Ashraf, M.A.; Murtaza, N.; Brown, J.K.; Yu, N. In Silico Apple Genome-Encoded MicroRNA Target Binding Sites Targeting Apple Chlorotic Leaf Spot Virus. Horticulturae2023, 9, 808.
Ashraf, M.A.; Murtaza, N.; Brown, J.K.; Yu, N. In Silico Apple Genome-Encoded MicroRNA Target Binding Sites Targeting Apple Chlorotic Leaf Spot Virus. Horticulturae 2023, 9, 808.
Ashraf, M.A.; Murtaza, N.; Brown, J.K.; Yu, N. In Silico Apple Genome-Encoded MicroRNA Target Binding Sites Targeting Apple Chlorotic Leaf Spot Virus. Horticulturae2023, 9, 808.
Ashraf, M.A.; Murtaza, N.; Brown, J.K.; Yu, N. In Silico Apple Genome-Encoded MicroRNA Target Binding Sites Targeting Apple Chlorotic Leaf Spot Virus. Horticulturae 2023, 9, 808.
Abstract
Apple chlorotic leaf spot virus (ACLSV) is a widespread, deleterious and the most damaging pathogen of fruit tree plants including domesticated apple (Malus domestica) ―a great threat to apple production worldwide. The positive-sense single-stranded RNA genome of ACLSV (7.5 Kbp) encodes three proteins: RNA polymerase (Rep), movement protein (MP) and coat protein (CP). RNA interference (RNAi)-mediated antiviral innate immunity is a key sequence-specific biological phenomenon in eukaryotes to control plant viruses. The aim of this study was to analyze apple (M.domestica) locus-derived microRNAs (mdm-miRNAs) with predicted potential for targeting the ACLSV +ssRNA-encoded mRNAs, using ‘four algorithms’ approach. The ultimate goal in this research is to mobilize the in silico endogenous predicted mdm-miRNAs to trigger RNAi catalytic pathway experimentally and generate apple tree varieties for evaluating potential antiviral resistance monitoring capability and capacity for ACLSV. Experimentally validated mature apple (M.domestica, 2n = 2X = 34) mdm-miRNAs (n = 322) were acquired from miRBase database and tested for alignment with the ACLSV genome. Of the 322 targeting mature locus-derived mdm-miRNAs investigated, nine apple mdm-miRNA homologs (mdm-miR395k, mdm-miR5225c and mdm-miR7121 (a, b, c, d, e, f, g, h) were predicted by all ‘four algorithms’. Only fifty eight mdm-miRNAs were predicted consensus binding sites by union of consensus between two algorithms. The miRanda, RNA22, TAPIR algorithms predicted binding of mdm-miR395k at unique nucleotide position 4691, as the most effectively interacting mdm-miRNAs in targeting the ORF1 sequence. In order to validate target prediction accuracy, whether the apple mdm-miRNAs might bind predicted ACLSV mRNA target(s), we created an integrated Circos plot. Genome-wide in-silico-predicted miRNA-mediated target gene regulatory network validated interactions that warrant in vivo analysis. The current work provides valuable evidence and biological material for generating ACLSV-resistant apple varieties.
Keywords
trichovirus; in silico tools; apple chlorotic leaf spot virus; miRNA; RNA interference
Subject
Biology and Life Sciences, Biology and Biotechnology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.