Ciliates are unique among unicellular organisms in that they separate germline and somatic functions1. Each cell harbours two kinds of nucleus, namely silent diploid micronuclei and highly polyploid macronuclei. The latter are unusual in that they contain an extensively rearranged genome streamlined for expression and divide by a non-mitotic process. Only micronuclei undergo meiosis to perpetuate genetic information; the macronuclei are lost at each sexual generation and develop anew from the micronuclear lineage.

In Paramecium the exact number of micronuclear chromosomes (more than 50) and the structures of their centromeres and telomeres remain unknown. During macronuclear development, these chromosomes are amplified to about 800 copies and undergo two types of DNA elimination event. Tens of thousand of short, unique copy elements (internal eliminated sequences) are removed by a precise mechanism that leads to the reconstitution of functional genes2.

Transposable elements and other repeated sequences are removed by an imprecise mechanism leading either to chromosome fragmentation and de novo telomere addition or to variable internal deletions3. These rearrangements occur after a few rounds of endoreplication, leading to some heterogeneity in the sequences abutting the imprecisely eliminated regions3. The sizes of the resulting, acentric macronuclear chromosomes range from 50-1,000 kilobases (kb) as measured by pulsed-field gel electrophoresis. Because the sexual process of autogamy results in an entirely homozygous genotype4, the macronuclear DNA that was sequenced was genetically homogeneous.

The Paramecium genome sequence

The Paramecium macronuclear genome sequence was established with the use of a whole-genome shotgun and assembly strategy. Paired-end sequencing of plasmid and bacterial artificial chromosome (BAC) clones provided a coverage of 13 genome equivalents (Supplementary Table S1). We assembled the sequence reads with Arachne5 in 1,907 contigs connected in 697 scaffolds of size greater than 2 kb, giving a total coverage of 72 Mb. Half of the assembly is contained in 64 scaffolds larger than 413 kb (the N50 size), and 96% of the assembly (69 Mb) in 188 scaffolds larger than 45 kb. A majority of the 188 largest scaffolds are complete macronuclear chromosomes, as determined by analysis of telomere repeats, and on average they contain one gap every 120 kb with a mean estimated size of 0.66 kb (Supplementary Table S2). The largest scaffold, 981 kb long, corresponds to the largest chromosome observed by pulsed-field analysis. Consistent with the estimated gap frequency and sizes, alignment of this scaffold with the finished, independently determined, reference sequence of that chromosome6 revealed only four small gaps (less than 250 bases), and less than one difference per 6 kb. If this chromosome is representative, then the present assembly contains more than 99% of the genome sequence with more than 99.95% accuracy.

The Paramecium macronuclear genome has a composition of 28% G + C and is devoid of highly repeated sequences (Supplementary Figure S1). The CpG dinucleotide frequency is severely depressed (0.42-fold the expected value) and this cannot be accounted for by codon usage (Supplementary Table S3). In plant and vertebrate genomes, CpG depression is thought to be a consequence of cytosine methylation, but cytosine methylation has never been observed in Paramecium.

The genome sequence was annotated by using a combination of ab initio predictions, comparative genomics and complementary DNA alignments. A specific resource of about 90,000 expressed sequence tags (ESTs) from six physiological states or developmental stages of Paramecium was generated for this purpose. The current protein-coding catalogue is composed of 39,642 genes (Table 1). About 55% of predicted Paramecium proteins have no currently referenced InterPro domain, a surprisingly high percentage that probably reflects the great evolutionary distance between Paramecium and other eukaryotic genomes sequenced so far. The macronuclear genome is compact (78% coding density), with extremely small intergenic regions (352 bases on average) and introns (25 bp on average). Remarkably, in contrast with other compact genomes, Paramecium genes contain many introns and have an intron/exon ratio closer to that of some invertebrates such as D. melanogaster than to that of other sequenced unicellular eukaryotes (Table 1). When looking at the ESTs mapped to each annotated gene, we found no evidence of exon skipping. Adaptation of the splicing machinery to the reduced intron sizes may be incompatible with alternative splicing.

Table 1 Comparison of P. tetraurelia gene characteristics with selected sequenced eukaryotes

The ciliate clade is generally considered to have evolved from an ancestor with a red algal endosymbiont that gave rise to all extant species of the chromist and alveolate groups (the ‘chromalveolate’ hypothesis)7. We failed to find any clear case of genes characteristic of the algal lineage, or of genes of chloroplastic origin (see Supplementary Information). This implies that ciliates may have lost all traces of this ancient event because they no longer need photosynthesis or other algal-associated functions. Alternatively, endosymbiosis might not have occurred at the root of the chromalveolate lineage. In this hypothesis, the plastid-derived genes observed in apicomplexan parasites may be the result of a symbiotic event that occurred after their separation from the ciliate lineage.

A surprising result of the annotation process was the prediction of 39,642 protein-coding genes, a number unlikely to be an artefact of the gene prediction procedure (see Supplementary Table S5). P. tetraurelia is among the most gene-rich organisms yet sequenced, including many metazoans and plants. Using all-against-all comparisons, we observed that many of the protein-coding genes in Paramecium are present in closely related gene families (not shown). This redundancy may explain the high gene number.

Genome duplications

We aligned each protein against the whole proteome to identify duplicated genes (see Methods). This yields a complete picture of a whole-genome duplication (WGD) linking two by two all of the 188 large scaffolds (example in Fig. 1 and global view in the outer circle of Fig. 2).

Figure 1: Comparison of two scaffolds originating from a common ancestor at the recent WGD.
figure 1

Each arrow represents one gene with its direction of transcription. Brown arrows are genes with a detected paralogue, and pink arrows are genes with no paralogue. Paralogy relations are indicated by a solid line, red for genes with a BRH match, and blue for genes with a non-BRH syntenic match. Genes at the telomeric ends have paralogues scattered between different chromosomes, probably as a result of frequent recombination.

Figure 2: Representation of the successive duplications of the Paramecium genome.
figure 2

The exterior circle displays all chromosome-sized scaffolds, and the three interior circles show the reconstructed sequences obtained by fusion of the paired sequences from each previous step. Red lines link pairs of genes with a BRH match, and blue lines link pairs of genes with a non-BRH match that were added on the basis of syntenic position. Only the BRHs that link two genes in the same paralogon are represented. The position of an ancestral block is unrelated to the position of its constituents in the previous circle.

One remarkable characteristic of this WGD is the conservation of synteny: only 8 translocations and 76 internal inversions of chromosomal segments could be deduced. We found 10 instances in which two scaffolds ending in telomeres were paired with a single, longer scaffold, indicating that the germline fragmentation regions (for example transposons) might have moved since the WGD. However, validation of this will require examination of the corresponding micronuclear regions, because DNA elimination events that lead to chromosome fragmentation can also resolve to internal deletions. A second striking feature of this recent duplication is the number of genes retained in duplicate. About 68% of the proteome is composed of two-gene families originating from this event, whereas only 32% corresponds to genes returned to a single state by the loss of one of the two paralogues. This translates into 51% of the preduplication genes still present in two copies, corresponding to 12,026 ancestral genes, a number far greater than for any previously studied WGD. The recent Paramecium WGD thus contrasts with the WGDs discovered in yeast, fish or higher plants in recent years, in which synteny, or duplicate gene conservation, is greatly eroded and the WGD events could not always be detected without comparison with a non-duplicated reference genome8,9,10,11,12,13,14,15,16,17.

All Paramecium chromosomes seem to be conserved after the duplication, and the 11,451 genes lost since the WGD seem to have disappeared through local decay mechanisms acting on a single gene or small region (Supplementary Fig. S11). The fact that we could detect a wide range of decay states (Supplementary Table S8 and Supplementary Fig. S12), indicates that pseudogenization might not have occurred abruptly after the WGD event, and we cannot exclude the possibility that some of these regions are still present in the micronuclear genome but are no longer amplified during macronuclear development18. We estimate the number of recent pseudogenes present in the annotated genes to be about 1,500 (see Supplementary Information).

We inferred the ancient gene order on the basis of the actual chromosomes (see Methods), revealing that two other WGD events had occurred before the recent WGD (Fig. 2, second and third circles from the outside). In comparison with the recent WGD, the number of genes conserved is smaller, as is the average similarity between paralogues (Table 2 and Fig. 3). We calculate the number of protein-coding genes in the ancestral genome before the three WGD events to be 19,552 by extrapolation of the number of genes present in the paralogons (paralogons are pairs of paralogous blocks that could be recognized as deriving from a common ancestral region). Therefore, taken together, the three WGDs have led to an approximate doubling of the gene count, explaining most of the gene number paradox in P. tetraurelia.

Table 2 Gene content of the paralogons for each duplication
Figure 3: Percentage identity between paralogous proteins, and comparisons with inter-species distances.
figure 3

a, Percentage identity is plotted as a function of the percentage of cases for paralogues originating from the recent (black), intermediary (red) and old (green) WGDs and from the ancient duplicates (blue). b, Comparison of the three WGD plots with the distribution of orthologous matches between human and mouse (orange broken line), between human and the fish Tetraodon (brown broken line), and between Paramecium and Tetrahymena thermophila (pink broken line).

Application of the reconstruction and matching method a third time revealed a significant number of duplicated blocks with 436 duplicated genes (Fig. 2, innermost circle), and yet lower similarity between paralogues (Fig. 3a). It is therefore probable that the Paramecium lineage underwent a fourth, more ancient, WGD. The paralogous genes obtained in the final round of reconstruction, near detection limits, are called ‘ancient duplicates’, with no assumption as to their origin.

Nuclear dimorphism in Paramecium may have helped in tolerating WGD, because the ploidy of the expressed macronucleus is subject to physiological regulation to maintain a constant nucleocytoplasmic ratio19; it is therefore possible that a sudden duplication of the micronuclear genome does not alter macronuclear ploidy. However, it is not clear whether this influences the recurrent appearance of WGDs, which have been found in other taxa without nuclear dimorphism9,10.

Retention and evolution of duplicate genes

The nature of the duplicated genes that are retained or not after a WGD can shed light on the still debated forces shaping the genome in the wake of these drastic molecular events20. Most studied WGDs are ancient and have provided clues about their long-term effects. In particular, over-retention of signalling molecules and transcription factors has been observed, linking WGD with the evolution of regulatory complexity21,22. Short-term effects have not been easy to track. Very different theories on the forces that drive the retention or loss of gene duplicates include buffering for essential genes, enhancement of metabolic fluxes, protein dosage effects and rapid divergence of gene pairs23,24,25,26,27,28. Because these models predict different retention outcomes according to gene classes, we analysed the predicted gene categories in Paramecium for their propensity for duplicate retention.

The relative expression levels of proteins involved in the same complex (or metabolic pathway; see below) must be balanced to ensure proper stoichiometry within the complex24. Thus, if duplicated genes are involved in a protein complex, the loss of one gene copy is expected to be counterselected unless it is compensated for by the upregulation of the other copy or by gene losses of other partners. To test this hypothesis we defined Paramecium orthologues of Saccharomyces cerevisiae genes involved in known complexes (Comprehensive Yeast Genome Database (CYGD) on the MIPS website (, and ref. 29). Because we retained only clear orthologues between the two species, we expect most of the detected proteins to have ancient conserved functions and therefore a high probability of belonging to conserved complexes. We observed a strong over-retention of genes from the recent WGD involved in known complexes (Fig. 4a). The absence of any common functional theme among the complexes analysed here makes it unlikely that there has been enrichment of specific functions. In contrast, the copy number of each protein within a complex is significantly correlated with that of the other components of the complex (P-value details are given in Supplementary Tables S9 and S10). We concluded that stoichiometry of the proteins constituting most complexes tends to be conserved. It has been previously shown that imbalance in the concentration of complex components can frequently be harmful24. A key function for stoichiometry in this covariation is supported by two observations. First, the conservation of gene duplicates in a complex sometimes arises from the retention of genes originating from different duplication events, resulting in identical copy numbers for each protein (Supplementary Table S11). Second, proteins involved in many different complexes are highly retained in the recent WGD but are completely absent as retained duplicates from the old WGD (Supplementary Fig. S20). This indicates that gene loss for complex constituents might be a two-step process, in which proteins with many interactions are preferentially lost as more genes are inactivated, after a first period of preferential conservation to maintain the initial stoichiometry.

Figure 4: Retention of duplicated genes according to biological criteria.
figure 4

For each curve, a value of 1 means that the retention of duplicates in one particular category is equal to the mean retention for all the genes. Values below 1 indicate under-retention and values over 1 indicate over-retention. a, Retention rates for proteins forming known complexes in S. cerevisiae. Each point represents the ratio of duplicated to non-duplicated genes for genes in complexes in S. cerevisiae with orthologues in P. tetraurelia, divided by the ratio of total duplicated genes to non-duplicated genes for each duplication. The blue curve is for orthologues of the CYGD list (, and the red curve is for orthologues of ref. 29. b, Retention of gene duplicates in central metabolic pathways: blue, amino-acid metabolism; red, carbohydrate metabolism; green, energy metabolism; orange, lipid metabolism; purple, nucleotide metabolism. Each point represents the ratio of duplicated to non-duplicated genes for genes with unambiguous EC number, divided by the ratio of total duplicated genes to non-duplicated genes for each duplication. c, Expression versus retention across the three WGDs. Each point represents the ratio of duplicated to non-duplicated genes for genes with a defined number of EST matches, divided by the ratio of total duplicated genes to non-duplicated genes for each duplication. Yellow, zero to two EST matches; orange, three to five EST matches; red, six to nine EST matches; purple, ten or more EST matches.

A striking result came from an analysis of central metabolism genes, which show a clear decline in retention over time. All central pathways evolve with the same trend, although at different rates (Fig. 4b). Most pathways are still significantly overamplified with respect to the recent duplication, an effect that has not been observed in WGDs analysed in other organisms21,30. As with protein complexes, the genes involved in a common metabolic pathway show a tendency to covary across the duplications, behaviour that can probably be attributed to stoichiometry, because imbalance in metabolic pathways may have a similar negative effect to that in multiprotein complexes. The loss of one paralogue would be a slow process, involving overexpression of the other copy to maintain stoichiometric constraints.

A strong correlation is observed between expression levels and retention rates of WGD paralogues across all duplications (Fig. 4c). When we consider only the proteins previously defined as associated within complexes, the level of retention is greater (Supplementary Fig. S22), showing that retention is affected both by expression levels and by association in complexes. High expression is therefore a genuine effect in duplicate retention, whether or not the protein belongs to a complex. This correlation has already been observed on a smaller scale in the yeast genome duplication30, indicating that it might be a general trait of WGD.

We noticed the existence of a small group of paralogous genes that retained high expression levels, low amino-acid replacement rates and low rates of silent substitution of nucleotides. These genes also have biased codon usage (Supplementary Fig. S21), with many codons apparently optimized for high expression, because their anticodons correspond to the most abundant tRNA genes. Sequence homology allows us to propose a function for 40 of them (Supplementary Table S13). Most are involved in very basic cellular processes: ribosomal proteins, histones, cytoskeleton components, translation elongation factor 2 and succinate dehydrogenase, and many of them have conserved all eight possible copies. The resulting relative enhancement of these activities should be a significant effect of WGD. Indeed, retention of duplicates for some of these genes, such as those encoding ribosome assembly proteins, is also observed in the WGDs of yeast and Arabidopsis21,22,30.

Genome duplication and speciation

To allow dating of the intermediary and old duplications, we sampled 27 gene families for which homologues were found in Tetrahymena thermophila and several outgroup eukaryotes. Phylogenetic analyses indicate that the old duplication may have occurred shortly before the divergence between Tetrahymena and Paramecium lineages, whereas the intermediary duplication is specific to Paramecium (see Supplementary Information). The recent duplication was dated by analysing 12 gene families for which orthologues in species of the Paramecium genus were available. Phylogenetic trees indicate, with strong bootstrap support, that the recent event occurred after the divergence of P. tetraurelia from P. caudatum and P. multimicronucleatum (Fig. 5). P. tetraurelia belongs to a complex of 15 sibling species (the Paramecium aurelia complex)31. Data from other species of the P. aurelia complex indicate that the recent WGD occurred before their divergence from P. tetraurelia, which is indicative of a possible link between genome duplication and speciation. Indeed, after a genome duplication, many gene losses occur independently in different populations. This process is therefore expected to lead rapidly to reproductive isolation by Dobzhansky–Muller incompatibility32. Interestingly, species of the P. aurelia complex are extremely similar both morphologically and in terms of ecological environment (and hence they were initially thought to correspond to a single species31). We therefore propose that the explosion of speciation events that gave rise to the P. aurelia complex is not the result of adaptative evolutionary events (for example the colonization of new ecological niches) but the neutral consequence of the genome duplication32.

Figure 5: Dating of genome duplication events.
figure 5

The phylogenetic tree of the Paramecium genus was adapted from ref. 47. Phylogenetic analyses indicate that the old WGD occurred before the divergence of Paramecium and Tetrahymena, and the recent WGD before the divergence of P. tetraurelia and P. octaurelia. There are currently not enough data to date the intermediary WGD.

WGDs in genome evolution

Although there is no current consensus on gene fates after a WGD, many current models consider that gene loss is rapid after the duplication, and that functional divergence (either by sub-functionalization or neo-functionalization) can explain most of the retention pattern. The Paramecium data point to another model, which is summarized in Fig. 6. Some genes, representing a fraction of the genome, probably quickly lose their duplicated state, because they can never be detected as duplicates in any of the three WGDs. Duplication of these genes may provide no advantage or may even be counter-selected. However, most of the gene duplicates did not go through this rapid elimination. Their maintenance may be driven at least partly by the maintenance of high expression and stoichiometric constraints. Indeed, many of the duplicates of the recent WGD are functionally redundant. Patterns of retention of more ancient WGDs indicate that most of these duplicates will be progressively lost. Yet the distribution of Ka/Ks ratios shows that almost all recent duplicates are under strong purifying selection (Supplementary Fig. S18), indicating that deleterious mutations affecting the coding sequence of one gene are not masked by the expression of the other copy. As gene regulation evolves to permit loss without affecting dosage, most genes then gradually resolve to a single state. Another model for duplicate retention favours a buffering effect, in which genes are retained in two copies to provide robustness against mutation for important functions23, which would be especially important for a homozygous population. It is worth noting that many plants and Paramecium can undergo self-fertilization and that natural populations of P. tetraurelia are probably homozygous most of the time. This model is consistent with high retention for basic physiological processes in Paramecium. However, it is difficult to consider buffering as the main effect of WGD, because it does not explain why so many genes have been retained in many more than two copies.

Figure 6: A model for gradual gene loss after a WGD deduced from differential retention of genes in Paramecium.
figure 6

Top: evolution of gene number through the three WGD events. Estimates of gene numbers at the time of the duplications were made under the simplifying assumption that further gene loss affected only the new duplicates. Bottom: focus on an inter-WGD period. Just after WGD, genes subject to dosage constraints (that is, genes in complexes or metabolic pathways) and highly expressed genes are preferentially retained as duplicates. Differential loss of paralogues in subpopulations will create barriers to reproduction, favouring speciation. Gradually, the duplicates will erode as the dosage effects are compensated for by new mutations. This massive retention of duplicates across a long evolutionary time enables selection to retain a few new genes with new derived functions.

The appearance of new derived functions may be a secondary product of this basic model. Entire gene modules are retained initially as duplicates with redundant functions, but some of them will evolve to derived ones if there is no need other than stoichiometry for maintaining the redundancy. One example of neo-functionalization is provided by δ- and η-tubulins, paralogues of the old WGD, which have distinct functions in the assembly (δ-tubulin33) or duplication (η-tubulin34) of ciliary basal bodies. η-Tubulin is known only in ciliates, whereas δ-tubulin is conserved in eukaryotes that perpetuate the centriolar structure.

To gain insight into the acquisition of new functions through WGD, we looked for cases of marked sequence divergence between paralogues, because the neo-functionalization model predicts that the two copies will exhibit asymmetric rates of molecular evolution. After correction for multiple testing, we find that 10.9% of recent duplicates and 16.2% of intermediary duplicates show asymmetric evolutionary rates. This difference is significant (χ2 = 7.55, P < 0.01; see Supplementary Information) and can probably be attributed to the progressive nature of duplicate gene loss: a larger proportion of functionally redundant genes remain among recent duplicates than among the intermediary ones.

Among the 62 intermediary duplicates with asymmetric evolutionary rate, we noticed that the rapidly evolving copy tends to be less retained after the recent WGD than the slowly evolving one (26% versus 66%; χ2 = 20, P < 10-4). This indicates that neo-functionalized copies might be more prone to pseudogenization at subsequent WGDs.

The sub-functionalization model predicts that a gene that has been preserved by sub-functionalization at a given WGD is less likely to be retained in two copies at a subsequent WGD35. We observed the opposite pattern: 57% of genes already retained in the intermediary duplication are retained after the recent WGD, whereas only 47% of genes not retained after the intermediary duplication are retained after the recent WGD (P < 10-4). Because this might simply reflect different retention rates between functional classes, only genes from the same functional class were considered. We selected families resulting from the ancient duplication for which one member has been retained in two copies after the intermediary WGD but the other has not (n = 343 families). In agreement with the prediction of the sub-functionalization model, the frequency of retention after the recent WGD was lower for genes retained after the intermediary WGD than for genes that had lost their duplicate (60% versus 67%; χ2 = 4.58, P < 5%). Although significant, this difference is not very strong, which is consistent with the fact that sub-functionalization is an unlikely evolutionary pathway in species with large population sizes35.


The Paramecium duplications have many traits that render them particularly attractive for studying the fates of duplicate genes. Both the high level of gene retention and the strong conservation of synteny helped to define an unprecedentedly large collection of paralogues, with high confidence in their exact origin. In particular, the most recent WGD proved informative on the early evolution of paralogues. We predict a pattern of gene loss that is consistent with progressive decay, acting predominantly at the gene level. The initial maintenance of a complete double set of genes is therefore probably an essential difference between WGD and other large-scale duplications.

We can see parallel evolution for whole protein complexes, metabolic pathways, and known interacting protein groups. All these observations are consistent with a central function of dosage constraints on the evolution of gene duplicates after WGD. We propose a new model for WGD evolution, in which expression and stoichiometry are important in the retention of many duplicate genes, that can thereafter evolve in a few cases towards new derived functions. WGD is therefore fundamentally different from single-gene duplication. Indeed, the gene categories that participate in these two duplication mechanisms are significantly different22. The fact that WGDs have been postulated or demonstrated at important diverging points in eukaryotic evolution28,36,37,38 makes plausible the direct link between these amplifications and the appearance of some eukaryote-specific novelties. Paramecium supports different mutational systems for genetic analysis, including the use of RNA-mediated interference, that can be implemented at the genome scale. We expect that the present study will lead to further work exploring the functional fate of WGDs in detail.


Sequencing and assembly

The whole-genome shotgun and assembly method is described in detail in Supplementary Information.

Gene annotation

Protein-coding genes were predicted by combining ab initio models, Paramecium cDNA alignments, and alignments of proteins and genomic DNA from other species. The integration of the data was realized using GAZE39. Details are given in Supplementary Information.

Genome duplication

A global all-against-all comparison of every predicted protein was performed with the Smith–Waterman algorithm (e value < 0.1) and a set of 12,504 best reciprocal hits (BRHs) based on alignment scores. Each scaffold was scanned with a sliding window of BRHs with window size (w) of 10, and 60% of genes were paired (parameter p). Paralogous blocks were obtained with this windowing strategy and by merging contiguous windows associated with a common target scaffold. In the next step, 1,477 non-BRH syntenic matches found among the ten best matches of any protein with no BRH were added to the paralogue list. These paralogons were fused to create a single molecule with the assumption that every gene without a paralogue corresponds to a gene whose paralogue was lost after the duplication. This creates a succession of genes approximating the gene order of the pre-duplication region, which we called an ancestral block.

To describe the older duplications, the same approach was iterated three times with the following parameters: intermediary WGD, w = 10 and p = 41%; old WGD and ancient duplicates, w = 20 and p = 30%. The paralogous links for each duplication are presented in Supplementary Tables S17-S20, and the composition of the ancestral blocks is given in Supplementary Table S21. Figure 2 was constructed using Circos 〈〉.

Evolution of genes and non-coding sequences

Ks and Ka values were calculated on the entire set of paralogues for each WGD, using the codeml software from the PAML package40.

Analysis of metabolic pathways

We used PRIAM41 to identify 5,617 genes containing at least one Enzyme Commission (EC) number. They were remapped on to metabolic pathways by using the KEGG database42.

Protein complexes

We remapped Saccharomyces cerevisiae complexes (ref. 29 and on to the Paramecium proteome by using orthologous links (see Supplementary Information). A protein–protein interaction was considered conserved if each protein had an orthologue in the Paramecium genome, and a protein complex was considered conserved if it contained at least one conserved protein–protein interaction. From the 1,602 complexes of the MIPS catalogue and the 422 complexes from ref. 29, we found respectively 443 and 61 conserved complexes in the paralogons of the old WGD.

Phylogeny of the WGDs

Phylogenetic trees were inferred from protein sequence alignments by maximum likelihood. We used Phyml43 under the JTT model of protein evolution44, with site-to-site rate variation modelled on a discrete γ distribution (four categories, shape parameter α and proportion of invariable sites estimated from the data). The robustness of the phylogenetic inference was estimated by bootstrap (500 replicates). Phylogenetic trees are available as Supplementary Information. Data on the Tetrahymena proteins were from The Institute for Genomic Research (