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McMaster, E. S.

Publications and source records attributed to McMaster, E. S..

2 recordsLinked to original sources

Genome assembly of Eucalyptus recurva provides insights into inbreeding and conservation priorities in Australia's rarest Eucalyptus

Eucalyptus recurva (Mongarlowe Mallee) is Critically Endangered, with only six known adult individuals persisting across two sites in the Southern Tablelands of New South Wales, Australia. Its extreme rarity, uniquely long lifespan, and limited reproductive output make it a priority for conservation genomics. Here we report the first genome assembly of E. recurva: a haplotype-resolved, gapless, telomere-to-telomere (T2T) assembly produced from Oxford Nanopore Technologies (ONT) long-read sequencing. Both haplotypes span 11 chromosomes (consistent with the conserved Eucalyptus karyotype of 2n = 22), with assembly sizes of 521.1 Mb (Hap 1) and 501.5 Mb (Hap 2), BUSCO completeness >99.6%, and quality values of >QV 62. Comparative analyses place E. recurva within section Maidenaria as sister to Eucalyptus viminalis and reveal high synteny between the two species. Inter-haplotype comparison identified 3.6 million SNPs and modest structural variation, suggesting that, despite extreme demographic bottlenecking, E. recurva retains meaningful genomic heterozygosity. We also characterise the chloroplast genome, which exhibits heteroplasmy, and report an apparently bipartite mitochondrial genome. This reference genome provides an essential resource for conservation management, population genetics, and the study of eucalypt genome evolution.

genomics↗

GHIST 2024: The 1st Genomic History Inference Strategies Tournament

Evaluating population genetic inference methods is challenging due to the complexity of evolutionary histories, potential model misspecification, and unconscious biases in self-assessment. The Genomic History Inference Strategies Tournament (GHIST) is a community-driven competition designed to evaluate methods for inferring evolutionary history from population genomic data. The inaugural GHIST competition ran from July to November 2024 and featured four demographic history inference challenges of varying complexity: a bottleneck model, a split with isolation model, a secondary contact model with demographic complexity, and an archaic admixture model. Data were provided as error-free VCF files, and participants submitted numerical parameter estimates that were scored by relative root mean squared error. Approximately 60 participants competed, using diverse approaches. Results revealed the current dominance of methods based on site frequency spectra, while highlighting the advantages of flexible model-building approaches for complex demographic histories. We discuss insights regarding the competition and outline the next iteration, which is ongoing with expanded challenge diversity. By providing standardized benchmarks and highlighting areas for improvement, GHIST represents a substantial step toward more reliable inference of evolutionary history from genomic data.

evolutionary biology↗