Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Jan 18:8:6.
doi: 10.3389/fpls.2017.00006. eCollection 2017.

Identification of Submergence-Responsive MicroRNAs and Their Targets Reveals Complex MiRNA-Mediated Regulatory Networks in Lotus (Nelumbo nucifera Gaertn)

Affiliations

Identification of Submergence-Responsive MicroRNAs and Their Targets Reveals Complex MiRNA-Mediated Regulatory Networks in Lotus (Nelumbo nucifera Gaertn)

Qijiang Jin et al. Front Plant Sci. .

Abstract

MicroRNAs (miRNAs) are endogenous non-coding RNAs with important regulatory functions in plant development and stress responses. However, their population abundance in lotus (Nelumbo nucifera Gaertn) has so far been poorly described, particularly in response to stresses. In this work, submergence-related miRNAs and their target genes were systematically identified, compared, and validated at the transcriptome-wide level using high-throughput sequencing data of small RNA, Mrna, and the degradome. A total of 128 known and 20 novel miRNAs were differentially expressed upon submergence. We identified 629 target transcripts for these submergence-responsive miRNAs. Based on the miRNA expression profiles and GO and KEGG annotation of miRNA target genes, we suggest possible molecular responses and physiological changes of lotus in response to submergence. Several metabolic, physiological and morphological adaptations-related miRNAs, i.e., NNU_far-miR159, NNU_gma-miR393h, and NNU_aly-miR319c-3p, were found to play important regulatory roles in lotus response to submergence. This work will contribute to a better understanding of miRNA-regulated adaption responses of lotus to submergence stress.

Keywords: Nelumbo nucifera; high-throughput sequencing; microRNAs; small RNA; submergence.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Length distribution (A), and composition (B) of the unique small RNA in Ck (control) and Sub (submergence) libraries.
Figure 2
Figure 2
Abundance of known (A) and novel (B) miRNAs in lotus in Ck (control) and Sub (submergence) treatment.
Figure 3
Figure 3
Differential expression of significantly changed known (A) and novel (B) miRNAs (>3-fold) comparing Sub (submergence treatment) vs. Ck (control) libraries.
Figure 4
Figure 4
Validation of differentially expressed miRNAs (A) and corresponding target genes (B) using RT-qPCR comparing Sub (submergence treatment) vs. Ck (control) in lotus. Data are mean ± SE of four independent experiments.
Figure 5
Figure 5
Heat map of expression of submergence-responsive miRNAs and corresponding target genes which were validated by degradome and transcriptome. Color scale represents normalized log2 transformed counts. Blue indicates low expression and red indicates high expression. Black indicates the genes that were not been detected.
Figure 6
Figure 6
GO classification of target genes for submergence responsive miRNAs identified in lotus. The number of genes for each Gene Ontology (GO) term from each gene category.
Figure 7
Figure 7
The most enriched KEGG pathways of target genes for differentially expressed miRNAs.
Figure 8
Figure 8
The potential regulating network of submergence-responsive miRNAs in lotus. Red triangle, down-regulated miRNAs; Green triangle, up regulated miRNAs. Blue circle, mRNAs. MA, Morphological adaptation; ST, Stress tolerance; EB, Enhancement of breakdown of starch; DE, Decrease in biosynthesis of starch; PP, Plant-pathogen interaction.

Similar articles

Cited by

References

    1. Addo-Quaye C., Eshoo T. W., Bartel D. P., Axtell M. J. (2008). Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome. Curr. Biol. 18, 758–762. 10.1016/j.cub.2008.04.042 - DOI - PMC - PubMed
    1. Addo-Quaye C., Miller W., Axtell M. J. (2009). CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets. Bioinformatics 25, 130–131. 10.1093/bioinformatics/btn604 - DOI - PMC - PubMed
    1. Ambros V., Bartel B., Bartel D. P., Burge C. B., Carrington J. C., Chen X., et al. . (2003). A uniform system for microRNA annotation. RNA 9, 277–279. 10.1261/rna.2183803 - DOI - PMC - PubMed
    1. Arazi T., Talmor-Neiman M., Stav R., Riese M., Huijser P., Baulcombe D. C. (2005). Cloning and characterization of micro-RNAs from moss. Plant J. 43, 837–848. 10.1111/j.1365-313X.2005.02499.x - DOI - PubMed
    1. Asha S., Nisha J., Soniya E. (2013). In silico characterisation and phylogenetic analysis of two evolutionarily conserved miRNAs (miR166 and miR171) from Black Pepper (Piper nigrum L.). Plant Mol. Biol. Rep. 31, 707–718. 10.1007/s11105-012-0532-5 - DOI

LinkOut - more resources