Combinations of Small RNA, RNA, and Degradome Sequencing Uncovers the Expression Pattern of microRNA–mRNA Pairs Adapting to Drought Stress in Leaf and Root of Dactylis glomerata L.

Abstract

Drought stress is a global problem, and the lack of water is a key factor that leads to agricultural shortages. MicroRNAs play a crucial role in the plant drought stress response; however, the microRNAs and their targets involved in drought response have not been well elucidated. In the present study, we used Illumina platform () and combined data from miRNA, RNA, and degradome sequencing to explore the drought- and organ-specific miRNAs in orchardgrass (Dactylis glomerata L.) leaf and root. We aimed to find potential miRNA–mRNA regulation patterns responding to drought conditions. In total, 519 (486 conserved and 33 novel) miRNAs were identified, of which, 41 miRNAs had significant differential expression among the comparisons (p < 0.05). We also identified 55,366 unigenes by RNA-Seq, where 12,535 unigenes were differently expressed. Finally, our degradome analysis revealed that 5950 transcripts were targeted by 487 miRNAs. A correlation analysis identified that miRNA ata-miR164c-3p and its target heat shock protein family A (HSP70) member 5 gene comp59407_c0 (BIPE3) may be essential in organ-specific plant drought stress response and/or adaptation in orchardgrass. Additionally, Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses found that “antigen processing and presentation” was the most enriched downregulated pathway in adaptation to drought conditions. Taken together, we explored the genes and miRNAs that may be involved in drought adaptation of orchardgrass and identified how they may be regulated. These results serve as a valuable genetic resource for future studies focusing on how plants adapted to drought conditions.

Unique miRNAs and their targets in tomato leaf responding to combined drought and heat stress

“…Of the miRNAs, 21-nt miRNAs (42.7%) were most abundant followed by 24-nt miRNAs (35.0%) ( Fig. 2a), representing the predominant length of mature miRNAs in plant species, which was also reported by Zhou et al, (2016) [6] and Ji et al (2018) [7]. Usually, the mature miRNA were incorporated into argonaute (AGO) to form the RNA-induced silencing complex (RISC), resulting in mRNAs cleavage in plant [5,19].…”

“…Due to extensive complementarity between miRNAs and target genes, the miRNA regulates gene expression by target cleavage in plants [5]. The miRNAs-mRNAs relationship has been widely identified by dengradome sequencing in various crops, such as tomato [6] and orchard grass [7]. Active response of miRNAs and mRNAs in plants has been widely associated to individual abiotic stress, including drought condition [7,8] and high temperature [6].…”

“…The miRNAs-mRNAs relationship has been widely identified by dengradome sequencing in various crops, such as tomato [6] and orchard grass [7]. Active response of miRNAs and mRNAs in plants has been widely associated to individual abiotic stress, including drought condition [7,8] and high temperature [6]. It was found that 111 miRNAs were predominantly expressed in wheat after dehydration caused by polyethylene glycol (PEG) solution for 12 h [8], while 41 miRNAs were responsive to 18 days of individual drought condition in orchard grass and 5950 genes were targeted by 487 miRNAs [7].…”

“…Active response of miRNAs and mRNAs in plants has been widely associated to individual abiotic stress, including drought condition [7,8] and high temperature [6]. It was found that 111 miRNAs were predominantly expressed in wheat after dehydration caused by polyethylene glycol (PEG) solution for 12 h [8], while 41 miRNAs were responsive to 18 days of individual drought condition in orchard grass and 5950 genes were targeted by 487 miRNAs [7]. Moreover, 96 and 150 miRNAs exhibited different expression levels in heat-tolerant wild tomato at moderately (33°C) and acutely elevated temperature (40°C) for 8 h [6].…”

Prediction and Characterization of miRNA/Target Pairs in Non‐Model Plants Using RNA‐seq

“…This protocol is based on our previous work to identify defense-associated miRNA/target pairs in the non-model plant Phytolacca americana (Neller, Klenov, & Hudak, 2016, 2018. To provide greater context for the reader, we carry out the bioinformatic workflow using an example RNA-seq dataset that was generated by random sampling of our published data.…”