Biology subjects

Dearden, P.

Publications and source records attributed to Dearden, P..

9 recordsLinked to original sources

bioRxiv2026

OrthoGLMM: Phylogenetic Association Testing for Gene Content and Trait Evolution

1MotivationComparative genome projects can now assemble and annotate hundreds of species, creating an opportunity to test whether species-level traits are associated with repeated changes in gene content. These tests must account for shared ancestry, sparse orthogroups, rare trait origins, and thousands of simultaneous associations. ResultsWe present OrthoGLMM, a phylogenetically informed framework for the association of traits and orthogroup presence/absence or copy number across species. OrthoGLMM combines deterministic GLMM scans with solver-rerun empirical calibration and calibrated FDR estimation. In three benchmark datasets, OrthoGLMM recovered expected signals for bacterial diazotrophy, plant nodulation, and marine mammals. Availability and ImplementationSource code, documentation, example data, and reproducibility scripts will be available at http://github.com/jguhlin/OrthoGLMM. Contactjoseph.guhlin@gmail.com

bioinformatics↗

bioRxiv2025

D-BLUP: a differentiable genomic BLUP model with learnable variance and marker weights

1.Genomic best linear unbiased prediction (GBLUP) is widely used for genomic selection in livestock and crop breeding. There is growing interest in connecting machine learning with genomic breeding value prediction. Although the BLUP formula is itself mathematically differentiable, existing implementations do not expose a differentiable computational graph and cannot be trained end-to-end. Here, we present [D]-BLUP, a differentiable implementation of the genomic mixed model in JAX that makes the BLUP solve part of the training process rather than an external step. The variance ratio {lambda} and optional block-level kernel weights are treated as trainable parameters, allowing these components to be learned directly from prediction error while preserving the BLUP structure used in animal and plant breeding. This means BLUP can now fit naturally within gradient-based models common in machine learning without losing its interpretability. The method solves the familiar system (Gw + {lambda}I) u = y* with either an unweighted VanRaden genomic relationship matrix G or a block-weighted variant Gw, via automatic differentiation, allowing simultaneous training. On a public dataset, [D]-BLUP with a fixed VanRaden kernel reproduces rrBLUP estimated breeding values and predictive performance, while learning {lambda}, and optionally SNP block weights, from a mean squared error objective. [D]-BLUP preserves the structure of BLUP used in routine breeding programs but makes it differentiable, maintaining its interpretability while making it embeddable in machine learning pipelines.

genomics↗

bioRxiv2025

Population genomics of yellow-eyed penguins uncovers subspecies divergence and candidate genes linked to respiratory distress syndrome

Yellow-eyed penguins (hoiho/takaraka, Megadyptes antipodes) are among the worlds rarest penguins and are regarded as a taonga (treasured) species in Aotearoa New Zealand. Since 2019, chicks on the New Zealand mainland have been affected by a deadly neonatal disease called respiratory distress syndrome (RDS), contributing to a decline to fewer than 143 breeding pairs. To investigate the putative genetic basis of this disease, we generated high-quality whole-genome data from 249 individuals spanning the species range, including from the New Zealand mainland (Northern range) and subantarctic Enderby and Campbell Islands (Southern). Population genomic analyses unexpectedly revealed three deeply divergent lineages with negligible gene flow, consistent with recognition of three distinct subspecies. Phylogenetic divergence dating suggests that these splits predate human arrival by several millennia, with the Northern lineage diverging from the Southern populations 5-16 ka. Genome scans for local adaptation revealed regions of strong differentiation, and genome-wide association analyses identified candidate immune and respiratory genes linked to RDS. In partnership with Ng[a]i Tahu, who hold indigenous guardianship over yellow-eyed penguins, we recommend recognition of three subspecies, urgent conservation action for the critically small and rapidly declining Northern subspecies, and the need for immediate population size and trend assessments for Auckland and Campbell Island populations.

genomics↗

bioRxiv2024

Rapid and cost-effective production of high-quality insect genome sequences

Insects are the most diverse group of animals on earth, with nearly 1 million species described to date, yet this variation is not reflected within the ranks of genomes currently available. In the current age of genetics, the generation of high-quality reference genomes is invaluable, often necessary and expensive. We prove that insect genomes do not need to come at a large cost. We demonstrate a cost-efficient method for producing high-quality insect genomes, with comparisons to current reference assemblies.

genomics↗

bioRxiv2024

Development of Germline Progenitors in Larval Queen Honeybee ovaries.

Honeybees (Apis mellifera) are a keystone species for managed pollination and the production of hive products. Eusociality in honeybees leads to much of the reproduction in a hive driven by the queen. Queen bees have two large active ovaries that can produce large numbers of eggs if conditions are appropriate. These ovaries are also active throughout the long lives of these insects, up to 5 years in some cases. Recent studies have indicated that the germline precursors of the adult honeybee queen ovary are organized into 8 cell clusters, joined together by a polyfusome; a cytoplasmic bridge. To understand the origin of these clusters, and trace the development of the honeybee queen ovary, we examined the cell types and regionalization of the developing larval and pupal queen ovaries. We used established (nanos and castor), and novel (odd skipped) gene expression markers to determine regions of the developing ovary. Primordial germline cells develop in the honeybee embryo and are organized into ovary structures before the embryo hatches. The ovary is regionalized by Larval Stage 3 into terminal filaments and germaria. At this stage clusters of germline cells in the germaria are joined by fusomes and are dividing synchronously. The origin of the 8-cell clusters in the adult germarium is therefore during larval stages. On emergence, the queen ovary has terminal filaments and germaria but has not yet developed any vitellaria, which are produced after the queen embarks on a nuptial flight. The lack of germaria, and the storing of germline progenitors as clusters, may be adaptions for queen bees to endure the metabolic demands of a nuptial flight, as well as rapidly lay large numbers of eggs to establish a hive.

developmental biology↗

bioRxiv2023

Scaffold-level genome assemblies of two parasitoid biocontrol wasps reveal the parthenogenesis mechanism and an associated novel virus

BackgroundBiocontrol is a key technology for the control of pest species. Microctonus parasitoid wasps (Hymenoptera: Braconidae) have been released in Aotearoa New Zealand as biocontrol agents, targeting three different pest weevil species. Despite their value as biocontrol agents, no genome assemblies are currently available for these Microctonus wasps, limiting investigations into key biological differences between the different species and strains. Methods and findingsHere we present high-quality genomes for Microctonus hyperodae and Microctonus aethiopoides, assembled with short read sequencing and Hi-C scaffolding. These assemblies have total lengths of 106.7 Mb for M. hyperodae and 129.2 Mb for M. aethiopoides, with scaffold N50 values of 9 Mb and 23 Mb respectively. With these assemblies we investigated differences in reproductive mechanisms, and association with viruses between Microctonus wasps. Meiosis-specific genes are conserved in asexual Microctonus, with in-situ hybridisation validating expression of one of these genes in the ovaries of asexual Microctonus aethiopoides. This implies asexual reproduction in these Microctonus wasps involves meiosis, with the potential for sexual reproduction maintained. Investigation of viral gene content revealed candidate genes that may be involved in virus-like particle production in M. aethiopoides, as well as a novel virus infecting M. hyperodae, for which a complete genome was assembled. Conclusion and significanceThese are the first published genomes for Microctonus wasps used for biocontrol in Aotearoa New Zealand, which will be valuable resources for continued investigation and monitoring of these biocontrol systems. Understanding the biology underpinning Microctonus biocontrol is crucial if we are to maintain its efficacy, or in the case of M. hyperodae to understand what may have influenced the significant decline of biocontrol efficacy. The potential for sexual reproduction in asexual Microctonus is significant given that empirical modelling suggests this asexual reproduction is likely to have contributed to biocontrol decline. Furthermore the identification of a novel virus in M. hyperodae highlights a previously unknown aspect of this biocontrol system, which may contribute to premature mortality of the host pest . These findings have potential to be exploited in future in attempt to increase the effectiveness of M. hyperodae biocontrol.

genomics↗

bioRxiv2022

Species-wide genomics of kakapo provides transformational tools to accelerate recovery

The k[a]k[a]p[o] is a critically endangered, intensively managed, long-lived nocturnal parrot endemic to Aotearoa New Zealand. We generated and analyzed whole-genome sequence data for nearly all individuals living in early 2018 (169 individuals) to generate a high-quality species-wide genetic variant callset. We leverage extensive long-term metadata to quantify genome-wide diversity of the species over time and present new approaches using probabilistic programming, combined with a phenotype dataset spanning five decades, to disentangle phenotypic variance into environmental and genetic effects while quantifying uncertainty in small populations. We find associations for growth, disease susceptibility, clutch size, and egg fertility within genic regions previously shown to influence these traits in other species. Finally, we generate breeding values to predict phenotype and illustrate that active management over the past 45 years has maintained both genome-wide diversity and diversity in breeding values, and hence, evolutionary potential. We provide new pathways for informing future conservation management decisions for k[a]k[a]p[o], including prioritizing individuals for translocation and monitoring individuals with poor growth or high disease risk. Overall, by explicitly addressing the challenge of small sample size, we provide a template for the inclusion of genomic data that will be transformational for species recovery efforts around the globe.

genomics↗

bioRxiv2021

Nasonia segmentation is regulated by an ancestral insect segmentation regulatory network also present in flies

Insect segmentation is a well-studied and tractable system with which to investigate the genetic regulation of development. Though insects segment their germband using a variety of methods, modelling work implies that a single gene regulatory network can underpin the two main types of insect segmentation. This means limited genetic changes are required to explain significant differences in segmentation mode between different insects. Evidence for this idea is limited to Drosophila melanogaster, Tribolium castaneum, and the spider Parasteatoda tepidariorum, and the nature of the gene regulatory network (GRN) underlying this model has not been tested. Some insects, for example Nasonia vitripennis and Apis mellifera segment progressively, a pattern not examined in studies of this segmentation model, producing stripes at different times throughout the embryo, but not from a segment addition zone. Here we aim to understand the GRNs patterning Nasonia using a simulation-based approach. We found that an existing model of Drosophila segmentation (Clark, 2017) can be used to recapitulate Nasonias progressive segmentation, if provided with altered inputs in the form of expression of the timer genes N{nu}-caudal and N{nu}-odd paired. We also predict limited topological changes to the pair rule network. Together this implies that very limited changes to the Drosophila network are required to simulate Nasonia segmentation, despite the differences in segmentation modes, implying that Nasonia use a very similar version of an ancestral GRN also used by Drosophila.

developmental biology↗

bioRxiv2019

Transcriptional analysis defines TCR and cytokine-stimulated MAIT cells as rapid polyfunctional effector T cells that can coordinate the immune response

MAIT cells are an abundant innate-like T cell population which can be activated via either their T cell receptor (TCR), which recognizes MR1-bound pyrimidine antigens derived from microbial riboflavin biosynthesis, or via cytokines, such as IL-12 and IL-18. In vivo, these two modes of activation may act in concert or independently depending upon the nature of the microbial or inflammatory stimuli. It is unknown, however, how the MAIT cell response differs to the different modes of activation. Here, we define the transcriptional and effector responses of human MAIT cells to TCR and cytokine stimulation. We report that MAIT cells rapidly respond to TCR stimulation through the production of multiple effector cytokines and chemokines, alteration of their cytotoxic granule content and transcription factor expression, and upregulation of co-stimulatory proteins CD40L and 4-1BB. In contrast, cytokine-mediated activation is slower and results in more limited production of cytokines, chemokines, and co-stimulatory proteins; differences in granule content and transcription factor expression are also evident. Therefore, we propose that in infections by riboflavin-synthesizing bacteria, MAIT cells play a key early role in effecting and coordinating the immune response, while in the absence of TCR stimulation (e.g. viral infection) their role is likely to differ.

immunology↗