Uncovering small RNA-mediated responses to cold stress in a

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Running head: Small RNAs in response to cold stress in TGMS line

Name: Zhonghui Tang

Address: Beijing Engineering and Technique Research Center of Hybrid Wheat, Beijing Academy of

Agricultural and Forestry Sciences, Beijing 100097, China

Tel: 86-10-51503765

E-mail: [email protected]

Research Category: ENVIRONMENTAL STRESS AND ADAPTATION TO STRESS

Plant Physiology Preview. Published on April 17, 2012, as DOI:10.1104/pp.112.196048

Copyright 2012 by the American Society of Plant Biologists

www.plantphysiol.orgon March 29, 2018 - Published by Downloaded from Copyright © 2012 American Society of Plant Biologists. All rights reserved.

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Uncovering small RNA-mediated responses to cold stress in a wheat

thermosensitive genic male sterile line by deep sequencing

ZHONGHUI TANG1,2, LIPING ZHANG1,CHENGUANG XU1, SHAOHUA, YUAN1, FENGTING,

ZHANG1, CHANGPING ZHAO1 * & YONGLIAN ZHENG2*

1Beijing Engineering and Technique Research Center of Hybrid Wheat, Beijing Academy of

Agricultural and Forestry Sciences, Beijing 100097, China

2National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan

430070, China

*Authors for correspondence: CHANGPING ZHAO, Tel: 86-010-51503765, Email:

[email protected]; YONGLIAN ZHENG, Tel: 86-027-87286870, Fax: 86-027-87286870 Email:

[email protected].



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Financial sources: National Science Foundation (No.31171172), National “863” Program

(No.2011AA10A106), the Program of Beijing Basic Research and Innovation Platform for

Agricultural Breeding (No. D08070500690801; No. D111100001311002), Beijing Science Foundation

(No.5091001), and Science Foundation of Beijing Academy of Agricultural and Forestry Sciences

(KJCX201101007).

Authors for correspondence: CHANGPING ZHAO, [email protected];

YONGLIAN ZHENG, [email protected].



4

Abstract 1

The male sterility of thermosensitive genic male sterile (TGMS) lines of wheat (Triticum aestivum) 2

is strictly controlled by temperature. The early phase of anther development is especially susceptible 3

to cold stress. MicroRNAs (miRNA) play an important role in plant development and in responses to 4

environmental stress. In this study, deep sequencing of small RNA (smRNA) libraries obtained from 5

spike tissues of the TGMS line under cold and control conditions identified a total of 78 unique 6

miRNA sequences from 30 families, and trans-acting small interfering RNAs (tasiRNAs) derived 7

from two TAS3 genes. To identify smRNA targets in the wheat TGMS line, we applied the degradome 8

sequencing method, which globally and directly identifies the remnants of smRNA-directed target 9

cleavage. We identified 26 targets of 16 miRNA families and three targets of tasiRNAs. Comparing 10

smRNA sequencing datasets and TaqMan qPCR results, we identified six miRNAs and one tasiRNA 11

(tasiRNA-ARF) as cold stress-responsive smRNAs in spike tissues of the TGMS line. We also 12

determined the expression profiles of target genes that encode transcription factors in response to cold 13

stress. Interestingly, expressions of cold-stress responsive smRNAs integrated in the auxin-signaling 14

pathway and their target genes were largely anticorrelated. We investigated tissue-specific expression 15

of smRNAs using a tissue microarray approach. Our data indicated that miR167 and tasiRNA-ARF 16

play roles in regulating the auxin-signaling pathway, and possibly in the developmental response to 17

cold stress. These data provide evidence that smRNA regulatory pathways are linked with male 18

sterility in the TGMS line during cold stress. 19

Keywords: deep sequencing, microRNA, trans-acting small interfering RNA, auxin responsive factor, 20

wheat thermosensitive genic male sterility21



5

Introduction 1

In flowering plants, the male gametophyte plays an important role in plant fertility and crop 2

production through the generation and delivery of male gametes to the embryo sac for double 3

fertilization (Borg et al., 2009). The development of the male gametophyte involves an array of 4

extraordinary events, including the differentiation of sporogenous cells, the transition from the 5

sporophytic to gametophytic generation, and the modification of cell division to produce microspores 6

(Wilson and Yang, 2004). Plants are more vulnerable at the reproductive growth stage than the 7

vegetative growth phase to many environmental stresses, including cold stress. Recently, the 8

molecular basis underlying the developmental responses of the anther to environmental stresses has 9

been an intense subject of research (Tang et al., 2011). 10

Since microRNAs (miRNAs) and other endogenous small silencing RNAs were discovered in 11

plants (Llave et al., 2002; Mette et al., 2002; Park et al., 2002), these small RNA (smRNA)-based 12

silencing systems have changed our understanding of mechanisms of transcription, translation, and 13

regulation of gene expression. In plants, miRNAs and small interfering RNAs (siRNAs) of 21 to 24 14

nucleotides (nt) are two broad categories of these regulatory RNA molecules, and both types function 15

as negative regulators of gene expression (Voinnet, 2009). The major difference between these two 16

categories lies in their genomic origin and biogenesis. miRNA primary transcripts arise from 17

intergenic regions via the action of RNA polymerase II (Lee et al., 2004). miRNAs are processed from 18

their precursors by RNase III enzyme DICER-LIKE1 (DCL1) or DCL4, which digests the imperfectly 19

complementary hairpin structure of precursors into miRNA:miRNA* duplexes (Kim, 2005). The 20

mature miRNAs of the duplexes combine with protein factors to form RNA-induced silencing 21

complexes (RISCs). Subsequently, miRNAs guide the RISCs to target mRNA molecules, where they 22

regulate mRNAs primarily at the posttranscriptional level by directing mRNA cleavage via the 23

endoribonuclease activity of the Argonaute (AGO) protein (Baulcombe, 2004; Chapman and 24

Carrington, 2007; Voinnet, 2009). In contrast, siRNAs are derived from long double-stranded RNA 25

molecules generated by RNA-dependent RNA polymerases; this feature distinguishes them from 26

miRNAs. Endogenous siRNAs can be further classified into trans-acting siRNAs (tasiRNAs), natural 27



6

antisense transcript-derived siRNAs, and heterochromatin siRNAs (Schwach et al., 2009). Most 1

siRNAs target the same locus they were derived from, except for tasiRNAs, which target mRNAs 2

from different loci, similarly to miRNAs. tasiRNAs are phased 21-nt RNA molecules whose 3

production is triggered by miRNA-directed cleavage of the TAS transcripts (Allen et al., 2005; Axtell 4

et al., 2006). 5

The pool of smRNAs in plants is extremely complex, consisting of a diverse set of miRNAs (Lu et 6

al., 2005; Kasschau et al., 2007; Johnson et al., 2009). Extensive research has demonstrated the critical 7

role of miRNAs in controlling developmental processes and organ identity (Jones-Rhoades et al., 2006; 8

Mallory and Vaucheret, 2006; Chen, 2009). There is also evidence that miRNAs are associated with 9

abiotic stress responses (Sunkar et al., 2007; Leung and Sharp, 2010; Sunkar, 2010). In keeping with 10

this, many miRNAs target transcription factors with roles in developmental patterning and show 11

unique tissue-specific, development-related, and stress-induced expression (Juarez et al., 2004; Sunkar 12

and Zhu, 2004; Jones-Rhoades et al., 2006). 13

In Arabidopsis, the signaling pathway that mediates the response to the phytohormone auxin is 14

particularly densely packed with miRNA regulation. In this pathway, miR393 targets mRNAs 15

encoding TIR1 and other closely related F-box proteins (Jones-Rhoades and Bartel, 2004). These 16

F-box proteins are auxin receptors that target repressors of the Auxin Responsive Factor (ARF) for 17

ubiquitin-mediated degradation in response to auxin. Interestingly, not only the receptors of auxin, but 18

also the transcripts of ARFs are either directly or indirectly regulated by miRNAs (Jones-Rhoades et 19

al., 2006). miR160 targets ARF10, ARF16 and ARF17, and its regulation of these transcripts appears 20

to be important in many aspects of shoot and root development (Mallory et al., 2005; Wang et al., 21

2005; Liu et al., 2007b). ARF6 and ARF8, which are targeted by miR167, act redundantly to regulate 22

ovule and anther development (Wu et al., 2006; Ru et al., 2006). miR390 directs cleavage of TAS3, 23

leading to the production of tasiRNAs that target ARF3 and ARF4 mRNAs. The regulation of ARF3 24

and ARF4 mediated by tasiRNA promote abaxial identity of lateral organs as well as the expression of 25

adult vegetative traits in leaves (Adenot et al., 2006; Fahlgren et al., 2006; Garcia et al., 2006; Hunter 26

et al., 2006). Additionally, several studies have investigated the expression patterns of miRNAs under 27



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cold conditions using deep sequencing and/or miRNA microarrays (Liu et al., 2008; Lee et al., 2010; 1

An et al., 2011). That research identified the putative miRNAs and their targets, but the results require 2

validation, and the overall pathways are yet to be determined. 3

The thermosensitive genic male sterile (TGMS) lines of wheat are hypersensitive to low 4

temperature during the meiosis stage (Tang et al., 2011). Our previous study revealed that the 5

development of the pollen mother cell (PMC) in a wheat TGMS line relies on the proper regulation of 6

gene expression. In that transcriptome study, we identified thousands of differentially expressed genes 7

in the anthers from PMC through meiosis stages (Tang et al., 2011). However, our knowledge about 8

the gene regulatory link between anther development and the cold-stress response is very limited. 9

Because miRNAs play roles in both plant development and stress responses, it is plausible to assume 10

that miRNAs have important roles in anther development in the TGMS line under cold conditions. 11

However, to date only 44 wheat-annotated miRNAs have been deposited in the miRBase database, 12

and only a few miRNA targets have been validated experimentally. At present, it is unknown whether 13

important regulators like miRNAs play a role in the function of PMCs during cold stress. 14

To fill this knowledge gap, we have sequenced smRNAs from seven independent libraries to obtain 15

a large inventory of smRNA species in the TGMS line. We identified a total of 78 unique miRNAs 16

belonging to 30 families, and tasiRNAs derived from two TAS3 genes. To understand how miRNAs 17

are integrated in diverse biological networks, it is necessary to confirm their target genes. To identify 18

transcriptome-wide smRNA targets in the TGMS line of wheat, we generated two degradome 19

sequencing libraries from spike tissues under cold or control conditions. A total of 26 target genes 20

were confirmed as miRNA targets, and three ARF transcripts were identified as targets of TAS3-siRNA. 21

Similar to coding mRNAs, it is essential to obtain accurate expression profiles of individual miRNAs 22

to understand their function. To address this question, we examined the expression profiles of all 23

candidate smRNAs using TaqMan qPCR, with two biological replicates. A total of six miRNAs and 24

one tasiRNA (tasiRNA-ARF) showed significant changes in abundance under cold stress. The 25

tissue-specific expression of smRNAs was investigated using a tissue microarray (TMA) approach. 26



8

Comparing the expression profiles of smRNAs and their targets, we determined that smRNAs 1

involved in the auxin signaling pathway may play a significant and specific role in the plant response 2

to cold stress during spike development in the TGMS line. Changes in the abundance of these 3

cold-stress-responsive smRNAs mediate the abnormal activity of target ARFs that are important for 4

anther development, causing male sterility of the TGMS line under cold conditions. The results 5

presented in this study provide an insight into the regulatory role of smRNAs in the TGMS line in 6

response to cold stress, and provide valuable information about the cold-induced male sterility of the 7

TGMS line.8



9

Results 1

Overview of small RNA libraries from the wheat TGMS line at various spike developmental 2

stages 3

We aimed to identify smRNAs from the wheat TGMS line that may be involved in the regulation 4

of anther development and/or the response to cold stress. Therefore, we constructed seven smRNA 5

libraries from spikes of plants that were treated or not with cold (10°C), which strongly affects 6

anther development in the TGMS line during the fertility-sensitive stage (Tang et al., 2011). The 7

seven smRNA libraries were sequenced using Solexa sequencing technology, and yielded an 8

average of 12.3 million raw reads per sample (Supplemental Table S1). Poor quality reads, those 9

without inserts, and those with inserts smaller than 18 nt were excluded from further analysis. 10

Finally, we obtained an average of 4.5 million nonredundant reads per sample, ranging from 18 to 11

27 nt (Supplemental Table S1). 12

The composition of smRNAs often reflects roles of different categories of smRNAs in a 13

particular tissue or species, in different physiological conditions, and in various biogenesis 14

machineries (Wei et al., 2009). In our study, the majority of the smRNAs were 20 to 24 nt long, 15

which is the typical size range for DCL-derived products. Consistent with previous reports on plants, 16

the 24 nt and 21 nt smRNAs were the most abundant smRNA species (Supplemental Figure S1A) 17

(Moxon et al., 2008; Hsieh et al., 2009). The distribution of redundant sequences in different size 18

classes was similar in spikes from cold-stressed and control plants (Supplemental Figure S1A). 19

When the unique read signatures were examined, the patterns of all seven libraries were also nearly 20

identical (Supplemental Figure S1B). As generally described, the 24 nt smRNA population was 21

clearly the most diverse. As expected, the 21 nt class showed the highest redundancy because a 22

relatively small number of non-redundant sequences were expressed at high levels (Supplemental 23

Figure S1). 24



10

Conserved miRNAs in spikes of the wheat TGMS line 1

Conserved families of miRNAs are found in many plant species and have important functions in 2

plant development and stress responses (Jones-Rhoades et al., 2006; Chen, 2009; Rubio-Somoza et 3

al., 2009). To identify conserved miRNAs, we analyzed the smRNAs by BLAST searches against 4

the known noncoding RNAs (rRNA, tRNA, snRNA, and snoRNA) deposited in Rfam and NCBI 5

databases. An average of 45,203 distinct smRNAs per cDNA library belonging to these categories 6

was filtered to avoid degradation contamination. The remaining reads were analyzed to identify 7

conserved and novel miRNAs. 8

We compared the entire sets of unique smRNAs to the miRBase database (Version 17). The 9

search criteria were more rigorous, requiring smRNAs to display a perfect or nearly perfect match 10

(mismatch < 2) to published miRNAs and the mismatch was required to be outside the ‘seed’ region. 11

Based on these criteria, a total of 553 sequences from seven independent libraries showing less than 12

two mismatches or deletions in comparison to a registered miRNA were identified, corresponding 13

to 2,388,039 reads (3.08% of the total reads). These smRNAs belong to 30 miRNA families, 14

containing 78 miRNAs previously described in other plant species (Table I). Some miRNA* in 15

addition to the miRNAs were also identified for the miR156, miR160, miR166, miR390, miR396, 16

and miR399 families (Table I). Only nine of the tae-miRNAs found in wheat tissues (pooled sample 17

of leaves, roots, and spikes) by Yao et al. (2007) were retrieved in our libraries, possibly because of 18

low expression levels, tissue-specific expression in the TGMS spikes, or still unsaturated miRNA 19

sequencing due to the large wheat genome. 20

As expected, we identified members of almost all conserved miRNA families (18 of 24 families 21

conserved in plants) in the seven cDNA libraries (Table I) (Jones-Rhoades et al., 2006; Sunkar and 22

Jagadeeswaran, 2008). Sequence analysis revealed that 13 conserved miRNA families were 23

represented by more than one member in our libraries (Table I). Among these conserved families, 24

the miR166 family was the largest, and included 11 miRNA members and three miRNA*. The 25

second largest family was miR167, containing six miRNA members. The expression levels of a few 26



11

miRNA families were similarly high (miR166 and miR167) or low (miR160, miR399, miR408, and 1

miR444) (Supplemental Table S2), indicating that expression varies greatly among the different 2

miRNA families in spike tissues of the wheat TGMS line. In other families, only one particular 3

member showed high abundance in all libraries (Supplemental Table S2). This result highlights that 4

some specific miRNA isoforms show differential expression patterns in spike tissues of the wheat 5

TGMS line. 6

In addition to the broadly conserved miRNAs, there are other known miRNAs that are not 7

conserved, but are found in only one or a few plant species (Jones-Rhoades et al., 2006). Several 8

nonconserved miRNAs from nine families were present with very low abundance in our data sets, 9

except for tae-miR528 and tae-miR894, which showed high read numbers (Table I). Interestingly, in 10

a previous study, it was speculated that tae-miR894 might be specific to moss (Fattash et al., 2007). 11

The miR2118 family is conserved in rice and maize, and its members are almost exclusively 12

expressed in the inflorescence; therefore, members of this family were proposed to play an 13

important role in the development of reproductive structures in both cereals (Johnson et al., 2009). 14

However, in our seven independent smRNA cDNA libraries, tae-miR2118 was present with low 15

abundance in spike tissues (Supplemental Table S2). Our qRT-PCR also showed that tae-miR2118 16

only could be detected with extended PCR cycle number to 40 in optimized PCR performance 17

(small nuclear RNA U6 with 18.5 Ct value). These results indicated that data on smRNAs from 18

more species are necessary to understand the evolution of these weakly conserved miRNAs. 19

To further characterize the sequenced miRNA candidates, we searched for putative precursors 20

within the genomic trace file archive and expressed sequence tag (EST) databases. We found seven 21

conserved miRNA precursors among the ESTs and whole genome shotgun sequences 22

(Supplemental Figure S2). 23



12

Identification of tasiRNAs in spikes of the wheat TGMS line 1

Trans-acting siRNAs (tasiRNAs) constitute a small class of phased smRNAs that are also capable 2

of altering gene expression. Although tasiRNAs play an important role in developmental timing and 3

patterning in Arabidopsis (Peragine et al., 2004; Vazquez et al., 2004; Fahlgren et al., 2006), their 4

expressions have not been reported to change under cold stress. In our study, we analyzed the 5

smRNA sequencing datasets to identify clusters of smRNAs that exactly matched some transcripts 6

in a phased manner, which clearly revealed the presence of tasiRNAs. We detected phased smRNAs 7

from transcripts that are homologous with previously described TAS genes (TAS3a and TAS3b) in 8

Arabidopsis (Axtell et al., 2006; Shen et al., 2009), having approximately 4 to 9 group-phased 9

smRNAs matching their transcripts in both strands (Supplemental Figure S3). The most abundant 10

phased siRNAs were generated from the 5’D6(+) and 5’D2(-) position in TAS3a and TAS3b, 11

respectively (Supplemental Figure S3). However, the TAS3 homolog (accession: BQ171265) 12

predicted by Allen et al. (2005) in wheat was not detected in our phased smRNA dataset. Both 13

TAS3a and TAS3b transcripts are first cleaved by miR390 to initiate the generation of phased 14

siRNAs. As we described above, tae-miR390 was present as a highly abundant read in our smRNA 15

datasets. These results indicated that the TAS3-miR390 tasiRNA pathway was operating in spikes of 16

the wheat TGMS line. 17

Construction of degradome libraries, sequencing, and sequence analysis 18

To identify transcriptome-wide smRNA targets in spikes of the wheat TGMS line, we applied the 19

recently developed high-throughput technology of degradome library sequencing (Addo-Quaye et 20

al., 2008; German et al., 2009; Li et al., 2010; Pantaleo et al., 2010). We obtained a total of 21

26,387,851 and 35,477,509 sequencing reads that represented the 5’ ends of uncapped and 22

poly-adenylated RNAs from cold-stressed spikes and controls, respectively (Supplemental Table 23

S1). After initial processing, we obtained 11,132,526 and 14,363,576 unique signatures from 24

cold-stressed spikes and controls, respectively. Using BLASTN searches against the Rfam database, 25

we were able to exclude the known noncoding RNAs (rRNA, tRNA, snRNA, and snoRNA), which 26



13

were represented at an average rate of 0.27% in our two unique signature datasets. Similarly, we 1

removed signatures corresponding to transposable elements from the unique datasets by performing 2

searches against the repeat sequence database (http://www.repeatmasker.org/). The remaining reads 3

were mapped to the wheat unigene dataset. In total, 11,132,526 (65.9%) and 14,363,576 (64.1%) 4

unique reads from cold-stressed spikes and controls were mapped to the wheat unigene dataset, 5

representing 12,713 unigenes. Previous degradome analyses reported that reads composed of polyA 6

fragments is another source of noise in the degradome sequencing library (German et al., 2008; Li 7

et al., 2010). However, only an average of 0.2% of the unique reads ended with four or more A 8

residues in our two degradome sequencing libraries. Taken together, these results indicated the high 9

quality of the degradome sequencing libraries obtained in the present study. The reads that mapped 10

to wheat unigenes were subjected to further analysis. 11

Identification of targets for annotated miRNAs and tasiRNAs 12

In plants, miRNAs degrade their mRNA targets by slicing precisely between the 10th and 11th 13

nucleotide from the 5’ end of miRNA in the complementary region of the target transcript. 14

Therefore, the sliced mRNA should have distinct peaks of degradome sequence tags at the 15

predicated cleavage site relative to other regions of the transcript (German et al., 2008; German et 16

al., 2009). In this study, we applied the recently developed CleaveLand technology to identify sliced 17

targets for miRNAs that were annotated as described above (Addo-Quaye et al., 2009a). 18

For the miRNAs shown in Table I, we identified a total of 26 target mRNAs (Table II). We also 19

analyzed the phased siRNAs shown in Supplemental Figure S3 to identify their targets. Only the 20

tasiRNAs derived from the 5’D6(+) position in TAS3a and the 5’D4(+) position in TAS3b targeted 21

to three Auxin responsive factor (ARF) genes (Table II). Based on the sequenced tags at the sliced 22

site and all along the region of the transcript, the cleaved target transcripts were categorized into 23

three classes (class I, II, or III) as described previously in other degradome analyses (Addo-Quaye 24

et al., 2008; Addo-Quaye et al., 2009b). Among the 29 mRNAs targeted by miRNAs and tasiRNAs, 25

21 fall into the class I category (Figure 1A, Table II), where the degradome tags corresponding to 26



14

the expected miRNA-mediated cleavage site were the most abundant tags matching the transcript. 1

In the class II category, the abundance of the cleavage signatures was greater than the median 2

number of signatures on the transcripts, but less than the maximum number. In our degradome 3

datasets, five target mRNAs were identified to belong to this category (Figure 1B, Table II). The 4

remaining targets, with a low abundance of cleavage signatures, were grouped into the class III 5

category. Only two transcripts were grouped into this category (Figure 1C, Table II). Because the 6

abundance of miRNA-guided cleavage remnants in class I and class II categories was much higher 7

than those of other signatures, targets in these two categories could show low false discovery rates, 8

and therefore, could be more accurate. Most of the identified targets are members of different 9

families of transcription factors, such as ARF, Growth Regulator Factor (GRF), GAMYB and 10

Squamosa Promoter Binding (SPB) families (Table II), which play important roles in anther 11

development (Chen, 2009; Wilson and Zhang, 2009). 12

We identified target mRNAs for 16 out of 21 conserved miRNA families. Among the five 13

conserved miRNA families without any identified targets, miRNAs of three conserved families 14

(miR395, miR399, miR444) were expressed at very low levels (less than 10 TPM; Table I), which 15

may explain the absence of cleaved targets. However, in a few cases, miRNAs belonging miR168 16

and miR164 families were expressed at high levels without the targets being identified in the 17

degradome libraries. The degradome sequencing also revealed that one tasiRNA precursor (TAS3b) 18

was cleaved at a 3’ miR390 complementary site (Figure 1D), which then initiated the production of 19

phased siRNA from the cleaved end (Supplemental Figure S3). Furthermore, the abundance of tags 20

associated with 488 transcripts that are not targeted by known miRNAs (all viridiplantae miRNAs 21

in miRBase) showed distinct peaks of degradome sequencing tags, suggesting a high number of 22

novel and non-conserved miRNAs in wheat or a high rate of turnover of these transcripts through 23

uncapping and 5’ to 3’ exosome-mediated pathways (Li et al., 2010). 24



15

Expression profiles of smRNAs throughout spike development under cold stress 1

In our study, the challenge for measuring miRNA levels arises from the existence of miRNA 2

families, such as miR166 and miR167 families (Table I), whose members differ by as little as only 3

one nucleotide, but nevertheless show different expression patterns. Sequencing of smRNA by 4

Solexa technology allowed rapid discovery of miRNAs in spikes of the TGMS line under cold and 5

control conditions. However, digital gene expression of smRNAs has recently been demonstrated to 6

generate inherent biases (Linsen et al., 2009; Hafner et al., 2011). This highlights the importance of 7

further quantitative analysis to confirm the relative abundance of smRNAs. TaqMan qPCR is often 8

considered as the “gold standard” for detecting and quantifying miRNA (Chen et al., 2005). 9

Therefore, to complement the smRNA sequencing analysis and build a comprehensive repository of 10

information on cold-responsive miRNAs in spikes of the TGMS line, we measured the expression 11

levels of smRNAs by TaqMan qPCR. 12

We used two criteria to select miRNAs for validation by qPCR: 1) miRNAs must target 13

transcription factors in our degradome dataset or must be predicted to target transcription factors in 14

miRBase; and 2) the average number of sequencing tags of miRNAs must be greater than 10 TPM 15

in our smRNA sequencing datasets. Except for tae-miR171a, whose TaqMan probe could not be 16

designed, a total of 19 miRNAs and one tasiRNA (TAS3a-5’D6(+), tasiRNA-ARF) were selected 17

for further analysis with TaqMan qPCR, using two biological repeats (Supplemental Figure S4). 18

With the exception of tae-miR160, tae-miR164, and tae-miR167, all of the other miRNAs were 19

identified in other species by homology searches. All were readily detected by TaqMan qPCR 20

(Supplemental Figure S4), which indicated that these miRNAs are authentic miRNAs. Analysis of 21

the overall correlation between smRNA sequencing data and TaqMan qPCR data showed that they 22

were slightly inconsistent, with a Pearson correlation coefficient (r2) close to 0.62 (Supplemental 23

Figure S5). In contrast, the results of TaqMan qPCR for each biological replicate were highly 24

reproducible (r2 value: 0.86) (Supplemental Figure S5). Therefore, the mean expression value for 25

each miRNA at each time point was used for further analysis. 26



16

As described above, the miR166 and miR167 families showed the highest levels of expression 1

among the miRNAs in our smRNA sequencing dataset. Our TaqMan qPCR results demonstrated 2

that members of the miR166 family did not show significant changes in expression levels between 3

cold and control conditions (Figure 2). In addition, the expression patterns of these miRNAs were 4

similar in cold and control conditions (Figure 2). These observations indicated that the miR166 5

family might play a redundant role in spike development. However, in the miR167 family, four 6

miRNAs showed distinctive expression patterns; although tae-miR167 and tae-miR167e were 7

highly expressed and unaffected by cold stress in spike tissues, their expression patterns were 8

slightly reversed (Figure 2). tae-miR167d and tae-miR167c were dramatically repressed at the L1.5 9

stage during cold stress, but tae-miR167c was up-regulated at the L3.0 stage (Figure 2). This result 10

indicates that miRNAs in the miR167 family might play different roles in spike development. The 11

smRNA sequencing analysis revealed that TAS3a-5’D6(+) derived from TAS3a and tae-miR390 12

initiates the cleavage of TAS3a. During the cold treatment, TAS3a-5’D6(+) was specifically 13

down-regulated at the L1.5 stage, which is consistent with the slight reduction in the accumulation 14

of tae-miR390 at the L1.5 stage (Figure 2). Furthermore, the expression levels of tae-miR172a, 15

tae-miR393, tae-miR396a, and tae-miR444c.1 were lower at an early stage of the cold treatment 16

(Figure 2). The other miRNAs, including tae-miR156a, tae-miR160, tae-miR164, tae-miR169a, and 17

tae-miR319, did not show significant changes in their expression levels between cold and control 18

conditions (Figure 2). 19

The differentially expressed miRNAs with greater than 1.5-fold or less than 0.5-fold relative 20

change between cold and control conditions were selected as candidate miRNAs. A total of seven 21

smRNAs (tae-miR167c, tae-miR167d, tae-miR172a, tae-miR393, tae-miR396a, tae-miR444c.1, and 22

TAS3a-5’D6(+)) met these criteria. Among these smRNAs, homologs of tae-miR167c and 23

tae-miR444c.1 target ARFs in citrus (Song et al., 2009) and a MADS box gene in rice (Sunkar et al., 24

2005; Lu et al., 2008a), respectively. However, the targets of tae-miR167c and tae-miR444c.1 could 25

not be identified in the degradome sequencing dataset by CleaveLand pipeline, which might be a 26



17

limitation of the wheat unigene dataset. Therefore, tae-miR167d, tae-miR172a, tae-miR393, 1

tae-miR396a, and TAS3a-5’D6(+) were selected as candidates for further analysis. Among these 2

miRNAs, tae-miR167d, tae-miR393, and TAS3a-5’D6(+) are involved in auxin signaling pathways. 3

Expression patterns of smRNAs-targeted genes in response to cold stress 4

To assess whether the cold-stress responsive smRNAs identified in spikes of the TGMS play an 5

important role in spike development, we further analyzed the expression patterns of all target genes 6

that encode transcription factors (shown in Table II). 7

In the auxin-signaling pathway, the genes TIR1 and TIR1-like were targeted by tae-miR393 8

(Table II). Compared with its expression in control conditions, expression of tae-miR393 was 9

slightly depressed under cold stress, but there was no significant change in expression of its target 10

genes (Figure 3). Tae-miR160, tae-miR167, tae-miR167d, and TAS3a-5’D6(+) target different ARFs 11

(Table II). Among these nine ARFs, the transcript levels of ARFs that were targeted by tae-miR160 12

and tae-miR167 were not significantly altered by cold stress (Figure 3), which is consistent with the 13

expression patterns of tae-miR160 and tae-miR167 as described above. These results suggest that 14

tae-miR160 and tae-miR167 do not act downstream of these ARF genes. Tae-miR167d targets one 15

ARF gene (EST Contig9875, Table II). The expression level of this ARF was induced at the L1.5 16

stage under cold conditions but was unchanged at the L2.2 and L3.0 stages (Figure 3). The ARF 17

genes located at EST Contig28378, Contig4296, and Contig1892 were targeted by TAS3a-5’D6(+) 18

(Table II). Compared with its expression in control conditions, there was no significant change in 19

expression of EST Contig28378 under cold stress (Figure 3). However, the ARF genes located at 20

EST Contig4296 and Contig1892 showed increased expressions at the L1.5 stage, and then 21

dramatically repressed expressions at the L2.2 stage (Figure 3). Taken together, these analyses 22

revealed that the expression levels of tae-miR167d and TAS3a-5’D6(+) and their target ARFs were 23

largely anti-correlated at the transcript levels, and raised the possibility that the auxin-signaling 24

pathway, via tae-miR167d and TAS3a-5’D6(+), may play an important role in spike development in 25

the TGMS line. 26



18

To better understand the molecular mechanisms by which tae-miR167d and TAS3a-5’D6(+) 1

regulate the cold-stress response in spikes of the TGMS line, we investigated the global expression 2

pattern in spike tissues in cold and control conditions using the Digital Gene Expression (DGE) 3

technique. The self-organizing map analysis indicated that the cluster including the ARF gene 4

located at EST Contig1892 showed different expression patterns in cold and control conditions 5

(Figure 4A). This expression cluster in Figure 4A comprised transcripts with markedly increased 6

abundance at the L1.5 stage and then decreased abundance at the L2.2 stage; however, these 7

transcripts also showed slight changes in abundance in the controls (Figure 4A). The transcripts 8

cluster in Figure 4B, including ARF genes located at EST Contig9875 and Contig4296, showed 9

increased expressions from the L1.5 to L2.2 stages (Figure 4B). Compared with their expressions 10

during cold treatment, these genes showed slight changes in transcript levels in controls (Figure 11

4B). 12

In addition, tae-miR396a targeted two Growth-Regulating Factors (GRFs) (Table II). Although 13

tae-miR396a showed depressed expression at the L1.5 and L2.2 stages (Figure 2), only one GRF 14

(CJ645826, NCBI EST accession number) showed slight changes in expression levels at the L1.5 15

and L2.2 stages (Figure 3). In contrast, the GRF gene C0347544 (NCBI EST accession number) 16

showed no significant changes in expression levels under cold stress (Figure 3). The APETALA2 17

gene located at EST Contig803, which was targeted by tae-miR172a (Table II), showed similar 18

expression patterns in cold and control conditions (Supplemental Figure S6). As described above, 19

tae-miR156a, tae-miR169a, and tae-miR319 showed no significant changes in expression levels 20

under cold-stress, compared with their respective expressions in the control (Figure 2). Consistent 21

with their expression profiles, their target genes also showed no changes in transcript levels during 22

cold stress (Supplemental Figure S6). 23

In summary, we observed changes in expression patterns of tae-miR167d and TAS3a-5’D6(+) and 24

their targeted ARF genes under cold conditions, suggesting a link between miR167/tasiRNA-ARF 25

and ARFs in the control of cold-induced male sterility in the TGMS line. Taking into consideration 26



19

the observation that activities of ARFs are also regulated by the ubiquitin-mediated degradation 1

pathway in response to endogenous auxin (Vanneste and Friml, 2009; Sakata et al., 2010), we 2

measured endogenous auxin levels in anthers of the TGMS line under both cold and control 3

conditions. The levels of endogenous auxin did not change in response to cold stress, compared 4

with that in the control (Supplemental Figure S7). The endogenous auxin accumulated normally 5

throughout the developing anthers, from rachis cells around vascular bundles to epidermal and 6

sporogenous cells (Supplemental Figure S7). This result suggests that the cold-induced change in 7

fertility as controlled by miR167/tasiRNA-ARF was largely mediated by ARFs in the TGMS line. 8

Differentially expressed small RNAs are associated with anther development 9

To understand the precise role of smRNAs in biological processes, we investigated the spatial 10

and temporal patterns of smRNA accumulation by in situ hybridization. In our study, we conducted 11

anther TMA to interpret the tissue-specific expressions of miRNAs/tasiRNA-ARFs. Using this 12

method, the entire cohort representing tissues from hundreds of anthers is treated in an identical 13

manner, which provides for rigorous statistical analysis (Supplemental Figure S8). 14

We selected three differentially expressed miRNAs (tae-miR167d, tae-miR172a and tae-miR396a) 15

and one differentially expressed tasiRNA-ARF (TAS3a-5’D6(+)) for in situ hybridization. The in 16

situ hybridization results showed that tae-miR172a and tae-miR396a showed similar expression 17

patterns in anther tissues of the TGMS line (Figure 5A–L). Tae-miR172a and tae-miR396a were 18

mainly localized in the tapetum and microsporocytes during anther development (Figure 5A–L). 19

However, tae-miR167d and TAS3a-5’D6(+) showed similar expression patterns, and were expressed 20

in different zones and in broader regions than those in which other miRNAs were expressed. 21

Tae-miR167d and TAS3a-5’D6(+) were expressed in all of the anther tissues at an earlier stage of 22

anther development (Figure 5M-X). Consequently, tae-miR167d and TAS3a-5’D6(+) showed the 23

highest expression levels in vascular bundles, the middle layer, the tapetum, and in microsporocytes 24

(Figure 5M-X). Based on rigorous statistical analysis of the TMAs, the expression levels of 25



20

miRNAs/tasiRNA-ARF in TMAs was consistent with their expression profiles as described in 1

Figure 2. 2

Spatial localization of miRNAs/tasiRNA-ARFs expressions showed that all of them were 3

expressed in the microsporocytes. In our previous study, we reported that cold stress contributed to 4

abnormal development of microsporocytes in the TGMS line (Tang et al., 2011). Therefore, 5

miRNA/tasiRNA–ARF-mediated regulation in response to cold stress may be linked to male 6

sterility of the TGMS line.7



21

Discussion 1

The thermosensitive genic male sterile (TGMS) line is very important for the utilization of heterosis 2

in wheat breeding. The sterile male phenotype is heritable in the TGMS line, but is strictly regulated 3

by an appropriate temperature (Li et al., 2006; Tang et al., 2011). Our previous study demonstrated 4

that cold stress contributes to abnormal development of pollen mother cells (PMCs) during meiosis 5

(Tang et al., 2011); however, the regulation of the developmental transition underlying the histological 6

changes remains poorly understood. In terms of their biological roles, miRNAs are predominantly 7

associated with plant development, but they also play an important role in stress responses 8

(Jones-Rhoades et al., 2006; Mallory and Vaucheret, 2006; Sunkar et al., 2007; Chen, 2009; Leung 9

and Sharp, 2010; Sunkar, 2010). Realizing that anther development in the TGMS line is controlled by 10

cold stress, identification of miRNAs and elucidation of their functions in anther development will 11

help us understand the regulation of male sterility by cold stress. 12

Known miRNAs and tasiRNAs in spike tissues of the TGMS line 13

As post-transcriptional regulators of gene expression, miRNAs are widely distributed in plants, 14

animals, and some viruses (Mallory and Vaucheret, 2006; He et al., 2008; Siomi and Siomi, 2010). 15

There are 232 and 491 annotated miRNAs in Arabidopsis thaliana and rice, respectively, according to 16

the miRBase database (version 17; www.mirbase.org). Wheat is an ancient polyploid crop with a 17

larger and more complex genome than those of Arabidopsis and rice (Chalupska et al., 2008; 18

Matsuoka, 2011). Although 44 wheat miRNAs were identified in previous studies, the number of 19

annotated miRNAs in wheat is still very limited, and there are considerably fewer annotated in wheat 20

than in Arabidopsis and rice. Recent innovations in sequencing technology and accumulation of 21

known miRNAs in the miRBase have allowed extensive surveys of smRNA populations in crop plants, 22

notably in species for which the genome has not been fully sequenced. Here, we show that miRNAs 23

are a diverse component of the smRNA transcriptome during spike development in the wheat TGMS 24

line. We identified a total 78 miRNAs belonging to 30 miRNA families by deep sequencing. Although 25

most of these miRNAs were identified by homology searches in other species, at least 19 miRNAs 26



22

were validated by TaqMan qPCR as genuine mature miRNAs. According to the recent criteria for 1

plant miRNAs (Meyers et al., 2008), seven of the conserved miRNA genes can be considered as 2

genuine miRNA precursors (Supplemental Figure S2), based on the detection of both the miRNA and 3

miRNA* in our smRNA sequencing libraries. When the sequencing of the wheat genome is completed 4

in the near future, biological research on miRNA will be greatly advanced. 5

In the analysis of miRNAs, we found that miR390 was abundantly present in spike tissues of the 6

TGMS line. The non-coding TAS3 transcripts are the targets of miR390, and cleaved TAS3 gives rise 7

to tasiRNAs that target transcripts in the ARF family (Allen et al., 2005; Axtell et al., 2006). It will be 8

interesting to see whether TAS3 or other TAS-like are involved in the cold stress response in spike 9

tissues of the wheat TGMS line. We predicted that phased siRNAs were derived from two TAS3 loci 10

that are targeted by tae-miR390 (Supplemental Figure S3), which is consistent with a previous report 11

that AtTAS3 homologs are present in diverse seed plants (Allen et al., 2005). The successful prediction 12

of TAS3-like genes was validated experimentally. This is clear evidence that both the miRNA pathway 13

and the tasiRNA pathway are functioning during spike development. 14

Furthermore, we emphasize that the high-throughput degradome sequencing dataset was especially 15

useful for global identification of targets of miRNA in the TGMS line. Functional characterization of 16

the miRNA targets is essential to provide deep biological insights into certain miRNA-mediated 17

pathways in spike development of the TGMS line under cold stress. In previous studies, the majority 18

of miRNA targets in wheat were predicted using bioinformatics approaches, and only a few targets 19

were validated experimentally. Computational analysis of the degradome dataset confirmed 29 20

mRNAs as genuine targets for wheat miRNAs/tasiRNAs. Our previous transcriptomic study showed 21

that many transcription factors exhibit dynamic gene expression changes during anther development 22

under cold stress, and miRNAs target transcription factors that are well represented in our degradome 23

sequencing dataset. Given the presence of miRNAs targeting a transcription factor family, such as 24

ARF (miR160, miR167, tasiRNA-ARF), HD-ZIP (miR165, miR166), GRF (miR396) and AP2 25

(miR172), there should be no doubt that miRNAs modulate the expression of many transcription 26

factors during spike development under cold stress and control conditions. 27



23

miRNAs/tasiRNA-ARF responses to cold stress in spikes of the TGMS line 1

In this study, we used the TaqMan qPCR technique to investigate the expression profiles of 19 2

miRNAs and one tasiRNA-ARF. Among these miRNAs, miR169, miR319, miR393, miR160 and 3

miR167 families are known to show differential expression during abiotic stress, such as cold, drought, 4

salt, oxidative stress, and hormone signaling (Sunkar and Zhu, 2004; Ding et al., 2009; Zhang et al., 5

2009b; Lee et al., 2010; An et al., 2011). We selected miR156, miR166, tasiRNA-ARF, miR172, and 6

miR396 to assess whether miRNAs reported to be involved in plant primary developmental processes 7

such as phase transitions, pattern formation, and morphogenesis, are affected by cold stress during 8

spike development in the TGMS line (Jones-Rhoades et al., 2006; Axtell and Bowman, 2008; Chen, 9

2009; Nogueira et al., 2009). 10

TaqMan qPCR analyses showed that six miRNAs and one tasiRNA-ARF were differentially 11

expressed during cold stress, compared with control conditions (Figure 2). Surprisingly, all of them 12

were significantly repressed at the early stage of the cold treatment (Figure 2). Several studies have 13

focused on the regulatory roles of miRNAs in response to abiotic stress (Phillips et al., 2007; Sunkar 14

et al., 2007). miR393 is responsive to all tested stresses in Arabidopsis (Sunkar et al., 2007). In 15

addition, several cold- or low temperature-responsive miRNAs have been identified by many 16

platforms (Sunkar and Zhu, 2004; Lu et al., 2008b; Zhou et al., 2008; Zhang et al., 2009a; Lee et al., 17

2010; Lv et al., 2010; An et al., 2011). However, for several miRNAs, the expression profiles were 18

inconsistent among plant species, and even among different tissues of the same species (Supplemental 19

Table S3). During cold stress, tae-miR393 was repressed in spike tissues of the TGMS line, the 20

reverse of its expression pattern in Arabidopsis (Sunkar et al., 2007). However, the target genes of 21

tae-miR393 did not show significant changes in expression levels during cold stress (Figure 3). This 22

result indicated that the 10°C treatment causes male sterility of the TGMS line, but is less stressful 23

than extreme cold conditions for common wheat lines. In Arabidopsis, low ambient temperature (16°C) 24

treatment resulted in decreased expression of miR172 during flowering. We obtained a similar result 25

in the present study; tae-miR172a was significantly repressed at the early stage of spike development 26

during cold stress (Figure 3). A previous study demonstrated that miR172 plays an important role in 27



24

regulation of flowering time under normal (non-stress) temperature conditions (Lee et al., 2010). The 1

accumulation of miR172 contributes to complete flowering through negative regulation of AP2-like 2

transcription factors. We identified one AP2-like with a predicted miR172 target site in our degradome 3

dataset; however, the expression pattern of the target gene was not completely anti-correlated as would 4

have been expected (Supplemental Figure S6). Previous studies demonstrated that miR172 mainly 5

plays its regulatory role via translational repression rather than by transcript cleavage (Aukerman and 6

Sakai, 2003; Chen, 2004). Although more research is required to identify the downstream target genes 7

of miR172, these results indicated that miR172-mediated regulatory pathways in response to 8

non-stress low temperature may be similar in Arabidopsis and the TGMS wheat line. 9

In addition, cold-responsive members of a miRNA family may be further differentiated by their 10

temporal response to cold treatment. Thus, the functions of plant miRNAs can be dissimilar even if 11

they share a high degree of sequence similarity and belong to the same family. In our smRNA dataset, 12

we identified nine members of the miR166 family. We selected the five most abundant of these 13

miRNAs for TaqMan qPCR analyses, and found that they showed similar expression patterns in cold 14

stress and control conditions and were insensitive to cold stress in spike tissues of the TGMS line 15

(Figure 2). Two HD-ZIP transcription factors, which could not be detected by extended qPCR cycles, 16

were completed repressed by members of the miR166 family (Table II). A previous study 17

demonstrated that the miR166 family exhibits complex spatiotemporal patterns of expression in 18

developing primordia (Nogueira et al., 2009). Furthermore, several studies showed that members of 19

miR166 family are induced during cold stress (Supplemental Table S3). In contrast, our results could 20

indicate that the miR166 family plays a redundant role during spike development, because its 21

members showed no changes in expression levels during cold stress in the TGMS line. Members of 22

the miR166 family may function in the formation or maintenance of floral organs after phase 23

transition. 24

Members of the miR166 family showed different expression patterns (Figure 2). Tae-miR167 and 25

tae-miR167e showed similar expression patterns in cold and control conditions (Figure 2). 26

Interestingly, Tae-miR167 and tae-miR167e showed completely reversed expression profiles in spikes 27



25

of the TGMS line (Figure 2). Tae-miR167c and tae-miR167d showed distinct expression patterns to 1

response cold stress in the TGMS line (Figure 2). The miR167 family is strongly expressed in floral 2

organs of Arabidopsis, and the target genes of the miR167 family are ARF genes (Reinhart et al., 2002; 3

Ru et al., 2006; Wu et al., 2006; Fujioka et al., 2008). Additionally, individual miRNAs within the 4

miR167 family target different ARF genes in spike tissues of the TGMS line (Table II). Taken together, 5

these results suggest that each individual miRNA in the miR167 family has a unique function in spike 6

development in the TGMS line via targeting specific ARF transcripts. 7

ARF signaling pathways activated by miR167 and tasiRNA-ARF in the TGMS line during cold 8

stress 9

Cold stress-responsive miRNAs may be involved in signaling pathway(s) during spike development 10

in the TGMS line. An interesting observation is that cold-stress responsive tae-miR167d and 11

tasiRNA-ARF may affect auxin-signaling pathways. The expression of tae-miR167d and 12

tasiRNA-ARF were dramatically depressed at an early stage of spike development (L1.5 stage) during 13

cold stress (Figure 2). The accumulations of tae-miR167d and tasiRNA-ARF were inversely 14

correlated with the expression levels of three ARF transcripts (Figure 2). Another striking observation 15

is that one ARF targeted by tasiRNA-ARF was significantly induced (70-fold) during cold stress 16

(Figure 3). 17

Auxin regulates many important aspects of plant growth and development, as well as responses to 18

environmental stresses (Cecchetti et al., 2008; Sundberg and Østergaard, 2009; Vanneste and Friml, 19

2009; Sakata et al., 2010). Within the auxin-signaling pathway, ARFs function as core positive and 20

negative regulators (Guilfoyle and Hagen, 2007; Lau et al., 2008). miR167 plays a role in regulating 21

the auxin signal by cleaving atARF6 and atARF8 transcripts during anther development (Nagpal et al., 22

2005; Ru et al., 2006; Wu et al., 2006). miR167 was abundantly accumulated in floral organs during 23

an early stage of anther development (Fujioka et al., 2008; An et al., 2011). In Arabidopsis, 24

overexpression of miR167 causes male sterility (Ru et al., 2006; Wu et al., 2006). These observations 25

indicated that miR167 plays an important role in accurate regulation of anther development. 26



26

Combined with our results, miR167 might also play a role in the cold stress response by affecting the 1

auxin-signaling pathway, which possibly links cold stress with male sterility in the TGMS line. 2

The roles of tasiRNA-ARF in the spike remain obscure. However, tasiRNA-ARF regulates target 3

genes, including ARF3/ETTIN mRNA, in a gradient across the leaf primordium. Interestingly, 4

modeling of a polarized maize leaf suggests that morphogen-like movement of TAS3 tasiRNA could 5

sharpen the boundaries of target gene expression (Nogueira et al., 2009; Rubio-Somoza et al., 2009). 6

In Arabidopsis, the juvenile-to-adult phase transition is normally suppressed by TAS3a tasiRNAs 7

through negative regulation of ARF3 mRNA (Fahlgren et al., 2006). Late stages of flower 8

development in Arabidopsis, rice, and Lotus japonicus rely on regulated ARF3 function (Hunter et al., 9

2006; Liu et al., 2007b; Yan et al., 2009). Furthermore, recent data indicate that tasiRNAs are also 10

involved in environmental stress responses (Moldovan et al., 2010). Therefore, it is tempting to 11

speculate that during cold stress, the abnormal decline of tasiRNA-ARF levels contributes to aberrant 12

development of the anther in the TGMS line, through the negative regulation of ARFs. 13

Because the activity of ARFs is known to be controlled by endogenous auxin levels, we 14

investigated the auxin levels in the anther in cold and control conditions. The auxin levels in the anther 15

did not change during cold stress (Supplemental Figure S7), suggesting that the abnormally repressed 16

miR167 and tasiRNA-ARF directly contribute to up-regulation of three ARFs, consequently causing 17

male sterility in the TGMS line during cold stress. 18

A previous study showed that miR167 accumulated in the vasculature of the anther (Válóczi et al., 19

2006). However, we detected expression of miR167 throughout the entire anther, including the 20

vascular bundle, PMC, tapetum, and middle layer; thus, expression of miR167 showed a similar 21

spatiotemporal pattern to that of tasiRNA-ARF (Figure 5). This difference suggests that the expression 22

patterns of members of the miR167 family may differ in different developmental stages of the anther, 23

or that miR167 may move between cells, like tasiRNA-ARF as described elsewhere (Nogueira et al., 24

2009). Both miR167 and tasiRNA-ARF showed depressed expressions in PMCs during cold stress 25

(Figure 5), which is consistent with our previous finding that PMCs are more vulnerable than 26



27

sporogenous cells during anther development (Tang et al., 2011).1



28

Conclusion 1

In summary, we have presented an extensive survey of the smRNAs showing differential expression 2

profiles in response to cold stress in a TGMS line of wheat. These cold-responsive smRNAs and their 3

target genes are possibly involved in anther development and regulation of adaptive responses to cold 4

stress. Research on the miR167 family and tasiRNA-ARF target regulation may increase our 5

understanding of the biological role of these smRNAs and their contribution to cold-induced male 6

sterility in wheat TGMS lines. Our work has opened a new avenue for functional studies on 7

smRNAs-mediated gene regulation in response to cold stress in wheat TGMS lines.8



29

Materials and methods 1

Plant materials and growth conditions 2

The wheat (Triticum aestivum) TGMS line BS366 was used in this study (Tang et al., 2011). As 3

described in our previous report, the cold treatment was initiated when plants were at the flag leaf 4

stage (anther length of approx. 1.5 mm), when the flag leaf had half-emerged from the collar of the 5

penultimate leaf (Tang et al., 2011). During the cold treatment, plants of BS366 were grown at 10°C 6

with a 12-h light/12-h dark photoperiod for 5 days. Under control conditions, plants of BS366 were 7

grown at 20°C with a 12-h light/12-h dark photoperiod. The reproductive growth of individual plants 8

was well synchronized under the controlled conditions in the growth phytotrons (Koito, Tokyo, 9

Japan). 10

Sample collection and RNA isolation 11

During the cold treatment, the anthers of the TGMS line developed from the pollen mother cell 12

stage to the meiosis stage. We analyzed spikes from anthers at three developmental stages (including 13

the T0 stage): 1.5-mm anthers in which secondary sporogenous cells were formed; 2.2-mm anthers in 14

which all cell layers were present and mitosis had ceased; and 3.0-mm anthers at the meiotic division 15

stage (Tang et al., 2011). To maximize the morphological synchronicity of samples at each individual 16

stage, approximately 20 spikes were collected from primary stems at each stage. The spikes at 17

corresponding stages were also harvested from stems of plants kept in control conditions, using leaf 18

age index and anther length as guide. Total RNAs were isolated from spike tissues using TRIzol 19

reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. 20

Small RNA library, DGE library and degradome library construction 21

After total RNA isolation, size-selected small RNAs (smRNAs) 16 to 30 nt in length were obtained 22

from total RNA by size fractionation. SmRNA libraries were constructed following the instructions of 23

the manufacturer. The 3' tag Digital Gene Expression (DGE) libraries were constructed with 24

Illumina’s DGE Tag Profiling kit according to the manufacturer’s protocol. The degradome libraries 25



30

were constructed as previously described by Addo-Quaye et al. (2008) and German et al. (2008). 1

SmRNA reads, DGE tags, and degradome reads were all generated by an Illumina Genome Analyzer 2

(BGI, Shenzhen, China). 3

Bioinformatic analysis of sequencing data 4

The raw sequencing datasets were preprocessed by the Fastx-toolkit pipeline to filter low quality 5

reads and to trim adaptors (http://hannonlab.cshl.edu/fastx_toolkit/index.html). The ESTs from NCBI 6

public and private wheat EST databases were assembled by CAP3 into wheat unigenes for 7

bioinformatic analysis (Huang and Madan, 1999; Yang et al., 2009). For the smRNA libraries, 8

smRNAs ranging from 18 to 28 nt were collected and mapped to the wheat unigene dataset using 9

SOAP2 (Li et al., 2009). SmRNA reads showing sequences identical to those of known miRNAs in 10

the miRBase were selected as the miRNA dataset of the wheat TGMS line (Griffiths-Jones, 2006). We 11

modified the perl scripts previously described by Chen et al. (2007) to identify smRNAs phased in 21 12

nt increments that could represent potential TAS genes. 13

Before annotation of DGE tags, a preprocessed database of all possible CATG + 17 nt tag sequences 14

was created from assembled wheat unigenes. The DGE tags were aligned against the preprocessed 15

database using megaBLAST with a size of 12 and filtering of low-complexity regions turned off 16

(Morgulis et al., 2008). Only DGE tags that perfectly matched to tags in the preprocessed database 17

without mismatches and gaps were considered. DGE tags mapping to unigenes with multiple 18

homologous family members were excluded from our analysis. When there were multiple types of 19

DGE tags aligned to different locations of the same unigene, the unigene expression levels were 20

represented by the sum of all. The expressions of smRNAs and unigenes were normalized to tag 21

counts per million total tags (TPM) in each lane of a flow cell. 22

For the degradome libraries, we used CleaveLand pipeline to find sliced miRNA targets using the 23

wheat unigenes, viridiplantae miRBase 15.0 mature miRNAs, and miRNAs identified in our study as 24

inputs (Addo-Quaye et al., 2009a). All alignments with scores up to 7 and no mismatches at the 25



31

cleavage site (between the 10th and 11th nucleotides of mature miRNA) were considered as candidate 1

miRNA targets. 2

All smRNA reads and degradome tags obtained in this study have been deposited in the GEO 3

database with the accession number GSE36867 and GSE37134, respectively. 4

TaqMan miRNA assay and real-time PCR for mRNA quantification 5

TaqMan miRNA assays were used to quantify miRNAs in this study, each with two independent 6

biological replicates, as described previously (Chen et al., 2005). Briefly, 5 ng total RNA was 7

incubated with 1.5 µl 10× reaction buffer, 0.15 µl dNTPs (100 mM), 0.19 µl RNase inhibitor, 1 µl 8

reverse transcriptase, and 3 µl stem-loop RT primer (Applied Biosystems, Foster City, USA) in a 9

15-µl reaction mixture. The real-time PCR for each assay was set up as a 20 µl reaction mixture 10

containing 1.5 μl cDNA, 10 μl Taqman 2× Universal PCR master mix, and 1 μl 20× TaqMan assay 11

mix including miRNA-specific primers and the TaqMan probe. The reaction was incubated in an 12

Applied Biosystems 7900HT Fast Real-Time PCR System in 384-well plates at 95°C for 10 min, 13

followed by 40 cycles of 95°C for 15 s and 60°C for 60 s. Normalization was performed with small 14

nuclear RNA U6 (NCBI accession number: X63066). Comparative real-time PCR was performed in 15

triplicate, including template-free reactions. 16

For mRNAs, quantitative real-time PCR (qPCR) was performed with a MiniOpticon (Bio-Rad, 17

Hercules, CA, USA) using Maxima SYBR Green qPCR Master mix (Fermentas, Vilnius, Lithuania). 18

TaGAPdH was used as the internal standard to reduce systematic and biological variance. Three 19

replicates were analyzed for each sample along with template-free reactions as negative controls. 20

The relative expression ratio was calculated using the ‘Livak’ method (Livak and Schmittgen, 2001). 21

We used t-tests to detect significant differences (P < 0.05) in expression between two samples. 22

RNA ligase-mediated 5’ rapid amplification of cDNA ends (RLM-RACE) 23

Total RNAs from spikes were used to purify mRNA using the Oligotex kit (Qiagen, Germany). 24

5’-RACE analysis was carried out using the poly(A) plus fraction and a GeneRacer kit (Invitrogen, 25



32

USA). The final PCR products were detected by gel electrophoresis and cloned for sequencing. 1

Primers used in RLM-5’RACE are listed in Supplemental Table S4. 2

Construction of anther tissue microarray (TMA) 3

The formalin-fixed and paraffin-embedded anthers from cold-stressed or control plants of the 4

TGMS line were used to construct TMAs. The entire paraffin-embedded anthers as tissue cores were 5

transferred to the recipient tissue microarray blocks using a precision instrument (Chemicon model 6

ATA-100, Chemicon International, Temecula, CA, USA). For each anther developmental stage, 20 7

individual anthers were placed side-by-side on the recipient tissue microarray block. The block was 8

then cut into 6-µm slices with a microtome (Leica, Heidelberg, Germany). The cross sections were 9

placed on positively charged slides, and then heated to 40°C for 30 min. After leveling paraffin and 10

tissues, the TMA was cooled to 4°C for 15 min. 11

Small RNA in situ hybridization 12

We used anther TMAs for smRNA in situ hybridization as described by Kidner and Timmermans 13

(2006). Locked nucleic acid probes with sequences complementary to those of smRNAs were 14

synthesized by TakaRa (Japan) and digoxigenin-labeled with the DIG Oligonucleotide 3’-end 15

Labeling kit (Roche Applied Science, Indianapolis, IN, USA). Ten picomoles of each probe was used 16

for each TMA slide, and hybridization and washing steps were performed at 55°C. Two TMA slides 17

were prepared for each probe.18



33

Acknowledgements 1

The authors acknowledge Prof. Zongxiu Sun, Prof. Yaping Fu and Dr. Wenzhen Liu (China National 2

Rice Research Institute) for their technical assistance. The authors thank the two anonymous referees 3

for their constructive comments that have improved the presentation of this manuscript.4



34

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Figure 1. Targets of smRNAs identified by degradome sequencing are shown as target plots (t-plots) 1

by identical reads. Signature abundance (absolute number) along the indicated transcript is plotted. 2

Red dots on the X-axis indicate predicted cleavage sites. Red lines indicate signatures produced by 3

miRNA-directed cleavage. The t-plots for category I (A), category II (B), and category III (C) are 4

shown. In (A)–(C), cleavage frequency as determined by gene-specific 5’ RACE at the indicated 5

position is shown below t-plot. In ARF transcripts with dual target sites for tasiRNA-ARF (B, C), only 6

the second (3’) cleavage site was validated by 5’ RACE. (D), cleavage abundance on TAS3b precursor 7

by tae-miR390.8



46

Figure 2. Differentially expressed small RNAs in response to cold stress in spikes of wheat TGMS 1

line. Relative fold change (FC) greater than 1.5 or less than 0.5 are highlighted in red. The ** and * 2

indicate the significant differences between cold-stress and control at P < 0.01 and P< 0.05 levels, 3

respectively.4



47

Figure 3. qPCR analysis of target genes in spikes from TGMS line in cold and control conditions. 1

Error bars indicate standard deviation. 2



48

Figure 4. Self-organizing map (SOM) clusters of expression profiles. Wheat unigenes differentially 1

expressed in cold and control conditions were subjected to SOM clustering based on their relative 2

expression levels in both conditions. Y-axis represents normalized log2 of transcript-expression levels. 3

X-axis represents anther developmental stages in cold (L) and control (C) treatments. (A), SOM 4

cluster includes ARF gene EST Contig1892 that was targeted by tasiRNA-ARF. (B), SOM cluster 5

includes ARF genes EST Contig9875 and Contig4296, which were targeted by tae-miR167d and 6

tasiRNA-ARF, respectively.7



49

Figure 5. Differential accumulation of miRNAs/tasiRNA-ARF in anthers of wheat TGMS line. 1

Cross-sections of anthers in anther tissue microarray were hybridized with 5’ and 3’ double-labeled 2

LNA-modified oligonucleotides detecting tae-miR172a (A-F), tae-miR396a (G-L), tae-miR167d 3

(M-R), and TAS3a-5’D6(+) (S-X). Anther developmental stage and treatment conditions (L: cold 4

stress; C: control condition) are shown in parentheses. LNA-probe complementary to Caenorhabditis 5

elegans let-7 serves as negative control. Brown staining shows probe localization. ML, middle layer; 6

PMC, pollen mother cell; Ta, tapetum; VB, vascular bundles. Scale bar represents 50 µm. 7



1

EST Contig15112 (ARF; Control) EST Contig15112 (ARF; Cold) A

EST Contig1892 (ARF; Control) EST Contig1892 (ARF; Cold)

B

Position in transcript

Position in transcript Position in transcript


Tag

s

nu

mbe

r

Tag

s

nu

mbe

r

Tag

s

nu

mbe

r

Tag

s

nu

mbe

r



2

Figure 1. Targets of smRNAs identified by degradome sequencing are shown as target plots

(t-plots) by identical reads. Signature abundance (absolute number) along the indicated transcript

is plotted. Red dots on the X-axis indicate predicted cleavage sites. Red lines indicate signatures

produced by miRNA-directed cleavage. The t-plots for category I (A), category II (B), and

category III (C) are shown. In (A)–(C), cleavage frequency as determined by gene-specific 5’

RACE at the indicated position is shown below t-plot. In ARF transcripts with dual target sites for

tasiRNA-ARF (B, C), only the second (3’) cleavage site was validated by 5’ RACE. (D), cleavage

abundance on TAS3b precursor by tae-miR390.

EST Contig4296 (ARF; Control) EST Contig4296 (ARF; Cold)

C

TAS3b (Control) TAS3b (Cold)

D



Tag

s

nu

mbe

r

Tag

s

nu

mbe

r

Tag

s

nu

mbe

r

Tag

s

nu

mbe

r



3

Figure 2. Differentially expressed small RNAs in response to cold stress in spikes of wheat

TGMS line. Relative fold change (FC) greater than 1.5 or less than 0.5 are highlighted in red. The

** and * indicate the significant differences between cold-stress and control at P < 0.01 and P<

0.05 levels, respectively.



4

Figure 3. qPCR analysis of target genes in spikes from TGMS line in cold and control conditions. Error bars indicate standard deviation.

tae-miR167d tae-miR167 TAS3a-5’D6(+) tae-miR160 tae-miR393 tae-miR396a

L1.5 vs

C1.5

L2.2 vs C2.2 L3.0 vs

L1.5 vs

C1.5 L2.2 vs C2.2

L1.5 vs

C1.5 L2.2 vs C2.2

L1.5 vs

C1.5 L2.2 vs C2.2

L3.0 vs

L1.5 vs

C1.5 L2.2 vs C2.2

L1.5 vs C1.5 L2.2 vs

C2.2

L1.5 vs C1.5 L2.2 vs

C2.2

L1.5 vs C1.5 L2.2 vs

C2.2

L1.5 vs

C1.5 L2.2 vs C2.2

L1.5 vs C1.5 L2.2 vs

C2.2

L1.5 vs

C1.5 L2.2 vs

C2.2

L1.5 vs C1.5 L2.2 vs

C2.2 L3.0 vs

Contig29283 Contig9875 Contig28378 Contig4296 Contig1892 Contig15112 GH726882 Contig19398 CK208780 Contig21707 CJ645826 C0347544

w

ww

.plantphysiol.orgon M

arch 29, 2018 - Published by

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nloaded from

Copyright ©

2012 Am

erican Society of P

lant Biologists. A

ll rights reserved.


5

Figure 4. Self-organizing map (SOM) clusters of expression profiles. Wheat unigenes differentially expressed in cold and control conditions were subjected to SOM

clustering based on their relative expression levels in both conditions. Y-axis represents normalized log2 of transcript-expression levels. X-axis represents anther

developmental stages in cold (L) and control (C) treatments. (A), SOM cluster includes ARF gene EST Contig1892 that was targeted by tasiRNA-ARF. (B), SOM

cluster includes ARF genes EST Contig9875 and Contig4296, which were targeted by tae-miR167d and tasiRNA-ARF, respectively.

A B

T0 C1.5 C2.2 C3.0 T0 C1.5 C2.2 C3.0 T0 L1.5 L2.2 L3.0 T0 L1.5 L2.2 L3.0

w

ww



Dow

nloaded from

Copyright ©

2012 Am

erican Society of P

lant Biologists. A

ll rights reserved.


6

(A) (C1.5) (B) (C2.2) (C) (C3.0)

(D) (L1.5) (E) (L2.2) (F) (L3.0)

(G) (C1.5) (H) (C2.2) (I) (C3.0)

(J) (L1.5) (K) (L2.2) (L) (L3.0)

(M) (C1.5) (N) (C2.2) (O) (C3.0)

(P) (L1.5) (Q) (L2.2) (R) (L3.0)

PMC V

Ta

ML



7

Figure 5. Differential accumulation of miRNAs/tasiRNA-ARF in anthers of wheat TGMS line.

Cross-sections of anthers in anther tissue microarray were hybridized with 5’ and 3’

double-labeled LNA-modified oligonucleotides detecting tae-miR172a (A-F), tae-miR396a (G-L),

tae-miR167d (M-R), and TAS3a-5’D6(+) (S-X). Anther developmental stage and treatment

conditions (L: cold stress; C: control condition) are shown in parentheses. LNA-probe

complementary to Caenorhabditis elegans let-7 serves as negative control. Brown staining shows

probe localization. ML, middle layer; PMC, pollen mother cell; Ta, tapetum; VB, vascular bundles.

Scale bar represents 50 µm.

(S) (C1.5) (T) (C2.2) (U) (C3.0)

(V) (L1.5) (W) (L2.2) (X) (L3.0)



8

Table I Known miRNAs present in spikes of wheat TGMS line

miRNA

family Namea Sequence (5' to 3')b Length (nt) TPMc

Typical homology in

miRBase pri-miRNA (EST no.)

miR156 tae-miR156a UGACAGAAGAGAGUGAGCAC 20 2263.87 ath-miR156a

tae-miR156b CGACAGAAGAGAGUGAGCAC 20 1.6 ath-miR156g

tae-miR156c UGACAGAAGAGAGCGAGCAC 20 1.44 zma-miR156k

tae-miR156d UGACAGAGGAGAGUGAGCAC 20 0.93 vvi-MIR156e

tae-miR156e UGACAGAAGAGAGAGAGCAC 20 0.84 ahy-miR156a

Ta_zma-miR156l* GCUCACUGCUCUAUCUGUCACC 22 12.67 zma-miR156l*

miR157 tae-miR157 UUGACAGAAGAUAGAGAGCAC 21 1.36 ath-miR157a

miR159 tae-miR159a UUUGGAUUGAAGGGAGCUCUG 21 7.24 tae-miR159a

miR160 tae-miR160 UGCCUGGCUCCCUGUAUGCCA 21 6.86 tae-miR160

tae-miR160b UGCCUGGCUCCCUGAAUGCCA 21 0.54 osa-miR160f

Ta_zma-miR160b* GCGUGCAAGGAGCCAAGCAUG 21 3.85 zma-miR160b*

Ta_zma-miR160a* GCGUGCAAGGGGCCAAGCAUG 21 1.35 zma-miR160a*

miR164 tae-miR164 UGGAGAAGCAGGGCACGUGCA 21 99.87 tae-miR164

tae-miR164b UGGAGAAGCAGGGCACGUGCU 21 2.96 osa-miR164d AEOM01043585.1

miR165 tae-miR165 UCGGACCAGGCUUCAUCCCCC 21 10.64 ath-miR165a

miR166 tae-miR166a UCGGACCAGGCUUCAUUCCCC 21 8342.82 ath-miR166a

tae-miR166b UCGGACCAGGCUUCAAUCCCU 21 1673.45 osa-miR166k

tae-miR166c UCGGACCAGGCUUCAUUCCUU 21 982.4 ptc-miR166n

tae-miR166d UCGGACCAGGCUUCAUUCCCU 21 828.67 osa-miR166m

tae-miR166e UCGGACCAGGCUUCAUUCCUC 21 32.48 osa-miR166i

tae-miR166f UCGGACCAGGCUUCAUUCCU 20 11.86 sbi-miR166k

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tae-miR166g UCGGACCAGGCUUCAUUCCCUU 22 3.8 crt-miR166b

tae-miR166h UCGAACCAGGCUUCAUUCCCC 21 2.56 osa-miR166e

tae -miR16i UCGGACCAGGCUUCAUUCCCCC 22 0.66 ctr-miR166

tae-miR166j UCGGACCAGGCUUCAUUCCUA 21 0.73 mtr-miR166b

tae-miR166k UCGGACCAGGCUCCAUUCCUU 21 0.37 ptc-miR166p

Ta_zma-miR166g* GGAAUGUUGUCUGGUUGGAGA 21 10.3 zma-miR166g*

Ta_zma-miR166a* GGAAUGUUGUCUGGCUCGGGG 21 7.79 zma-miR166a*

Ta_zma-miR166b* GGAAUGUUGUCUGGUUCAAGG 21 4.22 zma-miR166b*

miR167 tae-miR167 UGAAGCUGCCAGCAUGAUCUA 21 2155.13 tae-miR167

tae-miR167c UGAAGCUGCCAGCAUGAUCUGA 22 4429.17 ccl-miR167a AEOM01105062.1

tae-miR167d UGAAGCUGCCAGCAUGAUCUU 21 37.06 ahy-miR167-5p

tae-miR167e UGAAGCUGCCAGCAUGAUCUG 21 14.15 osa-miR167d

tae-miR167f UGAAGCUGCCAGCAUGAUCUC 21 2.07 vvi-miR167c

tae-miR167g UGAAGCUGCCAGCAUGAUCUGG 22 1.59 ath-miR167d

miR168 tae-miR168a UCGCUUGGUGCAGAUCGGGAC 21 16321.81 osa-miR168a

tae-miR168b UCGCUUGGGCAGAUCGGGAC 20 0.64 sof-miR168b

miR169 tae-miR169a UAGCCAAGGAUGACUUGCCGG 21 24.07 osa-miR169e

tae-miR169b UAGCCAAGGAUGAAUUGCCAG 21 10 ata-miR169

tae-miR169c CAGCCAAGGAUGACUUGCCGG 21 9.21 ath-miR169b

tae-miR169d CAGCCAAGGAUGACUUGCCGA 21 7.03 ath-miR169a

tae-miR169e UAGCCAAGGAUGAUUUGCCU- 20 1.04 sbi-miR169o BJ225371.1

miR171 tae-miR171a UGAUUGAGCCGUGCCAAUAUC 21 67.24 tae-miR171a

tae-miR171b UUGAGCCGUGCCAAUAUCACG 21 0.74 tae-miR171b

tae-miR171c UGAUUGAGCCGCGCCAAUAUC 21 14.38 ath-miR171a

miR172 tae-miR172a AGAAUCUUGAUGAUGCUGCAU 21 356.03 ath-miR172a

tae-miR172b GGAAUCUUGAUGAUGCUGCAU 21 22.38 ath-miR172e AEOM01013727.1

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tae-miR172d AGAAUCUUGAUGAUGCUGCA 20 1.35 zma-miR172a

miR319 tae-miR319 UUGGACUGAAGGGUGCUCCCU 21 7.01 bdi-miR319b

miR390 tae-miR390 AAGCUCAGGAGGGAUAGCGCC 21 231 ath-miR390a AEOM01223153.1

tae-miR390* CGCUAUCUAUCCUGAGCUCCA 21 1.67 zma-miR390a* AEOM01223153.1

miR393 tae-miR393 UUCCAAAGGGAUCGCAUUGAU 21 125.25 osa-miR393

miR394 tae-miR394 UUGGCAUUCUGUCCACCUCC 20 3.31 ath-miR394a

miR395 tae-miR395b UGAAGUGUUUGGGGGAACUC 20 3.64 tae-miR395b

miR396 tae-miR396a UCCACAGGCUUUCUUGAACUG 21 221.13 osa-miR396d CJ776495.1

tae-miR396b UUCCACAGCUUUCUUGAACUU 21 10.56 ath-miR396b

tae-miR396c UUCCACAGCUUUCUUGAACUG 21 5.74 ath-miR396a

Ta_zma-miR396f* GGUCAAGAAAGCUGUGGGAAG 21 141.45 zma-miR396f*

Ta_zma-miR396b* GUUCAAUAAAGCUGUGGGAAA 21 8.02 zma-miR396b*

Ta_osa-miR396e-3p AUGGUUCAAGAAAGCCCAUGGAAA 24 0.84 osa-miR396e-3p

miR399 tae-miR399 UGCCAAAGGAGAAUUGCCC 19 1.42 tae-miR399

tae-miR399b UGCCAAAGGAGAGUUGCCCUG 21 6.17 ath-miR399b CJ667854.1

Ta_zma-miR399h* GUGCAGUUCUCCUCUGGCAUG 21 5.7 zma-miR399h*

miR408 tae-miR408b -UGCACUGCCUCUUCCCUGGC 20 0.68 ath-miR408

miR444 Ta_osa-miR444c.1 UGUUGUCUCAAGCUUGCUGCC 21 10.38 osa-miR444b.1

Ta_osa-miR444d.1 UGCAGUUGCUGCCUCAAGCUU 21 8.84 osa-miR444a.2

Ta_osa-miR444c.2 UGCAGUUGUUGUCUCAAGCUU 21 2.96 osa-miR444b.2

miR528 tae-miR528 UGGAAGGGGCAUGCAGAGGAG 21 643.26 osa-miR528

miR827 tae-miR827 UUAGAUGACCAUCAGCAAACA 21 24.07 osa-miR827a

miR894 tae-miR894 GUUUCACGUCGGGUUCACCA 20 173.55 ppt-miR894

miR1135 tae-miR1135 CUGCGACAAGUAAUUCCGAACGGA 24 0.49 tae-miR1135

miR1318 tae-miR1318 UCAGGAGAGAUGACACCGACG 21 4.31 osa-miR1318

miR1432 tae-miR1432a AUCAGGAGAGAUGACACCGAC 21 1.27 osa-miR1432

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tae-miR1432b CUCAGGAGAGAUGACACCGAC 21 2.03 sbi-miR1432

miR1436 tae-miR1436 ACAUUAUGGGACGGAGGGAGU 21 0.82 osa-miR1436

miR2118 tae-miR2118 UUCCUGAUGUCUCCCAUUCCUA 22 0.58 zma-miR2118e

miR2275 tae-miR2275 UUUGGUUUCCUCCAAUAUCUCA 22 0.74 osa-miR2275a

Ta_zma-miR2275b-3p UUCAGUUUCCUCUAAUAUCUCA 22 0.64 zma-miR2275b-3p

a ‘Ta’ at the start of the name indicates homologous miRNA*. b Underlined and red nucleotides represent non-conserved nucleotides among wheat and other plant

species. Dash indicates deletion of non-conserved nucleotide. c Relative number of reads was obtained by normalizing reads counts of each miRNA in each smRNA

cDNA library to tags per million (TPM) (Supplemental Table S2). Reads only encompass defined mature miRNAs. Maximum TPM of each miRNA in the seven

smRNA cDNA libraries is shown.

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Table II. Identified targets of known miRNAs/tasiRNAs in wheat

miRNA/tasiRNA

family miRNAs/tasiRNAs

Target

Unigenea Category Target annotation

miR156/miR157 tae-miR156a, tae-miR157 CJ811938 II SBP

BJ314081 I SBP

miR159/miR319 tae-miR159a, tae-miR319 Contig22875 I GAMYB

Contig12163 I GAMYB

miR160 tae-miR160

Contig15112 I ARF

Contig19398 I ARF

GH726882 I ARF

miR165/miR166

tae-miR165, tae-miR166a, tae-miR166b, tae-miR166c,

tae-miR166d, tae-miR166e, tae-miR166f, tae-miR166g,

tae-miR166i, tae-miR166j

CJ629056

GH723151

I HD-ZIP

I HD-ZIP

miR167

tae-miR167 Contig29283 II ARF

tae-miR167d Contig9875 II ARF

tae-miR167f CJ906388 I ARF

miR169 tae-miR169a, tae-miR169b, tae-miR169c, tae-miR169d,

tae -miR169e

Contig4061

Contig28782

Contig20398

Contig20251

I CCAAT-binding transcription factor




miR171 tae-miR171a CK210886 I GRAS

miR172 tae-miR172a, tae-miR172b Contig803 I AP2

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miR390 tae-miR390 CJ711765 II TAS3b

miR393 tae-miR393 Contig21707 III Transport inhibitor response 1-like protein

CK208780 I Transport inhibitor response 1-like protein

miR394 tae-miR394 BE427348 I F-box protein

CV781001 I F-box protein

miR396 tae-miR396a CO347544 I GRF

CJ645826 I GRF

miR408 tae-miR408b CK216079 I Unknown

tasiRNA TAS3a 5’D6(+)

TAS3b 5’D4(+)

Contig1892 I ARF

Contig4296 II ARF

Contig28378 III ARF

a Contig sequences were assembled from wheat ESTs (shown in Supplemental File S1). Other identifiers are NCBI EST accession numbers. Bold entries were

independently confirmed by RLM-5’RACE.

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