Cotton Genomics and Genetics 2016, Vol.7, No.2, 1-23
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abundance of same members of miR482 highlights the need for more in-depth and detailed characterization of
stress-responsive miRNAs in plants, particularly in cotton.
Up regulation of all the 10 members of miR535 family were reported in this study in KC3-WS (Supplementary
Table 1). Similarly, miR535 was the most abundant miRNA in drought-exposed peach (Eldem et al., 2012). It has
been suggested that stress-regulated miRNAs might be regulated by stress-related transcription factors.
Interestingly, the promoters of miR535 in Arabidopsis contained all of the stress-related cis-elements investigated,
including the drought-responsive element, low temperature-induced element, MYC-binding site, and MYB-
binding site (Abdel-Ghany and Pilon, 2008).
The most abundant conserved miRNA family that has highly induced in drought tolerant cotton cultivar KC3-WS
is miR750: there was 196.813 orders of magnitude of changes when compared with drought susceptible, Suvin. It
has been shown that expression of miR750 was the most abundant miRNA after infecting silkworm with
Bombyx
mori
cytoplasmic polyhedrosis virus and has six target genes including kinases (Wu et al., 2013). Nevertheless,
the role of miR750 in plant abiotic stress resistance is yet to be determined. Similarly, high accumulation of
several conserved miRNA families such as miR3027, miR3050, miR5176, miR7496, miR7499 and miR7500
(20.390, 15.514, 33.688, 6.660, 11.525 and 7.535 folds, respectively) were found in KC3-WS. However, their role
in drought or abiotic stress resistance in crop plants have not yet been reported. Thus, this study has identified
several drought responsive highly induced conserved miRNAs in cotton and they provided strong lead to
specifically characterize such miRNA roles in drought tolerance in plants, particularly in cotton.
Two members of miR2118 were up regulated in KC3-WS with maximum of 7.806 folds (Supplementary Table 1).
Similar kind of accumulation of miR2118 upon drought and ABA treatments in legumes were reported and
showed that they may target regulatory elements for cellular processes (Arenas-Huertero et al., 2009). In our
previous study in cotton, we have computationally identified miR2118 and established through
in silico
analysis
that miR2118 might be involved in abiotic stress resistance (Boopathi and Pathmanaban, 2012). In addition,
significant level of expression of miR2118 was reported in drought tolerant cowpea genotype (Barrera-Figueroa et
al., 2011) and it was also up regulated in response to drought stress in
Medicago truncatula
(Wang et al., 2011).
Further, it has been shown that miR2118 targets TIR-NBS-LRR domain protein, which usually expressed in
response to multiple abiotic stresses such as drought, cold, salinity and ABA (Wang et al., 2011; Mantri et al.,
2013).
More than six fold up regulation of two members of miR2949 and two fold induction of miR3476 were displayed
in KC3-WS (Supplementary Table 1). Though the role of miR2949 and miR3476 in drought tolerance has not
been reported in plants, high accumulation of miR2949 and miR3476 in cotton was predicted as positive
regulators of the process of fiber initiation (Wang et al., 2012) and somatic embryogenesis (Yang et al., 2013).
The increased rates of miRNA detection afforded by deep-sequencing technologies provide challenges to the level
of confidence required to annotate a sequence as a miRNA. A typical RNA deep-sequencing experiment will
identify millions of short sequences. Increased coverage results in detection of sequences of ever-lower abundance.
It therefore becomes more and more challenging to distinguish true miRNAs from fragments of other transcripts,
other short RNAs and spurious transcription. Guidelines for microRNA annotation were established in 2003
(Ambros et al., 2003), requiring evidence of expression of a ~22 nt sequence (for example, cloning, sequencing or
northern blot), together with evidence for a microRNA precursor structure (predicted stem–loop flanking the
mature sequence). Updated annotation criteria were recently suggested to distinguish microRNAs from other
classes of short RNAs in plants (Meyers et al., 2008). These standards have proved extremely powerful in
maintaining a clean data set of miRNA sequences for the community. The eukaryotic genome also contains
millions of predicted hairpins, so a flanking stem–loop structure should be considered necessary but not sufficient
to annotate a sequence as a miRNA. If poorly analysed, a single data set thus has the potential to generate a large
number of suspicious annotations, thus overwhelming the real miRNAs. However, correct interpretation of RNA
