Ingo Braasch1, Andrew R Gehrke2, Jeramiah J Smith3, Kazuhiko Kawasaki4, Tereza Manousaki5, Jeremy Pasquier6, Angel Amores1, Thomas Desvignes1, Peter Batzel1, Julian Catchen7, Aaron M Berlin8, Michael S Campbell9, Daniel Barrell10,11, Kyle J Martin12, John F Mulley13, Vydianathan Ravi14, Alison P Lee14, Tetsuya Nakamura2, Domitille Chalopin15, Shaohua Fan16, Dustin Wcisel17,18, Cristian Cañestro19,20, Jason Sydes1, Felix E G Beaudry21, Yi Sun22,23, Jana Hertel24, Michael J Beam1, Mario Fasold24, Mikio Ishiyama25, Jeremy Johnson8, Steffi Kehr24, Marcia Lara8, John H Letaw1, Gary W Litman26, Ronda T Litman26, Masato Mikami27, Tatsuya Ota28, Nil Ratan Saha29, Louise Williams8, Peter F Stadler24, Han Wang22,23, John S Taylor21, Quenton Fontenot30, Allyse Ferrara30, Stephen M J Searle10, Bronwen Aken10,11, Mark Yandell9, Igor Schneider31, Jeffrey A Yoder17,18, Jean-Nicolas Volff15, Axel Meyer16,32, Chris T Amemiya29, Byrappa Venkatesh14, Peter W H Holland12, Yann Guiguen6, Julien Bobe6, Neil H Shubin2, Federica Di Palma8, Jessica Alföldi8, Kerstin Lindblad-Toh8,33, John H Postlethwait1. 1. Institute of Neuroscience, University of Oregon, Eugene, Oregon, USA. 2. Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois, USA. 3. Department of Biology, University of Kentucky, Lexington, Kentucky, USA. 4. Department of Anthropology, Pennsylvania State University, University Park, Pennsylvania, USA. 5. Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Greece. 6. Institut National de la Recherche Agronomique (INRA), UR1037 Laboratoire de Physiologie et Génomique des Poissons (LPGP), Campus de Beaulieu, Rennes, France. 7. Department of Animal Biology, University of Illinois, Urbana-Champaign, Illinois, USA. 8. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. 9. Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah, USA. 10. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. 11. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, UK. 12. Department of Zoology, University of Oxford, Oxford, UK. 13. School of Biological Sciences, Bangor University, Bangor, UK. 14. Comparative Genomics Laboratory, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore. 15. Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, Lyon, France. 16. Department of Biology, University of Konstanz, Konstanz, Germany. 17. Department of Molecular Biomedical Sciences, North Carolina State University, Raleigh, North Carolina, USA. 18. Center for Comparative Medicine and Translational Research, North Carolina State University, Raleigh, North Carolina, USA. 19. Departament de Genètica, Universitat de Barcelona, Barcelona, Spain. 20. Institut de Recerca de la Biodiversitat, Universitat de Barcelona, Barcelona, Spain. 21. Department of Biology, University of Victoria, Victoria, British Columbia, Canada. 22. Center for Circadian Clocks, Soochow University, Suzhou, China. 23. School of Biology and Basic Medical Sciences, Medical College, Soochow University, Suzhou, China. 24. Bioinformatics Group, Department of Computer Science, Universität Leipzig, Leipzig, Germany. 25. Department of Dental Hygiene, Nippon Dental University College at Niigata, Niigata, Japan. 26. Department of Pediatrics, University of South Florida Morsani College of Medicine, St. Petersburg, Florida, USA. 27. Department of Microbiology, Nippon Dental University School of Life Dentistry at Niigata, Niigata, Japan. 28. Department of Evolutionary Studies of Biosystems, SOKENDAI (Graduate University for Advanced Studies), Hayama, Japan. 29. Molecular Genetics Program, Benaroya Research Institute, Seattle, Washington, USA. 30. Department of Biological Sciences, Nicholls State University, Thibodaux, Louisiana, USA. 31. Instituto de Ciências Biológicas, Universidade Federal do Pará, Belem, Brazil. 32. International Max Planck Research School for Organismal Biology, University of Konstanz, Konstanz, Germany. 33. Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Abstract
To connect human biology to fish biomedical models, we sequenced the genome of spotted gar (Lepisosteus oculatus), whose lineage diverged from teleosts before teleost genome duplication (TGD). The slowly evolving gar genome has conserved in content and size many entire chromosomes from bony vertebrate ancestors. Gar bridges teleosts to tetrapods by illuminating the evolution of immunity, mineralization and development (mediated, for example, by Hox, ParaHox and microRNA genes). Numerous conserved noncoding elements (CNEs; often cis regulatory) undetectable in direct human-teleost comparisons become apparent using gar: functional studies uncovered conserved roles for such cryptic CNEs, facilitating annotation of sequences identified in human genome-wide association studies. Transcriptomic analyses showed that the sums of expression domains and expression levels for duplicated teleost genes often approximate the patterns and levels of expression for gar genes, consistent with subfunctionalization. The gar genome provides a resource for understanding evolution after genome duplication, the origin of vertebrate genomes and the function of human regulatory sequences.
To connect human biology to fish biomedical models, we sequenced the genome of spotted gar (Lepisosteus oculatus), whose lineage diverged from teleosts before teleost genome duplication (TGD). The slowly evolving gar genome has conserved in content and size many entire chromosomes from bony vertebrate ancestors. Gar bridges teleosts to tetrapods by illuminating the evolution of immunity, mineralization and development (mediated, for example, by Hox, ParaHox and microRNA genes). Numerous conserved noncoding elements (CNEs; often cis regulatory) undetectable in direct human-teleost comparisons become apparent using gar: functional studies uncovered conserved roles for such cryptic CNEs, facilitating annotation of sequences identified in human genome-wide association studies. Transcriptomic analyses showed that the sums of expression domains and expression levels for duplicated teleost genes often approximate the patterns and levels of expression for gar genes, consistent with subfunctionalization. The gar genome provides a resource for understanding evolution after genome duplication, the origin of vertebrate genomes and the function of human regulatory sequences.
Teleost fish represent about half of all living vertebrate species[1] and provide important models for human
disease (e.g. zebrafish and medaka)[2-9]. Connecting teleost genes and gene
functions to human biology (Fig. 1a) can be
challenging, however, due to 1) two rounds of early vertebrate genome duplication (VGD1
and VGD2[10], but see[11]) followed by reciprocal loss of some
ohnologs (gene duplicates derived from genome duplication[38]) in teleosts and tetrapods, including humans
(e.g.,[12,13]); 2) the teleost genome duplication (TGD), which
resulted in duplicates of many human genes[14,15]; and 3) rapid teleost
sequence evolution[16,17], often due to asymmetric rates of ohnolog evolution
that frustrates ortholog identification. To help connect teleost biomedicine to human
biology, we sequenced the genome of spotted gar (Lepisosteus oculatus,
henceforth ‘gar’; see also Supplementary Note 1, Supplementary Fig. 1), because its lineage represents the
unduplicated sister group of teleosts[18,19] (Fig. 1a).
Figure 1
Spotted gar bridges vertebrate genomes
a) Spotted gar is a ray-finned fish that diverged from teleost fish, including
the major biomedical models zebrafish, platyfish, medaka, and stickleback,
before the teleost genome duplication (TGD). Gar connects teleosts to
lobe-finned vertebrates, such as coelacanth and tetrapods, including human, by
clarifying evolution after two earlier rounds of vertebrate genome duplication
(VGD1, VGD2) that occurred before the divergence of ray-finned and lobe-finned
fish 450 million years ago (MYA). b) Bayesian phylogeny inferred from an
alignment of 97,794 amino acid site positions from 243 proteins with one-to-one
orthology ratio from 25 jawed (gnathostome) vertebrates using PhyloBayes under
the CAT+GTR+Γ4 model and rooted on cartilaginous fish. Node support is
shown as posterior probability and bootstrap support from maximum likelihood
analysis (Supplementary Fig.
6). The tree shows the monophyly and slow evolution of Holostei (gar
plus bowfin) compared to their sister lineage, the teleosts (Teleostei). See
also Supplementary File
1 and Source
Dataset 1.
Gar informs the evolution of vertebrate genomes and gene functions after genome
duplication and illuminates evolutionary mechanisms leading to teleost biodiversity. The
gar genome evolved comparatively slowly and clarifies the evolution and orthology of
problematic teleost protein-coding and miRNA gene families. Surprisingly, many entire
gar chromosomes have been conserved with some tetrapods for 450 million years.
Importantly, gar reveals conserved non-coding elements (CNEs), which are often
regulatory, that teleosts and humans share but that direct sequence comparisons do not
detect. Global gene expression analyses show that expression domains and levels of TGD
duplicates usually sum to those in gar, as expected if ancestral regulatory elements
partitioned after the TGD. By illuminating the legacy of genome duplication, the gar
genome bridges teleost biology to human health, disease, development, physiology, and
evolution.
RESULTS
Genome assembly and annotation
The genome of a single adult gar female collected in Louisiana (USA) was
Illumina sequenced to 90X coverage. The ALLPATHS-LG[20] draft assembly covers 945 Mb with quality
metrics comparable to other vertebrate Illumina assemblies[20]. To generate a
‘chromonome’ (chromosome-level genome assembly[21]), we anchored scaffolds to a
meiotic map[19] capturing 94% of
assembled bases in 29 linkage groups (LGs) (Supplementary Note 2).
Transcriptomes from adult tissues and developmental stages (Supplementary Note 3)
facilitated a MAKER[22]-annotated gene set of 21,443 high confidence protein-coding
genes, while ENSEMBL annotation identified 18,328 protein-coding genes (mostly a
subset of MAKER annotations), 42 pseudogenes, and 2,595 ncRNAs (Supplementary Note 4),
compared to human (20,296 protein coding genes) and zebrafish (25,642). About
20% of the gar genome is repetitive, including transposable elements (TEs)
representing most lobe-finned and teleost TE superfamilies and a TE profile
similar to that of coelacanth[23], thus clarifying TE phylogenetic origins (Supplementary Note 5,
Supplementary
Tabs.1-3,
Supplementary Figs.
2-5).
The gar lineage evolved slowly
Phylogenies of 243 one-to-one orthologs in 25 jawed vertebrates[16], including gar and our
transcriptome of bowfin Amia calva (Supplementary Notes
3,4, Supplementary File 1),
strongly support the monophyly of Holostei (gar+bowfin) as sister group to
teleosts (Fig. 1b, Supplementary Note 6,
Supplementary Fig.
6)[24-27], suggesting that morphologies
shared by bowfin and teleosts[28,29] may be
convergent or ancestral traits altered in the gar lineage.Darwin applied his term ‘living fossil’ to ‘ganoid
fishes’, including gars[30]; indeed, gars show low rates of speciation and phenotypic
evolution[31].
Evolutionary rate analyses using cartilaginous fish outgroups show that gar and
bowfin proteins evolved significantly slower than teleost sequences. Holostei
have a significantly shorter branch length to the cartilaginous outgroup than
most other bony vertebrates except coelacanth, the slowest evolving bony
vertebrate[16,32] (Fig. 1b, Supplementary Note 7, Supplementary Tab. 4). Our results support the hypothesis
that the TGD could have facilitated the high rate of teleost sequence evolution
[16,17,33]. Gar
TEs also show a low turnover rate compared to teleosts, mammals, and even
coelacanth[23] (Supplementary Note 5,
Supplementary Fig.
5).
Gar informs the evolution of bony vertebrate karyotypes
Gar represents the first chromonome[21] of a non-tetrapod, non-teleost jawed vertebrate,
allowing for the first time long-range gene order analyses without the
confounding effects of the TGD. The gar karyotype (2N=58) contains both macro-
and microchromosomes (Fig. 2a, Supplementary Note 8.1,
Supplementary Fig.
7). Aligning gar chromosomes to those of human, chicken, and teleosts
revealed distinct conservation of orthologous segments in all species (Fig. 2b-e, Supplementary Note 8.2,
Supplementary Figs.
8,9).
Strikingly, gar-chicken comparisons revealed conservation of many entire
chromosomes (Fig. 2c). Chicken and gar
karyotypes differ only by about 17 large fissions, fusions, or translocations.
Almost half of the gar karyotype (14/29 chromosomes) showed a nearly one-to-one
relationship in gar-chicken comparisons, including macro- and microchromosomes
with highly correlated chromosome assembly lengths (Fig. 2d, Supplementary Note 8.2). Similarity in chromosome size and gene
content is strong evidence that the karyotype of the common bony vertebrate
ancestor possessed both macro-and microchromosomes as Ohno (1969)[34] hypothesized, consistent with
microchromosomes in coelacanth[35] and cartilaginous fish[34], for which no chromonomes are yet available.
Figure 2
Spotted gar preserves ancestral genome structure
a) The spotted gar karyotype consists of macro- and microchromosomes (see Supplementary Fig. 7 for
chromosome annotations). b) Circos plot[109] showing conserved synteny of gar (colored, left) vs.
human (black, right) chromosomes. c) Gar vs. chicken shows strong conservation
of genomes for 450 million years and one-to-one synteny conservation for many
entire chromosomes, particularly microchromosomes (e.g., Loc13 and Gga14; Loc23
and Gga11, etc.). d) Assembled chromosome lengths (in megabases, Mb) for gar and
chicken chromosomes with one-to-one conserved synteny are highly correlated
(R2 = 0.97). e) Gar vs. medaka shows the overall one-to-two
double-conserved synteny relationship of gar to a post-TGD teleost genome (e.g.,
gar Loc24 and Ola16/Ola11). Gar chromosomes are displayed in a different order
in d compared to b/c; asterisks indicate chromosomes inverted with respect to
the arbitrarily oriented reference genomes. f) Gar-chicken-medaka comparisons
illuminate karyotype evolution leading to modern teleosts. The bony vertebrate
ancestor genome contained both macro- and microchromosomes, some of which remain
largely conserved in chicken and gar, e.g., macrochromosome Loc2/GgaZ and
microchromosomes Loc20/Gga15 and Loc21/Gga17. All three chromosomes possess
double conserved synteny with medaka chromosomes Ola9 and Ola12, which is
explained by chromosome fusion in the lineage leading to teleosts after
divergence from gar, followed by TGD duplication of the fusion chromosome and
subsequent intrachromosomal rearrangements and rediploidization. Multiple
examples of such pre-TGD chromosome fusions explain the absence of
microchromosomes in teleosts. See Supplementary Note 8.2 and Source Dataset 2 for
details.
The gar chromonome also tests the hypothesis that an increase in
interchromosomal rearrangements occurred in teleosts after, and possibly due to,
the TGD[19]. For each gar
chromosome segment, teleosts usually have two ohnologous segments, verifying a
pre-TGD gar-teleost divergence[19]. Each TGD pair in teleosts usually shares conserved synteny
with more than one gar chromosome, indicating rearrangements before the TGD
(Fig. 2e, Supplementary Note 8.2,
Supplementary Figs.
8,9). Gar
shares many whole chromosomes with chicken (Fig.
2c) but few with teleosts (Fig.
2e). These results show that chromosome fusions thought to have
occurred in the ray-finned lineage after divergence from the lobe-finned
lineage[36] actually
occurred in the teleost lineage after divergence from gar but before the TGD
(Fig. 2f, Supplementary Fig. 10).
This finding explains how spotted gar has more chromosomes (N=29, Fig. 2a) than typical teleosts
(N~24-25[37])
without experiencing the TGD. Comparisons taking the TGD into account further
revealed an average fission/translocation rate in percomorphs (stickleback,
medaka, pufferfish) relative to gar similar to that in the chicken lineage.
Zebrafish has a higher rearrangement rate, however, even after accounting for
the TGD (Supplementary Note
8.2, Supplementary
Fig. 11). These comparisons indicate that the TGD might not fully
account for high teleost rearrangement rates.
Gar clarifies vertebrate gene family evolution
Lineage-specific loss of ohnologs often followed VGD1, VGD2, and the TGD
(Fig. 1a), which complicates
identification of true orthologs[21,39] and
frustrates translating knowledge from teleosts biomedical models to human
biology, e.g.,[12]. Gar is
uniquely informative because its lineage did not experience the TGD and often
retained ancestral VGD1/VGD2 ohnologs that were reciprocally lost in teleosts
and tetrapods, thus clarifying the evolution of gene families involved in
vertebrate development, physiology, and immunity (Supplementary Note
9).Developmental gene family analyses revealed stability in
the gar gene repertoire, including (Supplementary Note 9.1). Gar has 43 hox genes
organized in four clusters expected for an unduplicated ray-finned fish (Supplementary Fig. 12).
No hox gene has been completely lost in gar since divergence
from the last common ray-finned ancestor. The hoxD14 gene,
missing from teleosts but present in paddlefish[40], is recognizable as a pseudogene in gar (Supplementary Fig. 13).
In contrast, teleosts have far fewer hox cluster genes than the
82 expected after genome duplication (e.g., zebrafish, 49 genes; stickleback,
46), demonstrating massive hox cluster gene loss after the TGD.
Teleosts lack orthologs of hoxA6 and hoxD2,
zebrafish lacks all hoxDb cluster protein-coding
genes[14], and
percomorphs lack the hoxCb cluster[41], but gar lacks just one hox
cluster gene from the last common bony vertebrate ancestor
(hoxA14), fewer than tetrapods (e.g., human: three losses)
and coelacanth (two) (Supplementary Fig. 12). Gar (Supplementary Note 9.2, Supplementary Tab. 5) are also more complete than those in
teleosts and tetrapods, with four clusters containing seven genes. Gar retained
cdx2, revealing a VGD1/VGD2 ohnolog ‘gone
missing’ from teleosts (Supplementary Fig. 14). Gar possesses the VGD1/VGD2 ohnolog
pdx2, previously found only in cartilaginous fish and
coelacanth[42], showing
that pdx2 was lost independently in teleosts and tetrapods
(Supplementary Figs.
14,15).
Retinoic acid regulates Hox cluster
gene expression[43] but retinoic
acid-synthesizing Aldh enzymes (Supplementary Note 9.3) vary in number among
vertebrates[44]:
tetrapods have three genes (Aldh1a1, Aldh1a2,
Aldh1a3), zebrafish has two (aldh1a2,
aldh1a3), medaka just one
(aldh1a2)[45]. Finding all three genes in gar rules out the
hypothesis[45] that
Aldh1a1 was a lobe-finned innovation (Supplementary Fig.
16).Physiological mechanisms are shared among vertebrates,
including light control of circadian rhythms, despite important gene repertoire
differences between teleosts and tetrapods [46,47]. Analyses of
gar circadian clock (Supplementary Note 9.4,
Supplementary Tab.
6, Supplementary
Fig. 17)[48] and
opsin genes (Supplementary Note 9.5, Supplementary Tab. 7,
Supplementary Fig.
18)[49] link gene
repertoires of teleosts and tetrapods: e.g., gar clarifies circadian gene
origins in VGD vs. TGD events. Gar has pinopsin, present in
tetrapods but absent from teleosts, along with exo-rhodopsin,
previously thought to compensate the lack of pinopsin in
teleosts[50].Evolution of vertebrate immunity becomes clearer using gar
(Supplementary Note
9.6). Major-histocompatibility complex (MHC)
class I and class II genes (Supplementary Figs. 19-21) are tightly linked in tetrapods and cartilaginous fish
but are unlinked in teleosts[51,52]. In gar, at least one pair of
class I and class II genes are linked as in tetrapods[53,54],
suggesting that gar retains the ancestral configuration although most gar MHC
genes remain on unassembled scaffolds (Supplementary Fig. 21). Gar has some class I genes thought
to be teleost-specific (Z/P-, L-, and U/S-like, e.g.[54-56];
Supplementary Fig.
19) and some class II genes similar to, and some distinct from,
teleost DA/DB and DE lineages (Supplementary Fig. 20). Several gar MHC region genes are on
unassembled scaffolds linked to genes whose human orthologs are encoded in MHC
class II or MHC class III regions on Hsa6 and some are adjacent to orthologs of
teleost MHC class I genes (Supplementary Tab. 8). The human MHC class III region on Hsa6 has
syntenic segments on Hsa1, Hsa9, and Hsa19; these four ohnologons likely arose
in VGD1 and VGD2[57] as
supported by the gar genome (Supplementary Tab. 8).Gar immunoglobulin (Ig) genes (Supplementary Fig. 22)
and transcripts generally resemble those of teleosts. Unexpectedly, gar has a
second, distinct IgM locus but lacks IgT (IgZ)[58,59],
thought to provide mucosal immunity[60], suggesting that IgT is teleost-specific and that gar
ganoid scales may suffice for exterior surface protection. Gar T-cell
receptor genes (Supplementary Fig. 23) are tightly linked as in mammals,
but unlike in Xenopus[61], they are downstream of VH and JH
segments. Phylogenetic analyses of Toll-like receptor
(TLR) genes (Supplementary
Fig. 24) from tetrapods, teleosts, and gar revealed that the 16
identifiable gar TLRs embrace all six major TLR families[62]. Gar TLRs appear to share
evolutionary histories with teleosts and/or tetrapods. Gar encodes
NITR (novel immune-type receptor) genes (Supplementary Fig. 25),
which function in allorecognition and were thought to be
teleost-specific[63,64]. The 17 gar
nitr genes form 15 families, suggesting few recent tandem
duplications or rapid divergence after gene duplication. In sum, the gar
immunogenome bridges teleosts to tetrapods.
Gar uncovers evolution of vertebrate mineralized tissues
Bony vertebrates share mineralized tissues (bone, dentin, enameloid, and
enamel), yet gene repertoires for the secretory calcium-binding phosphoproteins
(Scpp) that form these tissues[65,66] differ
substantially between teleosts and tetrapods and their evolution remains
controversial[17,67,68]. Gar clarifies understanding because it retains ancient
characteristics both in its ganoid scales, which contain ganoin, hypothesized to
be a type of enamel[69], and in
its teeth, which are covered by both enameloid and enamel[70] (Supplementary Note 10).
Mammalian genomes were thought to contain the largest number of
Scpp genes (human, 23 genes; coelacanth, 14; zebrafish, 15)
and only two (Spp1 and Odam) seemed common
between lobe-finned vertebrates and teleosts[68] (Fig. 3a). We
identified 35 scpp genes in gar in two clusters on LG2 and LG4
(Fig. 3a, Supplementary Note 10,
Supplementary Tab.
9), which contain spp1 and odam,
respectively. Importantly, gar includes orthologs of five scpp
genes previously found only in teleosts and six known only from lobe-finned
vertebrates. Another 18 gar scpp genes have no identified
ortholog in either lobe-finned vertebrates or teleosts (Fig. 3a, Supplementary Note 10, Supplementary Tab. 9).
Figure 3
Gar helps connect vertebrate protein-coding and miRNA genes
a) Scpp gene arrangement in human, coelacanth, gar, and
zebrafish including P/Q-rich (red) and acidic Scpp genes (blue)
and Sparc-like genes (yellow) (Supplementary Note 10,
ref.[68]). Orthologies
(gray vertical bars) among lobe-finned vertebrates (e.g., human, coelacanth) and
teleosts (e.g., zebrafish) had previously been limited to Odam
and Spp1. Gar connects lineages through orthologs of genes
previously known only from either teleosts (scpp1,
scpp3 genes, scpp5,
scpp7, scpp9) or lobe-finned vertebrates
(enam, ambn, dmp1,
dsppl1, ibsp, mepe).
Further putative orthologies supported by only short stretches of sequence
similarity (‘?’) connect gar enam,
ambn, and lpq14 with zebrafish
fa93e10, scpp6, and
scpp8, respectively; gar lpq1 and
Scpppq4 in coelacanth; and gar lpq5 with
Amtn in lobe-finned vertebrates. Arrows in human and
zebrafish indicate intra-chromosomal rearrangements separating originally
clustered genes into distant chromosomal locations (distance in megabases, Mb).
Conserved synteny analysis of the gar scpp gene cluster on LG2
suggests that the scpp gene regions on zebrafish chromosomes 10
and 5 are derived from the TGD (Supplementary Note 10, Supplementary Fig. 26).
b) The gar ‘conserved synteny bridge’ (Supplementary Note 11.2)
infers that the miRNA cluster of mir731 and
mir462 on gar LG4 and zebrafish chromosome 8 and a
miRNA-free region on zebrafish chromosome 2 are TGD ohnologous to the mammalian
Mir425-191 cluster. c) Gar newly connects through synteny
zebrafish TGD ohnologs mir135c-1 and mir135c-2
with mammalian Mir135B. See Source Dataset 3 for
genomic locations in a-c.
Enamel matrix protein genes Ameloblastin
(Ambn), Enamelin (Enam),
and Amelogenin (Amel) are found in lobe-finned
vertebrates with enamel-bearing teeth, but not in teleosts, which lack
enamel-bearing teeth[66,68]. For the first time in a
ray-finned vertebrate, we identified ambn and
enam genes (but no Amel ortholog) in gar
genome and transcriptomes. Gar ambn and enam
genes show sequence similarities to zebrafish scpp6 and
fa93e10, respectively, suggesting that teleosts may have
divergent orthologs, supported by conserved gene orders in gar and zebrafish
clusters (Fig. 3a).RT-PCR and our gar skin transcriptome revealed expression of
ambn and enam in enamel-containing gar
teeth and in gar skin that includes scales with ganoin (Supplementary Note 10,
Supplementary Tab.
9), suggesting that strong expression of ambn and
enam is limited to enamel and ganoin. Thus, enamel in teeth
and ganoin in ganoid scales likely represent the same tissue and common
expression of Ambn and Enam in lobe-finned
enamel and in gar enamel/ganoin supports homology of these tissues. Analysis of
gnathostome fossils suggested that ganoin is plesiomorphic for crown
osteichthyans and arose before enamel[71]; thus, enamel-bearing teeth likely evolved by co-opting
enamel matrix genes originally used in ganoid scales. Amel may
have evolved subsequently to encode the principal organic component of
“true enamel” that appears to have originated in lobe-finned
vertebrates[68].Gar expressed twelve additional scpp genes (including
odam and scpp9 hypermineralization
genes[66]) in both teeth
and scales and another four genes in bone (Supplementary Tab. 9),
strongly suggesting that the common ancestor of extant bony vertebrates had a
rich repertoire of Scpp genes, many of which were expressed in
mineralized tissues, and that although teleosts and lobe-finned vertebrates
independently lost subsets of ancient Scpp genes[65], gar retained characteristics
of both lineages.
Gar connects vertebrate microRNAomes
MicroRNA genes could become teleost- or tetrapod-specific[17,72] by loss in one lineage or gain in the other. We studied
gar miRNAs computationally (Supplementary Note 11.1, Supplementary Tab. 10, Supplementary Fig. 27)
and annotated them using a sequence-based approach (Supplementary Note 11.2).
Small RNA sequencing from four tissues identified 302 mature miRNAs from 233
genes, 229 belonging to 107 families and four without a known family (Supplementary Tab. 11,
Supplementary Fig.
28). Gar-zebrafish[73,74] comparisons
showed that four families and four individual miRNA genes emerged in teleosts.
Of 22 families thought to be teleost losses[17], two actually belong to the same family and orthologs
of four gar miRNA genes were previously overlooked in teleosts. Fourteen
families are absent from both gar and teleosts, and three are present in gar and
many teleosts[74] but absent
from zebrafish. A single family present in teleosts and lobe-finned fish
(mir150) was not found in gar. Notably, no miRNA family
loss was teleost-specific, suggesting that the TGD did not accelerate family
loss.The ‘gar bridge’ helps identify miRNA orthologies. For
example, mammalian Mir425 and Mir191, thought
to be lost in teleosts[17], are
orthologs of teleost mir731 and mir462,
respectively (Fig. 3b). Additionally,
mammalian Mir135B is orthologous to gar
mir135c and zebrafish TGD ohnologs
mir135c-1 and mir135c-2 (Fig. 3c). The post-TGD retention rate for
zebrafish miRNA ohnologs is 39% (81/208 analyzable cases), considerably higher
than the rate for protein-coding genes (20-24%[75]), consistent with the hypothesis that miRNA
genes are likely to be retained after duplication due to their incorporation
into multiple gene regulatory networks[76-79].
Gar reveals hidden orthology of cis-regulatory
elements
Conserved non-coding elements (CNEs) often function as
cis-acting regulators[80,81], but many are
not visible in teleosts, presumably due to rapid teleost sequence evolution
(Fig. 1b, Supplementary Note 7);
ancient CNEs identified in tetrapods, however, might be detected in ray-finned
fish using the slowly evolving gar.CNE analyses near developmental gene loci
(Hox/ParaHox clusters,
Pax6, IrxB) showed that gar contains more
gnathostome CNEs (conserved between bony vertebrates and elephant shark) than
teleosts. Analyses incorporating gar identified many bony vertebrate CNEs (i.e.,
absent from elephant shark) that were not predicted by direct human-teleost
comparisons; furthermore, gar-based alignments identified CNEs recruited in the
common ancestor of ray-finned fishes (Supplementary Notes 9.2, 12.1, Supplementary Tabs.
12-19, Supplementary Figs.
14-15,29-35).Gar unravels the origins of tetrapod limb enhancers, evidenced by
whole-genome alignments for 13 vertebrates (gar, five teleosts, coelacanth, five
tetrapods, elephant shark, Supplementary Note 12.2, Supplementary Tabs. 20-21, Supplementary Fig. 36).
For 153 known human limb enhancers [32, 82-84], human-centric alignments
identified 71% (108) in gar but only 53% (81) in direct human-teleost
alignments. Of 72 limb enhancers lacking a human-teleost alignment, 40% (29/72)
aligned to gar, confirming their presence in the bony vertebrate ancestor and
loss or considerable divergence in teleosts. Of these 29 enhancers, 15 also
aligned to elephant shark, revealing their existence in the gnathostome
ancestor. Fourteen occurred in gar but not teleosts and would have been
incorrectly characterized as lobe-finned innovations without gar (Supplementary Note 12.3,
Supplementary Tab.
22).Using the ‘gar bridge’ (Fig.
4a), we tested whether these 29 enhancers not directly identified in
teleosts might represent rapid divergence rather than definitive loss.
Inspection of human-centric and gar-centric alignments revealed 48% (14/29)
aligning to at least one teleost (Supplementary Tab. 22). Gar thus substantially improves
understanding of the evolutionary origin of vertebrate limb enhancers and their
fate in teleosts (Fig. 4b, Supplementary Tab. 22,
Supplementary Fig.
37). Strikingly, despite using the ‘gar bridge’, we
found that teleosts lost substantially more limb enhancers (15) than gar (two)
(Fig. 4b, Supplementary Fig. 37),
suggesting gar as a better model than teleosts for investigating the fin-to-limb
transition[85].
Figure 4
Gar provides connectivity of vertebrate regulatory elements
a) The ‘gar bridge principle’ of vertebrate CNE connectivity from
human through gar to teleosts. Hidden orthology is revealed for elements that do
not directly align between human and teleosts but become evident when first
aligning tetrapod genomes to gar, and then aligning gar and teleost genomes. b)
Connectivity analysis of 13-way whole-genome alignments reveals the evolutionary
gain (green) and loss (red) of 153 human limb enhancers. Direct human-teleost
orthology could only be established for 81 elements as opposed to 95 when taking
gar as bridge (a). See Supplementary Notes 12.2,12.3, Supplementary Tab. 22, and Supplementary Fig. 37 for details.
Functional studies of a
tested the utility of a ‘gar CNE bridge’. HoxD
and HoxA clusters pattern proximal and distal mammalian limbs
by ‘early’ and ‘late’ phases of gene expression,
respectively[86]. Early
phase HoxD expression in fins and limbs shows several presumed
homologous features[87] and may
derive from shared but cryptic regulatory elements. Elements CNS39 and CNS65
drive early phase HoxD activation in mammals[88] (Figure 5a). Human-centric (Supplementary Tab. 22) and local mouse-centric alignments
(Figure 5a) failed to detect CNS39 in
ray-finned fish, but identified CNS65 in gar. Significantly, CNS65 appeared in
teleosts only using the ‘gar bridge’ (Figure 5a, Supplementary Tab. 22).
Figure 5
Identification and functional analysis of the gar and teleost early phase
HoxD enhancer CNS65
a) Schematic of the mouse HoxD telomeric gene desert, which
contains enhancers CNS39 and CNS65 that drive early phase HoxD
expression in limbs (upper part). Using mouse as baseline, Vista alignments of
the HoxD gene desert show sequence conservation with human and
chicken for CNS65, but not with teleosts (zebrafish, pufferfish) (lower part,
left). An alignment including gar, however, reveals a significant peak of
conservation in the gar sequence (middle). Using the identified gar CNS65 as
baseline revealed CNS65 orthologs in zebrafish and pufferfish (right). b) Gar
(left) and zebrafish (right) CNS65 orthologs drive robust and reproducible GFP
expression in zebrafish pectoral fins at 36 hours post fertilization (hpf)
(upper panel). Pectoral fin activity of gar CNS65 begins at 31 hpf, drives
activity throughout the fin, and becomes deactivated around 48 hpf (lower
panel). Dotted lines: distal portion of the pectoral fins. c) Gar CNS65 drives
expression throughout the early mouse fore-and hindlimbs (arrows) at stage e10.5
(left). At later stages (e12.5), gar CNS65 activity is restricted to the
proximal portion of the limb and absent in developing digits (middle). Zebrafish
CNS65 drives reporter expression in developing mouse limbs at e10.5, but only in
forelimbs (right). Number of LacZ-positive embryos showing limb signal is
indicated at the bottom right; fl, forelimb, hl, hindlimb (c). Scale bars: 50
μm (b); 500 μm (c). See also Supplementary Note
12.4.
To test if cryptic CNE orthologs preserve enhancer function, we used
CNS65-driven reporter constructs to generate transgenic zebrafish and mice
(Supplementary Note
12.4). CNS65 from either gar or zebrafish drove early expression in
the developing zebrafish pectoral fin (Figure
5b). Gar CNS65 drove expression in fore- and hindlimbs of stage e10.5
mice (Figure 5c) indistinguishable from
murine CNS65[88]. Zebrafish
CNS65 activated forelimb expression somewhat weaker than gar CNS65 (Figure 5c). At e12.5, gar CNS65 activated
proximal but not distal limb expression (Figure
5c), mimicking the endogenous murine enhancer[88]. These functional experiments
demonstrate that regulation of HoxD early phase expression in
limbs and fins is an ancestral, conserved feature of bony vertebrates and that
gar connects otherwise cryptic teleost regulatory mechanisms to mammalian
developmental biology.
Gar bridges human CNEs to teleost biomedical models
Genome-wide, we identified approximately 28% of human-centric CNEs
(39,964/143,525) in gar, more than in any of five aligned teleost genomes.
Around 19,000 human-centric CNEs aligned to gar but not to any teleost
(Supplementary Note
12.2, Supplementary Tab. 21). Without gar, one would have erroneously
concluded that these elements originated in lobe-finned vertebrates or were
lost in teleosts. The ‘gar bridge’ (Fig. 4a) established hidden orthology from human to gar
to zebrafish for many of these human-centric CNEs (30-36%, depending on
overlap; Supplementary
Note 12.2, Supplementary Tab. 21). These approximately 6,500 newly
connected human CNEs contain around a thousand SNPs linked to human
conditions in genome-wide association studies (GWAS), thereby connecting
otherwise undetected disease-associated haplotypes to genomic locations in
zebrafish (Supplementary
Tab. 21). The gar bridge thus helps identify biomedically
relevant candidate regions in model teleosts for functional testing, thereby
enhancing teleost models for personalized medicine.
Gar illuminates gene expression evolution following the TGD
Ohnologs experience several non-exclusive fates after genome
duplication: loss of one copy, evolution of new expression domains or protein
functions, and the partitioning of ancestral functions[89-92].
Because the contribution of various fates has not yet been studied using a close
TGD outgroup, we generated a list of gar genes and their orthologous TGD
ohnologs or singletons in zebrafish and medaka using phylogenetic[93] and conserved synteny
analyses[94] (Fig. 6a,b, Supplementary Note 13.1,
Supplementary Tab.
23).
Figure 6
Gar illuminates gene expression evolution post-TGD
Origin (a) and distribution (b) of gar and teleost singletons or TGD ohnologs
(Supplementary Note
13.1, Supplementary Tab. 23). c) Neofunctionalized ohnologs
(slc1a3): novel expression in liver; d) Subfunctionalized
ohnologs (gpr22): one is expressed in brain like in gar, the
other in heart like in gar; r: correlation of expression profiles of each
ohnolog vs. gar pattern. Supplementary Note 13.2 lists neo- and subfunctionalization
criteria. e-h) Expression conservation for ohnologs or singletons in zebrafish
(Zf; e, g) and medaka (Md; f, h) (Supplementary Note 13.2). e, f) Mean correlations (r
values) between expression patterns of gar genes and teleost ortholog(s).
Correlations of average expression levels of ohnolog-pairs to gar were greater
than ohnologs alone and than singletons, showing sharing of ancestral
subfunctions between the ohnolog-pair (multiple Wilcoxon Mann-Whitney tests with
Bonferroni correction; alpha value 0.05 for significance). g, h) Mean Log10
ratios between expression levels of gar genes and teleost ortholog(s).
Individual ohnologs compared to gar were expressed at significantly lower levels
than singletons, but ohnolog-pair/gar ratios were not statistically different
from singleton/gar ratios, suggesting that expression levels of ohnolog-pairs
approach pre-duplication genes (multiple two-sided Student t-test with
Bonferroni correction; alpha value 0.05 for significance). Error bars: standard
error of the mean (s.e.m.). ‘OhnoPair’: average expression of
ohnolog-pair (Supplementary
Note 13.2). Br, brain; Gil, gill; Hrt, heart; Mus, muscle; Liv,
liver, Kid, kidney; Bo, bone; Int, intestine; Ov, ovary; Te, testis; Emb,
embryo. Source Dataset
4 contains data for Fig. 6c-h.
To compare tissue-specific gene expression patterns, we conducted
RNA-seq for ten adult organs and for stage-matched embryos for gar, zebrafish,
and medaka, then normalized reads across tissues for each gene in each species
(Supplementary Notes
3.2,13.2).
For example, gar expressed slc1a3 mainly in brain, bone, and
testis, but both teleosts expressed one ohnolog primarily in brain and the other
primarily in liver, a novel expression domain, with little expression in bone or
testis (Fig. 6c). Novel expression domains
like this are expected if one ohnolog maintained ancestral patterns while the
other evolved new functions[95]
before the teleost radiation. In contrast, gar expressed gpr22
mostly in brain and heart but both teleosts expressed one ohnolog in brain, the
other in heart (Fig. 6d), as expected by
partitioning of ancestral regulatory subfunctions[89].To characterize effects of the TGD on evolution of gene expression, we
plotted tissue-specific expression levels in gar vs. 1) expression of
orthologous teleost singletons, 2) expression of each TGD ohnolog when both were
retained, and 3) the averaged expression level of both retained ohnologs
(‘ohnolog-pair’), and then calculated correlation coefficients.
Results showed that the correlation of expression patterns of
gar genes to their teleost singleton orthologs (‘Singl’ in Fig. 6e,f) was not significantly different
from the correlation of expression patterns of gar genes to either copy of their
teleost TGD co-orthologs (‘Ohno1’ and ‘Ohno2’ in
Fig. 6e,f); thus, compared to ancestral
single-copy genes as estimated from gar, teleost ohnologs binned at random do
not appear to have evolved expression pattern differences significantly more
rapidly than singletons. In contrast, the average tissue-specific patterns of
both TGD duplicates (‘OhnoPair’ in Fig. 6e,f) correlated significantly more closely to gar than either
ohnolog taken alone and more closely than singletons; thus, ancestral gene
subfunctions tended to partition between TGD ohnologs and to maintain ancestral
functions as a gene pair, as predicted by the subfunctionalization
model[89].We next calculated average expression levels for each
gene over the 11 tissues and computed the ratio of each teleost gene to its gar
ortholog. Comparisons showed that individual ohnologs (Fig. 6g,h) were each expressed at significantly lower levels
than singletons (Fig. 6g,h) compared to
their gar orthologs. The ratio of expression levels of ohnolog-pairs to gar
expression levels, however, showed no statistical difference from singleton/gar
expression ratios (Fig. 6g,h). This finding
suggests that the aggregate expression level of ohnolog-pairs tends to evolve to
approximate the level of the pre-duplication gene as expected by quantitative
subfunctionalization[89,90,96].Taken together, our analyses indicate that post-TGD, ohnolog-pairs
evolved so that the sum of their expression domains and the sum of their
expression levels usually approximated the patterns and levels of
pre-duplication genes.
DISCUSSION
Gar is the first ray-finned fish genome sequence not impacted by the TGD.
Due to its phylogenetic position, slow rate of sequence evolution, dense genetic
map, and ease of laboratory culture, this resource provides a unique bridge between
tetrapods and teleost biomedical models. Analysis revealed that gar bridges teleosts
to tetrapods in genome arrangement, identifying orthologous genes, possessing
ancient VGD ohnologs lost reciprocally in teleosts and tetrapods, understanding
evolution of vertebrate-specific features including adaptive immunity and
mineralized tissues, and the evolution of gene expression. Clarification of gene
orthology and history is crucial for the design, analysis, and interpretation of
teleost models of human disease, including those generated with CRISPR/Cas9-induced
genome editing[97,98]. Gar analyses show that sequences formerly
considered unique to teleosts or tetrapods are often shared between ray-finned and
lobe-finned vertebrates including human. Importantly, the gar bridge helps identify
potential gene regulatory elements that are shared by teleosts and humans but
invisible in direct teleost-tetrapod comparisons. Availability of gar embryos and
ease of raising eggs to adults in the laboratory[21] (Supplementary Fig. 1) makes gar a ray-finned species of choice when
analyzing many vertebrate developmental and physiological features. In conclusion,
the gar bridge facilitates the connectivity of teleost medical models to human
biology.
ONLINE METHODS
A full description of methods can be found in the Supplementary Note. Animal
work was approved by the University of Oregon Institutional Animal Care and Use
Committee (Animal Welfare Assurance Number A-3009-01, IACUC protocol 12-02RA).
Gar genome sequencing and assembly
The spotted gar genome was sequenced and assembled using DNA from a
single adult female gar wild-caught in Bayou Chevreuil, St. James Parish,
Louisiana, USA (Supplementary
Note 1). It was sequenced by Illumina sequencing technology and
jumping libraries to 90X coverage and assembled into LepOcu1 (accession number
AHAT00000000.1) using ALLPATHS-LG[20]. The draft assembly is 945 Mb in size and is composed of
869 Mb of sequence plus gaps between contigs. The spotted gar genome assembly
has a contig N50 size of 68.3 kb, a scaffold N50 size of 6.9 Mb, and quality
metrics comparable to other vertebrate Illumina genome assemblies[20]. A total of 209 scaffolds were
anchored in 29 linkage groups using 2,153 of 8,406 meiotic map RAD-tag
markers[19], thus
capturing 891 Mb of sequence or 94.2% of bases in the chromonome assembly (Supplementary Note
2).
RNA-seq transcriptomes
The Broad Institute gar RNA-seq transcriptome (Supplementary Note 3.1)
was generated from 10 tissues (stage 28 embryo[99], 8 day larvae, eye, liver, heart, skin,
muscle, kidney, testis) and assembled using Trinity[100]. PhyloFish RNA-seq transcriptomes of gar
(Supplementary Note
3.2), bowfin (Supplementary Note 3.3), zebrafish, and medaka (Supplementary Note 13.2)
were generated from 10 adult tissues (ovary, testis, brain, gills, heart,
muscle, liver, kidney, bone, intestine) and one embryonic stage
(‘pigmented eye’ stage of gar, zebrafish, medaka) and assembled
using the Velvet/Oases package[101].
Genome annotation
Using evidence from the Broad and PhyloFish gar transcriptomes (Supplementary Note 3),
all RefSeq teleost proteins, and all Uniprot/Swissprot proteins,
MAKER2[22] annotated
25,645 protein-coding genes (Supplementary Note 4.1). Using the Broad transcriptome (Supplementary Note 3.1),
the Ensembl gene annotation pipeline identified 18,328 protein-coding genes for
22,470 transcripts along with 42 pseudogenes and 2,595 ncRNAs (Supplementary Note 4.2).
Annotations for 762 and 6,877 genes are specific to Ensembl and MAKER,
respectively. The 21,443 high confidence gene set predicted by MAKER is likely
close to the true number of gar protein-coding genes.
Annotation of transposable elements
Manual and automatic classification (using RepeatScout and
RepeatModeler) of gar TEs was performed on the basis of Wicker’s
nomenclature[102] and
identified elements were combined into a single library (Supplementary Note 5),
which was then used to mask the genome with RepeatMasker. The TE age profile was
determined using Kimura distances of individual TE copies to the corresponding
TE consensus sequence (Supplementary Note 5).
Phylogenomic and evolutionary rate analyses
Phylogenetic analyses (Supplementary Note 6) were based on protein-coding sequence
alignments described for the coelacanth genome analysis[16] but updated with orthologous
sequences from gar and bowfin (Supplementary Notes 3,4) and from the slowly evolving Western painted
turtle[103].
Phylogenetic reconstructions were carried out with RAxML[104] and PhyloBayes MPI[105]. Molecular rate analyses
(Supplementary Note
7) were performed at the protein alignment level with Tajima’s
relative rate tests[106] and at
the level of the reconstructed phylogenies with Two-Cluster tests[107].
Genome structure analyses
The spotted gar karyotype was determined from caudal fin fibroblast cell
cultures established as described for zebrafish[108] (Supplementary Note 8.1). Conserved synteny analyses between
gar, tetrapods (human, chicken) and teleosts (Supplementary Note 8.2)
were performed with 1) Circos plots[109] based on orthology relations from Ensembl75 and as
described in Supplementary
Note 13.1); 2) the Synteny Database[94] after integration of the gar genome assembly
(Ensembl74 version); and 3) comparative synteny maps derived as described in
refs.[16,110].
Gene family analyses
Individual gene families were analyzed as described in Supplementary Notes 9.
RT-PCR and sequencing was performed to annotate and to analyze gene expression
of scpp mineralization genes using cDNA libraries from gar
teeth, jaw, and scales (Supplementary Note 10).
miRNA annotation and analysis
Gar miRNAs were studied in silico (Supplementary Note 11.1)
by blasting teleost and tetrapod miRNAs from miRBase[74,111-113] against the gar genome
assembly and confirmed with RNAfold[114] (see also ref.[72]). miRNA annotation and analyses based on sequencing
data of gar miRNAs (Supplementary Note 11.2) was performed as described for
zebrafish[73] by
utilizing small RNA-seq data from adult brain, heart, testis, and ovary tissue,
which were processed and annotated with Prost![115] according to miRNA gene nomenclature
guidelines[116]; miRNA
orthologies based on conserved synteny were established using Ensembl[117], the Synteny
Database[94] and
Genomicus[118,119].
Analysis of conserved non-coding elements
Investigation of CNEs in developmental gene loci were performed using
SLAGAN[120] in
VISTA[121] (Supplementary Notes
9.2,12.1).
Gar-, zebrafish-, and human-centric 13-way multi-genome alignments were
generated with MultiZ[122]
based on lastZ[123] pairwise
whole genome alignments (WGAs). We used phyloFit[124] to generate a neutral model of 4d site
evolution to identify conserved elements with phastCons[124]; genic elements and
repetitive sequences were filtered out to obtain CNEs. Evolution of human limb
enhancers[32,82-84] was established using WGAs and conserved synteny
curation. Genome-wide connectivity of CNEs and embedded GWAS-SNPs from human to
zebrafish through gar was established from WGAs using liftOver[125] and BEDtools[126] (Supplementary Notes
12.2,12.3).
HoxD enhancer functional analysis
Gar and teleost orthologs of HoxD early enhancer CNS65
were identified with VISTA (LAGAN)[121]. Gar and zebrafish CNS65 were cloned into
pXIG-cFos-eGFP and Gateway-Hsp68-LacZ vectors for zebrafish[127] and mouse transgenesis
(Cyagen Biosciences), respectively (Supplementary Note 12.4).
Comparative gene expression analyses
Curated lists of TGD ohnologs and TGD singletons of zebrafish and medaka
and their gar (co-)orthologs were generated by integrating phylogenetic
information from EnsemblCompara GeneTrees[93] (Ensembl74) and conserved synteny data from the Synteny
Database[94] (Supplementary Note 13.1).
For all three species, RNA-seq reads from the PhyloFish transcriptomes (Supplementary Note
3.2,13.2)
were mapped against the longest Ensembl reference coding sequence of each gene
with BWA-Bowtie[128,129], counted with
SAMtools[130] and
normalized for each gene across the 11 tissues using DESeq[131]. The correlation of
expression patterns and relative levels of expression between each
zebrafish/medaka gene and its gar ortholog and of singletons, ohnolog 1, ohnolog
2, and ‘ohnolog pairs’ were determined using R[132]. See Supplementary Note 13.2
for additional information including definition of ‘ohnolog pair’
expression and criteria for detecting neo- and subfunctionalization
detection.
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