Biology subjects

Day, T.

Publications and source records attributed to Day, T..

5 recordsLinked to original sources

bioRxiv2018

Managing Marek’s disease in the egg industry

The industrialization of farming has had an enormous impact. To most, this impact is viewed solely in the context of productivity, but the denser living conditions and shorter rearing periods of industrial livestock farms provide pathogens with an ideal opportunity to spread and evolve. For example, the industrialization of poultry farms drove the Mareks disease virus (MDV) to evolve from causing a mild paralytic syndrome to causing a highly contagious, globally prevalent, disease that can have up to a 100% mortality rate. Fortunately, the economic catastrophe that would occur from MDV evolution has been prevented through widespread use of live imperfect vaccines that limit disease symptoms, but fail to prevent transmission. Unfortunately, the continued rollout of such imperfect vaccines is steering the evolution of MDV towards an even greater virulence and an ability to evade vaccine protection. Thus, there is a need to investigate alternative economically viable control measures for their ability to inhibit MDV spread and evolution. In what follows we examine the economic viability of standard husbandry practices for their ability to inhibit the spread of both virulent MDV and very virulent MDV throughout an industrialized egg farm. To do this, we parameterized a dynamic MDV transmission model and calculate the loss in egg production due to disease. We find that the MDV strain as well as the cohort duration had the greatest influence on disease burden and hence egg production. Additionally, we find that the standard husbandry practice involving conventional cages, often referred to as \"battery cages\", results in the least per capita loss in egg production due to MDV infection when compared to alternative enriched or aviary (free-run) systems for virulent MDV, but not very virulent MDV, in which case the Aviary system performs the best. These results highlight an important cost that managers will face when implementing new hen husbandry practices.

epidemiology↗

bioRxiv2018

Parp3 promotes long-range end-joining in murine cells

Chromosomal rearrangements, including translocations, are early and essential events in the formation of many tumors. Previous studies that defined the genetic requirements for rearrangement formation have identified differences between murine and human cells, most notably in the role of classical- and alternative-nonhomologous end joining factors (NHEJ). We reported that poly(ADP)ribose polymerase 3 (PARP3) promotes chromosomal rearrangements induced by endonucleases in multiple human cell types. In contrast to c-NHEJ factors, we show here that Parp3 also promotes rearrangements in murine cells, including translocations in murine embryonic stem cells (mESCs), class switch recombination in primary B cells and inversions in tail fibroblasts that generate Eml4-Alk fusions. In mESCs, Parp3-deficient cells had shorter deletion lengths at translocation junctions. This was corroborated using next-generation sequencing of Eml4-Alk junctions in tail fibroblasts and is consistent with a role for Parp3 in promoting the processing of DNA double-strand breaks. We confirmed a previous report that Parp1 also promotes rearrangement formation. In contrast with Parp3, rearrangement junctions in the absence of Parp1 had longer deletion lengths, suggesting Parp1 may suppress DSB processing. Together, these data indicate that Parp3 and Parp1 promote rearrangements with distinct phenotypes.

cancer biology↗

bioRxiv2018

qFit-ligand reveals widespread conformational heterogeneity of drug-like molecules in X-ray electron density maps

Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein-ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor-ligand complexes. We found that up to 29 % of a dataset of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand-receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multi-temperature crystallography could therefore augment the structure-based drug design toolbox.

biophysics↗

bioRxiv2017

Pathogen evolution: slow and steady spreads the best

The theory of life history evolution provides a powerful framework to understand the evolutionary dynamics of pathogens in both epidemic and endemic situations. This framework, however, relies on the assumption that pathogen populations are very large and that one can neglect the effects of demographic stochasticity. Here we expand the theory of life history evolution to account for the effects of finite population size on the evolution of pathogen virulence. We show that demographic stochasticity introduces additional evolutionary forces that can qualitatively affect the dynamics and the evolutionary outcome. We discuss the importance of the shape of pathogen fitness landscape and host heterogeneity on the balance between mutation, selection and genetic drift. In particular, we discuss scenarios where finite population size can dramatically affect classical predictions of deterministic models. This analysis reconciles Adaptive Dynamics with population genetics in finite populations and thus provides a new theoretical toolbox to study life-history evolution in realistic ecological scenarios.

evolutionary biology↗

bioRxiv2017

The genetics of the human face: identification of large effect single gene variants

In order to discover specific variants with relatively large effects on the human face we have devised an approach to identifying facial features with high heritability. This is based on using twin data to estimate the additive genetic value of each point on a face, as provided by a 3D camera system. In addition, we have used the ethnic difference between East Asian and European faces as a further source of face genetic variation. We use principal components analysis to provide a fine definition of the surface features of human faces around the eyes and of the profile, and chose upper and lower 10% extremes of the most heritable PCs for looking for genetic associations. Using this strategy for the analysis of 3D images of 1832 unique volunteers from the well characterised People of the British Isles study [1, 2] and 1567 unique twin images from the TwinsUK cohort (www.twinsuk.ac.uk), together with genetic data for 500,000 SNPs, we have identified three specific genetic variants with notable effects on facial profiles and eyes.\n\nSignificance statementThe human face is extraordinarily variable and the extreme similarity of the faces of identical twins indicates that most of this variability is genetically determined. This level of genetic variability has probably arisen through natural selection, for example, for recognition of membership of a group or as a consequence of differential mate selection with respect to facial features. We have devised an approach to identifying specific genetic effects on particular facial features. This should enable the understanding, eventually at the molecular level, of the nature of this extraordinary genetic variability, which is such an important feature of our everyday human interactions.\n\nAuthor ContributionsWFB conceived the project. BW and TD organised collection of PoBI data and KH, DJMC, DM, AB and WFB assisted in data collection. TDS, PH and AN collected TwinsUK data. WPK and WJC conducted image registration analysis under supervision of JK. DJMC analysed registered image data and genetic data under supervision of WFB. WFB and DJMC wrote the manuscript, with WJC and WPK contributing additional technical material. WFB and BW supervised the project.

genetics↗