Abstract

Plasmopara viticola is considered one of the most damaging grapevine pathogens, costing growers millions of dollars in losses. Despite the discovery of resistance to P. viticola (RPV) loci in grapevines to combat this pathogen, recent research shows that P. viticola can rapidly adapt virulence on some RPV loci, reducing their effectiveness. This thesis explored two strategies to understand how P. viticola adapted to two resistance loci of moderate strength, RPV3.1 and RPV10.3, by identification and characterization of P. viticola genomic regions showing a high selective sweep. Using sequenced natural infections from field samples, multiple tools and custom R scripts were applied to detect high selective sweep signals, objectively select regions of interest, and determine what genes and proteins are present. This pipeline of analysis revealed distinct sweep regions and patterns across the RPV resistant samples tested. While no selective sweep was detected for P. viticola collected from vines with only RPV3.1, P. viticola from RPV10.3 showed a strong selective sweep on scaffold 6, spanning 42 genes. These genes included a homologue of a known RxLR effector protein critical in host-pathogen interactions (PVIT_0003606) and a hypothetical protein predicted by SignalP to be secreted (PVIT_0003584). Similarly, vines containing both RPV3.1 and RPV10.3 showed strong selective sweeps on scaffolds 3, 11, and 6. The strong selective sweep on scaffold 3 spanned 21 genes, including two homologues of known avirulence proteins (PVIT_0002214 and PVIT_0002215). The sweep on scaffold 11 corresponded with another hypothetical protein predicted by SignalP to be secreted (PVIT_0006058). Comparative genomic analysis of scaffold 6 between samples revealed that RPV10.3 and RPV3.1+10.3 grown samples contain the same genes. This substantial overlap suggests a conserved selective sweep on scaffold 6 when RPV10.3 is present in the host vine. The findings suggest regions within P. viticola that are responsible for overcoming resistance and how these differ between RPVs as well as providing insight into possible future evolutionary responses of P. viticola.

Publication Date

10-8-2024

Document Type

Thesis

Student Type

Graduate

Degree Name

Bioinformatics (MS)

Department, Program, or Center

Thomas H. Gosnell School of Life Sciences

College

College of Science

Advisor

Michael V. Osier

Advisor/Committee Member

Eli J. Borrego

Advisor/Committee Member

Lance Cadle-Davidson

Campus

RIT – Main Campus

Download

Share

COinS