Viral expression vectors differentially impact gain-of-function analyses in model and non-model plants
Year: 2025
Type: article
Abstract: Cotton ( Gossypium hirsutum ) is the world’s most important fiber crop. However, cotton’s recalcitrance to standard genetic technologies and long life cycle challenge functional analysis and limit mechanisms for genetic improvement. Plant viruses are powerful tools for genetic analyses, and their applications provided new insights into cotton biology. Virus-induced gene silencing with the cloned Tobacco rattle virus (TRV) supports transient loss-of-function analyses while the geminivirus Cotton leaf crumple virus (CLCrV) is used for gain and loss of function in cotton. Both viruses have limitations and finding ways to combine the attributes of each is highly desired. TRV gain-of-function vectors were constructed and rigorously tested in Nicotiana benthamiana and cotton. Systemic delivery of transgenes, including signals impacting meristem fate, from the TRV gain-of-function virus was compared with CLCrV in cotton. We demonstrate that although gene delivery was strong in N. benthamiana , TRV gain-of-function vectors were less stable in cotton and did not advance systemic transgene expression. In contrast, gain of function from CLCrV was consistently demonstrated in systemic cotton tissues. These findings are valuable in considering applications for transient expression and the translation of tools from model to non-model plants. • We compared DNA and RNA viral tools for gene delivery in model and non-model plants. Modified TRV vectors that robustly delivered a transgene to distal tissues in Nicotiana benthamiana were not effective in cotton, but CLCrV consistently advanced gain-of-function analyses in cotton.
Source: Current Plant Biology
Authors: Róisín C. McGarry, Brian G. Ayre
Institution: University of North Texas
Language: English
Topic: Plant Virus Research Studies
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,440
Awards: G5035637902, G6118191953
OpenAlex ID: W4416525126
