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. 2015 Feb;66(3):789-804.
doi: 10.1093/jxb/eru437. Epub 2014 Nov 4.

Deep sequencing reveals important roles of microRNAs in response to drought and salinity stress in cotton

Fuliang Xie  1 , Qinglian Wang  2 , Runrun Sun  3 , Baohong Zhang  4
Affiliations

Deep sequencing reveals important roles of microRNAs in response to drought and salinity stress in cotton

Fuliang Xie et al. J Exp Bot. 2015 Feb.

Abstract

Drought and salinity are two major environmental factors adversely affecting plant growth and productivity. However, the regulatory mechanism is unknown. In this study, the potential roles of small regulatory microRNAs (miRNAs) in cotton response to those stresses were investigated. Using next-generation deep sequencing, a total of 337 miRNAs with precursors were identified, comprising 289 known miRNAs and 48 novel miRNAs. Of these miRNAs, 155 miRNAs were expressed differentially. Target prediction, Gene Ontology (GO)-based functional classification, and Kyoto Encyclopedia of Genes and Genomes (KEGG)-based functional enrichment show that these miRNAs might play roles in response to salinity and drought stresses through targeting a series of stress-related genes. Degradome sequencing analysis showed that at least 55 predicted target genes were further validated to be regulated by 60 miRNAs. CitationRank-based literature mining was employed to determinhe the importance of genes related to drought and salinity stress. The NAC, MYB, and MAPK families were ranked top under the context of drought and salinity, indicating their important roles for the plant to combat drought and salinity stress. According to target prediction, a series of cotton miRNAs are associated with these top-ranked genes, including miR164, miR172, miR396, miR1520, miR6158, ghr-n24, ghr-n56, and ghr-n59. Interestingly, 163 cotton miRNAs were also identified to target 210 genes that are important in fibre development. These results will contribute to cotton stress-resistant breeding as well as understanding fibre development.

Keywords: Cotton; deep sequencing; drought; fibre; literature mining; microRNA; salinity..

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Figures

Fig. 1.
Fig. 1.
Size distribution of redundant and unique small RNA reads in cotton. (A and C) Size distribution of redundant small RNA reads from control, drought, and salt libraries. (B and D) Size distribution of unique small RNA reads from control, drought, and salt libraries. (C and D) Small RNA reads were fully mapped back to EST and GSS of upland cotton and the G. ramondii genome.
Fig. 2.
Fig. 2.
Distribution of miRNAs in control, drought, and salinity treatment. (A) Conserved miRNA families; (B) known miRNAs; (C) novel miRNAs.
Fig. 3.
Fig. 3.
Heatmaps of (A) the top 50 most abundant conserved miRNAs and (B) the top 50 most abundant novel miRNAs in control, salt, and drought libraries in cotton. Red, up-regulated; green, down-regulated.
Fig. 4.
Fig. 4.
Validation and comparison of the expression of 13 cotton miRNAs between qRT–PCR and small RNA sequencing. miRNA expression correlation between qRT–PCR and small RNA sequencing (A, drought versus control; B, salinity versus control). Fold change of miRNA expression relative to the control sample (C, qRT–PCR; and D, small RNA sequencing). qRT–PCR assay of the expression of each miRNA was performed on 10-day-old cotton seedlings in three biological replicates: control, drought, and salinity. The bar represents the standard deviation.
Fig. 5.
Fig. 5.
Cotton miRNA target alignment and its T-plot validated by degradome sequencing. (A) ghr-miR171a-g and contig7077 (Scarecrow-like protein 6-like); (B) ghr-miR390a-d and contig13815 (DEAD-box ATP-dependent RNA helicase 21-like); (C) ghr-miR395a/b and contig4429 (sulphate adenylyltransferase); and (D) ghr-miR172a/b/c/f and contig14537 (Avr9/Cf-9 rapidly elicited protein). Both the arrow and the dot represent the splice site on the miRNA target.
Fig. 6.
Fig. 6.
Top-ranked miRNA regulation networks involved in (A) drought response and (B) salinity response in cotton.
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