Functional classification of plant long noncoding RNAs: a transcript is known by the company it keeps.
Leandro E LuceroLucía V FerreroCamille Fonouni-FardeFederico D ArielPublished in: The New phytologist (2020)
The extraordinary maturation in high-throughput sequencing technologies has revealed the existence of a complex network of transcripts in eukaryotic organisms, including thousands of long noncoding (lnc) RNAs with little or no protein-coding capacity. Subsequent discoveries have shown that lncRNAs participate in a wide range of molecular processes, controlling gene expression and protein activity though direct interactions with proteins, DNA or other RNA molecules. Although significant advances have been achieved in the understanding of lncRNA biology in the animal kingdom, the functional characterization of plant lncRNAs is still in its infancy and remains a major challenge. In this review, we report emerging functional and mechanistic paradigms of plant lncRNAs and partner molecules, and discuss how cutting-edge technologies may help to identify and classify yet uncharacterized transcripts into functional groups.
Keyphrases
- gene expression
- high throughput sequencing
- network analysis
- protein protein
- machine learning
- deep learning
- single molecule
- dna methylation
- genome wide analysis
- small molecule
- long non coding rna
- binding protein
- nucleic acid
- cell wall
- rna seq
- cell free
- multidrug resistant
- gram negative
- physical activity
- human immunodeficiency virus
- long noncoding rna
- plant growth