Cotton Genomics and Genetics 2016, Vol.7, No.2, 1-23
9
sequence alone is sufficient for the identification of the physiologically relevant target genes (
e.g.,
hme-bantam by
Brennecke et al., 2003).
This study has helped to identify several drought responsive candidate miRNAs that has potential in revealing the
role of small RNA in drought tolerance in crop plants and cotton in particular. Among the several differentially
expressed conserved miRNAs, those that were found between KC3-WS and Suvin-WS has more pronounced role
in deciphering the molecular mechanism of drought resistance in cotton. The drought responsive miRNAs
identified in this study were also found to be associated with drought or other abiotic stresses elsewhere and they
were described hereunder.
The conserved miRNA, hme-bantam with 23 nt length has found to be highly down regulated (35.018 fold change
in RPKM reads; Supplementary Table 1) in the drought susceptible parent, Suvin. Bantam microRNA in
Heliconius melpomene
was predicted independently by two groups using computational approaches (Brennecke et
al., 2003; Lai et al., 2003). Northern blotting confirmed that hme-bantam with a 23 nt sequence was the most
commonly expressed. Interestingly, bantam microRNA simultaneously stimulates cell proliferation and prevents
apoptosis and targets the 3’ UTR of the pro-apoptotic gene
hid
in
Drosophila
. In addition to bantam miRNA,
miR2 family have also been shown to regulate the expression of the proapoptotic genes such as
reaper, grim
and
skl
and to limit apoptosis in
Drosophila
(Zhang and Cohan, 2013). Two members of miR2 was identified in this
study and both were highly down regulated (159.578 and 34.575 folds; Supplementary Table 1) in the drought
susceptible, Suvin.
Drosophila melanogaster
presents perhaps the most important model organism for
understanding the basic principles and molecular mechanisms of animal development. Similarly,
Drosophila
genetics has played an important role in understanding the functional roles of several animal and plant miRNAs.
Table 4 Putative novel miRNAs identified in this study that are differentially expressed between KC3-WS and Suvin-WS
S. No Contig number Mature sequence
Reads (RPKM)*
Fold Change
$
KC3-WS Suvin-WS
1.
Contig_4796
GCCUCCAGAAGAUACAUUAGCACCAUGGGAUAU
7.29372
5.46745
3.546 down
2.
Contig_8004
UGCCAAAUCAGGGAAGCGAAAG
6.7624
5.60693
2.227 down
3.
Contig_16568
UUUCCAUCAUAUUAUUCGCCAUG
17.41518 14.09761
9.969 down
4.
Contig_14218
AGAUGCAGUAUGGGUUGUGAUUGAUAAGCUAAC
7.27723
4.866
5.319 down
5.
Contig_15122
UGGAAGGUUUGGAGGAGAUUGA
6.61113
8.02587
2.666 up
6.
Contig_16528
GUAAGGGAGAUCUAGAUUCAUAA
13.88788 12.15502
3.323 down
7.
Contig_15303
CCAACGACCGAAGUUAUUGUUCC
7.44543
3.37123
16.844 down
8.
Contig_14086
AUCAACCGUGUUACUCUGUCUAAUC
8.45815
8.85407
1.315 up
9.
Contig_20063
UCUGUCGCAGGGGAGAUGGCUG
5.51943
3.37123
4.432 down
10.
Contig_15835
GAAGAGAUCACUUCUAUCUGU
6.58521
6.10724
1.392 down
11.
Contig_1094
GACACGAACACGUGUUGCUGCUCAACCACC
9.99151
11.22683
2.354 up
12.
Contig_8575
GUCACACACGGUCUAGACACACGCC
7.51461
7.53694
1.015 up
13.
Contig_16564
GAACCCUUUGUUGGAGAGUCC
8.33933
5.15551
9.087 down
14.
Contig_13633
UGUGUGUUUCGCGCGUGGACGACGUAA
7.42923
5.866
2.955 down
15.
Contig_17693
UUAUAGGUCUUUCAUUUAAAGU
9.24686
7.03592
4.629 down
16.
Contig_11693
UAUGACCUACAAGCUUACCGGAGA
8.47363
5.32543
8.865 down
17.
Contig_21397
UUGCAGUCGCAGAACUCCGUACCU
8.73666
7.54782
2.279 down
18.
Contig_18244
CAUUCCAGUGAUUUCCAGAGGC
8.59916
6.67335
3.799 down
19.
Contig_21146
AGUUCCUUCAAAUUCUUCAAC
10.00731 6.25504
13.475 down
20.
Contig_18155
AUUAAAGUAGUGUCCUGCAAACU
8.87607
3.80187
33.688 down
21.
Contig_15570
UGUGUUUCGCGCGUGGACGACG
10.88209 12.21473
2.518 up
