Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

In Supplementary Table 1 of this Article, 23 samples (B10K-DU-029-32, B10K-DU-029-33, B10K-DU-029-36 to B10K-DU-029-44, B10K-DU- 029-46, B10K-DU-029-47, B10K-DU-029-49 to B10K-DU-029-53, B10K-DU- 029-75 to B10K-DU-029-77, B10K-DU-029-80, and B10K-DU-030-03; styled in boldface in the revised table) were assigned to the incorrect institution. Supplementary Table 1 has been amended to reflect the correct source institution for these samples, and associated data (tissue, museum ID/source specimen ID, site, state/province, latitude, longitude, date collected and sex) have been updated accordingly. The original table is provided as Supplementary Information to this Amendment, and the original Article has been corrected online.

Whole-genome sequencing projects are increasingly populating the tree of life and characterizing biodiversity^1-4. Sparse taxon sampling has previously been proposed to confound phylogenetic inference⁵, and captures only a fraction of the genomic diversity. Here we report a substantial step towards the dense representation of avian phylogenetic and molecular diversity, by analysing 363 genomes from 92.4% of bird families-including 267 newly sequenced genomes produced for phase II of the Bird 10,000 Genomes (B10K) Project. We use this comparative genome dataset in combination with a pipeline that leverages a reference-free whole-genome alignment to identify orthologous regions in greater numbers than has previously been possible and to recognize genomic novelties in particular bird lineages. The densely sampled alignment provides a single-base-pair map of selection, has more than doubled the fraction of bases that are confidently predicted to be under conservation and reveals extensive patterns of weak selection in predominantly non-coding DNA. Our results demonstrate that increasing the diversity of genomes used in comparative studies can reveal more shared and lineage-specific variation, and improve the investigation of genomic characteristics. We anticipate that this genomic resource will offer new perspectives on evolutionary processes in cross-species comparative analyses and assist in efforts to conserve species.