ORIGINAL RESEARCH
published: 09 July 2015
doi: 10.3389/fpls.2015.00506
Edited by:
Rajeev K. Varshney,
International Crops Research Institute
for the Semi-Arid Tropics, India
Reviewed by:
Eduard Akhunov,
Kansas State University, USA
Manoj K. Sharma,
Jawaharlal Nehru University, India
*Correspondence:
Kailash C. Bansal,
Indian Council of Agricultural
Research-National Bureau of Plant
Genetic Resources (NBPGR), IARI
Pusa Campus,
New Delhi 110012, India
kailashbansal@hotmail.com
Identification of novel
drought-responsive microRNAs and
trans-acting siRNAs from Sorghum
bicolor (L.) Moench by
high-throughput sequencing analysis
Amit Katiyar 1, 2 † , Shuchi Smita 1, 2 † , Senthilkumar K. Muthusamy 3 † ,
Viswanathan Chinnusamy 4 , Dev M. Pandey 2 and Kailash C. Bansal 1*
1
Indian Council of Agricultural Research-National Bureau of Plant Genetic Resources, New Delhi, India, 2 Department of
Biotechnology, Birla Institute of Technology, Mesra, Ranchi, India, 3 Indian Council of Agricultural Research-National Research
Centre on Plant Biotechnology, New Delhi, India, 4 Division of Plant Physiology, Indian Council of Agricultural Research-Indian
Agricultural Research Institute, New Delhi, India
†
Present Address:
Amit Katiyar,
Department of Biophysics, All India
Institute of Medical Sciences,
New Delhi, India
Shuchi Smita,
Centre for Agricultural Bio-Informatics,
Indian Council of Agricultural
Research-Indian Agricultural Statistics
Research Institute, New Delhi, India
Senthilkumar K. Muthusamy,
Division of Crop Improvement, Indian
Council of Agricultural
Research-Indian Institute of Wheat
and Barley Research, Karnal, India
Specialty section:
This article was submitted to
Plant Genetics and Genomics,
a section of the journal
Frontiers in Plant Science
Received: 24 February 2015
Accepted: 23 June 2015
Published: 09 July 2015
Citation:
Katiyar A, Smita S, Muthusamy SK,
Chinnusamy V, Pandey DM and
Bansal KC (2015) Identification of
novel drought-responsive microRNAs
and trans-acting siRNAs from
Sorghum bicolor (L.) Moench by
high-throughput sequencing analysis.
Front. Plant Sci. 6:506.
doi: 10.3389/fpls.2015.00506
Small non-coding RNAs (sRNAs) namely microRNAs (miRNAs) and trans-acting small
interfering RNAs (tasi-RNAs) play a crucial role in post-transcriptional regulation of gene
expression and thus the control plant development and stress responses. In order to
identify drought-responsive miRNAs and tasi-RNAs in sorghum, we constructed small
RNA libraries from a drought tolerant (M35-1) and susceptible (C43) sorghum genotypes
grown under control and drought stress conditions, and sequenced by Illumina Genome
Analyzer IIx. Ninety seven conserved and 526 novel miRNAs representing 472 unique
miRNA families were identified from sorghum. Ninety-six unique miRNAs were found to
be regulated by drought stress, of which 32 were up- and 49 were down-regulated (fold
change ≥ 2 or ≤ −2) at least in one genotype, while the remaining 15 miRNAs showed
contrasting drought-regulated expression pattern between genotypes. A maximum of
17 and 18 miRNAs was differentially regulated under drought stress condition in the
sensitive and tolerant genotypes, respectively. These results suggest that genotype
dependent stress responsive regulation of miRNAs may contribute, at least in part,
to the differential drought tolerance of sorghum genotypes. We also identified two
miR390-directed TAS3 gene homologs and the auxin response factors as tasi-RNA
targets. We predicted more than 1300 unique target genes for the novel and conserved
miRNAs. These target genes were predicted to be involved in different cellular, metabolic,
response to stimulus, biological regulation, and developmental processes. Genome-wide
identification of stress-responsive miRNAs, tasi-RNAs and their targets identified in this
study will be useful in unraveling the molecular mechanisms underlying drought stress
responses and genetic improvement of biomass production and stress tolerance in
sorghum.
Keywords: sorghum, microRNAs, tasiRNA, drought, next-generation sequencing, transcriptome
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microRNAs and trans-acting siRNAs from Sorghum bicolor
Introduction
a sequential alphabetical suffix (for more details please refer to
Meyers et al., 2008).
Nearby 7000 plant miRNAs have been deposited in the
miRBase 21, including 427 from Arabidopsis, 713 from rice, 321
from maize, 241 from sorghum and 525 from brachypodium.
Compared with the number of miRNAs identified in rice,
miRNAs reported in sorghum are very less. This suggests the
potential for identification of many more miRNAs. Sorghum crop
is highly tolerant to drought and heat stress, and the extension
of MIR gene family members, including miR169 family, was
suggested as one of the possible reasons for adaptation of
sorghum to abiotic stresses (Paterson et al., 2009). Recently,
small RNA sequencing approaches has been used to identify
spatial and temporal expression pattern of miRNAs in sweet
sorghum (Calviño et al., 2011; Zhang et al., 2011a). However,
no drought stress regulated miRNAs and tasi-RNAs have been
identified so far either through experimental or computational
approaches in sorghum. To date, only four TAS families (TAS1,
TAS2, TAS3, and TAS4) targeted by three miRNAs miR173,
miR828, and miR390 have been identified in Arabidopsis. For
the identification of genotype-specific and drought-responsive
miRNAs, we constructed a small RNA library using RNA samples
of two genotypes namely M35-1 (drought tolerant/DT) and
C43 (drought susceptible/DS) grown under control and drought
stress conditions. The miRNAs and tasi-RNAs were identified
by sequencing the small RNA libraries using the Solexa deep
sequencing technology combined with bioinformatics analysis.
The comprehensive profile of miRNAs and tasi-RNAs, and their
regulatory cascades in sorghum identified in this study will
provide a basic platform for genetic improvement of sorghum.
Sorghum (Sorghum bicolor (L.) Moench) is the 4th most
important nutritious cereal crop of the world after wheat, rice
and maize. Sorghum is widely grown for food, feed, fiber
and fuel and serve as a major staple food crop of millions
of people, especially in semi-arid tropics including Africa,
China, India, Mexico and USA. Drought is one of the major
agronomic problems contributing to severe yield losses in
sorghum worldwide. Further significant reduction in average
yield has been reported due to the drought condition at flowering
and grain filling phases, ultimately leading to a reduction in the
grains number and size in sorghum. However, few genotypes
of sorghum are relatively drought tolerant and known for its
adaptation to water-limited environment (Ludlow and Muchow,
1990). Therefore, sorghum may serve as a model crop system
for understanding the physiological and molecular mechanisms
underlying drought tolerance. Dwindling fresh water resources
and projected increase in incidences of drought under global
climate change scenario warrant development of climate resilient
sorghum varieties and hybrids. This necessitates a thorough
understanding of the mechanisms of the physiological and
molecular levels that contribute to drought tolerance. The
interplay between drought and changes in gene expression
has been studied only a few instances in sorghum (Buchanan
et al., 2005). Therefore, molecular analysis of gene expression in
sorghum needs further studies.
Several classes of small RNAs (sRNAs) regulate gene
expression in plants. These include miRNAs (microRNAs),
nat-miRNAs (natural antisense miRNAs), hc-siRNAs
(heterochromatic small interfering RNAs), tasi-RNAs (transacting small interfering RNAs), nat-siRNAs (natural antisense
small interfering RNAs), and ra-siRNAs (repeat-associated small
interfering RNAs). These sRNAs are involved in growth and
differentiation, genome stability, gene expression and defense
in plants. miRNAs are coded by MIR (MICRORNA) genes in
plants. MIR genes are transcribed by RNA Pol II. The 5′ methyl
capped and 3′ polyadenylated pri-miRNA transcripts forms
stem-loop secondary structures, and these processed into mature
miRNAs of typically ∼21 nt length by DCL1-SE-HYL1 complex.
The biogenesis of tasi-RNAs is triggered by the miRNA that
targets the TAS (tasi-RNA producing locus) gene transcripts
(Allen et al., 2005). Based on the similarity of the mature miRNA
sequence, the miRNA (MIR) genes coding for identical or nearly
identical mature miRNAs are grouped in to same family. For
naming the miRNA in the same family usually zero to two
mismatches are considered. Different MIR genes code for same
family of miRNAs, the loci is named with the same number and
Materials and Methods
Plant Materials and Stress Treatment
Sorghum [Sorghum bicolor (L.) Moench] seeds of two genotypes
i.e., M35-1 (drought tolerant/DT) (Jogeswar et al., 2006) and
C43 (drought susceptible/DS) (Mukri et al., 2010) were obtained
from the Indian Institute of Millets Research (formerly known as
Directorate of Sorghum Research), Hyderabad, India. Plants were
grown at 28–32◦ C day/night temperature with 12/12 h light/dark
period in the National Phytotron Facility of Indian Agricultural
Research Institute, New Delhi, India. Plants of both genotypes
were irrigated alternately with water and Hoagland’s solution
at 3 days interval. Thirty days after sowing, drought stress was
imposed by withholding irrigation to one set of plants (drought
stressed) until the leaf relative water content reached to about 60–
65% in both the genotypes. Thus the level of stress experienced
by plants measured as RWC was similar in both the genotypes.
The fully opened uppermost leaves from untreated (control) and
treated (drought stressed) seedlings were harvested, frozen in
liquid nitrogen and stored at −80◦ C in the same day for the
construction of small RNA libraries.
Abbreviations: AGO, ARGONAUTE; ARF, auxin response factor; DCL, dicerlike protein; DCL1, endoribonuclease Dicer-like 1; DS, drought susceptible;
dsRNAs, double-stranded RNAs; DT, drought tolerant; GO, gene ontology; MFEI,
minimal folding free energy index; miRNA, microRNA; NGS, next-generation
sequencing; PTGS, post-transcriptional gene silencing; RdRP, RNA-dependent
RNA polymerase; RISC, RNA-induced silencing complex; RWC, relative water
content; siRNA, small interfering RNA; sRNA, small RNA; tasi-RNA, trans-acting
siRNAs; TFs, transcription factors; TPM, transcript per million genome-matched
reads; UTR, untranslated region.
Frontiers in Plant Science | www.frontiersin.org
Small RNA Library Construction and Sequencing
Total RNA was isolated from the leaves using the TRIzol reagent
(Invitrogen, USA), according to the manufacturer’s protocol.
The RNA quality was examined using gel electrophoresis
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microRNAs and trans-acting siRNAs from Sorghum bicolor
Differential Expression Analysis of miRNAs
(28S:18S > 1.5) and Bioanalyzer (Agilent 2100, RIN = 8.0). Small
RNA sequencing libraries were prepared using Illumina Truseq
small RNA library preparation kit following manufacturer’s
protocol. Briefly, one microgram of total RNA was ligated
with 3′ Illumina RNA adapter using Truncated T4RNA Ligase
(NEB), followed by 5′ RNA adapter ligation and RT-PCR. The
PCR amplicons were separated in a 6% PAGE along with a
custom size ladder to select small RNA fraction. The final library
was quantified using Agilent Bioanalyser DNA1000 chip and
normalized to 10 nM. Seven pM concentration of the small RNA
library was used for cluster generation and sequencing analysis
(by Sandor Pvt. Ltd., Hyderabad, India) using the Illumina
Genome Analyzer IIx according to the manufacturer’s protocol
(Illumina Inc., USA). The Illumina FASTQ files generated from
this study have been submitted to the EMBL-EBI ArrayExpress
(https://www.ebi.ac.uk/arrayexpress) with the accession number
E-MTAB-1630.
To compare abundance of miRNAs in control and treatment
library, the count of each miRNA was normalized to transcripts
per million (TPM) following appropriate statistical method
(Audic and Claverie, 1997). (i) Normalization criterion: TPM
= (actual miRNA count/total count of clean reads)∗ 1,000,000.
Afterwards, the fold-change and P-value of the normalized
expression were calculated by using the following formula,
(ii) Fold-change criterion: Fold change = log2 (miRNA TPM
in the treatment library/miRNA TPM in the control library),
(iii) P-value: The P-value of precursor miRNA candidate was
tested using randfold (using a cutoff of 0.1) tool (Bonnet
et al., 2004) and integrated on the UEA sRNA workbench.
The Poisson distribution model was used for estimating the
statistical significance of miRNA expression changes under
control and treatment conditions. Upregulation of any miRNA
expression levels was considered a positive value, while negative
values indicate down-regulation. To identify drought-responsive
miRNAs, several standards (Eldem et al., 2012) were followed as:
(1) normalized count was at least 1 TPM in either control or
stress library; (2) P-value = 0.01 as the threshold; (3) log2 ratio
of the normalized count under stress or control libraries was >1
or < −1. Unique (active form of the miRNA) or identical mature
miRNAs, generated from two or more homologous miRNA genes
were only considered for differential expression analysis.
Bioinformatics Analysis of sRNA Sequences
Adaptor and low-quality sequences were trimmed as suggested
by Sunkar et al. (2008). Sunkar et al. (2008) by using the
“sequence file pre-processing tool” from UEA sRNA workbench
V2.5.0-Plant version (http://srna-tools.cmp.uea.ac.uk/) (Stocks
et al., 2012). High quality trimmed sequences (reads with no
“N,” no more than 6 bases with quality score <13) with a length
of 16–30 nt were further subjected to remove, if mapped with
plant t/rRNAs from “Rfam” (excepted miRNAs), Arabidopsis
tRNAs from “The Genomic tRNA Database,” and plant t/rRNA
sequences from “EMBL release 95” by using the “filter tool” from
UEA sRNA workbench V2.5.0-Plant version.
Tasi-RNA Analysis
To detect phased small RNA clusters corresponding to tasiRNAs, the “The UEA Small RNA Workbench V2.5.0” (http://
srna-workbench.cmp.uea.ac.uk/tools/ta-si-prediction/) (Stocks
et al., 2012) was used. Small RNAs (sRNAs) that are not identical
to the genome were rejected. A minimum abundance 2 and
p-value threshold of 0.0001 was used to detect statistically
significant clusters. Potential phase-initiators for these TASs were
predicted by using psRobot program (http://omicslab.genetics.
ac.cn/psRobot/) (Wu et al., 2012) and psRNATarget program
(http://plantgrn.noble.org/psRNATarget/) (Dai and Zhao, 2011)
with default parameters and an assumption that the 10th
nucleotide position on the sRNA serving as the phase-initiator
corresponds to the cleavage start position of its targeted TAS.
The overlapping TAS on chromosome was merged as a single
cluster. The identical tasi-RNAs within TAS gene were removed
and retain only unique tasi-RNAs for further analysis.
Prediction of Conserved and Novel miRNA
Members in Sorghum
The unique reads were submitted to the miRCat pipeline (UEA
sRNA workbench V2.5.0-Plant version). The miRCat (miRNA
Categorization) was run with the following parameters: The
minimum sRNA abundance: 1 read; the minimum sRNA size:
16 nt; the maximum sRNA size: 30 nt, the minimum length
of hairpin: 60 nt; the maximum number genome hits: 16. The
100 nt flanking regions of aligned reads were extracted from
the genome and folded using RNAfold (http://rna.tbi.univie.ac.
at/cgi-bin/RNAfold.cgi). The miRCat trimmed and analyzed the
resulting secondary structure to verify the characteristic miRNA
as per the plant miRNAs annotation criteria (Meyers et al., 2008)
and executed the following additional checks: (1) The miRNA
and miRNA∗ are derived from opposite stem-arms and form
a duplex with two nucleotide 3′ overhangs. (2) The number of
mismatches between miRNA and miRNA∗ should be less than or
equal to four. (3) The frequency of asymmetric bulges is one or
less and size of the bulge is no more than 2 nucleotides within the
miRNA/ miRNA∗ duplex. The maximum number of occurrences
(reads) for a particular miRNA family was denoted as miRNA
abundance. The folding structure of precursors was examined
using RNA folding/annotation tool (UEA sRNA workbench
V2.5.0-Plant version) that uses the Vienna Package to obtain the
secondary structure of a precursor sequence and highlighting up
miRNA/miRNA∗ sequences on hairpin structure.
Frontiers in Plant Science | www.frontiersin.org
Target Gene Prediction
The potential targets of sorghum miRNAs were predicted using
the psRobot; plant small RNA analysis toolbox (http://omicslab.
genetics.ac.cn/psRobot/) (Wu et al., 2012) with strict parameters
and psRNATarget (http://plantgrn.noble.org/psRNATarget/)
(Dai and Zhao, 2011) with default parameters. For psRobot
program, we used the following parameters for the target
prediction- Penalty score threshold: 3.0; Five prime boundary
of essential sequence: 1; Three prime boundary of essential
sequence: 31; Maximal number of permitted gaps: 0; Position
after which with gaps permitted: 1. For psRNATarget program,
we used the following standards for the target predictionMaximum expectation: 3.0; Length for complementarity scoring
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microRNAs and trans-acting siRNAs from Sorghum bicolor
whereas 22,878,203 and 21,740,738 primary reads, respectively,
were generated under drought stress conditions. Initially, the
raw reads were filtered for possible adaptor contaminations
and subsequently mapped to the sorghum genome. For each
library, more than 90% reads were mapped to the genome,
suggesting slight contamination in library construction and
Illumina sequencing. The remaining raw reads (after adaptor
removal) were further filtered for poor quality sequences, invalid
sequences and sequences smaller than 16 nt and larger than
30 nt and as a result, a total of 9,472,887 clean reads were
obtained which represented 975,457 unique reads under irrigated
condition. Similarly, a sum of 7,296,968 clean reads with 944,141
unique reads were also determined from small RNA libraries
of drought stress treated seedlings (Table S1 in Supplementary
Material). The unique reads (after filtering out for t/rRNA
matches) from each library that perfectly mapped (with no
mismatch) to the sorghum genome represented the small RNA
(sRNA) population.
(hspsize): 20; Target accessibility (UPE): 25.0; Flanking length
around the target site for target accessibility analysis: 17; Range
of central mismatch leading to translational inhibition: 9–11 nt.
All the mutual and unique targets were accepted and listed in
this article. Further, all the targets regulated by sorghum miRNAs
identified in this study were subjected to AgriGO toolkit (http://
bioinfo.cau.edu.cn/agriGO/) (Du et al., 2010) to investigate gene
ontology enrichment. The singular enrichment analysis (SEA)
was performed to find enriched GO terms within annotated
miRNA targets.
RNA-Seq Library Construction, Sequencing, and
Data Analysis
One microgram of total RNA was used for the preparation
of RNA-Seq library using Illumina TruSeq mRNA library
preparation kit following the manufacturer’s protocol. In short,
poly-A RNA was isolated from total RNA and chemically
fragmented. First and second strand synthesis were followed by
end repair, and adenosines were added to the 3′ ends. Adapters
were ligated to the cDNA and 200 ± 25 bp fragments were
gel purified and enriched by PCR. The libraries generated were
quantitated using an Agilent Bioanalyzer (DNA 1000 kit; Agilent
Technologies, Santa Clara, CA) and a 2 × 101 cycle paired
end sequencing (sequenced by Sandor Pvt. Ltd., Hyderabad,
India) was performed using an Illumina HiScanSQ sequencer
(Illumina Inc.). Initially, raw reads were processed by the NGSQC
toolkit (http://www.nipgr.res.in/ngsqctoolkit.html) and high
quality reads were subjected to de-novo assembly using Trinity
assembler (Patel and Jain, 2012). Assembled transcripts were
quantified by standard pipeline (Trinity→RSEM→R→DESeq),
and those transcripts were removed, which has zero FPKM in
all four samples (Anders, 2010; Grabherr et al., 2011; Li and
Dewey, 2011). These transcripts were further processed by the
transdecoder tool to retrieve the full length coding sequence and
subsequent annotated by FastAnnotator (http://fastannotator.
cgu.edu.tw/) (Chen et al., 2012). Pathway enrichment analysis
was performed for the predicted transcripts by KEGG Automatic
Annotation Server (KAAS; www.genome.jp/tools/kaas/) for the
classification of spatial and temporal governed pathways. The
Illumina FASTQ files generated from this study have been
submitted to the EMBL-EBI ArrayExpress (https://www.ebi.ac.
uk/arrayexpress) with the accession number E-MTAB-3571.
Identification of Conserved and Novel miRNAs
To predict miRNAs, all unique reads (gained after filtering)
were submitted to the miRCat pipeline (UEA sRNA workbench
V2.5.0-Plant version) and were mapped (with no mismatch)
against the reference genome of sorghum. The 100 nt flanking
regions of aligned reads were extracted from the genome
and folded using RNAfold. The resulting secondary structures
(potential precursor) were then trimmed and analyzed by
miRCat. To recover the putative miRNA candidate, the potential
precursors were subjected to a series of stringent criteria
suggested for the annotation of plant miRNAs (Ambros et al.,
2003; Meyers et al., 2008; Kozomara and Griffiths-Jones,
2013). The probable miRNA candidates that perfectly matched
(miRNAs with ≤3 mismatches) with mature miRNAs of sorghum
in the miRBase 21 were acknowledged as known miRNAs.
The sequences that matched with miRBase entries of other
plant species were designated as conserved miRNAs. Finally,
the sequences that showed no homology to any previously
known and conserved plant miRNAs were denoted as novel
miRNA in sorghum. In this study, 97 miRNAs belonging to 26
miRNA families were found identical with the known miRNAs
of plant species in miRBase 21. Among these, 32 miRNAs were
perfectly matched with mature miRNAs of sorghum and the
remaining 65 miRNAs were highly conserved in other plant
species and hence are referred to as known and conserved
miRNAs, respectively (Table S2 in Supplementary Material).
In addition, a total of 526 miRNAs derived from 518 loci
identified in this study did not show sufficient homology with
any of previously reported plant miRNAs in miRBase 21, and
hence classified as novel miRNAs (Table S2 in Supplementary
Material). The identification of miRNA∗ candidates provided
further support to consider them as true miRNAs. In this study,
47 and 130 miRNA∗ were predicted from 97 conserved and 130
novel miRNAs, respectively. A close observation revealed that
541, 499, and 274 reads of miR167h∗ , miR169e∗ , and miR167d∗
accumulated, respectively. Likewise, 117, 63, and 47 reads of
novel miRNAs namely novel-sbi-miR-383∗ , novel-sbi-miR-77b∗ ,
and novel-sbi-miR-51∗ accumulated, respectively (Table S2 in
Results
Analysis of Small RNA Population in Sorghum
To identify drought stress regulated miRNAs from sorghum,
four libraries of small RNAs from two genotypes namely M351 (drought tolerant or DT) and C43 (drought susceptible
or DS) grown under irrigated and drought stress conditions
were constructed and sequenced independently. The relative
water content (RWC) of drought stressed seedlings were about
65% in both genotypes (Figure S1 in Supplementary Material),
indicating similar level of stress imposed to these genotypes. The
Solexa (Illumina) sequencing of small RNA libraries from M351 and C43 led to the generation of 19,821,595 and 18,890,943
primary reads, respectively, under well irrigated condition,
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microRNAs and trans-acting siRNAs from Sorghum bicolor
Supplementary Material). Furthermore, minimal folding free
energy index (MFEI), a sufficient criterion to distinguish miRNA
from coding mRNAs and non-coding RNA, i.e., tRNAs and
rRNAs, defines that a candidate RNA sequence is more likely
to be a miRNA when the MFEI is greater than 0.85 (Zhang
et al., 2006). In this study, 96.91% conserved (except for miR166f,
miR396f, and miR399b) and 58.56% novel pre-miRNAs of
sorghum had an MFEI = 0.85. Additionally, nucleotide bias
analysis showed that uracil was the most prominent nucleotide at
the beginning in 84 (86.60%) conserved and 177 (33.65%) novel
miRNAs. The pre-miRNAs of novel and conserved miRNAs bore
a canonical stem-loop structure with free energies ranging from
−16 to −131.8 kcal·mol−1 (average of −54.29 kcal mol−1 ). The
chromosomal distributions of predicted miRNAs are listed in
Figure 1.
was calculated to identify the normalized expression level. A
total of 96 unique miRNAs (fold change = 2), belongs to 8
known and 88 novel families, showed differential expression
under drought stress as compared to the control, in at least
one genotype (Figure 2; Table 1; Table S3 in Supplementary
Material). Out of the 96 drought stress regulated miRNAs, 23
and 9 miRNAs were up- and down-regulated, respectively, under
the drought stress, in both genotypes. Forty four miRNAs were
upregulated in drought tolerant M35-1, while these miRNAs were
downregulated in drought sensitive C43 genotype under drought
stress. In contrast, 19 miRNAs were downregulated in drought
tolerant M35-1, while these miRNAs were upregulated in drought
sensitive C43 genotype under drought stress. The novel-sbi-miR259 was undetectable in M35-1, while it was downregulated in
C43 (Figure 2; Table 1; Table S3 in Supplementary Material).
Drought-responsive and Genotype-specific
miRNA
Targets of Known and Novel miRNAs
Recently, 64 target genes for 17 miRNAs (Jiangfeng et al., 2010),
125 target genes for 42 miRNAs (Zhang et al., 2011a) and
72 potential target genes for 31 miRNAs (Katiyar et al., 2012)
were reported in sorghum. Here we identified more than 1300
unique potential targets for 49 conserved and 383 novel miRNA
families in sorghum (Table S4 in Supplementary Material). For
the remaining 96 new miRNAs, no target could be identified,
which might due to the stringency of target prediction used in
this study. The further BLAST analysis identified miRNA targets
homologous to conserved target genes of several plant species.
The putative target genes were considered to be a key factor in
a wide range of biological processes. Inconsistent with previous
reports (Rhoades et al., 2002; Bartel and Bartel, 2003; Song
et al., 2011), many of the miRNA target genes predicted in this
study encode transcription factors belonging to SPB, Zinc finger,
WRKY, WD-40, NAC, MYB, HSFs, GRAS, ARFs, and bHLH
families. Several targets for novel miRNAs identified in this study
were genes with unknown function. Further functional analysis
of miRNA-target gene pair will contribute to our understanding
of the role of these miRNAs in sorghum.
We compared the normalized count of each miRNAs in a stressed
library against the control library to compute the stress regulated
expression of miRNAs. The number of mature miRNAs per
million clean reads (known as transcripts per million or TPM)
Go Enrichment Analysis of miRNA Target Genes
Widely used standard for functional annotation and enrichment
analysis through gene ontology (GO) was carried out for more
than 1300 unique potential targets of 472 unique sorghum
miRNAs using AgriGO database (Du et al., 2010) with default
parameters. Significantly high percentages of these targets
were found to be involved in cellular, metabolic, response to
stimulus, biological regulation, and developmental processes
(Figure 3). Further dissection of “response to stimulus” led
to the identification of seven genes with over-represented GO
term “response to water deprivation” (GO: 0009414), one
with “response to water stimulus” (GO: 0009415), five with
“response to heat” (GO: 0009408) and two with “response to
heat acclimation” (GO: 0010286) (Figure S3 in Supplementary
Material; Table S5 in Supplementary Material). To explore the
modulated biological processes between tolerant and sensitive
genotypes under drought stress, differentially expressed genes
regulated by miRNAs specific to drought tolerant and sensitive
genotypes were analyzed separately using GO term enrichment
FIGURE 1 | Distribution of predicted miRNAs. Chromosomal distribution
(A) showed that the maximum numbers of miRNAs were predicted from
chromosome 1 and 4. Distribution of conserved miRNAs (B) showed that
miR169, miR166, and miR167 were the most abundant miRNAs in sorghum
genome.
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microRNAs and trans-acting siRNAs from Sorghum bicolor
and tolerant genotypes of sorghum are given in (A) with the
confidence of P ≤ 0.05. The numbers of extended drought-responsive
miRNAs with the confidence of ≥5 reads at least in one genotype
are illustrated in (B).
FIGURE 2 | The Venn diagram illustrates the numbers of
common and unique differentially expressed miRNAs induced by
drought stress. Up- and Down-regulated miRNAs (≥2 or ≤ −2 fold
changes) under the control and drought stages of drought-susceptible
miR529, novel-sbi-miR-111, novel-sbi-miR-120a-b, novel-sbimiR-227a-c, novel-sbi-miR-268, novel-sbi-miR-376, and novelsbi-miR-350 led to up-regulation of their target gene. The lists
of differentially expressed target genes under drought stress are
listed in Table S6 in Supplementary Material.
analysis. Gene ontology enrichment analysis was performed
using an FDR-adjusted p-value of ≤0.05 to select pathways that
were statistically enriched with miRNA targets. The significantly
enriched GO terms, including response to abiotic stimulus,
response to stress, response to stimulus, response to external
stimulus, response to organic substances, response to starvation,
response to hormone stimulus, response to gravity, response
to endogenous stimulus, response to chemical stimulus, and
response to auxin stimulus were found among the up- or
down-regulated genes in at least one genotype of sorghum
(Table S5 in Supplementary Material). Interestingly, three stressrelated biological process GO terms varied significantly between
tolerant and sensitive genotypes under drought stress. We
noticed that GO terms “response to inorganic substance” (GO:
0010035, FDR p-value = 0.038) and “response to stress” (GO:
0006950, FDR p-value = 0.024) were significantly enriched only
in sensitive genotype, whereas “response to abiotic stimulus”
(GO: 0009628, FDR p-value = 0.045) only in tolerant genotype
under drought stress. The results indicate that the inherent
preparedness and responsiveness of tolerant cultivar toward
drought stress is much higher as compared with sensitive
cultivar.
Identification of Sorghum Tass
Phase-initiators direct the cleavage of trans-acting siRNA (tasiRNA or TAS; a newly identified class of 21 nt short siRNAs) and
later initiate the production of tasi-RNA clusters. Initially, we
identified 135 unique clusters comprising 155 unique tasi-RNA
sequences. The predicted tasi-RNAs were found to be conserved
in plants. Further investigation revealed that six phase-initiators
(e.g., miR390, miR5567, miR5568, miR6220, miR6225, and
miR6230) directing 31 unique TASs lead to 64 unique tasi-RNAs
(Table S7 in Supplementary Material). The length of the phaseinitiator, a key determinant for triggering tasi-RNA biogenesis, is
usually 22 nt (except 21 nt long miR390) in Arabidopsis (Chen
et al., 2010). A similar exception was observed for sorghum
miR390 (21 nt long). The length of other phase-initiators varied
from 21 to 24 nt (e.g., 21/24 nt, miR5567; 21 nt, miR5568;
23/24 nt, miR6220, and 23/24 nt, miR6225). The variable length
of the phase-initiators suggests the cleavage of double-stranded
RNAs (dsRNAs) by multiple Dicer-like (DCL) proteins, thereby
generating siRNA classes with different sizes (Axtell, 2009).
Biogenesis of tasi-RNAs is dependent on miRNA triggers and
requires either dual miRNA target sites (known as “two-hit”
model) or single-target site (known as “one-hit” model) in the
non-coding RNA precursor (Axtell et al., 2006). While most of
the target genes were cleaved by only one miRNA at a single
recognition site, we identified two target sites for five TASs (e.g.,
sbiTAS_miR5567/6225a-d and sbiTAS_miR5568/6220a) (Figure
S2 in Supplementary Material). The length of each TAS in this
study is restricted to 251 bp and the corresponding P-values
varying from 4.47E-08 to 8.20E-05. The targets for tasi-RNAs
were predicted by degradome supported psRobot server with
default parameters. Predicted target genes for unique 64 tasiRNAs were found to be involved in plant development and stress
responses (Table S8 in Supplementary Material).
Digital Expression Analysis of miRNAs and their
Targets
To investigate the relationship between predicted miRNAs and
their targets, expression levels were calculated for randomly
selected 20 miRNAs (eight conserved and 12 novels) and their
corresponding target genes from small RNA and RNA-Seq
sequencing experiments, respectively. A negative correlation
(miRNA up, target gene down, and vice versa) was observed
between the expression levels of several up- or down-regulated
miRNAs and their targets (Figure 4). For instance, the induced
expression of miR156b, miR396b-c, miR396d-e, miR396f,
miR5385, novel-sbi-miR-46, novel-sbi-miR-48, novel-sbi-miR141, novel-sbi-miR-176, novel-sbi-miR-224, and a novel-sbimiR-335 resulted in enhanced level of accumulation of their
target genes under drought stress in DT-genotype. Conversely,
drought-induced down-regulation of miR156a, miR319a-b,
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TABLE 1 | Drought stress-responsive miRNAs (fold change >2 “at-lest” in one genotype) and their putative targets are listed.
S.No.
miRBase ID
M (DT)
C (DS)
Targets
UP-REGULATED UNDER DROUGHT IN BOTH M35-1 AND C43
1
novel-sbi-miR-44
N
N
Acyl-CoA N-acyltransferases (NAT) superfamily protein (Sb02g008700); Dicarboxylate diiron protein, putative (Crd1) (Sb03g011270); Glycosyl hydrolase 9B10
(Sb09g002490)
2
novel-sbi-miR-94
N
N
ATP/GTP-binding protein family (Sb10g022230); RING/FYVE/PHD zinc finger superfamily protein (Sb04g029710); fatty acid desaturase 8 (Sb02g043980)
3
novel-sbi-miR-105a-b
N
N
ATP binding cassette subfamily B4 (Sb02g019540, Sb03g023740); COBRA-like extracellular glycosyl-phosphatidyl inositol-anchored protein family
(Sb02g038740); F-box family protein (Sb04g026045, Sb09g018050); Leucine-rich repeat protein kinase family protein (Sb01g036160); RING-H2 group F2A
(Sb05g022230)
4
novel-sbi-miR-108
N
N
AUTOPHAGY 6 (Sb03g031280); GDSL-like Lipase/Acylhydrolase superfamily protein (Sb02g040890); methyl esterase 1 (Sb03g045050);NOP56-like pre RNA
processing ribonucleoprotein (Sb01g035410, Sb03g044260); peroxisomal ABC transporter 1 (Sb09g000670); zinc finger protein-related (Sb09g027620); SAR
DNA binding protein (TC121990); Polyubiquitin containing 7 ubiquitin monomers (CN152471, TC123393, TC127226, TC115840); GDSL-like
Lipase/Acylhydrolase family protein (TC117544)
5
novel-sbi-miR-114
N
N
DEAD/DEAH box RNA helicase family protein (Sb09g030730); Ethylene-responsive nuclear protein/ethylene-regulated nuclear protein (ERT2) (Sb08g022350);
Major facilitator superfamily protein (Sb01g004100); Pentatricopeptide repeat (PPR-like) superfamily protein (Sb06g026460); Stabilizer of iron transporter
SufD/Polynucleotidyl transferase (Sb01g011870); Serine/threonine protein phosphatase 3 (Sb10g004490); UDP-D-glucose/UDP-D-galactose 4-epimerase 5
(Sb07g018840)
6
novel-sbi-miR-131
N
N
Zinc finger (CCCH-type) family protein/RNA recognition motif (RRM)-containing protein (Sb06g014350); Ubiquitin-specific protease 26 (Sb08g014950); F-box
family protein (Sb08g004750); RmlC-like cupins superfamily protein (Sb04g019700); cAMP-regulated phosphoprotein 19-related protein (Sb03g000280)
7
7
novel-sbi-miR-141
N
N
Phosphoinositide 4-kinase gamma 7 (Sb02g027450); zinc transporter 1 precursor (Sb06g028270)
8
novel-sbi-miR-149
N
N
Fumarylacetoacetate (FAA) hydrolase family(Sb01g011570); RNA recognition motif (RRM)-containing protein (Sb02g020460); Zinc carboxy peptidase
(BM327804); Nucleoside diphosphate kinase (TC134154)
9
novel-sbi-miR-182a-b
N
N
Beta glucosidase 13/16 (Sb08g007570, Sb08g007586, Sb08g007650, Sb08g007610); NB-ARC domain-containing disease resistance protein
(Sb02g011040); NIMA-related kinase 2 (Sb01g013950); RNA polymerase II, Rpb4, core protein (Sb08g014990); RNA-binding KH domain-containing protein
(Sb03g038070); Serine hydroxymethyltransferase 4 (Sb08g019520); Xyloglucan endotransglucosylase/hydrolase 32 (Sb02g033240)
10
novel-sbi-miR-191
N
N
RNA polymerase II transcription mediators (Sb10g000410); VQ motif-containing protein (Sb01g005740); SPla/RYanodine receptor (SPRY) domain-containing
protein (Sb04g022720); Regulator of Vps4 activity in the MVB pathway protein (Sb03g031550); Ribosomal protein L10 family protein (Sb05g000460); WD-40
repeat family protein/beige-related (Sb04g032555); Transcription factor HBP-1a (bZIP) (TC118669); HAD-superfamily hydrolase (TC123668); RanBPM-like
(TC113595)
novel-sbi-miR-192
N
N
RPM1 interacting protein 13 (Sb01g019820)
novel-sbi-miR-205
N
N
WRKY DNA-binding protein 21 (Sb01g008550)
13
novel-sbi-miR-221a-h
N
N
Polypyrimidine tract-binding protein 2 (Sb03g028150)
14
novel-sbi-miR-224
N
N
Chitinase A (Sb02g004650); cytochrome P450, family 96, subfamily A, polypeptide 10 (Sb01g047610); Major facilitator superfamily protein (Sb09g020280);
Xylanase inhibitor protein 1 precursor (CD223557, TC116590, TC130018)
15
novel-sbi-miR-229
N
N
RNA-binding (RRM/RBD/RNP motifs) family protein (Sb02g034650); auxin response factor 11 (Sb03g000530); Pentatricopeptide repeat (PPR) superfamily
protein (Sb06g028710); formate dehydrogenase (Sb10g016920); Golgi-localized GRIP domain-containing protein (Sb02g033040)
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16
novel-sbi-miR-255
N
N
Lipase-like (TC116103)
17
novel-sbi-miR-263a-c
N
N
Hydrolase family protein/HAD-superfamily protein (Sb01g038800); lipase class 3 family protein(Sb04g019260, Sb06g020820); Protein kinase family protein with
leucine-rich repeat domain (Sb10g022060)
18
novel-sbi-miR-269
N
N
GDSL-like Lipase/Acylhydrolase superfamily protein (Sb03g027670); plastid division2 (Sb02g001890); Gnetum gnemon chloroplast psaC ccsA 4.5S rRNA 5S
rRNA 16S rRNA (partial) 23S rRNA and tRNA (AW286089)
19
novel-sbi-miR-313
N
N
FtsJ-like methyltransferase family protein (Sb09g028780); NAD(P)-binding Rossmann-fold superfamily protein (Sb01g029980); Glycosyltransferase (TC111346)
20
novel-sbi-miR-322
N
N
Phosphoglycerate/bisphosphoglycerate mutase family protein (Sb03g000470); Protein phosphatase 2A, regulatory subunit PR55 (Sb03g027000)
(Continued)
microRNAs and trans-acting siRNAs from Sorghum bicolor
11
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TABLE 1 | Continued
S.No.
miRBase ID
M (DT)
C (DS)
Targets
21
novel-sbi-miR-324
N
N
Protein kinase family protein with leucine-rich repeat domain (Sb08g005100)
22
novel-sbi-miR-337
N
N
SLOW GROWTH 1 (Sb08g008260); Peptidyl-prolyl cis-trans isomerase (TC114053)
23
novel-sbi-miR-383
N
N
Alpha/beta-Hydrolases1 superfamily protein(Sb04g002780); BolA-like (EH409271); 1-deoxy-D-xylulose 5-phosphate synthase 1-like (TC116788); squamosa
promoter binding protein-like 2/9/14 (Sb05g017510, Sb02g029300, Sb07g026220, Sb03g044160, Sb06g024630, Sb04g004940, Sb10g029190,
Sb04g003175, Sb02g028420, Sb07g027740)
DOWN-REGULATED UNDER DROUGHT IN BOTH M35-1 AND C43
miR169d-l
H
H
AAA-type ATPase family protein (Sb07g002080); nuclear factor Y, subunit A1/A3/A6/A7 (Sb01g011220, Sb01g011220, Sb01g045500, Sb08g021910,
Sb01g011220); CCAAT-box transcription factor (TC119556)
2
miR529
H
H
Squamosa promoter-binding proteins (Sb07g026220, Sb02g029300); protease-related (Sb09g024450); cellulose-synthase-like C12 (Sb09g025260);
development and cell death (DCD) domain protein (Sb02g011270); Ubiquitin fusion protein (TC113579)
3
novel-sbi-miR-57
H
H
Heavy metal atpase 5 (Sb04g006600)
4
novel-sbi-miR-111
H
H
Pumilio 1 (Sb09g001090); AMP-binding enzyme family protein (CF430224); YT521-B-like family protein (CD209184, TC112887, TC133512)
5
novel-sbi-miR-211
H
H
ACT-like protein tyrosine kinase family protein (Sb02g031600); BTB-POZ and MATH domain 2 (Sb10g026770); Cellulose synthase-like D5 (Sb02g036000,
Sb02g036010); HAT dimerization domain-containing protein/transposase-related (Sb08g016890); MATE efflux family protein (Sb03g012960); NB-ARC
domain-containing disease resistance protein (Sb0019s003010); PGR5-LIKE A (Sb01g000570); protein serine/threonine phosphatases;protein kinases; ATP
binding (Sb04g011020); Relative of early flowering 6 (Sb03g043210); Sulfite oxidase (Sb09g003680); UDP-glycosyltransferase 73B4 (Sb09g024630); WRKY
DNA-binding protein 49 (Sb03g047350)
6
novel-sbi-miR-245
H
H
MATE efflux family protein (Sb03g012960); Pentatricopeptide repeat (PPR) superfamily protein (Sb08g020000); tetratricopeptide repeat (TPR)-containing protein
(Sb04g029850)
7
novel-sbi-miR-266
H
H
GRAS family transcription factor (Sb01g015165); Protein kinase superfamily protein (Sb04g037460); RING/FYVE/PHD zinc finger superfamily protein
(Sb09g003580)
8
novel-sbi-miR-339
H
H
Formin homology 1 (Sb02g030000); Cytochrome P450, family 71, subfamily B, polypeptide 37 (Sb08g003380, Sb08g003390, Sb01g041085, Sb03g045960);
BTB-POZ and MATH domain 4 (Sb01g005590, Sb02g003880); RING/FYVE/PHD zinc finger superfamily protein (Sb08g003900, Sb04g008370); Highly
ABA-induced PP2C gene 2 (Sb01g039890)
9
novel-sbi-miR-387
H
H
Aluminium activated malate transporter family protein (Sb04g032070); GRAS family transcription factor (Sb10g000520; Sb01g040270; Sb01g050333;
Sb06g024820, Sb04g032570, Sb04g032590, Sb01g029650); CTD-phosphatase-like protein (TC121585)
8
1
UP-REGULATED IN M35 BUT DOWN-REGULATED IN C43
miR160a
N
H
Auxin-responsive (ARF 10, 16, 17) family proteins (Sb06g033970, Sb04g026610, Sb06g022810, Sb01g019130, Sb10g027790); Malic enzyme (TC114069);
Sensor protein (BM325690)
2
miR396b-c
N
H
Argonaute family protein (sb02g032990); Myosin heavy chain-related protein (sb07g029120); OSBP(oxysterol binding protein)-related protein 1D
(sb08g011100); poly(A) polymerase 1 (sb01g012650); Protein phosphatase 2C family protein (sb08g022065)
3
miR396d-e
N
H
Argonaute family protein (Sb02g032990); MuDR family transposase (Sb10g010620); Proline-rich spliceosome-associated (PSP) family protein/zinc knuckle
(CCHC-type) family protein (Sb04g023010)
4
miR5385
N
H
Alba DNA/RNA-binding protein (Sb01g046110); ARM repeat superfamily protein (Sb09g028200); basic helix-loop-helix (bHLH) DNA-binding superfamily protein
(Sb03g028030); HXXXD-type acyl-transferase family protein (Sb01g027380); Long-chain fatty alcohol dehydrogenase family protein (Sb01g019470); DNA
internalization-related competence protein (CN125947); SH3 domain binding protein (AW924710); Gibberellin regulated protein (BE355997)
5
novel-sbi-miR-4
N
H
Auxin response factor 9 (TC123217)
6
novel-sbi-miR-6
N
H
ATP-dependent helicase family protein (Sb10g000310); TTF-type zinc finger protein with HAT dimerization domain (Sb01g020840); VQ motif-containing protein
(Sb10g026640)
7
novel-sbi-miR-19
N
H
Receptor like protein 7 (Sb03g004950); RNA-binding (RRM/RBD/RNP motifs) family protein (Sb06g024100); D-isomer specific 2-hydroxyacid dehydrogenase
family protein (Sb06g000620); cytochrome P450, family 97, subfamily B, polypeptide 3 (Sb04g004850); ABC2 homolog 12 (Sb0067s002260)
(Continued)
microRNAs and trans-acting siRNAs from Sorghum bicolor
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TABLE 1 | Continued
S.No.
miRBase ID
M (DT)
C (DS)
Targets
8
novel-sbi-miR-26
N
H
Alanine dehydrogenase/PNT, N-terminal domain containing protein (CD206106); ABC transporter, ATP-binding/permease protein (CD211686); Heat shock
70 kDa protein (AW679261); NAC domain containing protein 76 (Sb07g000470)
9
novel-sbi-miR-41
N
H
Auxin transport protein (Sb07g010440); Eukaryotic aspartyl protease family protein (Sb02g038150); Exonuclease-like protein (TC113816); LigA (TC123718)
10
novel-sbi-miR-46
N
H
Aldehyde oxidase 4 (Sb02g003720); AMP-dependent synthetase and ligase family protein (Sb01g046790); D-alanine–D-alanine ligase family (Sb02g002970);
Leucine-rich repeat transmembrane protein kinase (Sb04g008350); Rad23 UV excision repair protein family (Sb10g009520); Ribosomal protein L2 family
(Sb02g009810); AMP-binding enzyme family protein (TC122720); Smr domain-containing protein-like (CF484339); Methionine aminopeptidase (CN150723);
Nucleoside diphosphate kinase (TC134154); Protein kinase domain containing protein (TC114900); Zinc transporter (TC114013)
11
novel-sbi-miR-48
N
H
UB-like protease 1A (Sb01g033010); Major facilitator superfamily protein (Sb01g046010); Leucine-rich repeat transmembrane protein kinase (Sb02g033810);
Amidase family protein (Sb01g025910); FAR1-related sequence 5 (Sb04g022400)
9
12
novel-sbi-miR-76a-d
N
H
NB-ARC domain-containing disease resistance protein (Sb02g005210)
13
novel-sbi-miR-82
N
H
Serine carboxypeptidase-like 26 (Sb05g024460); UDP-Glycosyltransferase superfamily protein (Sb01g002870)
14
novel-sbi-miR-87
N
H
Purple acid phosphatase 3 (Sb01g041570); RING/FYVE/PHD zinc finger superfamily protein (Sb02g037120); Transcriptional factor B3 family
protein/auxin-responsive factor AUX/IAA-related (Sb09g028450); Ubiquitin-specific protease 4 (Sb06g018520)
15
novel-sbi-miR-119
N
H
Acyl-CoA N-acyltransferase with RING/FYVE/PHD-type zinc finger domain (Sb10g000260); MuDR family transposase (Sb08g020220); squamosa promoter
binding protein-like 2/9/14 (Sb06g024630, Sb07g027740, Sb02g028420, Sb04g003175, Sb10g029190, Sb04g004940)
16
novel-sbi-miR-138
N
H
P-loop containing nucleoside triphosphate hydrolases superfamily protein (Sb01g036270); RNI-like superfamily protein (Sb06g017410);
S-adenosyl-L-methionine-dependent methyltransferases superfamily protein (Sb06g025840); Cysteine-rich RLK (RECEPTOR-like protein kinase)
(Sb09g024140); Dgd1 suppressor 1 (Sb01g035060)
17
novel-sbi-miR-144
N
H
Evolutionarily conserved C-terminal region 2 (Sb01g046550); HXXXD-type acyl-transferase family protein (Sb03g040180); YT521-B-like family protein
(TC114776, TC128350, TC112012); RR1 cuticle protein 2 (TC119816); Chlorophyll synthase (TC127744)
18
novel-sbi-miR-151
N
H
NOL1/NOP2/sun family protein (Sb07g014990); ARM repeat superfamily protein (Sb10g027680); Cytochrome P450, family 71, subfamily A, polypeptide 25
(Sb10g027350)
novel-sbi-miR-164
N
H
Alpha-amylase-like 3 (Sb03g032830); F-box/RNI-like superfamily protein (Sb02g002776)
novel-sbi-miR-259
ND
H
Trehalose-phosphatase/synthase 7(Sb03g034640); NB-ARC domain-containing disease resistance protein (Sb05g002510); phloem protein 2-A13
(Sb01g031190); Ribosomal protein L27 family protein (Sb09g025720)
21
novel-sbi-miR-176
N
H
Amino acid permease family protein (Sb01g034170); Calcium-binding EF-hand family protein (Sb07g023990); RING-box 1 (Sb04g030370); Transducin/WD40
repeat-like superfamily protein (Sb10g004900); GAMYB-binding protein (TC117630); CRISPR-associated autoregulator DevR family (CF486137)
22
novel-sbi-miR-178a-b
N
H
HXXXD-type acyl-transfera se family protein (Sb08g005680); ZPR1 zinc-finger domain protein (Sb01g007380); 2-oxoglutarate (2OG) and Fe(II)-dependent
oxygenase superfamily protein (Sb10g005230); Trehalose-6-phosphate phosphatase (Sb10g007770); Mitochondrial editing factor 9 (Sb10g008110); HAT
dimerization domain-containing protein/transposase-related (Sb08g018265); PHE ammonia lyase 1 (Sb04g026520); Myosin heavy chain-related
(Sb01g031580, Sb06g018840); DEAD/DEAH box helicase, putative (Sb04g028500); Cytochrome P450, family 78, subfamily A, polypeptide 7 (Sb01g022690)
23
novel-sbi-miR-180a-c
N
H
Cellulose synthase like E1 (Sb02g027610); retinoblastoma-related 1 (Sb07g025760); F-box associated ubiquitination effector family protein (Sb09g002420)
24
novel-sbi-miR-212
N
H
Pollen Ole e 1 allergen and extensin family protein (Sb09g026510); Ubiquitin fusion degradation UFD1 family protein (Sb03g023980)
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25
novel-sbi-miR-240
N
H
Nucleotide-sugar transporter family protein (Sb02g038010); Glycine/D-amino acid oxidase (TC120362)
26
novel-sbi-miR-285
N
H
SU(VAR)3-9 homolog 5 (Sb06g024160); Probable Ufm1-specific protease (TC124720)
27
novel-sbi-miR-287
N
H
RAD3-like DNA-binding helicase protein (Sb03g026660)
28
novel-sbi-miR-292
N
H
FUS3-complementing gene 2 (Sb04g024880); PIF1 helicase (Sb06g016400)
29
novel-sbi-miR-304
N
H
ARM repeat superfamily protein (Sb04g038390); NOL1/NOP2/sun family protein (Sb07g014990); Protein phosphatase 2C family protein (Sb02g021050);
Diphenol oxidase laccase (CF071060); Armadillo-like (TC122146)
30
novel-sbi-miR-310a-e
N
H
NAD(P)-binding Rossmann-fold superfamily protein (Sb01g029950, Sb01g029960, Sb01g029980); Translation elongation factor EF1A/initiation factor
IF2gamma family protein (Sb06g032980)
(Continued)
microRNAs and trans-acting siRNAs from Sorghum bicolor
19
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TABLE 1 | Continued
S.No.
miRBase ID
M (DT)
C (DS)
Targets
31
novel-sbi-miR-314a-c
N
H
NB-ARC domain-containing disease resistance protein (Sb02g005210); Shaggy-like kinase(TC115703)
32
novel-sbi-miR-316
N
H
NB-ARC domain-containing disease resistance protein (Sb02g033350)
33
novel-sbi-miR-335
N
H
ABC transporter family protein (Sb03g001690); RNI-like superfamily protein (Sb09g022040)
34
novel-sbi-miR-336
N
H
SCAR homolog 2 (Sb01g038070); Heat shock factor A2b (CB929268)
35
novel-sbi-miR-340
N
H
Cysteine-rich RLK (RECEPTOR-like protein kinase) 40 (Sb08g014920); peroxisomal 3-ketoacyl-CoA thiolase 3 (Sb01g020150); Pre-rRNA-processing protein
ipi1 (CD225395); 1-acyl-sn-glycerol-3-phosphate acyltransferase (CF483158); Eosinophil-associated ribonuclease 10(CF430012); CinA domain protein
(TC128307); Protein WIR1B (TC127450)
36
novel-sbi-miR-351
N
H
SART-1 family (Sb02g040465)
37
novel-sbi-miR-368
N
H
Leucine-rich repeat protein kinase family protein (Sb04g007490)
38
novel-sbi-miR-373
N
H
Protein of unknown function (Sb09g020740)
39
novel-sbi-miR-385
N
H
Phosphate starvation response 1 (Sb02g010520); MYB-related protein 1 (Sb09g023830)
40
novel-sbi-miR-390
N
H
31-kDa RNA binding protein (Sb07g024400)
41
novel-sbi-miR-391
N
H
Auxin efflux carrier family protein (Sb10g004430)
42
novel-sbi-miR-392a-c
N
H
U-box domain containing protein (CD210713); FAD-linked oxidoreductase (TC125560); Bundle sheath cell specific protein (TC124246); Calmodulin-binding
transcription activator protein with CG-1 and Ankyrin domains (Sb03g044220); FAD-binding Berberine family protein (Sb10g021700); plectin-related
(Sb01g034550); Ubiquitin fusion degradation UFD1 family protein (Sb03g023980)
10
43
novel-sbi-miR-412
N
H
Auxin transport protein (Sb07g010440); response regulator 9 (Sb02g010680); Amine oxidase family protein (TC118219)
44
novel-sbi-miR-413
N
H
NB-ARC domain-containing disease resistance protein (Sb05g008250, Sb05g008270, Sb05g008030); Thioredoxin-like (TC118042)
45
novel-sbi-miR-416
N
H
HAMP domain (BI074248); 2 3-bisphosphoglycerate-independent phosphoglycerate mutase (CF771695); ATP-binding cassette sub-family B member
(CB928529); F-box and associated interaction domains-containing protein (Sb08g004745); Pentatricopeptide repeat (PPR) superfamily protein (Sb08g000870,
Sb08g000890)
DOWN-REGULATED IN M35 BUT UP-REGULATED IN C43
miR2118e
H
N
Keratin-associated protein (TC123298); 4-amino-4-deoxychorismate synthase (BE598671); splicing factor, arginine/serine-rich 4 (SRp75) isoform 2
(TC133348); Disease resistance protein (CC-NBS-LRR class) family (Sb09g004410); NB-ARC domain-containing disease resistance protein (Sb06g028930)
2
miR2275
H
N
Pentatricopeptide repeat (PPR) superfamily protein (Sb02g038430); receptor like protein 7 (Sb08g006800); SEC6 (Sb04g027870); Protein kinase superfamily
protein (Sb03g028800); Calcium-dependent lipid-binding (CaLB domain) family protein (Sb02g009740); terpene synthase 21 (Sb05g006470); ferrochelatase 1
(Sb04g000740)
3
novel-sbi-miR-36
H
N
DNA polymerase epsilon subunit B2 (sb07g022680); heat shock transcription factor (sb01g005250, sb01g042370); LUC7 related protein (sb01g001640);
monogalactosyldiacylglycerol synthase type C (sb07g027910); NHL domain-containing protein (sb03g027320); Pollen Ole e 1 allergen and extensin family
protein (sb09g026510); Transducin/WD40 repeat-like superfamily protein (sb04g022100); Sarcoplasmic reticulum protein-like protein (TC130664); VMP4
protein (TC115388)
4
novel-sbi-miR-59a-c
H
N
Glucose-methanol-choline (GMC) oxidoreductase family protein (Sb04g031910); Leucine-rich receptor-like protein kinase family protein (Sb04g008470);
Tetratricopeptide repeat (TPR)-like superfamily protein (Sb01g037150)
July 2015 | Volume 6 | Article 506
5
novel-sbi-miR-64
H
N
Alanyl-tRNA synthetase (Sb08g008230); basic leucine-zipper 44 (Sb02g020760); Protein kinase family protein (Sb09g006270)
6
novel-sbi-miR-120a-b
H
N
Enolase 1(Sb02g023480); S15/NS1, RNA-binding protein(Sb04g036260); ubiquitin-specific protease 12 (Sb05g022390); uridine-ribohydrolase 2
(Sb03g009290); Walls Are Thin 1 (Sb10g002840)
7
novel-sbi-miR-200
H
N
BTB-POZ and MATH domain 2 (Sb05g024650); cytochrome P450, family 87, subfamily A, polypeptide 6 (Sb01g017160); plastidic pyruvate kinase beta subunit
1 (Sb01g028470); RING/U-box superfamily protein (Sb03g030660)
8
novel-sbi-miR-215
H
N
Phosphate transporter 3;2 (Sb02g026490); RHOMBOID-like 1 (Sb05g027720); Ribosomal protein S11-beta (Sb06g028330); TPX2 (targeting protein for Xklp2)
protein family (Sb02g020830)
9
novel-sbi-miR-223
H
N
Short-chain dehydrogenase/reductase (CF072307)
(Continued)
microRNAs and trans-acting siRNAs from Sorghum bicolor
1
11
S.No.
miRBase ID
M (DT)
C (DS)
Targets
10
novel-sbi-miR-227a-c
H
N
Amidase family protein (Sb05g020350); Pleckstrin homology (PH) domain-containing protein (Sb09g030860); S-locus lectin protein kinase family protein
(Sb10g002600); ThiF family protein (Sb03g027840); Protein WIR1B (TC127450); Beta-1,3-glucanase (CD208397); Nuclear pore protein (TC132690);
Non-ribosomal peptide synthetase modules and related proteins-like (EH407477); J-domain protein (TC125925)
11
novel-sbi-miR-256
H
N
Dinitrogenase iron-molybdenum cofactor biosynthesis (TC121074)
12
novel-sbi-miR-268
H
N
IQ-domain 25 (Sb03g034245); Late embryogenesis abundant (LEA) hydroxyproline-rich glycoprotein family (Sb04g009840); like SEX4 1(Sb07g019250);
non-specific phospholipase C2 (Sb03g046200); phosphate 1 (Sb04g036730); Remorin family protein (Sb01g049810); Ubiquitin domain-containing protein
(Sb09g026390, Sb02g022530); C-terminal region family protein (TC130454)
13
novel-sbi-miR-295
H
N
Heat shock protein DnaJ (Sb03g024860); Subtilase family protein (Sb02g025810)
14
novel-sbi-miR-297a-c
H
N
Gibberellin 20 oxidase (Sb02g003940)
15
novel-sbi-miR-301
H
N
Signal recognition particle, SRP9/SRP14 subunit (Sb06g029010)
16
novel-sbi-miR-344
H
N
DEA(D/H)-box RNA helicase family protein (Sb02g029690); Inorganic H pyrophosphatase family protein (Sb04g005710); BTB-POZ & MATH domain
(Sb05g024650); DCD (Development and Cell Death) domain protein (Sb10g005050); WPP domain interacting protein (Sb07g028540); methyl esterase11
(Sb02g038650); long-chain base (LCB) kinase1 (Sb01g017100)
17
novel-sbi-miR-359
H
N
Methionine S-methyltransferase (Sb09g000490); pleckstrin homology (PH) domain-containing protein (Sb01g028690)
18
novel-sbi-miR-360a-c
H
N
SNF2 domain-containing protein/helicase domain-containing protein (Sb01g046180); FAD/NAD(P)-binding oxidoreductase family protein (Sb01g046710);
Alpha/beta-Hydrolases superfamily protein (Sb02g007580); Flavodoxin-like quinone reductase 1 (Sb09g024730); Adenine nucleotide alpha hydrolases-like
superfamily protein (Sb03g005760); Transcription factor jumonji (jmj) family protein/zinc finger (C5HC2 type) family protein (Sb04g036630); GDP-L-fucose
synthase 1 (TC126325)
19
novel-sbi-miR-376
H
N
ARF GTPase-activating protein (Sb02g029540); Methylthiotransferase (Sb05g023010); NB-ARC domain-containing disease resistance protein (Sb05g004640);
RNA-binding CRS1/YhbY (CRM) domain-containing protein (Sb03g013160); Tetratricopeptide repeat (TPR)-like superfamily protein (Sb03g026520);
Transketolase (Sb06g004280); ubiquitin-protein ligase 4 (Sb09g022820)
Katiyar et al.
Frontiers in Plant Science | www.frontiersin.org
TABLE 1 | Continued
The up arrow head shows upregulation of miRNA under drought, while down arrow head shows downregulation of miRNA under drought; the cell with “ND” and no arrow indicate that miRNA was not detected neither in control nor in
drought.
microRNAs and trans-acting siRNAs from Sorghum bicolor
July 2015 | Volume 6 | Article 506
Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
annotated sorghum gene mapping to GO terms. (B) Further dissection
of “response to stimulus” exposes various stress responsive target
genes, including drought (7 genes) and heat (6 genes) highlighted with
red and yellow color, respectively.
FIGURE 3 | Gene ontology (GO) analysis of miRNAs target genes
identified in sorghum genotypes drought-susceptible and
drought-tolerant. (A) Blue bars indicate the enrichment of miRNA
targets in GO terms. Green bars indicate the percentage of total
Discussion
suggesting the function of these miRNA∗ in a genotype specific
manner. We also observed that the majority of the miRNA
transcripts showed higher abundance in tolerant genotype as
compared to susceptible genotype under drought treatment
(Table S4 in Supplementary Material).
High-throughput Sequencing of Sorghum Small
RNAs
In the past few years, high-throughput sequencing is being
used to identify miRNAs in several crop plants, including
barley, brassica, cowpea, cucumber, maize, peanut, rice, sorghum,
soybean, and wheat. In sorghum, 17 (Du et al., 2010), 29 (Zhang
et al., 2011a) and 31 (Katiyar et al., 2012) new miRNAs were
identified recently. Compared with the number of miRNAs that
have been identified in other cereal crops such as rice, only
limited miRNAs have been discovered in sorghum. Additionally,
drought-regulated miRNAs have not been identified either
through experimental or computational methods in sorghum.
In the present study, we constructed and sequenced sRNA
libraries from seedlings of M35-1 (drought tolerant) and C43
(drought susceptible) genotypes grown under irrigated and
drought stress conditions. As a sequencing throughput, the
small RNAs population of size 17–29 nt have been found. After
eliminating the adapter sequences, the highest read abundance
was found for 21–24 nt small RNAs, which is consistent with
the size of the DCL enzyme products (Figure 5). The read
abundance for each miRNA families highly differed. The miR166,
miR167, miR156, and miR399 are the largest miRNA families
with 11, 10, 8, and 7 members, respectively, in sorghum. The
miR160 and miR396 families have 6 members each (Figure 1;
Table S2 in Supplementary Material). Likewise, miR156g∗ and
miR398∗ were found to accumulate at high levels under drought
condition in DS and DT genotypes of sorghum, suggesting that
these two miRNA∗ might function in stress response mechanism
irrespective of genotypes. The miR166f∗ , miR167g∗ , miR169e∗ ,
miR398∗ , and novel-sbi-miR-383∗ accumulated at high levels
exclusively in DS genotype, whereas, miR166g∗ , miR167h∗ , and
miR169h∗ accumulated at high levels exclusively in DT genotype,
Frontiers in Plant Science | www.frontiersin.org
Monocot- and Dicot-abundant miRNAs
Previous studies have shown that some miRNAs are conserved
across the plant kingdom, while other miRNAs have been
reported in either monocot or dicot plants. In this study,
49 conserved miRNAs belonging to 26 miRNA families were
identified from previously deposited miRNAs in miRBase 21
(Table 2). Among these, 30 (61.22%) miRNA families (denoted
with the symbol “&” in Table 2) were found to be highly
conserved between dicot and monocot plants. The remaining
19 (38.78%) miRNA families (denoted with the symbol “#” in
Table 2) were found conserved in monocot plants only. In this
study, miR156g-h was identified first time in monocot, which was
previously reported only in dicot plant, suggesting the conserved
nature of this family in monocot and dicots. Likewise, variants of
selected miRNA members, namely miR156b, miR169b, miR396a,
and miR399a were found in sorghum as reported previously
in monocots. However, other variants of the same family
were found to be conserved in dicot plants. This suggests
that these miRNAs might have evolved after the divergence
of monocots and dicots. In the present study, we found
monocot abundant miR156g-h, miR166c-i, miR167f-j, miR169b,
miR171a-b, miR172a-c, miR319a-b, miR395, miR396a, miR437,
miR529, miR2118a-b, miR2118d, miR2118e, miR2275, miR5385,
and miR6221 (denoted with the symbol “@” in Table 2) which
were not previously reported in sorghum. Similarly, miRNA
families, namely miR437, miR156g-h, miR2118d, miR5385,
and miR6221 (denoted with the symbol “$” in Table 2) were
identified first time in monocots. In addition, we found that
12
July 2015 | Volume 6 | Article 506
Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
expressions obtained by next-generation sequencing is represented by red
color. The color blue represents the expression level of target genes obtained
from transcriptome analyses of sorghum.
FIGURE 4 | Negative correlation between drought-responsive
miRNAs and their predicted target genes; where (A,B) represents
miRNA up, target gene down, and vice versa, respectively. The miRNA
sensitive genotypes, i.e., 44 of them were upregulated in
M35-1 but downregulated in C43, while 19 of them were
downregulated in M35-1 but upregulated in C43 (Figure 2;
Table 1, Table S3 in Supplementary Material). Among the
conserved miRNAs, miR160a, miR169d-l, 396b-c, 396d-e,
miR529, miR2118e, miR2275, and miR5385 were found
as drought stress responsive in sorghum. The miR160 is
known to regulate ARF10/ARF16/ARF17 repressors family
and overexpression of miR160 confers auxin hypersensitivity
(Turner et al., 2013). In Arabidopsis, ARF17, a target of
miR160, negatively regulate the expression of auxin inducible
Gretchen Hagen3 (GH3) genes, encoding acyl-acid-amido
synthetase which fine-tuning adventitious root initiation in the
Arabidopsis (Gutierrez et al., 2012). In cereals, adventitious
(nodal/crown) roots, contributes significantly to soil moisture
uptake under drought stress (Rostamza et al., 2013). In the
present study, we also found that miR160a targets several ARF
the expression levels of conserved miRNAs were higher than
that of unique miRNAs. For example, conserved miRNAs such
as miR156c-f, miR156g-h, miR160b-f, miR166c-i, miR166j-k,
miR167d-e, miR167f-j, miR396a, and miR398 exhibited high
levels of read abundant (more than 750 TPM) in all four
libraries. These observations support the earlier conclusion
that phylogenetically conserved miRNAs are highly abundant
(Sunkar et al., 2008).
Response of Known and Novel miRNAs to
Drought Stress
We compared the small RNA expression profiles of drought
tolerant and sensitive genotypes of sorghum and identified 96
drought-responsive miRNAs with more than twofold change
at-least in one genotype (Table 1; Table S3 in Supplementary
Material). Of the 96 drought regulated miRNAs, 63 miRNAs
showed opposite regulation in drought tolerant and drought
Frontiers in Plant Science | www.frontiersin.org
13
July 2015 | Volume 6 | Article 506
Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
genotype, respectively. (C,D) Represent reads distribution in control and
stress library of drought-tolerant genotype, respectively. The highest sRNA
read abundance was found for 24 nt in all 4 libraries.
FIGURE 5 | Distribution of sRNA reads produced from control and
drought stress libraries of sorghum; where, (A,B) represents reads
distribution in control and stress library of drought-susceptible
family members, including ARF10, ARF16, and ARF17. Thus,
miR160 upregulation in M35-1 and downregulation in C43,
might be contributing to better tolerance of M35-1. We also
observed that the downregulation of miR396b-c and miR396d-e
in the DS genotype of sorghum as reported previously in rice
(Zhou et al., 2010) and cowpea (Barrera-Figueroa et al., 2011),
but were upregulated in the DT genotype of sorghum as reported
previously in Arabidopsis (Liu et al., 2009) and tobacco (Feng-Xi
and Di-Qiu, 2009) under drought-stress. Previous studies
showed that miR396a-overexpressing transgenic plants were
more drought tolerant than wild-type plants (Liu et al., 2009;
Yang et al., 2009). Thus, upregulation of miR396 in DT genotype
appears to be contributing to drought stress tolerance of M35-1.
Likewise, downregulation of miR529 in both genotypes of
sorghum was observed as previously shown in rice (Zhou
et al., 2010; Jeong et al., 2011). In addition to the conserved
miRNA family members, we found drought regulation of several
members of novel miRNA families. These miRNAs might be
involved in lineage- or species-specific stress response pathways
and functions. In general, many of the miRNA families consist
of more than one miRNA gene, which may have identical or
Frontiers in Plant Science | www.frontiersin.org
diverse mature miRNA sequences. These homologous miRNA
genes may functionally diverge from each other during the
evolutionary process. For instance, in our study, miR156
and miR164 families showed clear evidence for functional
diversification. While one member of miR156 family known as
miR156b was induced by drought stress, while another member
miR156a was significantly down-regulated in drought sensitive
genotype. On the other hand, all members of the miR396 family
were up-regulated by drought stress in the tolerant genotype, but
not in the sensitive cultivar. Detailed analyses revealed that the
majority of the sorghum miRNAs was expressed in a genotype
specific manner.
MicroRNAs Regulated Targets in Response to
Drought Stress
In general, plants respond to environmental stresses by regulating
target genes through up- or down-regulation of miRNAs to
cope with these stresses. In the present study, 108 targets were
predicted for 49 known miRNAs using bioinformatics analysis,
and many of these were conserved in plant species, indicating
broad conservation of the known miRNA regulatory roles in
14
July 2015 | Volume 6 | Article 506
miR family
Monocot
a
t
a
b
d
i
f
a
r
h
v
u
o
s
a
#miR1432
&miR156a
+
+
+
#miR156b
&miR156c-f
+ +
+
s
s
p
Dicot
s
b
i
t
a
e
t
t
u
z a
m a
a u
+
+
+
+
+
+
+ +
$&miR156g-h
a a
m t
g r
a
q
c
a
l
y
a
t
h
b
r
a
b b c
c g p
y y a
c
c
l
c
r
t
c
s
i
c
t
r
c d
m p
e r
+ +
+
+
+
&miR160b-f
+ + +
+
+
+ + + +
+ + + +
&miR164a-b
+ +
+
+
+
+
&miR164c
+ +
+
+
+
&miR166a-b
+ +
+
+
&miR166c-i
+ +
&miR166j-k
+
+
+ @
+
+ +
+
+
+
15
+ +
+
+
+
+
+ + +
+
+
+
+ +
&miR167f-j
+ +
@
&miR169a
+
+
@
+
+
&miR171a-b
+
&miR171c-f
+ + + + +
+
&miR172a-c
+ +
@
+
+
+
+
+ +
+
p
v
u
p
t
c
p
p
e
r
c
o
s
s
l
s
l
y
s
t
u
v
u
n
v
v
i
+
+
+
+ + + +
+ +
+
+
+
+ +
+
+ + +
+
+
+ +
+
+
+
+ + + +
+ + +
+ + + +
+ + + +
+ + + + +
+
+
+ + + + +
+
+
+ +
+
+
+ +
+ +
+ + + + + +
+ +
+ + + + + +
+
+
+
+
+ + + +
+
+
+
+ + +
+
+
+
+
+ +
+
+ + +
+
+
+ + + +
+ +
+
+
+
+
+ + +
+
@
+
#miR2118c
+
+
+
+
+
+
@
+ +
+
+ +
+
+
+ +
+ + +
+
+
+
+ + +
+ + + + +
+
+
+ + +
+ +
+ +
+
+
#miR2118a-b +
$#miR2118d
m m m n
d e t t
m s r a
+ +
@
+
l
j
a
+ +
+
+
+
+
+ +
+
+
+
+ + + + +
+ + +
+ + + +
+ +
+
+ + + +
@
#miR2275
July 2015 | Volume 6 | Article 506
#miR319a-b
+
@
+
@
+
+ +
+
+
+
+
+ +
+ +
+
+ + +
+
+
&miR393a-b
+
+
+
+
+
+ +
+
+
+ + +
+
+
&miR394a-b
+ +
+
+
+
+
+ + +
+
+
+ + +
+
+
#miR395
+
@
+
#miR396a
+ + +
+
+
+ +
+
+ +
+ + +
+ +
+ + +
+ + +
+
+ +
+
+
+
+
+ + +
+
@
(Continued)
microRNAs and trans-acting siRNAs from Sorghum bicolor
+ + +
+ + +
h
b
r
+
+
+
+
+ +
h
t
u
+ +
+ +
&miR169d-l
h
p
a
+
+ + + + +
+
+ +
&miR169c
h
e
x
+ + +
+ + +
&miR167d-e
+
h
a
r
+
&miR167a-c
#miR169b
g
h
r
+
+
+
g
h
b
+
+ + +
+
+
g g
m s
a o
+
+
&miR160a
&miR390
a b
m n
a a
@
&miR159
#miR2118e
a
h
y
Katiyar et al.
Frontiers in Plant Science | www.frontiersin.org
TABLE 2 | Conservedβ miRNA families in monocot and dicot species.
miR family
Monocot
Dicot
a
t
a
b
d
i
f h o
a v s
r u a
s
s
p
s
b
i
&miR396b-c
+
+
+
+
+
+
&miR396d-e
+
+
+
+
+
+
&miR396f
+
+
+
#miR398
+
+
+
#miR399a
t
a
e
t z a
t m a
u a u
+
+
+
+
+
+
&miR399e
+
+
+
&miR399f
+
+
+
&miR399g
+
+
+
+
+
$#miR437
#miR529
$#miR5385
a
q
c
a
l
y
a
t
h
a a b
h m n
y a a
b
r
a
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
b
c
y
b
g
y
+
+
+
+
+
c
p
a
c
c
l
c c
r s
t i
+
+
+
+
+
c
t
r
+
+
c d
m p
e r
g g g g
m s h h
a o b r
h
a
r
+
+
+
+
+
+
+
+
h h h h
e p t b
x a u r
l
j
a
m m m n
d e t t
m s r a
p
v
u
p
t
c
p
p
e
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
r
c
o
+
s
s
l
s
l
y
s
t
u
v
u
n
v
v
i
+
+
+
+
+
+
+
+
+
+
&miR399b-d
a a
m t
g r
Katiyar et al.
Frontiers in Plant Science | www.frontiersin.org
TABLE 2 | Continued
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
@
+
@
+
@
#miR5564a-b
+
$#miR6221
@
#miR6230a-b
+
16
+, Known miRNAs; @, miRNAs reported first time in sorghum; #, Monocot specific miRNAs; &, miRNAs conserved in both monocot and dicot; $, miRNAs reported first time in monocot. β ata, Aegilops tauschii; bdi, Brachypodium
distachyon; far, Festuca arundinacea; hvu, Hordeum vulgare; osa, Oryza sativa; ssp, Saccharum sp. ; sbi, Sorghum bicolor; tae, Triticum aestivum; ttu, Triticum turgidum; zma, Zea mays; aau, Acacia auriculiformis; amg, Acacia mangium;
atr, Amborella trichopoda; aqc, Aquilegia caerulea; aly, Arabidopsis lyrata; ath, Arabidopsis thaliana; ahy, Arachis hypogaea; ama, Avicennia marina; bna, Brassica napus; bra, Brassica rapa; bcy, Bruguiera cylindrica; bgy, Bruguiera
gymnorhiza; cpa, Carica papaya; ccl, Citrus clementina; crt, Citrus reticulata; csi, Citrus sinensis; ctr, Citrus trifoliata; cme, Cucumis melo; dpr, Digitalis purpurea; gma, Glycine max; gso, Glycine soja; ghb, Gossypium herbaceum; ghr,
Gossypium hirsutum; har, Helianthus argophyllus; hex, Helianthus exilis; hpa, Helianthus paradoxus; htu, Helianthus tuberosus; hbr, Hevea brasiliensis; lja, Lotus japonicus; mdm, Malus domestica; mes, Manihot esculenta; mtr, Medicago
truncatula; nta, Nicotiana tabacum; pvu, Phaseolus vulgaris; ptc, Populus trichocarpa; ppe, Prunus persica; rco, Ricinus communis; ssl, Salvia sclarea; sly, Solanum lycopersicum; stu, Solanum tuberosum; vun, Vigna unguiculata; vvi,
Vitis vinifera.
microRNAs and trans-acting siRNAs from Sorghum bicolor
July 2015 | Volume 6 | Article 506
Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
levels under drought stress in both the genotypes. These miRNAs
may control a genotype-independent common drought response
mechanism. All these miRNA members putatively target a zinc
finger protein. Downregulation of novel-sbi-miR-112 (targeted to
“basic region/leucine zipper protein-60” or bZIP60) and novelsbi-miR-254 (targeted to “homeobox-leucine zipper protein17” or HD-ZIP17) in response to drought may increase the
abundance of bZIPs, and contribute to drought tolerance in
the DS genotype of sorghum. The importance of bZIPs in
stress tolerance of plants was also reported previously (Yang
et al., 2009; Golldack et al., 2011). Moreover, miR5385 was
up-regulated by drought in the tolerant cultivar, but downregulated in sensitive cultivar. The predicted target for this
miRNA is a basic-helix loop-helix (bHLH) transcription factor.
Several reports elucidated the role of bHLH in response to
abiotic stresses, e.g., freezing (Chinnusamy et al., 2003), iron
deficiency (Long et al., 2010) and salt stress (Li et al., 2010a).
Abiotic stresses lead to accumulation of excess concentrations of
reactive oxygen species (ROS), resulting in oxidative damage to
the cell. Peroxidases help restrict ROS build up and thus oxidative
damage to the cells. We predicted peroxidise family as target for
six miRNA families, namely novel-sbi-miR-30, novel-sbi-miR106, novel-sbi-miR-177, novel-sbi-miR-204, novel-sbi-miR-272,
and a novel-sbi-miR-217 in sorghum. In tolerant genotype, the
expression level of novel-sbi-miR-272 was lower than that of
sensitive cultivar during drought stress. The increase of novelsbi-miR-272 in the sensitive genotype C43 under drought stress
may lead to a decrease in the transcript levels of peroxides and
thus could be one of the factors associated with vulnerability of
this genotype. Several droughts-responsive miRNA families such
as novel-sbi-miR-105a-b, novel-sbi-miR-180a-c, and novel-sbimiR-416 targeted to Kelch repeat-containing F-box protein in
sorghum. These proteins are known to be involved in response
to biotic and abiotic stresses (Sun et al., 2010; Jia et al.,
2012). In sorghum, we observed similar expression patterns
for these miRNAs irrespective of genotypes. Three miRNA
families (e.g., Novel-sbi-miR-213, miR169c, and a miR169d-l)
were down-regulated by drought stress in sensitive genotype C43.
These miRNAs targeted to nuclear factor Y (NFY) transcription
factor. Li et al. (2008) reported that NFYA5 transcript is
strongly induced by drought stress in an abscisic acid (ABA)dependent manner, whereas miR169 was down-regulated by
drought stress through an ABA-dependent pathway. Transgenic
plants overexpressing miR169 and NFYA5 knockout plants
exhibited hypersensitivity to drought stress. Thus, NFYA5 is
important for drought tolerance in plants (Li et al., 2008).
In contrast, tomato plants over-expressing miR169c exhibited
better tolerance to drought due to reduced stomata opening
(Zhang et al., 2011b). Thus, drought tolerance may likely involve
divergent mechanisms in the different plants. Plants respond to
heat or drought stress by the induction of the synthesis of heatshock proteins (HSPs). HSPs play a crucial role in protecting
plants under diverse abiotic stresses (Wang et al., 2004). Four
miRNA families (e.g., miR396d-e; novel-sbi-miR-26; novel-sbimiR-85a-k, and a novel-sbi-miR-336) that targeted to HSPs/HSFs
were found to be down-regulated during drought stress in the
drought sensitive genotype of sorghum. In contrast, miR396d-e
plants (Table 1; Table S4 in Supplementary Material). In addition
to the well-documented conserved targets, a few of the known
miRNAs, including miR2118c, miR529, and miR399a were found
to target additional genes in sorghum that have not been
previously reported. Selected miRNAs, such as miR529 (targeting
genes coding for SBP, DCD, cellulase, protease-related, and
ubiquitin), and miR398 (targeting genes coding for Cu/Zn SOD,
selenium-binding protein, and cytochrome C) showed multiple
target genes, indicating that these miRNAs have diverse roles.
Furthermore, a single gene may be regulated by several miRNAs.
For example, squamosa promoter binding protein (SBP) gene is
targeted by miR156a, miR156b, miR156c-f, miR156g-h, miR529,
novel-sbi-miR-119, novel-sbi-miR-383, novel-sbi-miR-329, and a
novel-sbi-miR-350 in sorghum. In addition, several conserved
members of identical miRNA families were found to possess
conserved target genes. For instance, all members from the
sbi-miR156 and sbi-miR160 family targeted to SBP and auxin
response factor (ARF), respectively. Similarly, all members of
the sbi-miR399 and sbi-miR164 families targeted phosphate
transporter (PHT), and NAC domain containing protein,
respectively. Similar results were observed previously in several
plant species and these miRNA target genes have been found to
be involved in plant growth and/or responses to environmental
changes (Unver and Budak, 2009; Xie et al., 2011). The putative
targets of the drought regulated miRNAs offered important
clues on the drought response in sorghum. For instance, sbimiR164 (targeted to NAC transcription factor) was found to
be downregulated by drought stress at-lest in one genotype of
sorghum. This is consistent with previous reports in Arabidopsis
and sugarcane (Guo et al., 2005; Raman et al., 2008; Ferreira
et al., 2012). NAC transcription factors regulate the development,
growth and stress responses, including cold, drought and
pathogen attack (Kikuchi et al., 2000; Ooka et al., 2003).
Similarly, several droughts regulated miRNAs such as novel-sbimiR-4, novel-sbi-miR-41, novel-sbi-miR-87, novel-sbi-miR-391,
and novel-sbi-miR-412, which target ARFs, were upregulated in
DT M35-1 but down regulated in DS C43 sorghum genotype
under drought stress. This is consistent with earlier studies that
showed stress adaptation by ARFs regulated auxin-mediated
mechanisms (Guilfoyle and Hagen, 2007). Proper regulation of
auxin transport is critical for drought tolerance (Remy et al.,
2013). These results suggest that the predicted targets such as
NAC and ARFs play important roles in the drought response in
tolerant genotype of sorghum. The suppression of novel-sbi-miR335 in the sensitive genotype under drought stress could be one
of the factors associated with susceptibility of sorghum cultivar
C43. The induction of novel- sbi-miR-335 in tolerant genotype
under drought stress might contribute to drought-tolerance of
the M35-1 cultivar. Moreover, the up-regulation of novel-sbimiR-389, responsive to dehydration stress in drought tolerant
M35-1 cultivar was consistent with earlier observations in barley
(Kantar et al., 2010) and soybean (Kulcheski et al., 2011). Some
miRNAs such as novel-sbi-miR-360a-c showed up-regulation in
drought sensitive C43, but showed down-regulation in drought
tolerant M35-1 indicating different adaptive mechanisms by
respective genotype. Interestingly, the novel-sbi-miR-266 and a
novel-sbi-miR-339 miRNA family showed decreased expression
Frontiers in Plant Science | www.frontiersin.org
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Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
these tasiRNAs. miR828-TAS4 pathway is widely represented in
dicot species (Luo et al., 2012), while the miR173-TAS1/TAS2
pathway has been found to be restricted in Arabidopsis. We
mapped TAS loci with coding or non-coding regions, and found
that 11 TASs did not have homology to coding regions, 18
TASs showed partial homology to coding regions, and two
TASs showed significant similarity (>50% query coverage and
sequence identity) with coding regions. In addition, miR5567
and miR6225 target TASs were found to be highly conserved
(Figure S2 in Supplementary Material). We also observed that
two putative TAS3 genes have similar sequences, but different
predicted structures. Previous reports disclosed the connection
of Arabidopsis tasi-RNAs (TAS1, TAS2, and TAS3) with hypoxia
stress (Moldovan et al., 2009). In addition, TAS4-derived
siRNAs regulate the biosynthesis of anthocyanins in response
to phosphorous deficiency (Hsieh et al., 2009; Luo et al., 2012).
Likewise tasi-RNAs from Pinus taeda was predicted to target the
transcripts of two disease resistance proteins of pine, suggesting
its role in the response to pathogens (Lu et al., 2007). However,
no drought-stress related tasi-RNAs have been reported in
plants. In the present study, we noticed that most of miR390derived tasi-RNA sequences were present in both DS and DT
libraries under control and stress conditions. We assume that
neither miR390 nor tasi-RNAs from TAS3 genes were affected
by drought stress. Furthermore, we noticed that all tasi-RNAs
derived from miR5567 targeted TASs, and miR6230 targeted
TASs were found only in the control library of drought sensitive
genotype. Targets of miRNAs and tasi-RNAs play important roles
in many pathways involved in the development or responses to
the environment. Our result revealed that 5′ cleavage product of
miR390-TAS3 produces two tasi-RNAs [e.g., SbiTAS3a-siR3905′ D4 (+); sbiTAS3b-siR390-5′ D3 (+)] that target transcripts
of auxin response factors (Figure 6). This is consistent with
previous reports in Arabidopsis (Allen et al., 2005). Similarly,
miR5568-TAS derived tasi-RNA [e.g., SbiTAS-siR5568c-3′ D2
(+)], found in drought-stressed library of drought sensitive
genotype, targets to universal stress protein (USP). Genes
encoding the universal stress protein domain confer enhanced
ability of plants to tolerate stress. The other tasi-RNAs are novel,
which will help further broaden the scope of tasi-RNA mediated
gene regulation.
and novel-sbi-miR-336 were found to be up-regulated under
drought stress in the drought tolerant genotype of sorghum.
In addition, GO analysis exposed the response of several
target genes in heat (GO: 0009408), water deprivation (GO:
0009414), water stimulus (GO: 0009415) and heat acclimation
(GO: 0010286). The miR156b (targets IRREGULAR XYLEM
1), miR396b-c (targets mitochondrial HSP70-2); novel-sbi-miR27 (targets HSP21), novel-sbi-miR-55 (targets HOMEBOX 7),
novel-sbi-miR-171 (targets early responsive to dehydration 15),
novel-sbi-miR-254 (targets nitrate transmembrane transporter),
novel-sbi-miR-268 (targets HSP101), novel-sbi-miR-272 (targets
HSP1; WRKY; Heat-intolerant 1 and Cytochrome P450), novelsbi-miR-277 (targets F-box family protein), novel-sbi-miR-329
(targets abscisic acid responsive elements-binding factor 2), and
novel-sbi-miR-389 (DEHYDRIN XERO1), were observed as a
regulator of drought and heat responsive proteins (Table S5 in
Supplementary Material). The novel-sbi-miR-268 and a novelsbi-miR-272 was found to be up-regulated in sensitive genotype,
whereas, down-regulated in the tolerant genotype of sorghum.
Likewise, miR396b-c and novel-sbi-miR-254 was found to be
down-regulated in sensitive, but up-regulated in the tolerant
genotype of sorghum. These results suggested that the two
genotypes studied here have differential molecular mechanisms
to respond to drought stress. In addition to conserved targets,
genotype-specific miRNA regulated gene targets were also
observed (Table S4 in Supplementary Material). Although many
newly evolved miRNAs that may exhibit weak expression,
imperfect processing and lack of targets are believed to serve
no biological function, many of them have been shown to target
and regulate specific genes or gene families in sorghum (Li et al.,
2010b; Pantaleo et al., 2010; Zhang et al., 2010).
Conserved miR390-TAS3 Pathway in Sorghum
Tasi-RNAs were originally discovered in Arabidopsis, where
four TAS families (e.g., TAS1/2, TAS3, and TAS4) code for
TAS transcripts which are targeted by three miRNA families,
namely miR173, miR390, and miR828. The tasi-RNA prediction
approach includes the detection of phased 21 nt sRNAs,
characteristic of tasi-RNA loci and the assessment of statistical
significance in term of P-value. Using this approach, various
research groups have demonstrated the existence of tasi-RNAs
in Arabidopsis, rice, grapevine, brassica, apple and soybean. To
examine whether there are any homologous genes of predicted
TASs in sorghum, we aligned 31 TASs with non-redundant (nr)
nucleotide database. Surprisingly, we did not find homologs
of 29 TASs. However, two miR390 targeted TASs (Table S7
in Supplementary Material) showed significant similarity with
TAS3 gene of Sorghum bicolor and Saccharum officinarum.
Further, these two TASs were aligned with Arabidopsis TAS
genes, and found that sorghum TAS is similar to that of
AtTAS3 gene, hence named these as sorghum TAS3 genes. Thus,
the miR390-TAS3 pathway is conserved in sorghum also in
addition to the previously reported plants such as Arabidopsis,
rice, grapevine, brassica, apple and soybean. Conversely, we
did not find miR828-TAS4 and miR173-TAS1/TAS2 pathway
in sorghum. In consistency with previous observations that
TAS1, TAS2, and TAS4 families do not occur in monocots
(Axtell et al., 2006), in our study, we also did not find
Frontiers in Plant Science | www.frontiersin.org
Conclusions
Small RNA-seq in combination with bioinformatic analysis
identified 97 conserved and 526 novel miRNAs in sorghum. In
addition, we discovered several novels and conserved miRNAs
regulated by drought stress. Common as well as genotypespecific miRNA expression patterns were discovered from
DS and DT-genotypes of sorghum elucidated the underlying
molecular mechanisms and diverse physiological pathways. The
targets for predicting miRNAs were found to be involved
in cellular, metabolic, response to stimulus, biological
regulation, and developmental processes. Additionally, the
discovery of two TAS3 genes (orthologs of Arabidopsis TAS3
genes) targeted by miR390 revealed conserved miR390-TAS3
pathway in sorghum. The prediction of miR390-TAS3 derived
tasiARF suggested their role in the auxin signaling pathway.
18
July 2015 | Volume 6 | Article 506
Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
is given a number D1, D2… starting at the miRNA target site
[17]; the processing direction is noted by a 5′ or 3′ prefix; the
orientation is indicated by adding the suffix [+] for the positive
(original transcript) strand, or [−] for the negative (RDR generated
and denoted by #) strand.
FIGURE 6 | Diagrammatic representation of miR390 directed
TAS3a (A) and TAS3b (B) genes in sorghum. Predicted
miR30-TAS binding sites are shown in red; all tasi-RNAs are shown
in other than red color with an underline; tasi-RNAs have been
named by using a standardized nomenclature in which the register
Author Contributions
The outcomes of this study provide valuable information
for further functional characterization of miRNAs in
response to drought stress in sorghum. Our findings laid
the groundwork for functional characterization of droughtresponsive miRNAs and manipulating miRNAs or their targets
for improving biomass production and stress tolerance in
sorghum.
Frontiers in Plant Science | www.frontiersin.org
AK initiated the research, performed the downstream analyses,
interpreted the results and drafted the manuscript. SS helped in
computational analyses and data management. SM conducted
the plant stress treatment and collected the tissues. VC
interpreted the results and designed the experiments. DP
19
July 2015 | Volume 6 | Article 506
Katiyar et al.
microRNAs and trans-acting siRNAs from Sorghum bicolor
and KB conceived the idea of the study and drafting the
manuscript. All authors have read and approved the manuscript
for publication.
germplasm of sorghum. SM gratefully acknowledges the
Department of Science and Technology (DST) for DST-INSPIRE
fellowship grant.
Acknowledgments
Supplementary Material
We thank to Dr. Monika Dalal, Indian Institute of Millets
Research, Hyderabad (presently working as a Senior Scientist
in NRC on Plant Biotechnology, New Delhi), for providing
The Supplementary Material for this article can be found
online at: http://journal.frontiersin.org/article/10.3389/fpls.2015.
00506
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2015 Katiyar, Smita, Muthusamy, Chinnusamy, Pandey and Bansal.
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July 2015 | Volume 6 | Article 506