bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

1 Single cell transcriptomics, mega-phylogeny and the genetic basis of

2 morphological innovations in Rhizaria

3

4 Anders K. Krabberød1, Russell J. S. Orr1, Jon Bråte1, Tom Kristensen1, Kjell R. Bjørklund2 & Kamran 5 Shalchian-Tabrizi1*

6

7 1Department of Biosciences, Centre for Integrative Microbial Evolution and Centre for Epigenetics, 8 Development and Evolution, University of Oslo, Norway

9 2Natural History Museum, Department of Research and Collections University of Oslo, Norway

10

11 *Corresponding author:

12 Kamran Shalchian-Tabrizi

13 [email protected]

14 Mobile: + 47 41045328

15

16

17 Keywords: cytoskeleton, phylogeny, protists, Radiolaria, Rhizaria, SAR, single-cell, transcriptomics

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18 Abstract

19 The innovation of the eukaryote cytoskeleton enabled phagocytosis, intracellular transport and 20 cytokinesis, and is responsible for diverse eukaryotic morphologies. Still, the relationship between 21 phenotypic innovations in the cytoskeleton and their underlying genotype is poorly understood. 22 To explore the genetic mechanism of morphological evolution of the eukaryotic cytoskeleton we 23 provide the first single cell transcriptomes from uncultivable, free-living unicellular eukaryotes: the 24 radiolarian species Lithomelissa setosa and Sticholonche zanclea. Analysis of the genetic 25 components of the cytoskeleton and mapping of the evolution of these to a revised phylogeny of 26 Rhizaria reveals lineage-specific gene duplications and neo-functionalization of α and β tubulin in 27 Retaria, actin in Retaria and Endomyxa, and Arp2/3 complex genes in Chlorarachniophyta. We 28 show how genetic innovations have shaped cytoskeletal structures in Rhizaria, and how single cell 29 transcriptomics can be applied for resolving deep phylogenies and studying gene evolution of 30 uncultivable protist species.

31

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32 Introduction

33 One of the major eukaryotic innovations is the cytoskeleton, consisting of microtubules, actin 34 filaments, actin-related proteins, intermediate filaments and motor proteins. Together these 35 structures regulate the internal milieu of the cell, aid in movement, cytokinesis, phagocytosis, and 36 predation (Dustin 1984, Grain 1986, Vale 2003, Wickstead & Gull 2011, Katz 2012, Cavalier-Smith 37 et al. 2014). Of essential importance, and the main focus of this work, the cytoskeleton of 38 unicellular eukaryotes determines the morphological patterning of the cell.

39 The evolution of the eukaryotic cytoskeleton is an intriguing story of gene evolution. Homologs to 40 actin and tubulin genes can be found in prokaryotes and Archaea, but the origin of the motor 41 proteins is unclear, lacking distinct homologs in prokaryotes (Vale 2003, Wickstead & Gull 2011). 42 All three major types of motor proteins – kinesin, dynein and myosin – are present in all eukaryote 43 supergroups. Therefore, it is likely that they were already present in the last eukaryotic common 44 ancestor (LECA). Early in the evolution of eukaryotes the cytoskeletal filaments of prokaryotes 45 were given new functions and new motor proteins were invented in addition to a large repertoire 46 of molecules that modify and interact with both the cytoskeleton and the motor proteins 47 (Goldstein 2001, Karcher et al. 2002, Schliwa & Woehlke 2003, Vale 2003, Seabra & Coudrier 2004, 48 Wickstead & Gull 2011).

49 Most of what we know about the eukaryotic cytoskeleton comes from studies of humans, plants 50 and fungi (Jékely 2007, Wickstead & Gull 2011), but less is known about the genetic machinery 51 and the molecular architecture of the cytoskeleton in non-model single celled eukaryotes 52 (protists). Our current knowledge about the evolution of cytoskeletal genes in protists stems from 53 human pathogens, e.g. Plasmodium, Toxoplasma and Cryptosporidium (Wickstead & Gull 2011, 54 Burki & Keeling 2014), but virtually nothing is known about how the evolution of these genes has 55 shaped cytoskeletal morphology in other protists.

56 In this paper we therefore trace the evolution of key cytoskeletal genes in a major group of 57 eukaryotes, Rhizaria, consisting predominantly of understudied single celled protists (Burki & 58 Keeling 2014). Rhizaria is a huge eukaryotic group and harbours species displaying a stunning 59 variety of morphological traits, from naked amoebas to species with delicate and spectacular tests 60 or skeletons. Rhizaria as a group was originally established based on molecular phylogenies that 61 placed the three clades Cercozoa, Radiolaria, and Foraminifera together (Cavalier-Smith 2002,

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62 Nikolaev et al. 2004). Although no clearly defined phenotypic synapomorphies for Rhizaria have 63 been described (Pawlowski 2008), there is a common theme to many rhizarians: well-developed 64 pseudopodia which are often reticulose or filose. The different groups of rhizarians use their 65 pseudopodia in different ways: Some form complicated reticulose networks, e.g. many 66 chlorarachniophytes, others use pseudopodia stiffened by microtubules to capture prey, e.g. 67 Radiolaria, to move molecules and organelles, e.g. Foraminifera, or even as oars in Taxopodida 68 (Cachon et al. 1977, Anderson 1978, Sugiyama et al. 2008, Bass et al. 2009). But how this widely 69 different application of pseudopodia has evolved and how the morphological evolution is reflected 70 in changes to cytoskeletal genes is unknown. The cytoskeleton and motor proteins are an integral 71 part of pseudopod development and usage. In the formation of pseudopods in mouse melanoma, 72 actin and myosin interacts in order to make a protrusion in the plasma membrane creating the 73 leading edge of the pseudopod. Nucleators anchor actin to the cell membrane and actin-related 74 proteins (i.e. the Arp2/3-complex) recruits additional actin filaments to form the branching 75 network that supports the pseudopod (Giannone et al. 2007, Mogilner & Keren 2009). The same 76 mechanism drives pseudopod growth and development in the amoeba Dictyostelium (Ura et al. 77 2012). More rigid pseudopods are made with bundles of microtubules that stiffen and support the 78 pseudopods (called axopodia in Radiolaria and reticulopodia in Foraminifera ; Anderson 1983, Lee 79 & Anderson 1991). The microtubules are typically hollow tubes or helical filament composed of 80 alternating α- and β-tubulin subunits (Welnhofer & Travis 1998). The evolution of the molecular 81 components of the cytoskeleton and pseudopodia in Rhizaria, and protists in general, remains 82 unclear.

83 To understand the evolution of the cytoskeleton and pseudopodia in Rhizaria a fully resolved 84 phylogenetic tree is vital, but getting a stable phylogeny for the entire group has proven 85 problematic. The main issues have been the relationship between Radiolaria and Foraminifera (i.e. 86 Retaria), the monophyly of Cercozoa, as well as the relationship between Rhizaria and its 87 immediate neighbours in the SAR supergroup, Stramenopiles and Alveolata (Burki et al. 2007, 88 2013, 2016, Parfrey et al. 2010, Krabberød et al. 2011, Sierra et al. 2013, 2015, Katz & Grant 2014, 89 Cavalier-Smith et al. 2015).

90 Reconstruction of multi-gene phylogenies have been hindered by lacking molecular data from key 91 rhizarian groups (Burki & Keeling 2014). The main reason for scarce data from Rhizaria is lacking 92 knowledge of how to hold species in culture. We have previously applied single cell genomics 93 (combined with gene-targeted PCR) to study the diversity of Retaria, but this method is not

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94 optimal to obtain large numbers of protein coding genes as it also covers intergenic regions (Bråte 95 2012, Krabberød 2011). Other studies targeting the retarian transcriptome have required pooling 96 many, sometimes several hundred cells (Sierra et al. 2013, Balzano et al. 2015), a method not 97 optimal when morphological markers for species identification are missing or hard to define and 98 cultures cannot be established.

99 Here, we use single cell transcriptomics on two key Rhizaria species (Sticholonche zanclea and 100 Lithomelissa setosa) to build multi-gene phylogenies and investigate the genetic basis of 101 cytoskeletal differences in Rhizaria. Our aim is to reveal processes at the genetic level that may 102 have caused phenotypic changes to the cytoskeleton, and thereby better understand major 103 morphological transitions in this group of organisms. A key aspect is to understand if gene changes 104 are due to co-option processes, where deeply diverging homologs of cytoskeleton genes have 105 been recruited to new functions, or if novelties of morphologies are caused by innovations of new 106 gene families through gene duplication and neofunctionalization. Are genetic changes specific for 107 each subgroup of Rhizaria or are they common between lineages? And can these changes be used 108 to define homological structures and thereby define morphologically distinct categories of 109 organismal lineages in Rhizaria? To address these questions we apply single cell transcriptomics on 110 two free-living radiolarian species.

111

112 Results

113 Single cell transcriptomics of two uncultured protists

114 We generated cDNA libraries from two radiolarian specimens: Lithomelissa setosa and 115 Sticholonche zanclea (Figure 1). The cDNA was sequenced on the Illumina MiSeq platform, 300bp 116 paired end. This resulted in 19,894,654 reads for S. zanclea and 11,590,658 for L. setosa, which 117 were de novo assembled using the Trinity platform (Haas et al. 2013). Assembly resulted in two 118 Single Cell Transcriptomes (SCT) with 4,749 predicted genes for S. zanclea and 2,122 predicted 119 genes for L. setosa (Table 1). Subsampling and re-assembly of reads showed that the sequencing 120 threshold for both libraries was close to maximum (Figure 1 - figure supplement 1). We assessed 121 the suitability of the data for phylogenomic reconstruction by using the BIR pipeline for single 122 gene alignment and tree construction (Kumar et al. 2015). Using 255 seed alignments covering the 123 eukaryote Tree of Life (Burki et al., 2012) we identified 54 and 16 corresponding orthologous gene

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124 sequences from S. zanclea and L. setosa respectively. In addition BIR extracted 3,534 gene 125 sequences from Marine Microbial Eukaryote Transcriptome Sequencing Project, MMETSP (Keeling 126 et al., 2014) and 793 proteins from GenBank with TaxID 543769 (Rhizaria) and added these to their 127 corresponding alignments (See supplementary table S1). After concatenation of all gene 128 alignments we had a super-matrix consisting of 91 taxa and 54,898 amino acids (255 genes).

129

130 Bayesian GTRCAT trees show consistent phylogeny for SAR and subgroups

131 In the Bayesian analysis of the full dataset using the CATGTR model (255 genes 54,898 AA, 91 taxa, 132 Figure 2), Stramenopiles and Alveolates formed a clade, with Rhizaria as sister; branches for these 133 groups are fully supported (1.00 posterior probability (pp)). Haptophytes appeared as sister to SAR 134 (0.87 pp). The relationship and support values did not change for SAR with the removal of fast 135 evolving sites (Figure 2 – figure supplement 1; supplementary table S4). The haptophytes, jumped 136 to a position basal to Archaeplastida (0.82 pp) when four bins of fast evolving sites were removed 137 (Supplementary table S4).

138 Within Rhizaria, the three groups Foraminifera, Radiolaria and Taxopodida, all monophyletic, 139 formed a cluster (i.e. Retaria) with maximum support even when fast evolving sites were removed 140 (i.e. always 1.00 pp). Radiolaria and Foraminifera were placed together as a monophyletic group 141 (0.71 pp) with S. zanclea branching off as sister to them both. This topology remained constant 142 after removing fast evolving sites (Figure 2 – figure supplement 1; supplementary table S4). The 143 posterior probability for the monophyly of Radiolaria together with Foraminifera, i.e. excluding S. 144 zanclea, increased to 0.97 when fast evolving sites were removed (Figure 2 – figure supplement 1). 145 Endomyxa was monophyletic (1.00 pp) and always sister to Retaria with full support (1.00 pp), 146 rendering Cercozoa paraphyletic. Filosa was monophyletic in all analyses (1.00 pp).

147

148 ML trees converged towards Bayesian topology after removal of fast evolving sites

149 In contrast, the maximum likelihood (ML) analysis of the full dataset using the LG model (255 150 genes, 54,898 AA, 91 taxa, Figure 3), grouped Alveolata with Rhizaria instead of the Stramenopiles

151 (96% bootstrap support (bs)). Retaria was recovered with high support (88% bs) as in the Bayesian 152 tree, but S. zanclea was no longer placed ancestrally to radiolarians and Foraminifera. Instead S. 153 zanclea was sister to Radiolarians (88% bs). Importantly, however, S. zanclea changed to a basal

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154 position in Retaria after removal of fast evolving sites, consistent with all the GTRCAT Bayesian 155 trees (Figure 3 - figure supplement 1; Supplementary table S4).

156 Removal of fast evolving sites did not change the monophyly of Foraminifera and Radiolaria 157 (excluding S. zanclea) or the sister relation between alveolates and Rhizaria, but the support 158 values were reduced in both instances to 50% bs for Radiolaria together with Foraminifera and 159 67% bs for the alveolates together with Rhizaria (Figure 3 – figure supplement 1; Supplementary 160 table S4). Endomyxa and Retaria group together with full support as in the Bayesian analysis 161 (100% bs), making Cercozoa paraphyletic. As in the Bayesian phylogeny haptophytes appeared as 162 sister to SAR (77% bs) and changed position basal to the plants, glaucophytes and cryptomonads 163 (73% bs) after removal of fast evolving sites. Species with more than 10% missing data in the final 164 concatenated data matrix were placed on the ML phylogeny using the Evolutionary Placement 165 Algorithm (Berger & Stamatakis 2011). Five species were placed in Endomyxa, five in Filosa, two in 166 Radiolaria, and finally ten species in Foraminifera (Figure 14).

167

168 Influence of fast evolving sites and the choice of model on the phylogeny

169 The discrepant topologies of the Bayesian (CATGTR) and ML (LG) trees could be due to the 170 different models implemented in these two approaches. We assessed the influence of these two 171 models by running Bayesian inferences using the LG model (the opposite: running ML with a 172 CATGTR model is currently not possible). This was done on a smaller alignment to reduce the 173 computational burden (146 genes, 33,081 AA, 91 taxa, see methods for further explanation). The 174 resulting Bayesian tree showed an important result: S. zanclea now grouped with Radiolaria (0.67 175 pp, Figure 3 – figure supplement 1) as in the ML (LG) tree, and not as sister to Foraminifera and 176 Radiolaria, as in all Bayesian trees with the CATGTR model. Other branching patterns in the 177 Rhizaria phylogeny were unaffected.

178 We repeated the ML (LG) analyses after removing fast evolving sites on the full dataset as well as 179 the reduced dataset. While alveolates and Rhizaria formed a clade in the full and small dataset 180 (85% bs, Figure 3- figure supplement 1), removal of four categories of fast evolving site moved 181 alveolates to the stramenopiles in the dataset with 146 genes (74% bs, Figure 3 - figure 182 supplement 1; Supplementary table S4), a result congruent with the Bayesian topology. The 183 support for alveolates together with Rhizaria was also weakened in the dataset with 255 gene 184 when four categories of fast evolving sites where removed, from 96% bs, to 67% bs. When

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185 Foraminifera was excluded from the 255 gene dataset with four categories removed, 186 Stramenopiles and Alveolata formed a group with Rhizaria as sister (57% bs. Table S4).

187

188 Actin radiation in Rhizaria and unique duplications in Retaria and Endomyxa

189 We identified 6 actin sequences in our SCTs. From MMETSP we identified 18 foraminiferan actin 190 and 18 chlorarachniophyte sequences. Phylogenetic analysis of these and other available actin 191 sequences retrieved from GenBank and Pfam revealed that Retaria (including S. zanclea) have two 192 distinct paralogs of actin – actin1 and 2 – where actin2 is fully supported (Figure 4). Actin1 is 193 supported in the Bayesian analysis (0.87 pp) but not in by ML analysis. Actins from Endomyxa form 194 a weakly supported monophyletic group with retarian actin2 (14% bs/0.68 pp). This clade, in turn, 195 groups together with retarian actin1 (59% bs/ 0.97 pp), and is a synapomorphy for Retaria and 196 Endomyxa. There are possibly three paralogs of endomyxean actin, (named a-c in Figure 4) albeit 197 lacking support (a: 32%bs /0.6 pp, b: 16 %bs /- and c: 22 %bs /0.62 pp, Figure 4).

198

199 Arp2/3 complex gene duplication in Chlorarachniophyta

200 Of the seven genes in the Arp2/3 complex, which is responsible for branching of actin filaments 201 and recruitment of new actin, we identified Arp2, Arp3, ARPC2 and ARPC5 from S. zanclea, but 202 only Arp2 from L. setosa (Figure 5). From MMETSP we identified sequences of all seven genes 203 from both Chlorarachniophyta and Foraminifera. Phylogenetic analysis of these genes revealed 204 that all chlorarachniophytes have two distinct paralogs of both Arp2 and APRC1 (Figure 5A), 205 recovered with maximum support (100% bs/1.0 pp). No other species of Rhizaria has undergone 206 the same gene duplication in the Arp2/3 complex as the chlorarachniophytes (Figure 5B).

207

208 Neofunctionalization of Arp2/3 in Chlorarachniophytes

209 Comparative evolutionary analyses of the duplicated Arp2/3 complex genes (Arp2 and ARPC1) 210 were performed by examining the evolutionary rates for each paralog, and then mapping the 211 genes to structural models using Consurf (Ashkenazy et al. 2010, Celniker et al. 2013). The analysis 212 showed that the two different forms of Arp2 (Arp2a and Arp2b, Figure 6) and the two different 213 forms of ARPC1 (ARPC1a and ARPC1b, Figure 7) follow a pattern where the most conserved sites 214 are localized inside the protein structure. Comparison of the surface between the two Arp2

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215 proteins (Arp2a and Arp2b, Figure 6) show shared conserved residues in contact surfaces against 216 other proteins in the Arp2/3 complex (colored green in Figure 8). Similarly, the two different 217 paralogs of ARPC1 (ARPC1a and ARPC1b, Figure 8) show shared conserved sites localized inside 218 the complex. In contrast, the surfaces of the two Arp2 and ARPC1 copies show more variable 219 substitution rates, and all paralogs have patches with mutually exclusive conserved residues 220 (figure 8). As the surfaces of Arp2 and ARPC1 are responsible for the recruitment of the daughter 221 filament and are important for anchoring the two actin strands to each other, the divergent 222 substitution patterns imply that the pairs of paralogs have evolved into different directions from 223 the ancestral gene and thereby undergone sub-functionalization.

224

225 Myosin evolution in Rhizaria

226 We identified 133 myosin transcripts from MMETSP with rhizarian origin. A phylogenetic 227 reconstruction of the newly identified rhizarian myosins together with already published myosin 228 classes spanning a broad taxonomical distribution of eukaryotes (Richards & Cavalier-Smith 2005, 229 Sebé-Pedrós et al. 2014) revealed the presence of two known classes (If and IV) and three 230 previously unknown classes of myosin in Rhizaria (XXXV, XXXVI and XXXVII, following the naming 231 scheme of Sebé-Pedrós et al. (2014)). Myosin XXXVII is unique for Rhizaria, and marks the first 232 known synapomorphy for the group (Figure 9). It is highly supported (100 % bs and 1.0 pp) and has 233 a molecular signal distinct from other described myosins (Richards & Cavalier-Smith 2005, Sebé- 234 Pedrós et al. 2014). In this rhizarian-unique class there has been an additional radiation within the 235 chlorarachniophytes into three separate paralogs, all fully supported (100 % bs and 1.0 pp, Figure 236 9). Rhizarians have also gained a large repertoire of myosin IV, with six paralogs in 237 Chlorarachniophyta and two in Foraminifera. All paralogs were well supported phylogenetically (bs 238 > 90 % and pp >0.9) and differed from each other in functional domains (Figure 9). There was also 239 a class unique to Chlorarachniophyta that resembled myosin IV by having a MYTH4 domain at the 240 C-terminal, but with additional domains at the N-terminal usually not present in myosin IV 241 (Richards & Cavalier-Smith 2005, Sebé-Pedrós et al. 2014). However both paralogs of 242 Chlorarachniophyta in this class were phylogenetically distinct from myosin IV to warrant them to 243 be given a new class (myosin XXXV). We also found myosin If in Chlorarachniophyta, which have 244 been suggested to be present in the last common ancestor of all eukaryotes and recently lost in 245 Rhizaria (Sebé-Pedrós et al. 2014). However the presence of two paralogs of myosin If in 246 chlorarachniophytes show that it was present in the ancestor to Rhizaria, but that it might have

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247 been lost in Endomyxa and Retaria after they separated from the chlorarachniophytes. Finally 248 there was a group unique to Chlorarachniophyta with two paralogs, named myosin XXXVI (Figure 249 9).

250

251 α- and β-tubulin gene duplications in Retaria

252 We report 16 new α-tubulin and 19 new β-tubulin sequences from our two retarian 253 transcriptomes: 4 α-tubulin, and 9 β-tubulin from L. setosa, 12 α-tubulin and β-tubulin from S. 254 zanclea. Additionally, we identified 26 α-tubulin and 42 β-tubulin sequences from other rhizarian 255 species in the MMETSP data (i.e. 12 Chlorarachniophyta and 14 Foraminifera α-tubulins; 10 256 Chlorarachniophyta and 32 Foraminifera β-tubulin). All these genes and other homolog sequences 257 identified in GenBank were added to the Pfam seed alignment for α and β-tubulin (Finn et al. 258 2014). The phylogenetic tree of rhizarian α-tubulin revealed two different version of the gene: the 259 canonical version of the α-tubulin gene (α1-tubulin; α1) and a novel group (α2-tubulin; α2) found 260 only in Retaria (Figure 10). The split separating the two versions received maximal support (100% 261 bs/ 1.0 pp). We identified α2-tubulin in the SCTs from both L. setosa and S. zanclea. Together with 262 the available data from other Rhizaria, we confirm that this paralog is unique for Retaria. In 263 Foraminifera there were several paralogs of α2, with most copies in Reticulomyxa filosa (25 264 copies). Foraminifera α2 was paraphyletic with a clade branching at the base of Retaria (100% bs/ 265 1.0 pp), before the Radiolaria and Taxopodida α2 clade. The bootstrap support was low (70 % bs), 266 while the posterior probability was high (0.97 pp) for the branch that separated this group from 267 the rest of the Foraminifera (Figure 10).

268 Similarly, the β-tubulin trees contained a clearly divergent clade (i.e. β2-tubulins) with several 269 copies for each Retarian group (Figure 11). All β2-tubulin copies where grouped together with high 270 support (100% bs/ 1.0 pp) in agreement with earlier studies (Hou et al. 2013). We also found that 271 the β2 copies were present in Taxopodida as well as in Foraminifera and Radiolaria.

272

273 Neofunctionalization of tubulin genes in Retaria

274 Comparative evolutionary analyses of the tubulin paralogs were done to identify patterns of 275 functional change. This was performed by estimation of evolutionary rates and mapping site rates 276 to tubulin structural models with Consurf (Ashkenazy et al. 2010, Celniker et al. 2013). Highly 277 conserved amino acid residues were assumed to be functionally important and variable residues

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278 to be of less importance for function. We therefore compared separately α1 with α2, and β1 with 279 β2; identifying sites conserved in one paralog and variable in the other. Such sites were believed 280 to have undergone functional shifts and therefore considered important for cytoskeleton 281 evolution. We also examined regions of the α- and β-tubulin structures known to be important for 282 microtubule function and dynamics. Evolutionary changes in these areas are likely to affect the 283 overall function of the microtubules.

284 Tracing evolutionary rates on the molecular structure of α- and β-tubulin (figure 12 and 13) 285 revealed two patterns of functional change between the conventional and new tubulin genes: 286 First, areas that are considered to be functionally important and conserved in α- and β-tubulin in 287 general were conserved in α1 and β1 genes while being highly variable in α2 and β2, with 288 differences being most prominent in α-tubulin. This pattern was observed for both inter- and 289 intra-dimerization surfaces between monomers (i.e. longitudinal interactions important for 290 protofilament assembly and disassembly), as well as lateral interactions between protofilaments. 291 Both the T7-loop and H8 helix, important for longitudinal interactions, are extremely conserved in 292 the original variant, while highly variable in the novel paralog. And similarly for the lateral contact 293 points, helix H12, which forms a ridge on the outside of the microtubule and therefore affects 294 binding and movement of motor proteins along the filament (Löwe et al. 2001) is much more 295 variable in the novel α2-tubulin paralog than α1. Even the highly conserved residues in the M-loop 296 of the original tubulin variants are highly variable for α2 and β2. These are residues directly 297 interacting between neighboring protofilaments (Löwe et al. 2001). Taken together, all major 298 contact areas both for lateral and longitudinal interactions are less conserved in the novel paralogs 299 compared to the original, especially for α2.

300 Second, and in contrast to the pattern above, areas of the tubulin molecules considered to be 301 functionally less important typically evolve faster than the contact surfaces. Several residues 302 outside of the conventional longitudinal and lateral binding sites are highly conserved in both α2 303 and β2 while highly variable in the original α1 and β1 genes (Supplementary alignment). Many of 304 these residues are exposed on the surface of the monomers and could represent new sites for 305 other tubulin interactions or surfaces for motor protein attachment and movement.

306 Altogether, both the α2- and β2-tubulins have undergone dramatic evolutionary changes and are 307 likely functionally distinct from their α1 and β1 counterparts (Figure 12 and 13).

308

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310 Discussion

311 The last common ancestor of Rhizaria was most likely a naked, heterotrophic flagellate, who relied 312 extensively on its pseudopodia to explore the environment and to catch prey (Cavalier-Smith 313 2009). Its pseudopods were supported by actin and at least one group of myosins unique to 314 Rhizaria (Figure 4 and 9, summarized in Figure 14). The Rhizarian cytoskeletons have since 315 undergone evolutionary changes and their diversification follows a pattern where the major 316 groups have their own favoured filament: the chlorarachniophytes have relied on actin to support 317 their reticulose pseudopodia while the axopodia and reticulopodia in Retaria have been stiffened 318 by microtubules composed of tubulin. Although some structural differences between lineages are 319 known, little is established about the genetic basis of these phenotypes. Here we investigate the 320 genetic evolution responsible for diversification of the cytoskeleton and present a hypothesis that 321 relate these evolutionary changes to the varying morphology of Rhizaria groups. In order to fully 322 understand the evolution of the cytoskeleton in Rhizaria we started by constructing a robust 323 phylogenetic tree on which to map the evolutionary events.

324

325 Placing Rhizaria in the Tree of Life

326 Rhizaria has an evolutionary origin at the intersection between two very morphologically diverse 327 and abundant lineages in the Tree of Life: the alveolates and stramenopiles. Together the three 328 lineages form the supergroup SAR (Burki et al. 2007). Although there is little doubt that these 329 three lineages are closely related to each other, the exact relationship between them remains 330 debated. Three main hypotheses exists: either Stramenopiles and Rhizaria are monophyletic and 331 sister to Alveolates (Burki et al. 2007, 2013, Katz & Grant 2014), alveolates and stramenopiles 332 constitute a monophyletic group with Rhizaria as sister (Burki et al. 2008, 2010, 2012, 2016, 333 Parfrey et al. 2010, Cavalier-Smith et al. 2015), or finally Rhizaria and Alveolates are monophyletic 334 with Stramenopiles as sister group (Sierra et al. 2013, 2015, He et al. 2016).

335 Our Bayesian and ML inferences resulted in two different phylogenies. The Bayesian tree inferred 336 with the CATGTR model grouped alveolates and stramenopiles, whereas the ML tree with the LG 337 model clustered alveolates with Rhizaria. This inconsistency was evaluated by removing fast 338 evolving sites, which have been suggested to contain misleading phylogenetic information 339 (Philippe et al. 2005, Townsend 2007, Cummins & McInerney 2011, Townsend et al. 2012).

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340 Removing such sites, caused no changes in the Bayesian phylogeny of the SAR groups, but the ML 341 analyses converged towards the Bayesian tree by grouping alveolates and stramenopiles (Figure 342 4A and Suppl. table S4). The CATGTR model is a better representation of amino acid substitution 343 patterns than the LG model, because it takes into account substitution pattern heterogeneity 344 (Lartillot & Philippe 2004). In addition, the Bayesian inferences were less affected by site selection 345 and were always reconstructing essentially identical phylogenies with the CATGTR model, 346 altogether strongly supporting the grouping of alveolates and stramenopiles with exclusion of 347 Rhizaria.

348 One of the remaining challenges about the SAR phylogeny is to identify the closest sister group of 349 SAR in the global phylogeny of eukaryotes. Recently it has been proposed that haptophytes 350 together with Centrohelida make up the sister clade to SAR (Burki et al. 2016). This is congruent to 351 our Bayesian and ML trees where the haptophytes branch at the base of SAR, at least prior to the 352 removal of fast evolving sites. However, removal of fast evolving sites typically groups 353 haptophytes together with cryptophytes at the base of the Archaeplastida, as seen in other recent 354 multi-gene phylogenies (Supplementary table S4; Parfrey et al., 2010; Brown et al., 2012; Katz & 355 Grant, 2014; Cavalier-Smith et al., 2015). This shifting position between SAR and the 356 Archaeplastida may reflect that haptophytes diverged at the base of both groups and therefore is 357 a key group for understanding the origin and evolution of this huge diversity of eukaryotes.

358

359 Resolving Rhizarian Relationships

360 Within Rhizaria, it has been suspected for some time that Foraminifera and Radiolaria are closely 361 related, and they have therefore been grouped together as Retaria (Cavalier-Smith 2002, Moreira 362 et al. 2007, Krabberød et al. 2011, Ishitani et al. 2011, Sierra et al. 2013). In phylogenies based on 363 ribosomal DNA, Foraminifera groups within radiolarians, although this placement has been 364 contested based on the aberrant nature of both the small (18S) and large (28S) subunit of 365 ribosomal genes in Foraminifera (Pawlowski & Burki 2009, Krabberød et al. 2011). Recent 366 phylogenomic analyses place Foraminifera either within Radiolaria implying Radiolaria to be a 367 paraphyletic group (Burki et al. 2013, Sierra et al. 2013, 2015) or as sister to Radiolaria (Cavalier- 368 Smith et al. 2015, Burki et al. 2016). However, these analyses lack two crucial pieces in the puzzle; 369 representatives from Nassellaria, one of the major polycystine radiolarian orders, and S. zanclea, 370 the only species of Taxopodida. Including both in combined 18S and 28S rDNA phylogenies, 371 divided the Radiolaria in two main groups, Polycystina and Spasmaria, where the latter contained

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372 Taxopodida, but the position of Foraminifera was unresolved (Krabberød et al. 2011). Here, we 373 have generated transcriptome data and protein sequences from both the missing Radiolaria 374 groups in our multi-gene analyses, L. setosa (Nassellaria) and S. zanclea (Taxopodida). In addition, 375 we have reduced the impact of missing data in earlier phylogenomic analyses (Sierra et al. 2013, 376 2015, Cavalier-Smith et al. 2015, Burki et al. 2016) by adding genes to Foraminifera and a 377 substantially larger sampling of other Rhizaria species.

378 Using these data, our analyses always cluster Radiolaria, Foraminifera and Taxopodida into 379 Retaria. We find that Radiolaria (excluding Taxopodida) is monophyletic (congruent with Cavalier- 380 Smith et al. 2015). Endomyxa and Retaria form a monophyletic group, revealing Cercozoa as 381 paraphyletic. But in our multi-gene alignments, as in those of Sierra et al. (2013), data from two 382 important endomyxean clades (i.e. Haplosporida and Vampyrellida) are absent. However, we 383 included representatives from the two clades on the ML tree with the Evolutionary Placement 384 Algorithm (Berger & Stamatakis 2011) and they fall inside the endomyxean clade, strengthening 385 the monophyly of Retaria and Endomyxa (Figure 14).

386

387 Taxopodida and Endomyxa revealed as sister lineages to Foraminifera and Radiolaria

388 Taxopodida have previously been placed within Radiolaria (Nikolaev et al. 2004, Krabberød et al. 389 2011), but has two different positions in our trees dependent on the analysis. The Bayesian 390 CATGTR trees show Taxopodida as the sister to Radiolaria and Foraminifera, while ML LG place the 391 species as sister to Radiolaria. We assessed the basis for this discrepancy by running Phylobayes 392 with the substitution model used in the ML analyses (i.e. the LG model). The resulting Bayesian LG 393 tree placed Taxopodida as sister to Radiolaria – congruent with the ML tree – clearly 394 demonstrating the impact of the model on the phylogeny. It should also be noted that removing 395 fast evolving sites in the ML LG analysis changed the tree correspondingly by placing Taxopodida 396 at the base of Retaria (Figure 4B). While all the Bayesian inferences were highly congruent, the ML 397 topologies were less stable and converged towards the Bayesian tree with removal of fast evolving 398 sites. The stability of the Bayesian results may be due to the use of the CATGTR model which more 399 realistically estimates the evolutionary substitution patterns in amino acids by taking into account 400 across site heterogeneities in the amino acid substitution process (Lartillot & Philippe 2004, 401 Lartillot et al. 2013) and therefore preferable over the LG model.

402

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403 All evidence taken into account, Taxopodida most likely diverged early in the radiation of Retaria 404 and before the separation of Radiolaria and Foraminifera. This has consequences for the 405 interpretation of the cytoskeleton and morphological evolution of Retaria. Taxopodida and 406 Acantharia were grouped together as Spasmaria based on the existence of contractile myonemes 407 in both groups (Cavalier-Smith 1993), a grouping also supported in 18S and 28S rDNA phylogenies 408 (Krabberød et al. 2011). Myonemes give taxopodidans the ability to swim using their pseudopodia 409 like oars while giving acantharians the ability to regulate their buoyancy by altering their cell 410 volume (Cachon et al. 1977, Febvre 1981). However, if Taxopodida is sister to both Radiolaria and 411 Foraminifera it implies that contractile myonemes and flexible pseudopodia, were an ancestral 412 trait of Retaria, and have later been lost or modified in Radiolaria and Foraminifera.

413 Endomyxa was originally defined as a clade within Cercozoa (Cavalier-Smith 2002). In our trees, 414 however, Endomyxa was consistently excluded from the filose Cercozoa in both ML and Bayesian 415 inferences, and placed as sister to Retaria. Our trees show both Endomyxa and Taxopodida as 416 sister lineages to Foraminifera and Radiolaria. This means that Rhizaria is split into three lineages: 417 Filosa, Endomyxa and Retaria. Taxopodida, Foraminifera and Radiolaria constitute Retaria. This 418 new branching order of rhizarian lineages forms the framework we here use to map changes of 419 the cytoskeleton-related gene families and establish the order of macroevolutionary changes in 420 Rhizaria.

421

422 Expansion of actin, myosin and subfunctionalization of Arp2/3 in Chlorarachniophyta

423 The chlorarachniophytes can form extensive networks of reticulose actin-based pseudopodia that 424 they rely on for foraging and movement (Margulis 1990). The evolution of these extensive 425 pseudopodial networks seems to have been made possible by gene duplications of proteins 426 controlling actin network dynamics as well as several duplications of the actin gene, and of myosin 427 specific to chlorarachniophytes. The interaction between actin, the Arp2/3 complex, and myosin is 428 important for pseudopod formation and branching. Branching points between two actin filaments 429 are formed as the Arp2/3 complex recruits actin filaments into networks (Volkmann et al. 2001, 430 Goley & Welch 2006, Pollard 2007, Mattila & Lappalainen 2008, Xu et al. 2011). Here we present 431 evidence for a duplication ancestral to chlorarachniophytes for two of the proteins in the complex: 432 Arp2 and ARPC1. Both proteins are involved in the initial binding of nucleation promoting factors 433 (NPFs) that are essential for the formation of protrusions that eventually leads to pseudopodia at 434 the leading edge of motile cells (Boczkowska et al. 2008, 2014, Xu et al. 2011, Ura et al. 2012, Kast

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435 et al. 2015). Although the exact nature and conformation of the Arp2/3 complex are still under 436 investigation, it seems clear that actin NPFs bind first to Arp2 and ARPC1, then extend the 437 daughter filament by adding an actin subunit at the barbed end of Arp2 and Arp3 (Boczkowska et 438 al. 2008, 2014). This in turn creates attachment points for daughter actin filaments to bind to the 439 existing mother filament (Rouiller et al. 2008). In chlorarachniophytes the Arp2 and ARPC1 440 paralogs have undergone divergent substitution patterns. The differences between the two Arp2 441 paralogs as well as the two ARPC1 paralogs are mainly found on the surface areas of the Arp2/3 442 complex where the actin recruiting proteins, NTPs and ultimately the newly formed actin filaments 443 attach. Sites that are conserved and shared between both paralogs (marked green in Figure 8) are 444 most likely important for the original function of the complex, while the sites that are conserved in 445 one of the paralogs but not the other points to functional differentiation and innovation. In 446 addition myosin duplications have occurred ancestrally to Rhizaria before several independent 447 events in chlorarachniophytes and Foraminifera.

448 Over evolutionary time scales these genetic innovations have likely formed the molecular basis of 449 cellular and morphological differentiation in chlorarachniophytes: In turn, this has given them a 450 larger repertoire of Arp2 and ARPC1 and an increased potential to recruit actin filaments to 451 facilitate a reticulate cell and a gliding lifestyle.

452

453 Unique duplication and neofunctionalization of α- and β-tubulin in Retaria

454 Similar to Chlorarachniophytes many species in Retaria and Endomyxa can form highly branched 455 pseudopodial networks (Anderson 1976a, b, Lee & Anderson 1991, Suzuki & Aita 2011). This is also 456 reflected in the expansion of actin genes: Retaria has two distinct subfamilies of actin genes, one 457 grouping with actin homologs from Endomyxa. In Endomyxa the actin diversity is extensive with 458 three possible paralogs (Figure 4). Unlike Chlorarachniophyta however, Retaria have additional 459 pseudopods supported by microtubules called axopodia (Anderson 1983, Travis & Bowser 1986, 460 Lee & Anderson 1991, Suzuki & Aita 2011). The axopodia in Radiolaria are often contractile and 461 withdraw upon contact; rapid movement can cause prey to be drawn towards the cytoplasm of 462 the cell where digestion occurs (Sugiyama et al. 2008). Similarly Foraminifera have stiffened 463 pseudopods called reticulopodia. These microtubule mediated pseudopods can extend and retract 464 at a speed two orders of magnitude faster than in animal cells (Travis & Allen 1981, Bowser 2002). 465 The extraordinary speed at which the microtubules can nucleate in Foraminifera has been linked 466 to a duplication and neo-functionalization of β-tubulin (Habura et al. 2005, Hou et al. 2013). The

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467 discovery of the aberrant β2-tubulin was a paradox, because the corresponding α-tubulin paralog 468 of the heterodimer was absent in all Retaria (Hou et al. 2013). The question is how an aberrant β- 469 tubulin can function without a correspondingly deviant α-tubulin. Here we solve this paradox by 470 presenting α2-tubulin in the single cell transcriptomes of Sticholonche zanclea and Lithomelissa 471 setosa, which enabled identification of homologs from other Retarian species. We also add new β- 472 tubulin data from both S. zanclea and L. setosa, confirming gene expansion in all major Radiolaria 473 lineages, and the origin of new paralogs in the common ancestor to Retaria. Interestingly, none of 474 the α2-tubulin and β2-tubulin paralogs could be identified in available Endomyxa data, suggesting 475 that these gene duplications are synapomorphic for Retaria, with an origin after Retaria and 476 Endomyxa diverged (Figure 14).

477 Both the α2- and β2-tubulin genes form distinct phylogenetic clades and diverged from the 478 conventional α1- and β1-tubulin genes through changes in functionally important residues. 479 Subsequent to the initial duplication, these paralogs have undergone repeated duplications to 480 form subgroups of each gene family. These duplications and increased evolutionary rate have 481 developed both α2- and β2-tubulin as more divergent genes than the conventional α1- and β1- 482 tubulins.

483 Modelling of evolutionary rates on the tubulin structure shows global changes of the molecule 484 along two different paths: Firstly, a large number of conserved and functionally important residues 485 in α1 and β1 have become more variable, and probably therefore less functionally important in α2 486 and β2. This pattern is particularly clear at the interface between the α and β heterodimers (which 487 is the basic unit of protofilaments), and in the lateral surfaces between protofilaments that create 488 microtubule (i.e. the M-loop, the T3-loop and 8H helix etc.). Secondly, many variable sites localized 489 outside of the classical contact surfaces in the conventional α1 and β1, have become conserved in 490 α2 and β2 and have probably gained new functional roles. In addition, tracing the evolutionary 491 rates of all tubulin paralogs show higher evolutionary rate at the interface between the α and β 492 heterodimers (which are the basic units of protofilaments), and in the lateral surfaces between 493 protofilaments that create microtubules (i.e. the M-loop, the T3-loop and 8H helix etc.). The 494 overall pattern is that the new α2-tubulin paralog presented here evolved with a similar mode to 495 that of the β2-tubulin gene (Habura et al. 2005, Hou et al. 2013).

496 Retaria is unique among eukaryotes in having such divergent tubulin genes. It is not clear how 497 Retaria combines the four tubulin variants α1, α2, β1 and β2 into heterodimers, but it certainly 498 enables modularity. We hypothesize that Retaria can assemble four types (type 1-4) of

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499 heterodimers; i.e. type1: α1+β1, type2: α1+β2, type3: α2+ β1, type4: α2+ β2. These four 500 heterodimers can function as modules and can be combined to develop protofilaments with 501 different properties. The different affinities between the α and β tubulins will certainly affect 502 assembly and disassembly of microtubules, and may be used to adjust flexibility, strength and 503 conformation of the axopodia or reticulopodia (Löwe et al. 2001). Retaria is known to develop 504 elaborate pseudopodia stiffened by bundles of microtubules. The axopodial microtubules in 505 Taxopodida and Acantharia attach laterally to other microtubules and form multiple hexagonal 506 rings (Cachon et al. 1973). The microtubules of polycystine radiolarians axopodia on the other 507 hand form a branching pattern (Cachon & Cachon 1971, Grain 1986). In some Foraminifera (e.g. 508 Astrammina) the microtubules coil tightly around one around another increasing the tensile 509 strength of the pseudopodia used to capture prey (Lee & Anderson 1991). Having several types of 510 α and β heterodimers allows a large repertoire of architectural structures to be drawn upon when 511 forming microtubules. In addition, we observe that many of the sites that have undergone 512 evolutionary change are located on the surface of the heterodimer. This can be linked to binding 513 sites for microtubule associated proteins (MAPs) as well as motor proteins further expanding the 514 range and flexibility of cytoskeletal structures (Brouhard & Rice 2014).

515

516 Single cell transcriptomics for macroevolutionary studies of unculturable protists

517 Here we have applied single cell transcriptomics as a new approach for phylogenomic 518 reconstruction of SAR, and the genetic basis of cytoskeleton and morphological evolution in 519 Rhizaria. Presently single cell transcriptomics has been applied to animal model organisms, such as 520 cell differentiation studies in mouse (Liang et al. 2014, Liu et al. 2014). To date, the only 521 application on protists has been on single cells grown from culture, confirming that the method 522 gives comparable results to that of sequencing many thousand cells (Kolisko et al. 2014). Although 523 single cell transcriptomic studies from cultured cells confirm the approach, they do not address 524 how efficient the method works on free-living protists, with highly divergent cell types, from 525 natural samples.

526

527 One of the main challenges of applying single cell transcriptomics to protists is the optimization of 528 cell lysis. This is emphasized when studying species with rigid skeletons and tough cell walls. Here 529 we modified lysis procedures for single cell transcriptomics (Picelli et al. 2014). Radiolaria species

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530 have a though cellular wall that protects the endoplasm; successful lysis demonstrates how the 531 method can be applied to less hardy unicellular species. The number of predicted genes from our 532 single cell transcriptomes are comparable to that generated from colonies, or pooling of hundreds 533 of cells from other Radiolarian species (Burki et al. 2010, Balzano et al. 2015). Subsampling of 534 sequence reads showed sufficient sequencing depth, suggesting that an incomplete transcriptome 535 was likely due to stochastic loss of mRNA. Despite these challenges we have shown that 536 transcriptomes of sufficient quality for phylogenomic and molecular evolutionary analyses can be 537 generated from single cells isolated from natural samples. This protocol can undoubtedly be 538 applied to other uncultivable protists, adding resolution to the relationships between eukaryotes, 539 in addition to revealing the evolution of morphologically related genes.

540

541 Morphological diversification by lineage specific innovation of cytoskeleton genes in Rhizaria

542 Data generated from these transcriptomes demonstrate that genetic innovation through multiple 543 gene duplication and neo-functionalization processes, rather than co-option of deep gene 544 homologs, have taken place in cytoskeletal genes of Chlorarachniophyta and Retaria. Differential 545 expansion of genes in chlorarachniophytes and Retaria show that underlying genetic changes to 546 cytoskeletal evolution have taken different routes in morphologically distinct groups; the overall 547 pattern of the data reveals extensive gene duplications of actin-related proteins in 548 chlorarachniophytes and of α- and β-tubulins in Retaria, with group specific expansions of myosin 549 in both groups (Figure 14). The hypothesized connection between the evolutionary changes to 550 cytoskeletal genes and the cellular morphology of the cells suggest that genetic innovations 551 occurred in the ancestor of the respective groups, subsequently forming the basis for 552 morphological and species diversification. While the actin-related proteins, and the myosin motor 553 proteins that use them have driven changes in chlorarachniophytes; tubulin has directed central 554 components of Retaria evolution. Subsequent to the initial innovation, additional expansions of 555 functional genes crucial to cytoskeletal formation have impacted on the morphological 556 diversification of Chlorarachniophyta and Retaria. Our analyses elucidate relationships between 557 genotype and phenotype of these organisms, linking gene evolution to evolution of cell 558 morphology. Better understanding of macroevolution in these organisms will require functional 559 studies of what types of actin branching the new Arps can form in chlorarachniophytes and how 560 Retaria combine the two sets of α and β tubulin proteins in their protofilaments. Such studies 561 should be complemented with more data from other gene families known to be involved in

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562 cytoskeleton development, regulation, and transportation, such as MAPs, GTPases, dynein and 563 kinesin (Hammer & Wu 2002, Kollmar et al. 2012, Rojas et al. 2012, Brouhard & Rice 2014), .

564 Using the transcriptome data, we addressed uncertainties in the phylogeny of SAR by 565 phylogenomic analyses of supermatrices and by identification of synapomorphic gene 566 duplications. The phylogenomic analyses strongly support Rhizaria as sister to Stramenopiles and 567 Alveolates, and reveal Endomyxa and Taxopodida as two sister lineages to Foraminifera and 568 Radiolaria, with the latter two being divided into two distinct clades. Foraminifera is not placed 569 within Radiolaria as earlier reported (Krabberød et al. 2011, Sierra et al. 2013, 2015). In addition, 570 we identified independent synapomorphic gene duplications characters on several taxonomic 571 levels in Rhizaria, including a myosin family unique to Rhizaria. The actin-2 paralog of 572 Foraminifera, Radiolaria and Taxopodida is shared with Endomyxa, arguing for the grouping of 573 Endomyxa with Retaria, instead of being placed within Cercozoa. However, Retaria is divided from 574 Endomyxa by the Retaria-specific α2 and β2 tubulin synapomorphies. The duplication of genes in 575 the Arp2/3 complex is a synapomorphy for Chlorarachniophyta. Altogether the phylogenomic 576 trees and synapomorphic gene-duplications shown here, form a new framework for future 577 revisions of the classification of SAR and Rhizaria. In total, we demonstrate single cell 578 transcriptomics as a promising approach for inclusion of a larger diversity of uncultured protists in 579 macroevolutionary studies and phylogenomic inferences.

580

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581 Methods:

582 Sampling and transcriptome amplification

583 Plankton samples were collected from the inner part of the Oslo fjord (May 2014) using a net haul 584 with mesh size of 60 μm. The seawater samples were stored overnight in an incubator holding the 585 same temperature as the fjord to let living cells recover and self-clean. Radiolarian cells were 586 manually extracted from the plankton samples by capillary isolation with Pasteur pipettes and an 587 inverted microscope. Cells were individually photographed and then thoroughly washed in sterile 588 PBS to remove possible surface contamination (Figure 1). Immediately following isolation, cells 589 were placed in Nucleospin RNA XS lysis buffer (Macherey-Nagel) and processed further. Total RNA 590 was isolated from the free-living Radiolarian cells using Nucleospin RNA XS (Macherey-Nagel) 591 following standard protocol, with on-column DNase treatment and eluting with 5μl elution buffer. 592 Hybridization of oligo(dT) primer, reverse transcription, template switching and PCR amplification 593 of cDNA were performed by modification of a protocol outlined in (Picelli et al. 2014) called Smart- 594 seq2; we used 7 μl of mRNA mix (5 μl isolated RNA, 1 μl oligo(dT) primer and 1 μl 10 mM dNTPs) 595 which was added to 9 μl of reverse transcriptase (RT) mix). All 16 μl (mRNA+RT mix) was used for 596 PCR amplification (adjusting concentrations accordingly) employing 20 cycles. The quality and 597 integrity of the resulting cDNA were confirmed using a Bioanalyzer (Agilent) with a high-sensitivity 598 DNA chip, in addition to visualization on a 1% TAE gel. cDNA concentration was confirmed using a 599 Qubit fluorometer (Life Technologies) and the dsDNA HS assay kit.

600

601 Sequencing and assembly

602 Library preparation and sequencing of the cDNA with Illumina MiSeq were performed at the 603 Natural History Museum in London. The sample was prepared using the Illumina TruSeq Nano 604 DNA LT Library Preparation Kit (FC-121-4001). The standard Illumina protocol was followed with 605 fragmentation on a Covaris M220 Focused-ultrasonicator. The finished library was quality checked 606 using an Agilent Tapestation to check the size of the library fragments, and a qPCR in a Corbett 607 RotorGene instrument to quantify the library. This was repeated for two MiSeq 600 cycle runs, 608 2*300 cycle paired end sequencing. The MiSeq platform was chosen over HiSeq since the longer 609 reads would provide an easier assembly when dealing with a possible metatranscriptomic library. 610 The raw reads (19,894,654 for S. zanclea and 11,590,658 for L. setosa) were quality filtered and

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611 pairwise assembled with PEAR (Zhang et al. 2013) using default parameters. The reads where 612 further cleaned with Trimmomatic (Bolger et al. 2014) and then de novo assembled into contigs 613 with Trinity (Haas et al. 2013) using default settings. TransDecoder in the Trinity package was used 614 to predict genes from the assembled cDNA (Haas et al. 2013).

615

616 To check if all transcripts in the library had been sequenced, the raw reads were randomly split up 617 in 10 different datasets representing 10%, 20%, up to 90% of the original raw reads. The sub- 618 sampled datasets were assembled and new gene predictions were independently performed using 619 PEAR, Trimmomatic and Trinity as for the full dataset. Accumulation curves obtained by plotting 620 the predicted gene number against increasing partition size show that the slope of the curves 621 decrease with increasing partition size and more or less flattens when it reaches 100% of the total 622 dataset for both libraries (Figure 1 – figure supplement 1). We therefore assume that acceptable 623 sequencing depth for each library has been achieved, and that a further sequencing effort would 624 not have increased the number of predicted genes significantly.

625

626 Alignment construction, paralog identification, and phylogenetic inference

627 The BIR pipeline: We used the BIR pipeline (www.bioportal.no; Kumar et al., 2015) to extract 628 genes and prepare single gene alignments to be used in multi-gene phylogenetic analyses. As seed 629 alignments for the BIR pipeline we used 258 genes previously published in multi-gene phylogenies 630 (Burki et al. 2012). As a query database we used the generated transcripts from our single cell 631 transcriptomes (6898 in total), all proteins in GenBank with Rhizaria as TaxID (44278 sequences at 632 the time of retrieval, October 2014), all 16 transcriptomes assigned to Rhizaria from the Marine 633 Microbial Eukaryote Transcriptome Sequencing Project (MMETSP; Keeling et al., 2014. See table 1) 634 , as well as all Rhizarian sequences from Sierra et al., (2013). In addition seven reference genomes 635 are included in the BIR pipeline (Arabidopsis thaliana, Bigelowiella natans, Dictyostelium 636 discoideum, Guillardia theta, Homo sapiens, Monosiga brevicollis, Naegleria gruberi, Paramecium 637 tetraurelia, Saccharomyces cerevisiae and Thalassiosira pseudonana (Kumar et al. 2015). In short 638 the BIR pipeline will screen the query sequences against the database consisting of one or more 639 seed alignments, using BLAST, and assign the sequences that match the criteria set by the user to 640 the corresponding alignment (for details see Kumar et al., (2015)).

641

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642 Single gene analyses: Maximum Likelihood (ML) trees for all single genes were constructed with 643 RAxML v 8.0.2, with the program calculating the best fitting model for each gene (the option -m 644 PROTGAMMAAUTO), and with the automatic bootstrapping criteria MRE (option -l autoMRE) 645 (Pattengale et al. 2010, Stamatakis 2014). The Tree Certainty index (Salichos et al. 2014) was 646 calculated for each tree separately, and all trees were run through a custom made R script to see 647 whether the following clades were monophyletic or not: Opisthokonta, Fungi, Alveolata, 648 Stramenopiles, Haptophyta, Rhizaria, Viridiplantae, Excavata, Fungi and Rhodophyta. This allowed 649 us to screen for genes containing artefacts and dubious sequences such as sequences that had 650 been assigned to the wrong species, sequences that originated from contamination and possible 651 paralogs. Three genes (β-tubulin, actin and rac1) were found to have paralogs and deemed not 652 suitable for multi-gene phylogenies. We therefore proceeded with 255 genes for the multi-gene 653 analysis.

654

655 Supermatrix construction: After screening we were left with 255 genes that were concatenated 656 using ScaFos (Roure et al. 2007). We also merged close species into composite sequences when 657 they covered different parts of the supermatrix (see table S2). The final matrix had a length of 658 54,898 amino acids with 124 taxa.

659

660 Removal of jumping and long branched taxa: Mikrocytos mackini was not included in the analysis 661 due to an extremely long branch (Burki et al. 2013) and RogueNaRok, using default parameters 662 (Aberer et al. 2013) was used to identify jumping taxa, which also were excluded from further 663 analysis (Supplementary table S2)

664

665 Reduced dataset: We also constructed a concatenated dataset consisting of 146 representative 666 genes for easier and faster analysis. The selection of genes were made to meet several criteria: we 667 excluded genes that had less than 45 taxa (50% of the inferred taxa), a low relative Tree Certainty 668 index (Salichos et al. 2014), or that failed to group at least two of the major clades mentioned 669 above.

670

671 Missing data: To assess the impact of missing data we excluded taxa with low coverage in 672 increments from the two concatenated dataset. First we sat the lowest allowed percentage of

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673 missing data for a taxon to be 10% of the total characters (i.e. if a taxon had more than 90% data 674 missing it was excluded), the next cut-off at 20%, and finally at 30%. The number of characters in 675 the matrix was held constant. The Tree Certainty index (Salichos et al. 2014) was calculated for 676 each increment see supplementary table S2 and S3 for details. The relative Tree Certainty index 677 increased markedly when the threshold was set at 90%, but did not increase significantly after 678 that, in fact there seem to be a decrease in the relative TC value as the number of taxa drops 679 (Supplementary table S1).

680 Influence of taxa with low coverage, or uncertain position: we also remove taxa and clades from 681 Rhizaria that had a consistently low bootstrap value (< 75%) or low posterior probability (< 75 pp), 682 but that had not been flagged by RogueNaRok to see if they affected the topology of the 683 phylogenetic inference. Spongosphaera streptacantha and Sticholonche zanclea were removed 684 one by one and together from both the full and the reduced dataset. Foraminifera were also 685 removed in analyses (see table S3).

686 Removal of fast evolving sites: TIGER (Cummins & McInerney 2011) was used with default 687 settings to produce categories of fast evolving sites, 10 categories in total for each dataset. 688 Categories of fast evolving sites were removed in increments, starting with the category with the 689 fastest evolving sites, subsequently removing the category with the second fastest evolving sites 690 etc. Up to 4 categories where removed from all datasets before phylogenetic analyses.

691 Phylogenetic analyses: Phylogenetic trees were inferred for all concatenated datasets, with 692 RAxML choosing the best fitting model, and with the automatic bootstrapping criteria as 693 previously described. The preferred model was always LG+Γ (see supplementary table S3). Due to 694 the heavy demand on computational resources from Bayesian inference only six of the alignments 695 were included for analysis with the CATGTR model in Phylobayes MPI version 1.5a (Lartillot et al. 696 2013), as well as 1 dataset with the LG model. For these we ran 2 chains in parallel for at least 697 15.000 iteration only stopping when the maxdiff was >0.3 (see supplementary table S3).

698 Evolutionary Placement Algorithm: In order to place rhizarian species that had been excluded 699 when the cut-off threshold for missing data had been raised on the phylogenetic tree we used the 700 Evolutionary Placement Algorithm (EPA) included in RAxML 8.0.26 (Stamatakis et al. 2010, Berger 701 et al. 2011, Stamatakis 2014). As reference tree we used the 255-gene maximum likelihood tree 702 with a 10% missing data cut off.

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703 Genes related to cytoskeleton formation and motor proteins

704 The assembled transcriptomes from the single cells were annotated with InterProscan 5 (Jones et 705 al. 2014) as implemented in Geneious 8 (Kearse et al. 2012). The annotations were screened for 706 genes commonly involved in the formation and development of the cytoskeleton, as well as the 707 most common motor proteins using the cytoskeleton. In particular we looked for α- and β-tubulin, 708 myosin, actin, the actin regulating Arp2/3-complex consisting of seven actin-related proteins 709 (arp2, arp3, ARPC1, ARPC2, ARPC3, ARPC4 and ARPC5). Reference alignments and sequences were 710 downloaded from PFAM (http://pfam.xfam.org/), as well as relevant other recently published 711 alignments (Hou et al. 2013, Sebé-Pedrós et al. 2014, Cavalier-Smith et al. 2015) and used in BIR 712 as seed alignments with the same query database as before. In addition representatives for all the 713 genes where blasted against 6 additional non-rhizarian transcriptomes from MMETSP 714 (MMETSP0039 Eutreptiella gymnastica, MMETSP0046 Guillardia theta, MMETSP0308 Gloeochaete 715 wittrockiana, MMETSP0380 Alexandrium tamarense, MMETSP0902 Thalassiosira Antarctica, and 716 MMETSP1150 Emiliania huxleyi), as well as against the non-redundant protein database in 717 GenBank. For each gene ML trees were constructed with RAxML as before, and manually curated 718 for any confounding artefacts. Redundant and short sequences were manually removed in 719 Geneious 8 (Kearse et al. 2012) before another round of ML analysis with RAxML and a Bayesian 720 analysis with the CATGTR model implemented in Phylobayes MPI version 1.5a (Lartillot et al. 721 2013). Comparative evolutionary analyses of tubulin and the duplicated genes in the Arp2/3 722 complex were performed by examining the evolutionary rates of the paralogs separately and then 723 mapping the genes to structural models using Consurf (Ashkenazy et al. 2010, Celniker et al. 2013). 724 InterPro annotations of functional domains of myosin was performed with InterProscan 5 (Jones 725 et al. 2014, Mitchell et al. 2015).

726

727 All sequences from S. zanclea and L. setosa used in this study have been deposited in GenBank 728 with accession numbers (xxxx-xxxx). All data, alignments, and trees can be downloaded from 729 www.bioportal.no .

730 Acknowledgment

731 We would like to thank Bente Edvardsen, UiO, for providing the plankton haul from which the 732 sampled cells were isolated, the Sequencing centre at Natural History Museum in London for

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733 performing the Illumina library preparations and sequencing. We would also like to thank Simon 734 Picelli for answering questions related to the Smart-seq2 method, Fabien Burki for providing single 735 gene alignments and The Gordon and Betty Moore Foundation for making all those wonderful 736 protists transcriptomes available for the public. All analyses were run either on the Abel 737 supercomputer at The High Performance Computing cluster at University Of Oslo, or on Lifeportal 738 (www.lifeportal.uio.no). For more information on BIR see www.bioportal.no. This project was 739 funded by University of Oslo. This work was supported by grants from University of Oslo and from 740 Research Council of Norway to Shalchian-Tabrizi (NFR216475).

741

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963

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964 Table 1: Single cell transcriptome statistics

Species name Raw Reads Contigs1 GC-content (%) Predicted Genes2

Sticholonche zanclea 19,894,654 19,509 53.5 4,749

Lithomelissa setosa 11,590,658 12,212 48.8 2,122

965 1 Number of contigs assembled by Trinity (Haas et al. 2013). 2The number of genes predicted by TransDecoder in the 966 Trinity platform. 967

968 Table 2: Rhizarian transcriptomes from MMETSP (Keeling et al. 2014) used in this study.

Sample Id Phylum Species Strain Transcripts1 MMETSP0040 Chlorarachniophyta Lotharella oceanica CCMP622 17,354 MMETSP0041 Chlorarachniophyta Lotharella globosa LEX01 25,644 MMETSP0042 Chlorarachniophyta Amorphochlora amoebiformis* CCMP2058 23,387 MMETSP0045 Chlorarachniophyta Bigelowiella natans CCMP 2755 22,651 MMETSP0109 Chlorarachniophyta Chlorarachnion reptans CCCM449 26,481 MMETSP0110 Chlorarachniophyta Gymnochlora sp. CCMP2014 15,507 MMETSP0111 Chlorarachniophyta Lotharella globosa CCCM811 19,670 MMETSP0112 Chlorarachniophyta Lotharella globosa CCCM811 11,910 MMETSP0113 Chlorarachniophyta Norrisiella sphaerica BC52 14,550 MMETSP0186 Cercozoa Minchinia chitonis Missing 461 MMETSP1052 Chlorarachniophyta Bigelowiella natans CCMP623 24,186 MMETSP1318 Chlorarachniophyta Partenskyella glossopodia RCC365 15,025 MMETSP1358 Chlorarachniophyta Bigelowiella natans CCMP1242 18,273 MMETSP1359 Chlorarachniophyta Bigelowiella longifila CCMP242 15,959 MMETSP1384 Foraminifera Ammonia sp. Missing 31,225 MMETSP1385 Foraminifera Elphidium margaritaceum Missing 25,184 969 1The number of amino acid sequences for the sample. *Amorphochlora amoebiformis is called Lotharella 970 amoebiformis in MMETSP, but it was moved to the genus Amorphochlora by Ishida et al., (2011) 971

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972 Figure Legends

973 Figure 1: The two specimens sequenced. A) Lithomelissa setosa, B) Sticholonche zanclea. Scale bar 974 50 μm.

975 Figure 1 – figure supplement 1: Gene accumulation curve. The number of predicted genes is 976 plotted against subsamples of the original dataset. Each subsample is independently assembled 977 before gene prediction.

978

979 Figure 2: Bayesian phylogeny with the CATGTR model, 255 genes, 54,898 AA, and 91 taxa, maxdiff 980 0.2666. Species sequenced for this paper in bold. Thick branches represent maximal support 981 (posterior probability = 1). Number after ‘@’ is concatenated sequence length. Important clades in 982 Rhizaria are coloured for easier identification: brown = Foraminifera, dark red = Taxopodida, red = 983 Radiolaria, yellow = Endomyxa, blue= Chlorarachniophyta (Filosa), and green = Mondaofilosa 984 (Filosa). The scale bar equals the mean number of substitutions per site. The changing support 985 values for selected branches depending on the number of genes, and the number of fast evolving 986 sites removed are shown in Figure 2 – figure supplement 1.

987 Figure 2 – figure supplement 1: Influence of number of genes, and fast evolving sites on the 988 Bayesian analysis using the CATGTR model, with the exception of the dataset 146 (LG) where the 989 LG model was used. See text for discussion. Number of genes is the number of genes used in the 990 concatenated data set. Number of bins removed equals the number of bins of fast evolving sites 991 removed by TIGER (Cummins & McInerney 2011). The numbers in the matrix represent posterior 992 probability for the branch marked with an asterisk. (A) The internal relationship in SAR, the first 993 tree represents the monophyly of Stramenopiles and Alveolates, with Rhizaria as sister. The 994 second tree represents the monophyly of Alveolates and Rhizaria, with Stramenopiles as sister. (B) 995 The placement of Taxopodida: The first tree is the support value for Taxopodida as sister to 996 Radiolarians, with Foraminifera as outgroup. In the second tree Taxopodida is basal in Retaria with 997 the values showing support for the monophyly of Radiolaria and Foraminifera, excluding 998 Taxopodida.

999

1000 Figure 3: Maximum likelihood with the LG model, 255 genes, 54,898 AA, and 91 taxa. Species 1001 sequenced for this paper in bold. Thick branches represent maximal support (bootstrap = 100 %). 1002 Number after ‘@’ is concatenated sequence length. As in figure 2 important clades in Rhizaria are

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1003 coloured for easier identification: brown = Foraminifera, dark red = Taxopodida, red=Radiolaria, 1004 yellow = Endomyxa, blue= Chlorarachniophyta (Filosa), and green = Mondaofilosa (Filosa). The 1005 scale bar equals the mean number of substitutions per site. The changing support values for 1006 selected branches depending on the number of genes, and the number of fast evolving sites 1007 removed are shown in Figure 3 – figure supplement 1.

1008 Figure 3 – figure supplement 1: Influence of number of genes, and fast evolving sites on the ML 1009 analysis. Number of genes is the number of genes used in the concatenated data set. Number of 1010 bins removed equals the number of bins of fast evolving sites removed by TIGER (Cummins & 1011 McInerney 2011). The numbers in the matrix represent ML bootstrap values for the branch 1012 marked with an asterisk. (A) The internal relationship in SAR, the first tree represents the 1013 monophyly of Stramenopiles and Alveolates, with Rhizaria as sister. The second tree represents 1014 the monophyly of Alveolates and Rhizaria, with Stramenopiles as sister. (B) The placement of 1015 Taxopodida: The first tree is the support value for Taxopodida as sister to Radiolarians, with 1016 Foraminifera as outgroup. In the second tree Taxopodida is basal in Retaria with the values 1017 showing support for the monophyly of Radiolaria and Foraminifera, excluding Taxopodida.

1018

1019 Figure 4: Actin phylogeny (229 taxa, 374 AA). Thick branches represents bootstrap > 75% and 1020 posterior probability > 0.9. Some branches are collapsed to save space. Support values for selected 1021 nodes discussed in the text added for clarity. The scale bar equals the mean number of 1022 substitutions per site. The colouring scheme is the same as in figure 2. (Brown = Foraminifera, red= 1023 Radiolaria/Taxopodida, yellow = Endomyxa and blue= Filosa)

1024

1025 Figure 5: Phylogenies of the seven genes in the Arp2/3 complex. Arp2 (39 taxa, 373 AA), Arp3 (33 1026 taxa, 403 AA), ARPC1 (34 taxa, 328 AA), ARPC2 (24 taxa, 303 AA), ARPC3 (30 taxa, 181 AA), ARPC4 1027 (23 taxa, 169 AA) and ARPC5 (29 taxa, 151 AA). Colouring of groups as in figure 2 (Brown = 1028 Foraminifera, red= Radiolaria, yellow = Endomyxa and blue= Filosa). Thick branches represents 1029 bootstrap > 75% and posterior probability > 0.9 and the scale bar equals the mean number of 1030 substitutions per site. (A) The two genes with a recent duplication in Chlorarachniophyta (Arp2 1031 and APRC1). (B) The five genes without duplication in Chlorarachniophyta (ARP3, ARPC2, ARPC3, 1032 ARPC4, ARPC5).

1033

36 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

1034 Figure 6: Molecular models of the Arp2a and Arp2b paralogs in Chlorarachniophyta with 1035 evolutionary rates from Consurf superimposed on the Arp2/3 complex (PDB accession 4JD2; Arp2 1036 red, Arp3 orange, APRC1 green, ARPC2 cyan, ARPC3 pink, ARPC4 blue, ARPC5 yellow). Residues are 1037 coloured according to the evolutionary rates calculated by Consurf. Turquoise residues are highly 1038 variable and maroon means conserved residues.

1039

1040 Figure 7: Molecular models of the ARPC1a and ARPC1b paralogs in Chlorarachniophyta with 1041 evolutionary rates from Consurf superimposed on the Arp2/3 complex (PDB accession 4JD2; Arp2 1042 red, Arp3 orange, APRC1 green, ARPC2 cyan, ARPC3 pink, ARPC4 blue, ARPC5 yellow). Residues are 1043 coloured according to the evolutionary rates calculated by Consurf. Turquoise residues are highly 1044 variable and maroon means conserved residues.

1045

1046 Figure 8: Comparison of conserved residues between the two paralogs of Arp2 and the two 1047 paralogs of ARPC1 in Chlorarachniophytes superimposed on PDB accession 4JD2. A) Conserved 1048 residues from the two different paralogs of Arp2 (Arp2a and Arp2b). Red represent residues 1049 conserved in Arp2a only, blue are conserved in Arp2b only, while green residues are conserved in 1050 both paralogs. B) Conserved site from the two different paralogs of ARPC1 (ARPC1 and ARPC1b). 1051 Red sites represent residues conserved in ARPC1 only, blue are conserved in ARPC1 only, while 1052 green residues are conserved in both paralogs.

1053

1054 Figure 9: Myosin maximum likelihood phylogeny, (830 taxa, 754 AA). Groups coloured according 1055 to taxonomic affinity as in figure 2 (blue= Chlorarachniophyta, brown= Foraminifera). Branches 1056 collapsed according to myosin class affiliation and following the nomenclature of Sebé-Pedrós et 1057 al., (2014). The tree is midpoint-rooted and thick branches represents bootstrap > 75%, and 1058 Bayesian support > 0.8 pp. The scale bar equals the mean number of substitutions per site. The 1059 domain architectures for each class with representatives from Rhizaria are shown. IPR annotation 1060 of functional domains is listed Figure 9 – figure supplement 1. A complete ML tree without 1061 collapsed branches can be found in Figure 9 – figure supplement 2.

1062 Figure 9 – figure supplement 1: InterPro domains of myosins annotated with InterProscan (Jones 1063 et al. 2014, Mitchell et al. 2015).

37 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

1064 Figure 9 – figure supplement 2: Maximum likelihood tree of myosin showing all branches. Names 1065 of taxa and myosin classes are from of Sebé-Pedrós et al. (2014), except newly discovered 1066 sequences from MMETSP and new myosin classes. The scale bar equals the mean number of 1067 substitutions per site

1068

1069 Figure 10: Phylogeny of rhizarian α-tubulin (75 taxa, 453 AA). Thick branches represents bootstrap 1070 > 75% and posterior probability > 0.9. Some branches are collapsed to save space. Support values 1071 for selected nodes discussed in the text are added for clarity. The colouring scheme is the same as 1072 in figure 2. (Brown = Foraminifera, red= Radiolaria, yellow = Endomyxa, and blue= Filosa). The 1073 scale bar equals the mean number of substitutions per site.

1074

1075 Figure 11: Phylogeny of rhizarian β-tubulin (104 taxa, 456 AA). Thick branches represents 1076 bootstrap > 75% and posterior probability > 0.9. Some branches are collapsed to save space. 1077 Support values for selected nodes discussed in the text are added for clarity. The colouring scheme 1078 is the same as in figure 2. (Brown = Foraminifera, red= Radiolaria, yellow = Endomyxa, and blue= 1079 Filosa). The scale bar equals the mean number of substitutions per site.

1080

1081 Figure 12 Molecular models of paralogs of α-tubulin (α1- and α2-tub) in Retaria using PDB 1082 accession 3du7 as template. Residues are coloured according to the evolutionary rates calculated 1083 by Consurf. Turquoise residues are highly variable and maroon means conserved residues.

1084 Figure 13: Molecular models of paralogs of β-tubulin (β1- and β2-tub) in Retaria using PDB 1085 accession 3du7 as template. Residues are coloured according to the evolutionary rates calculated 1086 by Consurf. Turquoise residues are highly variable and maroon means conserved residues.

1087

1088 Figure 14. Phylogenetic tree of Rhizaria based on the full dataset, 255 genes, summarizing the 1089 major evolutionary events. Taxa with large portions of missing data are placed on the maximum 1090 likelihood reference tree with the Evolutionary Placement Algorithm (EPA; Berger et al., 2011). 1091 Taxa in bold are sequenced for this study. Arrows mark important evolutionary events, 1092 morphological changes and gene duplications. Thick branches are highly supported withe 1093 bootstrap support >90% and posterior probability > 0.9. Branches in grey are the most likely 1094 placement of taxa from EPA with numbers showing the expected likelihood weights for the 38 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

1095 placement. Branches that differ between maximum likelihood and Bayesian trees are marked 1096 with dashed lines. For Sticholonche zanclea the blue line represent the Bayesian CATGR placement 1097 with posterior probability, red dashed line represents the maximum likelihood LG placement with 1098 bootstrap support. For a further discussion of the placement of Sticholonche zanclea and the 1099 relationship between Alveolates, Stramenopiles and Rhizaria see the text. The scale bar equals the 1100 mean number of substitutions per site.

1101

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Figure 1

A B bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 1 - figure supplement 1

# predicted genes

4500

4000

3500

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2500 Stcholonche zanclea Lithomelissa setosa 2000

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0 10 20 30 40 50 60 70 80 90 100 % of raw reads bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 2

Nonionellina sp. @4207 Globobulimina turgida @6820 Elphidium sp. @27337 Foraminifera Ammonia sp. @28023 Retculomyxa filosa @27304 0.71 0.98 0.97 Collozoum sp. @3943 Lithomelissa setosa @3315 0.97 Spongosphaera streptacantha @5035 Radiolaria Phyllostaurus sp. @9342 Astrolonche sp. @15589 Rhizaria Stcholonche zanclea @10190 Taxopodida Gromia sphaerica @12626 Endomyxa Filoreta tenera @4344 Bigelowiella natans @48144 Bigelowiella longifila @26482 Norrisiella sphaerica @32413 0.97 Chlorarachnion reptans @37172 0.83 Lotharella oceanica @29843 Chlorararchnio- Lotharella globosa @36021 phyta Partenskyella glossopodia @37249 Amorphochlora amoebiformis @35889 SAR Gymnochlora sp. @33562 0.97 Paracercomonas marina @8708 Monadoflosa Aulacantha scolymantha @4206 Toxoplasma gondii @41434 Neospora caninum @40818 Alveolata Eimeria tenella @4866 Theileria parva @12383 Cryptosporidium parvum @37045 0.9 Karenia brevis @9352 Alexandrium sp. @14177 Amphidinium carterae @5806 Oxyrrhis marina @12320 Perkinsus marinus @41224 Tetrahymena pyriformis @44657 Paramecium tetraurelia @43533 Phaeodactylum tricornutum @44510 0.87 Fragilariopsis cylindrus @18272 Stramenopiles Fragilaria pinnata @7669 Thalassiosira pseudonana @45605 Aureococcus anophagefferens @45054 Laminaria sp. @4191 Ectocarpus siliculosus @50323 Pythium oligandrum @8857 Phytophthra sp. @51865 Saprolegnia parasitca @49304 Isochrysis galbana @10168 Emiliania huxleyi @39038 Coccolithus braarudii @7487 Haptophyta Prymnesium parvum @10874 Pavlova lutheri @11848 Sorghum bicolor @48440 Oryza satva @47973 Viridiplantae Brachypodium distachyon @48433 Populus trichocarpa @47554 Arabidopsis sp. @49206 Mimulus gutatus @46192 Physcomitrella patens @50589 Mesostgma viride @9094 Volvox carteri @48592 Chlamydomonas reinhardti @46229 Coccomyxa sp. @48075 Ostreococcus sp. @44191 Micromonas pusilla @30432 Eucheuma dentculatum @6958 Chondrus crispus @8205 Rhodophyta Gracilaria changii @11385 Coralline sp. @11078 Porphyra yezoensis @20935 Porphyridium cruentum @27510 Glaucocysts nostochinearum @14982 Cyanophora paradoxa @15916 Glaucophyta Plagioselmis sp. @13451 Guillardia theta @52524 Rhodomonas salina @4709 Cryptophyta Roombia truncata @37306 0.54 Reclinomonas americana @21383 Histona aroides @7324 Excavata Jakoba sp. @17150 Seculamonas ecuadoriensis @16794 Stachyamoeba lipophora @7582 Naegleria gruberi @45100 Euglena sp. @17257 Homo sapiens @54136 Branchiostoma floridae @51760 Nematostella vectensis @51596 Opisthokonta Monosiga brevicollis @31790 Phycomyces blakesleeanus @46490 Batrachochytrium dendrobatdis @50017 Dictyostelium discoideum @48753 Acanthamoeba sp. @23847 Amoebozoa

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Figure 2 - figure supplement 1

A) SAR - relatonship B) Placement of Taxopodida Bayesian

Number Number StramenopilesAlveolataRhizaria StramenopilesAlveolataRhizaria TaxopodidaRadiolariaForaminifera TaxopodidaRadiolariaForaminifera of genes of bins removed * * * * 0 1 - - 0.71 255 4 1 - - 0.97 146 0 1 - - 0.81 146 (LG) 0 1 - 0.67 - bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 3 Maximum likelihood Ammonia sp. @28023 Elphidium sp. @27337 Nonionellina sp. @4207 Foraminifera Globobulimina turgida @6820 Retculomyxa filosa @27304 Collozoum sp.@3943 73 Lithomelissa setosa @3315 67 Spongosphaera streptacantha @5035 Radiolaria 88 Astrolonche sp. @15589 Phyllostaurus sp. @9342 Rhizaria Stcholonche zanclea @10190 Taxopodida Filoreta tenera @4344 Gromia sphaerica @12626 Endomyxa Bigelowiella natans @48144 Bigelowiella longifila @26482 Norrisiella sphaerica @32413 81 Chlorarachnion reptans @37172 65 Lotharella globosa @36021 Chlorararchnio- Lotharella oceanica @29843 phyta Partenskyella glossopodia @37249 Gymnochlora sp. @33562 SAR Amorphochlora amoebiformis @35889 Aulacantha scolymantha @4206 Monadoflosa Paracercomonas marina @8708 Neospora caninum @40818 Toxoplasma gondii @41434 Alveolata Eimeria tenella @4866 Theileria parva @12383 Cryptosporidium parvum @37045 Alexandrium sp. @14177 Karenia brevis @9352 Amphidinium carterae @5806 Oxyrrhis marina @12320 Perkinsus marinus @41224 Tetrahymena pyriformis @44657 Paramecium tetraurelia @43533 83 Phaeodactylum tricornutum @44510 Fragilariopsis cylindrus @18272 Stramenopiles Fragilaria pinnata @7669 Thalassiosira pseudonana @45605 79 Aureococcus anophagefferens @45054 Laminaria sp. @4191 Ectocarpus siliculosus @50323 Phytophthora sp. @51865 Pythium oligandrum @8857 Saprolegnia parasitca @49304 Emiliania huxleyi @39038 Isochrysis galbana @10168 Haptophyta Coccolithus braarudii @7487 Prymnesium parvum @10874 Pavlova lutheri @11848 Populus trichocarpa @47554 Arabidopsis sp. @49206 Viridiplantae Mimulus gutatus @46192 75 Sorghum bicolor @48440 Oryza satva @47973 Brachypodium distachyon @48433 Physcomitrella patens @50589 Mesostgma viride @9094 Chlamydomonas reinhardti @46229 Volvox carteri @48592 Coccomyxa sp. @48075 Micromonas pusilla @30432 81 Ostreococcus sp. @44191 Chondrus crispus @8205 Eucheuma dentculatum @6958 Rhodophyta Gracilaria changii @11385 Coralline sp. @11078 79 Porphyra yezoensis @20935 Porphyridium cruentum @27510 94 Plagioselmis sp. @13451 Guillardia theta @52524 Cryptophyta Rhodomonas salina @4709 Roombia truncata @37306 52 Cyanophora paradoxa @15916 Glaucophyta Glaucocysts nostochinearum @14982 Histona aroides @7324 75 Reclinomonas americana @21383 Excavata Seculamonas ecuadoriensis @16794 Jakoba sp. @17150 Naegleria gruberi @45100 87 Stachyamoeba lipophora @7582 Euglena sp. @17257 Branchiostoma floridae @51760 Homo sapiens @54136 Opisthokonta Nematostella vectensis @51596 Monosiga brevicollis @31790 Batrachochytrium dendrobatdis @50017 Phycomyces blakesleeanus @46490 Acanthamoeba sp. @23847 Dictyostelium discoideum @48753 Amoebozoa

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Figure 3 - figure supplement 1

Maximum A) SAR - relatonship B) Placement of Taxopodida Likelihood

Number Number of StramenopilesAlveolataRhizaria StramenopilesAlveolataRhizaria TaxopodidaRadiolariaForaminifera TaxopodidaRadiolariaForaminifera genes of bins removed * * * * 0 - 96 88 - 255 4 - 67 - 50 - 85 146 0 87 - 4 74 - - 75 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 4

Foraminifera Elphidium sp. (3 sequences) AAX09576 | Ammonia sp. AAX09585| Tretomphalus sp. MMETSP1384 | Ammonia sp. Ammonia sp. (3 sequences) MMETSP1384 | Ammonia sp. MMETSP1384 | Ammonia sp.

AAX09593| Trochammina sp. actn 1 AAX09579| Haynesina germanica MMETSP1385 | Elphidium margaritaceum MMETSP1384 | Ammonia sp. AAX09586| Reophax sp. AAX09591| Sorites sp. 1/2 R. filosa Retculomyxa filosa (5 sequecnes) (5 sequences) AAX09573| Allogromia sp. 26/- CAB42989|Allogromia sp. AAX09584| Edaphoallogromia australica BAE48506| Planoglabratella opercularis ADK98507| Ovammina opaca Lithomelissa setosa Lithomelissa setosa Radiolaria 10/- BAK61737| Larcopyle butschlii 59/0.98 Stcholonche zanclea Taxopodida AAR88393| Sorosphaerula veronicae AAR88394| Sorosphaerula veronicae Endomyxa a CAM98703| Plasmodiophora brassicae AAR88397| Spongospora subterranea AAS13681| Urosporidium crescens 32/0.6 AAS13677| Minchinia tapets Endomyxa b 6/- AAS13675| Minchinia tapets AAS13680| Minchinia teredinis CAL69233| Bonamia ostreae CAL69235| Bonamia ostreae AAS13679| Minchinia teredinis 39/0.5 AAS13682| Haplosporidium sp. 41/0.71 AAS13666| Haplosporidium costale 14/0.68 AAS13676| Minchinia tapets 16/- AAS13667| Haplosporidium louisiana AAS13671| Haplosporidium nelsoni AGR40660| Leptophrys sp. AAQ75374| Gromia oviformis AAS13683| Haplosporidian parasite Endomyxa c AAT42195| Gromia oviformis AAS13673| Minchinia chitonis 72/1.0 AAS13678| Minchinia teredinis AAS13670| Haplosporidium louisiana ABP93408| Filoreta tenera 22/0.62 MMETSP1384 | Ammonia sp. AAX09519| Bolivina sp. Foraminifera AAX09563| Rosalina sp. AAX09561| Tretomphalus sp. AAX09506| Rosalina sp. AAX09514| Ammonia sp. AAX09530| Elphidium cf. williamsoni AAX09531| Elphidium cf. williamsoni MMETSP1384 | Ammonia sp. AAX09571| Globigerinella siphonifera AAX09538| Hyalinea balthica AAX09558| Nonionella labradorica AAX09533| Globobulimina turgida 59/0.97 AAX09567| Stainforthia fusiformis AAX09562| Reophax sp. MMETSP1384 | Ammonia sp. MMETSP1385 MMETSP1384 | Ammonia sp. E.margaritaceum MMETSP1385 | Elphidium margaritaceum actn 2 AAX09518|Amphisorus hemprichii AAX09564| Sorites sp. AAX09548| Amphisorus kudakajimaensis AAX09552| Marginopora vertebralis AAX09622| Toxisarcon alba AAX09550| Miliammina fusca AAX09543| Miliolidae sp. CAB43029| Retculomyxa filosa AAX09526| Bathysiphon sp. AAX09525| Bathysiphon sp. AEV46060| Allogromia latcollaris 16/- AAX09540| Edaphoallogromia australica MMETSP1385 | Elphidium margaritaceum MMETSP1384 | Ammonia sp. 30/- MMETSP1385 | Elphidium margaritaceum MMETSP1384 | Ammonia sp. Astrolonche sp. 42/0.78 12/- Stcholonche zanclea Stcholonche zanclea Taxopodida AAS79226| Collozoum inerme 36/0.87 AAS79225| Collozoum inerme BAK61743| Collozoum amoeboides BAK61750| Sphaerozoum punctatum Radiolaria AAS79227| Thalassicolla pellucida Lithomelissa setosa 42/1.0 Bigelowiella natans (6 sequences) MMETSP1359 | Bigelowiella longifila Strain CCMP242 Chlorarachniophyta MMETSP0111 | Lotharella globosa Strain CCCM811 MMETSP0040| Lotharella oceanica Strain CCMP622 54/1.0 MMETSP0045 | Bigelowiella natans Strain CCMP 2755 MMETSP1359 | Bigelowiella longifila Strain CCMP242 MMETSP1318| Partenskyella glossopodia Strain RCC365 MMETSP0042| Amorphochlora amoebiformis Strain CCMP2058 32/0.60 MMETSP0111| Lotharella globosa Strain CCCM811 MMETSP0040| Lotharella oceanica Strain CCMP622 MMETSP0041| Lotharella globosa Strain LEX01 AAR88398| Lotharella globosa AAP34634| Gymnochlora stellata MMETSP0113| Norrisiella sphaerica Strain BC52 MMETSP0042| Amorphochlora amoebiformis Strain CCMP2058 MMETSP1318 | Partenskyella glossopodia Strain RCC365 29/0.51 MMETSP0109| Chlorarachnion reptans Strain CCCM449 46/0.97 MMETSP0110| Gymnochlora sp. Strain CCMP2014 AF363528| Bigelowiella natans MMETSP1359| Bigelowiella longifila Strain CCMP242 AAP93826| Hedriocysts retculata AAP93836| Clathrulina elegans 35/0.87 ACR46941| Gymnophrys sp. ACR46939| Cholamonas cyrtodiopsidis Cercomonas (4 sequences) ADK26634| Capsellina sp. AAP93827| Lecythium sp. ACR46940| Heteromita globosa ACR46937| Bodomorpha minima ABP73251| Euglypha rotunda ACN54041| Paulinella chromatophora ACN54042| Paulinella chromatophora 47/0.98 ABJ80927| Thaumatomonas sp. Alveolata Stramenopiles

0.2 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 5

A Arp2 ARPC1 Amorphochlora amoebiformis Arp2a Gymnochlora sp. Chlorarachniophyta Lotharella oceanica Lotharella globosa Lotharella globosa ARPC1a Bigelowiella natans Gymnochlora sp. Chlorarachniophyta Bigelowiella longifila Bigelowiella natans Chlorarachnion reptans Bigelowiella longifila Bigelowiella natans Arp2b Chlorarachnion reptans Norrisiella sphaerica Amorphochlora amoebiformis Partenskyella glossopodia Bigelowiella natans Lotharella oceanica Bigelowiella longifila ARPC1b Lotharella globosa Norrisiella sphaerica Elphidium martgaritaceum

Retaria Lotharella oceanica Ammonia sp. Lotharella globosa ETO23469 Retculomyxa filosa Partenskyella glossopodia Stcholonche zanclea

CEP01544 | Plasmodiophora brassicae Retaria Lithomelissa setosa Ammonia sp. XP_012203460 Saprolegnia parasitca Elphidium margaritaceum XP_009822902 Aphanomyces astaci Stramenopiles CCA20063 Albugo laibachii XP_005829519 Guillardia theta CBJ31870 Ectocarpus siliculosus CEO98710 Plasmodiophora brassicae MMETSP0039 Eutreptella Gymnastca XP_005772488 Emiliania huxleyi XP_002669371 Naegleria gruberi MMETSP0308 Gloeochaete witrockiana MMETSP1150 Emiliania huxleyi Opisthokonta Opisthokonta Amoebozoa Amoebozoa + Glaucophyta MMETSP0046 Guillardia theta

0.2 0.2

B Arp3 29/0.95 Chlorarachniophyta (8) S. zanclea Foraminifera (3 sequences) ARPC4 CEO99505|Plasmodiophora brassicae Chlorararchniophyta (7) Non-rhizarian Arp2 MMETSP0039 | Eutreptella Gymnastca Foraminifera (3) 0.2 ARPC2 Non-rhizarian ARPC4 Chlorarachniophyta (9) 0.1 CEP02911 | Plasmodiophora brassicae Foraminifera (2 ) ARPC5 Stcholonche zanclea Chlorarachniophyta (7) Non-rhizarian ARPC2 Stramenopiles (2) 0.3 ETO23706|Retculomyxa filosa Stcholonche zanclea ARPC3 MMETSP1385 | Elphidium margaritaceum Chlorarachniophyta (9) CEO94794|Plasmodiophora brassicae Non-rhizarian ARPC5 Foraminifera (3) CEP02429|Plasmodiophora brassica 0.3 Non-rhizarian ARPC3 0.2 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 6

Arp2 Arp2a ARPC1 Arp2b

ARPC5

ARPC4 ARPC3 Arp3

ARPC2

120° Variable Conserved

Arp2a Arp2b bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 7

ARPC1 Arp2 ARPC1a ARPC1b

ARPC5

ARPC4 ARPC3 Arp3

ARPC2

120°

Variable Conserved ARPC1a ARPC1b ARPC1a ARPC1b bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 8

Arp2 a vs. b ARPC1 a vs. b Arp2 ARPC1

ARPC5

ARPC4

ARPC3 Arp3

ARPC2 Conserved in Arp2a Conserved in ARPC1a Conserved in Arp2b Conserved in ARPC1b Conserved in both 120° Conserved in both

Arp2 a vs. b ARPC1 a vs. b bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 9

Myosin If Chlorarachniophyta 1 Myosin head IQ Myosin TH1 SH3 WW 2 Chlorarachniophyta 2 Myosin head IQ Myosin TH1 SH3 Myosin If Myosin I a/b/c/h/d/g/k Myosin I a/b/c/h/d/g/k P. infestans XP002998568 Myosin I a/b/c/h/d/g/k Myosin IV Chlorarachniophyta 1 WW Myosin head MyTH4 WW Chlorarachniophyta 2 Myosin head MyTH4 ( WW ) Chlorarachniophyta 3 DUF Myosin head IQ MyTH4 WW Chlorarachniophyta 4 Myosin head IQ MyTH4 WW Chlorarachniophyta 5 ( DUF ) WW MN Myosin head IQ MyTH4 WW Chlorarachniophyta 6 WW MN Myosin head MyTH4 Foraminifera 1 MN Myosin head MyTH4 WW 4 Foraminifera 2 WW Myosin head MyTH4 Myosin IV A. castellani 1_9 E. siliculosus CBJ33811 Myosin XXXV Chlorarachniophyta 1 DH PH FYVE MN Myosin head MyTH4 Chlorarachniophyta 2 Myosin head MyTH4 Haptophyta orphan - NEW Myosin XIV Myosin XXXVI Chlorarachniophyta 1 Myosin head PH Chlorarachniophyta 2 Myosin head EF PH G. theta MMETSP0046 Myosin XXIX Myosin V, Vp, VIII, XXI, XIX, XXVII, XXXIII, Cryptophyta orphan G. theta 78981 Myosin II, XVIII, XXXII Myosin VI, XXIII, XXX, Hapt. orphan Myosin XXXVII Chlorarachniophyta 1 Myosin head CH LRR_RI x3 Myosin head IQ Chlorarachniophyta 2 LRR_RI x3 Chlorarachniophyta 3 Myosin head CH Foraminifera Myosin head IQ PH Myosin XIII, XXXI Myosin III, IX, VII, X, XV, XVII, XX, XXIV, Myosin XXII XXVI, Apusozoa orphan Myosin XXV

0.4 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 9 - Figure supplement 1

Functional InterPro domains

Myosin head IPR001609

WW IPR001202

IQ IPR000048

Myosin TH1 IPR010926

EF IPR002048

SH3 IPR001452

CH IPR001715

LRR_RI IPR032675

MyTH4 IPR000857

DUF IPR025640

MN IPR004009

DH IPR000219

PH IPR011993

FYVE IPR013083

MORN IPR003409

RCC1 IPR000408 100 Figure 9 - fgure supplement 2 93 11400_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 72 26181_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 11656_1_TaxId_629695_Gymnochlora_sp_CCMP2014 85 21750_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 91 100 5374_1_TaxId_91324_Lotharella_globosa_LEX01 Functional InterPro domains 27711_1_TaxId_91324_Lotharella_globosa_LEX01 83 10121_1_TaxId_91324_Lotharella_globosa_LEX01 Myosin head IQ Myosin TH1 SH3 WW WW 69 3730704_1_TaxId_227086_Bigelowiella_natans_CCMP623 100 100 1537_1_TaxId_227086_Bigelowiella_natans_CCMP1242 Myosin head IPR001609 21909_1_TaxId_227086_Bigelowiella_natans_CCMP623 3990_1_TaxId_753081_Bigelowiella_natans_CCMP_2755 53403_1_TaxId_91329_Norrisiella_sphaerica_BC52 WW IPR001202 91 65160_1_TaxId_227086_Bigelowiella_natans_CCMP1242 54 36 30851_1_TaxId_227086_Bigelowiella_natans_CCMP623 100 5817650_1_TaxId_227086_Bigelowiella_natans_CCMP623 IQ IPR000048 3292_1_TaxId_227086_Bigelowiella_natans_CCMP623 50 27510_1_TaxId_227086_Bigelowiella_natans_CCMP623 100 24701_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 Myosin TH1 IPR010926 98 9132_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 Myosin head IQ Myosin TH1 SH3 100 85 100 422_1_TaxId_629695_Gymnochlora_sp_CCMP2014 4716_1_TaxId_629695_Gymnochlora_sp_CCMP2014 EF IPR002048 3242_1_TaxId_552666_Partenskyella_glossopodia_RCC365 100 27051_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 14821_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 SH3 IPR001452 73 Dpul_94402 66 Ctel_95339 63 99 Hsap_NP_004989 CH IPR001715 85 Hsap_NP_036467 Nvec_1162932_8 83 85 Ocar_g5747_t1 LRR_RI IPR032675 Aque_228465_14 57 100 Sros_PTSG_00762_4 MyTH4 Mbre_17459_6 IPR000857 58 Mvib_comp12887 52 Cowc_CAOG_02007_3 Myosin If 100 DUF IPR025640 94 Pgem_Contig12529 75 Pgem_Contig12528 93 33 Awhi_Contig13230 MN IPR004009 Apar_comp23834 Clim_Contig3292 100 50 Spun_SPPG_01225 DH IPR000219 29 Bden_Batde5_91391 Clim_Contig1063 100 Sarc_SARC_15169 PH 19 92 Myosin head Myosin TH1 SH3 IPR011993 28 100 Cfra_g4021 24 Apar_comp22927 Awhi_Contig28258 FYVE IPR013083 Mvib_comp8208 Ttra_AMSG_05284 55 MORN 96 Ccin_CC1G_13719 IPR003409 Cneo_XP_568003 76 Umay_XP_760259 95 RCC1 82 Tmel_XP_002840103 IPR000408 56 Aory_AoQ2US4 4 100 Spom_NP_595402_1 100 Rory_9588 99 Pbla_Phybl2_106479 98 Mver_MVEG_02573 Amac_AMAG_12690 Chlorarachniophyta 92 Cowc_CAOG_02007_6 100 Foraminifera 18 99 Ddis_XP_643060 Ppal_EFA78349_1 32 Acas_1_3 Ngru_XP_002669917 4 100 100 MYOB_DICDI/11-678 100 Ddis_XP_636359 Ppal_EFA78234_1 25 Acas_1_4 100 100 Ppal_EFA84632_1 71 Ddis_XP_643950 Acas_1_15 72 Pinf_XP_002906848 Lmaj_XP_001686193 100 Ddis_XP_643200 28 100 100 MYOD_DICDI/9-674 75 Ppal_EFA81458_1 35 Acas_1 Ttra_AMSG_02590 Ngru_XP_002680436 MYOA_DICDI/14-707 100 65 Hsap_NP_001094891 Hsap_NP_001074248 42 Ctel_120713 51 88 Dmel_NP_728594 85 Dpul_199690 Nvec_1162932_4 78 56 Ocar_g8308_t1 Aque_228465_2 32 Mvib_comp14411 5 39 99 Mbre_17459_16 100 Sros_PTSG_00762_19 Mbre_17459_8 100 77 Awhi_Contig13344 Pgem_Contig71137 Apar_comp23938 79 59 Dpul_198464 Dmel_NP_523538 55 66 Nvec_1162932_3 100 44 Hsap_EAL23748 96 Hsap_EAW80221 Ctel_167519 44 100 Aque_228465_10 95 Aque_228465_17 93 Mbre_17459_32 100 Sros_PTSG_00762_8 Ocar_g878_t1 94 Mvib_comp14986 39 Cowc_CAOG_02007_9 100 99 Hsap_NP_005370 MYO1A_BOVIN/10-681 74 Hsap_NP_036355 100 73 Dpul_57481 37 Dmel_NP_001027208 72 Ctel_166394 Ocar_g3678_t1 52 15 54 Nvec_1162932_14 49 Aque_228465_5 100 Myosin I a/b/c/d/h/g/k 92 Sros_PTSG_00762_14 Mbre_17459_10 75 39 Mvib_comp13454 Mvib_comp15884 Cowc_CAOG_02007_17 54 Mvib_comp15194 77 56 Cowc_CAOG_02007_11 100 Mbre_17459_19 96 Sros_PTSG_00762_17 50 58 Pgem_Contig67758 100 Pgem_Contig41835 Awhi_Contig70925 33 32 Awhi_Contig56589 Spun_SPPG_08031 91 92 Ttra_AMSG_07376 24 Ttra_AMSG_07592 60 Ttra_AMSG_09890 25 Ttra_AMSG_07283 100 56 Ppal_EFA85721_1 Ddis_XP_636359_3 100 100 MYOE_DICDI/10-680 85 Ddis_XP_636359_2 Ppal_EFA77144_1 Ttra_AMSG_02589 30 30 Esil_CBN78038 Ehux_457182 Ehux_75288 Pinf_XP_002998568 99 99 Ngru_XP_002683472 65 Ngru_XP_002676561 Ngru_XP_002682373 Ngru_XP_002676946 31 100 4749_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 73 26683_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 22335_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 WW Myosin head MyTH4 WW WW 100 6936_1_TaxId_91324_Lotharella_globosa_CCCM811 100 69 2684_1_TaxId_227086_Bigelowiella_natans_CCMP623 Bnat_44500 87 53321_1_TaxId_91329_Norrisiella_sphaerica_BC52 100 100 369_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 100 28029_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 7214_1_TaxId_629695_Gymnochlora_sp_CCMP2014 Myosin head MyTH4 ( WW ) Bnat_138429 100 100 76 21390_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 59 16206_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 50 10238_1_TaxId_629695_Gymnochlora_sp_CCMP2014 68333_1_TaxId_552666_Partenskyella_glossopodia_RCC365 63 100 3199_1_TaxId_91324_Lotharella_globosa_LEX01 7327_1_TaxId_91324_Lotharella_globosa_CCCM811 DUF Myosin head IQ MyTH4 WW 100 100 22267_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 17740_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 100 46 5204_1_TaxId_227086_Bigelowiella_natans_CCMP623 Bnat_89109 100 48 68808_1_TaxId_641309_Lotharella_oceanica_CCMP622 34 1636_1_TaxId_91324_Lotharella_globosa_CCCM811 36 2959_1_TaxId_552666_Partenskyella_glossopodia_RCC365 92 Bnat_140911 9015_1_TaxId_629695_Gymnochlora_sp_CCMP2014 44 100 14930_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 Myosin head IQ MyTH4 WW 100 22743_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 9773_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 Bnat_127316 3 18569_1_TaxId_91324_Lotharella_globosa_LEX01 100 0 0 12561_1_TaxId_91324_Lotharella_globosa_CCCM811 0 8_1_TaxId_91324_Lotharella_globosa_CCCM811 6 0 6705_1_TaxId_91324_Lotharella_globosa_CCCM811 Myosin IV 1329130_1_TaxId_91324_Lotharella_globosa_LEX01 2 23651_1_TaxId_91324_Lotharella_globosa_CCCM811 100 6105_1_TaxId_91324_Lotharella_globosa_LEX01 50 22188_1_TaxId_91324_Lotharella_globosa_CCCM811 8534_1_TaxId_91324_Lotharella_globosa_CCCM811 44 100 7052_1_TaxId_629695_Gymnochlora_sp_CCMP2014 32 13821_1_TaxId_629695_Gymnochlora_sp_CCMP2014 6319_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 100 2083_1_TaxId_552666_Partenskyella_glossopodia_RCC365 DUF WW MN Myosin head IQ MyTH4 WW 65 Bnat_41654 ( ) 100 65464_1_TaxId_227086_Bigelowiella_natans_CCMP1242 63 68 19789_1_TaxId_227086_Bigelowiella_natans_CCMP623 96 9476_1_TaxId_227086_Bigelowiella_natans_CCMP623 13121_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 93 9014938_1_TaxId_629695_Gymnochlora_sp_CCMP2014 100 13501_1_TaxId_629695_Gymnochlora_sp_CCMP2014 88 3937_1_TaxId_629695_Gymnochlora_sp_CCMP2014 9363_1_TaxId_629695_Gymnochlora_sp_CCMP2014 100 27949_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 1065_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 100 100 WW WW Myosin head MyTH4 100 5958_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 100 30175_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 68 22975_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 Bnat_34821 79 100 5591_1_TaxId_91324_Lotharella_globosa_CCCM811 79 2233_1_TaxId_91324_Lotharella_globosa_CCCM811 91 100 ETO25680|class_VII_unconventional_myosin 77 ETO02461|hypothetical_protein_RFI_34970_partial 0 100 ETN98288|myosin_IA_partial MN Myosin head MyTH4 WW 100 7978_1_TaxId_29189_Ammonia_sp_ 4 6494_1_000861_TaxId_933848_Elphidium_margaritaceum 100 ETO14295|Rab_GTPase_binding_protein_partial ETO28708|class_VII_unconventional_myosin 100 58 100 Ttra_AMSG_02747 69 Ttra_AMSG_00218 Ttra_AMSG_08941 88 Ttra_AMSG_07795 80 100 Pgem_Contig82264 WW Myosin head MyTH4 81 54 Awhi_Contig11171 Pgem_Contig13705 100 Acas_1_6 Acas_1_16 Acas_1_9 Esil_CBJ33811 19 52 71 23017_1_TaxId_753081_Bigelowiella_natans_CCMP_2755 100 6130_1_TaxId_753081_Bigelowiella_natans_CCMP_2755 65888_1_TaxId_227086_Bigelowiella_natans_CCMP1242 38 1638_1_TaxId_227086_Bigelowiella_natans_CCMP623 100 75 5242_1_TaxId_629695_Gymnochlora_sp_CCMP2014 9259_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 DH PH FYVE Myosin head MyTH4 100 27 29137_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 11924_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 98 100 13045_1_TaxId_629695_Gymnochlora_sp_CCMP2014 4567_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 Myosin head MyTH4 5584_1_TaxId_629695_Gymnochlora_sp_CCMP2014 100 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023933379|m_95489 5 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023963495|m_51407 19 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023938211|m_86915 Myosin head MORN MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023938867|m_84654 7 Haptophyta orphan - NEW 100 42 Tthe_XP_001013713 Tthe_XP_001017158 46 Tthe_XP_001010638 99 87 Tthe_XP_001015568 Tthe_XP_001027753 99 99 Tthe_XP_001032548 0 Tthe_XP_001032549 Tthe_XP_001026495 Myosin head IQ RCC1 RCC1 57 100 Ptet_A0E835_A0E835 1-6 96 Ptet_A0BUP0_A0BUP0 30 82 46 Ptet_A0CKH1_A0CKH1 94 Ptet_A0D4P3_A0D4P3 Tthe_XP_001018813 99 Tthe_XP_001014642 Myosin XIV 77 Tthe_XP_001013408 Tthe_XP_001007637 100 Ptet_A0D6K3_A0D6K3 Ptet_A0BQ00_A0BQ00 94 74 100 Pfal_Q8IDR3_MYOA 98 Tgon_XP_002368942 99 Tgon_XP_002365418 100 Tgon_XP_002366595 69 Tgon_XP_002364848 85 Pfal_Q8I465_Q8I465 Tgon_XP_002366825 Pmar_XP_002780157 97 67 7343_1_TaxId_91324_Lotharella_globosa_CCCM811 100 15581_1_TaxId_91324_Lotharella_globosa_CCCM811 14439_1_TaxId_91324_Lotharella_globosa_CCCM811 19 35 4145_1_TaxId_91324_Lotharella_globosa_CCCM811 Myosin head PH 100 98 2008_1_TaxId_629695_Gymnochlora_sp_CCMP2014 95 16871_1_TaxId_629695_Gymnochlora_sp_CCMP2014 82 3301_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 Bnat_36277 36 68 13543_1_TaxId_629695_Gymnochlora_sp_CCMP2014 Myosin XIV - like or 84 18482_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 4 Bnat_75564 Chlorachniophyta orphan 100 100 21870_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 7709_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 100 2784_1_TaxId_91329_Norrisiella_sphaerica_BC52 100 69 14926_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 100 5261_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 5928_1_TaxId_629695_Gymnochlora_sp_CCMP2014 Myosin head EF PH 0 Bnat_132607 MMETSP0046_Guillardia_theta|cds_CAMNT_0000755029|m_36111 98 50 Ptri_XP_002181408 Tpse_XP_002291453 88 Ngad_20744 100 36 Ngad_06667 Myosin XXIX Esil_CBJ27624 68 Pinf_XP_002998463 100 100 Ptet_A0CVB8_A0CVB8 Ptet_A0E4V4_A0E4V4 Tthe_XP_001028088 100 63 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048400801|m_15038 Tpse_XP_002286167 48 Ptri_XP_002181360 100 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048432041|m_33750 97 Tpse_XP_002293770 100 95 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048420683|m_30394 98 Tpse_XP_002294196 Tpse_XP_002297047 100 Ptri_XP_002184750 100 Tpse_XP_002289050 99 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048422651|m_34150 100 Tpse_XP_002288954 100 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048440243|m_2224 43 88 77 Tpse_XP_002294433 62 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048401891|m_13165 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048432239|m_25676 Ptri_XP_002181018 Myosin XXVII 100 96 Esil_CBN77168 12 Esil_CBJ28361 Esil_CBJ27444 100 100 Tpse_XP_002296378 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048420915|m_24569 4 46 Ptri_XP_002179003 99 100 Esil_CBN73971 Esil_CBN73968 Ngad_31040 33 69 Pinf_XP_002900773 Pinf_XP_002907688 100 26 Pinf_XP_002909135 Pinf_XP_002894917 88 9 Pinf_XP_002896847 40 Pinf_XP_002908680 Pinf_XP_002905000 100 Pfal_Q8IE50_Q8IE50 100 Tgon_XP_002370590 100 Pmar_XP_002788507 45 Pmar_XP_002772878 100 100 Gthe_158776 100 MMETSP0046_Guillardia_theta|cds_CAMNT_0000767341|m_35451 90 MMETSP0046_Guillardia_theta|cds_CAMNT_0000783265|m_552 Gthe_72379 62 100 Gthe_44931 Gthe_48710 64 Gthe_165588 Cryptophyta orphan 27 Gthe_68130 64 Gthe_82670 48 Gthe_57369 Gthe_158791 100 25 Tpse_XP_002287576 100 MMETSP0902_Thalassiosira_antarctica|cds_CAMNT_0048439303|m_5533 Tpse_XP_002297174 100 Ptri_XP_002186480 60 100 Ptri_XP_002179793 21 48 Ptri_XP_002176413 51 Ptri_XP_002176359 28 Esil_CBN79305 37 Ngad_02898 33 Esil_CBJ26663 Pinf_XP_002899967 Pinf_XP_002907993 29 98 81 Pinf_XP_002908251 Myosin XXI 61 Pinf_XP_002908185 51 75 Pinf_XP_002998411 Pinf_XP_002906363 97 Pinf_XP_002896433 Pinf_XP_002904187 44 96 Esil_CBJ31129 Esil_CBJ26119 100 31 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023974505|m_83166 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023940039|m_98645 68 Ehux_461567 100 58 MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027082367|m_6122 100 MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027096629|m_26647 100 MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027105741|m_33199 Cryptophyta orphan - New MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027119815|m_11700 MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027119763|m_9835 100 Atha_AT1G04160 96 Atha_AT5G43900 81 Atha_AT4G28710 27 Atha_AT2G20290 0 100 65 Sbic_01g000330 48 Sbic_02g010040 Sbic_04g037210 100 100 Atha_AT1G04600 Atha_AT2G33240 74 75 Acoe_005_00115 Acoe_034_00206 52 15 98 Atha_AT2G31900 Sbic_01g008180 Acoe_004_00667 100 98 99 Sbic_03g032770 Sbic_09g026840 71 Sbic_03g026110 81 37 Atha_AT1G17580 Acoe_076_00141 Atha_AT5G20490 100 100 Myosin XI 60 Atha_AT1G54560 24 Atha_AT1G08730 35 Sbic_10g008210 9824 Acoe_017_00666 Acoe_034_00422 Atha_AT3G58160 40 37 Sbic_01g023150 Sbic_04g034830 100 37 90 Acoe_020_00543 Atha_AT4G33200 Sbic_01g023160 97 99 Php_XP_001770954 Php_XP_001764154 79 Php_XP_001770957 100 42 78 Smol_XP_002982428 Smol_XP_002966591 100 Smol_XP_002988982 Smol_XP_002975092 38 100 Vcar_XP_002954496 44 Crei_XP_001697846 54 100 Vcar_XP_002947426 99 Crei_XP_001693409 Cvar_EFN58364 Otau_XP_003079970 Cvar_EFN53725 100 80 100 Acas_1_21 Acas_1_30 58 Acas_1_26 100 31 Ddis_XP_001733030 Ppal_EFA79637_1 100 97 Ppal_EFA74941_1 Myosin XXXIII Ddis_XP_645195 99 55 Acas_1_20 Acas_1_25 Acas_1_29 100 83 Rory_6035 37 Rory_15113 95 Pbla_Phybl2_136641 Pbla_Phybl2_137096 100 Rory_16422 Rory_10110 99 92 50 Rory_6086 80 Rory_15185 79 92 Pbla_Phybl2_154650 Pbla_Phybl2_185687 Rory_13880 85 100 Mver_MVEG_02983 Mver_MVEG_00810 10 100 Amac_AMAG_017532 96 89 Amac_AMAG_04247 100 Bden_Batde5_13697 Spun_SPPG_01285 88 88 81 Cneo_XP_570120 Ccin_CC1G_03780 98 Umay_XP_760702 100 Aory_AoQ2UTJ 100 Tmel_XP_002838720 100 MYO2_YEAST/72-769 MYO4_YEAST/73-765 90 Spom_NP_596233_1 Spom_NP_588492_1 Myosin V 100 88 MYO5A_CHICK/71-752 97 Hsap_NP_000250 18 Hsap_NP_061198 Hsap_NP_001073936 23 50 Dmel_NP_477186 90 8 Dpul_227507 Ctel_225225 54 19 Nvec_1162932_13 60 Mlei_ML00121a 76 Ocar_g2311_t1 Aque_228465_11 54 100 Mbre_17459_4 49 Sros_PTSG_00762_25 Mvib_comp3686 Clim_Contig1231 98 85 65 Pgem_Contig49795 99 57 Pgem_Contig51197 Awhi_Contig57820 92 Awhi_Contig17957 81 72 Apar_comp24261 Apar_comp23853 Cfra_g3780 56 52 Awhi_Contig78316 Awhi_Contig63236 18 Pgem_Contig73864 100 89 93 Pgem_Contig70571 99 Awhi_Contig10582 98 Pgem_Contig80832 Apar_comp24301 Cowc_CAOG_02007_16 100 Sarc_SARC_07634 100 Cfra_g1016 16 6 96 Apar_comp20627 Awhi_Contig68299 100 98 Pgem_Contig17235 Myosin XIX Awhi_Contig71392 42 Ctel_222718 99 Dpul_221760 50 Nvec_1162932_5 Hsap_NP_001157207 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023944501|m_103602 100 54 Atha_AT5G54280 Atha_AT4G27370 51 Acoe_063_00017 2 37 Sbic_02g036390 100 Acoe_008_00012 100 62 Atha_AT1G50360 100 Atha_AT3G19960 60 Acoe_035_00049 Sbic_01g018770 99 12 99 Php_XP_001777862 Php_XP_001755337 Myosin XVIII 100 98 Php_XP_001774306 100 Php_XP_001775964 Php_XP_001768683 100 Smol_XP_002972734 97 58 Smol_XP_002993349 100 Smol_XP_002975651 Smol_XP_002978834 100 99 Vcar_XP_002956099 Crei_XP_001696752 Cvar_EFN52211 Gthe_78981 100 Tmel_XP_002835249 38 Aory_AoQ2U49 88 77 Spom_NP_593816_1 Spom_NP_588114_1 90 MYO1_YEAST/77-779 100 100 Cneo_XP_569902 Ccin_CC1G_09915 Umay_XP_759433 100 68 87 Pbla_Phybl2_71839 100 Pbla_Phybl2_21117 Rory_10685 79 Rory_13107 71 98 Amac_AMAG_11379 Spun_SPPG_07224 Mver_MVEG_07901 6 100 MYO4_CAEEL/83-775 54 39 MYO3_CAEEL/88-779 100 Dpul_207855 95 Dmel_NP_724005 100 60 42 Hsap_NP_001093582 MYH6_HUMAN/87-768 44 Ctel_118513 Nvec_1162932_6 69 98 Mlei_ML022011a 99 Mlei_ML02275a 95 Aque_228465_12 Ocar_g1608_t1 Myosin II Mvib_comp15821 31 37 Awhi_Contig2145 29 Pgem_Contig29655 79 8 Pgem_Contig29653 Pgem_Contig29652 15 Awhi_Contig28024 41 56 Awhi_Contig64826 88 Pgem_Contig28362 Awhi_Contig33757 30 92 Awhi_Contig41061 Pgem_Contig29654 100 Sarc_SARC_01270 45 Cfra_g1004 100 Apar_comp19786 Apar_comp19210 100 62 100 Dmel_NP_523860 92 MYSN_DROME/134-855 48 Dpul_198935 100 100 Hsap_P_074035 72 MYH11_CHICK/86-777 71 Hsap_NP_005955 Nvec_1162932_16 64 34 Aque_228465_13 2 51 Ocar_g8625_t1 83 100 Mbre_17459_9 Sros_PTSG_00762_9 Cowc_CAOG_02007_5 79 100 Ttra_AMSG_08437 Ttra_AMSG_04291 Ttra_AMSG_09069 100 94 MYS2_DICDI/88-747 Ppal_EFA84750_1 46 Acas_1_12 73 100 Ngru_XP_002671980 Ngru_XP_002680829 82 63 Dpul_64163 Dmel_NP_732108 74 Ctel_191825 60 93 Hsap_NP_510880 94 Hsap_EAW59702 Nvec_1162932_11 Myosin XVIII 100 79 Ocar_g6279_t1 90 Aque_228465_8 Mlei_ML02153a 3 Cowc_CAOG_02007_12 100 100 Ehux_436181 Ehux_213306 100 Ehux_415936 100 Ehux_115214 81 Ehux_110275 100 Ehux_426799 20 100 Ehux_450146 100 Ehux_450657 Myosin XXXII 19 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023976953|m_11348 16 Ehux_194888 Ehux_194887 100 100 Ehux_76086 Ehux_200475 Ehux_108791 98 94 Dpul_225324 58 MYS9_DROME/59-754 48 Ctel_154601 Hsap_NP_004990 83 Nvec_1162932_17 23 19 Mlei_ML12625a 77 Aque_228465_15 Ocar_g10472_t1 83 100 Sros_PTSG_00762_6 47 Mbre_17459_15 100 Mvib_comp12907 44 Cowc_CAOG_02007_4 Myosin VI Clim_Contig6856 38 Ttra_AMSG_00252 96 95 Cowc_CAOG_02007_2 94 Mvib_comp13670 11 Mvib_comp15617 2 Mvib_comp10197 100 31 54 Ehux_448407 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023948495|m_43730 Ttra_AMSG_09274 100 MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027091637|m_26489 MMETSP0308_Gloeochaete_wittrockiana|cds_CAMNT_0027089567|m_32787 35 6 66 Esil_CBN74726 Esil_CBN79332 100 Esil_CBJ30507 60 71 Esil_CBJ27150 100 Esil_CBN74765 Myosin XXX Pinf_XP_002908958 88 92 Pinf_XP_002908139 Pinf_XP_002903656 10 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023975205|m_15318 85 67 Pmar_XP_002765636 21 Pfal_Q8IHW0_Q8IHW0 Tgon_XP_002367823 8 Pmar_XP_002765635 Myosin XXIII 79 20 Tgon_XP_002364981 Pmar_XP_002765212 Ehux_210818 8 50 23 Ehux_103727 35 Ehux_51153 24 Ehux_62642 Haptophyta orphan 9 Ehux_462187 Ehux_447539 MMETSP1150_Emiliania_huxleyi|cds_CAMNT_0023946303|m_99269 26 6819647_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 5920415_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 100 4578_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 10568_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 Myosin head CH Rhizaria 23 100 LRR_RI 87 20417_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 x3 Orphan 20464_1_TaxId_29199_Chlorarachnion_reptans_CCCM449 100 100 7925_1_TaxId_227086_Bigelowiella_natans_CCMP1242 82 5282_1_TaxId_227086_Bigelowiella_natans_CCMP623 Bnat_28683 56 100 6173_1_TaxId_91324_Lotharella_globosa_CCCM811 7468_1_TaxId_91324_Lotharella_globosa_CCCM811 36 100 100 11999_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 10581_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 Myosin head IQ LRR_RI 22279_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 x3 99 7417_1_TaxId_629695_Gymnochlora_sp_CCMP2014 100 100 4841_1_TaxId_227086_Bigelowiella_natans_CCMP623 100 8526_1_TaxId_227086_Bigelowiella_natans_CCMP623 84 Bnat_132297 968_1_TaxId_168855_Amorphochlora_amoebiformis_CCMP2058 56 100 Bnat_45663 Bnat_91633 Myosin head CH 100 Bnat_21545 92 100 ETO02343|hypothetical_protein_RFI_35091 100 ETO31547|hypothetical_protein_RFI_05577 100 ETO20092|hypothetical_protein_RFI_17126 100 ETO25957|hypothetical_protein_RFI_11180 Myosin head IQ PH ETO11692|hypothetical_protein_RFI_25684_partial 184362_1_000861_TaxId_933848_Elphidium_margaritaceum 91 77 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000686349|m_9681 84 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000736109|m_34685 64 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000725537|m_32031 79 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000668091|m_58401 100 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000685007|m_4144 59 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000734735|m_33918 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000669591|m_43953 Myosin XIII 100 100 Ngru_XP_002680898 Ngru_XP_002681567 100 95 Lmaj_XP_001685713 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000663201|m_57975 MMETSP0039_Eutreptiella_Gymnastica|cds_CAMNT_0000683597|m_17096 6 100 Esil_CBJ27565 100 Esil_CBJ27566 96 87 Esil_CBJ33547 79 Ngad_04122 45 Pinf_XP_002900600 Myosin XXXI Pinf_XP_002999253 Ehux_427301 100 Mbre_17459_17 51 Sros_PTSG_00762_18 71 Sros_PTSG_00762_30 28 Sros_PTSG_00762_3 100 100 Mbre_17459_7 80 Sros_PTSG_00762_5 Sros_PTSG_00762_23 100 Mbre_17459_24 29 Sros_PTSG_00762_16 100 87 Sros_PTSG_00762_27 100 Mbre_17459_11 39 Mbre_17459_5 Sros_PTSG_00762_28 4 Aque_228465_4 89 92 Mbre_17459_18 100 Sros_PTSG_00762_15 83 Sros_PTSG_00762_10 Mbre_17459_31 Myosin III 15 100 Sros_PTSG_00762_21 Mbre_17459_23 100 Sros_PTSG_00762_7 Mbre_17459_25 100 Hsap_NP_001077084 6 35 23 Hsap_NP_059129 26 Ctel_226099 Nvec_1162932_15 63 100 Dmel_NP_652630 48 Dpul_222155 Aque_228465_16 Ocar_g4520_t1 25 100 Sros_PTSG_00762_24 82 Mbre_17459_12 33 100 32 Sros_PTSG_00762_20 6 Mbre_17459_21 100 Sros_PTSG_00762_2 Mbre_17459_14 79 Ocar_g9905_t1 99 Hsap_AAI46792 93 Mbre_17459_22 86 Sros_PTSG_00762_13 28 100 Mbre_17459_13 Sros_PTSG_00762_29 Sros_PTSG_00762_12 39 94 Mvib_comp15601 Mvib_comp14521 84 Cowc_CAOG_02007_8 61 78 Ctel_5381 Dpul_64918 96 Ctel_226894 100 34 Hsap_NP_004136 14 Hsap_AAD49195 Myosin IX 61 43 Aque_228465_6 92 Ocar_g1966_t1 100 Nvec_1162932_2 Mlei_ML16038a Cowc_CAOG_02007_7 100 Ddis_XP_643200_2 Myosin XXVI Ppal_EFA84521_1 100 92 Dmel_NP_523571 95 Dpul_224910 97 Dmel_NP_723295 Ctel_226057 22 100 Hsap_NP_000251 2 Hsap_NP_001073936_2 77 51 Nvec_1162932_9 Nvec_1162932_10 Myosin VII 52 24 Ocar_g9829_t1 100 Aque_228465_9 Ocar_g9435_t1 50 48 100 Sros_PTSG_00762_22 Mbre_17459_20 Mbre_17459_28 Clim_Contig4055 99 87 Dmel_NP_572669 73 Dpul_191611 32 94 Ctel_227847 98 Hsap_NP_057323 12 96 Nvec_1162932_12 Ocar_g2829_t1 100 Myosin XV 93 Mbre_17459_3 Sros_PTSG_00762_11 85 96 90 Cowc_CAOG_02007_13 Mvib_comp15616 Mvib_comp15942 Clim_Contig4137 67 Ocar_g1598_t1 98 Aque_228465 69 bioRxiv preprint doi: https://doi.org/10.1101/06403067 ; this version postedNvec_116293 July 15, 2016.2 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who hasHsap_NP_03646 granted bioRxiv a license6 to display the preprint in perpetuity. It is made 100 available under aCC-BY 4.0 International license. 99 Mbre_17459 Sros_PTSG_00762 88 95 Mvib_comp15717 Myosin X 97 Cowc_CAOG_02007 Cowc_CAOG_02007_10 100 72 Cfra_g3530 Sarc_SARC_07848 Clim_Contig2052 84 Rory_17367 53 Pbla_Phybl2_85927 81 Pbla_Phybl2_95968 96 Rory_12406 100 100 Rory_230 96 Rory_6001 Pbla_Phybl2_115666 100 Rory_8615 99 Pbla_Phybl2_17470 100 54 Pbla_Phybl2_153081 Rory_5687 38 74 Umay_XP_759351 Ccin_CC1G_11270 86 Cneo_XP_571494 7 42 100 Tmel_XP_002839897 Aory_AoQ8TGC 85 Mver_MVEG_06060 100 Rory_9123 100 Rory_2233 90 Pbla_Phybl2_95943 26 Pbla_Phybl2_95920 XVII 78 99 Pbla_Phybl2_107631 100 15 Rory_6642 72 Pbla_Phybl2_107887 Ccin_CC1G_10992 17 Mver_MVEG_04343 Mver_MVEG_06404 100 63 Spun_SPPG_06138 Bden_Batde5_35424 73 Bden_Batde5_86403 100 63 Bden_Batde5_8502 94 Bden_Batde5_23120 99 58 Spun_SPPG_06659 50 Bden_Batde5_34502 Spun_SPPG_03441 78 Spun_SPPG_00937 100 Amac_AMAG_01753 Amac_AMAG_17492 100 66 Dmel_NP_788005 65 Dpul_40897 6 40 Ctel_96159 18 100 Nvec_1162932_7 Myosin XX Aque_228465_7 Ocar_g2767_t1 32 81 Cfra_g6086 100 Sarc_SARC_06769 99 Cfra_g1302 100 Sarc_SARC_14486 Myosin XXXIV 5 Apar_comp22180 100 Awhi_Contig26872 Pgem_Contig12780 97 Ttra_AMSG_02296 100 Ttra_AMSG_10103 37 100 Ttra_AMSG_05986 Apusozoa orphan 98 Ttra_AMSG_09426 Ttra_AMSG_07281 Ttra_AMSG_06739 93 65 Aque_228465_3 Ocar_g340_t1 100 Dmel_NP_001015270 100 100 Sros_PTSG_00762_26 Mbre_17459_2 Myosin XXII 96 100 100 Cowc_CAOG_02007_15 Mvib_comp15915 Cowc_CAOG_02007_14 Spun_SPPG_07005 100 83 100 Acas_1_10 Acas_1_7 35 Acas_1_17 100 62 Ppal_EFA75546_1 87 Ddis_XP_644171 Myosin XXV Acas_1_5 100 100 Acas_1_13 Acas_1_11 Acas_1_8

0.3 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 10

Ammonia sp. Foraminifera Elphidium margaritaceum BAE48507 | Planoglabratella opercularis Ammonia sp. Elphidium margaritaceum

E. margaritaceum α2-tubulin 65/0.97 Elphidium margaritaceum Ammonia sp. Ammonia sp. 48/0.92 AEV46059 | Allogromia latcollaris 70/0.97 R. filosa (24 sequences) S. zanclea (4 sequences) Taxopodida L.setosa (2 sequences) Radiolaria E.margaritaceum Foraminifera Ammonia sp. Retculomyxa filosa ABP93406 | Filoreta tenera Retaria (6 sequences) ACR46956 | Cholamonas cyrtodiopsidis Stcholonche zanclea (5 sequences) Lithomelissa setosa (2 sequences) Rotallida (2 sequences) Retculomyxa filosa (2 sequences) α1-tubulin Stcholonche zanclea Chlorarachniophyta 55/1.0 Chlorarachniophyta (8 seqs.) 67/1.0 63/1.0 Chlorarachniophyta (4 seqs.)

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Figure 11 Foraminifera Rotallida (13 sequences) Miliolida (3 sequences) AAY58152 | Rhabdammina cornuta CDZ92723 | Foraminifera sp. Allogormiida (3 sequences) β2-tubulin AY818714 |Crithionina delacai R. filosa (5 sequences) Rotallida HM244875 | Ovammina opaca (9 sequences) Rotallida (2 sequences) Polycystna (5 sequences) Radiolaria Acantharia (5 sequences) Stcholonche zancela (3 sequences) Taxopodida R. filosa (5 sequences) Endomyxa (4 sequences) Phaeodaria (2 sequences) ETO00283| Retculomyxa filosa Acantharia (3 sequences) Chlorarachniophyta (10 sequences) Monadofilosa(3 sequences) Stcholonche zanclea Stcholonche zanclea Lithomelissa setosa β1-tubulin Foraminifera (9 sequences) Stcholonche zanclea Foraminifera (7 sequences) BAK61733 | Larcopyle butschlii BAK61747 | Larcopyle butschlii BAK61740 | Collozoum amoeboides KF170530| Collozoum sp. Filoreta tenera 0.3 bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 12

α1-tub α2-tub H1-S2 H1-S2 M-loop M-loop

H3 H3 T5 T5 T3 T3 H11’ H11’

T7 T7 H8 H8

H12 H12

H5 H5

Variable Conserved bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 13

β1-tub β2-tub H1-S2 H1-S2 M-loop M-loop

H3 H3 T5 T5 T3 T3 H11’ H11’

T7 T7 H8 H8

H12 H12

H5 H5

Variable Conserved bioRxiv preprint doi: https://doi.org/10.1101/064030; this version posted July 15, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.

Figure 14 0.25 Haynesina germanica (EPA) 0.54 Rossyatella sp. (EPA) Elphidium sp. Ammonia sp. 1.0 1/2 Brizalina sp. (EPA)

Nonionellina sp. Foraminifera -Lineage specific 0.95 Bulimina marginata (EPA) tubulin duplicaton Globobulimina turgida 0.93 Allogromia sp. (EPA) 0.64

Globigerinella siphonifera (EPA) Retaria 0.31 Globigerinita glutnata (EPA) 1.0 Micatuba flexilis (EPA) 1.0 - α- and β-tubulin Miliolidae sp. (EPA) -Lineage specific 1.0 neofunctonalizaton Quinqueloculina sp. (EPA) tubulin duplicaton Retculomyxa filosa

Collozoum sp. Polycystna Lithomelissa setosa

Larcopyle butschlii (EPA) Radiolaria 1.0 - Actn Spongosphaera streptacantha Acantharia duplicaton Phyllostaurus sp. -/69 Astrolonche sp. Rhizaria 1.0 Amphilonche elongata (EPA) 0.79/- Stcholonche zanclea Taxopodida Filoreta tenera 0.55 - Complex pseudopodia, 1/4 Bonamia ostreae (EPA) Endomyxa 0.85 ofen retculose, 1/4 Haplosporidium litoralis (EPA) Gromia sphaerica anastomosing 0.81 Leptophrys sp. (EPA) - Unique myosin XXXVII 0.75 Plasmodiophora brassicae (EPA) 0.98 Spongospora subterranea (EPA)

Bigelowiella longifila Chlorarachniophyta Bigelowiella natans

- Duplicaton of arp2 and ARPC 1 Norrisiella sphaerica Retculofilosa - Myosin If and IV duplicaton Chlorarachnion reptans - Unique mysoin XXXV and XXXVI 0.83/71 Lotharella globosa Lotharella oceanica

Partenskyella glossopodia Filosa Gymnochlora sp. Amorphochlora amoebiformis 0.99 Limnofila borokensis (EPA) Aulacantha scolymantha Monadofilosa 0.57 Bodomorpha minima (EPA) 0.64 Heteromita sp. (EPA) Paracercomonas marina 0.25 Gymnophrys sp. (EPA) 0.54 Massisteria marina (EPA) Alveolata Stramenopiles Haptophyta Chloroplastda Rhodophycdeae 0.2 Cryptophyta For the rest of the tree, see Fig. 2 (maximum likelihood)Glaucophyt and Fig.a 3 (Bayesian) Excavata Opisthokonta Amoebozoa

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S1 Single gene statistics

Supplementary table S1: Statistics for single gene alignments. Gene name: Name of the gene alignment, adopted from Burki et. al (2012). Number of taxa: The number of taxa in the gene alignment after BIR and selection in SCaFos. Min seq. length: The lenght of the shortest sequence in the alignment in AA. Max seq. length: Length of the longest sequence in the alignment in AA. Pairwise Identity: Identity calculated for all pairs of sequneces in the alignment. Model: The model chosen as the best fitting the sequence data in the alignment by RAxML (Stamatakis 2014). Likelihood of model:The likelihood of the model chosen by RAxML. Realtive TC and Realtive TCA: Relative Tree Certainity for the phylogentic tree of the gene calculate from the boostrap trees (Salichos et al. 2014). S. zanclea: indicaties if the newly sequenced Sticholonche zanclea is present in the gene alignment L. setosa: indicaties if the newly sequenced Lithomelissa setosa is present in the gene alignment. Selected for reduced dataset: about half of the genes were selected for a smaller dataset . Genes marked with ACCEPT was selected to the 147-genes dataset.

Number Min. Seq. Max seq. Pairwise Likelihood of Selected for Gene name Model Relative TC Relative TCA S. zanclea L. setosa of taxa length length Identity model red.dataset ABHD13 36 47 137 57,00% LG -5760,505024 0,318832 0,357927 0 0 AGX 43 131 270 53,30% LG -13578,0947 0,319509 0,337786 0 0 ALG11 33 86 209 58,00% LG -8078,540125 0,230892 0,301337 0 0 ap1m1 58 62 256 70,60% LG -8282,246972 0,450315 0,463256 0 yes ACCEPTED AP1S2 51 75 109 65,40% LG -3948,823321 0,344491 0,386934 0 0 ACCEPTED ap2m1 48 40 202 60,00% LG -7015,548224 0,46415 0,477977 0 0 ACCEPTED ap3m1 37 63 189 52,80% LG -6785,573219 0,51729 0,521267 0 0 AP3S1 46 47 116 64,70% LG -3638,753749 0,290083 0,315354 0 0 AP4S1 43 79 114 67,80% LG -3717,694654 0,353887 0,356413 0 0 ARL6 21 83 126 59,40% LG -2850,923763 0,48422 0,492966 0 0 ARP2 42 27 157 67,20% LG -4811,863091 0,369159 0,38038 0 0 arpc3 30 43 107 50,70% LG -3988,11484 0,416454 0,431791 0 0 arpc4 45 35 143 60,80% LG -5306,773776 0,289444 0,306523 0 0 ACCEPTED atad1 34 106 152 61,70% LG -4634,564786 0,354555 0,385238 0 0 atp6 77 47 127 75,70% MTZOA -4423,911594 0,2374 0,278178 0 0 ACCEPTED ATP6V0A1 61 78 455 52,50% LG -25700,3205 0,381807 0,406443 0 0 ACCEPTED atp6v1a 76 37 447 74,10% LG -14189,67727 0,388532 0,397548 0 0 ACCEPTED atp6v1b 78 69 433 76,30% LG -14137,02466 0,461456 0,473029 yes yes ACCEPTED atp6v1d 64 65 167 55,20% LG -10167,97542 0,339726 0,349941 0 0 ACCEPTED atp6v1e 55 83 138 41,30% LG -11233,94332 0,386724 0,422531 0 0 ACCEPTED bat1 73 88 258 71,80% LG -10630,98133 0,404242 0,438108 yes 0 ACCEPTED C16orf80 48 91 165 88,40% LG -2248,848997 0,109672 0,189948 yes 0 ACCEPTED C22orf28 38 91 466 76,40% LG -9894,363438 0,281505 0,336485 yes 0 ACCEPTED calm 78 49 129 90,00% LG -2110,01212 0,148728 0,192604 yes 0 ACCEPTED calr 60 57 170 67,00% WAG -7815,156224 0,231478 0,268941 0 0 ACCEPTED capzb 45 52 139 59,00% LG -5504,958066 0,320148 0,343714 0 0 CCDC113 18 82 237 51,10% LG -5508,47554 0,539594 0,536236 0 0 CCDC37 30 90 303 46,10% LG -11786,2832 0,47835 0,503777 0 0 CCDC40 19 115 467 42,60% LG -12842,83032 0,491146 0,525936 0 0 CCDC65 25 82 321 42,20% LG -10626,90619 0,420871 0,438333 0 0 CDK5 42 65 280 63,40% LG -9418,462225 0,417232 0,422685 yes 0 ACCEPTED clgn 34 48 145 62,00% LG -4899,706222 0,114411 0,173907 0 0 COP-beta 48 61 243 60,00% LG -9593,223689 0,294955 0,308558 0 0 ACCEPTED COPE 44 123 223 41,50% LG -12970,30913 0,517069 0,526119 0 0 ACCEPTED COPG2 55 70 509 56,20% LG -23616,91598 0,521554 0,536455 yes 0 ACCEPTED COPS2 44 89 309 58,50% LG -11230,39468 0,527241 0,541656 0 0 COPS6 28 123 187 50,70% LG -6346,544893 0,537547 0,560168 0 0 COQ4_mito 36 109 151 49,00% LG -7280,812689 0,401101 0,422436 0 0 CORO1C 31 97 222 47,20% LG -8167,847504 0,374021 0,403971 0 0 crfg 51 76 292 69,20% LG -10103,6544 0,406951 0,411905 0 0 ACCEPTED CS 64 77 322 63,40% LG -16434,00411 0,371514 0,398614 yes 0 ACCEPTED CTU1 21 88 268 73,10% LG -4782,043678 0,323508 0,330796 0 0 D2HGDH_mito 44 90 309 58,60% LG -14265,88235 0,283087 0,324249 0 0 ACCEPTED DCAF13 52 68 300 55,20% LG -15029,30276 0,40634 0,422661 0 0 ACCEPTED DIMT1L 55 63 183 68,60% LG -6863,39766 0,412767 0,445715 0 0 ACCEPTED DNAI2 28 43 230 54,30% LG -6502,660093 0,52915 0,534576 0 0 DNAL1 25 130 153 54,40% LG -5228,202384 0,446404 0,448189 0 0 dpagt1 45 76 170 65,60% LG -6228,299749 0,359216 0,402348 0 0 DPP3 15 131 528 41,70% LG -12511,48145 0,401157 0,423351 0 0 DRG2 52 63 245 64,70% LG -9836,526877 0,385974 0,421983 0 0 ACCEPTED eef2 81 94 562 67,30% LG -24983,51597 0,4763 0,494258 yes yes ACCEPTED EFG_mito 41 51 281 75,00% LG -6495,903547 0,223644 0,236228 0 0 EFTUD1 31 36 270 60,60% LG -7839,893152 0,363824 0,388091 0 0 eftud2 47 103 322 70,00% LG -9505,018307 0,412589 0,428361 0 0 ACCEPTED eif1a 66 47 108 69,70% LG -4471,341828 0,297396 0,3331 0 0 ACCEPTED eif2b 44 72 94 57,20% LG -3973,460453 0,328507 0,348898 0 0 eif2g 58 70 366 76,40% LG -9647,829098 0,36947 0,389087 0 0 ACCEPTED EIF3I 52 52 221 51,60% LG -11650,70359 0,425295 0,457061 0 0 ACCEPTED EIF4A3 63 60 203 80,80% LG -4512,305984 0,193142 0,209894 yes yes ACCEPTED

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S1 Single gene statistics

EIF4E 33 72 107 54,00% LG -4350,586754 0,41534 0,420327 0 0 eif5A 59 43 100 59,60% LG -5896,500255 0,236079 0,266349 0 0 eif5b 52 66 379 65,00% LG -14629,03823 0,369459 0,387896 0 0 ACCEPTED eif6 73 39 189 68,90% LG -9203,168463 0,316631 0,323257 0 0 ACCEPTED emg1 50 48 137 58,70% LG -6251,800505 0,32807 0,364891 0 0 ACCEPTED ERLIN1 26 58 270 58,10% LG -6995,632051 0,446725 0,475001 0 0 etf1 62 82 326 74,40% LG -10397,59059 0,282949 0,3303 0 0 ACCEPTED FA2H 22 100 138 56,10% LG -3792,536181 0,362447 0,376038 0 0 FAM18B 39 55 106 48,40% MTZOA -5587,027958 0,031813 0,111896 0 0 FAM96B 40 47 111 66,70% LG -3987,056771 0,156244 0,1794 0 0 fbl 64 50 195 74,00% LG -7444,494885 0,389779 0,422724 yes 0 ACCEPTED FTSJ1 49 88 165 66,80% LG -6088,454206 0,366011 0,379057 0 0 ACCEPTED GAS8 32 81 372 44,90% LG -12643,31147 0,491982 0,508781 0 0 gdi2 72 46 212 61,80% LG -11089,82621 0,333202 0,358492 0 0 ACCEPTED gnb2L1 79 48 192 75,20% LG -8732,103713 0,265904 0,306306 yes yes ACCEPTED GPD1L 37 101 221 61,30% LG -7689,745256 0,37787 0,406056 0 0 gpn1 56 45 144 71,20% LG -5363,738803 0,212174 0,27348 0 0 ACCEPTED gpn2 41 32 162 55,70% LG -6613,807943 0,30105 0,342609 0 0 gpn3 46 50 156 61,30% LG -6745,689652 0,364161 0,370243 0 0 ACCEPTED GRWD1 45 85 193 55,90% LG -8675,085077 0,328738 0,367185 0 0 ACCEPTED GSS 34 114 218 54,40% LG -9180,431006 0,316714 0,349284 0 0 H2A 71 81 104 78,90% LG -3316,468046 0,179693 0,235261 0 0 H2B 51 79 98 75,60% LG -2796,842548 0,28254 0,293791 0 0 ACCEPTED h3-2 72 58 129 91,60% LG -2055,800843 0,098365 0,155827 yes 0 h4 55 65 99 92,10% LG -1122,507982 0,101839 0,133267 0 0 ACCEPTED HDDC2 35 74 119 59,60% LG -4442,215557 0,164491 0,184876 0 0 hsp90 83 66 415 75,30% LG -17790,87246 0,346099 0,362569 yes 0 ACCEPTED HYOU1 33 80 223 48,00% LG -8724,657423 0,486438 0,488844 0 0 IFT46 33 88 174 58,20% LG -5956,901367 0,264837 0,299679 yes 0 IFT57 27 93 260 39,40% LG -10551,41885 0,404256 0,426612 0 0 IFT88 34 92 458 51,10% LG -16827,41096 0,501749 0,515524 0 0 IMP4 54 79 202 62,90% LG -9421,343366 0,325505 0,371947 0 0 ino1 61 41 344 70,00% LG -14295,91978 0,217782 0,283593 0 yes ACCEPTED IPO4 30 84 376 38,80% LG -15957,99189 0,591417 0,598396 0 0 KARS 62 62 264 70,80% LG -10600,97116 0,214743 0,2715 0 0 ACCEPTED KDELR2 49 77 156 59,10% LG -7062,524635 0,434685 0,441327 yes 0 ACCEPTED LRRC48 23 104 293 42,10% LG -9179,427104 0,430746 0,43918 0 0 MAT1A 64 71 260 75,30% LG -8605,46176 0,412943 0,422438 0 0 ACCEPTED mcm2 50 90 263 73,80% LG -8012,514112 0,315807 0,340618 yes yes ACCEPTED mcm3 51 93 271 72,50% LG -9047,602802 0,30263 0,325999 yes 0 ACCEPTED mcm4 44 81 296 70,10% LG -9420,901756 0,393779 0,405547 yes 0 ACCEPTED mcm5 45 46 246 74,20% LG -7002,009287 0,501695 0,516008 0 yes ACCEPTED mcm6 52 77 299 70,30% LG -9645,961336 0,429845 0,469787 yes 0 ACCEPTED mcm7 51 62 263 72,40% LG -8287,185832 0,356912 0,366708 0 0 mcm8 29 76 249 65,10% LG -6245,43182 0,354433 0,373885 0 0 mcm9 29 143 255 64,60% LG -6777,807545 0,312351 0,329352 0 0 memo1 38 44 168 60,10% LG -6043,619772 0,262226 0,299762 0 0 metap2 65 46 258 68,80% LG -11415,57471 0,254494 0,270575 0 0 ACCEPTED METTL1 54 77 160 55,60% LG -8932,773544 0,396241 0,40591 0 0 ACCEPTED MMAA_mito 26 109 250 53,90% LG -7212,012798 0,346028 0,362445 0 0 MTHFR 45 65 334 63,30% LG -11874,32317 0,323083 0,343072 0 0 ACCEPTED NAA15 47 66 431 47,70% LG -23715,45616 0,418084 0,435806 0 0 ACCEPTED NAE1 31 136 236 52,20% LG -9548,540186 0,342409 0,373591 0 0 NAPB 44 93 199 42,50% LG -12243,68002 0,332845 0,365541 0 0 ndufv1 62 75 402 73,80% LG -12540,76853 0,376573 0,403972 0 0 ACCEPTED NDUFV2_mito 51 54 155 58,60% LG -7609,888533 0,398947 0,408587 0 0 ACCEPTED NFS1_mito 61 46 232 75,50% LG -7853,794077 0,193981 0,243005 0 0 ACCEPTED nhp2 37 41 68 62,10% LG -2330,871773 0,167164 0,230068 0 0 nhp2L1 52 99 115 72,30% LG -3873,133239 0,202258 0,248085 0 0 ACCEPTED NLN_mito 30 78 381 48,60% LG -14240,63183 0,421332 0,44309 0 0 nop56 60 96 281 67,10% LG -11882,5291 0,338887 0,362741 yes 0 ACCEPTED nop58 55 45 213 74,40% LG -7000,149845 0,231158 0,263766 0 0 ACCEPTED NSA2 64 68 240 72,40% LG -9499,737422 0,303197 0,325586 0 0 ACCEPTED nsf 53 65 270 69,00% LG -9891,769117 0,374889 0,39972 0 0 oplah 38 50 564 64,90% LG -14938,31009 0,394035 0,411375 0 0 ORF1 16 57 134 54,50% LG -2767,405751 0,422535 0,458527 0 0 osgep 46 59 259 73,60% LG -7878,100778 0,251901 0,259963 0 0 PABPC4 52 80 293 62,30% LG -13166,19715 0,439501 0,458006 0 0 PACRG 38 70 160 67,00% LG -3910,462495 0,451179 0,462882 0 0 PIK3C3 29 81 304 57,80% LG -8753,142845 0,378127 0,390866 0 0 PLS3 46 72 299 56,40% LG -12508,93565 0,331283 0,355786 0 0 PMM2 56 80 196 63,40% LG -10196,48796 0,28168 0,318027 0 0 ACCEPTED

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S1 Single gene statistics

pno1 52 82 147 64,60% LG -5798,528592 0,321841 0,346093 0 0 ACCEPTED polr2a 58 38 772 67,80% LG -28598,87753 0,501619 0,51791 0 0 ACCEPTED polr3a 44 35 722 64,70% LG -25416,11427 0,448526 0,453603 0 0 ACCEPTED PPP2R3 51 98 216 51,10% LG -10956,80171 0,33061 0,357455 yes 0 ACCEPTED PPP2R5C 53 100 254 65,40% LG -9093,0928 0,452387 0,470386 yes 0 ACCEPTED prmt8 56 70 193 68,40% LG -7952,374899 0,115864 0,189454 yes 0 ACCEPTED PROSC 40 68 146 61,30% LG -6082,345294 0,167065 0,217243 0 0 ACCEPTED psma1 59 60 137 67,50% LG -5245,198916 0,280318 0,306409 0 0 ACCEPTED psma2 58 63 121 76,10% LG -3542,825171 0,250677 0,29696 0 0 ACCEPTED psma3 59 70 135 60,10% LG -6965,175678 0,308209 0,344862 0 0 psma4 52 52 128 72,50% LG -4080,020923 0,355296 0,383875 0 0 ACCEPTED psma6 54 37 126 64,70% LG -5607,745264 0,29337 0,322105 0 0 ACCEPTED psma7 74 93 171 69,20% LG -7389,740101 0,387995 0,40465 yes 0 ACCEPTED psmb1 49 43 107 62,90% LG -4522,89283 0,189984 0,264529 0 0 psmb2 48 57 136 51,30% LG -7681,533281 0,299603 0,336806 0 0 ACCEPTED psmb3 63 38 155 60,60% LG -8500,309613 0,206209 0,269064 0 0 ACCEPTED psmb4 60 31 127 56,10% LG -7943,98869 0,345529 0,364564 0 0 ACCEPTED psmb5 67 39 165 67,70% LG -7447,399713 0,320037 0,332597 yes 0 ACCEPTED psmb6 61 69 156 60,90% LG -8273,200252 0,245688 0,285231 yes 0 ACCEPTED psmb7 59 79 167 71,60% LG -6434,285244 0,257649 0,308525 0 0 ACCEPTED psmc1 62 17 231 85,30% LG -4624,959992 0,221607 0,227897 yes 0 ACCEPTED psmc2 62 69 192 86,10% LG -3452,946091 0,257755 0,276869 yes 0 ACCEPTED psmc3 65 68 205 82,00% LG -5119,32424 0,233063 0,257247 yes yes ACCEPTED psmc4 65 62 217 85,70% LG -4527,047494 0,228069 0,257664 yes 0 ACCEPTED psmc5 62 77 227 87,50% LG -4087,161508 0,22135 0,245021 yes 0 ACCEPTED psmc6 57 79 205 85,00% LG -3653,729711 0,336373 0,34444 0 0 ACCEPTED psmd1 60 47 399 59,60% LG -19493,56751 0,327354 0,349363 0 0 ACCEPTED PSMD12 60 58 254 50,40% LG -14784,39862 0,386045 0,41888 0 0 ACCEPTED psmd14 63 63 257 74,40% LG -9323,920868 0,316358 0,343751 0 0 ACCEPTED PYGB 37 95 544 59,90% LG -17011,34898 0,452082 0,462753 0 0 rad51 40 44 256 67,80% LG -7401,132592 0,400212 0,420737 0 0 ran 76 92 165 80,20% LG -4827,137813 0,29601 0,325396 yes 0 ACCEPTED RBX1 42 53 81 84,50% JTTDCMUT -1321,38173 0,160756 0,207393 0 0 RPF1 44 78 174 57,00% LG -7822,702904 0,227766 0,307594 0 0 rpl10 83 61 159 74,40% LG -7018,621297 0,335667 0,35485 0 0 ACCEPTED rpl10a 67 45 161 64,90% LG -9013,950253 0,328544 0,354329 0 0 ACCEPTED rpl11 79 69 152 70,00% LG -8075,80399 0,257236 0,298261 yes 0 ACCEPTED rpl12 67 79 123 66,00% LG -6772,058452 0,263227 0,305638 yes 0 ACCEPTED rpl13 59 33 103 63,60% LG -5917,390741 0,142489 0,191396 0 0 rpl13a 76 49 147 60,00% LG -10377,96112 0,181501 0,248287 0 0 ACCEPTED rpl14 55 58 106 46,50% LG -8034,119988 0,091558 0,14002 0 0 rpl15 84 68 175 69,90% LG -9673,89018 0,32926 0,369159 yes yes ACCEPTED rpl17 63 72 113 64,70% LG -5723,051921 0,246751 0,280843 0 0 ACCEPTED rpl18 55 41 112 70,30% LG -4767,156378 0,114703 0,152984 0 0 ACCEPTED rpl18a 66 51 91 60,90% LG -5269,811383 0,303035 0,316073 0 0 rpl19 76 70 141 69,10% LG -7501,80192 0,286695 0,336505 0 0 ACCEPTED rpl21 57 62 97 62,10% LG -5129,179991 0,267927 0,299892 0 0 ACCEPTED rpl24 50 55 74 50,20% LG -4410,209795 0,319932 0,32644 0 0 rpl26 67 44 99 67,70% LG -4801,451332 0,214933 0,25063 0 0 ACCEPTED rpl3 88 55 311 70,50% LG -18214,71205 0,36935 0,395013 yes yes ACCEPTED rpl30 59 50 79 68,80% LG -3682,374608 0,072009 0,128008 0 0 rpl31 55 49 74 59,60% LG -4354,221301 0,128679 0,147874 0 0 rpl32 51 57 97 65,50% LG -4399,083884 0,184069 0,218971 0 0 rpl35 53 33 89 58,40% RTREV -5252,732522 0,160468 0,225778 0 0 rpl35a 68 50 90 56,90% LG -6333,63494 0,227962 0,272497 0 0 ACCEPTED rpl36a 61 43 81 72,10% LG -3333,656145 0,194011 0,224686 0 0 rpl37a 56 24 85 67,50% LG -3716,721948 0,204181 0,22087 0 0 rpl4 76 43 198 68,30% LG -11227,56917 0,182645 0,252107 yes yes ACCEPTED rpl5 73 43 144 68,10% LG -8208,175351 0,212312 0,213534 0 0 rpl6 53 22 94 67,60% LG -4388,032474 -0,043405 0,02437 0 0 rpl7 82 69 149 62,50% LG -10755,8653 0,287812 0,332822 0 0 ACCEPTED rpl7a 81 36 132 65,90% LG -8859,248599 0,274114 0,318738 0 0 ACCEPTED rpl8 77 124 240 67,90% LG -13793,04187 0,311511 0,352076 yes 0 ACCEPTED rpl9 64 53 115 64,50% LG -6691,555067 0,196335 0,260506 0 0 rplp0 78 40 180 51,10% LG -15763,68346 0,381238 0,389908 0 0 ACCEPTED rps10 40 62 75 63,20% LG -2814,409652 0,244271 0,28835 0 0 rps11 73 50 107 71,80% LG -5361,813968 0,219257 0,26323 yes 0 ACCEPTED rps12 54 57 94 60,40% LG -4519,596208 0,314607 0,341976 0 0 rps13 75 44 128 73,70% LG -5701,230706 0,212594 0,241174 0 0 ACCEPTED rps14 64 48 127 83,50% LG -3390,476476 0,180371 0,231673 0 yes rps15 61 31 98 71,60% LG -4180,540985 0,20494 0,23828 0 0 rps15a 73 62 129 73,30% LG -5860,161627 0,197495 0,227841 yes 0 ACCEPTED

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S1 Single gene statistics

rps16 61 65 124 72,70% LG -4965,414355 0,136972 0,165743 yes 0 ACCEPTED rps17 53 38 83 78,40% LG -2181,131702 0,246075 0,271472 0 0 rps18 72 56 117 70,20% LG -5474,465755 0,26954 0,318506 yes 0 ACCEPTED rps2 78 47 190 71,90% LG -9334,854998 0,252889 0,298213 yes yes ACCEPTED rps20 64 48 91 74,60% LG -3381,434534 0,169691 0,206879 0 0 rps23 75 62 126 79,50% LG -4486,572429 0,318774 0,334894 0 0 ACCEPTED rps26 61 40 85 61,30% LG -4199,599607 0,299643 0,313042 0 0 rps27 52 35 65 75,00% LG -2194,238872 0,156599 0,213324 0 0 rps3 78 59 178 74,30% LG -7468,33651 0,208557 0,247935 0 0 ACCEPTED rps3a 75 25 204 62,00% LG -12542,94964 0,31865 0,355165 0 0 ACCEPTED rps4y1 81 58 218 63,00% LG -15664,68245 0,354728 0,379183 yes 0 ACCEPTED rps5 70 68 162 75,40% LG -5794,456167 0,319957 0,334876 0 0 ACCEPTED rps6 68 104 169 64,80% LG -10147,66672 0,325746 0,348633 yes yes ACCEPTED rps8 68 37 147 70,60% LG -7105,316255 0,203985 0,24948 0 0 ACCEPTED rps9 46 45 162 68,20% LG -5623,640554 0,303148 0,332849 0 0 ACCEPTED rpsa 56 54 169 65,90% LG -7072,3259 0,35915 0,38947 0 0 RRM1 58 36 564 71,10% LG -20008,85311 0,423029 0,439685 yes 0 ACCEPTED sars 56 96 237 67,40% LG -9924,277015 0,346782 0,361108 0 0 ACCEPTED SCO1_mito 42 66 123 54,40% LG -5480,379693 0,257199 0,301144 0 0 ACCEPTED sec61 78 73 399 70,80% LG -16785,0376 0,383642 0,39609 yes 0 ACCEPTED SND1 34 255 443 44,50% LG -19473,31849 0,519936 0,539994 0 0 SORCS3 21 72 207 47,50% LG -6614,66172 0,436617 0,448523 0 0 SPTLC1 28 153 173 53,90% LG -5674,688333 0,454531 0,490133 0 0 srp54 67 58 304 64,30% LG -12873,87608 0,274982 0,314687 0 0 srpr 57 57 157 72,10% LG -4987,352766 0,309341 0,331631 0 0 ACCEPTED STXBP1 30 138 200 45,10% LG -8270,480822 0,437103 0,459147 0 0 suclg1 70 54 238 75,50% LG -9519,676276 0,292659 0,335853 yes 0 ACCEPTED tbp 43 39 142 69,60% LG -4720,390277 0,172201 0,213067 yes 0 ACCEPTED tcp1-alpha 50 70 267 73,50% LG -7326,908482 0,324951 0,349667 0 0 tcp1-beta 57 34 285 71,00% LG -8833,546155 0,208771 0,24571 0 0 ACCEPTED tcp1-delta 63 43 280 70,80% LG -9007,103802 0,330709 0,353747 yes 0 ACCEPTED tcp1-epsilon 68 58 243 72,50% LG -7502,59552 0,260491 0,312204 yes 0 ACCEPTED tcp1-eta 59 54 273 70,70% LG -9944,671421 0,315724 0,348581 0 0 ACCEPTED tcp1-gamma 43 66 226 71,60% LG -5856,5992 0,312327 0,328966 0 0 tcp1-theta 46 30 172 63,20% LG -5905,817557 0,343444 0,361182 0 0 tcp1-zeta 51 42 212 66,50% LG -7354,641576 0,297075 0,343551 0 0 TM9SF1 49 22 218 57,50% MTZOA -7848,370323 0,324587 0,350012 0 0 ACCEPTED tubg 58 95 340 76,70% LG -9313,404275 0,345022 0,375534 0 0 UBA3 45 45 142 69,00% LG -4447,790728 0,234178 0,24643 0 0 ubc 78 50 67 94,00% JTTDCMUT -651,559846 0,068042 0,105242 0 0 UBE2J2 44 59 109 63,60% LG -4583,840059 0,267364 0,277833 0 0 ACCEPTED VARS 48 66 526 65,90% LG -19329,61625 0,459151 0,46621 0 0 VBP1 43 79 129 47,90% LG -7049,32631 0,319827 0,370876 0 0 vpc 73 54 456 79,70% LG -10499,67654 0,294834 0,323803 yes yes ACCEPTED VPS18 27 101 441 46,70% LG -15118,53653 0,521031 0,539672 0 0 VPS26B 60 65 187 66,90% LG -6771,809835 0,398249 0,420922 0 0 ACCEPTED vps4 63 60 194 72,60% LG -6591,279974 0,338121 0,354526 0 0 ACCEPTED wars 59 38 244 66,10% LG -11033,81374 0,248931 0,291756 yes 0 ACCEPTED WBSCR22 50 66 201 59,90% LG -10051,88619 0,404664 0,426312 0 0 ACCEPTED xpb 49 109 285 67,30% LG -10121,99666 0,424055 0,438759 0 0 ACCEPTED XRP2 22 91 129 46,50% LG -4369,734607 0,278992 0,306433 0 0 YKT6 49 102 117 53,00% LG -5621,869644 0,39287 0,405895 0 0 ACCEPTED

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Supplementary table S2: Statistics for the taxa in the multigene datasets. Taxon name: the name of the taxon as used in the multigene trees and alignmnent. Composite: Some closely related spiecies have been merged into one sequence in the alignment. Missing, 255G: The percentage of missing data for the given taxon in the 255 gene alignment. Missing, 146G: The percentage of missing data for the given taxon in the 255 gene alignment. Notes: Taxa marked EPA have been placed with the Evolutinary Placement Algorithm (Berger, et al. 2011), taxa marked with RogueNaRok was identified as jumping taxa and removed before concatination (Aberer et al., 2013)

Taxon name Composite Missing, 255G Missing , 146G Notes Acanthamoeba sp, Acanthamoeba astronyxis, Acanthamoeba sp. Acanthamoeba castellanii 57 46 - Alexandrium catenella, Alexandrium fundyense, Alexandrium sp. Alexandrium tamarense 74 69 - Ammonia sp., Ammonia Ammonia sp. beccarii 49 32 - Amorphochlora amoebiformis - 35 14 - Amphidinium carterae - 89 84 - Arabidopsis lyrata, Arabidopsis sp. Arabidopsis thaliana 10 2 - Astrolonche sp - 72 60 - Aulacantha scolymantha - 92 88 - Aureococcus anophagefferens - 18 6 - Batrachochytrium dendrobatidis - 9 4 - Bigelowiella longifila - 52 37 - Bigelowiella natans - 12 2 - Brachypodium distachyon - 12 3 - Branchiostoma floridae - 6 3 - Calliarthron tuberculosum - 90 90 - Cercomonas longicauda - 84 80 - Chlamydomonas reinhardtii - 16 6 - Chlorarachnion reptans - 32 9 - Chondrus crispus - 85 81 - Coccolithus braarudii - 86 82 - Coccomyxa sp - 12 1 - Collozoum sp., Collozoum Collozoum sp inerme 93 90 - Coralline - 80 74 - Corallomyxa sp., Corallomyxa sp Corallomyxa tenera 92 88 - Cryptosporidium parvum - 33 15 - Cyanophora paradoxa - 71 65 - Dictyostelium discoideum - 11 4 - Ectocarpus siliculosus - 8 4 - Eimeria tenella - 91 88 - Elphidium sp., Elphidium Elphidium sp margaritaceum 50 32 - Emiliania huxleyi - 29 17 - Eucheuma denticulatum - 87 85 - Euglena gracilis, Euglena Euglena sp mutabilis 69 63 - Fragilaria pinnata - 86 79 - Fragilariopsis cylindrus - 67 51 - Glaucocystis nostochinearum - 73 66 - Globobulimina turgida - 88 81 - Gracilaria changii - 79 74 - Gromia sphaerica - 77 69 - Guillardia theta - 4 1 - Gymnochlora sp - 39 16 - Histiona aroides - 87 84 -

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Homo sapiens - 1 1 - Isochrysis galbana - 81 74 - Jakoba bahamensis, Jakoba Jakoba sp libera 69 65 - Karenia brevis - 83 77 - Laminaria sp - 92 89 - Lithomelissa setosa - 94 90 - Lotharella globosa - 34 17 - Lotharella oceanica - 46 27 - Mesostigma viride - 83 81 - Micromonas pusilla - 45 46 - Mimulus guttatus - 16 6 - Monosiga brevicollis - 42 27 - Naegleria gruberi - 18 14 - Nematostella vectensis - 6 5 - Neospora caninum - 26 13 - Nonionellina sp, Nonionella Nonionellina sp labradorica 92 89 - Norrisiella sphaerica - 41 23 - Oryza sativa - 13 3 - Ostreococcus lucimarinus, Ostreococcus sp Ostreococcus tauri 20 8 - Oxyrrhis marina - 78 73 - Paramecium tetraurelia - 21 17 - Partenskyella glossopodia - 32 12 - Pavlova lutheri - 78 74 - Perkinsus marinus - 25 7 - Phaeodactylum tricornutum - 19 6 - Phycomyces blakesleeanus - 15 7 - Phyllostaurus sp., Phyllostaurus sp Phyllostaurus siculus 83 76 - Physcomitrella patens - 8 3 - Phytophthora ramorum, Phytophthora sp Phytophthora sojae 6 3 -

Plagioselmis sp., Plagioselmis sp Plagioselmis nannoplanctica 75 73 - Populus trichocarpa - 13 6 - Porphyra yezoensis - 62 50 - Porphyridium cruentum - 50 36 - Prymnesium parvum - 80 74 - Pythium oligandrum - 84 76 - Reclinomonas americana - 61 57 - Reticulomyxa filosa - 50 36 - Rhodomonas salina - 91 89 - Roombia truncata - 32 32 - Saprolegnia parasitica - 10 6 - Seculamonas ecuadoriensis - 69 62 - Sorghum bicolor - 12 2 - Spongosphaera streptacantha - 91 87 - Stachyamoeba lipophora - 86 83 - Sticholonche zancela - 81 70 - Tetrahymena pyriformis - 19 14 - Thalassiosira pseudonana - 17 5 - Theileria parva - 77 67 - Toxoplasma gondii - 25 10 - Volvox carteri - 11 3 - Allogromia sp. - 99 99 EPA Amphilonche elongata - 95 92 EPA Bodomorpha minima - 99 99 EPA Bonamia ostreae - 99 99 EPA

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Brizalina sp - 98 97 EPA Bulimina marginata - 95 93 EPA Globigerinella siphonifera - 99 99 EPA Globigerinita glutinata - 99 99 EPA Gymnophrys sp - 99 99 EPA Haplosporidium littoralis - 99 99 EPA Haynesina germanica - 99 99 EPA Larcopyle butschlii - 99 99 EPA Leptophrys sp - 99 99 EPA Limnofila borokensis - 97 96 EPA Massisteria marina - 99 99 EPA Micatuba flexilis - 99 99 EPA Miliolidae sp - 99 99 EPA Plasmodiophora brassicae - 94 92 EPA Quinqueloculina sp - 96 95 EPA Rossyatella sp - 99 99 EPA Spongospora subterranea - 96 94 EPA Blastocystis hominis - - - RogueNaRok Cyanidioschyzon merolae - - - RogueNaRok Galdieria sulphuraria - - - RogueNaRok Schizochytrium sp. - - - RogueNaRok

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S3 Concatenated alignments

Supplementary table S3: Statistics for the concatenated alignments. Genes: the number of genes in the alignment. Characters: The number of amino acids in the alignment. Min.mis: the lowest allowed percentage for missing data for a taxon in the alingnment. Cat.rem.: the number of categories of fast evolving sites removed. Taxa: the number of taxa in the alignment. Excluded taxa: The name of excluded taxa, if any. Method: The method used for phylogenetic inference pb=bayesian inference with Phylobayes mpi version 1.5a (Lartillot et al., 2013), RAxML= maximum likelihood inference with RAxML v 8.0.26 (Stamatkis 2014). Model: The model used for the inference. Max.diff: (only for Bayesian), maximum difference in posterior probability supportbetween two chains that ran independenlty. TCA_rel: (only for maximum likelihood),The relative Tree certainity index for all nodes (Salichos et al., 2014), calculated on the bootstrap files for the inferrence.

Table 3A: 255 Genes, Bayesian alignment name Genes Characters min.mis. Cat.rem taxa Excluded taxa Method Model Max diff 255G_min10 255 54898 10 0 91 0 pb CATGTR 0,266411 255G_min10_rmcat4 255 54898 10 4 91 0 pb CATGTR 0,30002

Table 3B: 147 Genes, Bayesian alignment name Genes Characters min.miss. #cat.rem taxa Excluded taxa Method Model Max diff 146G_min10.CATGTR 146 33081 10 0 91 0 pb CATGTR 0,286544 146G_min10.LG 146 33081 10 0 91 0 pb LG 0,355603 146G_min10_exSpongo.CATGTR 146 32952 10 0 90 S. streptacantha pb CATGTR 0,171197 146G_min10_exSticho.CATGTR 146 32952 10 0 90 S. zanclea pb CATGTR 0,29748

Table 3C: 255 Genes, Maximum Likelihood. alignment name Genes Characters min.mis. #cat.rem taxa Excluded taxa Method Model TCA_rel 255G 255 54898 0 0 124 0 RAxML LG 0,565162 255G_min10 255 54898 10 0 91 0 RAxML LG 0,891783 255G_min20 255 54898 20 0 69 0 RAxML LG 0,879462 255G_min30 255 54898 30 0 55 0 RAxML LG 0,881501 255G_min10_rmcat1 255 54825 10 1 91 0 RAxML LG 0,886363 255G_min10_rmcat2 255 54247 10 2 91 0 RAxML LG 0,899755 255G_min10_rmcat3 255 52502 10 3 91 0 RAxML LG 0,888871 255G_min10_rmcat4 255 48410 10 4 91 0 RAxML LG 0,842282 255G_min10_exSpongo 255 54898 10 0 90 S. streptacantha RAxML LG 0,893954 255G_min10_exSpongo_rmcat1 255 54814 10 1 90 S. streptacantha RAxML LG 0,908864 255G_min10_exSpongo_rmcat2 255 54131 10 2 90 S. streptacantha RAxML LG 0,910279 255G_min10_exSpongo_rmcat3 255 52157 10 3 90 S. streptacantha RAxML LG 0,897523 255G_min10_exSpongo_rmcat4 255 47572 10 4 90 S. streptacantha RAxML LG 0,852508 255G_min10_exSticho 255 54898 10 0 90 S. zanclea RAxML LG 0,900949 255G_min10_exSticho_rmcat1 255 54831 10 1 90 S. zanclea RAxML LG 0,904303 255G_min10_exSticho_rmcat2 255 54309 10 2 90 S. zanclea RAxML LG 0,906108 255G_min10_exSticho_rmcat3 255 52624 10 3 90 S. zanclea RAxML LG 0,883426 255G_min10_exSticho_rmcat4 255 48585 10 4 90 S. zanclea RAxML LG 0,817331 255G_min10_exSpongo_exSticho 255 54898 10 0 89 S. strep. and S. zanclea RAxML LG 0,901578 255G_min10_exSpongo_exSticho_rmcat1 255 54823 10 1 89 S. strep. and S. zanclea RAxML LG 0,898729 255G_min10_exSpongo_exSticho_rmcat2 255 54211 10 2 89 S. strep. and S. zanclea RAxML LG 0,902772 255G_min10_exSpongo_exSticho_rmcat3 255 52308 10 3 89 S. strep. and S. zanclea RAxML LG 0,895606 255G_min10_exSpongo_exSticho_rmcat4 255 47774 10 4 89 S. strep. and S. zanclea RAxML LG 0,871055 255G_min10_exForams 255 54898 10 0 86 Foraminifera RAxML LG 0,896866 255G_min10_exForams_rmcat1 255 54842 10 1 86 Foraminifera RAxML LG 0,903465 255G_min10_exForams_rmcat2 255 54188 10 2 86 Foraminifera RAxML LG 0,902428 255G_min10_exForams_rmcat3 255 52222 10 3 86 Foraminifera RAxML LG 0,887357 255G_min10_exForams_rmcat4 255 47464 10 4 86 Foraminifera RAxML LG 0,848266

Table 3D: 147 Genes, Maximum Likelihood. alignment name Genes Characters min.mis. #cat.rem taxa Excluded taxa Method Model TCA_rel 146G 146 33081 0 0 124 0 RAxML LG 0,544504 146G.rmcat1 146 25236 0 1 124 0 RAxML LG 0,436772 146G.rmcat2 146 13424 0 2 124 0 RAxML LG 0,204149 146G.rmcat3 146 8470 0 3 124 0 RAxML LG 0,074327 146G_min10 146 32952 10 0 91 0 RAxML LG 0,854739 146G_min20 146 33081 20 0 74 0 RAxML LG 0,860809 146G_min30 146 33081 30 0 62 0 RAxML LG 0,843727 146G_min10_rmcat1 146 33007 10 1 91 0 RAxML LG 0,856469 146G_min10_rmcat2 146 32344 10 2 91 0 RAxML LG 0,87058 146G_min10_rmcat3 146 30512 10 3 91 0 RAxML LG 0,829692 146G_min10_rmcat4 146 26726 10 4 91 0 RAxML LG 0,77852 146G_min10_exSpongo 146 32952 10 0 90 S. streptacantha RAxML LG 0,865018 146G_min10_exSpongo_rmcat1 146 32869 10 1 90 S. streptacantha RAxML LG 0,870338 146G_min10_exSpongo_rmcat2 146 32109 10 2 90 S. streptacantha RAxML LG 0,873687 146G_min10_exSpongo_rmcat3 146 30202 10 3 90 S. streptacantha RAxML LG 0,82786 146G_min10_exSpongo_rmcat4 146 26177 10 4 90 S. streptacantha RAxML LG 0,787182 146G_min10_exSticho 146 33081 10 0 90 S. zanclea RAxML LG 0,873601

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S3 Concatenated alignments

146G_min10_exSticho_rmcat1 146 33021 10 1 90 S. zanclea RAxML LG 0,890642 146G_min10_exSticho_rmcat2 146 32483 10 2 90 S. zanclea RAxML LG 0,888718 146G_min10_exSticho_rmcat3 146 30767 10 3 90 S. zanclea RAxML LG 0,863364 146G_min10_exSticho_rmcat4 146 27153 10 4 90 S. zanclea RAxML LG 0,791703 146G_exSpongo_exSticho_min10 146 32952 10 0 89 S. strep. and S. zanclea RAxML LG 0,878715 146G_exSpongo_exSticho_min10_rmcat1 146 32887 10 1 89 S. strep. and S. zanclea RAxML LG 0,876233 146G_exSpongo_exSticho_min10_rmcat2 146 32258 10 2 89 S. strep. and S. zanclea RAxML LG 0,879483 146G_exSpongo_exSticho_min10_rmcat3 146 30450 10 3 89 S. strep. and S. zanclea RAxML LG 0,85276 146G_exSpongo_exSticho_min10_rmcat4 146 26609 10 4 89 S. strep. and S. zanclea RAxML LG 0,795294 146G_min10_exForam 146 33081 10 0 86 Foraminifera RAxML LG 0,874225 146G_min10_exForam_rmcat1 146 33026 10 1 86 Foraminifera RAxML LG 0,869218 146G_min10_exForam_rmcat2 146 32328 10 2 86 Foraminifera RAxML LG 0,878678 146G_min10_exForam_rmcat3 146 30417 10 3 86 Foraminifera RAxML LG 0,847643 146G_min10_exForam_rmcat4 146 26443 10 4 86 Foraminifera RAxML LG 0,764009

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S4 Topologies

Supplementary table S4: The posterior probability (bayesian) and bootstrap support (maximum likelihood) for selected nodes. The support values has been heatmapped with a three color scheme, Green color= high support, yellow=medium support, red= low support. NM= not monophyletic, i.e. the clade or node does not exist for that particular inference. NA=Not applicable, i.e. the clade or node does not exist because some taxa has been removed. For the specifics for each alignment refer to table S3. Tax=Taxopodida; Rad=Radiolaria; Foram=Foraminifer; SAR=Stramenopile, Alveolates, Rhizaria; Red=Rhodophyta; Green=Chlorophytes; Glauco=Glaucophyta; Crypto=Cryptophyta

Table 4A: 255 Genes, Bayesian Topologies/Clades (Tax, Rad) Tax* Endomyxa+R Green+ Red+Green+ Red+Green+ Rhizaria (SA)*R S*(AR) (SAR) Hapt (Red + Green) Hapt+Crypto *Foram (Rad,Foram) etaria Glauco Glauco Glauco+Crypto alignment name 255G_min10.CATGTR 1 NM 0,71 1 1 NM 0,87 1 NM 1 1 NM 255G_min10_rmcat4..CATGTR 1 NM 0,97 1 1 NM NM 1 NM 0,96 0,93 NM

Table 4B: 147 Genes, Bayesian Topologies/Clades (Tax, Rad) Tax* Endomyxa+R Green+ Red+Green+ Red+Green+ Rhizaria (SA)*R S*(AR) (SAR) Hapt (Red + Green) Hapt+Crypto *Foram (Rad,Foram) etaria Glauco Glauco Glauco+Crypto alignment name 146G_min10.CATGTR 1 NM 0,81 1 1 NM 1 0,84 NM 1 1 NM 146G_min10.LG 1 0,67 NM 1 1 NM 1 0,53 NM 1 1 NM 146G_min10_exSpongo.CATGTR 1 1 NM 1 1 NM 1 0,93 NM 0,93 1 NM 146G_min10_exSticho.CATGTR 1 NA NA 1 1 NM 1 0,82 NM 0,95 1 NM

Table 4C: 255 Genes, Maximum Likelihood. Topologies/Clades (Tax, Rad) Tax* Endomyxa+R Green+ Red+Green+ Red+Green+ Rhizaria (SA)*R S*(AR) (SAR) Hapt (Red + Green) Hapt+Crypto alignment name *Foram (Rad,Foram) etaria Glauco Glauco Glauco+Crypto 255G NM 63 NM NM NM NM NM NM NM NM NM NM 255G_min10 100 88 NM 98 NM 96 79 81 NM NM 79 NM 255G_min20 100 51 NM 94 NM 96 90 79 NM NM 90 NM 255G_min30 100 NA NA 100 NM 97 77 92 100 92 77 NM 255G_min10_rmcat1 100 65 NM 98 NM 94 88 94 NM NM 90 NM 255G_min10_rmcat2 100 69 NM 100 NM 94 77 77 NM NM 79 NM 255G_min10_rmcat3 100 NM 25 100 NM 94 85 85 NM NM 92 NM 255G_min10_rmcat4 100 NM 50 90 NM 67 NM 79 NM NM 50 NM 255G_min10_exSpongo 100 71 NM 100 NM 94 81 81 NM NM 81 NM 255G_min10_exSpongo_rmcat1 100 67 NM 98 NM 98 90 88 NM NM 90 NM 255G_min10_exSpongo_rmcat2 100 67 NM 98 NM 96 90 96 NM NM 92 NM 255G_min10_exSpongo_rmcat3 100 48 NM 98 NM 96 85 90 NM NM 88 NM 255G_min10_exSpongo_rmcat4 100 49 NM 95 48 NM NM 67 NM 46 NM 33 255G_min10_exSticho 100 NA NA 98 NM 94 81 88 NM NM 83 NM 255G_min10_exSticho_rmcat1 100 NA NA 100 NM 98 90 85 NM NM 90 NM 255G_min10_exSticho_rmcat2 100 NA NA 100 NM 100 88 87 NM NM 88 NM 255G_min10_exSticho_rmcat3 100 NA NA 98 NM 92 83 87 NM NM 90 NM 255G_min10_exSticho_rmcat4 100 NA NA 94 NM 71 NM 83 NM NM 44 NM 255G_min10_exSpongo_exSticho 100 NA NA 98 NM 100 83 81 NM NM 83 NM 255G_min10_exSpongo_exSticho_rmcat1 100 NA NA 98 NM 100 85 83 NM NM 87 NM 255G_min10_exSpongo_exSticho_rmcat2 100 NA NA 98 NM 100 87 90 NM NM 90 NM 255G_min10_exSpongo_exSticho_rmcat3 100 NA NA 97 NM 83 77 85 NM NM 90 NM 255G_min10_exSpongo_exSticho_rmcat4 100 NA NA 100 NM 60 NM 60 NM 44 NM 37 255G_min10_exForams 100 NA NA 100 NM 92 83 83 NM NM 85 NM 255G_min10_exForams_rmcat1 100 NA NA 100 NM 85 87 92 NM NM 88 NM 255G_min10_exForams_rmcat2 100 NA NA 100 NM 92 96 83 NM NM 96 NM 255G_min10_exForams_rmcat3 100 NA NA 100 NM 85 94 92 NM NM 96 NM 255G_min10_exForams_rmcat4 100 NA NA 100 57 NM NM 64 NM 59 NM 42

Table 4D: 147 Genes, Maximum Likelihood. Topologies/Clades (Tax, Rad) Tax* Endomyxa+R Green+ Red+Green+ Red+Green+ Rhizaria (SA)*R S*(AR) (SAR) Hapt (Red + Green) Hapt+Crypto *Foram (Rad,Foram) etaria Glauco Glauco Glauco+Crypto alignment name 146G NM 62 NM NM NM NM NM NM NM NM NM NM 146G_rmcat1 NM 53 NM NM 60 NM NM NM NM NM NM NM 146G_rmcat2 NM NM NM NM NM NM NM NM NM NM NM NM 146G_rmcat3 NM 4 NM NM NM NM NM NM NM NM NM NM 146G_min10 100 87 NM 100 NM 85 69 44 NM 46 67 NM 146G_min20 100 64 NM 100 NM 85 72 NM 55 42 73 NM 146G_min30 100 NA NA NA NM 95 66 NM 58 47 69 NM 146G_min10_rmcat1 100 85 NM 100 NM 90 79 48 NM 65 77 NM 146G_min10_rmcat2 100 58 NM 100 NM 92 90 NM 46 71 85 NM 146G_min10_rmcat3 100 27 NM 96 NM 71 85 NM 60 69 88 NM 146G_min10_rmcat4 100 NM 75 97 74 NM NM 48 NM 52 NM 29 146G_min10_exSpongo 100 86 NM NM NM 86 69 39 NM 53 70 NM 146G_min10_exSpongo_rmcat1 100 79 NM 100 NM 87 65 42 NM 58 69 NM 146G_min10_exSpongo_rmcat2 100 83 NM 100 NM 96 88 50 NM 65 90 NM 146G_min10_exSpongo_rmcat3 100 63 NM 98 NM 78 78 56 NM NM 84 NM 146G_min10_exSpongo_rmcat4 100 51 NM 97 70 NM NM NM NM 74 NM 38 146G_min10_exSticho 100 NA NA 100 NM 90 67 46 NM 52 69 NM 146G_min10_exSticho_rmcat1 100 NA NA 100 NM 92 83 42 NM 65 71 NM 146G_min10_exSticho_rmcat2 100 NA NA 100 NM 94 85 65 NM 62 83 NM 146G_min10_exSticho_rmcat3 100 NA NA 98 NM 75 88 NM 46 48 90 NM 146G_min10_exSticho_rmcat4 100 NA NA 96 67 NM NM 52 NM 58 NM 35 146G_exSpongo_exSticho_min10 100 NA NA 100 NM 85 71 40 NM 67 73 NM 146G_exSpongo_exSticho_min10_rmcat1 100 NA NA 100 NM 96 69 42 NM 56 71 NM 146G_exSpongo_exSticho_min10_rmcat2 100 NA NA 100 NM 94 79 52 NM 65 81 NM 146G_exSpongo_exSticho_min10_rmcat3 100 NA NA 100 NM 79 79 NM 52 63 85 NM 146G_exSpongo_exSticho_min10_rmcat4 100 NA NA 98 66 NM NM NM NM 63 NM 38 146G_min10_exForam 100 NA NA 100 NM 85 75 44 NM 67 71 NM 146G_min10_exForam_rmcat1 100 NA NA 100 NM 94 73 38 NM 52 75 NM 146G_min10_exForam_rmcat2 100 NA NA 100 NM 87 87 NM 62 73 79 NM 146G_min10_exForam_rmcat3 100 NA NA 100 NM 82 83 61 NM NM 91 NM 146G_min10_exForam_rmcat4 100 NA NA 89 68 NM 52 43 NM 63 56 NM

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