Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Comparative genomic data of the Avian Phylogenomics Project

GigaScience20143:26

https://doi.org/10.1186/2047-217X-3-26

Received: 25 March 2014

Accepted: 6 November 2014

Published: 11 December 2014

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.

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 file1 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[35], 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

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

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

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 file2. 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 file1.

Abbreviations

CDS: 

Coding sequence

Gb: 

Giga base pair

Kb: 

Kilo base pair

LINE: 

Long interspersed nuclear elements

MSA: 

Multiple sequences alignment

TE: 

Transposable element.

Declarations

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).

Authors’ Affiliations

(1)
China National GeneBank
(2)
Centre for Social Evolution, Department of Biology, Universitetsparken 15, University of Copenhagen
(3)
Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen
(4)
Trace and Environmental DNA laboratory, Department of Environment and Agriculture, Curtin University
(5)
Department of Neurobiology, oward Hughes Medical Institute, Duke University Medical Center
(6)
Department of Biology, University of Copenhagen
(7)
Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University
(8)
Macau University of Science and Technology, Avenida Wai long
(9)
Department of Medicine, University of Hong Kong

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: Comparative Genomics Reveals Insights into Avian Genome Evolution and Adaptation. Science. 2014, DOI:10.1126/science.1251385Google Scholar
  2. Zhang G, Li B, Li C, Gilbert MTP, Jarvis E, The Avian Genome Consortium, Wang J: The avian phylogenomisc project data. GigaSci Database. 2014,http://dx.doi.org/10.5524/101000,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. 10.1126/science.1230422.View ArticlePubMedPubMed CentralGoogle 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. 10.1038/ng.2588.View ArticlePubMedGoogle 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: The duck genome and transcriptome provide insight into an avian influenza virus reservoir species. Nat Genet. 2013, 45: 776-783. 10.1038/ng.2657.View ArticlePubMedPubMed CentralGoogle 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: 11-10.1186/2047-217X-3-11.View ArticlePubMedPubMed CentralGoogle 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: Two Antarctic penguin genomes reveal insights into their evolutionary history and molecular changes related to the Antarctic environment. GigaScience. 2014, 3: 27-http://www.gigasciencejournal.com/content/3/1/27,View ArticlePubMedPubMed CentralGoogle 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. 10.1101/gr.097261.109.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Smit AFA, Hubley R, Green P: RepeatMasker Open-3.0. 1996–2010,http://www.repeatmasker.org,Google Scholar
  10. Smit AFA, Hubley R: RepeatModeler Open-1.0. 2008–2010,http://www.repeatmasker.org,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: Ensembl 2012. Nucleic Acids Res. 2012, 40: D84-D90. 10.1093/nar/gkr991.View ArticlePubMedGoogle Scholar
  12. Birney E, Clamp M, Durbin R: GeneWise and Genomewise. Genome Res. 2004, 14: 988-995. 10.1101/gr.1865504.View ArticlePubMedPubMed CentralGoogle 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: Whole Genome Analyses Resolve the Early Branches to the Tree of Life of Modern Birds. Science. 2014, DOI:10.1126/science.1253451Google 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. 10.1093/sysbio/syr095.View ArticlePubMedGoogle Scholar
  15. Harris RS: PhD thesis. Improved pairwise alignment of genomic DNA. 2007, Penn State University, Computer Science and EngineeringGoogle 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. 10.1073/pnas.1932072100.View ArticlePubMedPubMed CentralGoogle 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. 10.1101/gr.1933104.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Yang Z: PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007, 24: 1586-1591. 10.1093/molbev/msm088.View ArticlePubMedGoogle 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. 10.1101/gr.3715005.View ArticlePubMedPubMed CentralGoogle Scholar
  20. Hubisz MJ, Pollard KS, Siepel A: PHAST and RPHAST: phylogenetic analysis with space/time models. Brief Bioinform. 2011, 12: 41-51. 10.1093/bib/bbq072.View ArticlePubMedGoogle Scholar

Copyright

© Zhang et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. 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.