Dense sampling of bird diversity increases power of comparative genomics

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 inference(5), 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. A dataset of the genomes of 363 species from the Bird 10,000 Genomes Project shows increased power to detect shared and lineage-specific variation, demonstrating the importance of phylogenetically diverse taxon sampling in whole-genome sequencing.Peer reviewe

Author Correction: Dense sampling of bird diversity increases power of comparative genomics

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

Common genetic variants influence human subcortical brain structures

The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction