Motivation:The ongoing revolution in genome sequencing is delivering an unprecedented number of genome assemblies to global repositories, resulting in an overwhelming amount of data imported to UniProt in the form of proteomes. To manage this growth sustainably, there is a need for a systematic workflow to select the best proteomes. Results:We propose a novel pipeline for cellular organisms to select the best Reference Proteomes, i.e. those that best represent the protein space of a species. The pipeline uses a clustering algorithm based on MMseqs2 to select the minimum number of Reference Proteomes whilst maximising the representation of the protein space for each species. Additionally, we aligned our viral Reference Proteomes with the exemplar genome set defined by the International Committee on Taxonomy of Viruses. Because this method ensures that all species are represented with at least one Reference Proteome, the UniProt Knowledgebase increased the number of Reference Proteomes of 36% and covering 34% more species in the Tree of Life. The UniProt Knowledgebase will mainly retain proteins from Reference Proteomes and therefore this method reduces the overall number of proteins by 43%, leading to a more concise yet representative knowledgebase.

The Quest for Orthologs (QfO) orthology benchmark service (https://orthology.benchmarkservice.org) hosts a wide range of standardized benchmarks for orthology inference evaluation. It is supported and maintained by the QfO consortium, and is used to gather ortholog predictions and to examine strengths and weaknesses of newly developed and existing orthology inference methods. The web server allows different inference methods to be compared in a standardized way using the same proteome data. The benchmark results are useful for developing new methods and can help researchers to guide their choice of orthology method for applications in comparative genomics and phylogenetic analysis. We here present a new release of the Orthology Benchmark Service with a new benchmark based on feature architecture similarity as well as updated reference proteomes. We further provide a meta-analysis of the public predictions from 18 different orthology assignment methods to reveal how they relate in terms of ortholog predictions and benchmark performance. These results can guide users of orthologs to the best suited method for their purpose.

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 publication we describe enhancements made to our data processing pipeline and to our website to adapt to an ever-increasing information content. The number of sequences in UniProtKB has risen to over 227 million and we are working towards including a reference proteome for each taxonomic group. We continue to extract detailed annotations from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations provided by automated systems using a variety of machine-learning techniques. In addition, the scientific community continues their contributions of publications and annotations to UniProt entries of their interest. Finally, we describe our new website (https://www.uniprot.org/), designed to enhance our users' experience and make our data easily accessible to the research community. This interface includes access to AlphaFold structures for more than 85% of all entries as well as improved visualisations for subcellular localisation of proteins.

Abstract The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed. Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

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/.

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed. Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

The universal protein knowledgebase (UniProtKB) collects and centralises functional information on proteins across a wide range of species. In addition to the functional information added to all protein entries, for enzymes, which represent 20–40% of most proteomes, UniProtKB provides additional information about Enzyme Commission classification, catalytic activity, cofactors, enzyme regulation, kinetics and pathways, all based on critical assessment of published experimental data. Computer‐based analysis and structural data are used to enrich the annotation of the sequence through the identification of active sites and binding sites. While the annotation of enzymes is well‐defined, the curation of pseudoenzymes in UniProtKB has highlighted some challenges: how to identify them, how to assess their lack of catalytic activity, how to annotate their lack of catalytic activity in a consistent way and how much can be inferred and propagated from experimental data obtained from other species. Through various examples, we illustrate some of these issues and discuss some of the changes we propose to enhance the annotation and discovery of pseudoenzymes. Ultimately, improving the curation of pseudoenzymes will provide the scientific community with a comprehensive resource for pseudoenzymes, which in turn will lead to a better understanding of the evolution of these molecules, the aetiology of related diseases and the development of drugs.

Mosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii . We analysed whole genomes of 1,142 individual mosquitoes sampled from the wild in 13 African countries, and a further 234 individuals comprising parents and progeny of 11 lab crosses. The data resource includes high confidence single nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We used these data to analyse genetic population structure, and characterise genetic diversity within and between populations. We also illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance, and for accelerating research and development of new vector control tools.

Background As the prevalence of artemisinin-resistant Plasmodium falciparum malaria increases in the Greater Mekong subregion, emerging resistance to partner drugs in artemisinin combination therapies seriously threatens global efforts to treat and eliminate this disease. Molecular markers that predict failure of artemisinin combination therapy are urgently needed to monitor the spread of partner drug resistance, and to recommend alternative treatments in southeast Asia and beyond.Methods We did a genome-wide association study of 297 P falciparum isolates from Cambodia to investigate the relationship of 11630 exonic single-nucleotide polymorphisms (SNPs) and 43 copy number variations (CNVs) with in-vitro piperaquine 50% inhibitory concentrations (IC(50)s), and tested whether these genetic variants are markers of treatment failure with dihydroartemisinin piperaquine. We then did a survival analysis of 133 patients to determine whether candidate molecular markers predicted parasite recrudescence following dihydroartemisinin piperaquine treatment.Findings Piperaquine IC(50)s increased significantly from 2011 to 2013 in three Cambodian provinces (2011 vs 2013 median IC(50)s: 20.0 nmol/L [IQR 13.7-29.0] vs 39.2 nmol/L [32.8-48.1] for Ratanakiri, 19.3 nmol/L [15.1-26.2] vs 66.2 nmol/L [49.9-83.0] for Preah Vihear, and 19.6 nmol/L [11.9-33.9] vs 81.1 nmol/L [61.3-113.1] for Pursat; all p <= 10(-3); Kruskal-Wallis test). Genome-wide analysis of SNPs identified a chromosome 13 region that associates with raised piperaquine IC(50)s. A non-synonymous SNP (encoding a Glu415Gly substitution) in this region, within a gene encoding an exonuclease, associates with parasite recrudescence following dihydroartemisinin piperaquine treatment. Genome-wide analysis of CNVs revealed that a single copy of the mdrl gene on chromosome 5 and a novel amplification of the plasmepsin 2 and plasmepsin 3 genes on chromosome 14 also associate with raised piperaquine IC(50)s. After adjusting for covariates, both exo-E415G and plasmepsin 2-3 markers significantly associate (p=3.0 x10(-8) and p=1.7 x10(-7), respectively) with decreased treatment efficacy (survival rates 0.38 [95% CI 0.25-0.51] and 0.41 [0.28-0.53], respectively).Interpretation The exo-E415G SNP and plasmepsin 2-3 amplification are markers of piperaquine resistance and dihydroartemisinin piperaquine failures in Cambodia, and can help monitor the spread of these phenotypes into other countries of the Greater Mekong subregion, and elucidate the mechanism of piperaquine resistance. Since plasmepsins are involved in the parasite's haemoglobin-to-haemozoin conversion pathway, targeted by related antimalarials, plasmepsin 2-3 amplification probably mediates piperaquine resistance. Copyright (C) The Author(s). Published by Elsevier Ltd.

The current epidemic of artemisinin resistant Plasmodium falciparum in Southeast Asia is the result of a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of variations that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions.

ABSTRACT Translating genomic technologies into healthcare applications for the malaria parasite Plasmodium falciparum has been limited by the technical and logistical difficulties of obtaining high quality clinical samples from the field. Sampling by dried blood spot (DBS) finger-pricks can be performed safely and efficiently with minimal resource and storage requirements compared with venous blood (VB). Here, we evaluate the use of selective whole genome amplification (sWGA) to sequence the P. falciparum genome from clinical DBS samples, and compare the results to current methods using leucodepleted VB. Parasite DNA with high (> 95%) human DNA contamination was selectively amplified by Phi29 polymerase using short oligonucleotide probes of 8-12 mers as primers. These primers were selected on the basis of their differential frequency of binding the desired ( P. falciparum DNA) and contaminating (human) genomes. Using sWGA method, we sequenced clinical samples from 156 malaria patients, including 120 paired samples for head-to-head comparison of DBS and leucodepleted VB. Greater than 18-fold enrichment of P. falciparum DNA was achieved from DBS extracts. The parasitaemia threshold to achieve >5x coverage for 50% of the genome was 0.03% (40 parasites per 200 white blood cells). Over 99% SNP concordance between VB and DBS samples was achieved after excluding missing calls. The sWGA methods described here provide a reliable and scalable way of generating P. falciparum genome sequence data from DBS samples. Our data indicate that it will be possible to get good quality sequence data on most if not all drug resistance loci from the majority of symptomatic malaria patients. This technique overcomes a major limiting factor in P. falciparum genome sequencing from field samples, and paves the way for large-scale epidemiological applications.

Artemisinin resistant Plasmodium falciparum is advancing across Southeast Asia in a soft selective sweep involving at least 20 independent kelch13 mutations. In a large global survey, we find that kelch13 mutations which cause resistance in Southeast Asia are present at low frequency in Africa. We show that African kelch13 mutations have originated locally, and that kelch13 shows a normal variation pattern relative to other genes in Africa, whereas in Southeast Asia there is a great excess of non-synonymous mutations, many of which cause radical amino-acid changes. Thus, kelch13 is not currently undergoing strong selection in Africa, despite a deep reservoir of standing variation that could potentially allow resistance to emerge rapidly. The practical implications are that public health surveillance for artemisinin resistance should not rely on kelch13 data alone, and interventions to prevent resistance must account for local evolutionary conditions, shown by genomic epidemiology to differ greatly between geographical regions.

Gram-negative bacterial outer membrane proteins play important roles in the interaction of bacteria with their environment including nutrient acquisition, adhesion and invasion, and antibiotic resistance. In this study we identified 47 proteins within the Sarkosyl-insoluble fraction of Campylobacter jejuni 81-176, using LC–ESI-MS/MS. Comparative analysis of outer membrane protein sequences was visualised to reveal protein distribution within a panel of Campylobacter spp., identifying several C. jejuni-specific proteins. Smith–Waterman analyses of C. jejuni homologues revealed high sequence conservation amongst a number of hypothetical proteins, sequence heterogeneity of other proteins and several proteins which are absent in a proportion of strains.

Background: Drug resistance remains a chief concern for malaria control. In order to determine the genetic markers of drug resistant parasites, we tested the genome-wide associations (GWA) of sequence-based genotypes from 35 Kenyan P. falciparum parasites with the activities of 22 antimalarial drugs.Methods and Principal Findings: Parasites isolated from children with acute febrile malaria were adapted to culture, and sensitivity was determined by in vitro growth in the presence of anti-malarial drugs. Parasites were genotyped using whole genome sequencing techniques. Associations between 6250 single nucleotide polymorphisms (SNPs) and resistance to individual anti-malarial agents were determined, with false discovery rate adjustment for multiple hypothesis testing. We identified expected associations in the pfcrt region with chloroquine (CQ) activity, and other novel loci associated with amodiaquine, quinazoline, and quinine activities. Signals for CQ and primaquine (PQ) overlap in and around pfcrt, and interestingly the phenotypes are inversely related for these two drugs. We catalog the variation in dhfr, dhps, mdr1, nhe, and crt, including novel SNPs, and confirm the presence of a dhfr-164L quadruple mutant in coastal Kenya. Mutations implicated in sulfadoxine-pyrimethamine resistance are at or near fixation in this sample set.Conclusions/Significance: Sequence-based GWA studies are powerful tools for phenotypic association tests. Using this approach on falciparum parasites from coastal Kenya we identified known and previously unreported genes associated with phenotypic resistance to anti-malarial drugs, and observe in high-resolution haplotype visualizations a possible signature of an inverse selective relationship between CQ and PQ.

We describe an analysis of genome variation in 825 P. falciparum samples from Asia and Africa that identifies an unusual pattern of parasite population structure at the epicenter of artemisinin resistance in western Cambodia. Within this relatively small geographic area, we have discovered several distinct but apparently sympatric parasite subpopulations with extremely high levels of genetic differentiation. Of particular interest are three subpopulations, all associated with clinical resistance to artemisinin, which have skewed allele frequency spectra and high levels of haplotype homozygosity, indicative of founder effects and recent population expansion. We provide a catalog of SNPs that show high levels of differentiation in the artemisinin-resistant subpopulations, including codon variants in transporter proteins and DNA mismatch repair proteins. These data provide a population-level genetic framework for investigating the biological origins of artemisinin resistance and for defining molecular markers to assist in its elimination.

Next-generation sequencing is used here to analyse Plasmodium falciparum genome variation directly from clinical blood samples, as well as cultured isolates, from Africa, Asia and Oceania. Resistance to the major antimalarial drug artemisinin is emerging in the Plasmodium falciparum parasite across Southeast Asia, and there is concern that the increased deployment of antimalarials in pursuit of disease eradication might simply lead to increased drug resistance. To monitor these risks it is important to survey the parasite population for genetic changes. Next-generation sequencing is used here to analyse P. falciparum genome variation directly from nearly 300 clinical blood samples, and from cultured isolates from Africa, Asia and Oceania. The authors use these data to analyse the diversity of the parasite population across different geographical locations, as well as within-host diversity at the level of the whole genome, and they show how this may be used to estimate inbreeding rates, which are important for the evolution of drug resistance. Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance1,2. Here we describe methods for the large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short-term culture. Analysis of 86,158 exonic single nucleotide polymorphisms that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for the exploration of regional differences in allele frequency and of highly differentiated loci in the P. falciparum genome.