Analysis of Rice Transcriptome Reveals the LncRNA/CircRNA Regulation in Tissue Development

Abstract

Background Long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) can play important roles in many biological processes. However, no study of the influence of epigenetics factors or the 3D structure of the genome in their regulation is available in plants. Results In the current analysis, we identified a total of 15,122 lncRNAs and 7902 circRNAs in three tissues (root, leaf and panicle) in the rice varieties Minghui 63, Zhenshan 97 and their hybrid Shanyou 63. More than 73% of these lncRNAs and parental genes of circRNAs (P-circRNAs) are shared among Oryza sativa with high expression specificity. We found that, compared with protein-coding genes, the loci of these lncRNAs have higher methylation levels and the loci of circRNAs tend to locate in the middle of genes with high CG and CHG methylation. Meanwhile, the activated lncRNAs and P-circRNAs are mainly transcribed from demethylated regions containing CHH methylation. In addition, ~ 53% lncRNAs and ~ 15% P-circRNAs are associated with transposable elements (TEs), especially miniature inverted-repeat transposable elements and RC/Helitron. We didn’t find correlation between the expression of lncRNAs and histone modifications; however, we found that the binding strength and interaction of RNAPII significantly affects lncRNA expression. Interestingly, P-circRNAs tend to combine active histone modifications. Finally, we found that lncRNAs and circRNAs acting as competing-endogenous RNAs have the potential to regulate the expression of genes, such as osa-156 l-5p (related to yield) and osa-miR444a-3p (related to N/P metabolism) confirmed through dual-luciferase reporter assays, with important roles in the growth and development of rice, laying a foundation for future rice breeding analyses. Conclusions In conclusion, our study comprehensively analyzed the important regulatory roles of lncRNA/circRNA in the tissue development of Indica rice from multiple perspectives.

Ribosome profiling reveals the translational landscape and allele-specific translation efficiency in rice

“…To understand the translation ability of widely distributed lncRNAs reported in our previous work (Zhou et al ., 2021), we re-identified the lncRNAs in MH63RS3 genome with the same pipeline and predicted their coding potential. In total, only 4.95% (668) of all lncRNAs with one or more active ORFs could be translated (Figure 4A, Data S4), suggesting that the identification of a majority of lncRNAs in our previous study is reliable and the translation of lncRNAs is not universal in rice.…”

“…Five types of lncRNAs were previously classified and we found that 60.3% of active ORFs were derived from long intergenic noncoding RNAs (lincRNAs), followed by long noncoding natural antisense transcripts (lncNATs; 23.4%; Figure 4C). Considering the poor conservation of lncRNAs among varieties (Zhou et al ., 2021), and the relatively large number of shared active translational ORFs among varieties and tissues (Figure S5A), we speculate that these lncRNAs may have similar functions to protein-coding genes.…”

“…All fresh samples were immediately frozen in −80°C liquid nitrogen until use. The RNA-seq library construction and sequencing were performed as described in our early work (Zhou et al ., 2021). The Ribo-seq library construction was carried out according to a previous study (Ingolia et al ., 2012), and more details are described in Methods S1.…”

Identification of the Complex Interplay Between Nematode-Related lncRNAs and Their Target Genes in Glycine max L.

“…Some plant species represented the remarkable proportion of TE-lncRNAs. For instance, 65% of Zea mays lncRNAs (Lv et al, 2019) and 53% of Oryza sativa lncRNAs (Zhou et al, 2021) contained sequences that appear to be derived from TEs. On the other hand, some plant species, such as Brachypodium distachyon with 8% (De Quattro et al, 2017), Aegilops tauschii with 19%, and Triticum urartu with 27% (Pieri et al, 2018), exhibited less proportion of lncRNAs which can be attributed to TEs.…”

Integrated Lipidomic and Transcriptomic Analysis Reveals Lipid Metabolism in Foxtail Millet (Setaria italica)

“…Transcriptomic sequencing can be used to sequence almost all transcripts in specific biological tissues or cells at a certain period. Additionally, it can be applied to study gene expression, structure, variable splicing and to predict new transcription ( Patel et al, 2021 ; Sun et al, 2021 ; Wang et al, 2021 ; Zhou et al, 2021 ). Fei et al (2020) employed transcriptome sequencing and RT-qPCR to determine the expression levels of 20 genes related to fatty acid synthesis in Zanthoxylum bungeanum seeds, the results of intergroup correlation and RDA analysis suggested that ENR , ECR , and SAD1 are the key genes in fatty acid synthesis.…”