RNA silencing is a conserved mechanism in plants that targets viruses. Viral small RNAs (vsiRNAs) can be generated from viral double-stranded RNA replicative intermediates within the infected host, or from host RNA-dependent RNA polymerases activity on viral templates. The abundance and profile of vsiRNAs in viral infections have been reported previously. However, the involvement of vsiRNAs during infection of the Geminiviridae family member cotton leaf curl virus (CLCuD), which causes significant economic losses in cotton growing regions, remains largely uncharacterized. Cotton leaf curl Multan virus (CLCuMuV) associated with a betasatellite called Cotton leaf curl Multan betasatellite (CLCuMuB) is a major constraint to cotton production in South Asia and is now established in Southern China. In this study, we obtained the profiles of vsiRNAs from CLCuMV and CLCuMB in infected upland cotton (Gossypium hirsutum) plants by deep sequencing. Our data showed that vsiRNA that were derived almost equally from sense and antisense CLCuD DNA strands accumulated preferentially as 21- and 22-nucleotide (nt) small RNA population and had a cytosine bias at the 5'-terminus. Polarity distribution revealed that vsiRNAs were almost continuously present along the CLCuD genome and hotspots of sense and antisense strands were mainly distributed in the Rep proteins region of CLCuMuV and in the C1 protein of CLCuMuB. In addition, hundreds of host transcripts targeted by vsiRNAs were predicted, many of which encode transcription factors associated with biotic and abiotic stresses. Quantitative real-time polymerase chain reaction analysis of selected potential vsiRNA targets showed that some targets were significantly down-regulated in CLCuD-infected cotton plants. We also verified the potential function of vsiRNA targets that may be involved in CLCuD infection by virus-induced gene silencing (VIGS) and 5'-rapid amplification of cDNA end (5'-RACE). Here, we provide the first report on vsiRNAs responses to CLCuD infection in cotton.
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 20 August 2016.
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