Biology subjects

Powell, O.

Publications and source records attributed to Powell, O..

7 recordsLinked to original sources

bioRxiv2026

Metagenomic analysis of the effects of European bison Bison bonasus (Linnaeus, 1758) presence on soil community structure and function in West Blean and Thornden Woods, Kent

The reintroduction of extinct or endangered species to restore ecosystem function is an essential aspect of rewilding. The Wilder Blean Project at West Blean and Thornden Woods in Canterbury, UK, is committed to rewilding natural processes and enhancing biodiversity in one of England's oldest and largest areas of ancient woodland. The introduction of European bison (Bison bonasus) is an important part of the project. However, how the reintroduction of large herbivores influences local biodiversity and ecosystem functions during the early stages of rewilding remains poorly understood. Soil samples were collected from the same sampling sites before and two years after bison were reintroduced and profiled by metagenomic sequencing using Oxford Nanopore Technologies sequencing platforms. The results showed that the alpha diversity of soil organisms did not change significantly before and after the introduction of European bison, while beta diversity showed modest shifts in community composition. The relative abundance of some nitrogen-fixing and photosynthetic microbial genera showed declines in the 2024 Bison Area, while the mycorrhizal fungus genus Rhizophagus was significantly less abundant than in the 2024 Control Area. Despite relatively stable taxonomic diversity, functional composition differed significantly between the 2022 and 2024 Bison areas and among the 2024 rewilding treatments, revealing a decoupling between taxonomic diversity and functional composition. Amino acid synthesis pathways and carbon metabolism pathways were significantly enriched. These findings highlight the potential of long-read Oxford Nanopore metagenomics to reveal functional shifts that may not be apparent from taxonomic diversity alone. Although these early-stage responses cannot yet predict long-term rewilding trajectories, continued longitudinal monitoring integrating microbial, soil physicochemical, and ecosystem-level measurements will be essential to determine the persistence and ecological significance of these functional shifts.

ecology↗

bioRxiv2024

Elongation of the nascent avian foregut requires coordination of intrinsic and extrinsic cell behaviors

The foregut tube gives rise to the lungs and upper gastrointestinal tract, enabling vital functions of respiration and digestion. How the foregut tube forms during embryonic development has historically received considerable attention, but over the past few decades this question has primarily been addressed indirectly through studies on morphogenesis of the primitive heart tube, a closely related process. As a result, many aspects of foregut development remain unresolved. Here, we exploit the accessibility of the chick embryo to study the initial formation of the foregut tube, combining embryology with fate mapping, live imaging, and biomechanical analyses. The present study reveals that the foregut forms and elongates over a narrower time window than previously thought, and displays marked dorso-ventral and left-right asymmetries early in its development. Through tissue-specific ablation of endoderm along the anterior intestinal portal, we confirm its central biomechanical role in driving foregut morphogenesis, despite not directly contributing cells to the elongating tube. We further confirm the important role of this cell population in formation of the heart tube, with evidence that this role extends to later stages of cardiac looping as well. Together, these data reveal the need for an intricate balance between intrinsic cell behaviors and extrinsic forces for normal foregut elongation, and set the stage for future studies aimed at understanding the underlying molecular cues that coordinate this balance. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=171 HEIGHT=200 SRC="FIGDIR/small/621372v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@374c2corg.highwire.dtl.DTLVardef@69ed3aorg.highwire.dtl.DTLVardef@55823aorg.highwire.dtl.DTLVardef@1d8d4fd_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2024

Application of tissue-scale tension to avian epithelia in vivo to study multiscale mechanical properties and inter-germ layer coupling

As cross-disciplinary approaches drawing from physics and mechanics have increasingly influenced our understanding of morphogenesis, the tools available to measure and perturb physical aspects of embryonic development have expanded as well. However, it remains a challenge to measure mechanical properties and apply exogenous tissue-scale forces in vivo, particularly for epithelia. Exploiting the size and accessibility of the developing chick embryo, here we describe a simple technique to quantitatively apply exogenous forces on the order of 1-100 N to the endodermal epithelium. To demonstrate the utility of this approach, we performed a series of proof-of-concept experiments that reveal fundamental and unexpected mechanical behaviors in the early chick embryo, including mechanotype heterogeneity among cells of the midgut endoderm, complex non-cell autonomous effects of actin disruption, and a high degree of mechanical coupling between the endoderm and adjacent paraxial mesoderm. To illustrate the broader utility of this method, we determined that forces on the order of 10 N are sufficient to unzip the neural tube during primary neurulation. Together, these findings provide basic insights into the mechanics of embryonic epithelia in vivo in the early avian embryo, and provide a useful tool for future investigations of how morphogenesis is influenced by mechanical factors. Graphical AbstractO_ST_ABSSummary StatementC_ST_ABS O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/588089v2_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@7f0d90org.highwire.dtl.DTLVardef@153a4b0org.highwire.dtl.DTLVardef@614051org.highwire.dtl.DTLVardef@c5b432_HPS_FORMAT_FIGEXP M_FIG C_FIG A simple approach is devised to quantitatively apply tension to epithelia in vivo, and used to study endoderm mechanics in the deeloping chick embryo.

developmental biology↗

bioRxiv2022

Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: A case study of shoot branching in plants

Predictive breeding is now widely practised in crop improvement programs and has accelerated selection response (i.e., the amount of genetic gain between breeding cycles) for complex traits. However, world food production needs to increase further to meet the demands of the growing human population. The prediction of complex traits with current methods can be inconsistent across different genetic, environmental, and agronomic management contexts because the complex relationships between genomic and phenotypic variation are not well accounted for. Therefore, developing gene-to-phenotype network models for traits that integrate the knowledge of networks from systems biology, plant and crop physiology with population genomics has been proposed to close this gap in predictive modelling. Here, we develop a gene-to-phenotype network for shoot branching, a critical developmental pathway underpinning harvestable yield for many crop species, as a case study to explore the value of developing gene-to-phenotype networks to enhance understanding of selection responses. We observed that genetic canalization is an emergent property of the complex interactions among shoot branching gene-to-phenotype network components, leading to the accumulation of cryptic genetic variation, reduced selection responses, and large variation in selection trajectories across populations. As genetic canalization is expected to be pervasive in traits, such as grain yield, that result from interactions among multiple genes, traits, environments, and agronomic management practices, the need to model traits in crop improvement programs as outcomes of gene-to-phenotype networks is highlighted as an emerging opportunity to advance our understanding of selection response and the efficiency of developing resilient crops for future climates.

genetics↗

bioRxiv2020

Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

Plant breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeders equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeders equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimisation of selection in breeding programs.

genetics↗

bioRxiv2020

Spatial modelling improves genetic evaluation in smallholder breeding programs

Breeders and geneticists use statistical models for genetic evaluation of animals to separate genetic and environmental effects on phenotype. A common way to separate these effects is to model a descriptor of an environment, a contemporary group or herd, and account for genetic relationship between animals across the environments. However, separating the genetic and environmental effects in smallholder systems is challenging due to small herd sizes and weak genetic connectedness across herds. Our hypothesis was that accounting for spatial relationships between nearby herds can improve genetic evaluation in smallholder systems. Further, geographically referenced environmental covariates are increasingly available and could be used to model underlying sources of the spatial relationships. The objective of this study was therefore to evaluate the potential of spatial modelling to improve genetic evaluation in smallholder systems. We focus solely on dairy cattle smallholder systems. We performed simulations and real dairy cattle data analysis to test our hypothesis. We used a range of models to account for environmental variation by estimating herd and spatial effects. We compared these models using pedigree or genomic data. The results show that in smallholder systems (i) standard models are not able to separate genetic and environmental effects, (ii) spatial modelling increases accuracy of genetic evaluation for phenotyped and non-phenotyped animals, (iii) environmental covariates do not substantially improve accuracy of genetic evaluation beyond simple distance-driven spatial relationships between herds, (iv) the benefit of spatial modelling was the largest when the genetic and environmental effects were hard to separate and (v) spatial modelling was beneficial when using either pedigree or genomic data. We have demonstrated the potential of spatial modelling to improve genetic evaluation in smallholder systems. This improvement is driven by establishing environmental connectedness between herds that enhances separation of the genetic and environmental effects. We suggest routine spatial modelling in genetic evaluations, particularly for smallholder systems. Spatial modelling could also have major impact in studies of human and wild populations.

genetics↗

bioRxiv2020

ShearFAST: a user-friendly in vitro toolset for high throughput, inexpensive fluid shear stress experiments.

Fluid shear stress is a key modulator of cellular physiology in vitro and in vivo, but its effects are under-investigated due to requirements for complicated induction methods. Herein we report the validation of ShearFAST; a smartphone application that measures the rocking profile on a standard laboratory cell rocker and calculates the resulting shear stress arising in tissue culture plates. ShearFAST measured rocking profiles were validated against a graphical analysis and also against measures reported by an 8-camera motion tracking system. ShearFAST angle assessments correlated well with both analyses (r [≥]0.99, p [≤]0.001) with no significant differences in pitch detected across the range of rocking angles tested. Rocking frequency assessment by ShearFAST also correlated well when compared to the two independent validatory techniques (r [≥]0.99, p [≤]0.0001), with excellent reproducibility between ShearFAST and video analysis (mean frequency measurement difference of 0.006 {+/-} 0.005Hz) and motion capture analysis (mean frequency measurement difference of 0.008 {+/-} 0.012Hz) These data make the ShearFAST assisted cell rocker model make it an attractive approach for economical, high throughput fluid shear stress experiments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/929513v3_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1d8c1eborg.highwire.dtl.DTLVardef@1a346eborg.highwire.dtl.DTLVardef@8503a8org.highwire.dtl.DTLVardef@b31a3f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗