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Published on: May 9, 2020
Stress-responsive regulation of long non-coding RNA polyadenylation in Oryza sativa
Jiapei Yuan1, Jingrui Li1,2, Yang Yang1
1MOE Key Laboratory of Bioinformatics, Center for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Abstract:
Recently, long non-coding RNAs (lncRNAs) have been demonstrated to be involved in many biological processes of plants; however, a systematic study on transcriptional and, in particular, post-transcriptional regulation of stress-responsive lncRNAs in Oryza sativa (rice) is lacking. We sequenced three types of RNA libraries (poly(A)+, poly(A)- and nuclear RNAs) under four abiotic stresses (cold, heat, drought and salt). Based on an integrative bioinformatics approach and ~200 high-throughput data sets, ~170 of which have been published, we revealed over 7000 lncRNAs, nearly half of which were identified for the first time. Notably, we found that the majority of the ~500 poly(A) lncRNAs that were differentially expressed under stress were significantly downregulated, but approximately 25% were found to have upregulated non-poly(A) forms. Moreover, hundreds of lncRNAs with downregulated polyadenylation (DPA) tend to be highly conserved, show significant nuclear retention and are co-expressed with protein-coding genes that function under stress. Remarkably, these DPA lncRNAs are significantly enriched in quantitative trait loci (QTLs) for stress tolerance or development, suggesting their potential important roles in rice growth under various stresses. In particular, we observed substantially accumulated DPA lncRNAs in plants exposed to drought and salt, which is consistent with the severe reduction of RNA 3'-end processing factors under these conditions. Taken together, the results of this study reveal that polyadenylation and subcellular localization of many rice lncRNAs are likely to be regulated at the post-transcriptional level. Our findings strongly suggest that many upregulated/downregulated lncRNAs previously identified by traditional RNA-seq analyses need to be carefully reviewed to assess the influence of post-transcriptional modification.
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