The tuatara genome reveals ancient features of amniote evolution (2024)

The tuatara is an iconic terrestrial vertebrate that is unique to New Zealand². The tuatara is the only living member of the archaic reptilian order Rhynchocephalia (Sphenodontia), which last shared a common ancestor with other reptiles at about 250million years ago (Fig. 1); this species represents an important link to the now-extinct stem reptiles from which dinosaurs, modern reptiles, birds and mammals evolved, and is thus important for our understanding of amniote evolution².

a, The tuatara, (S.punctatus) is the sole survivor of the order Rhynchocephalia. b, c, The rhynchocephalians appear to have originated in the early Mesozoic period (about 250–240million years ago (Ma)) and were common, speciose and globally distributed for much of that era. The geographical range of the rhynchocephalians progressively contracted after the Early Jurassic epoch (about 200–175Ma); the most recent fossil record outside of New Zealand is from Argentina in the Late Cretaceous epoch (about 70Ma). c, The last bastions of the rhynchocephalians are 32islands off the coast of New Zealand, which have recently been augmented by the establishment of about 10new island or mainland sanctuary populations using translocations. The current global population is estimated to be around 100,000individuals. Rhynchocephalian and tuatara fossil localities are redrawn and adapted from ref. ¹ with permission, and incorporate data from ref. ². In the global distribution map (c, top); triangle=Triassic; square=Jurassic; circle=Cretaceous; and diamond=Palaeocene. In the map of the New Zealand distribution (c, bottom); asterisk=Miocene; cross=Pleistocene; circle=Holocene; blue triangle=extant population; and orange triangle=population investigated in this study. Scale bar, 200km. Photograph credit, F.Lanting.

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It is also a species of importance in other contexts. First, the tuatara is a taonga (special treasure) for Māori, who hold that tuatara are the guardians of special places². Second, the tuatara is internationally recognized as a critically important species that is vulnerable to extinction owing to habitat loss, predation, disease, global warming and other factors². Third, the tuatara displays a variety of morphological and physiological innovations that have puzzled scientists since its first description². These include a unique combination of features that are shared variously with lizards, turtles and birds, which left its taxonomic position in doubt for many decades². This taxonomic conundrum has largely been addressed using molecular approaches⁴, but the timing of the split of the tuatara from the lineage that forms the modern squamates (lizards and snakes), the rate of evolution of tuatara and the number of species of tuatara remain contentious². Finally, there are aspects of tuatara biology that are unique within, or atypical of, reptiles. These include a unique form of temperature-dependent sex determination (which sees females produced below, and males above, 22 °C), extremely low basal metabolic rates and considerable longevity².

To provide insights into the biology of the tuatara, we have sequenced its genome in partnership with Ngātiwai, the Māori iwi (tribe) who hold kaitiakitanga (guardianship) over the tuatara populations located on islands in the far north of New Zealand. This partnership—which, to our knowledge, is unique among the genome projects undertaken to date—had a strong practical focus on developing resources and information that will improve our understanding of the tuatara and aid in future conservation efforts. It is hoped that this work will form an exemplar for future genome initiatives that aspire to meet access and benefit-sharing obligations to Indigenous communities.

We find that the tuatara genome—as well as the animal itself—is an amalgam of ancestral and derived characteristics. Tuatara has 2n=36chromosomes in both sexes, consisting of 14pairs of macrochromosomes and 4pairs of microchromosomes⁵. The genome size, which is estimated to be approximately 5Gb, is among the largest of the vertebrate genomes sequenced to date; this is predominantly explained by an extraordinary diversity of repeat elements, many of which are unique to the tuatara.

At least 64% of the tuatara genome assembly is composed of repetitive sequences, made up of transposable elements (31%) and low-copy-number segmental duplications (33%). Although the total transposable element content is similar to other reptiles⁷, the types of repeats we found appear to be more mammal-like than reptile-like. Furthermore, a number of the repeat families show evidence of recent activity and greater expansion and diversity than seen in other vertebrates (Fig. 2).

a, A phylogenetic analysis on the basis of the reverse transcriptase domain of L2 repeats identifies two L2 subfamilies; one typical of other lepidosaurs and one that is similar to platypus L2. This phylogeny is based on L2 elements >1.5-kb long with a reverse transcriptase domain of >200amino acids. b, Landscape plot of SINE retrotransposons suggests the tuatara genome is dominated by MIR sequences that are most typically associated with mammals; the tuatara genome is now the amniote genome in which the greatest MIR diversity has been observed. Only SINE subfamilies that occupy more than 1,000bp are shown. Definitions of the abbreviations of the SINE subfamilies follow: ACASINE2, Anolis carolinesis SINE family; AmnSINE1, Amniota SINE1; AnolisSINE2, A.carolinesis SINE2 family, LFSINE, lobe-finned fishes SINE; SINE−2019−L_tua, tuatara SINE; SINE-2019_Crp, Crocodylus porosus SINE; SINE2-1_tua, tuatara SINE2; tuaCR1-SINE1a and b, tuatara CR1-mobilized SINEs; MIR_Aves, avian MIR sequence; MIR1_Crp, C.porosus MIR sequence; MIR1_Saur, Sauropsida MIR sequence; tuaMIR, tuatara MIRs. c, The tuatara genome contains about 7,500 full-length, long-terminal-repeat retro-elements, including nearly 450endogenous retroviruses that span the five major retroviral clades. A Ty1/Copia element (Mtanga-like) is especially abundant, but Bel-Pao long-terminal-repeat retro-elements are absent. At least 37complete spumaretroviruses are present in the tuatara genome.

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L2 elements account for most of the long interspersed elements in the tuatara genome (10% of the genome), and some may still be active (Supplementary Information4). CR1 elements—the dominant long interspersed element in the genomes of other sauropsids⁸—are rare. CR1 elements comprise only about 4% of the tuatara genome (Fig. 2a, Supplementary Table 4.1), but some are potentially active (Supplementary Fig. 4.4). L1 elements, which are prevalent in placental mammals, account for only a tiny fraction of the tuatara genome (<1%) (Supplementary Table 4.1). However, we find that an L2 subfamily that is present in the tuatara, but is absent from other lepidosaurs, is also common in monotremes⁹ (Supplementary Figs. 4.3–4.5). Collectively, these data suggest that stem-sauropsid ancestors had a repeat composition that was very different from that inferred in previous comparisons using mammals, birds and lizards⁷.

Many of the short interspersed elements (SINEs) in the tuatara are derived from ancient common sequence motifs (CORE-SINEs), which are present in all amniotes¹⁰; however, at least 16SINE subfamilies were recently active in the tuatara genome (Fig. 2b, Supplementary Information5). Most of these SINEs are mammalian-wide interspersed repeats (MIRs), and the diversity of MIR subfamilies in the tuatara is the highest thus far observed in an amniote^11,12. In the human genome, hundreds of fossil MIR elements act as chromatin and regulatory domains¹³; the very recent activity of diverse MIR subfamilies in the tuatara suggests these subfamilies may have influenced regulatory rewiring on rather recent evolutionary timescales.

We detected 24newly identified and unique families of DNA transposon, which suggests frequent germline infiltration by DNA transposons through horizontal transfer in the tuatara¹⁴. At least 30subfamilies of DNA transposon were recently active, spanning a diverse range of cut-and-paste transposons and polintons (Supplementary Figs. 5.1, 5.2). This diversity is higher than that found in other amniotes¹⁵. Notably, we found thousands of identical DNA transposon copies, which suggests very recent—and/or ongoing—activity. Cut-and-paste transposition probably shapes the tuatara genome, as it does in bats¹⁵.

We identified about 7,500full-length, long-terminal-repeat retro-elements (including endogenous retroviruses), which we classified into 12groups (Fig. 2c, Supplementary Information6). The general spectrum of long-terminal-repeat retroelements in the tuatara is comparable to that of other sauropsids^7,15. We found at least 37complete spumaretroviruses, which are among the most ancient of endogenous retroviruses¹⁶, in the tuatara genome (Fig. 2c, Supplementary Figs. 6.1, 6.2).

The tuatara genome contains more than 8,000elements related to non-coding RNA. Most of these elements (about 6,900) derive from recently active transposable elements, and overlap with a newly identified CR1-mobilized SINE (Fig. 2b, Supplementary Information7). The remaining high-copy-number elements are sequences closely related to ribosomal RNAs, spliceosomal RNAs and signal-recognition particle RNAs.

Finally, a high proportion (33%) of the tuatara genome originates from low-copy-number segmental duplications; 6.7% of these duplications are of recent origin (on the basis of their high level of sequence identity (>94% identity)), which is more than seen in other vertebrates⁹. The tuatara genome is 2.4× larger than the anole genome, and this difference appears to be driven disproportionately by segmental duplications.

Overall, the repeat architecture of the tuatara is—to our knowledge—unlike anything previously reported, showing a unique amalgam of features that have previously been viewed as characteristic of either reptilian or mammalian lineages. This combination of ancient amniote features—as well as a dynamic and diverse repertoire of lineage-specific transposable elements—strongly reflects the phylogenetic position of this evolutionary relic.

Our low-coverage bisulfite-sequencing analysis found approximately 81% of CpG sites are methylated in tuatara (Fig. 3a)—the highest reported percentage of methylation for an amniote. This pattern differs from that observed in mouse, human (about 70%) and chicken (about 50%), and is more similar to that of Xenopus (82%) and zebrafish (78%). One possible explanation for this high level of DNA methylation is the large number of repetitive elements found in tuatara, many of which appear recently active and might be regulated via DNA methylation.

a, Methylation levels in the tuatara genome are high (mean 81%), but show no significant differences among the sexes (female n=13, mean=81.13, s.d.=1.55; male n=12; mean=81.02, s.d.−1.07). The black horizontal line represents the mean in each dataset. b, No single-nucleotide variant (SNV) is significantly differentiated with respect to sex in the tuatara genome. Each point represents a Pvalue from a test of sexual differentiation for a single SNV. The dashed line represents the threshold for statistical significance after accounting for multiple testing (n=28; 13 males and 15 females). Pvalues calculated using Fisher’s exact test, two-tailed test and corrected for multiple testing using the Bonferroni method. c, Pairwise sequential Markovian coalescent plot of the demographic history of tuatara using a mutation rate of 1.4×10⁻⁸ substitutions per site per generation and a generation time of 30years. d, We examined the three known axes of genetic diversity in tuatara: northern New Zealand (Little Barrier Island (LBI) (n=9)) and two islands in the Cook Strait (Stephens Island (SI) (n=9) and North Brother Island (NBI) (n=10)), using genotype-by-sequencing methods. Principal component (PC) analysis and structure plots demonstrate substantial structure among tuatara populations, and strongly support previous suggestions that the tuatara on the North Brother Island are genetically distinct and warrant separate management.

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The low normalized CpG content of the tuatara suggests its genome has endured substantial historic methylation¹⁷. The tuatara has a significantly bimodal distribution of normalized CpG (Extended Data Fig. 3) in all of the genomic regions we examined, a similarity it shares with other reptiles that have temperature-dependent sex determination¹⁷. The low normalized CpG count of the tuatara in non-promoter regions may result from methylation silencing of repeat elements, and the bimodality of normalized CpG promoters suggests dual transcriptional regulation (Extended Data Fig. 3, Supplementary Information8).

The mitochondrial genome in the tuatara reference animal is 18,078bp in size, containing 13protein-coding, 2ribosomal RNA and 22 transfer (t)RNA genes, a gene content typical among animals (Extended Data Fig. 4). This contradicts previous reports¹⁸ that the tuatara mitochondrial genome lacks three genes: ND5, tRNA^Thr and tRNA^His. These genes are found—with an additional copy of tRNA^Leu(CUN) and an additional non-coding block (which we refer to as NC2)—in a single segment of the mitochondrial genome. Three non-coding areas (NC1, NC2 and NC3) with control-region (heavy-strand replication origin) features, and two copies of tRNA^Leu(CUN) adjacent to NC1 and NC2, possess identical or near-identical sequences that are unique to the tuatara mitochondrial genome. These three non-coding regions may be a result of concerted evolution.

As befits the taxonomic distinctiveness of the tuatara, we find that its genome displays multiple innovations in genes that are associated with immunity, odour reception, thermal regulation and selenium metabolism.

Genes of the major histocompatibility complex (MHC) have an important role in disease resistance, mate choice and kin recognition, and are among the most polymorphic genes in the vertebrate genome. Our annotation of MHC regions in the tuatara, and comparisons of the gene organization with that of six other species, identified 56MHC genes (Extended Data Fig. 5, Supplementary Information9).

Of the six comparison species, the genomic organization of tuatara MHC genes is most similar to that of the green anole, which we interpret as typical for Lepidosauria. Tuatara and other reptiles show a gene content and complexity more similar to the MHC regions of amphibians and mammals than to the highly reduced MHC of birds. Although the majority of genes annotated in the tuatara MHC are well-conserved as one-to-one orthologues, we observed extensive genomic rearrangements among these distant lineages.

The tuatara is a highly visual predator that is able to capture prey under conditions of extremely low light². Despite the nocturnal visual adaptation of the tuatara, it shows strong morphological evidence of an ancestrally diurnal visual system¹⁹. We identified all five of the vertebrate visual opsin genes in the tuatara genome (Supplementary Information10).

Our comparative analysis revealed one of the lowest rates of visual-gene loss known for any amniote, which contrasts sharply with the high rates of gene loss observed in ancestrally nocturnal lineages (Extended Data Fig. 6). Visual genes involved in phototransduction showed strong negative selection and no evidence for the long-term shifts in selective pressures that have been observed in other groups with evolutionarily modified photoreceptors²⁰. The retention of five visual opsins and the conserved nature of the visual system also suggests tuatara possess robust colour vision, potentially at low light levels. This broad visual repertoire may be explained by the dichotomy in tuatara life history: juvenile tuatara often take up a diurnal and arboreal lifestyle to avoid the terrestrial, nocturnal adults that may predate them². Collectively, these results suggest a unique path to nocturnal adaptation in tuatara from a diurnal ancestor.

Odorant receptors are expressed in the dendritic membranes of olfactory receptor neurons and enable the detection of odours. Species that depend strongly on their sense of smell to interact with their environment, find prey, identify kin and avoid predators may be expected to have a large number of odorant receptors. The tuatara genome contains 472predicted odorant receptors, of which 341sequences appear intact (Supplementary Information11). The remainder lack the initial start codon, have frameshifts or are presumed to be pseudogenes. Many odorant receptors were found as tandem arrays, with up to 26genes found on a single scaffold.

The number and diversity of odorant receptor genes varies greatly in Sauropsida: birds have 182–688such genes, the green anole lizard has 156genes, and crocodilians and testudines have 1,000–2,000 genes²¹. The tuatara has a number of odorant receptors similar to that of birds, but contains a high percentage of intact odorant receptor genes (85%) relative to published odorant receptor sets from the genomes of other sauropsids. This may reflect a strong reliance on olfaction by tuatara, and therefore pressure to maintain a substantial repertoire of odorant receptors (Extended Data Fig. 7). There is some evidence that olfaction has a role in identifying prey², as well as suggestions that cloacal secretions may act as chemical signals.

The tuatara is a behavioural thermoregulator, and is notable for having the lowest optimal body temperature of any reptile (16–21 °C). Genes that encode transient receptor potential ion channels (TRP genes) have an important role in thermoregulation, as these channels participate in thermosensation and cardiovascular physiology²²; this led us to hypothesize that TRP genes may be linked to the thermal tolerance of the tuatara. Our comparative genomic analysis of TRP genes in the tuatara genome identified 37TRP-like sequences, spanning all 7known subfamilies of TRP genes (Extended Data Fig. 8, Supplementary Information12)— an unusually large repertoire of TRP genes.

Among this suite of genes, we identified thermosensitive and non-thermosensitive TRP genes that appear to result from gene duplication, and have been differentially retained in the tuatara. For example, the tuatara is unusual in possessing an additional copy of a thermosensitive TRPV-like gene (TRPV1/2/4, sister to the genes TRPV1, TRPV2 and TRPV4) that has classically been linked to the detection of moderate-to-extreme heat²²—a feature it shares with turtles. A strong signature of positive selection among heat-sensitive TRP genes (TRPA1, TRPM and TRPV) was also observed.

In general, these results show a high rate of differential retention and positive selection in genes for which a function in heat sensation is well-established²². It therefore seems probable that the genomic changes in TRP genes are associated with the evolution of thermoregulation in tuatara.

Barring tortoises, tuatara are the longest lived of the reptiles—probably exceeding 100years of age². This enhanced lifespan may be linked to genes that afford protection against reactive oxygen species. One class of gene products that affords such protection is the selenoproteins. The human genome encodes 25selenoproteins, the roles of which include antioxidation, redox regulation, thyroid hormone synthesis and calcium signal transduction, among others²³.

We identified 26genes that encode selenoproteins in the tuatara genome, as well as 4selenocysteine-specific tRNA genes; all of these appear to be functional (Supplementary Information13). Although further work is needed, the additional selenoprotein gene (relative to the human genome) and the selenocysteine-specific tRNA genes may be linked to the longevity of tuatara or might have arisen as a response to the low levels of selenium and other trace elements in the terrestrial systems of New Zealand.

Tuatara has a unique mode of temperature-dependent sex determination, in which higher temperatures during egg incubation result in males². We found orthologues for many genes that are known to act antagonistically in masculinizing (for example, SF1 and SOX9) and feminizing (for example, RSPO1 and WNT4) gene networks to promote testicular or ovarian development, respectively²⁴. We also found orthologues of several genes that have recently been implicated in temperature-dependent sex determination, including CIRBP²⁴ (Supplementary Information17, Supplementary Table 17.2). Tuatara possess no obviously differentiable sex chromosomes⁵, and we found no significant sex-specific differences in global CG methylation (Fig. 3a) and no sex-specific single-nucleotide variants between male and female tuatara (Fig. 3b). On a gene-by-gene basis, sex-specific differences in methylation and gene expression patterns probably exist, but this remains to be investigated.

Our phylogenomic analyses, which incorporated both whole-genome alignments and clusters of single-copy orthologues (Supplementary Information14, 15) recapitulated many patterns that have been observed in the fossil record and corroborated during the genomic era (Fig. 1). After their appearance about 312million years ago²⁵, amniote vertebrates diversified into two groups: the synapsids (which include all mammals) and the sauropsids (which include all reptiles and birds). We obtained full phylogenomic support for a monophyletic Lepidosauria, marked by the divergence of the tuatara lineage from all squamates (lizards and snakes) during the early part of the Triassic period at about 250million years ago, as estimated using a penalized likelihood method (Fig. 1, Supplementary Information14–16).

The rate of molecular evolution in the tuatara has previously been suggested to be paradoxically high, in contrast to the apparently slow rate of morphological evolution^26,27. However, we find that the actual divergence in terms of DNA substitutions per site per million years at fourfold degenerate sites is relatively low, particularly with respect to lizards and snakes; this makes the tuatara the slowest-evolving lepidosaur yet analysed (Extended Data Fig. 9a, b). We also find that in general amniote evolution can be described by a model of punctuated evolution, in which the amount of genomic change is related to the degree of species diversification within clades^28,29. The tuatara falls well below this trend, accumulating substitutions at a rate expected given the lack of rhynchocephalian diversity (Extended Data Fig. 9c, Supplementary Information16). This suggests that rates of phenotypic and molecular evolution were not decoupled throughout the evolution of amniotes³⁰.

Once widespread across the supercontinent of Gondwana, Rhynchocephalia is now represented by a single species (the tuatara) found on a few islands offshore of New Zealand (Fig. 1c). Historically, tuatara declined in range and numbers because of introduced pests and habitat loss². They remain imperilled owing to their highly restricted distribution, threats imposed by disease and changes in sex ratios induced by climate change that could markedly affect their survival³¹. Previous work has found that populations in northern New Zealand are genetically distinct from those in the Cook Strait, and that the population on North Brother Island in the Cook Strait might be a distinct species³. Although subsequent studies have not supported species status for the population on North Brother Island³², it is managed as a separate conservation unit.

We used the tuatara reference genome to perform ancestral demographic and population genomic analyses of this species. First, we investigated genome-wide signals for demographic change using a pairwise sequentially Markovian coalescent method (Supplementary Information18). Our reconstructed demography (Fig. 3c) reveals an increase in effective population size (N_e) that is detectable around 10million years ago, a marked decrease in N_e about 1–3million years ago and a rapid increase in N_e between 500 thousand years ago and 1 million years ago. These events correlate well with the known geological history of New Zealand³³, and may reflect an increase in available landmass subsequent to Oligocene drowning, a period of considerable climatic cooling that probably reduced tuatara habitat and the formation of land bridges that facilitated population expansion.

Our population genomic analyses examined the major axes of genetic diversity in tuatara^32,34, and revealed substantial genetic structure (Fig. 3d, Supplementary Information19). Our genome-wide estimate of the fixation index (F_ST) is 0.45, and more than two-thirds of variable sites have an allele that is restricted to a single island. All populations have relatively low genetic diversity (nucleotide diversity ranges from 8×10⁻⁴ for North Brother Island to 1.1×10⁻³ for Little Barrier Island). The low within-population diversity and marked population structure we observe in the tuatara suggests that the modern island populations were isolated from each other sometime during the Last Glacial Maximum at about 18 thousand years ago.

Our results also support the distinctiveness of the North Brother Island tuatara, which has variously been described as S.punctatus or Sphenodon guntheri^3,32. This population is highly inbred and shows evidence of a severe bottleneck, which most probably reflects a founder event around the time of the last glaciation³⁴. It is not clear whether the distinctiveness we observe is due to changes in allele frequency brought about by this bottleneck, or is reflective of a deeper split in the population history of tuatara. Regardless, this population is an important source of genetic diversity in tuatara, possessing 8,480private alleles. Although we support synonymization of S.punctatus and S.guntheri³², the ongoing conservation of the North Brother Island population as an independent unit is recommended.

The tuatara has a genomic architecture unlike anything previously reported, with an amalgam of features that have previously been viewed as characteristic of either mammals or reptiles. Notable among these features are unusually high levels of repetitive sequences that have traditionally been considered mammalian, many of which appear to have been recently active, and—to our knowledge—the highest level of genome methylation thus far reported. We also found a mitochondrial-genome gene content at odds with previously published reports that omitted the ND5 gene¹⁸; this gene is present, nested within a repeat-rich region of the mitochondrial DNA.

Our phylogenetic studies provide insights into the timing and speed of amniote evolution, including evidence of punctuated genome evolution across this phylogeny. We also find that, in contrast to previous suggestions that the evolutionary rate for tuatara is exceptionally fast²⁶, it is the slowest-evolving lepidosaur yet analysed.

Our investigations of genomic innovations identified genetic candidates that may explain the ultra-low active body temperature, longevity and apparent resistance to infectious disease in tuatara. Further functional exploration will refine our understanding of these unusual facets of tuatara biology, and the tuatara genome itself will enable many future studies to explore the evolution of complex systems across the vertebrates in a more complete way than has previously been possible.

Our population genomic work reveals considerable genetic differences among tuatara populations, and supports the distinctiveness of the North Brother Island tuatara.

Finally, this genome will greatly aid in future work on population differentiation, inbreeding and local adaptation in this global icon, the last remaining species of the once globally dominant reptilian order Rhynchocephalia.

No statistical methods were used to predetermine sample size. The experiments were not randomized and investigators were not blinded to allocation during experiments and outcome assessment.

A full description of the methods can be found in theSupplementary Information.

Sampling and sequencing

A blood sample was obtained from a large male tuatara from Lady Alice Island (35° 53′ 24.4′′ S 174° 43′ 38.2′′ E) (New Zealand), with appropriate ethical permissions and iwi consultation and support (Supplementary Information20). Total genomic DNA and RNA were extracted and sequenced using the Illumina HiSeq 2000 and MiSeq sequencing platforms (Illumina) supported by New Zealand Genomics (Supplementary Information1).

Genome, transcriptome and epigenome

Raw reads were de novo-assembled using Allpaths-LG (version 49856). With a total input data of 5,741,034,516 reads for the paired-end libraries and 2,320,886,248 reads of the mate-pair libraries, our optimal assembly used 85% of the fragment libraries and 100% of the jumping libraries (Supplementary Information1.4). We further scaffolded the assembly using Chicago libraries and HiRise (Supplementary Information1.3).

We assembled a de novo transcriptome as a reference for read-mapping using total RNA derived from the blood of our reference male tuatara, and a collection of transcriptomic data previously collected from early-stage embryos³⁵. In total, we had 131,580,633 new 100-bp read pairs and 60,637,100 previous 50-bp read pairs. These were assembled using Trinity v.2.2.0 (Supplementary Information1.4).

Low-coverage bisulfite sequencing was undertaken using a modified post-bisulfite adaptor tagging method to explore global patterns of methylation in the genome for 12 male and 13 female tuatara (Fig. 3d, Supplementary Information1.5).

Repeat and gene annotation

We used a combination of ab initio repeat identification in CARP/RepeatModeler/LTRharvest, manual curation of specific newly identified repeats, and hom*ology to repeat databases to investigate the repeat content of the tuatara genome (Supplementary Information1.6). From these three complementary repeat identification approaches, the CARP results were in-depth-annotated for long interspersed elements and segmental duplications (Supplementary Information4), the RepeatModeler results were in-depth-annotated for SINEs and DNA transposons (Supplementary Information5), and the LTRharvest results were in-depth-annotated for long-terminal-repeat retrotransposons (Supplementary Information6).

For the gene annotation, we used RepeatMasker (v.4.0.3) along with our partially curated RepeatModeler library plus the Repbase sauropsid repeat database to mask transposable elements in the genome sequence before the gene annotation. We did not mask simple repeats at this point to allow for more efficient mapping during the hom*ology-based step in the annotation process. Simple repeats were later soft-masked and protein-coding genes predicted using MAKER2. We used anole lizard (A.carolinensis, version AnoCar2.0), python (Python bivittatus, version bivittatus-5.0.2) and RefSeq (www.ncbi.nlm.nih.gov/refseq) as protein hom*ology evidence, which we integrated with ab initio gene prediction methods including BLASTX, SNAP and Augustus. Non-coding RNAs were annotated using Rfam covariance models (v.13.0) (Supplementary Information7).

Orthologue calling

We performed a phylogenetic analysis to infer orthology relationships between the tuatara and 25other species using the Ensembl GeneTree method (Supplementary Information Tables 2.1, 2.2). Multiple-sequence alignments, phylogenetic trees and hom*ology relationships were extracted in various formats (https://zenodo.org/record/2542571). We also calculated the gene order conservation score, which uses local synteny information around a pair of orthologous genes to compute how much the gene order is conserved. For each of these species, we chose the paralogue with the best gene order conservation score and sequence similarity, which resulted in a total set of 3,168 clusters of orthologues (Supplementary Information2, Table 2.3).

Gene tree reconstructions and substitution rate estimation

We constructed phylogenies using only fourfold-degenerate-site data derived from whole-genome alignments for 27 tetrapods, analysed as a single partition in RAxML v.8.2.3. Using the topology and branch lengths obtained from the best maximum likelihood phylogeny, we estimated absolute rates of molecular evolution in terms of substitution per site per million years and estimated the divergence times of amniotes via the semiparametric penalized likelihood method in r8s v.1.8 (Supplementary Information14.5).

We also generated gene trees on the basis of 245 single-copy orthologues found between all species using a maximum-likelihood-based multi-gene approach (Supplementary Information15). Sequences were aligned using the codon-based aligner PRANK. The FASTA format alignments were then converted to PHYLIP using the catfasta2phyml.pl script (https://github.com/nylander/catfasta2phyml). Next, we used the individual exon PHYLIP files for gene tree reconstruction using RaxML using a GTR + G model. Subsequently, we binned all gene trees to reconstruct a species tree and carried out bootstrapping using Astral (Supplementary Information15, Supplementary Fig. 15.1).

Divergence times and tests of punctuated evolution

We inferred time-calibrated phylogenies with BEAST v.2.4.8 using the CIPRES Science Gateway to explore divergence times (Supplementary Information16.1). We then used Bayesian phylogenetic generalized least squares to regress the total phylogenetic path length (of fourfold-degenerate sites) on the net number of speciation events (nodes in a phylogenetic tree) as a test for punctuated evolution (Supplementary Information16.2).

Analysis of genomic innovations

We explored the genomic organization and sequence evolution of genes associated with immunity, vision, smell, thermoregulation, longevity and sex determination (Supplementary Information8–13). Tests of selection were undertaken across multiple genes, including those linked to metabolism, vision and sex determination using multispecies alignments and PAML (Supplementary Information17).

Population genomics

Demographic history was inferred from the diploid sequence of our tuatara genome using a pairwise sequential Markovian coalescent method (Supplementary Information18). We also sampled 10 tuatara from each of three populations that span the main axes of genetic diversity in tuatara (Supplementary Information19, Table 19.1), and used a modified genotype-by-sequencing approach to obtain the SNVs that we used for population genomic analysis, investigations of loci associated with sexual phenotype and estimates of genetic load (Supplementary Information19).

Permits and ethics

This project was undertaken in partnership with Ngatiwai and in consultation with other iwi who are kaitiaki of tuatara (Supplementary Information20). Samples were collected under Victoria University of Wellington Animal Ethics approvals 2006R12; 2009R12; 2012R33; 22347 and held and used under permits 45462-DOA and 32037-RES 32037-RES issued by the New Zealand Department of Conservation.

Reporting summary

Further information on research design is available in theNature Research Reporting Summary linked to this paper.

Authors and Affiliations

1. Department of Anatomy, University of Otago, Dunedin, New Zealand

   Neil J. Gemmell,Kim Rutherford,Tim A. Hore,Nicolas Dussex,Helen Taylor,Hideaki Abe&Donna M. Bond

2. LOEWE-Center for Translational Biodiversity Genomics, Senckenberg Museum, Frankfurt, Germany

   Stefan Prost

3. South African National Biodiversity Institute, National Zoological Garden, Pretoria, South Africa

   Stefan Prost

4. School of Life Sciences, Arizona State University, Tempe, AZ, USA

   Marc Tollis,Melissa Wilson&Shawn M. Rupp

5. School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA

   Marc Tollis

6. School of Fundamental Sciences, Massey University, Palmerston North, New Zealand

   David Winter

7. Peralta Genomics Institute, Oakland, CA, USA

   J. Robert Macey,Charles G. Barbieri&Dustin P. DeMeo

8. School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia

   David L. Adelson,Terry Bertozzi,Lu Zeng,R. Daniel Kortschak&Joy M. Raison

9. Department of Ecology and Genetics – Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, Uppsala, Sweden

   Alexander Suh,Valentina Peona,Claire R. Peart&Vera M. Warmuth

10. Department of Organismal Biology – Systematic Biology, Evolutionary Biology Centre (EBC), Uppsala University, Uppsala, Sweden

    Alexander Suh&Valentina Peona

11. Evolutionary Biology Unit, South Australian Museum, Adelaide, South Australia, Australia

    Terry Bertozzi

12. Amedes Genetics, Amedes Medizinische Dienstleistungen, Berlin, Germany

    José H. Grau

13. Museum für Naturkunde Berlin, Leibniz-Institut für Evolutions- und Biodiversitätsforschung an der Humboldt-Universität zu Berlin, Berlin, Germany

    José H. Grau

14. Department of Earth Sciences, Montana State University, Bozeman, MT, USA

    Chris Organ

15. Department of Biochemistry, University of Otago, Dunedin, New Zealand

    Paul P. Gardner

16. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK

    Matthieu Muffato,Mateus Patricio,Konstantinos Billis,Fergal J. Martin&Paul Flicek

17. Section for Evolutionary Genomics, The GLOBE Institute, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

    Bent Petersen

18. Edward Via College of Osteopathic Medicine, Blacksburg, VA, USA

    Lin Kang&Pawel Michalak

19. Center for One Health Research, Virginia–Maryland College of Veterinary Medicine, Blacksburg, VA, USA

    Pawel Michalak

20. Institute of Evolution, University of Haifa, Haifa, Israel

    Pawel Michalak

21. Manaaki Whenua - Landcare Research, Auckland, New Zealand

    Thomas R. Buckley&Victoria G. Twort

22. School of Biological Sciences, The University of Auckland, Auckland, New Zealand

    Thomas R. Buckley&Victoria G. Twort

23. School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia

    Yuanyuan Cheng

24. Biomatters, Auckland, New Zealand

    Hilary Miller

25. Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA

    Ryan K. Schott

26. The New Zealand Institute for Plant and Food Research, Auckland, New Zealand

    Melissa D. Jordan&Richard D. Newcomb

27. Departamento de Ecología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile

    José Ignacio Arroyo

28. Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA

    Nicole Valenzuela,Valeria Velásquez Zapata&Zhiqiang Wu

29. Instituto de Investigaciones Biomédicas ‘Alberto Sols’ CSIC-UAM, Madrid, Spain

    Jaime Renart

30. Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximilian University of Munich, Planegg-Martinsried, Germany

    Claire R. Peart&Vera M. Warmuth

31. Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Universitat Pompeu Fabra (UPF), Barcelona, Spain

    Didac Santesmasses,Marco Mariotti&Roderic Guigó

32. School of Biological Sciences, University of Canterbury, Christchurch, New Zealand

    James M. Paterson

33. Global Genome Initiative, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA

    Daniel G. Mulcahy&Vanessa L. Gonzalez

34. Austrian Institute of Technology (AIT), Center for Health and Bioresources, Molecular Diagnostics, Vienna, Austria

    Stephan Pabinger

35. AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand

    Tracey Van Stijn&Shannon Clarke

36. San Diego Zoo Institute for Conservation Research, Escondido, CA, USA

    Oliver Ryder

37. Department of Organismic and Evolutionary Biology and the Museum of Comparative Zoology, Harvard University, Cambridge, MA, USA

    Scott V. Edwards

38. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Steven L. Salzberg

39. School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand

    Lindsay Anderson&Nicola Nelson

40. Ngatiwai Trust Board, Whangarei, New Zealand

    Clive Stone,Clive Stone,Jim Smillie&Haydn Edmonds

Consortia

Contributions

N.J.G. designed the original concept and scientific objectives and oversaw the project and analyses. N.J.G., L.A., N.N., H.T., O.R., S.V.E., C.S. contributed samples or assisted in sample preparation and permitting. N.J.G., K.M.R., S.P., M.T., D.W., J.R.M., D.L.A., A.S., T.B., J.H.G., C.O., P.P.G., M.M. M.P., K.B., F.J.M., P.F., B.P., L.K., P.M., T.R.B., M.W., Y.C., H.M., R.K.S., M.D.J., R.D.N., J.I.A., N.V., T.A.H., J.R., V.P., C.R.P., V.M.W., L.Z., R.D.K., J.M.R., V.V.Z., Z.W., D.S., M. Mariotti, R.G., S.M.R., V.G.T., N.D., H.A., D.M.B, J.M.P., D.G.M., V.L.G., C.G.B., D.P.D., S. Pabinger, T.v.S., S.C., S.L.S. planned and carried out experiments or analyses. N.J.G., K.M.R., S.P., M.T., D.W., J.R.M., D.L.A., A.S., T.B., J.H.G., C.O., P.P.G., M. Muffato. M.P., K.B., F.J.M., B.P., L.K., P.M., T.R.B., M.W., Y.C., H.M., R.K.S., M.D.J., R.D.N., J.I.A., N.V., T.A.H., J.R., V.P., C.R.P., V.M.W., L.Z., R.D.K., J.M.R., V.V.Z., Z.W., D.S., M. Mariotti, R.G., S.M.R., V.G.T., N.D., H.T., H.A., J.M.P., D.G.M., V.L.G., C.G.B., D.P.D., S. Pabinger, S.L.S. contributed to the interpretation and presentation of results in the main manuscript and supplementary documents. N.J.G. wrote the first draft of the manuscript with input from all other authors.

Corresponding author

Correspondence to Neil J. Gemmell.

Competing interests

The authors declare no competing interests.

Peer review information Nature thanks Rebecca Johnson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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