the archaeal legacy of eukaryotes: a phylogenomic perspective – supplementary...

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Cold Spring Harbor – Perspectives in Biology The archaeal legacy of eukaryotes: a phylogenomic perspective – Supplementary

material

Lionel Guy, Jimmy H. Saw and Thijs J. G. Ettema Supplementary Methods 3 Figure S1 arCOGdb, all species, 55 unique panorthologs / RAxML / PROTGAMMAWAG 9 Figure S2 A: 3E3BConcatenate, no eukaryotes / RAxML / PROTCATLG 10 B: 3E3BConcatenate, no eukaryotes / Phylobayes / CAT-Poisson 11 C: Concatenated SSU/LSU rRNA, no eukaryotes / RAxML / GTR+GAMMA 12 D: Concatenated SSU/LSU rRNA, no eukaryotes / Phylobayes / CAT-Poisson 13 Figure S3 A: fullConcatenate / RAxML / PROTCATLG 14 B: fullConcatenate / Phylobayes / CAT-Poisson 15 C: 3E3BConcatenate / RAxML / PROTCATLG 16 D: 3E3BConcatenate / Phylobayes / CAT-Poisson 17 E: discFilter15p / RAxML / PROTCATLG 18 F: discFilter15p / Phylobayes / CAT-Poisson 19 G: discFilter15p / Phylobayes / CAT-GTR 20 H: discFilter15p / Phylobayes / CAT-LG 21 I: chi2filter50 / RAxML / PROTCATLG 22 J: chi2filter50 / Phylobayes / CAT-Poisson 23 Figure S4 A: Concatenated SSU/LSU rRNA / RAxML / GTR+GAMMA 24 B: Concatenated SSU/LSU rRNA / Phylobayes / CAT-Poisson 25 Figure S5 A: Genes removed in discFilt5p dataset / RAxML / PROTCATLG 26 B: Genes removed in discFilt10p dataset / RAxML / PROTCATLG 27 C: Genes removed in discFilt15p dataset / RAxML / PROTCATLG 28 D: Genes removed in discFilt20p dataset / RAxML / PROTCATLG 29 E: Genes removed in discFilt25p dataset / RAxML / PROTCATLG 30 F: Genes removed in discFilt30p dataset / RAxML / PROTCATLG 31 G: Genes removed in discFilt40p dataset / RAxML / PROTCATLG 32 H: Genes removed in discFilt50p dataset / RAxML / PROTCATLG 33 Figure S6 A: discFilt5p / RAxML / PROTCATLG 34 B: discFilt10p / RAxML / PROTCATLG 35 C: discFilt15p / RAxML / PROTCATLG 36 D: discFilt20p / RAxML / PROTCATLG 37 E: discFilt25p / RAxML / PROTCATLG 38 F: discFilt30p / RAxML / PROTCATLG 39 G: discFilt40p / RAxML / PROTCATLG 40 H: discFilt50p / RAxML / PROTCATLG 41 Figure S7 A: chi2filter50 / RAxML / PROTCATLG 42 B: chi2filter75 / RAxML / PROTCATLG 43 C: chi2filter100 / RAxML / PROTCATLG 44 D: chi2filter125 / RAxML / PROTCATLG 45 E: chi2filter150 / RAxML / PROTCATLG 46 F: chi2filter175 / RAxML / PROTCATLG 47 G: chi2filter200 / RAxML / PROTCATLG 48 H: chi2filter225 / RAxML / PROTCATLG 49 Figure S8 A: discFilter15p with Eukaryotes removed / RAxML / PROTCATLG 50 B: discFilter15p with ACK removed / RAxML / PROTCATLG 51 C: discFilter15p with TCK removed / RAxML / PROTCATLG 52

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D: discFilter15p with TAK removed / RAxML / PROTCATLG 53 E: discFilter15p with TAC removed / RAxML / PROTCATLG 54 F: discFilter15p with CK removed / RAxML / PROTCATLG 55 G: discFilter15p with AK removed / RAxML / PROTCATLG 56 H: discFilter15p with AC removed / RAxML / PROTCATLG 57 I: discFilter15p with TC removed / RAxML / PROTCATLG 58 J: discFilter15p with TK removed / RAxML / PROTCATLG 59 K: discFilter15p with TA removed / RAxML / PROTCATLG 60 L: discFilter15p with T removed / RAxML / PROTCATLG 61 M: discFilter15p with A removed / RAxML / PROTCATLG 62 N: discFilter15p with C removed / RAxML / PROTCATLG 63 O: discFilter15p with K removed / RAxML / PROTCATLG 64 Figure S9 A: Concatenated SSU/LSU rRNA with Eukaryotes removed / RAxML /

GTR+GAMMA 65

B: Concatenated SSU/LSU rRNA with ACK removed / RAxML / GTR+GAMMA 66 C: Concatenated SSU/LSU rRNA with TCK removed / RAxML / GTR+GAMMA 67 D: Concatenated SSU/LSU rRNA with TAK removed / RAxML / GTR+GAMMA 68 E: Concatenated SSU/LSU rRNA with TAC removed / RAxML / GTR+GAMMA 69 F: Concatenated SSU/LSU rRNA with CK removed / RAxML / GTR+GAMMA 70 G: Concatenated SSU/LSU rRNA with AK removed / RAxML / GTR+GAMMA 71 H: Concatenated SSU/LSU rRNA with AC removed / RAxML / GTR+GAMMA 72 I: Concatenated SSU/LSU rRNA with TC removed / RAxML / GTR+GAMMA 73 J: Concatenated SSU/LSU rRNA with TK removed / RAxML / GTR+GAMMA 74 K: Concatenated SSU/LSU rRNA with TA removed / RAxML / GTR+GAMMA 75 L: Concatenated SSU/LSU rRNA with T removed / RAxML / GTR+GAMMA 76 M: Concatenated SSU/LSU rRNA with A removed / RAxML / GTR+GAMMA 77 N: Concatenated SSU/LSU rRNA with C removed / RAxML / GTR+GAMMA 78 O: Concatenated SSU/LSU rRNA with K removed / RAxML / GTR+GAMMA 79 Table S1 Taxa selected for this study 80 Table S2 arCOGs selected for this study 82 Dataset S1

Fasta files for 3E3B dataset

Dataset S2

Fasta files for concatenated SSU+LSU dataset

Dataset S3

Fasta files for 16S archaeal phylogeny

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SUPPLEMENTARY!MATERIAL!AND!METHODS!

A general description of how datasets were obtained and which analyses were run on each dataset can be found in Figure 2.

Sequence!alignment!

In general, sequences were aligned with mafft-linsi v6.847b (Katoh and Toh 2008), and positions that had a majority (> 50%) of gaps were trimmed using an in-house Perl script.

Phylogeny!

Unless otherwise stated, maximum likelihood trees were inferred with RAxML 7.2.7 (Stamatakis 2006), using the PROTCATLG model and performing 100 rapid bootstraps. Bayesian phylogenies were inferred with the MPI implementation of Phylobayes 1.3b (Lartillot et al. 2009) running 4 chains. For Bayesian algorithms, about a third of the total trees were discarded as burn-in. If convergence between chains was not fully achieved, the topology of individual trees was examined, to ensure that critical nodes (TACK, placement of the Eukaryotes, etc.) were highly supported in all trees.

Initial!taxon!selection!in!archaea!

The recently updated arCOGs database (Wolf et al. 2012), which contains 120 genomes, was used as a starting point. Fifty-five unique panorthologs, i.e. genes that are present in a single copy in all 120 genomes, were selected. Individual arCOGs were aligned and trimmed, concatenated, and a maximum-likelihood was inferred under the PROTGAMMAWAG model. Taxa were clustered with CD-HIT Suite (Huang et al. 2010), with a 70% identity threshold, using the concatenated alignment as an input, and resulting in 56 clusters. In each of the clusters, one of the genomes that included most of the most common arCOGs (missing in at most 10 genomes) was retained. After examination of the maximum-likelihood tree, manual modifications were done: in three cases, a lesser-studied organisms was replaced with one or two other model organisms that contained one or a few less arCOGs (Staphylothermus marinus instead of S. hellenicus, one arCOG less; Thermosphaera aggregans instead of Desulfurococcus mucosus, 4 arCOGs less; Haloarcula marismortui and Haloferax volcanii, instead of Natrialba magadii, 4 and 2 arCOGs less, respectively). Four genomes that were well represented by their neighboring clusters were removed (Haloarcula hispanica, Methanosaeta concilii, Methanothermobacter marburgensis, and Pyrobaculum arsenaticum) and five well-studied genomes were added (Methanocaldococcus jannaschii, Methanothermobacter thermoautotrophicum, Pyrobaculum calidifontis, Pyrococcus furiosus, and Sulfolobus solfataricus). In total, 58 of the 120 archaeal genomes from the ArCOG dataset were retained for further analysis (Suppl. Table S1).

Addition!of!eukaryotic,!bacterial!and!new!archaeal!genomes!

For 10 Bacteria and 10 eukaryotes (Suppl. Table S1), the COG-arCOG correspondence available in the arCOG database was used to create separate

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databases including the members of a COG in a given organism. COG attribution and sequences were retrieved from the STRING database v9.0 (Szklarczyk et al. 2011). For 8 new archaeal genomes (Suppl. Table S1), protein sequences were retrieved from Genbank, and genome-specific databases were created.

Each of the 256 arCOGs present in at least 90% (i.e. 52 of 58) of the archaeal genomes selected in the previous step were aligned and trimmed. These alignments were used as psi-blast (Altschul et al. 1997) queries against the corresponding COG- and genome-specific databases for Bacteria and eukaryotes, and the genome-specific databases for new archaea. A less restrictive E-value threshold (10-6) was used for the former than for the latter (10-10), given that the genome-specific databases for the new Archaea are larger and more prone to return false positives. Subject genes were included in the arCOGs if they had hits with an E-value (i) below the E-value threshold and (ii) not larger that the square root of the best hit’s E-value.

Protein!cluster!selection!

The extended arCOG clusters, including now bacteria, eukaryotes and new Archaea (86 genomes in total, Suppl. Table S1) were individually aligned and maximum likelihood phylogenies inferred, as described above. All trees were rooted with Bacteria and visually inspected to join split genes and remove paralogs. The following rules were followed to remove all but one paralog in each genome: (i) join split genes, by inspecting the alignment; (ii) prune very long branches; (iii) prune eukaryotic sequences branching inside the bacterial clade, i.e. probably transfers from mitochondria or chloroplasts; (iv) prune all remaining paralogs but the one with the shortest branch. If pruning was not reasonably possible due to the presence of too many paralogs, the tree was discarded. Trees without any eukaryote, or for which either Bacteria or eukaryotes were not monophyletic, were also discarded. After joining split genes and removing paralogs, sequences belonging to the same cluster were realigned and trimmed, and a maximum likelihood tree inferred under PROTGAMMAWAG model. The resulting concatenated dataset (called fullConcatenate) includes 162 clusters with in total 40,585 aligned sites (Suppl. Table S2). Both maximum-likelihood and Bayesian (CAT-Poisson model) phylogenies were inferred from this dataset.

The dataset was further trimmed to remove clusters that did not include at least 3 bacterial and 3 eukaryotic sequences, resulting in a 67 cluster-dataset counting 19,103 sites (referred to as 3E3BConcatenate dataset; Suppl. Table S2). Maximum-likelihood and Bayesian phylogenies (CAT-Poisson model) were also inferred from this dataset. Unaligned fasta files for this dataset are available as Suppl. Dataset S1.

Filtering!clusters!with!discordant!tree!topologies!

To mitigate the effect of horizontal gene transfers on the phylogenies, clusters displaying the most divergent phylogenies were removed using a discordance filter, as in (Williams et al. 2010). In brief, for each cluster, the 100 bootstraps from the maximum likelihood phylogeny were screened, keeping only high-support bipartitions (HSBs), supported by 75 bootstraps or more. A pairwise discordance score was then calculated for each possible pair of clusters, by counting the number of incompatible HSBs in the pair and dividing that count by the product of the counts of HSBs in each member of the pair. HSBs were preliminarily modified to comprise

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only shared taxa. A cluster’s discordance score was defined as the sum of its pairwise discordance scores. Clusters were ranked by increasing discordance (Figure 3a) and different fractions of the most discordant clusters were removed (5, 10, 15, 25, 30, 40 and 50%). The resulting datasets were called discFilter5p, discFilter10p, etc.

For each fraction, the remaining clusters were concatenated and a maximum likelihood phylogeny was inferred from the alignment. To summarize the results, the support for seven selected bipartitions was assessed in the bootstraps calculated for each fraction: TACK superphylum and eukaryotes monophyletic (TACK+E); Korarchaeota grouping with eukaryotes (K+E); Bacteria and eukaryotes monophyletic, corresponding to a 3 Domain hypothesis (E+B); Thaumarchaeota and Aigarchaeota monophyletic (T+A); Crenarchaeota and Geoarchaeote NAG1 monophyletic (C+NAG1); and Crenarchaeota not including Geoarchaeote NAG1 monophyletic, i.e. Geoarchaeote NAG1 branching at the root or within the Crenarchaeota (C-NAG1) (Figure 3b).

In addition to the maximum-likelihood phylogeny, three Bayesian phylogenies were inferred from the discFilter15p (57 clusters, 15,108 sites) with Phylobayes (CAT-Poisson, CAT-GTR and CAT-LG models) and a non-homogeneous one with NH Phylobayes (CAT-BP model).

Filtering!positions!with!biased!aminoJacid!composition!

The alignment where 15% of the most discordant genes were removed (discFilter15p) was further filtered to remove positions with biased amino-acid composition, using a χ2 filter, as described in (Viklund et al. 2012). Briefly, each cluster alignment is analyzed individually: a global χ2-score is calculated for the alignment, by summing, for each sequence and each amino-acid, the normalized squared difference between the observed frequency of the amino-acid in this particular sequence and its expected frequency, deduced from the composition of all sequences. Each position in the alignment is individually trimmed and the difference (δχ2) between the global χ2-score and the χ2-score calculated on the trimmed alignment provides an estimation of the relative contribution of each position to the global amino-acid composition heterogeneity. Positions are then ranked by their δχ2 values, and the most biased sites up to a threshold are removed. Different thresholds were calculated as the average δχ2 minus 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2 and 2.25 times the standard deviation of the δχ2. For each threshold, the remaining positions of each cluster were concatenated and a maximum likelihood phylogeny was inferred from the concatenated alignment. The resulting datasets were called chi2filter50, chi2filter75, etc. The results were summarized as above. A Bayesian phylogeny under the CAT-Poisson model was inferred from the chi2filter50 dataset (57 clusters, 10816 sites).

Effect!of!removing!taxa!

The effect of removing various sets of genomes on the tree topology was also assessed. The discFilter15p was selected as a starting point, and the sequences from the following genomes were removed: (i) all eukaryotic sequences; (ii) only one, (ii) all combinations of two, and (iii) all combinations of three, of the phyla constituting the TACK superphylum (Guy and Ettema 2011) (Thaumarchaeota, Aigarchaetoa, Crenarchaeota, Korarchaeota). The clusters were realigned, trimmed and a maximum likelihood inferred from their concatenated alignment.

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Ribosomal!RNA!gene!phylogeny!

Small subunit (SSU) and large subunit (LSU) ribosomal RNA (rRNA) gene sequences were retrieved from the Silva database (Quast et al. 2013) and taxa with both SSU and LSU sequences were chosen for further analyses. Ten bacteria, 10 eukaryotes, and 82 Archaea (102 taxa in total) representing the key lineages within the tree of life were chosen. Unaligned fasta files for this dataset are available as Suppl. Dataset S2. Sequences were then aligned individually using mafft-linsi aligner (v7.012b) (Katoh and Toh 2008) and poorly aligned regions were removed using TrimAl tool (Capella-Gutierrez et al. 2009) to remove columns with more than 50% gaps. Trimmed individual alignments were then concatenated and phylogenetic analyses were carried out with RAxML (v7.4.1) (Stamatakis 2006) and Phylobayes (v1.3b) (Lartillot et al. 2009) programs. Selection of nucleotide substitutions model was done using JModelTest 2 program (Darriba et al. 2012) and GTR+GAMMA model of nucleotide substitution was chosen for RAxML analyses with 100 bootstrap replicates and GTR+CAT model was chosen for Phylobayes analyses. Bayesian phylogenetic analyses were done using MPI implementation of Phylobayes with 4 chains for 50,000 generations.

The effort of removing certain taxa, as in the amino acid based phylogenetic analyses, was also tested with the ribosomal RNA gene trees by removing eukaryotes, members of TACK superphylum (Thaumarchaeota, Aigarchaeota, Crenarchaeota, and Korarchaeota) (Guy and Ettema 2011), or combinations thereof from these phyla. Various combinations of excluded taxa were aligned with mafft-linsi aligner, trimmed, and maximum likelihood analyses were done using RaxML under a GTR+GAMMA model. Resulting trees were visualized using the program FigTree (http://tree.bio.ed.ac.uk/software/figtree/).

Construction!of!phylogenetic!tree!of!archaeal!16S!rRNA!gene!sequences!

Archaeal 16S rRNA sequences were first extracted from the Silva SSU reference sequence (release 111) and the recently included Geoarchaeote NAG-1 16S sequence (Kozubal et al. 2013) was added to this dataset prior to alignment. This initial extracted dataset contains 10,920 sequences. After removing sequences with ambiguous characters, 9,553 sequences remained for further analysis. A total of 9,554 sequences (including one bacterial outgroup) were aligned by Sina standalone aligner (v1.2.11) (Pruesse et al. 2012), using the Silva non-redundant (NR) SSU Ref dataset as a guide. Columns in the alignment with more than 50% gap characters were removed using TrimAl tool and resulting sequences were further processed by Mothur (Schloss et al. 2009) to check for chimeras. Care was taken to ensure that the sequences were of the same length prior to clustering step. Mothur was used to cluster operational taxonomic units (OTUs) at 90% sequence identity. OTUs were classified using an integrated classifier in Mothur, using the Greengenes taxonomic classification (DeSantis et al. 2006) as a guide. Full-length sequences of the 459 OTUs identified along with 91 guide 16S rRNA sequences (a total of 550 sequences) were then aligned using mafft-linsi, trimmed with TrimAl, and maximum likelihood tree was inferred using RAxML with GTRGAMMA model of nucleotide substitution and 100 bootstrap replicates. Aligned fasta files for this dataset are available as Suppl. Dataset S3.

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References

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Capella-Gutierrez S, Silla-Martinez JM, Gabaldon T. 2009. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25: 1972-1973.

Darriba D, Taboada GL, Doallo R, Posada D. 2012. jModelTest 2: more models, new heuristics and parallel computing. Nature methods 9: 772.

DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL. 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and environmental microbiology 72: 5069-5072.

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Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P et al. 2011. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic acids research 39: D561-568.

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Thermoproteus_uzoniensis_768_

Thermotoga_maritima_MSB8

Acidianus_hospitalis_W1

Thermoplasma_acidophilum_DSM_Ferroglobus_placidus_DSM_1064

Borrelia_burgdorferi_B31

Haloarcula_marismortui_ATCC_4

Pyrobaculum_calidifontis_JCM_

Metallosphaera_sedula_DSM_534

Nanoarchaeum_equitans_Kin4_M

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Sulfolobus_solfataricus_P2

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Hyperthermus_butylicus_DSM_54

Fervidicoccus_fontis_Kam940

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Chlamydia_trachomatis_D_UW_3_

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Methanotorris_igneus_Kol_5

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Methanothermus_fervidus_DSM_2

Sulfolobus_islandicus_M_16_4

Methanobacterium_AL_21

Thermofilum_pendens_Hrk_5

Desulfurococcus_kamchatkensis

Picrophilus_torridus_DSM_9790

Methanohalobium_evestigatum_Z

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Methanoplanus_petrolearius_DSMethanoculleus_marisnigri_JR1

Ca_Korarchaeum_cryptofilum_OP

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Sulfolobus_tokodaii_7

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Pyrolobus_fumarii_1A

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Campylobacter_jejuni_subsp__jejuni_NCTC_11168___ATCC_700819

Candidatus_Nitrosoarchaeum_limnia_SFB1

Candidatus_Korarchaeum_cryptofilum_OPF8

uncultured_MGII

Acidilobus_saccharovorans_345_15

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uncultured_marine_crenarchaeote_KM3_153_F8


Methanothermobacter_thermautotrophicus_str__Delta_H

Desulfurococcus_kamchatkensis_1221n

uncultured_marine_crenarchaeote_AD1000_202_A2


uncultured_marine_crenarchaeote_E6_3G





uncultured_archaeon_GZfos10C7



Methanosphaerula_palustris_E1_9c

uncultured_methanogenic_archaeon_RC_I


uncultured_archaeon_HE574568

Ferroglobus_placidus_DSM_10642Archaeoglobus_fulgidus_DSM_4304




Thermoplasma_acidophilum_DSM_1728

uncultured_marine_crenarchaeote_SAT1000_23_F7



uncultured_crenarchaeote_4B7

uncultured_crenarchaeote_AJ496176

Methanotorris_igneus_Kol_5Methanocaldococcus_jannaschii_DSM_2661


Bacteroides_thetaiotaomicron_VPI_5482



Halobacterium_sp__NRC_1







Escherichia_coli_str__K_12_substr__MG1655

Methanohalobium_evestigatum_Z_7303



uncultured_euryarchaeote_Alv_FOS5


Sulfolobus_tokodaii_str__7

Methanocorpusculum_labreanum_Z

uncultured_crenarchaeote_74A4

Caldivirga_maquilingensis_IC_167


Ca_Caldiarchaeum_subterraneum

Synechocystis_sp__PCC_6803Bacillus_subtilis_subsp__subtilis_str__168

100

50

100

100

87

22

100

100

10086

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10076

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10094

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94

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22

100

95

15

100

54

100

99

Supp. Fig. S2C: Concatenated SSU and LSU rRNA, no eukaryotes / RAxML / GTR+GAMMA 12

0.3






Bacillus_subtilis_subsp__subtilis_str__168
















Metallosphaera_sedula_DSM_5348Metallosphaera_cuprina_Ar_4







Methanohalobium_evestigatum_Z_7303Methanosarcina_acetivorans_C2A


Aeropyrum_pernix_K1









Methanosaeta_thermophila_PTuncultured_archaeon_CR937012





Methanocaldococcus_jannaschii_DSM_2661











Ignicoccus_hospitalis_KIN4_IStaphylothermus_marinus_F1


uncultured_MGII




uncultured_archaeon_CR937008Ferroglobus_placidus_DSM_10642








uncultured_marine_crenarchaeote_AD1000_202_A2uncultured_marine_crenarchaeote_KM3_47_D6





Synechocystis_sp__PCC_6803








NAG1




1

0.63

1

1

0.98

1

1

1

1

1

0.84

1

1

1

1

0.87

1

1

1

0.55

1

0.99

1

0.95

1

1

1

1

0.98

1

1

1

0.56

0.69

0.84

1

1

1

1

0.86

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1

0.95

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1

1

1

1

1

0.99

0.95

1

10.77

1

1

1

0.95

0.98

1

0.98

1

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0.98

0.79

1

1

1

1

0.65

1

1

1

1

1

1

1

0.99

0.8

0.96

1

0.85

1

1

0.95

1

0.83

0.99

1

1

Supp. Fig. S2D: Concatenated SSU and LSU rRNA, no eukaryotes / Phylobayes / CAT-Poisson 13

0.4

Bacillus_subtilis_168Chlamydia_trachomatis_D_UW_3_

Trichomonas_vaginalis


Entamoeba_histolytica_HM_1_IM



Arabidopsis_thaliana




Tetrahymena_thermophila






Thalassiosira_pseudonana_CCMP

Ferroglobus_placidus_DSM_1064

Dictyostelium_discoideum







Aeropyrum_pernix_K1









Geoarchaeon_NAG1






Leishmania_infantum












Uncultured_Marine_Group_II_EuThermoplasma_acidophilum_DSM_

Plasmodium_falciparum




Homo_sapiens






Ca_Micrarchaeum_acidiphilum_A














Halobacterium_NRC_1


Saccharomyces_cerevisiae


Ca_Nanosalinarum_sp_J07AB56Ca_Nanosalina_sp_J07AB43


100

100

72

100

99

98

88

73

100

100

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67

100

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24

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36

89

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66

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74

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Supp. Fig. S3A: fullConcatenate / RAxML / PROTCATLG 14

0.8

Campylobacter_jejuni_NCTC_111Chlamydia_trachomatis_D_UW_3_

Leishmania_infantum









Homo_sapiens














Geoarchaeon_NAG1






















Halobacterium_NRC_1





Pyrococcus_furiosus_DSM_3638Nanoarchaeum_equitans_Kin4_M















Aeropyrum_pernix_K1










Thermoplasma_acidophilum_DSM_





Methanococcus_maripaludis_C6Methanotorris_igneus_Kol_5


0.74

1

1

0.75

1

1

1

0.96

1

1

1

1

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1

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1

11

1

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1

0.74

1

1

1

1

1

1

1

1

1

1

1

1

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1

1

1

0.5

0.95

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0.75

1

1

1

1

0.5

1

1

1

1

1

Supp. Fig. S3B: fullConcatenate / Phylobayes / CAT-Poisson 15

0.4





Halobacterium_NRC_1













Homo_sapiens


















Leishmania_infantum














Pyrobaculum_calidifontis_JCM_Thermoproteus_uzoniensis_768_
















Geoarchaeon_NAG1


Aeropyrum_pernix_K1


















99

54

100

100

100

100

99

100

100

27

97

100

100

52

100

100

86

100

100

100

54

100

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86100

96

100

76

10036

100

100

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100

95

100

100

82

100

100

100

97

100

100

100

100

6060

100

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91

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100

100

100

88

8585

100

85

100

15

100

65

100

100

55

99

100

40

100

99

100

100

53

100

22

Supp. Fig. S3C: 3E3BConcatenate / RAxML / PROTCATLG 16

0.7














Leishmania_infantum




















Methanotorris_igneus_Kol_5Methanococcus_maripaludis_C6










Homo_sapiens

Geoarchaeon_NAG1










Aeropyrum_pernix_K1










Halobacterium_NRC_1





















1

1

1

1

0.9

1

1

1

0.9

1

1

0.5

1

1

1

1

1

0.89

0.74

1

1

1

0.5

1

1

0.94

1

1

1

1

0.51

1

1

0.5

1

1

1

1

1

1

1

0.5

1

1

1

11

1

1

0.5

1

1

1

1

1

1

1

1

1

0.781

1

0.98

1

1

1

0.74

0.92

0.75

1

1

1

11

1

1

1

1

1

Supp. Fig. S3D: 3E3BConcatenate / Phylobayes / CAT-Poisson 17

0.4











Aeropyrum_pernix_K1

Homo_sapiens

Geoarchaeon_NAG1










Leishmania_infantum
































Thalassiosira_pseudonana_CCMPSaccharomyces_cerevisiae






Halobacterium_NRC_1























Archaeoglobus_fulgidus_DSM_43Picrophilus_torridus_DSM_9790

100

100

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100

100

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100

85

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52

45

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98

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99

Supp. Fig. S3E: discFilter15p / RAxML / PROTCATLG 18

0.7

Campylobacter_jejuni_NCTC_111Borrelia_burgdorferi_B31



Leishmania_infantum





















Geoarchaeon_NAG1



























Pyrococcus_furiosus_DSM_3638Nanoarchaeum_equitans_Kin4_M





Homo_sapiens







Halobacterium_NRC_1
















Aeropyrum_pernix_K1


Methanococcus_maripaludis_C6Methanotorris_igneus_Kol_5


1

1

1

1

1

0.66

1

1

0.5

0.99

1

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1

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1

1

1

1

1

11

1

1

0.99

1

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1

0.75

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1

1

1

1

1

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1

1

1

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1

0.83

1

0.99

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1

0.75

1

1

1

1

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1

0.63

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1

1

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11

1

0.58

0.68

1

1

1

1

1

1

1

0.84

1

1

1

1

Supp. Fig. S3F: discFilter15p / Phylobayes / CAT-Poisson 19

0.9

Haloarcula_marismortui_ATCC_4Halalkalicoccus_jeotgali_B3

Geoarchaeon_NAG1



Halobacterium_NRC_1








Aeropyrum_pernix_K1







Rickettsia_prowazekii_Madrid_Escherichia_coli_K_12_substr_













































Homo_sapiens










Leishmania_infantumEntamoeba_histolytica_HM_1_IM









11

1

1

1

1

1

1

1

0.97

1

1

1

1

1

0.74

0.511

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

0.74

1

0.51

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11 1

1

1

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1

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1

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1

0.51

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0.76

1

1

0.74

1

1

1

1

1

1

1

1

1

Supp. Fig. S3G: discFilter15p / Phylobayes / CAT-GTR 20

0.9


















Homo_sapiens


Halobacterium_NRC_1
















Leishmania_infantum














Vulcanisaeta_distributa_DSM_1Caldivirga_maquilingensis_IC_


Aeropyrum_pernix_K1














Geoarchaeon_NAG1




















1

1

1

0.87

0.54

1

1

1

1

0.98

1

0.74

1

1

1

1

1

1

1

1

1

1

0.74

1

1

1

1

1

0.73

0.61

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1

1

1

1

1

1

1

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0.74

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1

0.87

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0.87

1

0.64

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1

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1

1

1

1

1

0.74

1

1

1

Supp. Fig. S3H: discFilter15p / Phylobayes / CAT-LG 21

0.4

















Leishmania_infantum
































Ca_Nitrososphaera_gargensis_GGeoarchaeon_NAG1












Homo_sapiens



















Aeropyrum_pernix_K1


Halobacterium_NRC_1




100

100

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31

100

100

100

86

80

100

91

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100

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100

100

99

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100100

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10066

52

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95

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100

74

50

Supp. Fig. S3I: chi2filter50 / RAxML / PROTCATLG 22

0.6

Metallosphaera_cuprina_Ar_4Thermotoga_maritima_MSB8














Leishmania_infantum

Aeropyrum_pernix_K1








Geoarchaeon_NAG1



















Homo_sapiens











Picrophilus_torridus_DSM_9790Ferroplasma_acidarmanus_fer1


























Halobacterium_NRC_1





0.66

0.661

1

0.87

1

1

0.56

1

1

0.66

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1

0.66

1

1

1

1

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1

1

1

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1

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1

10.87

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1

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1

1

1

1

0.96

1

1

0.66

1

0.88

Supp. Fig. S3J: chi2filter50 / Phylobayes / CAT-Poisson 23

0.4





uncultured_methanogenic_archaeon_RC_IHaloferax_volcanii_DS2











Aeropyrum_pernix_K1



Trichomonas_vaginalis_G3

















Entamoeba_histolytica




uncultured_MGII












Thalassiosira_pseudonana_CCMP1335












uncultured_marine_crenarchaeote_AD1000_325_A12uncultured_crenarchaeote_AJ627422



Leishmania_infantum_JPCM5


Homo_sapiens

Plasmodium_falciparum_3D7

NAG1






























100

100

9 3

100

100

5 3

9 2

6 7

4 0

8 0

7 9

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5 6

100

100

100

100

9 9

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9 9

8 9

100

7 3

5 8

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5 0

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7 6

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4 1

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6 2

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2 2

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3 2

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6 4

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8 9

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100

9 9

100

9 9

100

100

2 4

100

100

100

4 1

100

3 8

Supp. Fig. S4A: Concatenated SSU and LSU rRNA / RAxML / GTR+GAMMA 24

0.6









Ignisphaera_aggregans_DSM_17230Fervidicoccus_fontis_Kam940



Staphylothermus_marinus_F1Ignicoccus_hospitalis_KIN4_I













NAG1



Methanosaeta_thermophila_PTuncultured_archaeon_CR937012











































Leishmania_infantum_JPCM5



Aeropyrum_pernix_K1









Trichomonas_vaginalis_G3

Homo_sapiens


Entamoeba_histolytica

uncultured_archaeon_HE574568uncultured_archaeon_HE574567


uncultured_MGII



Plasmodium_falciparum_3D7


Thalassiosira_pseudonana_CCMP1335





0.92

1

1

0.98

1

1

0.57

0.99

1

0.54

1

1

1

1

0.98

0.98

0.99

0.59

1

1

1

1

0.87

1

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1

1

1

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0.81

1

0.53

1

Supp. Fig. S4B: Concatenated SSU and LSU rRNA / Phylobayes / CAT-Poisson 25

0.4




Halobacterium_NRC_1























Aeropyrum_pernix_K1


Homo_sapiens






















Ca_Korarchaeum_cryptofilum_OPIgnicoccus_hospitalis_KIN4_I


Geoarchaeon_NAG1













Leishmania_infantum


















Methanoculleus_marisnigri_JR1Methanospirillum_hungatei_JF_

100

76

100

61

1837

100

27

28

100

44

70

100

100

100

92

46

100

49

78

100

100

45

97

41

60

100

3470

6

100

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100

100

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7

36

79

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5

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98

56

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41

1928

100

7

71

79

7

33

29

24

6

100

Supp. Fig. S5A: Genes removed in discFilt5p dataset / RAxML / PROTCATLG 26

0.4




Halobacterium_NRC_1




















Aeropyrum_pernix_K1






Leishmania_infantum






















Geoarchaeon_NAG1



Arabidopsis_thalianaHomo_sapiens





























Methanosphaerula_palustris_E1Methanocorpusculum_labreanum_

100

100

100

95

99

35

100

22

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