Wellcome Open Research最新文献

We present the genome assemblies of three females of the Danio rerio strains, AB, Nadia and Cooch Behar (zebrafish; Chordata; Actinopteri; Cypriniformes; Cyprinidae). These assemblies were released in 2020 as part of the Danioninae Sequencing Project. The genome sequence of the strain AB is 1,405.10 megabases, the Nadia strain 1,465.10, and the Cooch Behar strain 1,421.80 megabases in length. Most of the assembly is scaffolded into 25 chromosomal pseudomolecules in each case. For each strain, the mitochondrial genome was also assembled and is 16.6 kilobases in length.

We present a genome assembly from an individual male Sussaba pulchella (ichneumonid wasp; Arthropoda; Insecta; Hymenoptera; Ichneumonidae). The genome sequence has a total length of 299.91 megabases. Most of the assembly (81.88%) is scaffolded into 15 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 34.69 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.

We present a genome assembly from an individual Bimastos rubidus (Cockspur worm; Annelida; Clitellata; Crassiclitellata; Lumbricidae). The genome sequence has a total length of 812.74 megabases. Most of the assembly (95.63%) is scaffolded into 17 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 16.57 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.

We present a genome assembly from a female specimen of Danio aesculapii (the Panther Danio; Chordata; Actinopteri; Cypriniformes; Cyprinidae). The genome sequence is 1,381.5 megabases in span. Most of the assembly is scaffolded into 25 chromosomal pseudomolecules. Gene annotation of this assembly on Ensembl identified 23,884 protein coding genes.

We present a genome assembly from an individual male Cnephasia stephensiana (Grey Tortrix; Arthropoda; Insecta; Lepidoptera; Tortricidae). The assembly contains two haplotypes with total lengths of 465.14 megabases and 465.69 megabases. Most of haplotype 1 (99.5%) is scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 16.63 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.

In January 2024, the Kenya Ministry of Health issued an outbreak alert following a surge in acute hemorrhagic conjunctivitis (AHC) cases along the Kenyan coast. Our investigations identified coxsackievirus A24 variant (CV-A24v) as the causative agent. In this study, we developed a novel whole genome sequencing assay for CV-A24v, and used it to recover three near complete genomes from the 2024 AHC outbreak in Kenya. This method will support future studies on CV-A24v genomic epidemiology and evolution across Kenya and beyond.

We present a genome assembly from an individual male Netelia melanura (ichneumonid wasp; Arthropoda; Insecta; Hymenoptera; Ichneumonidae). The genome sequence has a total length of 253.87 megabases. Most of the assembly (94.81%) is scaffolded into 7 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 28.04 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.

We present a genome assembly from an individual female Dromius quadrimaculatus (ground beetle; Arthropoda; Insecta; Coleoptera; Carabidae). The genome sequence has a total length of 778.78 megabases. Most of the assembly (95.73%) is scaffolded into 14 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled, with a length of 16.57 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces reference genomes for eukaryotic species found in Britain and Ireland.

Background: Systematic reviews of effectiveness estimate the relative average effects of interventions and comparators in a set of existing studies e.g., using rate ratios. However, policymakers, planners and practitioners require predictions about outcomes in novel scenarios where aspects of the interventions, populations or settings may differ. This study aimed to develop and evaluate an ontology-informed, interpretable machine learning algorithm to predict smoking cessation outcomes using detailed information about interventions, their contexts and evaluation study methods. This is the second of two linked papers on the use of machine learning in the Human Behaviour-Change Project.

Methods: The study used a corpus of 405 reports of randomised trials of smoking cessation interventions from the Cochrane Library database. These were annotated using the Behaviour Change Intervention Ontology to classify, for each of 971 study arms, 82 features representing details of intervention content and delivery, population, setting, outcome, and study methodology. The annotated data was used to train a novel machine learning algorithm based on a set of interpretable rules organised according to the ontology. The algorithm was evaluated for predictive accuracy by performance in five-fold 80:20 cross-validation, and compared with other approaches.

Results: The machine learning algorithm produced a mean absolute error in prediction percentage cessation rates of 9.15% in cross-validation, which was lower than the mean absolute error of other approaches including an uninterpretable 'black-box' deep neural network (9.42%), a linear regression model (10.55%) and a decision tree-based approach (9.53%). The rules generated by the algorithm were synthesised into a consensus rule set to create a publicly available predictive tool to provide outcome predictions and explanations in the form of rules expressed in terms of predictive features and their combinations.

Conclusions: An ontologically-informed, interpretable machine learning algorithm, using information about intervention scenarios from reports of smoking cessation trials, can predict outcomes in new smoking cessation intervention scenarios with moderate accuracy.

We present a genome assembly from an individual male Pasiphila rectangulata (the Green Pug; Arthropoda; Insecta; Lepidoptera; Geometridae). The genome sequence is 582.5 megabases in span. Most of the assembly is scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.74 kilobases in length. Gene annotation of this assembly on Ensembl identified 17,153 protein coding genes.