Co-chairs, Graduate Committee: Brendan Mumey and Jennifer A. LachowiecReynolds, Gillian Lucy2024-07-192024-07-192022https://scholarworks.montana.edu/handle/1/18646Genome comparison for large and complex polyploid crop genomes is a highly complex venture, yet it is critical. Given a rising demand for food coupled with yield-impacting resource limitations and rapidly changing global climates it has never been more important to characterise the underlying genetic variation which underpins traits of agronomic interest. In this work, the problem of polyploidy genome comparison is explored at three levels. The first chapter characterizes the sequence relationships that exist between, and within, polyploidy genomes. This is achieved by hijacking a metagenomic strategy for rapid, and efficient, genome sequence classification. The second chapter then utilizes the identified subgenome- specific k-mer profiles for recruitment of assembled contigs and scaffolds previously only recruitable via more resource intensive optical mapping strategies. This makes a greater proportion of the assembled data usable for downstream variant analysis. The third chapter then zooms into the problem of how to identify variants from large -scale sequencing data while minimizing bias and computational costs. A critical assessment of modern variant calling for crop genomes is performed and an algorithm to further extend a new, resource efficient, approach for large scale comparative genomics is presented and critically evaluated. In all, the work presented herein takes a top-down journey from genome- and subgenome- level comparative genomics all the way to identifying base-pair resolution strategies that are capable of revealing the underlying sequences responsible for keeping the world fed.enCropsPolyploidyGenomicsBioinformaticsAlgorithmsDissertationCopyright 2022 by Gillian Lucy Reynolds