Biology subjects

Korhonen, P. K.

Publications and source records attributed to Korhonen, P. K..

4 recordsLinked to original sources

bioRxiv2022

The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range

Genomic data provide valuable insights into pest management issues such as resistance evolution, historical patterns of pest invasions and ongoing population dynamics. We assembled the first reference genome for the redlegged earth mite, Halotydeus destructor (Tucker, 1925), to investigate adaptation to pesticide pressures and demography in its invasive Australian range using whole-genome pool-seq data from regionally distributed populations. Our reference genome comprises 132 autosomal contigs, with a total length of 48.90 Mb. We observed a large complex of ace genes, which has presumably evolved from a long history of organophosphate selection in H. destructor and may contribute toward organophosphate resistance through copy number variation, target-site mutations, and structural variants. In the putative ancestral H. destructor ace gene, we identified three target-site mutations (G119S, A201S, and F331Y) segregating in organophosphate resistant populations. Additionally, we identified two new para sodium channel gene mutations (L925I and F1020Y) that may contribute to pyrethroid resistance. Regional structuring observed in population genomic analyses indicates that gene flow in H. destructor does not homogenise populations across large geographic distances. However, our demographic analyses were equivocal on the magnitude of gene flow; the short invasion history of H. destructor makes it difficult to distinguish scenarios of complete isolation vs. ongoing migration. Nonetheless, we identified clear signatures of reduced genetic diversity and smaller inferred effective population sizes in eastern vs. western populations, which is consistent with the stepping-stone invasion pathway of this pest in Australia. These new insights will inform development of diagnostic genetic markers of resistance, further investigation into the multifaceted organophosphate resistance mechanism, and predictive modelling of resistance evolution and spread.

genomics↗

bioRxiv2019

Comparative genome analysis indicates rapid evolution of pathogenicity genes in Colletotrichum tanaceti

Colletotrichum tanaceti is an emerging foliar fungal pathogen of pyrethrum (Tanacetum cinerariifolium), posing a threat to the global pyrethrum industry. Despite being reported consistently from field surveys in Australia, the molecular basis of pathogenicity of C. tanaceti on pyrethrum is unknown. Herein, the genome of C. tanaceti (isolate BRIP57314) was assembled de novo and annotated using transcriptomic evidence. The inferred pathogenicity gene suite of C. tanaceti comprised a large array of genes encoding secreted effectors, proteases, CAZymes and secondary metabolites. Comparative analysis of its CAZyme pathogenicity profiles with those of closely related species suggested that C. tanaceti had additional hosts to pyrethrum. The genome of C. tanaceti had a high repeat content and repetitive elements were located significantly closer to genes inferred to influence pathogenicity than other genes. These repeats are likely to have accelerated mutational and transposition rates in the genome, resulting in a rapid evolution of certain CAZyme families in this species. The C. tanaceti genome consisted of a gene-sparse, A-T rich region facilitating a "two-speed" genome. Pathogenicity genes within this region were likely to have a higher evolutionary rate than the core genome. This "two-speed" genome phenomenon in certain Colletotrichum spp. was hypothesized to have caused the clustering of species based on the pathogenicity genes, to deviate from taxonomy. With the large repertoire of pathogenicity factors that can potentially evolve rapidly in response to control measures, C. tanaceti may pose a high-risk to global pyrethrum production. Knowledge of the pathogenicity genes will facilitate future research in disease management of C. tanaceti and other Colletotrichum spp..

genomics↗

bioRxiv2018

The Genomic Basis of Arthropod Diversity

BackgroundArthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods.\n\nResultsUsing 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality and chemoperception.\n\nConclusionsThese analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.

genomics↗

bioRxiv2017

Best Practice Data Life Cycle Approaches for the Life Sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a life cycle view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain.\n\nHere we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on omics datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

bioinformatics↗