In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus
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 (O...
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Published in | PloS one Vol. 17; no. 1; p. e0261807 |
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Main Authors | , , , , , , |
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Abstract | 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.) miRNAs 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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AbstractList | 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.) miRNAs 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. 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.) miRNAs 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. |
Audience | Academic |
Author | Zhang, Shuzhen Shen, Linbo Ashraf, Muhammad Aleem Hu, Xiaowen Ashraf, Fakiha Feng, Xiaoyan Iqbal, Muhammad Shahzad |
AuthorAffiliation | ICAR-Central Plantation Crops Research Institute, INDIA 1 Institute of Tropical Bioscience and Biotechnology, Sugarcane Research Centre of Chinese Academy of Tropical Agricultural Sciences, Haikou, China 2 Department of Bioscience and Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan 4 Department of Biotechnology, University of Central Punjab, Lahore, Pakistan 3 Zhanjiang Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China |
AuthorAffiliation_xml | – name: 1 Institute of Tropical Bioscience and Biotechnology, Sugarcane Research Centre of Chinese Academy of Tropical Agricultural Sciences, Haikou, China – name: ICAR-Central Plantation Crops Research Institute, INDIA – name: 2 Department of Bioscience and Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan – name: 3 Zhanjiang Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China – name: 4 Department of Biotechnology, University of Central Punjab, Lahore, Pakistan |
Author_xml | – sequence: 1 givenname: Muhammad Aleem orcidid: 0000-0001-5503-8223 surname: Ashraf fullname: Ashraf, Muhammad Aleem organization: Department of Bioscience and Technology, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan – sequence: 2 givenname: Xiaoyan surname: Feng fullname: Feng, Xiaoyan organization: Institute of Tropical Bioscience and Biotechnology, Sugarcane Research Centre of Chinese Academy of Tropical Agricultural Sciences, Haikou, China – sequence: 3 givenname: Xiaowen surname: Hu fullname: Hu, Xiaowen organization: Zhanjiang Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China – sequence: 4 givenname: Fakiha surname: Ashraf fullname: Ashraf, Fakiha organization: Institute of Tropical Bioscience and Biotechnology, Sugarcane Research Centre of Chinese Academy of Tropical Agricultural Sciences, Haikou, China – sequence: 5 givenname: Linbo surname: Shen fullname: Shen, Linbo organization: Institute of Tropical Bioscience and Biotechnology, Sugarcane Research Centre of Chinese Academy of Tropical Agricultural Sciences, Haikou, China – sequence: 6 givenname: Muhammad Shahzad orcidid: 0000-0001-5145-3075 surname: Iqbal fullname: Iqbal, Muhammad Shahzad organization: Department of Biotechnology, University of Central Punjab, Lahore, Pakistan – sequence: 7 givenname: Shuzhen surname: Zhang fullname: Zhang, Shuzhen organization: Institute of Tropical Bioscience and Biotechnology, Sugarcane Research Centre of Chinese Academy of Tropical Agricultural Sciences, Haikou, China |
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Snippet | Sugarcane bacilliform virus (SCBV) is considered one of the most economically damaging pathogens for sugarcane production worldwide. Three open reading frames... |
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SubjectTerms | Algorithms Badnavirus - genetics Badnavirus - metabolism Biology and life sciences Biotechnology Computer Simulation Deoxyribonucleic acid Diseases and pests DNA Engineering and Technology Food processing industry Free energy Gene expression Genetic aspects Genetic engineering Genomes Hybridization Identification and classification Infections MicroRNA MicroRNAs MicroRNAs - genetics MicroRNAs - metabolism miRNA mRNA Open Reading Frames Physical Sciences Proteins Research and Analysis Methods RNA, Plant - genetics Saccharum - genetics Saccharum - metabolism Saccharum - virology Saccharum officinarum Sugarcane Target recognition Viruses |
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Title | In silico identification of sugarcane (Saccharum officinarum L.) genome encoded microRNAs targeting sugarcane bacilliform virus |
URI | https://www.ncbi.nlm.nih.gov/pubmed/35051194 https://www.proquest.com/docview/2621662599/abstract/ https://search.proquest.com/docview/2622276199 https://pubmed.ncbi.nlm.nih.gov/PMC8775236 https://doaj.org/article/f275ef920a9e4e0bba35e15c1ccbe30c http://dx.doi.org/10.1371/journal.pone.0261807 |
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