genomics: 2,275 out of 4,011
• Year to date:
  • Site-wide: 25,813 out of 57,294
• Since beginning of last month:
  • Site-wide: 30,831 out of 57,294

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide