Identification of miRNAs and their targets using high-throughput sequencing and degradome analysis in cytoplasmic male-sterile and its maintainer fertile lines ... View Full Text


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Article Info

DATE

2013-01-16

AUTHORS

Jinghua Yang, Xunyan Liu, Baochen Xu, Na Zhao, Xiaodong Yang, Mingfang Zhang

ABSTRACT

BACKGROUND: Regulatory network of cytoplasmic male sterility (CMS) occurrence is still largely unknown in plants, although numerous researches have been attempted to isolate genes involved in CMS. Here, we employed high-throughput sequencing and degradome analysis to identify microRNAs and their targets using high-throughput sequencing in CMS and its maintainer fertile (MF) lines of Brassica juncea. RESULTS: We identified 197 known and 78 new candidate microRNAs during reproductive development of B. juncea. A total of 47 differentially expressed microRNAs between CMS and its MF lines were discovered, according to their sequencing reads number. Different expression levels of selected microRNAs were confirmed by using real-time quantitative PCR between CMS and MF lines. Furthermore, we observed that the transcriptional patterns of these microRNAs could be mimicked by artificially inhibiting mitochondrial F1F0-ATPase activity and its function in MF line by using treatment with oligomycin. Targeted genes of the microRNAs were identified by high-throughput sequencing and degradome approaches, including auxin response factor, NAC (No Apical Meristem) domain transcription factor, GRAS family transcription factor, MYB transcription factor, squamosa promoter binding protein, AP2-type transcription factor, homeobox/homeobox-leucine zipper family and TCP family transcription factors, which were observed to be differentially expressed between CMS and MF. CONCLUSION: Taken together, from these findings we suggested microRNA might participate in the regulatory network of CMS by tuning fork in gene expressions in CMS B. juncea. The differential expression of miRNAs observed between CMS and MF lines suggested that biogenesis of miRNAs could be influenced in the CMS. More... »

PAGES

9-9

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    33 schema:description BACKGROUND: Regulatory network of cytoplasmic male sterility (CMS) occurrence is still largely unknown in plants, although numerous researches have been attempted to isolate genes involved in CMS. Here, we employed high-throughput sequencing and degradome analysis to identify microRNAs and their targets using high-throughput sequencing in CMS and its maintainer fertile (MF) lines of Brassica juncea. RESULTS: We identified 197 known and 78 new candidate microRNAs during reproductive development of B. juncea. A total of 47 differentially expressed microRNAs between CMS and its MF lines were discovered, according to their sequencing reads number. Different expression levels of selected microRNAs were confirmed by using real-time quantitative PCR between CMS and MF lines. Furthermore, we observed that the transcriptional patterns of these microRNAs could be mimicked by artificially inhibiting mitochondrial F1F0-ATPase activity and its function in MF line by using treatment with oligomycin. Targeted genes of the microRNAs were identified by high-throughput sequencing and degradome approaches, including auxin response factor, NAC (No Apical Meristem) domain transcription factor, GRAS family transcription factor, MYB transcription factor, squamosa promoter binding protein, AP2-type transcription factor, homeobox/homeobox-leucine zipper family and TCP family transcription factors, which were observed to be differentially expressed between CMS and MF. CONCLUSION: Taken together, from these findings we suggested microRNA might participate in the regulatory network of CMS by tuning fork in gene expressions in CMS B. juncea. The differential expression of miRNAs observed between CMS and MF lines suggested that biogenesis of miRNAs could be influenced in the CMS.
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    52 SQUAMOSA PROMOTER BINDING PROTEIN
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    57 auxin response factors
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    59 biogenesis
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    61 candidate microRNAs
    62 cytoplasmic male sterility (CMS) occurrence
    63 degradome analysis
    64 degradome approach
    65 development
    66 different expression levels
    67 differential expression
    68 expression
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    89 miRNAs
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