Sugarcane mosaic virus genus Potyvirus (SCMV) is one of the most important viral pathogens affecting sugarcane worldwide. This thesis describes the complete nucleotide sequence and genome organisation of an Australian isolate of SCMV strain A; examines the taxonomic relationship of SCMV-A to other members of the family Potyrviridae; and describes the progress towards the construction of a full length in vivo clone of SCMV-A.
The SCMV-A viral genome is 9573 nucleotides in length, is polyadenylated at the 3' terminus and contains an open reading frame encoding 3065 amino acids, flanked by 5' and 3' untranslated regions of 147 and 230 nucleotides, respectively. The deduced polyprotein has conserved potyvirus specific motifs which are consistent with autocatalytic cleavage to result in the ten mature proteins. Phylogenetic analysis of SCMV-A genome and amino acid sequence indicate that the virus is closely related to other members in the genus Potyvirus, particularly maize dwarf mosaic virus and Johnsongrass mosaic virus which infect other tropical grasses. The sequence of the SCMV-A genome has been deposited into the EMBL database with accession number AJ278405.
The production of a full-length infectious cDNA clone of SCMV-A, which would have the capacity to generate full-length viral RNA within the plant cell, was partially achieved. A long-distance, megaprimer method of PCR was used to link viral cDNA to a plant promoter sequence, enhanced CaMV 35S, and a terminator, Nos. The components of this infectious clone have been developed and with further optimisation, a full-length cDNA clone could be produced. The complete genome sequence information along with the infectious cDNA clone will be available for further investigation of viral host range and pathogenicity; to analyse the function of individual mature viral proteins in replication, long distance and cell-to-cell movement; and to help explain the basis of transgenic resistance using mutation/knock-out studies of the full-length viral clone.
SCMV is a pathogen of major economic importance in sugarcane growing regions worldwide, causing financial impact due to crop yield losses. The resulting in costs in both breeding for disease resistance and discarding agronomically elite sugarcane cultivars from the breeding program due to disease susceptibility also impact financially on the sugar industry. A genetic engineering approach has been used to develop SCMV resistant sugarcane as a means of 'rescuing' these agronomically elite sugarcane cultivars.
Prior to this project, elite sugarcane variety, Q155, was transformed by scientists at the Bureau of Sugar Experiment Stations using sugarcane expression vector containing a translatable version of the coat protein coding region from SCMV-A. The transgenic sugarcane plants were tested previously for resistance to SCMV in a number of glasshouse and field trials and a variety of resistance phenotypes were observed, ranging from immune to tolerant to susceptible. This thesis describes the molecular analysis of the transgenic sugarcane plants which will assist in elucidating the molecular mechanism of pathogen derived resistance in sugarcane.
Ten genetically independent sugarcane lines were analysed as part of this investigation. The phenotypic data gathered from glasshouse inoculation trials revealed variation in the level of resistance within individual sugarcane lines. Further analysis of transgene expression in the mature transgenic sugarcane plants indicate an RNA-based resistance mechanism as there is no detectable transprotein produced in the transgenic sugarcane plants. However, there is transgene mRNA present in a range of abundance but the level of transgene mRNA does not correlate to the level of resistance observed.
The precise mechanism by which transgene-mediated resistance acts in SCMV resistant sugarcane remains unknown. However the selection of resistant transgenic lines cannot be predicted by the molecular profile of the plants RNA or DNA, so the plants must undergo phenotype verification for pathogen resistance and yield data. As our understanding of the complex molecular network increases, our ability to manipulate and predict the sugarcane phenotype from the molecular phenotype should increase.