|JENSEN, PHILIP - Pennsylvania State University
|HALBRENDT, NOEMI - Pennsylvania State University
|MAKALOWSKA, IZABELA - Adam Mickiewicz University
|ALTMAN, NAOMI - Pennsylvania State University
|PRAUL, CRAIG - Pennsylvania State University
|MAXIMOVA, SIELA - Pennsylvania State University
|CRASSWELLER, ROBERT - Pennsylvania State University
|TRAVIS, JAMES - Pennsylvania State University
|MCNELLIS, TIMOTHY - Pennsylvania State University
Submitted to: BMC Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/9/2012
Publication Date: 1/9/2012
Citation: Jensen, P.J., Halbrendt, N., Fazio, G., Makalowska, I., Altman, N., Praul, C., Maximova, S.N., Crassweller, R.M., Travis, J., Mcnellis, T. 2012. Rootstock-regulated gene expression patterns associated with fire blight resistance in apple. Biomed Central (BMC) Genomics. 13:9.
Interpretive Summary: Fire blight is a devastating disease that decimates apple orchards throughout the U.S. All commercial apple trees are made up by a variety scion (like Gala) grafted onto a rootstock. There are several rootstocks available to the apple industry. These rootstocks have been shown to affect productivity and other properties of the scion. This study was meant to discern what effect different rootstocks had on the magnitude of susceptibility of the apple variety Gala and connect that information to the gene transcription changes that the rootstock causes in that variety. This study quantified that the severity of fire blight on Gala trees differs depending on what rootstock they are grafted on and found significant differences among rootstocks. The same is true for several genes that are expressed differentially in Gala trees depending on what rootstock they are grafted on. The expression pattern of some of these genes modified by the rootstocks might be associated with fire blight severity.
Technical Abstract: Background: Desirable apple varieties are clonally propagated by grafting vegetative scions onto rootstocks. Rootstocks influence many phenotypic traits of the scion, including resistance to pathogens such as Erwinia amylovora, which causes fire blight, the most serious bacterial disease of apple. The purpose of the present study was to quantify rootstock-mediated differences in scion fire blight susceptibility and to identify transcripts in the scion whose expression levels correlated with this response. Results: Rootstock influence on scion fire blight resistance was quantified by inoculating three-year old, orchard-grown apple trees, consisting of ‘Gala’ scions grafted to a range of rootstocks, with E. amylovora. Disease severity was measured by the extent of shoot necrosis over time. ‘Gala’ scions grafted to G.30 or MM.111 rootstocks showed the lowest rates of necrosis, while ‘Gala’ on M.27 and B.9 showed the highest rates of necrosis. ‘Gala’ scions on M.7, S.4 or M.9 had intermediate necrosis rates. Using an apple DNA microarray, global gene expression patterns were compared in healthy, uninoculated, greenhouse-grown ‘Gala’ scions on the same series of rootstocks. We identified 686 transcripts whose expression levels correlated with the degree of fire blight susceptibility of the scion/rootstock combinations. Transcripts known to be differentially expressed during E. amylovora infection were disproportionately represented among these transcripts. A second-generation apple microarray was developed that allowed us to test these correlations in an orchard-grown population of trees segregating for fire blight resistance. Of the 686 transcripts, 93 had expression levels that correlated with fire blight resistance in the breeding population. Conclusions: Rootstocks had significant effects on the fire blight susceptibility of ‘Gala’ scions, and rootstock-regulated gene expression patterns could be correlated with differences in susceptibility. Genes and processes implicated in rootstock-regulated fire blight susceptibility include sorbitol dehydrogenase, phenylpropanoid metabolism, protein processing in the endoplasmic reticulum, and endocytosis, among others. This study illustrates the utility of our rootstock-regulated gene expression data sets for candidate trait-associated gene data mining.