New computational methods and plant models for evolutionary genomics
Creators: name: Murray, Kevin
Publisher: name: The Australian National University
Year: 2019

description: This thesis is in the service of a greater understanding of the genetic basis of adaptive traits. Chapter 1 introduces background literature relevant to this thesis. Chapters 2, 3, and 4 develop novel methods and software for the analysis of genetic sequencing data. Chapter 5 details a large collaborative project to establish genetic resources in the model cereal Brachypodium, and perform a genome-wide association study for several agriculturally-relevant traits under two climate change scenarios. Chapter 6 investigates the spatial genetic patterns in two species of woodland eucalypt, and determines the landscape process that could be driving these patterns. Finally, Chapter 7 summarises these works, and proposes some areas of further study. In Chapters 2 and 3, I develop methods that enable analysis of Genotyping-by-sequencing analysis. Axe, a short read sequence demultiplexer, demultiplexes samples from multiplexed GBS sequencing datasets. I show Axe has high accuracy, and outperforms previously published software. Axe also tolerates complex indexing schemes such as the variable-length combinatorial indexes used in GBS data. Trimit and libqcpp (Chapter 3) implements several low-level sequence read quality assessment and control methods as a C++ library, and as a command line tool. Both these works have been published in peer-reviewed journals, and are used by numerous groups internationally. In Chapter 4, I develop kWIP, a de novo estimator of genetic distance. kWIP enables rapid estimation of genetic distances directly from sequence reads. We first show kWIP outperforms a competing method at low coverage using simulations that mimic a population resequencing experiment. We propose and demonstrate several use cases for kWIP, including population resequencing, initial assessment of sample identity, and estimating metagenomic similarity. kWIP was published in PLoS Computational Biology. In Chapter 5, I present the results of a large, collaborative project which surveys the global genetic diversity of the model cereal Brachypodium. We amass a collection of over 2000 accessions from the Brachypodium species complex. Using GBS and whole genome sequencing we identify around 800 accessions of the diploid Brachypodium distachyon, within which we find extensive population structure and clonal families. Through population restructuring we create a core collection of 74 accessions containing the majority of genetic diversity in the "A genome" sub-population. Using this core collection, we assay several phenotypes of agricultural interest including early vigour, harvest index and energy use efficiency under two climates, and dissect the genetic basis of these traits using a genome-wide association study (GWAS). This work has been accepted for publication at Genetics; I am co-first author with Pip Wilson and Jared Streich, having lead many genomic analyses. In Chapter 6, I perform a study of landscape genomic variation in two woodland eucalypt species. Using whole genome sequencing of around 200 individuals from around 20 localities of both E. albens and E. sideroxylon, I find incredible genetic diversity and low genome-wide inter-species differentiation.I find no support for strong discrete population structure, but strong support for isolation by (geographic) distance (IBD). Using generalised dissimilarity modelling, I further examine the pattern of IBD, and establish additional isolation by environment (IBE). E. albens shows moderately strong IBD, explaining 26% of deviance in genetic distance using geographic distance, and an additional 6% deviance explained by incorporating environmental predictors (IBE). E. sideroxylon shows much stronger IBD, with 78% of deviance explained by geography, and stronger IBE (12% additional deviance explained). This work will soon be submitted for publication.