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In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus

文献类型： 外文期刊

作者： Ashraf, Muhammad Aleem 1 ; Feng, Xiaoyan 1 ; Hu, Xiaowen 3 ; Ashraf, Fakiha 1 ; Shen, Linbo 1 ; Iqbal, Muhammad Shahzad 4 ; Zhang, Shuzhen 1 ;

作者机构： 1.Chinese Acad Trop Agr Sci, Inst Trop Biosci & Biotechnol, Sugarcane Res Ctr, Haikou, Hainan, Peoples R China

2.Khwaja Fareed Univ Engn & Informat Technol, Dept Biosci & Technol, Rahim Yar Khan, Pakistan

3.Chinese Acad Trop Agr Sci, Zhanjiang Expt Stn, Zhanjiang, Peoples R China

4.Univ Cent Punjab, Dept Biotechnol, Lahore, Pakistan

期刊名称：PLOS ONE （ 影响因子：3.752； 五年影响因子：4.069 ）

ISSN： 1932-6203

年卷期： 2022 年 17 卷 1 期

页码：

收录情况： SCI

摘要： Sugarcane bacilliform virus (SCBV) is considered one of the most economically damaging pathogens for sugarcane production worldwide. Three open reading frames (ORFs) are characterized in the circular, ds-DNA genome of the SCBV; these encode for a hypothetical protein (ORF1), a DNA binding protein (ORF2), and a polyprotein (ORF3). A comprehensive evaluation of sugarcane (Saccharum officinarum L.) mi RNAs for the silencing of the SCBV genome using in silico algorithms were carried out in the present study using mature sugarcane miRNAs. miRNAs of sugarcane are retrieved from the miRBase database and assessed in terms of hybridization with the SCBV genome. A total of 14 potential candidate miRNAs from sugarcane were screened out by all used algorithms used for the silencing of SCBV. The consensus of three algorithms predicted the hybridization site of sof-miR159e at common locus 5534. miRNA-mRNA interactions were estimated by computing the free-energy of the miRNA-mRNA duplex using the RNAcofold algorithm. A regulatory network of predicted candidate miRNAs of sugarcane with SCBV-ORFs, generated using Circos-is used to identify novel targets. The predicted data provide useful information for the development of SCBV-resistant sugarcane plants.

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