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Small RNA sequencing reveals a role for sugarcane miRNAs and their targets in response to Sporisorium scitamineum infection

Overview of attention for article published in BMC Genomics, April 2017
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Title
Small RNA sequencing reveals a role for sugarcane miRNAs and their targets in response to Sporisorium scitamineum infection
Published in
BMC Genomics, April 2017
DOI 10.1186/s12864-017-3716-4
Pubmed ID
Authors

Yachun Su, Yuye Zhang, Ning Huang, Feng Liu, Weihua Su, Liping Xu, Waqar Ahmad, Qibin Wu, Jinlong Guo, Youxiong Que

Abstract

Sugarcane smut caused by Sporisorium scitamineum leads to a significant reduction in cane yield and sucrose content. MicroRNAs (miRNAs) play an important role in regulating plant responses to biotic stress. The present study was the first to use two sugarcane genotypes, YA05-179 (smut-resistant) and ROC22 (smut-susceptible), to identify differentially expressed miRNAs in sugarcane challenged with S. scitamineum by using high-throughput sequencing. The predicted target gene number corresponding to known differentially expressed miRNAs in YA05-179 was less than that in ROC22, however most of them were in common. Expression of differential miRNAs under S. scitamineum challenge was mostly downregulated, with similar trends in the two varieties. Gene ontology (GO) analysis showed that the target gene classification of known miRNAs was similar to that of the newly identified miRNAs. These were mainly associated with cellular processes and metabolic processes in the biological process category, as well as combination and catalytic activity in the molecular function category. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that these predicted target genes involved in a series of physiological and biochemical pathways or disease resistance-related physiological metabolism and signal transduction pathways, suggesting that the molecular interaction mechanism between sugarcane and S. scitamineum was a complex network system. These findings also showed certain predicted target genes of miR5671, miR5054, miR5783, miR5221, and miR6478 play roles in the mitogen-activated protein kinase (MAPK) signaling pathway, plant hormone signal transduction, and plant-pathogen interaction. Quantitative real-time PCR (qRT-PCR) analysis showed that majority of the known miRNAs and its predicted target genes followed a negatively regulated mode. Seven out of eight predicted target genes showed identical expression after 12 h treatment and reached the highest degree of matching at 48 h, indicating that the regulatory role of miRNAs on the target genes in sugarcane was maximized at 48 h after S. scitamineum challenge. Taken together, our findings serve as evidence for the association of miRNA expression with the molecular mechanism underlying the pathogenesis of sugarcane smut, particularly on the significance of miRNA levels in relation to the cultivation of smut-resistant sugarcane varieties.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Researcher 7 20%
Student > Master 4 11%
Professor 4 11%
Student > Doctoral Student 2 6%
Other 5 14%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 51%
Biochemistry, Genetics and Molecular Biology 7 20%
Psychology 1 3%
Physics and Astronomy 1 3%
Unknown 8 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2017.
All research outputs
#18,542,806
of 22,965,074 outputs
Outputs from BMC Genomics
#8,217
of 10,686 outputs
Outputs of similar age
#235,187
of 309,738 outputs
Outputs of similar age from BMC Genomics
#179
of 227 outputs
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