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Updated: Feb 20, 2026

Identification of Coding and Non-coding RNA Classes Expressed in Swine Whole Blood
Published on: November 28, 2018
A catalogue of novel bovine long noncoding RNA across 18 tissues
Lambros T Koufariotis1, Yi-Ping Phoebe Chen2, Amanda Chamberlain3
1College of Science, Health and Engineering, La Trobe University Bundoora, Melbourne, Victoria, Australia; Department of Environment and Primary Industries, AgriBio Bundoora, Melbourne, Victoria, Australia; Dairy Futures Co-operative Research Centre, Melbourne, Victoria, Australia.
Abstract:
Long non-coding RNA (lncRNA) have been implicated in diverse biological roles including gene regulation and genomic imprinting. Identifying lncRNA in bovine across many differing tissue would contribute to the current repertoire of bovine lncRNA, and help further improve our understanding of the evolutionary importance and constraints of these transcripts. Additionally, it could aid in identifying sites in the genome outside of protein coding genes where mutations could contribute to variation in complex traits. This is particularly important in bovine as genomic predictions are increasingly used in genetic improvement for milk and meat production. Our aim was to identify and annotate novel long non coding RNA transcripts in the bovine genome captured from RNA Sequencing (RNA-Seq) data across 18 tissues, sampled in triplicate from a single cow. To address the main challenge in identifying lncRNA, namely distinguishing lncRNA transcripts from unannotated genes and protein coding genes, a lncRNA identification pipeline with a number of filtering steps was developed. A total of 9,778 transcripts passed the filtering pipeline. The bovine lncRNA catalogue includes MALAT1 and HOTAIR, both of which have been well described in human and mouse genomes. We attempted to validate the lncRNA in libraries from three additional cows. 726 (87.47%) liver and 1,668 (55.27%) blood class 3 lncRNA were validated with stranded liver and blood libraries respectively. Additionally, this study identified a large number of novel unknown transcripts in the bovine genome with high protein coding potential, illustrating a clear need for better annotations of protein coding genes.
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