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Functional analysis of a novel βV1 gene identified in a geminivirus betasatellite

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Abstract

Betasatellites (DNA β) are circular ssDNA molecules that are associated with monopartite geminiviruses and exert a positive effect on the viral infection. Betasatellites encode one protein, named βC1, on the complementary strand; βC1 functions as a pathogenicity factor and RNA silencing suppressor. In this report, we describe the identification of another betasatellite-encoded protein, βVl, which also contributes to symptom development. The βVl open reading frame can be found on the viral strand of approximately 40% of reported betasatellite sequences, and is conserved in position and sequence. The presence of the βVl transcript was observed in plants infected with Tomato yellow leaf curl China virus (TYTCCNV) along with its associated betasatellite Tomato yellow leaf curl China betasatellite (TYTCCNB). Mutant viruses unable to produce βVl showed reduced virulence and decreased viral load. Ectopic expression of the TYTCCNB-PV1 gene in Nicotiana benthamiana plants from a PVX-based vector resulted in leaf mosaic and chlorosis. We further demonstrated that the βVl protein could elicit hypersensitive response (HR)-type cell death in N. benthamiana leaves. Our results uncover a novel betasatellite-encoded protein that contributes to the virus infection, and this discover gives us a more complete view of the plant-geminivirus interaction landscape.

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Acknowledgements

We thank Dr. Fangfang Li (Institute of Plant Protection, Chinese Academy of Agricultural Sciences) and Dr. Rosa Lozano-Duran (Shanghai Center for Plant Stress Biology, Chinese Academy of Sciences) for their critical reading of the manuscript and helpful comments. This work was supported by grants from the National Natural Science Foundation of China to Y.Q. W. (31972235) and to X.P.Z. (31720103914).

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Correspondence to Yaqin Wang or Xueping Zhou.

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Hu, T., Song, Y., Wang, Y. et al. Functional analysis of a novel βV1 gene identified in a geminivirus betasatellite. Sci. China Life Sci. 63, 688–696 (2020). https://doi.org/10.1007/s11427-020-1654-x

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