Virome Network Analysis: A Network Framework for Studying Landscape Agroecology of Plant Viromes for Disease Management

• Main Author: Alcala Briseno, Ricardo Ivan
• Format: Dissertation
• Language: English
• Published: ProQuest Dissertations & Theses 01.01.2021
• Subjects: Microbiology; Plant Pathology; Virology
• ISBN: 9798379732424

In the last decade, the amount of genomic information generated by high-throughput sequencing helped the discovery rate of viruses to skyrocket, with viruses either causing disease or merely being present in the host, revealing a vast number of virus–virus interactions in ecosystems. Despite increasing reports of virus co-infection in plants, traditional methodologies do not allow analysis of virus interactions in the ecological landscape. Phylogenetic analyses have often been implemented in virome studies, identifying the relationship between viruses. Other virome analyses have consisted of counting the number of reads or simple summary statistics. Recently, other ecological methods have been applied to complex viromes, such as classical ecological and spatial agrogenomics approaches. In this thesis I elaborated on a network analysis framework for the study of complex viromes using bipartite networks. Bipartite networks describe interactions between two types of nodes, wherein this case one type represents hosts and the other type represents viruses. Links represent the presence/absence of interaction; interactions cannot occur between nodes of the same type. These network characterizations allowed us to evaluate three systems. An analysis of the papaya orchard virome in Mexico described a highly nested structure (non-random), indicating that the host-virus associations shape the virome community. The analysis of the papaya orchard virome revealed about 60 plant virus species, 30 new plant virus species, including a novel papaya rhabdovirus and a novel papaya comovirus. Only 3 species were identified in both regions: PRSV, PapMV, and EuMV. The analysis of the sweetpotato virome in Sub-Saharan Africa described the spatial dynamics of virome communities and sweetpotato cropland connectivity of Sub-Saharan Africa, identifying seven sweetpotato regions, sharing a core virome. The Goodall dissimilarity index allowed us to make comparisons based on rare species in the virome communities, indicating that geographic proximity was not the only factor playing a role in the community structure of the sweetpotato virome. In an analysis of the Peruvian potato virome, we explored variation in the virome communities along the altitudinal gradient of potato production in the Andes. The analysis showed that the coast was more similar to the intermediate region compared to the Andean mountains, but the Andean mountains and the intermediate region do not have rare species among them, indicating one community above 2000 masl.As part of these analyses, I developed a framework for analyzing virome sequences, using contig and reference sequence cluster analyses. The identity networks represented nodes as contigs and links as the maximum identity between both sequences. The contig sequences were classified with an algorithm using demarcation criteria specific to virus species. Each virome cluster was decomposed and arranged as a meta–index, containing the contig sequence data of the virome species cluster (VSC). The VSCs were quantified using the reads of each virome for its quantification using read per kilobase million (RPKMs) normalization. The VSC by accession is integrated as an incidence matrix, which is analyzed as a bipartite network. The study of viromes using bipartite networks and community analysis contributes to understanding virome composition and dynamics at small and large scales as well along the altitudinal gradients. The datasets analyzed in this dissertation illustrate the applications of virome network analysis as an emergent discipline for the study of virome communities and its implication in the agroecological landscape