Skip to main content
NCBI home page
GigaScience logoLink to GigaScience
. 2014 Dec 11;3:26. doi: 10.1186/2047-217X-3-26

Comparative genomic data of the Avian Phylogenomics Project

Guojie Zhang 1,2,✉, Bo Li 1, Cai Li 1,3, M Thomas P Gilbert 3,4,✉, Erich D Jarvis 5,✉, Jun Wang 1,6,7,8,9,✉; The Avian Genome Consortium
PMCID: PMC4322804  PMID: 25671091

Abstract

Background

The evolutionary relationships of modern birds are among the most challenging to understand in systematic biology and have been debated for centuries. 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, and used the genomes to construct a genome-scale avian phylogenetic tree and perform comparative genomics analyses (Jarvis et al. in press; Zhang et al. in press). Here we release assemblies and datasets associated with the comparative genome analyses, which include 38 newly sequenced avian genomes plus previously released or simultaneously released genomes of Chicken, Zebra finch, Turkey, Pigeon, Peregrine falcon, Duck, Budgerigar, Adelie penguin, Emperor penguin and the Medium Ground Finch. We hope that this resource will serve future efforts in phylogenomics and comparative genomics.

Findings

The 38 bird genomes were sequenced using the Illumina HiSeq 2000 platform and assembled using a whole genome shotgun strategy. The 48 genomes were categorized into two groups according to the N50 scaffold size of the assemblies: a high depth group comprising 23 species sequenced at high coverage (>50X) with multiple insert size libraries resulting in N50 scaffold sizes greater than 1 Mb (except the White-throated Tinamou and Bald Eagle); and a low depth group comprising 25 species sequenced at a low coverage (~30X) with two insert size libraries resulting in an average N50 scaffold size of about 50 kb. Repetitive elements comprised 4%-22% of the bird genomes. The assembled scaffolds allowed the homology-based annotation of 13,000 ~ 17000 protein coding genes in each avian genome relative to chicken, zebra finch and human, as well as comparative and sequence conservation analyses.

Conclusions

Here we release full genome assemblies of 38 newly sequenced avian species, link genome assembly downloads for the 7 of the remaining 10 species, and provide a guideline of genomic data that has been generated and used in our Avian Phylogenomics Project. To the best of our knowledge, the Avian Phylogenomics Project is the biggest vertebrate comparative genomics project to date. The genomic data presented here is expected to accelerate further analyses in many fields, including phylogenetics, comparative genomics, evolution, neurobiology, development biology, and other related areas.

Electronic supplementary material

The online version of this article (doi:10.1186/2047-217X-3-26) contains supplementary material, which is available to authorized users.

Keywords: Avian genomes, Phylogenomics, Whole genome sequencing

Data description

Here we presented the genomes of 48 bird species, representing 36 orders of birds, including all Neognathae and two of the five Palaeognathae orders, collected by the Avian Genome Consortium ( [1], full author list of the Consortium provided in Additional file 1 and data in GigaDB [2]). The Chicken, Zebra finch, and Turkey genomes (sequenced using the Sanger method) were collected from the public domain. Another three genomes, the Pigeon, Peregrine Falcon and Duck, have been published during the development of this project [3–5], and five genomes, the Budgerigar, Crested Ibis, Little Egret, Emperor and Adele penguins, are reported in companion studies of this project [6, 7]. The data downloads for the remaining 38 genomes are released here.

Genome sequencing

Tissue samples were collected from multiple sources, with the largest contributions from the Copenhagen Zoo (Denmark) and the Louisiana State University (USA). Most DNA samples were processed and quality control performed at the University of Copenhagen (Dr. Gilbert’s lab, Denmark) and Duke University (Dr. Jarvis’ lab, USA). The collected samples were then used for constructing pair-end libraries and sequenced using Illumina HiSeq 2000 platforms at the BGI (China). For the high-coverage birds, multiple pair-end libraries with a series of up to 9 insert sizes (170 bp, 500 bp, 800 bp, 2 kb, 5 kb, 10 kb and 20 kb) were constructed for each species, as part the first 100 species of the G10K project. For four birds (Anas platyrhynchos, Picoides pubescens, Ophisthocomus hoazin and Tinamus guttatus), libraries of some insert sizes were not constructed due to limited sample amounts or the sequencing strategies applied to those species. In addition, for the budgerigar genome, Roche 454 longer reads of multiple insert sizes were used [6]. For the low-coverage genomes, libraries of two insert sizes (500 bp and 800 bp) were constructed. The sequencing depths for high-coverage genomes were 50X to 160X, whereas the sequencing depths for low-coverage genomes were 24X to 39X. An effort was made to obtain DNA samples from tissues with associated museum voucher specimens with high quality metadata.

Genome assembly

Before assembly, several quality control steps were performed to filter the low-quality raw reads. The clean reads of each bird were then passed to SOAPdenovo v1.05 [8] for de novo genome assembly. We tried different k-mers (from 23-mer to 33-mer) to construct contigs and chose the k-mer with the largest N50 contig length. In addition, we also tried different cut-offs of read pairs for different libraries to link contigs into scaffolds. The assembly with the largest N50 length was finally used.

All the assemblies have similar genome sizes, ranging from 1.04-1.26Gb (Table  1). The high-coverage genomes have a N50 scaffold length of >1 Mb, except for the White-throated Tinamou (Tinamous guttatus) with a scaffold N50 of 242 Kb and Bald Eagle (Haliaeetus leucocephalus) with a scaffold N50 of 670 Kb, due to no 10 kb and 20 kb libraries for these two genomes. For low-coverage genomes, the scaffold N50 lengths ranged from 30 kb to 64 kb. The N50 contig lengths for high-coverage genomes were from 19 kb to 55 kb, and the low coverage genomes were from 12 kb to 20 kb. The Parrot and Ostrich genomes were further assembled with the aid of optical mapping data, thus achieving much larger scaffold N50 sizes.

Table 1.

Basic statistics for the assemblies of avian species

Species Common name Sequencing depth Library Assembly (contig/scaffold N50;total length)
Published (Sanger sequencing)
Gallus gallus Chicken 7X - 36 K/7.07 M;1.05G
Taeniopygia guttata Zebra finch 6X - 39 K/10 M;1.2G
Meleagris gallopavo Turkey 17X - 12.6 K/1.5 M;1.04G
High - coverage genomes
Anas platyrhynchos domestica Peking duck 50X 200,500,2 k,5 k,10 k 26 K/1.2 M;1.1G
Columba livia Pigeon 63X 200,500,800,2 k,5 k,10 k,20 k 22 K/3.2 M;1.11G
Falco peregrinus Peregrine falcon 105X 200,500,800,2 k,5 k,10 k,20 k 28 K/3.9 M;1.18G
Pygoscelis adeliae Adelie penguin 60X 200,500,800,2 k,5 k,10 k,20 k 19 K/5.0 M;1.23G
Aptenodytes forsteri Emperor penguin 60X 200,500,2 k,5 k,10 k,20 k 30 K/5.1 M;1.26G
Nipponia nippon Crested ibis 105X 200,500,800,2 k,5 k,10 k,20 k 22 K/5.4 M;1.17G
Egretta garzetta Little egret 74X 200,500,800,2 k,5 k,10 k,20 k 24 K/3.1 M;1.2G
Calypte anna Anna's hummingbird 110X 200,500,800,2 k,5 k,10 k,20 k 23 K/4 M;1.1G
Chaetura pelagica Chimney swift 103X 200,500,800,2 k,5 k,10 k,20 k 27 K/3.8 M;1.1G
Charadrius vociferus Killdeer 100X 200,500,800,2 k,5 k,10 k,20 k 32 K/3.6 M;1.2G
Cuculus canorus Common cuckoo 100X 200,500,800,2 k,5 k,10 k,20 k 31 K/3 M;1.15G
Ophisthocomus hoazin Hoatzin 100X 200,500,800,2 k,5 k,10 k 24 K/2.9 M;1.14G
Geospiza fortis Medium ground finch 115X 200,500,800,2 k,5 k,10 k,20 k 30 K/5.2 M;1.07G
Manacus vitellinus Golden-collared manakin 110X 200,500,800,2 k,5 k,10 k,20 k 34 K/2.5 M;1.12G
Melopsittacus undulatus Budgerigar 160X 200, 500, 800, 2 k, 5 k, 10 k 55 K/10.6 M;1.1G
Picoides pubescens Downy woodpecker 105X 200,500,800,2 k,5 k,10 k 20 K/2 M;1.17G
Struthio camelus Ostrich 85X 200,500,800,2 k,5 k,10 k,20 k 29 K/3.5 M;1.23G
Tinamus guttatus White-throated tinamou 100X 200,500,800,2 k,5 k 24 K/242 K;1.05G
Corvus brachyrhynchos American crow 80X 200,500,800,2 k,5 k,10 k,20 k 24 K/6.9 M;1.1G
Haliaeetus leucocephalus Bald eagle 88X 300,400,3 k,8 k 10 K/670 K;1.26G
Low - coverage genomes
Antrostomus carolinensis Chuck-will's-widow 30X 500, 800 17 K/45 K;1.15G
Cariama cristata Red-legged seriema 24X 500, 800 17 K/54 K;1.15G
Colius striatus Speckled mousebird 27X 500, 800 18 K/45 k;1.08G
Merops nubicus Carmine bee-eater 37X 500, 800 20 K/47 K;1.06G
Gavia stellata Red-throated loon 33X 500, 800 16 K/45 K;1.15G
Balearica regulorum Grey-crowned crane 33X 500, 800 18 K/51 K;1.14G
Apaloderma vittatum Bar-tailed trogon 28X 500, 800 19 K/56 K;1.08G
Phalacrocorax carbo Great cormorant 24X 500, 800 15 K/48 K;1.15G
Phaethon lepturus White-tailed tropicbird 39X 500, 800 18 K/47 K;1.16G
Phoenicopterus ruber ruber American flamingo 33X 500, 800 16 K/37 K;1.14G
Podiceps cristatus Great-crested grebe 30X 500, 800 13 K/30 K;1.15G
Fulmarus glacialis Northern fulmar 33X 500, 800 17 K/46 K;1.14G
Tyto alba Barn owl 27X 500, 800 13 K/51 K;1.14G
Tauraco erythrolophus Red-crested turaco 30X 500, 800 18 K/55 K;1.17G
Cathartes aura Turkey vulture 25X 500, 800 12 K/35 K;1.17G
Eurypyga helias Sunbittern 33X 500, 800 16 K/46 K;1.1G
Mesitornis unicolor Brown mesite 29X 500, 800 18 K/46 K;1.1G
Leptosomus discolor Cuckoo-roller 32X 200, 500, 800 19 K/61 K;1.15G
Chlamydotis macqueenii MacQueen's Bustard 27X 500, 800 18 K/45 K;1.09G
Pelecanus crispus Dalmatian pelican 34X 500, 800 18 K/43 K;1.17G
Pterocles gutturalis Yellow-thoated sandgrouse 25X 500, 800 17 K/49 K;1.07G
Acanthisitta chloris Rifleman 29X 500, 800 18 K/64 K;1.05G
Buceros rhinoceros Rhinoceros hornbill 35X 500, 800 14 K/51 K;1.08G
Nestor notabilis Kea 32X 500, 800 16 K/37 K;1.14G
Haliaeetus albicilla White-tailed eagle 26X 500, 800 20 K/56 K;1.14G
Open in a new tab

Repeat annotation

RepeatMasker [9] and RepeatModeler [10] were used to perform repeat annotations for the bird genomes. The overall annotated content of transposable elements (TE) range from within 2-9% of all bird genomes except Woodpecker (Table  2). These TEs include long interspersed nuclear elements [LINEs], short interspersed nuclear elements [SINEs], long-terminal repeat [LTR] elements and DNA transposons). The exception Woodpecker genome has a TE content of 22%, which reflects a larger number of LINE CR1 elements (18% of the genome).

Table 2.

Percentages of genome annotated as transposable elements (TEs)

Species LINE SINE LTR DNA RC Unknown Total
Merops nubicus 5.01 0.07 1.30 0.14 0.01 1.26 7.78
Picoides pubescens 18.20 0.05 0.89 0.17 0.00 2.84 22.15
Buceros rhinoceros 3.62 0.08 1.05 0.16 0.01 1.09 6.00
Apaloderma vittatum 5.97 0.12 1.31 0.23 0.01 0.82 8.44
Leptosomus discolor 2.93 0.12 1.32 0.19 0.01 1.88 6.45
Colius striatus 6.54 0.10 2.19 0.19 0.00 0.39 9.42
Haliaeetus albicilla 2.55 0.14 1.71 0.19 0.01 0.77 5.37
Haliaeetus leucocephalus 2.01 0.17 1.89 0.22 0.00 2.59 6.89
Cathartes aura 2.21 0.17 1.05 0.19 0.00 0.92 4.54
Tyto alba 2.64 0.13 1.79 0.19 0.01 0.74 5.49
Geospiza fortis 3.65 0.06 3.37 0.31 0.04 0.80 8.23
Taeniopygia guttata 3.79 0.06 4.11 0.32 0.02 1.39 9.68
Corvus brachyrhynchos 3.73 0.07 2.43 0.22 0.02 0.90 7.37
Manacus vitellinus 4.43 0.08 1.08 0.25 0.01 0.72 6.58
Acanthisitta chloris 6.38 0.10 1.46 0.21 0.01 0.56 8.72
Melopsittacus undulatus 6.49 0.08 1.97 0.20 0.01 0.45 9.19
Nestor notabilis 4.60 0.10 1.32 0.18 0.00 0.37 6.57
Falco peregrinus 3.09 0.15 1.27 0.28 0.00 0.71 5.50
Cariama cristata 3.51 0.18 0.91 0.20 0.00 0.69 5.49
Egretta garzetta 3.92 0.12 1.42 0.24 0.01 1.22 6.93
Pelecanus crispus 3.94 0.15 1.87 0.21 0.01 1.27 7.45
Nipponia nippon 3.69 0.13 1.22 0.29 0.01 0.83 6.16
Phalacrocorax carbo 3.95 0.16 1.29 0.21 0.00 0.62 6.23
Aptenodytes forsteri 2.41 0.20 1.17 0.26 0.00 1.46 5.50
Pygoscelis adeliae 3.31 0.20 1.32 0.26 0.00 0.95 6.04
Fulmarus glacialis 2.86 0.18 1.19 0.22 0.01 0.87 5.32
Gavia stellata 3.17 0.14 0.71 0.22 0.01 0.85 5.09
Eurypyga helias 4.61 0.10 1.60 0.15 0.00 0.46 6.92
Phaethon lepturus 3.91 0.12 1.71 0.22 0.00 1.48 7.44
Ophisthocomus hoazin 4.69 0.11 1.30 0.16 0.01 1.63 7.90
Balearica regulorum 3.35 0.14 1.51 0.24 0.01 0.83 6.08
Charadrius vociferus 4.53 0.13 1.12 0.20 0.01 1.05 7.03
Calypte anna 5.62 0.07 1.23 0.21 0.01 0.91 8.05
Chaetura pelagica 5.28 0.11 0.90 0.19 0.00 2.57 9.05
Antrostomus carolinensis 5.40 0.12 1.84 0.33 0.02 0.53 8.24
Chlamydotis macqueenii 3.97 0.17 1.40 0.23 0.00 0.57 6.35
Tauraco erythrolophus 2.76 0.09 1.80 0.16 0.01 3.83 8.64
Cuculus canorus 7.84 0.08 0.67 0.27 0.01 0.58 9.45
Mesitornis unicolor 4.62 0.09 1.38 0.38 0.01 1.03 7.51
Pterocles gutturalis 3.46 0.09 1.36 0.17 0.01 0.67 5.75
Columba livia 4.18 0.09 0.76 0.35 0.01 1.87 7.25
Phoenicopterus ruber 2.69 0.15 1.04 0.23 0.01 1.49 5.60
Podiceps cristatus 4.80 0.10 1.60 0.20 0.01 0.60 7.31
Gallus gallus 6.01 0.08 1.65 1.01 0.01 1.07 9.82
Meleagris gallopavo 5.40 0.05 1.11 0.82 0.00 0.52 7.90
Anas platyrhynchos 4.05 0.10 1.10 0.20 0.01 0.39 5.85
Struthio camelus 2.88 0.18 0.17 0.36 0.01 0.90 4.49
Tinamus guttatus 2.73 0.09 0.30 0.33 0.01 0.65 4.11
Open in a new tab

Protein-coding gene annotation

We used the homology-based method to annotate genes, with gene sets of chicken, zebra finch and human in Ensembl release 60 [11]. Because the quality of homology-based prediction strongly depends on the quality of the reference gene sets, we carefully chose the reference genes for the annotation pipeline. The protein sequences of these three species were compiled and used as a reference gene set template for homology-based gene predictions for the newly assembled bird genomes. We aligned protein sequences of the reference gene set to each genome by TBLASTN and used Genewise [12] to predict gene models in the genomes. A full description of the homology-based annotations is in our comparative genomics paper [1]. All the avian genomes have similar coding DNA sequence (CDS), exon, and intron lengths (Table  3).

Table 3.

Statistics of protein-coding gene annotations of all the birds

Species Gene number Mean gene length (kb) Mean CDS length (bp) Mean exon length (bp) Mean intron length (bp) Mean intergenic length (kb)
Acanthisitta chloris 14596 13.5 1242 158.6 1800 12
Anas platyrhynchos domestica 16521 17.8 1317 160.7 2298 42
Antrostomus carolinensis 14676 12.0 1177 164.1 1747 12
Apaloderma vittatum 13615 13.5 1247 160.8 1806 12
Aptenodytes forsteri 16070 20.9 1397 161.6 2546 56
Balearica regulorum 14173 13.8 1276 162.7 1828 11
Buceros rhinoceros 13873 13.5 1267 160.4 1767 11
Calypte anna 16000 18.5 1386 161.7 2264 47
Cariama cristata 14216 13.7 1249 161.8 1849 11
Cathartes aura 13534 10.8 1109 166.4 1716 10
Chaetura pelagica 15373 19.8 1411 161.0 2364 51
Charadrius vociferus 16860 19.1 1324 161.8 2482 52
Chlamydotis macqueenii 13582 12.9 1257 162.9 1734 10
Colius striatus 13538 12.4 1190 161.1 1754 11
Columba livia 16652 18.3 1363 161.0 2277 46
Corvus brachyrhynchos 16562 17.9 1363 161.1 2220 48
Cuculus canorus 15889 20.0 1400 160.7 2413 48
Egretta garzetta 16585 18.6 1274 160.7 2496 52
Eurypyga helias 13974 12.3 1193 163.9 1763 11
Falco peregrinus 16242 19.9 1403 160.7 2389 49
Fulmarus glacialis 14306 12.8 1230 163.0 1765 11
Gallus gallus 16516 21.1 1433 158.1 2437 48
Gavia stellata 13454 13.2 1250 162.1 1776 11
Geospiza fortis 16286 17.9 1362 160.1 2198 46
Haliaeetus albicilla 13831 14.2 1258 161.1 1903 12
Haliaeetus leucocephalus 16526 19.0 1359 160.7 2370 36
Leptosomus discolor 14831 13.9 1236 163.2 1926 14
Manacus vitellinus 15285 18.8 1392 159.7 2262 46
Meleagris gallopavo 16051 17.4 1305 158.0 2215 52
Melopsittacus undulatus 15470 19.8 1395 162.2 2415 52
Merops nubicus 13467 13.0 1224 162.1 1798 11
Mesitornis unicolor 15371 11.4 1169 163.6 1666 11
Nestor notabilis 14074 14.4 1307 160.1 1822 12
Nipponia nippon 16756 19.4 1358 161.2 2434 51
Ophisthocomus hoazin 15702 20.0 1336 162.1 2582 55
Pelecanus crispus 14813 11.9 1183 164.8 1740 11
Phaethon lepturus 14970 12.7 1220 163.9 1781 11
Phalacrocorax carbo 13479 13.5 1258 162.0 1810 11
Phoenicopterus ruber 14024 11.7 1179 165.3 1716 10
Picoides pubescens 15576 20.0 1390 161.7 2450 47
Podiceps cristatus 13913 10.4 1137 165.8 1583 8
Pterocles gutturalis 13867 12.8 1235 162.5 1757 11
Pygoscelis adeliae 15270 21.3 1392 160.3 2589 58
Struthio camelus 16178 19.5 1289 161.0 2601 54
Taeniopygia guttata 17471 21.4 1383 153.5 2493 53
Tauraco erythrolophus 15435 13.2 1200 164.0 1894 12
Tinamus guttatus 15788 14.7 1288 162.0 1934 25
Tyto alba 13613 13.8 1240 160.8 1871 12
Open in a new tab

Syntenic-based orthlogous annotation

To obtain more accurate orthology annotations for phylogenetic analyses in [13], we re-annotated some genes of the Chicken and Zebra Finch based on synteny, thereby correcting errors in the annotations due to being annotated independently with different methods. We first ran bi-directional BLAST to recognize the reciprocal best hits (considered as pairwise orthologs) between our re-annotated chicken genome and each of the other genomes. Then we identified syntenic blocks by using pairwise orthologs as anchors. We only kept the pairwise orthologs with syntenic support. In addition, we also considered the genomic syntenic information inferred from the LASTZ genome alignments, and removed pairwise orthologs without genomic syntenic support. After the above filtering, all the remaining pairwise orthologs were combined into a merged list by using a chicken gene set as a reference. We also required each orthologous group to have members in at least 42 out of 48 avian species. Ultimately, we obtained a list of 8295 syntenic-based orthologs. We used the same methods to generate 12815 syntenic-based orthologs of 24 mammalian species. A full description of the synteny-based annotations is found in our phylogenomics paper [13].

Sequence alignments

Protein coding gene alignment

CDS alignments for all orthologous genes were obtained by two rounds of alignments. In order to preserve the reading frames of CDS, we aligned the amino acid sequences and then back translated them into DNA alignments. In the first round of alignment, SATé-Prank [14] was employed to obtain the initial alignments, which were used to identify the aberrant over-aligned and under-aligned sequences. The aberrant sequences were then removed, and the second round of alignment were performed by SATé-MAFFT [14] for the filtered sequences to create the final multiple sequence alignments. The default JTT model inside SATé [14] was used as we found it to fit the data best for most genes. We also used the same method to generate the alignments of mammalian orthologs. More details of the alignment are presented in Jarvis et al. [13].

Whole genome alignment

Whole genome alignments are very useful for comparative analyses, so we generated a multiple genome alignment of all 48 bird species. Firstly, pairwise alignments for each two genomes (with repeats masked) were produced by LASTZ [15], using chicken as the reference genome. Next chainNet [16] was introduced to obtain improved pairwise alignments. Finally, we used MULTIZ [17] to merge the pairwise alignments into multiple genome alignments. Approximately 400 Mb of each avian genome made it into the final alignment result. Thereafter, the alignment was filtered for over- and under-aligned errors, and for presence in 42 of 48 avian species. The resultant alignment was about 322 Mb, representing about one third of each genome, suggesting a large portion of the genome has been under strong constraints after different bird species diverged from their common ancestor. More details of the alignment are presented in Jarvis et al. [13].

dN/dS estimates

We deposit dN/dS estimates (ratio of non-synonymous versus synonymous substitution rates) of the protein coding genes from Zhang et al. [1]. The dN/dS ratios were estimated by PAML [18] program for the orthologs. Based on the CDS alignment of either protein coding data set, we used the one-ratio branch model to estimate the overall dN/dS ratios for each avian orthologous group and each mammalian orthologous group. In addition, to investigate the evolutionary rates in three major avian clades (Palaeognathae, Galloanserae and Neoaves), we used the three-ratio branch model, which estimated one identical dN/dS ratio for each clade. More details about dN/dS analyses are presented in Zhang et al. [1].

DNA sequence conservation

The overall level of conservation at the single nucleotide level could be estimated by PhastCons [19] based on multiple sequence alignments (MSA). First, the four-fold degenerate sites were extracted from 48-avian MSA and were used to estimate a neutral phylogenetic model by phyloFit [20], which is considered as the non-conserved model in PhastCons; we then ran PhastCons to estimate the conserved model. The conservation scores were predicted based on non-conserved and conserved models. We also used this method to estimate the sequence conservation for the 18-way mammalian genome alignments from the University of California at Santa Cruz (UCSC). Additional details of genome conservation are presented in the comparative genomics paper [1].

List of scripts used in avian comparative genome project

We also deposit the key scripts used in the avian comparative genome project in GigaDB [2], which include: 1) scripts for cleaning raw reads and assembling the genome using SOAPdenovo; 2) scripts for RepeatMasker and RepeatModeler repeat annotation; 3) scripts for homology-based protein-coding gene annotation and combining the gene annotation evidences into final gene sets; 4) scripts for generating whole genome alignment of multiple genomes; 5) scripts for running PAML to estimate branch model dN/dS ratios; 6) scripts for calculating conservation scores based on whole genome alignments and predicting highly conserved elements; 7) scripts for quantifying gene synteny percentages in birds and mammals; 8) scripts for identifying large segmental deletions from list of orthologous genes; 9) scripts for detecting gene loss in 48 avian genomes. We provide readme files in the script directories describing the usage of the scripts.

Availability and requirements

Download page for scripts:

https://github.com/gigascience/paper-zhang2014

Operating system: Linux

Programming language: Perl, R, Python

Other requirements: Some pipelines need external bioinformatics software, for which we provided executable files in the directories.

License: GNU General Public License version 3.0 (GPLv3)

Any restrictions to use by non-academics: No

Availability of supporting data

The NCBI BioProject/SRA/Study IDs for are listed in Additional file 2. Other data files presented in this data note are available in the GigaScience repository, GigaDB [2].

Authors’ information

The full author list of Avian Genome Consortium is provided in Additional file 1.

Electronic supplementary material

13742_2014_55_MOESM1_ESM.xls (85KB, xls)

Additional file 1: Author list of the Avian Genome Consortium and contribution information of each author. (XLS 85 KB)

13742_2014_55_MOESM2_ESM.xls (46.5KB, xls)

Additional file 2: NCBI accession numbers and GigaDB DOI for each bird. (XLS 46 KB)

Acknowledgements

The majority of this study was supported by internal funding from BGI. In addition, G.Z. was supported by a Marie Curie International Incoming Fellowship grant (300837). M.T.P.G. was supported by a Danish National Research Foundation grant (DNRF94) and a Lundbeck Foundation grant (R52-A5062). E.D.J. was supported by the Howard Hughes Medical Institute and NIH Directors Pioneer Award DP1OD000448. C.L. were partially supported by a Danish Council for Independent Research Grant (10–081390).

Abbreviations

CDS

Coding sequence

Gb

Giga base pair

Kb

Kilo base pair

LINE

Long interspersed nuclear elements

MSA

Multiple sequences alignment

TE

Transposable element.

Footnotes

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

The contribution information for all authors is provided in Additional file 1. All authors read and approved the final manuscript.

Contributor Information

Guojie Zhang, Email: zhanggj@genomics.cn.

Bo Li, Email: libo@genomics.cn.

Cai Li, Email: licai@genomics.cn.

M Thomas P Gilbert, Email: mtpgilbert@gmail.com.

Erich D Jarvis, Email: jarvis@neuro.duke.edu.

Jun Wang, Email: wangj@genomics.cn.

References

  • 1.Zhang G, Li C, Li Q, Li B, Larkin DM, Lee C, Storz JF, Antunes A, Greenwold MJ, Meredith RW, Odeen A, Cui J, Zhou Q, Xu L, Pan H, Wang Z, Jin L, Zhang P, Hu H, Yang W, Hu J, Xiao J, Yang Z, Liu Y, Xie Q, Yu H, Lian J, Wen P, Zhang F, Li H, et al. Science. 2014. Comparative Genomics Reveals Insights into Avian Genome Evolution and Adaptation. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Zhang G, Li B, Li C, Gilbert MTP, Jarvis E, Wang J, The Avian Genome Consortium . GigaSci Database. 2014. The avian phylogenomisc project data. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Shapiro MD, Kronenberg Z, Li C, Domyan ET, Pan H, Campbell M, Tan H, Huff CD, Hu H, Vickrey AI, Nielsen SC, Stringham SA, Hu H, Willerslev E, Gilbert MT, Yandell M, Zhang G, Wang J. Genomic diversity and evolution of the head crest in the rock pigeon. Science. 2013;339:1063–1067. doi: 10.1126/science.1230422. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Zhan X, Pan S, Wang J, Dixon A, He J, Muller MG, Ni P, Hu L, Liu Y, Hou H, Chen Y, Xia J, Luo Q, Xu P, Chen Y, Liao S, Cao C, Gao S, Wang Z, Yue Z, Li G, Yin Y, Fox NC, Wang J, Bruford MW. Peregrine and saker falcon genome sequences provide insights into evolution of a predatory lifestyle. Nat Genet. 2013;45:563–566. doi: 10.1038/ng.2588. [DOI] [PubMed] [Google Scholar]
  • 5.Huang Y, Li Y, Burt DW, Chen H, Zhang Y, Qian W, Kim H, Gan S, Zhao Y, Li J, Yi K, Feng H, Zhu P, Li B, Liu Q, Fairley S, Magor KE, Du Z, Hu X, Goodman L, Tafer H, Vignal A, Lee T, Kim KW, Sheng Z, An Y, Searle S, Herrero J, Groenen MA, Crooijmans RP, et al. The duck genome and transcriptome provide insight into an avian influenza virus reservoir species. Nat Genet. 2013;45:776–783. doi: 10.1038/ng.2657. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Ganapathy G, Howard JT, Ward JM, Li J, Li B, Li Y, Xiong Y, Zhang Y, Zhou S, Schwartz DC, Schatz M, Aboukhalil R, Fedrigo O, Bukovnik L, Wang T, Wray G, Rasolonjatovo I, Winer R, Knight JR, Koren S, Warren WC, Zhang G, Phillippy AM, Jarvis ED. High-coverage sequencing and annotated assemblies of the budgerigar genome. Gigascience. 2014;3:11. doi: 10.1186/2047-217X-3-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Li C, Zhang Y, Li J, Kong L, Hu H, Pan H, Xu L, Deng Y, Li Q, Jin L, Yu H, Chen Y, Liu B, Yang L, Liu S, Zhang Y, Lang Y, Xia J, He W, Shi Q, Subramanian S, Millar CD, Meader S, Rands CM, Fujita MK, Greenwold MJ, Castoe TA, Pollock DD, Gu W, Nam K, et al. Two Antarctic penguin genomes reveal insights into their evolutionary history and molecular changes related to the Antarctic environment. GigaScience. 2014;3:27. doi: 10.1186/2047-217X-3-27. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Li R, Zhu H, Ruan J, Qian W, Fang X, Shi Z, Li Y, Li S, Shan G, Kristiansen K, Li S, Yang H, Wang J, Wang J. De novo assembly of human genomes with massively parallel short read sequencing. Genome Res. 2010;20:265–272. doi: 10.1101/gr.097261.109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Smit AFA, Hubley R, Green P. RepeatMasker Open-3.0. 2010. [Google Scholar]
  • 10.Smit AFA, Hubley R. RepeatModeler Open-1.0. 2010. [Google Scholar]
  • 11.Flicek P, Amode MR, Barrell D, Beal K, Brent S, Carvalho-Silva D, Clapham P, Coates G, Fairley S, Fitzgerald S, Gil L, Gordon L, Hendrix M, Hourlier T, Johnson N, Kahari AK, Keefe D, Keenan S, Kinsella R, Komorowska M, Koscielny G, Kulesha E, Larsson P, Longden I, McLaren W, Muffato M, Overduin B, Pignatelli M, Pritchard B, Riat HS, et al. Ensembl 2012. Nucleic Acids Res. 2012;40:D84–D90. doi: 10.1093/nar/gkr991. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Birney E, Clamp M, Durbin R. GeneWise and Genomewise. Genome Res. 2004;14:988–995. doi: 10.1101/gr.1865504. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, Ho SYW, Faircloth BC, Nabholz B, Howard JT, Suh A, Weber CC, Fonseca RR, Li J, Zhang F, Li H, Zhou L, Narula N, Liu L, Ganapathy G, Boussau B, Bayzid MS, Zavidovych V, Subramanian S, Gabaldón T, Gutiérrez SC, Huerta-Cepas J, Rekepalli B, Munch K, Schierup M, et al. Science. 2014. Whole Genome Analyses Resolve the Early Branches to the Tree of Life of Modern Birds. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Liu K, Warnow TJ, Holder MT, Nelesen SM, Yu J, Stamatakis AP, Linder CR. SATe-II: very fast and accurate simultaneous estimation of multiple sequence alignments and phylogenetic trees. Syst Biol. 2012;61:90–106. doi: 10.1093/sysbio/syr095. [DOI] [PubMed] [Google Scholar]
  • 15.Harris RS. Improved pairwise alignment of genomic DNA. Computer Science and Engineering: Penn State University; 2007. PhD thesis. [Google Scholar]
  • 16.Kent WJ, Baertsch R, Hinrichs A, Miller W, Haussler D. Evolution's cauldron: duplication, deletion, and rearrangement in the mouse and human genomes. Proc Natl Acad Sci U S A. 2003;100:11484–11489. doi: 10.1073/pnas.1932072100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Blanchette M, Kent WJ, Riemer C, Elnitski L, Smit AF, Roskin KM, Baertsch R, Rosenbloom K, Clawson H, Green ED, Haussler D, Miller W. Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res. 2004;14:708–715. doi: 10.1101/gr.1933104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24:1586–1591. doi: 10.1093/molbev/msm088. [DOI] [PubMed] [Google Scholar]
  • 19.Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, Clawson H, Spieth J, Hillier LW, Richards S, Weinstock GM, Wilson RK, Gibbs RA, Kent WJ, Miller W, Haussler D. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15:1034–1050. doi: 10.1101/gr.3715005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Hubisz MJ, Pollard KS, Siepel A. PHAST and RPHAST: phylogenetic analysis with space/time models. Brief Bioinform. 2011;12:41–51. doi: 10.1093/bib/bbq072. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

13742_2014_55_MOESM1_ESM.xls (85KB, xls)

Additional file 1: Author list of the Avian Genome Consortium and contribution information of each author. (XLS 85 KB)

13742_2014_55_MOESM2_ESM.xls (46.5KB, xls)

Additional file 2: NCBI accession numbers and GigaDB DOI for each bird. (XLS 46 KB)

Articles from GigaScience are provided here courtesy of Oxford University Press

RESOURCES