Determining the evolutionary relationships among the major lineages of extant birds has been one of the biggest challenges in systematic biology. To address this challenge, we assembled or collected the genomes of 48 avian species spanning most orders of birds, including all Neognathae and two of the five Palaeognathae orders. We used these genomes to construct a genome-scale avian phylogenetic tree and perform comparative genomic analyses.
Here we present the datasets associated with the phylogenomic analyses, which include sequence alignment files consisting of nucleotides, amino acids, indels, and transposable elements, as well as tree files containing gene trees and species trees. Inferring an accurate phylogeny required generating: 1) A well annotated data set across species based on genome synteny; 2) Alignments with unaligned or incorrectly overaligned sequences filtered out; and 3) Diverse data sets, including genes and their inferred trees, indels, and transposable elements. Our total evidence nucleotide tree (TENT) data set (consisting of exons, introns, and UCEs) gave what we consider our most reliable species tree when using the concatenation-based ExaML algorithm or when using statistical binning with the coalescence-based MP-EST algorithm (which we refer to as MP-EST*). Other data sets, such as the coding sequence of some exons, revealed other properties of genome evolution, namely convergence.
The Avian Phylogenomics Project is the largest vertebrate phylogenomics project to date that we are aware of. The sequence, alignment, and tree data are expected to accelerate analyses in phylogenomics and other related areas.
Here we present FASTA files of loci, sequence alignments, indels, transposable elements, and Newick files of gene trees and species trees used in the Avian Phylogenomics Project [1-4]. We also include scripts used to process the data. The 48 species from which we collected these data span the phylogeny of modern birds, including representatives of all Neognathae (Neoaves and Galloanseres) and two of the five Palaeognathae orders (Table 1) [5-7].
Explanation of various data sets used to infer gene and species trees
Here we describe each locus data set in brief. Additional details are provided in Jarvis et al. .
8295 protein-coding exon gene set
This is an exon-coding sequence data set of 8295 genes based on synteny-defined orthologs we identified and selected from the assembled genomes of chicken and zebra finch [8,9]. We required these loci to be present in at least 42 of the 48 avian species and outgroups, which allowed for missing data due to incomplete assemblies. To be included in the dataset, the exons in each genome assembly had to be 30% or more of the full-length sequence of the chicken or zebra finch ortholog. Annotated untranslated regions (UTRs) were trimmed off to remove non-coding sequence, in order to infer a coding-only sequence phylogeny. We note that 44 genes were identified with various problems such as gene annotation issues, and we removed them in the phylogenetic analyses. However, we provide them here in the unfiltered alignments.
8295 protein amino acid alignment set
These are alignments of the translated peptide sequences for the 8295 protein-coding gene data set.
2516 intron gene set
This is an orthologous subset of introns from the 8295 protein-coding genes among 52 species (includes outgroups). Introns with conserved annotated exon-intron boundaries between chicken and another species (±1 codon) were chosen. We filtered out introns with length < 50 bp or intron length ratio > 1.5 between chicken and another species or another species and chicken. This filtering resulted in a conservative subset of introns that could be reliably identified and aligned.
3679 UCE locus set
This is the ultraconserved element (UCE) data set with 1000 bp flanking sequence at the 3′ and 5′ ends. The UCE dataset was filtered to remove overlap with the above exon and intron data sets, other exons and introns in the chicken genome assembly version 3, and overlapping sequences among the UCEs. The source UCE sequences used to search the genomes were determined from sequence capture probes [10-12] aligned to each avian genome assembly. Unlike the exon and intron data sets, we required that all 42 avian species and the alligator outgroup contain the UCEs. We found this requirement to be sufficient, because the central portions of UCEs are highly conserved across all species.
High and low variance introns and exons
These four data sets represent the 10% subsets of the 8295 exons and their associated introns when available (i.e. from the same genes) that had the highest and lowest variance in GC3 (third codon position) content across species. To calculate GC3 variance, we first calculated GC3 for each ortholog in each species, and then we used the correlation coefficient R to calculate variance in GC3 for each species. Orthologs were ranked by their GC3 variance and we selected the top and bottom 10% for analyses.
These are the concatenated sets of loci from various partitions of the TENT dataset (exons, introns, and UCEs described above), brought together using the statistical binning approach. The statistical binning approach put together sets of loci that were deemed “combinable”. Two genes were considered combinable if their respective gene trees had no pairs of incompatible branches that had bootstrap support above a 50% threshold. Alignments of genes in the same bin were concatenated to form supergenes, but boundaries of genes were kept so that a gene-partitioned phylogenetic analysis could be performed on each supergene.
Whole genome alignment
Whole genome alignments were first created by a LASTZ + MULTIZ alignment [13,14] (http://www.bx.psu.edu/miller_lab/) across all 48 bird species and outgroups using individual chromosomes of the chicken genome as the reference (initial alignment 392,719,329 Mb). They were filtered for segments with fewer than 42 avian species (>5 missing bird species) and aberrant sequence alignments. The individual remaining segments of the MULTIZ alignment were realigned with MAFFT. We did not use SATé + MAFFT due to computational challenges (too much input/output was required).
5.7 million insertions and deletions (indels) were scored as binary characters locus by locus from the same intron, exon, and UCE alignments as used in the TENT data set on the principle of simple indel coding using 2Xread [15,16] and then concatenated. Coding was verified using GapCoder  and by visual inspection of alignments for a small subset of data. Intron indels were scored on alignments that excluded non-avian outgroups (48 taxa), UCE indels were scored on alignments that included Alligator (49 taxa), and exons were scored on alignments that included all non-avian outgroups (52 taxa). Individual introns of the same gene were scored independently to avoid creating artifactual indels between concatenated intron or whole genome segments, whereas exons were concatenated as complete unigenes before scoring. For exons, indels >30 bp were excluded to avoid scoring missing exons as indels.
Transposable element markers
These are 61 manually curated presence/absence loci of transposable elements (TEs) present in the Barn Owl genome that exhibit presence at orthologous positions in one or more of the other avian species. The TE markers were identified by eye after a computational screening of 3,671 TguLTR5d retroposon insertions from the Barn Owl. For each TguLTR5d locus, we conducted BLASTn searches of TE-flanking sequences (1 kb per flank) against the remaining avian species and generated multispecies sequence alignments using MAFFT . Redundant or potentially paralogous loci were excluded from analysis and the remaining marker candidates were carefully inspected using strict standard criteria for assigning presence/absence character states [19-21].
FASTA files of loci datasets in alignments
We provide the above loci data sets as FASTA files of both unfiltered and filtered sequence alignments. The alignments were filtered for aberrant over- and under-aligned sequences, and for the presence of the loci in 42 of the 48 avian species. All multiple sequence alignments were performed in two rounds. The first round was used to find contiguous portions of sequences that we identified as aberrant, and the second round was used to realign the filtered sequences. We used SATé [22,23] combined with either MAFFT  or PRANK  alignment algorithms, depending on the limitations of working with large datasets. Alignments without and with outgroups are made available.
Filtered loci sequence alignments
Exon loci alignments
These are filtered alignments of exons from 8295 genes. Of these 8295, there were 42 genes that were identified to have annotation issues and we removed them from the phylogenetic analyses (the list is provided in the file FASTA_files_of_loci_datasets/Filtered_sequence_alignments/8295_Exons/42-exon-genes-removed.txt). Two more genes were removed because a gene tree could not be estimated for them. The first round of alignment was performed using SATé + PRANK, and the second round was performed using SATé + MAFFT. Before alignment, the nucleotide sequences were converted to amino acid sequences, and then reverted back to nucleotide sequences afterwards.
42-exon-genes-removed.txt: list of 42 genes removed due to various issues
pep2cds-filtered-sate-alignments-noout.tar.gz: DNA alignments (Amino acid alignments translated to DNA) without outgroups
pep2cds-filtered-sate-alignments-original.zip: DNA alignments (Amino acid alignments translated to DNA) with outgroups included
8295 Amino Acids
pep-filtered-sate-alignments-noout.tar.gz: Amino acid alignments with outgroups removed
pep-filtered-sate-alignments-original.zip: Amino acid alignments with outgroups included
Intron loci alignments
These are filtered alignments of introns from 2516 genes. Both rounds of alignment were performed using SATé + MAFFT, because SATé + PRANK was too computationally expensive on long introns.
introns-filtered-sate-alignments-with-and-without-outgroups.tar.gz: Includes both alignments with and without outgroups
UCE loci alignments
These are alignments of UCEs and their surrounding 1000 bp from 3769 loci after filtering. Both rounds of alignment were performed using SATé + MAFFT.
3769 UCE + 1000 flanking bp
uce-probes-used.fasta.gz: Probes targeting UCE loci shared among vertebrate taxa.
uce-raw-lastz-results-of-probe-matches.tar: LASTZ results of mapping probes onto genome assemblies.
uce-assembled-loci-from-probe-matches.tar: UCE loci assembled from probe + flank slices from each genome.
uce-filtered-alignments-w-gator.tar.gz: UCE individual alignments without outgroups
uce-filtered-alignments-without-gator.tar.gz: UCE individual alignments with outgroups
Supergenes generated from statistical binning
These are concatenated alignments for each of our 2022 supergene alignments. We note that although supergenes are concatenated loci, we estimated supergene trees using partitioned analyses where each gene was put in a different partition. Thus, we also provide the boundaries between genes in text files (these can be directly used as partition input files to RAxML).
supergene-alignments.tar.bz2: supergene alignments with partition files showing genes put in each bin and their boundaries in the concatenated alignment
Unfiltered loci sequence alignments
These are individual loci alignments of the above data sets, before filtering.
pep-unfiltered-alignments-original.zip: unfiltered SATé + Prank alignments used for the filtering step
pep2cds-unfiltered-alignemtns-original.zip: unfiltered SATé + Prank alignments used for the filtering step
introns-unfiltered-alignments-original.zip: intron SATé alignments before filtering with outgroups included
introns-unfiltered-alignments-noout.zip: intron SATé alignments before filtering with outgroups included
uce-unfiltered-alignments-w-gator.tar.gz: UCE alignments before filtering with alligator outgroup
Concatenated c12 (1st + 2nd codons) DNA sequence alignments from the 1156 clocklike genes were used for the dating analyses. These are alignments of the first and second codon positions of clock-like genes among the 8295 exon orthologs:
High and low variance exons and their associated introns
High variance exons:
Low variance exons:
High variance introns: These are heterogenous introns
Low variance introns: These are homogenous introns
Indel sequence alignments
This is a concatenated alignment of indels from exons, introns, and UCEs. A README file describes the content.
Transposable element markers
Species and gene tree files
Species trees (Newick format) were generated with either RAxML, an improved ExaML version for handling large alignments, or MP-EST* . We deposit both the maximum likelihood and bootstrap replicate trees.
Newick files for 32 species trees using different genomic partitions and methods
TENT + c3.ExaML.tre
TENT + outgroup.ExaML.tre
Newick files of the 11 timetrees (chronograms)
Newick file downloads of gene trees (species abbreviated with 5-letter names)
ML (bestML) gene trees
Bootstrap replicates of ML gene trees
ML (bestML) supergene trees used in MP-EST analyses
Bootstrap replicates of supergene trees used in MP-EST analyses
Partition files showing which loci make up which bins for MP-EST analyses
List of scripts used in avian phylogenomics project
We also deposit the key scripts used in this project in GigaDB, which include:
Script for filtering amino acid alignments
Script for filtering nucleotide sequence alignments
Script for mapping names from 5-letter codes to full names
Scripts related to indel analyses
We provide readme files in the script directories describing the usage of the scripts.
A Stamatakis, AJ Aberer. Novel parallelization schemes for large-scale likelihood-based phylogenetic inference. IEEE 27th International Symposium on Parallel and Distributed Processing, 1195–1204. 2013
Mirarab S, Bayzid MS, Boussau B, Warnow T. Statistical binning enables an accurate coalescent-based estimation of the avian tree. Science. 2014;346(6215):1–9.
Hillier LW, Miller W, Birney E, Warren W, Hardison RD, Ponting CP, et al. Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature. 2004;432:695–716.
Zhang G, Li B, Li C, Gilbert MTP, Jarvis ED, Wang J. The Avian genome Consortium, Wang J: Comparative genomic data of the Avian Phylogenomics Project. GigaSci Database 2014, http://dx.doi.org/10.5524/101000
Jarvis ED, Mirarab S, Aberer A, Houde P, Li C, Ho S, et al. Phylogenomic analyses data of the avian phylogenomics project. GigaScience Database. 2014. http://dx.doi.org/10.5524/101041
The majority of genome sequencing and annotation was supported by internal funding from BGI. Additional significant support is from the coordinators of the project: E.D.J. from the Howard Hughes Medical Institute (HHMI) and NIH Directors Pioneer Award DP1OD000448. S.M. from an HHMI International Student Fellowship. G.Z. from Marie Curie International Incoming Fellowship grant (300837); T.W. from NSF DEB 0733029, NSF DBI 1062335, NSF IR/D program; and M.T.P.G. from a Danish National Research Foundation grant (DNRF94) and a Lundbeck Foundation grant (R52-A5062).
We thank the following Centers that allowed us to conduct the computationally intensive analyses for this study: Heidelberg Institute for Theoretical Studies (HITS); San Diego Supercomputer Center (SDSC), with support by an NSF grant; SuperMUC Petascale System at the Leibniz Supercomputing Center; Technical University of Denmark (DTU); Texas Advanced Computing Center (TACC); Georgia Advanced Computing Resource Center (GACRC), a partnership between the University of Georgia’s Office of the Vice President for Research and Office of the Vice President for Information Technology; Amazon Web Services (AWS); BGI; Nautilus supercomputer at the National Institute for Computational Sciences of the University of Tennessee and Smithsonian; and Duke University Institute for Genome Sciences and Policy.
The full author list of The Avian Phylogenomics Consortium is provided at the end of the data note.
Authors and Affiliations
Department of Neurobiology, Howard Hughes Medical Institute and Duke University Medical Center, Durham, NC, 27710, USA
Erich D Jarvis & Jason T Howard
Department of Computer Science, The University of Texas at Austin, Austin, TX, 78712, USA
Siavash Mirarab & Tandy Warnow
Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
Andre J Aberer & Alexandros Stamatakis
China National GeneBank, BGI-Shenzhen, Shenzhen, 518083, China
Bo Li, Cai Li, Wang Jun & Guojie Zhang
College of Medicine and Forensics, Xi’an Jiaotong University, Xi’an, 710061, China
Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
Bo Li, Cai Li, Rute R da Fonseca, Alonzo Alfaro-Núñez & M Thomas Pius Gilbert
Department of Biology, New Mexico State University, Las Cruces, NM, 88003, USA
Peter Houde & Nitish Narula
School of Biological Sciences, University of Sydney, Sydney, NSW, 2006, Australia
Simon Y W Ho
Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
Brant C Faircloth
Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, 70803, USA
Brant C Faircloth
CNRS UMR 5554, Institut des Sciences de l’Evolution de Montpellier, Université Montpellier II, Montpellier, France
Department of Evolutionary Biology, Uppsala University, SE-752 36, Uppsala, Sweden
Alexander Suh, Claudia C Weber & Hans Ellegren
Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Onna-son, Okinawa, 904-0495, Japan
Department of Statistics and Institute of Bioinformatics, University of Georgia, Athens, 30602, USA
Department of Genomics and Genetics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA
Scott V Edwards
Institute of Theoretical Informatics, Department of Informatics, Karlsruhe Institute of Technology, D- 76131, Karlsruhe, Germany
Department of Biochemistry & Biophysics, University of California, San Francisco, CA, 94158, USA
David P Mindell
Department of Ornithology, American Museum of Natural History, New York, NY, 10024, USA
Department of Biology and Genetics Institute, University of Florida, Gainesville, FL, 32611, USA
Edward L Braun
Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
Macau University of Science and Technology, Avenida Wai long, Taipa, Macau, 999078, China
Department of Medicine, University of Hong Kong, Hong Kong, Hong Kong
Trace and Environmental DNA Laboratory Department of Environment and Agriculture, Curtin University, Perth, WA, 6102, Australia
M Thomas Pius Gilbert
Centre for Social Evolution, Department of Biology, Universitetsparken 15, University of Copenhagen, DK-2100, Copenhagen, Denmark
The authors declare that they have no competing interests.
Coordinated the project EDJ, TW, MTPG, and GZ; Wrote the paper and co-supervised the project EDJ, SM, AJA, PH, TW, MTPG, GZ, ELB, JC, SE, ASt, DPM; Sample coordination and collections JH, EDJ, MTPG, AAN; Alignments SM, AJA, TW, ASt, RdF, MTPG, CL, GZ, BCF, EDJ; Species trees and gene trees AA, SM, ASt, BCF, TW, CL, CCW; Indels PH, NN, AJA; Transposable Elements ASu, HE; Fossil-calibrated chronograms SYWH, PH, MTPG, JC, DM, SE. The contribution information for all authors is provided in Additional file 1. All authors read and approved the final manuscript.
Erich D Jarvis and Siavash Mirarab contributed equally to this work.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.