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A potential record of Earth’s magnetic field going back 4.2 billion years (Ga) ago is carried by magnetite inclusions in zircon grains from the Jack Hills. This magnetite may be secondary in nature, however, meaning that the magnetic record is much younger than the zircon crystallization age. Here, we use atom probe tomography to show that Pb-bearing nanoclusters in magnetite-bearing Jack Hills zircons formed during two discrete events at 3.4 and <2 Ga. The older population of clusters contains no detectable Fe, whereas roughly half of the younger population of clusters is Fe bearing. This result shows that the Fe required to form secondary magnetite entered the zircon sometime after 3.4 Ga and that remobilization of Pb and Fe during an annealing event occurred more than 1 Ga after deposition of the Jack Hills sediment at 3 Ga. The ability to date Fe mobility linked to secondary magnetite formation provides new possibilities to improve our knowledge of the Archean geodynamo.

Phytophthora species are oomycete plant pathogens that cause great economic and ecological impacts. The Phytophthora genus includes over 180 known species, infecting a wide range of plant hosts, including crops, trees, and ornamentals. We sequenced the genomes of 31 individual Phytophthora species and 24 individual transcriptomes to study genetic relationships across the genus. De novo genome assemblies revealed variation in genome sizes, numbers of predicted genes, and in repetitive element content across the Phytophthora genus. A genus-wide comparison evaluated orthologous groups of genes. Predicted effector gene counts varied across Phytophthora species by effector family, genome size, and plant host range. Predicted numbers of apoplastic effectors increased as the host range of Phytophthora species increased. Predicted numbers of cytoplasmic effectors also increased with host range but leveled off or decreased in Phytophthora species that have enormous host ranges. With extensive sequencing across the Phytophthora genus, we now have the genomic resources to evaluate horizontal gene transfer events across the oomycetes. Using a machine-learning approach to identify horizontally transferred genes with bacterial or fungal origin, we identified 44 candidates over 36 Phytophthora species genomes. Phylogenetic reconstruction indicates that the transfers of most of these 44 candidates happened in parallel to major advances in the evolution of the oomycetes and Phytophthora spp. We conclude that the 31 genomes presented here are essential for investigating genus-wide genomic associations in genus Phytophthora. [Formula: see text]

Many strains of Pseudomonas colonise plant surfaces, including the cherry canker pathogens, Pseudomonas syringae pathovars syringae and morsprunorum. We have examined the genomic diversity of P. syringae in the cherry phyllosphere and focused on the role of prophages in transfer of genes encoding Type 3 secreted effector (T3SE) proteins contributing to the evolution of virulence. Phylogenomic analysis was carried out on epiphytic pseudomonads in the UK orchards. Significant differences in epiphytic populations occurred between regions. Nonpathogenic strains were found to contain reservoirs of T3SE genes. Members of P. syringae phylogroups 4 and 10 were identified for the first time from Prunus. Using bioinformatics, we explored the presence of the gene encoding T3SE HopAR1 within related prophage sequences in diverse P. syringae strains including cherry epiphytes and pathogens. Results indicated that horizontal gene transfer (HGT) of this effector between phylogroups may have involved phage. Prophages containing hopAR1 were demonstrated to excise, circularise and transfer the gene on the leaf surface. The phyllosphere provides a dynamic environment for prophage-mediated gene exchange and the potential for the emergence of new more virulent pathotypes. Our results suggest that genome-based epidemiological surveillance of environmental populations will allow the timely application of control measures to prevent damaging diseases.

Society Impact Statement: Until the 1970s, the majority of commercial strawberry varieties produced a single bloom of flowers. However, continuously flowering, everbearing strawberries are now routinely cultivated and use is increasing. Indeed, introgression of the everbearing flowering trait can lead to economic benefits for growers through the production of a continual crop from the same plant. Genetically guided improvement has the power to streamline everbearing generation. As such, the genetic markers reported here can help to identify everbearing individuals at an early time point in the breeding process. Furthermore, these markers can help to improve the predictions of progeny segregation ratios. Summary: Previous work within the community led to the identification of a single dominant allele that controls the everbearing trait. However, frequent observations have indicated that crosses do not segregate in a Mendelian fashion, as would be expected for a trait controlled by a single dominant gene. Therefore, it was hypothesised that one or more unidentified epistatic alleles interact with the major gene. A genome-wide association study (GWAS) was conducted on 587 June bearers and 207 everbearers to assess the genetic components associated with flowering habit. The segregation ratios of parental strawberry lines with known phenotypes were used to validate the identified alleles. Three loci including the known major FaPFRU locus and two epistatic modifiers were identified. These modifiers function as enhancers of the everbearing trait in individuals containing a single copy of the FaPFRU everbearing allele and appear to be functionally redundant. Principally, heterozygous individuals required the presence of two modifying alleles in order to allow expression of the everbearing trait. Inclusion of the epistatic alleles improved the prediction of everbearing segregation ratios; beyond that of a single allele model, however, a large proportion of the variation rema

Particle acceleration is a fundamental process arising in many astrophysical objects, including active galactic nuclei, black holes, neutron stars, gamma-ray bursts, accretion disks, solar and stellar coronae, and planetary magnetospheres. Its ubiquity means energetic particles permeate the Universe and influence the conditions for the emergence and continuation of life. In our solar system, the Sun is the most energetic particle accelerator, and its proximity makes it a unique laboratory in which to explore astrophysical particle acceleration. However, despite its importance, the physics underlying solar particle acceleration remain poorly understood. The SPARK mission will reveal new discoveries about particle acceleration through a uniquely powerful and complete combination of γ-ray, X-ray, and EUV imaging and spectroscopy at high spectral, spatial, and temporal resolutions. SPARK’s instruments will provide a step change in observational capability, enabling fundamental breakthroughs in our understanding of solar particle acceleration and the phenomena associated with it, such as the evolution of solar eruptive events. By providing essential diagnostics of the processes that drive the onset and evolution of solar flares and coronal mass ejections, SPARK will elucidate the underlying physics of space weather events that can damage satellites and power grids, disrupt telecommunications and GPS navigation, and endanger astronauts in space. The prediction of such events and the mitigation of their potential impacts are crucial in protecting our terrestrial and space-based infrastructure.

Scripts and dataset for Vinchira-Villarraga et al., 2023 "Influence of the extraction protocol on the chemical diversity of tree woody-tissue metabolome". The files label as A1, C6, H2/HCN2 and O1 correspond to the dataset obtained for Ash, Cherry, Horse-chestnut and Oak respectively. _batch.xml files contains the script for the pre-processing of .mzML mass spectrometry data created on MzMine 3.2.8. The file can be uploaded to newer versions of MzMine, but due to the addition of new modules, some parameters name have changed. _SIRIUS.mfg files contains the mass spectrometry data of each dataset for analysis in SIRIUS. The files were used for chemical formula prediction, classification and compound annotation using SIRIUS 4.0 _quant.csv correspond to the output matrix as it was obtained from MzMine without noise, adducts and highly variable features filtering. _abundance.csv correspond to the output matrix after noise, adducts and highly variable features filtering.