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The Impact of Incongruence and Exogenous Gene Fragments on Estimates of the Eukaryote

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The Impact of Incongruence and Exogenous Gene Fragments on Estimates of the Eukaryote bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438903; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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-NC-ND 4.0 International license. Running head: THE IMPACT OF INCONGRUENCE ON THE EUKARYOTE ROOT 1 1 The impact of incongruence and exogenous gene fragments on estimates of the eukaryote 2 root 3 1 2 4 Caesar Al Jewari and Sandra L. Baldauf 5 6 Program in Systematic Biology, Department of Organismal Biology, Uppsala University, 7 Uppsala, Sweden 75236 8 1 9 Email: [email protected] 2 10 Email: [email protected] 11 12 ORCIDs: 13 Caesar Al Jewari: 0000-0002-0868-0384 14 Sandra L. Baldauf: 0000-0003-4485-6671 15 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438903; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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-NC-ND 4.0 International license. AL JEWARI, C., & BALDAUF, S. L. 2 16 Abstract 17 Phylogenomics uses multiple genetic loci to reconstruct evolutionary trees, under the 18 stipulation that all combined loci share a common phylogenetic history, i.e., they are 19 congruent. Congruence is primarily evaluated via single-gene trees, but these trees invariably 20 lack sufficient signal to resolve deep nodes making it difficult to assess congruence at these 21 levels. Two methods were developed to systematically assess congruence in multi-locus data. 22 Protocol 1 uses gene jackknifing to measure deviation from a central mean to identify 23 taxon-specific incongruencies in the form of persistent outliers. Protocol_2 assesses 24 congruence at the sub-gene level using a sliding window. Both protocols were tested on a 25 controversial data set of 76 mitochondrial proteins previously used in various combinations 26 to assess the eukaryote root. Protocol_1 showed a concentration of outliers in under-sampled 27 taxa, including the pivotal taxon Discoba. Further analysis of Discoba using Protocol_2 28 detected a surprising number of apparently exogenous gene fragments, some of which 29 overlap with Protocol_1 outliers and others that do not. Phylogenetic analyses of the full data 30 using the static LG-gamma evolutionary model support a neozoan-excavate root for 31 eukaryotes (Discoba sister), which rises to 99-100% bootstrap support with data masked 32 according to either Protocol_1 or Protocol_2. In contrast, site-heterogeneous (mixture) 33 models perform inconsistently with these data, yielding all three possible roots depending on 34 presence/absence/type of masking and/or extent of missing data. The neozoan-excavate root 35 places Amorphea (including animals and fungi) and Diaphoretickes (including plants) as 36 more closely related to each other than either is to Discoba (Jakobida, Heterolobosea, and 37 Euglenozoa), regardless of the presence/absence of additional taxa. 38 39 Keywords 40 phylogenomics, congruence, eToL, eukaryote root, Discoba, mitochondrial proteins. 41 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438903; this version posted April 9, 2021. 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-NC-ND 4.0 International license. THE IMPACT OF CONGRUENCE ON THE EUKARYOTE ROOT 3 42 Introduction 43 Over the past twenty years, large multigene (phylogenomic) datasets have confidently 44 and consistently identified the broad outlines of the eukaryote tree of life (eToL) (Baldauf et 45 al. 2000; Bapteste et al. 2002; Brown et al. 2018; Burki et al. 2016, 2020; Strassert et al. 46 2019). As a result, nearly all known eukaryotes can be assigned to one of three supergroups: 47 Amorphea, Diaphoretickes and Excavata. Amorphea includes animals (Holozoa), fungi 48 (Holomycota or Nucletmycea), amoebozoan amoebas (Amoebozoa) and several less well 49 characterized lineages. Diaphoretickes encompasses nearly all other well-known eukaryotes 50 including land plants and nearly all of the algae interspersed with numerous 51 non-photosynthetic lineages such as ciliates, oomycetes and apicomplexan parasites. 52 Excavata is by far the least well known and most poorly understood of the supergroups and is 53 thought to consist mainly of Discoba, Metamonada, and, possibly Malawimonadida (Adl et 54 al. 2018). Within Excavata only the monophyly of Discoba (Jakobida, Euglenozoa and 55 Heterolobosea) is well-established (Kamikawa et al. 2014). Discobans are largely free-living 56 and have functional, if molecularly diverse mitochondria, while all known metamonads are 57 micro- or anaerobic and lack mitochondrial DNA (mtDNA) and nearly all mitochondrial 58 proteins (Hjort et al. 2010). 59 One of the most important outstanding questions in eukaryote phylogeny is the 60 position of the root. Since eukaryote genomes are mosaics with roughly half of their genes of 61 clearly archaeal or bacterial origin (Brueckner & Martin 2020; Cotton & McInerney 2010), 62 eToL can be rooted with either bacterial or archaeal homologs. Of these, archaeal genes trace 63 to the eukaryote first common ancestor (FECA), while bacterial genes trace to the origin of 64 endosymbiotic organelles. Since mitochondria arose after FECA but before the eukaryote last 65 common ancestor (LECA; Gabaldón 2018), this makes bacteria a potentially closer outgroup 66 to eukaryotes than archaea. Nonetheless, rooting eToL with bacteria is complicated by the bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438903; this version posted April 9, 2021. 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-NC-ND 4.0 International license. AL JEWARI, C., & BALDAUF, S. L. 4 67 facts that only ~10% of mitochondrial proteins (mitoPs) are shared across eukaryotes (Gray 68 2012), and these proteins trace to different groups of bacteria, although mostly alpha- and 69 gamma-proteobacteria (aP_bac and gP_bac, respectively) (Kurland & Andersson 2000). In 70 addition, Discoba are the only excavates with mitoPs meaning that an eToL rooted with 71 bacteria can include only one representative of the diverse and not necessarily monophyletic 72 Excavata (Karnkowska et al. 2016). Thus, an eToL based on mitoPs is only one step in 73 defining the eukaryote root, albeit an important one. 74 Previous attempts to recover the eToL root with mitoP data are mainly the work of 75 Derelle and Lang 2012 (DL2012), He et al. 2014 (H2014) and Derelle et al. 2015 (D2015). 76 These studies used partially overlapping subsets of mitoPs and similar taxa but reached 77 different conclusions. DL2012 and D2015 recovered the more traditional unikont-bikont root 78 (Amorphea sister), while H2014 recovered a novel neozoan-excavate root (Discoba sister). 79 These studies differed mainly in outgroup selection (aP_bac only - DL2012/D2015, versus 80 mainly aP - and gP_bac - H2014) and inclusion (DL2012/D2015) or exclusion (H2014) of 81 Malawimonads. In addition, the two studies differ in phylogenetic method, with DL2012 and 82 D2015 using site-heterogeneous evolutionary models and removal of fast evolving site 83 (FSR), while H2014 used site-homogeneous models with no FSR and a site heterogeneous 84 model with a covarion process. Both studies also reported evidence of substantial 85 incongruence in the other data sets. 86 Congruence is a core premise of phylogenomics, i.e., the assumption that the loci to 87 be combined for phylogenetic analysis share the same underlying evolutionary history 88 (Huelsenbeck et al. 1996; Roger et al. 2012). If this premise is met, then increasing data 89 should amplify a weak common signal (Kupczok et al. 2010; Philippe et al. 2011; Wägele et 90 al. 2009). Thus, assessing congruence across a multi-gene dataset is critical. This is generally 91 done by evaluating single gene trees (SGTs) by either visual or automated inspection. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438903; this version posted April 9, 2021. 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-NC-ND 4.0 International license. THE IMPACT OF CONGRUENCE ON THE EUKARYOTE ROOT 5 92 However, SGTs generally lack sufficient phylogenetic signal to resolve the deepest branches 93 in a tree, making it particularly difficult to assess incongruence at deep levels. Variation in 94 length and degree of conservation among loci also make it challenging to apply a uniform 95 standard evaluation process for SGTs. Thus, evaluating SGTs individually becomes a 96 laborious and troublesome process for large numbers of loci. 97 The primary source of molecular incongruence is when genes arising by ancient 98 duplication (out-paralogs) or by horizontal transfer (xenologs) are mistaken for strictly 99 vertically inherited genes (orthologs), since only orthologs directly track organismal 100 phylogeny. Strategies for tackling the congruency problem can be classified into two general 101 categories: 1) detecting persistent outliers by measuring the deviation from a global reference 102 point or 2) clustering genetic loci into subsets based on a compatibility score. Both 103 approaches require a metric to measure the compatibility scores, whether between loci 104 (partitions) or between partitions and a global reference point. This metric is usually based on 105 tree dissimilarity (distance), tree likelihood, or a combination of the two (Smith et al. 2020). 106 The most widely cited methods for automated testing of congruence are Conclustador 107 (Leigh et al.
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