Microarray-based identification of conserved microRNA from wheat and their expression profiles response to Puccinia striiformis f. sp. tritici

Figures & data

Fig. 1 Identification of miRNAs by microarray. The identification of miRNAs was screened by miRNA array analysis. Total RNA was extracted from the leaves of 10-day-old wheat seedlings. One hundred micrograms of total RNA was used for the array. The extracted small RNAs were 5′ end labelled and probed against the antisense DNA oligonucleotides spotted onto the membrane.

Fig. 2 Validation of miRNAs using northern blot. Total RNA (80 μg) was used for the RNA gel blot analysis for the mock and wheat leaves inoculated with CYR23 and CYR31. The wheat leaves were sampled for the analysis at 24 and 48 hpi. M means MOCK, 23 means CYR23, and 31 means CYR31. U6 was used as the loading control. The sizes of the hybridization bands of ath-miR156a, ath-miR159a, ath-miR160a, osa-miR164c, ptc-mir164f, ath-miR164a, ath-miR167a, osa-miR160f, ath-miR166a and osa-miR168a were approximately 21 bp.

Table 1. Sequence analysis of the array-identified miRNAs in wheat.

Array-identified miRNAs	miRNA sequence	RNA gel blot analysis verified miRNAs	Sequence of miRNAs in wheat
ath-miR156a	TGACAGAAGAGAGTGAGCAC	tae-miR156	TGACAGAAGAGAGTGAGCACA
ath-miR159a	TTTGGATTGAAGGGAGCTCTA	tae-miR159ab	TTTGGATTGAAGGGAGCTCTG
ath-miR160a	TGCCTGGCTCCCTGTATGCCA	tae-miR160	TGCCTGGCTCCCTGTATGCCA
osa-miR160 f	TGCCTGGCTCCCTGAATGCCA
osa-miR164 c	TGGAGAAGCAGGGTACGTGCA	tae-miR164	TGGAGAAGCAGGGCACGTGCA
pt-cmiR164 f	TGGAGAAGCAGGGCACATGCT
ath-miR164a	TGGAGAAGCAGGGCACGTGCA
ath-miR167a	TGAAGCTGCCAGCATGATCTA	tae-miR167	TGAAGCTGCCAGCATGATCTA
ath-miR166a	TCGGACCAGGCTTCATTCCCC	PN-tae-miR166a	TCGGACCAGGCTTCATTCCCC
osa-miR168a	TCGCTTGGTGCAGATCGGGAC	PN-tae-miR168a	TCGCTTGGTGCAGATCGGGAC
ptc-miR160 h	TGCCTGGCTCCCTGCATGCCA	no
sbi-miR164 c	TGGAGAAGCAGGACACGTGAG	no
ath-miR165a	TCGGACCAGGCTTCATCCCCC	no
osa-miR166 l	TCGGACCAGGCTTCAATCCCT	no
osa-miR169e	TAGCCAAGGATGACTTGCCGG	no
ath-miR169a	CAGCCAAGGATGACTTGCCGA	no
ath-miR390a	AAGCTCAGGAGGGATAGCGCC	no
osa-miR528	UGGAAGGGGCAUGCAGAGGAG	no

Table 2. Pre-miRNA sequence of potentially new members of conserved miRNAs in wheat^a.

Potentially novel miRNA	Pre-miRNA sequence of potentially novel miRNAs
PN-tae-miR166a	GCTTTTTTACTTTGAGGGGAATGTTGTCTGGCTCGAGGTGCTGAGATCGAGAGAACTTGAAATTCGATCTCTAGATTGATCTCGGACCAGGCTTCATTCCCCTCAAGTAAAGCT
PN-tae-miR168a	CGCCGCCTCGGGCTCGCTTGGTGCAGATCGGGACCCTCCGCCCGCCCCCGCCGGGCCGGATCCCGCCTTGCACCAAGTGAATCGGAGCCGGC

^aThe sequences of potentially novel miRNAs identified through microarray were mapped to reference sequences using SOAP (http://soap.genomics.org.cn) and selected genomes (wheat transcript assemblies from TIGR and our lab). Four miRNAs were mapped, and the candidate sequences could be folded into standard stem-loop structures.

Fig. 3 (Colour online) The stem-loop structures of new miRNAs. The sequences were mapped to reference sequences using SOAP (http://soap.genomics.org.cn) and selected genomes (wheat transcript assemblies from TIGR and our lab) and were folded into standard stem-loop structures using RNAfold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi). (A, PN-tae-miR166a; B, PN-tae-miR168a).

Fig. 4 Relative expression analysis of miRNAs by RT-qPCR. Seven mature miRNAs were confirmed and selected for the transcript accumulation analysis in wheat after challenge with CYR23 and CYR31. (A, tae-miR156; B, tae-miR159; C, tae-miR160; D, tae-miR164; E, tae-miR167; F, PN-tae-miR166a; G, PN-tae-miR168a). The data were normalized to the expression level of wheat translation elongation factor 1 alpha-subunit (EF). The vertical bars represent the standard deviations. The relative expression level of the miRNAs in the Pst-inoculated plants at each time point was calculated as the fold of the mock-inoculated plants at that time point using the comparative 2^−ΔΔCT method. The vertical bars represent the standard deviations. The experiments were repeated in triplicates of independent biological replicates using newly extracted RNA and synthesized cDNA samples.

Table 3. The information of the selected miRNAs and their targets in wheat and Arabidopsis thaliana^a.

miRNA	Target gene	Functional description	Reference
tae-miR156	SBP	transcription factors	Yao et al. (2007)
ath-miR156	SPL	transcription factors	Schwarz et al. (2008)
tae-miR159	MYB3	transcription factor	predicted
tae-miR159	GAMYB	transcription factor	Yao et al. (2007)
ath-miR159	More than 20 MYB	transcription factor	Rajagopalan et al. (2006)
PN-tae-miR166a	Class III HD-Zip protein	transcription factor	predicted
ath-miR166a	Class III HD-Zip protein	transcription factor	predicted
tae-miR164	NAC1	transcription factor	Gupta et al. (2012)
ath-miR164	NAC domain proteins	transcription factor	Rhoades et al. (2002)
tae-miR160	ARF	auxin response factor	Yao et al. (2007)
ath-miR160a	ARF10	auxin response factor	Liu et al. (2007)
tae-miR167	ARF8	auxin response factor	Yao et al. (2007)
ath-miR167	ARF6,ARF8	auxin response factor	Wu et al. (2006)
PN-tae-miR168a	Not found	unknown
ath-miR168a	SUVR4	histone-lysine N-methyltransferase	predicted

^aThe target genes of these known and novel conserved miRNAs were predicted using psRNATarget (http://plantgrn.noble.org/psRNATarget/) and compared with the results of Yao and the data for Arabidopsis thaliana.

Yao Y, Guo G, Ni Z, Sunkar R, Du J, Zhu JK, Sun Q. 2007. Cloning and characterization of microRNAs from wheat (Triticum aestivum L.). Genome Biol. 8:96.

 PubMed Web of Science ®Google Scholar

Schwarz S, Grande AV, Bujdoso N, Saedler H, Huijser P. 2008. The microRNA regulated SBP-box genes SPL9 and SPL15 control shoot maturation in Arabidopsis. Plant Mol Biol. 67:183–195.

 PubMed Web of Science ®Google Scholar

Rajagopalan R, Vaucheret H, Trejo J, Bartel DP. 2006. A diverse and evolutionarily fluid set of microRNAs in Arabidopsis thaliana. Gene Dev. 20:3407–3425.

 PubMed Web of Science ®Google Scholar

Gupta OP, Permar V, Koundal V, Singh UD, Praveen S. 2012. MicroRNA regulated defense responses in Triticum aestivum L. during Puccinia graminis f. sp. tritici infection. Mol Biol Rep. 39:817–824.

 PubMed Web of Science ®Google Scholar

Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP. 2002. Prediction of plant microRNA targets. Cell. 110:513–520.

 PubMed Web of Science ®Google Scholar

Liu P-P, Montgomery TA, Fahlgren N, Kasschau KD, Nonogaki H, Carrington JC. 2007. Repression of AUXIN RESPONSE FACTOR10 by microRNA160 is critical for seed germination and post-germination stages. Plant J. 52:133–146.

 PubMed Web of Science ®Google Scholar

Wu M-F, Tian Q, Reed JW. 2006. Arabidopsis microRNA167 controls patterns of ARF6 and ARF8 expression, and regulates both female and male reproduction. Development. 133:4211–4218.

 PubMed Web of Science ®Google Scholar