Abstract
Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.
Highlights
ResultsWe used a whole-genome shotgun strategy to generate genome sequences of 45 new avian species [18], including two species representing two orders within the infraclass Paleognathae [common ostrich (Struthio camelus) and whitethroated tinamou (Tinamus guttatus)], the other order within Galloanserae [Peking duck (Anas platyrhynchos)], and 41 species representing 30 neoavian orders (table S1) [19]
Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields
To avoid systematic biases related to the use of different methods in annotations of previously published avian genomes, we created a uniform reference gene set that included all genes from the chicken, zebra finch, and human [23]
Summary
We used a whole-genome shotgun strategy to generate genome sequences of 45 new avian species [18], including two species representing two orders within the infraclass Paleognathae [common ostrich (Struthio camelus) and whitethroated tinamou (Tinamus guttatus)], the other order within Galloanserae [Peking duck (Anas platyrhynchos)], and 41 species representing 30 neoavian orders (table S1) [19]. For the remaining 25 species, we generated low (~30×) coverage data from two insert-size libraries and built less complete but still sufficient assemblies for comparative genome analyses. To avoid systematic biases related to the use of different methods in annotations of previously published avian genomes, we created a uniform reference gene set that included all genes from the chicken, zebra finch, and human [23]. This database was used to predict protein gene models in all avian genomes and American alligator (Alligator mississippiensis) [24]. Despite the fragmented nature of the lowcoverage genomes leading to ~3000 genes likely missing or partially annotated, it was still possible to predict 70 to 80% of the entire catalog of avian genes
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