The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

Evolution of insecticide resistance, measured by the though the rate at which this occurred varied. The slowfrequency of a resistant allele and by population size, was est response to selection occurred when (I) the populasimulated on a computer. The effects of dominance, tion was diluted by immigrants, (2) population density initial gene frequency, refugia, immigration, and repro-was drastically suppressed by severe selection, and (3) ductive potential were studied singly with a deterministic susceptible individuals had a reproductive advantage over model. In all cases, resistance evolved eventually, al-their resistant counterparts.

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Cry proteins produced by Bacillus thuringiensis are selective biodegradable insecticides used increasingly in bacterial insecticides and transgenic plants as alternatives to synthetic chemical insecticides. However, the potential for development of resistance and cross-resistance in target insect populations to Cry proteins used alone or in combination threatens the more widespread use of this novel pest control technology. Here we show that high levels of resistance to CryIV proteins in larvae of the mosquito, Culex quinquefasciatus, can be suppressed or reduced markedly by combining these proteins with sublethal quantities of CytA, a cytolytic endotoxin of B. thuringiensis. Resistance at the LC 95 level of 127-fold for a combination of three CryIV toxins (CryIVA, B, and D), resulting from 60 generations of continuous selection, was completely suppressed by combining sporulated powders of CytA in a 1:3 ratio with sporulated powders of a CryIVA, CryIVB, and CryIVD strain. Combining the CytA strain with a CryIVA and CryIVB strain also completely suppressed mosquito resistance of 217-fold to the latter toxins at the LC 95 level, whereas combination of CytA with CryIVD reduced resistance in a CryIVD-selected mosquito strain from greater than 1,000-fold to less than 8-fold. The CytA͞CryIV model provides a potential molecular genetic strategy for engineering resistance management for Cry proteins directly into bacterial insecticides and transgenic plants.

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