No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Releasing uncurated datasets is essential for reproducible phylogenomics
... Orthology is the foundation of gene and protein function prediction, and can be studied via two approaches: graph (pairwise sequence comparison)-based or tree (phylogenetic analysis)-based approach [5,6]. Graph (clustering)-based approach employs Bidirectional Best Hits (BBH) method, which is still used by researchers, even though there are reports of uncertainty regarding the identified orthologs [6][7][8]. Researchers improve this approach by using reciprocal best BLAST hits [8][9][10][11][12][13]. Alternatively, other researchers prefer using the manual curation of candidate homologs by phylogenetic analysis [14,15] as well as recent databases and software which use phylogenetic analysis-based protocols to identify orthologs [16,17]. ...
... Graph (clustering)-based approach employs Bidirectional Best Hits (BBH) method, which is still used by researchers, even though there are reports of uncertainty regarding the identified orthologs [6][7][8]. Researchers improve this approach by using reciprocal best BLAST hits [8][9][10][11][12][13]. Alternatively, other researchers prefer using the manual curation of candidate homologs by phylogenetic analysis [14,15] as well as recent databases and software which use phylogenetic analysis-based protocols to identify orthologs [16,17]. ...
In this chapter, we outline a pipeline for ortholog prediction and phylogenetic analysis in plants. This computational pipeline uses algorithms from different software to enable bioinformatic-beginner biologists to predict orthologs that can be shared with many distinct plant nonmodel and model species and identify gene loss events. Prediction of orthologs allows (1) investigation of the evolutionary relationships of plant genomes, (2) discovery of their origin, function, and (3) the impact of their adaptability to the environment.
We developed a pipeline to fit, not only eukaryote but also prokaryote organisms, with small or large genomes. All results acquired from the orthologs predication will enable phylogenetic tree construction, using gene and species (phylogenomic) phylogeny approaches.
... We were unable to assess the driving force behind the topology recovered by Janouškovec et al. [22]; however, we hypothesize that the differences may lie in our increased taxon sampling and use of data partitioning with complex models [34]. It is also possible that the extended taxon sampling improved our resolution of orthologs [35]. ...
... Additionally, maximum likelihood trees for the full datasets were constructed under the LG model were computed using IQtree (LG+F+G) with 1000 ultrafast bootstraps. Single gene datasets including all considered sequences (i.e., including orthologs and paralogs [35];) and ortholog-only datasets are available on figshare [107]. Log files for phylogenomic analyses containing commands and processor information are also available on figshare [117] as recommended by Shen et al. [118]. ...
Background
Apicomplexa is a diverse phylum comprising unicellular endobiotic animal parasites and contains some of the most well-studied microbial eukaryotes including the devastating human pathogens Plasmodium falciparum and Cryptosporidium hominis . In contrast, data on the invertebrate-infecting gregarines remains sparse and their evolutionary relationship to other apicomplexans remains obscure. Most apicomplexans retain a highly modified plastid, while their mitochondria remain metabolically conserved. Cryptosporidium spp. inhabit an anaerobic host-gut environment and represent the known exception, having completely lost their plastid while retaining an extremely reduced mitochondrion that has lost its genome. Recent advances in single-cell sequencing have enabled the first broad genome-scale explorations of gregarines, providing evidence of differential plastid retention throughout the group. However, little is known about the retention and metabolic capacity of gregarine mitochondria.
Results
Here, we sequenced transcriptomes from five species of gregarines isolated from cockroaches. We combined these data with those from other apicomplexans, performed detailed phylogenomic analyses, and characterized their mitochondrial metabolism. Our results support the placement of Cryptosporidium as the earliest diverging lineage of apicomplexans, which impacts our interpretation of evolutionary events within the phylum. By mapping in silico predictions of core mitochondrial pathways onto our phylogeny, we identified convergently reduced mitochondria. These data show that the electron transport chain has been independently lost three times across the phylum, twice within gregarines.
Conclusions
Apicomplexan lineages show variable functional restructuring of mitochondrial metabolism that appears to have been driven by adaptations to parasitism and anaerobiosis. Our findings indicate that apicomplexans are rife with convergent adaptations, with shared features including morphology, energy metabolism, and intracellularity.
... Concerns about reproducibility in phylogenetics are not new but have historically been attributed to the unavailability of the data used in inference 22,23 . For example, a 2013 meta-analysis reported that phylogenetic trees in 6277/7539 (83.3%) studies published in the last few decades are irreproducible due to the unavailability of the underlying data 22 . ...
... How can we increase the reproducibility of phylogenetic inference? One potential solution would be the mandatory reporting of not only sequence alignment (see also the recent commentary by Salomaki et al. 23 ), program, substitution model, and number of independent tree searches, but also of random starting seed numbers, number of threads, and processor type used (Supplementary Note 2). However, the benefits need to be weighed against the practical difficulty of implementing this solution for the hundreds or thousands of gene alignments present in current phylogenomic data sets. ...
Phylogenetic trees are essential for studying biology, but their reproducibility under identical parameter settings remains unexplored. Here, we find that 3515 (18.11%) IQ-TREE-inferred and 1813 (9.34%) RAxML-NG-inferred maximum likelihood (ML) gene trees are topologically irreproducible when executing two replicates (Run1 and Run2) for each of 19,414 gene alignments in 15 animal, plant, and fungal phylogenomic datasets. Notably, coalescent-based ASTRAL species phylogenies inferred from Run1 and Run2 sets of individual gene trees are topologically irreproducible for 9/15 phylogenomic datasets, whereas concatenation-based phylogenies inferred twice from the same supermatrix are reproducible. Our simulations further show that irreproducible phylogenies are more likely to be incorrect than reproducible phylogenies. These results suggest that a considerable fraction of single-gene ML trees may be irreproducible. Increasing reproducibility in ML inference will benefit from providing analyses' log files, which contain typically reported parameters (e.g., program, substitution model, number of tree searches) but also typically unreported ones (e.g., random starting seed number, number of threads, processor type).
... As a consequence, some researchers combine fast ortholog clustering with manual curation [158,159], a practice that can mitigate such issues but also introduces subjectivity. The greater part of these curation process (and the subjectivity involved) is lost to the wider scientific record and can produce data sets that are difficult to analyse, compare, and critically assess [160]. Providing access to the data from these "chains" of analyses will be important, especially for the systematic integration of new data sets which allows for the revision of ortholog classifications (see Box 2 recommendations and Fig 3B). ...
Understanding the origin of eukaryotic cells is one of the most difficult problems in all of biology. A key challenge relevant to the question of eukaryogenesis is reconstructing the gene repertoire of the last eukaryotic common ancestor (LECA). As data sets grow, sketching an accurate genomics-informed picture of early eukaryotic cellular complexity requires provision of analytical resources and a commitment to data sharing. Here, we summarise progress towards understanding the biology of LECA and outline a community approach to inferring its wider gene repertoire. Once assembled, a robust LECA gene set will be a useful tool for evaluating alternative hypotheses about the origin of eukaryotes and understanding the evolution of traits in all descendant lineages, with relevance in diverse fields such as cell biology, microbial ecology, biotechnology, agriculture, and medicine. In this Consensus View, we put forth the status quo and an agreed path forward to reconstruct LECA’s gene content.
... Tracking native and non-native crayfish distributions is therefore of the utmost importance for the conservation of both crayfish and the variety of aquatic ecosystems they inhabit (Jussila et al., 2021). Without rapid and accessible communication of field observations, along with geo-spatial descriptive information, effective early management actions are impossible (Sax & Gaines, 2003;Mcclenachan, Ferretti & Baum, 2012;Salomaki et al., 2020;Miller et al., 2021). Accurate species identification for many crayfish species, however, remains challenging, particularly in sympatric areas, with expert studies and reports remaining the most trustworthy sources for occurrence data (Costello, 2009;Costello et al., 2013;Costello & Wieczorek, 2014). ...
Freshwater crayfish are amongst the largest macroinvertebrates and play a keystone role in the ecosystems they occupy. Understanding the global distribution of these animals is often hindered due to a paucity of distributional data. Additionally, non-native crayfish introductions are becoming more frequent, which can cause severe environmental and economic impacts. Management decisions related to crayfish and their habitats require accurate, up-to-date distribution data and mapping tools. Such data are currently patchily distributed with limited accessibility and are rarely up-to-date. To address these challenges, we developed a versatile e-portal to host distributional data of freshwater crayfish and their pathogens (using Aphanomyces astaci, the causative agent of the crayfish plague, as the most prominent example). Populated with expert data and operating in near real-time, World of Crayfish™ is a living, publicly available database providing worldwide distributional data sourced by experts in the field. The database offers open access to the data through specialized standard geospatial services (Web Map Service, Web Feature Service) enabling users to view, embed, and download customizable outputs for various applications. The platform is designed to support technical enhancements in the future, with the potential to eventually incorporate various additional features. This tool serves as a step forward towards a modern era of conservation planning and management of freshwater biodiversity.
... Here we provide the logic used for ortholog selection during the construction of PhyloFisher v. 1.0.0 provided starting database as described in Salomaki et al. (2020) and Tice et al. (2021). However, many of these guidelines are flexible for users with knowledge of systematics and molecular evolution to adjust based on their preferences. ...
PhyloFisher is a software package written primarily in Python3 that can be used for the creation, analysis, and visualization of phylogenomic datasets that consist of protein sequences from eukaryotic organisms. Unlike many existing phylogenomic pipelines, PhyloFisher comes with a manually curated database of 240 protein‐coding genes, a subset of a previous phylogenetic dataset sampled from 304 eukaryotic taxa. The software package can also utilize a user‐created database of eukaryotic proteins, which may be more appropriate for shallow evolutionary questions. PhyloFisher is also equipped with a set of utilities to aid in running routine analyses, such as the prediction of alternative genetic codes, removal of genes and/or taxa based on occupancy/completeness of the dataset, testing for amino acid compositional heterogeneity among sequences, removal of heterotachious and/or fast‐evolving sites, removal of fast‐evolving taxa, supermatrix creation from randomly resampled genes, and supermatrix creation from nucleotide sequences. © 2024 Wiley Periodicals LLC.
Basic Protocol 1 : Constructing a phylogenomic dataset
Basic Protocol 2 : Performing phylogenomic analyses
Support Protocol 1 : Installing PhyloFisher
Support Protocol 2 : Creating a custom phylogenomic database
... Methods to detect and filter those outlier sequences have been used to curate phylogenomic matrices of protists (Strassert et al. 2021;Irisarri et al. 2022), plants (Laurin-Lemay et al. 2012), fungi (Varga et al. 2019), metazoans (Simion et al. 2017) or mammals (Scornavacca et al. 2019), and there are softwares to detect sequences that lead to unrealistically long branch lengths (TreeShrink: Mai and Mirarab 2018). In order to allow reproducibility, the release by the authors of both the candidate set of homologs and orthologs for a particular locus is encouraged, as well as the curated final alignments (Salomaki et al. 2020). ...
Over the last decade, molecular systematics has undergone a change of paradigm as high-throughput sequencing (HTS) now makes it possible to reconstruct evolutionary relationships using genome-scale datasets. The advent of ‘big data’ molecular phylogenetics provided a battery of new tools for biologists, but simultaneously brought new methodological challenges. The increase in analytical complexity comes at the price of highly specific training in computational biology and molecular phylogenetics, resulting very often in a polarized accumulation of knowledge (technical on one side, and biological on the other). Interpreting the robustness of genome-scale phylogenetic studies is not straightforward, particularly as new methodological developments have consistently shown that the general belief of ‘more genes, more robustness’ often does not apply, and because there is a range of systematic errors that plague phylogenomic investigations. This is particularly problematic because phylogenomic studies are highly heterogeneous in their methodology, and best practices are often not clearly defined. The main aim of this article is to present what I consider as the ten most important points to take into consideration when planning a well-thought-out phylogenomic study and while evaluating the quality of published papers. The goal is to provide a practical step-by-step guide that can be easily followed by non-experts and phylogenomic novices in order to assess the technical robustness of phylogenomic studies or improve the experimental design of a project.
Repeated runs of the same program can generate different molecular phylogenies from identical datasets under the same analytical conditions. This lack of reproducibility of inferred phylogenies casts a long shadow on downstream research employing these phylogenies in areas such as comparative genomics, systematics, and functional biology. We have assessed the relative accuracies and log-likelihoods of alternative phylogenies generated for computer-simulated and empirical datasets. Our findings indicate that these alternative phylogenies reconstruct evolutionary relationships with comparable accuracy. They also have similar log-likelihoods that are not inferior to the log-likelihoods of the true tree. We determined that the direct relationship between irreproducibility and inaccuracy is due to their common dependence on the amount of phylogenetic information in the data. While computational reproducibility can be enhanced through more extensive heuristic searches for the maximum likelihood tree, this does not lead to higher accuracy. We conclude that computational irreproducibility plays a minor role in molecular phylogenetics.
Apicomplexans and related lineages comprise many obligate symbionts of animals; some of which cause notorious diseases such as malaria. They evolved from photosynthetic ancestors and transitioned into a symbiotic lifestyle several times, giving rise to species with diverse non-photosynthetic plastids. Here we sought to reconstruct the evolution of the cryptic plastids in the Apicomplexa, Chrompodellids, and Squirmida (ACS clade) by generating five new single-cell transcriptomes from understudied gregarine lineages, constructing a robust phylogenomic tree incorporating all ACS clade sequencing datasets available, and using these to examine in detail the evolutionary distribution of all 162 proteins recently shown to be in the apicoplast by spatial proteomics in Toxoplasma. This expanded homology-based reconstruction of plastid proteins found in the ACS clade confirm earlier work showing convergence in the overall metabolic pathways retained once photosynthesis is lost, but also reveals differences in the degrees of plastid reduction in specific lineages. We show that the loss of the plastid genome is common and unexpectedly find many lineage- and species-specific plastid proteins, suggesting the presence of evolutionary innovations and neofunctionalizations that may confer new functional and metabolic capabilities that are yet to be discovered in these enigmatic organelles.
The resolution of the broad-scale tree of eukaryotes is constantly improving, but the evolutionary origin of several major groups remains unknown. Resolving the phylogenetic position of these "orphan" groups is important, especially those that originated early in evolution, because they represent missing evolutionary links between established groups. Telonemia is one such orphan taxon for which little is known. The group is composed of molecularly diverse biflagellated protists, often prevalent although not abundant in aquatic environments. Telonemia has been hypothesized to represent a deeply diverging eukaryotic phylum but no consensus exists as to where it is placed in the tree. Here, we established cultures and report the phylogenomic analyses of three new transcriptome data sets for divergent telonemid lineages. All our phylogenetic reconstructions, based on 248 genes and using site-heterogeneous mixture models, robustly resolve the evolutionary origin of Telonemia as sister to the Sar supergroup. This grouping remains well supported when as few as 60% of the genes are randomly subsampled, thus is not sensitive to the sets of genes used but requires a minimal alignment length to recover enough phylogenetic signal. Telonemia occupies a crucial position in the tree to examine the origin of Sar, one of the most lineage-rich eukaryote supergroups. We propose the moniker "TSAR" to accommodate this new mega-assemblage in the phylogeny of eukaryotes. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: [email protected]
Increasingly, large phylogenomic data sets include transcriptomic data from nonmodel organisms. This not only has allowed controversial and unexplored evolutionary relationships in the tree of life to be addressed but also increases the risk of inadvertent inclusion of paralogs in the analysis. Although this may be expected to result in decreased phylogenetic support, it is not clear if it could also drive highly supported artifactual relationships. Many groups, including the hyperdiverse Lissamphibia, are especially susceptible to these issues due to ancient gene duplication events and small numbers of sequenced genomes and because transcriptomes are increasingly applied to resolve historically conflicting taxonomic hypotheses. We tested the potential impact of paralog inclusion on the topologies and timetree estimates of the Lissamphibia using published and de novo sequencing data including 18 amphibian species, from which 2,656 single-copy gene families were identified. A novel paralog filtering approach resulted in four differently curated data sets, which were used for phylogenetic reconstructions using Bayesian inference, maximum likelihood, and quartet-based supertrees. We found that paralogs drive strongly supported conflicting hypotheses within the Lissamphibia (Batrachia and Procera) and older divergence time estimates even within groups where no variation in topology was observed. All investigated methods, except Bayesian inference with the CAT-GTR model, were found to be sensitive to paralogs, but with filtering convergence to the same answer (Batrachia) was observed. This is the first large-scale study to address the impact of orthology selection using transcriptomic data and emphasizes the importance of quality over quantity particularly for understanding relationships of poorly sampled taxa.
Almost all eukaryote life forms have now been placed within one of five to eight supra-kingdom-level groups using molecular phylogenetics1–4. The ‘phylum’ Hemimastigophora is probably the most distinctive morphologically defined lineage that still awaits such a phylogenetic assignment. First observed in the nineteenth century, hemimastigotes are free-living predatory protists with two rows of flagella and a unique cell architecture5–7; to our knowledge, no molecular sequence data or cultures are currently available for this group. Here we report phylogenomic analyses based on high-coverage, cultivation-independent transcriptomics that place Hemimastigophora outside of all established eukaryote supergroups. They instead comprise an independent supra-kingdom-level lineage that most likely forms a sister clade to the ‘Diaphoretickes’ half of eukaryote diversity (that is, the ‘stramenopiles, alveolates and Rhizaria’ supergroup (Sar), Archaeplastida and Cryptista, as well as other major groups). The previous ranking of Hemimastigophora as a phylum understates the evolutionary distinctiveness of this group, which has considerable importance for investigations into the deep-level evolutionary history of eukaryotic life—ranging from understanding the origins of fundamental cell systems to placing the root of the tree. We have also established the first culture of a hemimastigote (Hemimastix kukwesjijk sp. nov.), which will facilitate future genomic and cell-biological investigations into eukaryote evolution and the last eukaryotic common ancestor. Phylogenetic analyses based on single-cell transcriptomic data from two hemimastigotes, a Spironema species and the newly described Hemimastix kukwesjijk, indicate that Hemimastigophora is a supra-kingdom-level lineage of eukaryotes.
Recent phylogenetic analyses position certain ‘orphan’ protist lineages deep in the tree of eukaryotic life, but their exact placements are poorly resolved. We conducted phylogenomic analyses that incorporate deeply sequenced transcriptomes from representatives of collodictyonids (diphylleids), rigifilids, Mantamonas and ancyromonads (planomonads). Analyses of 351 genes, using site-heterogeneous mixture models, strongly support a novel supergroup-level clade that includes collodictyonids, rigifilids and Mantamonas, which we name ‘CRuMs’. Further, they robustly place CRuMs as the closest branch to Amorphea (including animals and fungi). Ancyromonads are strongly inferred to be more distantly related to Amorphea than are CRuMs. They emerge either as sister to malawimonads, or as a separate deeper branch. CRuMs and ancyromonads represent two distinct major groups that branch deeply on the lineage that includes animals, near the most commonly inferred root of the eukaryote tree. This makes both groups crucial in examinations of the deepest-level history of extant eukaryotes.
Phylogenomic studies have resolved countless branches of the tree of life, but remain strongly contradictory on certain, contentious relationships. Here, we use a maximum likelihood framework to quantify the distribution of phylogenetic signal among genes and sites for 17 contentious branches and 6 well-established control branches in plant, animal and fungal phylogenomic data matrices. We find that resolution in some of these 17 branches rests on a single gene or a few sites, and that removal of a single gene in concatenation analyses or a single site from every gene in coalescence-based analyses diminishes support and can alter the inferred topology. These results suggest that tiny subsets of very large data matrices drive the resolution of specific internodes, providing a dissection of the distribution of support and observed incongruence in phylogenomic analyses. We submit that quantifying the distribution of phylogenetic signal in phylogenomic data is essential for evaluating whether branches, especially contentious ones, are truly resolved. Finally, we offer one detailed example of such an evaluation for the controversy regarding the earliest-branching metazoan phylum, for which examination of the distributions of gene-wise and site-wise phylogenetic signal across eight data matrices consistently supports ctenophores as the sister group to all other metazoans.
Many of the eukaryotic phylogenomic analyses published to date were based on alignments of hundreds to thousands of genes. Frequently, in such analyses, the most realistic evolutionary models currently available are often used to minimize the impact of systematic error. However, controversy remains over whether or not idiosyncratic gene family dynamics (i.e., gene duplications and losses) and incorrect orthology assignments are always appropriately taken into account. In this paper, we present an innovative strategy for overcoming orthology assignment problems. Rather than identifying and eliminating genes with paralogy problems, we have constructed a data set comprised exclusively of conserved single-copy protein domains that, unlike most of the commonly used phylogenomic data sets, should be less confounded by orthology miss-assignments. To evaluate the power of this approach, we performed maximum likelihood and Bayesian analyses to infer the evolutionary relationships within the opisthokonts (which includes Metazoa, Fungi, and related unicellular lineages). We used this approach to test 1) whether Filasterea and Ichthyosporea form a clade, 2) the interrelationships of early-branching metazoans, and 3) the relationships among early-branching fungi. We also assessed the impact of some methods that are known to minimize systematic error, including reducing the distance between the outgroup and ingroup taxa or using the CAT evolutionary model. Overall, our analyses support the Filozoa hypothesis in which Ichthyosporea are the first holozoan lineage to emerge followed by Filasterea, Choanoflagellata, and Metazoa. Blastocladiomycota appears as a lineage separate from Chytridiomycota, although this result is not strongly supported. These results represent independent tests of previous phylogenetic hypotheses, highlighting the importance of sophisticated approaches for orthology assignment in phylogenomic analyses.
The phylogenetic relationships of amoebae are poorly resolved. To address this difficult question, we have sequenced 1,280 expressed sequence tags from Mastigamoeba balamuthi and assembled a large data set containing 123 genes for representatives of three phenotypically highly divergent major amoeboid lineages: Pelobionta, Entamoebidae, and Mycetozoa. Phylogenetic reconstruction was performed on approximately 25,000 aa positions for 30 species by using maximum-likelihood approaches. All well-established eukaryotic groups were recovered with high statistical support, validating our approach. Interestingly, the three amoeboid lineages strongly clustered together in agreement with the Conosa hypothesis [as defined by T. Cavalier-Smith (1998) Biol. Rev. Cambridge Philos. Soc. 73, 203-266]. Two amitochondriate amoebae, the free-living Mastigamoeba and the human parasite Entamoeba, formed a significant sister group to the exclusion of the mycetozoan Dictyostelium. This result suggested that a part of the reductive process in the evolution of Entamoeba (e.g., loss of typical mitochondria) occurred in its free-living ancestors. Applying this inexpensive expressed sequence tag approach to many other lineages will surely improve our understanding of eukaryotic evolution.
Reconstructing a global phylogeny of eukaryotes is an ongoing challenge of molecular phylogenetics. The availability of genomic data from a broad range of eukaryotic phyla helped in resolving the eukaryotic tree into a topology with a rather small number of large assemblages, but the relationships between these "supergroups" are yet to be confirmed. Rhizaria is the most recently recognized "supergroup," but, in spite of this important position within the tree of life, their representatives are still missing in global phylogenies of eukaryotes. Here, we report the first large-scale analysis of eukaryote phylogeny including data for 2 rhizarian species, the foraminiferan Reticulomyxa filosa and the chlorarachniophyte Bigelowiella natans. Our results confirm the monophyly of Rhizaria (Foraminifera + Cercozoa), with very high bootstrap supports in all analyses. The overall topology of our trees is in agreement with the current view of eukaryote phylogeny with basal division into "unikonts" (Opisthokonts and Ameobozoa) and "bikonts" (Plantae, alveolates, stramenopiles, and excavates). As expected, Rhizaria branch among bikonts; however, their phylogenetic position is uncertain. Depending on the data set and the type of analysis, Rhizaria branch as sister group to either stramenopiles or excavates. Overall, the relationships between the major groups of unicellular bikonts are poorly resolved, despite the use of 85 proteins and the largest taxonomic sampling for this part of the tree available to date. This may be due to an acceleration of evolutionary rates in some bikont phyla or be related to their rapid diversification in the early evolution of eukaryotes.
Oxygen plays a crucial role in energetic metabolism
of most eukaryotes. Yet adaptations to low-oxygen
concentrations leading to anaerobiosis have independently
arisen in many eukaryotic lineages, resulting
in a broad spectrum of reduced and modified
mitochondrion-related organelles (MROs). In this
study, we present the discovery of two new classlevel
lineages of free-living marine anaerobic ciliates,
Muranotrichea, cl. nov. and Parablepharismea, cl.
nov., that, together with the class Armophorea,
form a major clade of obligate anaerobes (APM ciliates)
within the Spirotrichea, Armophorea, and Litostomatea
(SAL) group. To deepen our understanding
of the evolution of anaerobiosis in ciliates, we predicted
the mitochondrial metabolism of cultured representatives
from all three classes in the APM clade
by using transcriptomic and metagenomic data and
performed phylogenomic analyses to assess their
evolutionary relationships. The predicted mitochondrial
metabolism of representatives from the APM ciliates
reveals functional adaptations of metabolic
pathways that were present in their last common
ancestor and likely led to the successful colonization
and diversification of the group in various anoxic environments.
Furthermore, we discuss the possible
relationship of Parablepharismea to the uncultured
deep-sea class Cariacotrichea on the basis of single-
gene analyses. Like most anaerobic ciliates, all
studied species of the APM clade host symbionts,
which we propose to be a significant accelerating
factor in the transitions to an obligately anaerobic
lifestyle. Our results provide an insight into the evolutionary
mechanisms of early transitions to anaerobiosis
and shed light on fine-scale adaptations in
MROs over a relatively short evolutionary time frame.
Phylogenetic analyses of transcriptome data for representatives of the red algal Acrochaetiales-Palmariales Complex provided robust support for the assignment of genera to the constituent families. In the Acrochaetiales, the genera Acrochaetium, Grania, and an unnamed genus-level lineage (Acrochaetiac sp._1Aus) were assigned to the Acrochaetiaceae, while Audouinella is placed in a resurrected Audouinellaceae and Rhodochorton and Rhododrewia constitute the resurrected Rhodochortonaceae. For the Palmariales, transcriptome data solidly support the inclusion of Camontagnea and Rhodothamniella in the Rhodothamniellaceae, Meiodiscus and Rubrointrusa in the Meiodiscaceae, Rhodonematella and Rhodophysema in the Rhodophysemataceae, while Devaleraea and Palmaria remained in the Palmariaceae. These analyses, however, questioned the monophyly of Palmaria, which prompted a second round of analyses using eight common red algal phylogenetic markers and including a broader sampling of red algal genera in our analyses. These results supported transfer of Palmaria callophylloides and P. mollis to the genus Devaleraea necessitating new combinations, and further added the genus Halosaccion to the Palmariaceae and the genera Kallymenicola and Rhodophysemopsis to the Meiodiscaceae. Finally, DNA barcode (mitochondrial COI-5P) and ITS data were explored and supported the continued recognition of Palmaria palmata as a single species in the North Atlantic.
Many anaerobic microbial parasites possess highly modified mitochondria known as mitochondrion-related organelles (MROs). The best-studied of these are the hydrogenosomes of Trichomonas vaginalis and Spironucleus salmonicida, which produce ATP anaerobically through substrate-level phosphorylation with concomitant hydrogen production; and the mitosomes of Giardia intestinalis, which are functionally reduced and lack any role in ATP production. However, to understand the metabolic specializations that these MROs underwent in adaptation to parasitism, data from their free-living relatives are needed. Here, we present a large-scale comparative transcriptomic study of MROs across a major eukaryotic group, Metamonada, examining lineage-specific gain and loss of metabolic functions in the MROs of Trichomonas, Giardia, Spironucleus and their free-living relatives. Our analyses uncover a complex history of ATP production machinery in diplomonads such as Giardia, and their closest relative, Dysnectes; and a correlation between the glycine cleavage machinery and lifestyles. Our data further suggest the existence of a previously undescribed biochemical class of MRO that generates hydrogen but is incapable of ATP synthesis.
- M M Leger
Leger, M. M. et al. Nat. Ecol. Evol. 1, 0092 (2017).
- J Rotterová
Rotterová, J. et al. Curr. Biol. 30, 2037-2050 (2020).
- G Lax
Lax, G. et al. Nature 564, 410-414 (2018).
- K Siu-Ting
Siu-Ting, K. et al. Mol. Biol. Evol. 36, 1344-1356 (2019).
- E Bapteste
Bapteste, E. et al. Proc. Natl Acad. Sci. USA 99, 1414-1419
(2002).
- F Burki
- Pawlowski
Burki, F. & Pawlowski, J. Mol. Biol. Evol. 23, 1922-1930
(2006).
- M W Brown
Brown, M. W. et al. Genome Biol. Evol. 10, 427-433 (2018).
- G Torruella
Torruella, G. et al. Mol. Biol. Evol. 29, 531-544 (2012).
- G W Saunders
- C Jackson
- E D Salomaki
Saunders, G. W., Jackson, C. & Salomaki, E. D. Mol. Phylogenet.
Evol. 119, 151-159 (2018).