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Borings in fossil turtle shells collected from the lowermost beds of the early Eocene Cathedral Bluffs Tongue of the Wasatch Formation in the northwestern part of the Green River Basin near South Pass, Wyoming, are herein described. Individual turtle shells in the study area are characterized by as few as one or two and as many as >100 borings. The borings include both non-penetrative forms (those which do not pass fully though the shell) as well as penetrative forms (those which pass fully from the exterior to the interior surface of the shell). All non-penetrative forms occur on external surfaces of the carapace and plastron (i.e. those that would have been accessible while the host taxon was alive). Two new ichnogenera and four new ichnospecies are established to describe these borings. Karethraichnus (new ichnogenus) includes three ichnospecies: K. lakkos (new ichnospecies), K. kulindros (new ichnospecies), and K. fiale (new ichnospecies). Karethraichnus lakkos are shallow (non-penetrating), hemispherical pits with rounded, to flattened bases. Karethraichnus kulindros are deep, non-penetrative traces with a cylindrical profile, an axis approximately perpendicular to the substrate surface and with rounded to flattened, hemispherical termini. Karethraichnus fiale are penetrative traces with a cylindrical to bi-convex or flask-shaped profile, and an axis approximately perpendicular to the substrate surface. Thatchtelithichnus (new ichnogenus) Thatchtelithichnus holmani (new ichnospecies) consist of non-penetrative borings into a bone substrate. They consist of a ring-shaped trace, with a central pedestal or platform. The position of the borings on the shells, and evidence of syn-emplacement healing of the borings in several of the turtles, indicates that these borings were emplacement by ectoparasites/mesoparasites while the animals were living. Similar traces in modern emydid turtles are attributed to ticks, leeches, or spirorchid liver flukes.

The ichnology of mixed siliciclastic/carbonate successions, in which sediment admixture has had a clear effect on infaunal populations, is discussed. Fundamental influences that allow for the development of unique ichnological signatures in mixed systems include grain size, grain shape, and early diagenetic alteration. Shell debris within dominantly siliciclastic successions introduces complexities into the infaunal habitat that are clearly reflected in trace-fossil assemblages. Some differences are preservational, with trace fossils inherently more difficult to recognize in coarser bioclastic intervals than in fine-grained siliciclastic intervals. Faunal level differences include those where some taxa are excluded by admixed bioclastic detritus or by reduced ecospace availability. Diagenetic processes in mixed systems also operate at different scales and temporal intervals, leading to fundamental differences in preservation and in substrate consistency. In mixed systems, quintessential carbonate ichnotextures co-occur with prototypical siliciclastic ichnotextures, such as successions with interstratified or coplanar firmground and hardground assemblages.

Understanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics. In this study, Aggarwal and colleagues perform prospective sequencing of SARS-CoV-2 isolates derived from asymptomatic student screening and symptomatic testing of students and staff at the University of Cambridge. They identify important factors that contributed to within university transmission and onward spread into the wider community.

The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. Our cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus pre-Alpha variants). The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages.

The objective of the present study was to estimate genetic co-variance parameters pertaining to live weight, feed intake, and 2 efficiency traits (i.e., residual feed intake and residual daily gain) in a population of pigs over a defined growing phase using Legendre polynomial equations. The data set used consisted of 51,893 live weight records and 903,436 feed intake, residual feed intake (defined as the difference between an animal’s actual feed intake and its expected feed intake), and residual daily gain (defined as the difference between an animal’s actual growth rate and its expected growth rate) records from 10,201 growing pigs. Genetic co-variance parameters for all traits were estimated using random regression Legendre polynomials. Daily heritability estimates for live weight ranged from 0.25 ± 0.04 (d 73) to 0.50 ± 0.03 (d 122). Low to moderate heritability estimates were evident for feed intake, ranging from 0.07 ± 0.03 (d 66) to 0.25 ± 0.02 (d 170). The estimated heritability for residual feed intake was generally lower than those of both live weight and feed intake and ranged from 0.04 ± 0.01 (d 96) to 0.17 ± 0.02 (d 159). The heritability for feed intake and residual feed intake increased in the early stages of the test period and subsequently sharply declined, coinciding with older ages. Heritability estimates for residual daily gain ranged from 0.26 ± 0.03 (d 188) to 0.42 ± 0.03 (d 101). Genetic correlations within trait were strongest between adjacent ages but weakened as the interval between ages increased; however, the genetic correlations within all traits tended to strengthen between the extremes of the trajectory. Moderate to strong genetic correlations were evident among live weight, feed intake, and the efficiency traits, particularly in the early stage of the trial period (d 66 to 86), but weakened with age. Results from this study could be implemented into the national genetic evaluation for pigs, providing comprehensive information on the profile of growth and efficiency throughout the growing period of the animal’s life, thus helping producers identify genetically superior animals.

Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations, and as an additional source of information when detecting possible transmission events. Due to their variable gene content and order, reference-free methods offer more sensitive detection of genetic differences, especially among closely related samples found in outbreaks. However, across longer genetic distances, frequent recombination can make calculation and interpretation of these differences more challenging, requiring significant bioinformatic expertise and manual intervention during the analysis process. Here we present a Population analysis PIPEline (PopPIPE) which combines rapid reference-free genome analysis methods to analyse bacterial genomes across these two scales, splitting whole populations into subclusters and detecting plausible transmission events within closely related clusters. We use k-mer sketching to split populations into strains, followed by split k-mer analysis and recombination removal to create alignments and subclusters within these strains. We first show that this approach creates high quality subclusters on a population-wide dataset of Streptococcus pneumoniae. When applied to nosocomial vancomycin resistant Enterococcus faecium samples, PopPIPE finds transmission clusters which are more epidemiologically plausible than core genome or MLST-based approaches. Our pipeline is rapid and reproducible, creates interactive visualisations, and can easily be reconfigured and re-run on new datasets. Therefore PopPIPE provides a user-friendly pipeline for analyses spanning species-wide clustering to outbreak investigations.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://github.com/bacpop/PopPIPE