Skip to main content
PLOS Genetics logoLink to PLOS Genetics
. 2020 Mar 16;16(3):e1008584. doi: 10.1371/journal.pgen.1008584

Cell cycle transcriptomics of Capsaspora provides insights into the evolution of cyclin-CDK machinery

Alberto Pérez-Posada 1, Omaya Dudin 1, Eduard Ocaña-Pallarès 1, Iñaki Ruiz-Trillo 1,2,3,*, Andrej Ondracka 1,*
Editor: Joseph Heitman4
PMCID: PMC7098662  PMID: 32176685

Abstract

Progression through the cell cycle in eukaryotes is regulated on multiple levels. The main driver of the cell cycle progression is the periodic activity of cyclin-dependent kinase (CDK) complexes. In parallel, transcription during the cell cycle is regulated by a transcriptional program that ensures the just-in-time gene expression. Many core cell cycle regulators are widely conserved in eukaryotes, among them cyclins and CDKs; however, periodic transcriptional programs are divergent between distantly related species. In addition, many otherwise conserved cell cycle regulators have been lost and independently evolved in yeast, a widely used model organism for cell cycle research. For a better understanding of the evolution of the cell cycle regulation in opisthokonts, we investigated the transcriptional program during the cell cycle of the filasterean Capsaspora owczarzaki, a unicellular species closely related to animals. We developed a protocol for cell cycle synchronization in Capsaspora cultures and assessed gene expression over time across the entire cell cycle. We identified a set of 801 periodic genes that grouped into five clusters of expression over time. Comparison with datasets from other eukaryotes revealed that the periodic transcriptional program of Capsaspora is most similar to that of animal cells. We found that orthologues of cyclin A, B and E are expressed at the same cell cycle stages as in human cells and in the same temporal order. However, in contrast to human cells where these cyclins interact with multiple CDKs, Capsaspora cyclins likely interact with a single ancestral CDK1-3. Thus, the Capsaspora cyclin-CDK system could represent an intermediate state in the evolution of animal-like cyclin-CDK regulation. Overall, our results demonstrate that Capsaspora could be a useful unicellular model system for animal cell cycle regulation.

Author summary

When cells reproduce, proper duplication and splitting of the genetic material is ensured by cell cycle control systems. Many of the regulators in these systems are present across all eukaryotes, such as cyclin and cyclin-dependent kinases (CDK), or the E2F-Rb transcriptional network. Opisthokonts, the group comprising animals, fungi and their unicellular relatives, represent a puzzling scenario: in contrast to animals, where the cell cycle core machinery seems to be conserved, studies in yeasts have shown that some of these regulators have been lost and independently evolved. For a better understanding of the evolution of the cell cycle regulation in opisthokonts, and ultimately in the lineage leading to animals, we have studied cell cycle regulation in Capsaspora owczarzaki, a unicellular amoeba more closely related to animals than fungi. Our findings suggest that, in the ancestor of Capsaspora and animals, cyclins oscillate in the same temporal order as in animals, and that expansion of CDKs occurred later in the lineage that led to animals.

Introduction

The cell cycle is an essential and fundamental biological process that underpins the cell division and proliferation of all cells. Progression through the cell cycle involves multiple layers of regulation [1]. The main regulatory networks that govern the transitions between cell cycle stages are broadly conserved in eukaryotes, both on the level of individual regulators [2], as well as on the level of network topology [3]. However, it is still not well understood how this conserved regulatory network is deployed in cells with different cellular lifestyles and how it changes across evolution.

Among the main regulators of the progression through the cell cycle are cyclins and cyclin-dependent kinases (CDKs), two gene families broadly conserved across eukaryotes [1,2]. Cyclins and CDKs have undergone independent expansions and subfunctionalization in every major lineage of eukaryotes, including opisthokonts [46]. In animals, there are multiple cyclins and CDKs that form discrete complexes, activating specific downstream effectors in different phases of the cell cycle [7,8]. Cyclin D-CDK4,6 complexes control entry into the cell cycle in response to mitogenic factors [911]. The G1/S transition is driven by the Cyclin E/CDK2 complex [12,13], and progression through S phase is controlled by the Cyclin A/CDK2 complex [13]. Lastly, cyclin B/CDK1 drive completion of mitosis [14,15]. In contrast, in the budding yeast Saccharomyces cerevisiae one single CDK sequentially binds to nine cyclins in three temporal waves [16,17]: Cln1-2 are expressed in G1 and mark the commitment to a new cycle [1821], Clb5,6 promote DNA replication at S phase [22,23], and Clb1-4 drive progression through mitosis [24,25]. The fission yeast Schizosaccharomyces pombe has a single CDK that also binds different cyclins at G1,S, and M: Cig1,2 drive progression through G1 and S phase [26,27], and Cdc13 drives progression through mitosis [28,29]. However, a single CDK-Cyclin complex can drive progression through the entire cell cycle in this species [30].

In addition to the cyclin-CDK activity, the cell cycle is also regulated at the transcriptional level by timing the expression of genes required in its different phases. For instance, the E2F-Rb network of transcription factors controls initiation of DNA replication in animals at the G1/S transition [3133]. In yeasts, transcriptional regulation of the G1/S transition is driven by SBF and MBF, two transcription factor complexes that bear no homology to E2F [34]. Recent findings show that these transcription factors were acquired through lateral gene transfer during fungal evolution [2]. In addition, other transcription factors are the mitotic Fkh1 and Fkh2 [35,36] in S. cerevisiae or the Hcm1 transcription factor, controlling progression through G2 and mitosis [37]. In human cells, a protein of the same family, FoxM1, also regulates gene expression in mitosis [32,38]. Although oscillatory transcriptional activity during the cell cycle is present in numerous species and cell types [32,33,37,3950], the genes affected by cell cycle-regulated transcription are divergent between distantly related species [51]. Likewise, even among different human cell types, periodic expression of only a fraction of genes is common to all of them [32,52].

Yeasts have historically been a powerful model system to understand the control of the cell cycle in animals. However, it has become clear that many otherwise conserved cell cycle regulators have been lost and independently evolved in the fungal lineage [2,3,5355]. Thus, we sought to investigate the cell cycle control in another organism within opisthokonts that could potentially retain the cell cycle regulation program before it diversified in animals. We focused on Capsaspora owczarzaki (hereafter Capsaspora), a species more closely related to animals than yeasts, easy to culture, and for which good genomic resources are available [5659]. This amoeba has a life cycle that includes three distinct stages that differ both in their morphology and transcriptional and proteomic profiles: amoebas with filopodia that proliferate in adherent cultures, an aggregative multicellular stage in which cells produce an extracellular matrix, and a cystic form that lacks filopodia [6062]. Moreover, Capsaspora has a compact, well-annotated genome, with many homologs to animal genes [59]. With recent advances that allow transfection in the laboratory [63], Capsaspora is becoming a tractable model organism.

In this work, we have established a protocol to synchronize cell cycle progression in Capsaspora and have characterized its cell division and transcriptional profile across the entire cell cycle. We found that globally, the periodic transcriptional program of Capsaspora is enriched in genes that date back to eukaryotic origin, and it resembles human cells more than the periodic transcriptomes of yeasts. Out of four human cyclin types, Capsaspora contains homologs of cyclins A, B, and E. We found that these three cyclins are transcriptionally regulated during the cell cycle and have a conserved temporal order and cell cycle stage with human cells. In contrast, Capsaspora only contains one ancestral copy of the CDK, which likely form complexes with all of the Capsaspora cyclins. We also found that orthologs of many other cell cycle regulatory genes have a conserved timing of expression compared with animal cells. Our findings suggest that the cyclin-CDK system of animals evolved gradually, through an intermediate stage where one single CDK was able to interact with several cyclins at distinct stages of the cell cycle. Thus, while expansion and subfunctionalization of the cyclins found in animals occurred earlier throughout eukaryote evolution, we hypothesize that the expansion of metazoan cell cycle CDKs occurred concomitantly with the emergence of animals.

Results

Synchronization of cell cultures in Capsaspora

Synchronization of cell cultures is a basic experimental tool required to study the cell cycle [64]. Cell synchronization methods include temperature-sensitive strains, elutriation, cell sorting and commercially available inhibitors that arrest the cell cycle. Arrest and release approaches have previously been used to assess cell cycle progression in several organisms [44,47,65,66]. Hydroxyurea, a widely used S-phase inhibitor in yeast cells [67], was already shown to inhibit cell proliferation in Capsaspora cultures during the adherent cell stage [62]. Therefore, to check if cell cycle inhibition occurred before entering S phase and was reversible, we treated Capsaspora adherent cultures with hydroxyurea and assessed DNA content by flow cytometry. Upon hydroxyurea treatment, cells exhibited 1C DNA content, indicating arrest in G1 phase (Fig 1A). Upon wash and release into fresh media, we observed synchronous progression through the cell cycle as assessed by DNA content (Fig 1C). This indicates that hydroxyurea inhibits the cell cycle in S phase in Capsaspora and that its effect is reversible.

Fig 1. Experimental setup for cell cycle synchronization in Capsaspora.

Fig 1

A: Effect of Hydroxyurea in Capsaspora cells. Control cells were treated with an equal volume of distilled water. HU treated cells were sampled every 2 hours, and a major decrease in 2C cells is observed after a minimum of 8 hours. B: Experimental layout used in this study. Two cell cultures growing independently for several generations were grown in fresh medium and kept in HU for a lapse of fifteen hours. After that, cells were released from HU and harvested every 45 minutes for 11 hours. Three different samples were taken from each culture at each time point. C: DNA content profile of synchronized Capsaspora cultures at representative time points of the whole experiment.

To measure the timing of cell cycle stages in Capsaspora, we treated two independently propagated cultures of Capsaspora adherent proliferative cells with hydroxyurea, and we later released them into fresh medium. Samples were taken at 45-minute intervals, starting from 2 hours after release, taking a total of 16 time points that were analyzed using flow cytometry (Fig 1B). Following release, cells spent approximately 1.5 hours duplicating their DNA content, and after 8 hours from release a G1 peak appeared again, indicating completion of the cell cycle (Fig 1C). These observations were reproduced in the two replicates. At later time points, we noticed co-occurrence of 1C and 2C peaks. This may be due to some cells progressing through the cell cycle more rapidly than others [68], causing loss of synchrony, or due to an irreversible arrest in a fraction of the cells upon HU treatment [69]. Based on our observations of DNA content, Capsaspora synchronized cultures took ten hours approximately to double in cell density (Fig 1C), a time slightly slower than non-treated cultures of Capsaspora (S1 Fig). Nevertheless, our time course encompasses a complete round of the cell cycle, as we observed an increase in 1C at later time points.

Dynamics and morphology of cell division in Capsaspora

To characterize the dynamics of cell division in Capsaspora, we used time-lapse microscopy in synchronized cells. In parallel, we analyzed synchronized cells for DNA content by flow cytometry and characterized the cell morphology during cell division using fluorescence microscopy. Out of a total of 100 mitotic cells observed by live imaging in the whole experiment (Fig 2A), the highest fraction underwent cytokinesis at approximately 10 hours (Fig 2C). Cells seemed to round up and slightly detach from the plate surface while retaining their filopodia (Fig 2A, S1 Video). This phenomenon has been previously characterized in other eukaryotic cells lacking a rigid cell wall, such as animal cells or Dictyostelium amoeboid cells [7077]. Cells took an average of 3 minutes to completely undergo cytokinesis (Fig 2A, S1 Video), measured as the time from rounding up to the splitting of two daughter cells. As shown in Fig 2D, the measured area of daughter cells is roughly the same, suggesting that cell division is symmetric and yields two equally sized cells.

Fig 2. Cell division in Capsaspora.

Fig 2

A: Time lapse of live imaging of a synchronous culture. Numbers indicate minutes since round up, with T0 still not rounded. White arrows indicate a cell dividing during the time lapse. Scale bar: 5μm. B: Fluorescence immunostaining of DNA (cyan) and Tubulin alpha (green) in Capsaspora synchronous cultures at different stages of cell division. White arrows indicate structures with a high concentration of tubulin. White dashed outline indicates cell perimeter. Scale bar: 5μm. C: Histogram depicting the number of cells at the moment of division in different times of the time lapse. Range goes from 7h to 11h. D: Stacked bar plot showing the normalized, relative cell area for each daughter cell in a total of 101 events of cell division.

To investigate the morphology of mitotic cells, we stained tubulin and DNA. On each cell, we observed one dot of dense concentrations of tubulin, from which microtubules emanate (Fig 2B, white arrows). These dots duplicated and remained close, first associated with the nucleus and then surrounding densely packed DNA. A central, thicker spindle emerged and grew as DNA separated and moved to opposite poles of the dividing cell. A similar phenomenon has been described for Dictyostelium [78]. These results came as a surprise, as a previous study has reported that Capsaspora lacks a centrosome and SPD-2/CEP192 homologs [79]. We further confirmed using BLAST best reciprocal hit that core human centrosomal proteins, as well as yeast spindle pole body proteins, are absent in several unicellular holozoan species, including Capsaspora (S2 Fig). These results suggests that Capsaspora mitotic spindle might be organized without a microtubule organizing center (MTOC) [80], or that it possesses an independently evolved MTOC, such as in yeast [81].

Detection of periodically expressed genes during the Capsaspora cell cycle

In many cell types, cell division cycles are accompanied by a transcriptional program of periodic gene expression over time. To understand the transcriptome dynamics during the cell cycle of Capsaspora, we performed time-series RNA-seq experiments. We used RNA extracts from the same two biological replicates as in the flow cytometry assay and sequenced them using Illumina HiSeq v4. We processed the sequencing reads using Kallisto [82] (S3A Fig, S4 Text). Pearson correlations by gene expression profiles showed that time points are grouped according to the temporal order of sampling (S4 Fig). This indicates that gene expression is not shifted over time and was reproducible between the two replicates (Fig 3A). To detect periodicity patterns in gene expression, we applied two algorithms, JTK_CYCLE [83] and RAIN [84], on an average dataset of the two replicates where non-expressed genes were filtered out (S3B Fig). We assigned two ranks to every gene according to the p-values calculated by JTK_CYCLE and RAIN (Fig 3B), and assigned the final periodicity rank as the sum of JTK and RAIN ranks. We applied a conservative cutoff to identify genes that are undoubtedly periodically transcribed by taking the top 800 genes ranked within the top 2000 ranking for each independent dataset (Fig 3B) (S3B Fig). This cutoff corresponds to 10% of the total number of genes in Capsaspora, a fraction similar to those observed in other species [43,44,47,85]. Although false negatives with higher ranks might have been discarded due to our conservative approach, we confirmed that top-ranked genes showed oscillatory behavior by visual inspection. We manually included Capsaspora Cyclin A (CAOG_04719T0) [4,59] (see below) to the list of periodic genes despite ranking in position 1916, as it has a periodic expression profile (See below).

Fig 3. Detection of periodic genes in Capsaspora.

Fig 3

A: Pearson correlation for the normalized expression level of every gene between replicates. Bright red indicates positive correlation, and dark purple indicates negative correlation. B: Spearman correlation between the two methods used to detect cell cycle regulated genes in Capsaspora. Scatter plots depicting the rank assigned for every gene by the JTK_CYCLE and RAIN on an average dataset of the two time-series replicates. These two algorithms rely on different approaches to finally assign, for every gene, a p-value interpreted as the probability that it can be considered periodic. For its proper functioning, we set the two algorithms to look for periodic behavior in a lapse of 11 to 13 hours, with time lapses of 0.75 hours. We assigned two ranks to every gene according to the p-values calculated by JTK_CYCLE and RAIN. Each dot represents a gene expressed in the time series. Colored dots represent the 801 genes that were finally taken as periodic according to our criteria. C: Pearson correlation for the top 801 cell cycle regulated genes, also based on normalized gene expression level. See Fig 4 for more details. D: Principal coordinate analysis on the set of 801 cell cycle regulated genes based on normalized gene expression level. Every dot represents a time point in the experiment.

Expression of periodic genes correlates across replicates more strongly than non-periodic genes (Fig 3C) (S5A Fig). We also observed a strong correlation between initial and late time points (Fig 3C), suggesting that the cultures indeed completed the entire cell cycle despite the loss of synchrony. A principal coordinate analysis using data for the top-ranked periodic genes retrieved a grouping of time points that resembles a circle with two components explaining around 70% of the total distance (Fig 3D, S5B Fig), and a similar layout is obtained on a t-SNE projection of periodically expressed genes (S6C Fig). The results from these analyses indicate that there is a set of periodically transcribed genes during the cell cycle of synchronous Capsaspora cells. This set of genes represents the periodic transcriptional program of Capsaspora (S5 Text).

Gene expression is clustered in periodic waves during the cell cycle

The cell-cycle-associated transcriptional program responds to the requirements of the cell at a given moment. For example, in many cell types, genes necessary for DNA replication or mitosis are transcribed only at the time of their biochemical activity. The detection of periodic genes in Capsaspora prompted us to classify them into temporal clusters, by centering their expression profiles to the mean and grouping them using hierarchical clustering based on a dissimilarity matrix by Euclidean distance (Fig 4A). Five clusters were detected according to the similarity in expression profiles over time (Fig 4A, S6A and S6B Fig), and we obtained very similar results by using k-means clustering (S7 Fig). We then associated these gene clusters to the cell cycle stage during the peak of expression, according to our DNA content and microscopy data: the G1/S cluster, S cluster, G2/M cluster, M cluster, and G1 cluster. Next, we calculated gene ontology (GO) enrichment for every cluster against the whole periodic transcriptional program using Ontologizer [86] Parental-Child-Union calculation (Fig 4B, S6 Text).

Fig 4. The periodic transcriptional program of Capsaspora.

Fig 4

A: heatmap of gene expression level depicting the five main clusters detected by Euclidean distance hierarchical clustering. Clusters were rearranged to visually represent their expression peaks over time. B: Top ten enriched gene ontology terms for every cluster shown in A. We considered an enrichment as significant when Bonferroni corrected p-value was lower than 0.05. For the full list of enriched GO terms, see S6 Text.

The G1/S cluster contains 194 genes peaking in the initial time points, from 2 to 3.5 hours after release. Genes found here exhibit the largest differences in gene expression between time points and are enriched in GO terms related to DNA replication, deoxyribonucleotide biosynthesis, and chromosome organization. There is also enrichment in the GO term “response to stress”, suggesting an effect of the treatment with hydroxyurea [68,69]. The small cluster assigned to S/early G2 contains 36 genes peaking between 3.5 to 5.75 hours enriched in the GO term “nucleosome binding” and includes several histone genes.

In the G2/M cluster, we found 176 genes with the peak of expression at 6.5–7.25 hours post-release. This cluster is enriched in the GO term “non-coding RNA metabolic process”, and contains genes related to tRNA maturation such as RTCB, DDX1 [87], and tRNA ligases. It has been previously reported that tRNA synthesis can increase during the cell cycle in several systems [8890]. To our knowledge, however, there is still no link reported between tRNA modification and progression through the cell cycle.

The M cluster is the largest one in the dataset, with 241 genes peaking between 9.5 and 11 hours. Genes reach the highest expression during time points when the cells enter mitosis, reaching a plateau which reflects the partial asynchrony of the cells at the time. This cluster is enriched for genes annotated with chromosome segregation, organelle fission, and diverse cytoskeletal components like spindle proteins and myosins. All these GO terms can be linked to mitotic cell division.

The G1 cluster has 157 genes. Genes in this cluster show higher expression levels in both the late and initial time points of the experiment. Many GO terms enriched in this cluster are related to the mitochondrion and diverse metabolic processes that indicate an increase in cell metabolism as the cell progresses through the cell cycle [91].

Taken together, the GO enrichment analyses show that gene expression clusters contain conserved genes involved in the cell cycle in Capsaspora.

Conserved temporal order of cyclin and CDK expression in Capsaspora

In eukaryotes, the cell cycle events are regulated by cyclins in complex with CDKs. While the cyclin and CDK gene families are broadly conserved across eukaryotes [2,3], some of the subfamilies are lineage specific and have radiated differently. In budding yeast, two types of cell cycle cyclins can be found: cyclin B and Cln-type cyclins. Both types bind to one single CDK, Cdk1 [16]. In animals, this ancestral CDK expanded and specialized [4] resulting in multiple cyclin-CDK partners involved in different phases of the cell cycle: CDK2 binds to cyclins E and A at the onset and later stages of S phase [13], cyclin B binds to CDK1 in mitosis [14], and CDK4 and CDK6 bind to cyclin D types during G1 [92]. To our knowledge, how cyclin-CDK binding partnership grew in complexity remains unclear.

To provide some insights into the evolution of cyclin-CDK binding partnership, we used our temporal gene expression dataset to infer the timing of cyclin-CDK activity during the cell cycle in Capsaspora. Due to inconsistencies in published work [4,59], we first revised the classification of cyclin and CDK genes found in Capsaspora by phylogenetic profiling using a complete taxon sampling for Holozoa (the clade comprising animals and their closest unicellular relatives) and validated the gene previously reported as Capsaspora CDK1 [59] by Sanger sequencing and transcriptomics (see Methods) (S8 and S10 Text, S8, S9 and S10 Figs). Despite the limited phylogenetic resolution, Capsaspora and other unicellular holozoan sequences appeared in earlier branching positions to the metazoan Cyclin A, B and E clades, this being compatible with Capsaspora having orthologs of these cyclins (S8 Fig). The phylogeny does not suggest the presence of a Cyclin D ortholog in Capsaspora. In the CDK phylogeny (S9 Fig), sequences from Capsaspora and other filastereans branch as a sister-group to the metazoan CDK1 clade (100% of UFBoot), whereas the branching of sequences from other unicellular holozoans is more uncertain concerning the CDK1 and CDK2-3 metazoan clades. From this, we envision two possible evolutionary scenarios. In a first scenario, an ancestral duplication of CDK1-3 into CDK1 and CDK2-3 occurred in a common ancestor of Holozoa. As most unicellular holozoans have only one sequence within the CDK1-3 clade, this would imply differential losses of either CDK1 or CDK2-3 in Ichthyosporea, Filasterea and Choanoflagellatea, and Metazoa conserving both paralogs. Despite Salpingoeca rosetta has two sequences within the CDK1-3 clade, both paralogs are likely to descend from a duplication event occurred in the Choanoflagellatea lineage, with Monosiga brevicollis losing one of the two copies. In a second scenario, the duplication would have occurred in the lineage leading to Metazoa, but the limiting phylogenetic signal would not have allowed reconstruction of the real phylogenetic pattern of the CDK1-3 clade. We find this scenario more parsimonious as it does not require any gene loss, whereas the other involves independent losses of an hypothetical paralog in all the holozoan lineages except Metazoa. This scenario is also supported by [2], where holozoan CDK1/2/3 is placed with plants CDKA. Thus, we propose that the subfunctionalization of CDK1-3 is a specific feature of Metazoa, with Capsaspora retaining the ancestral CDK1-3 gene instead of having a CDK1 ortholog as previously reported [59].

We report a clear temporal ordering of expression of the putative Capsaspora Cyclins A, B, and E (Fig 5A). Cyclin E belongs to the G1/S cluster, cyclin A clusters together with S-phase genes, and cyclin B is in the M cluster, peaking at mitosis (Fig 4) together with Capsaspora CDK1-3 (Fig 5B), although we found the CDK1/2/3 transcript expressed at high levels also during the rest of the cell cycle (S11B Fig). We also found periodic expression in G2 of a Capsaspora ortholog of the Cyclin G/I subfamily, with a known role as a G2/M repressor in human cells (Kimura et al., 2001), and a Capsaspora cyclin of uncertain phylogenetic relationship (CAOG_01199) (S11A Fig). We further confirmed the dynamic expression of Capsaspora’s CDK1/2/3, Cyclin B and Cyclin E using RT-qPCR (S11C Fig). In conclusion, our results suggest that cyclins A, B and E follow the same temporal order and cell cycle phases as cyclins in human cells.

Fig 5. Dynamics of the cyclin-CDK system and other cell cycle regulators in Capsaspora.

Fig 5

A: Gene expression profile of the Cyclin A, B, and E genes found in Capsaspora. B: Gene expression profile of the Capsaspora orthologue of CDK1/2/3 found by phylogenetic analyses (see S9 Fig). Normal and dashed lines indicate replicates 1 and 2, respectively. C: Gene expression level of Capsaspora orthologues of several G1/S regulators in animals. D: Gene expression level of Capsaspora orthologues of several G2/M regulators in animals. Genes in C and D as described by [32,44,45,93]. A full list is depicted in S12 and S13 Text.

The Capsaspora periodic transcriptional program includes conserved eukaryotic genes and is similar to that of animal cells

Besides the cyclin-CDK system, other regulators are periodically expressed during the cell cycle [32,44,45]. To characterize the periodic expression program in Capsaspora in comparison to other species, we identified what are the Capsaspora orthologs of genes with known roles in regulating the cell cycle in other species. We did so by using OrthoFinder [94] (table ‘Orthofinder’ in S8 Text and using a list of one-to-one Capsaspora-human orthologs from a set of phylogenies of Capsaspora [61]. From these sources, we identified which periodic human genes with known functions in the cell cycle (as described in [32,44,45,93]) have also a periodic ortholog in Capsaspora. We found that numerous DNA replication genes are upregulated in the G1/S cluster in Capsaspora, including DNA polymerase subunits, replication factors, and proteins CDC45 and PCNA (Fig 5C). We also found periodic expression of the protein Retinoblastoma (Rb), one of the main regulators of entry into S phase in many eukaryotes [95]. Capsaspora Rb is temporally coexpressed with E2F7, a member of the E2F family of transcription factors known to act as a transcriptional repressor of the cell cycle [96,97] (Fig 5C). Among human genes that peak in mitosis, we found Capsaspora orthologs of Aurora Kinase A (AURKA), protein regulator of cytokinesis 1 (PRC1) and the anaphase-promoting complex (APC) subunit UBE2S expressed in the G2/M cluster (Fig 5D). In human cells, AURKA regulates the assembly of the centrosome and the mitotic spindle [98], mitotic cyclins and cohesins are degraded by the APC [1], and PRC1 regulates cytokinesis by cross-linking spindle midzone microtubules [99]. Although we did not find regulatory APC subunits CDC20 and CDH1 [100,101] among periodically expressed genes in Capsaspora, the UBE2S peak in mitosis suggests that APC activity might also be transcriptionally regulated during the cell cycle in Capsaspora. During M phase, we also observed upregulation of different kinesins, microtubule motors with conserved function in the mitotic spindle, and centromere proteins; a more detailed overview is provided in S12 Fig. We also identified Capsaspora periodic genes belonging to the same orthogroups as other cell cycle regulators in human cells, but without a one-to-one ortholog relationship (S13 Fig).

In addition to the examples above, we were interested in the similarities of the periodic transcriptional program of Capsaspora with those of other eukaryote species. First, to understand the evolutionary origin of the periodic genes found in Capsaspora, we calculated gene age enrichment for every cell cycle cluster. We assigned a gene age to the orthogroups by Dollo parsimony [102], resulting in ancient genes present in all species and younger genes found only in Capsaspora (see Methods). We compared the gene age enrichment ratios for non-periodic genes and the five clusters separately with the gene age of the whole transcriptome of Capsaspora. Three of the clusters of periodic genes presented significant enrichment in pan-eukaryotic genes (Fig 6A, S14 Text). Our data thus shows that a large fraction of genes in the periodic transcriptional program of Capsaspora belong to gene families originating early in eukaryotic evolution.

Fig 6. The Capsaspora periodic transcriptional program has more resemblances to that of animal cells.

Fig 6

A: (Left) Phylogenetic tree of Capsaspora where colored nodes depict the different gene ages considered in this study. We used a database of 28 species of eukaryotes to infer groups of orthologs that were used to determine the gene age in Capsaspora. (Center) Gene age stratification profiles of the whole transcriptome of Capsaspora, as well as the periodic transcriptional program. (Right) Heatmap depicting gene age enrichment or depletion on each cluster of periodic genes in Capsaspora (see Fig 4), compared to non-periodic genes. Color scale indicates percentage of enrichment, and asterisks indicate the level of significance (Fisher’s Test). B: Heatmap showing periodic orthogroups in common in the tree of species used in the comparative analysis. Every column represents a group of orthologs, which can be present, absent, or contain at least one periodic gene in each species. C: Venn diagrams indicating how the binomial tests were calculated for each pair-wise comparison of species, e.g. Capsaspora and Homo sapiens HeLa cells. White circles indicate orthogroups from each species. The intersection between these represents the orthogroups in common, C. p1 and p2 areas represent periodic genes of each species within C. Null expectation probability (Aexp) is calculated as the product of p1 and p2 divided by C. P-values of all the binomial tests are provided in S16 and S17 Text. D: Bar plots indicating the amount of shared periodic orthogroups and/or periodic one-to-one orthologues between pairs of cell types or species. P-values of all the binomial tests are provided in S17 Text.

Next, we compared our dataset of Capsaspora periodic genes with datasets of cell cycle synchronized cells of different organisms, namely three different cell types of Homo sapiens (Hela Cells, U2OS cells, and foreskin primary fibroblasts) [32,43,46], S. cerevisiae [48], S. pombe [85], and Arabidopsis thaliana [49]. For each dataset, we took the published lists of periodic genes and corrected for the number of genes in each species (S15 Text). We set a threshold of less than 10% of genes to be periodic for human cells and the yeasts, and less than 5% for A. thaliana. Thus 1790 periodic genes were identified in HeLa cells, 1245 in U2OS cells, 461 in fibroblasts, 592 in S. cerevisiae, 499 in S. pombe, and 1060 in A. thaliana datasets. We found 1925 orthogroups that contained at least one periodic gene from either of the datasets (Fig 6B), and named these “periodic orthogroups”. Of these, one third had orthologs in all five species.

We first computed the number of periodic genes shared between pairs of species (defined by their presence in the same orthogroup). Overall, all species share a small number of periodic genes (S16 and S17 Text), with the number of genes being highest for Capsaspora with H. sapiens cell lines (167, 81 and 99 periodic orthogroups with HeLa cells, U2OS cells, and fibroblasts, respectively) rather than yeasts or A. thaliana (Fig 6D, S15 and S16 Text). Still, the periodic expression of the majority of the genes is not shared between species, consistent with former findings of 2% to 5% of periodic genes shared between different organisms [51]. This indicates that the periodic transcriptional program is divergent both between species and even between different cell types within an organism.

Despite the low numbers of periodically expressed genes in common, we wondered whether the periodic transcriptional program in each species indeed evolved independently, meaning that the pairs of genes that share the periodic expression between species are observed only by chance. To that end, we calculated the expected number of shared periodic orthogroups by chance as the product of ratios of periodic orthogroups from each species within their orthogroups in common (Fig 6C). We detected that, for most species, the number of shared periodic genes is higher than by chance, especially for Capsaspora and the core cell cycle gene set of H. sapiens (defined in [32]) (Fig 6D, S16 and S17 Text). We found the same when comparing periodic one-to-one orthologs [61] (Fig 6D), when applying a cuttof of 20% to the periodic transcriptional program of Capsaspora, or when defining periodic genes on every species using the same method that we applied to Capsaspora (S13 and S14 Figs, S16 and S17 Text). Likewise, we found similar results when using an expanded dataset of 20% of the total transcriptome Therefore, these findings are robust with respect to the methods used to identify periodically expressed genes and to assign orthology relationships. Thus, although the cell cycle periodic expression program largely evolves fast and independently, our data suggest there is a core set of genes of conserved oscillatory expression during the cell cycle (Fig 6B). This set comprises 55 orthogroups that are periodic in the five species. These orthogroups contain genes such as cyclins and histones, and are enriched in common functions such as protein phosphorylation, DNA-binding protein, and cell division (S12 Fig) (S18 and S19 Text) (See Methods).

Overall, our cross-species comparison of the periodic gene expression programs revealed that the Capsaspora periodic gene expression program is more similar (in terms of number of periodic orthologs) to human cells that to current unicellular model systems for the cell cycle. Furthermore, including a new species in the global analysis, we discovered a previously unappreciated core set of genes for which periodic expression is deeply conserved.

Discussion

In this study, we have used synchronized Capsaspora adherent cells to gain insight into key aspects of the cell cycle, such as cell division and periodic gene expression, in a unicellular relative of animals. Previously, the cell cycle has been studied in only a handful of species due to the inability to obtain synchronous cell cultures. With this synchronization protocol, the cell cycle of a closer relative of animals can be studied in cultures that can be synchronized from DNA replication to cell division.

Our experimental setup made possible to characterize mitotic cell division in Capsaspora, which we found relies on microtubule-based structures, as previously described in other eukaryote species [103]. Our observations suggest the presence of a putative non-centrosomal microtubule organizing center (MTOC) in Capsaspora, which raises new questions about the mechanisms of cell division in this species. As non-centrosomal MTOCs have independently evolved in many different species [104], it may well be that Capsaspora has a non-centrosomal, independently evolved MTOC, or that their microtubules are able to self-arrange, as previously shown in other systems [80].

Synchronization of Capsaspora cell cultures allowed us to study transcription during the cell cycle using RNA sequencing. We identified five waves of gene expression across time, with most genes being expressed in the G1/S transition and in mitosis. As in previously studied organisms, these waves of transcription can be grouped in clusters containing genes related to the main events of the phases of the cell cycle. The periodic transcriptional program of Capsaspora is enriched in genes that emerged at the onset of eukaryotes, showing that the cell cycle relies in numerous genes, such as DNA replication proteins and cytoskeleton components, which are common to all eukaryotes due to their roles in fundamental cellular processes. Although transcriptional activity during the cell cycle is present in numerous species and cell types [51], the genes affected by cell-cycle-regulated transcription are divergent between distantly related species, likely due to the fact that transcriptional regulation adapts to the environment and lifestyle of each particular cell type. Our observations suggest that this occurs largely by old genes gaining and losing periodic regulation, rather than new species-specific genes evolving to be regulated during the cell cycle. This is consistent with Jensen et al.’s observations that periodicity in complex activity can evolve rapidly in different lineages by recruiting different partners of the same complex, which preserves the periodic regulation of the entire complex [51]. Still, in contrast to this previous analysis with a more limited set of species [51], our analysis clearly revealed a core set of genes of which the periodic regulation is deeply conserved among eukaryotes.

From the temporal order of gene expression of Capsaspora cyclins, we conclude that cyclins A, E, and B follow the same order and are associated with the same cell cycle stage as in H. sapiens cells. In contrast to human cells, where these cyclins bind their respective partner CDKs, Capsaspora only possesses one ancestral CDK1-3, which, although periodically expressed with a peak in M-phase, exhibits high transcript levels throughout the cell cycle. Due to this, we propose that CDK1-3 might be the binding partner of cyclin A, B, and E in Capsaspora and that it might be involved in all phases of the cell cycle (Fig 7). Nevertheless, in the absence of biochemical data, we cannot exclude the possibility that Capsaspora cyclins A and E bind other non-canonical CDKs. Interestingly, in knock-out mice where all CDKs except for CDK1 were deleted, all cyclins were also found to bind CDK1 [105], which suggests that animal cyclins A, B and E are also able to bind CDK1.

Fig 7. A model of the dynamics of the Cyclin/CDK system in Capsaspora.

Fig 7

Bold lines indicate cyclin levels and dashed lines indicate CDK levels across the cell cycle. Independent phylogenetic studies suggest that a diversified set of cell cycle cyclins A and B existed prior to the last common ancestor of eukaryotes (LECA). Some of these components were secondarily lost and independently expanded in different eukaryotic lineages, such as in fungi (which includes S. cerevisiae). Based on our phylogenetic and transcriptomic analysis, a likely scenario is that several cell cycle cyclins may be binding to a single CDK that is not transcriptionally stable in Capsaspora. This suggests the expansions of cell cycle cyclins predate the expansion of cell cycle CDKs, which later acquired specific binding to cell cycle cyclins in animals.

Based on phylogenies made in S8 and S9 Figs (S8 and S9 Figs), and phylogenies previously made by [2], the last eukaryotic common ancestor (LECA) likely already contained cyclins A and B, and a single cyclin-dependent kinase. In contrast, deep-branching eukaryotic lineages do not contain cyclins D and E (note that although named as cyclin D, Archaeplastida cyclin D is phylogenetically related to metazoan cyclin G/I in [2] and our analysis)(S8 and S15 Figs). In the fungal lineage, well-studied organisms such as S. cerevisiae secondarily lost some of the components of the system. In Holozoa (the lineage that contains animals and their closest unicellular relatives), the ancestral cyclin-CDK system underwent further expansion and specialization, which in humans contains cyclins A, B, D and E forming discrete complexes with multiple CDKs acting at distinct cell cycle stages. Although the molecular biology of the cell cycle has mostly been studied in human cell lines, phylogenetic data suggest that the human cyclin-CDK system is conserved in all animals [4]. Unicellular Holozoa (which include ichthyosporeans, filastereans and choanoflagellates) contain only the ancestral CDK, but already contain cyclin E in addition to the other two ancestral cyclins. However, cyclin D also appears to be an animal innovation. Importantly, our work in Capsaspora shows that the cyclins A, B and E are already present during the same cell cycle phases as human counterparts.

Given these data, a likely evolutionary scenario is that cyclins underwent duplication and subfunctionalization before the emergence of animals, acquiring regulatory roles during distinct cell cycle phases while binding to the unique CDK. This evolutionary intermediate state is present in Capsaspora. During the emergence of animals, CDKs underwent expansion and subfunctionalized to bind specific cyclins, forming discrete, active complexes at distinct stages. This suggests that there was a gradual evolution of the cyclin-CDK control of the cell cycle in the holozoan lineage during the emergence of animals.

Materials and methods

Cell cultures and culture synchronization

Capsaspora cells were incubated at 23°C in ATCC medium 1034 (modified PYNFH medium). Two cultures of Capsaspora independently propagated (coming from a culture split two passagings before) at 30–50% confluency were treated using 10mM Hydroxyurea (Sigma Aldrich, Saint Louis, MO, USA, #H8627) in culture medium, and left incubating for approximately 14 hours. After treatment, cells were washed by: (i) centrifuging at 5000G for 5’, (ii) discarding the supernatant, (iii) resuspending in 15ml of fresh medium, (iv) centrifuging at 5000G for 5’, (v) discarding supernatant, (vi) eluting in fresh medium for a final cell density of ~1 million cells/ml. From this, cells were seeded in 5ml flask cultures for time-point sampling. Samples were collected by scraping and washing two hours after release, and from there on every 45 minutes until thirteen hours. A total of sixteen time points were taken, constituting a time window comprising one event of genome duplication and one mitotic division.

We also tested different concentrations and incubation times of hydroxyurea, nocodazole (Sigma-Aldrich, #M1404), and aphidicolin (Sigma-Aldrich, #A0781). Only 10mM hydroxyurea for longer than thirteen hours showed arrest of the cell cycle, while Nocodazole had no observable effect by DNA content measurement, and the rest ruined the samples due to insolubility of the compound.

Doubling time experiment

Doubling time of Capsaspora was measured using optical density (OD600). Briefly, three independent cultures of Capsaspora were seeded at a cell density of ~1M cells/ml. Every six hours, cells were scraped and optical density (OD600) was measured using an Eppendorf BioPhotometer model #6131 (Eppendorf Corporate, Hamburg, Germany, EU) with Capsaspora medium as a blank. Note that, due to time constraints, time point 18h was not measured. DNA content was also measured in parallel (Methods, see below). For each replicate, OD600 data points were fitted to a logarithmic curve. The reported doubling time was estimated as the mean doubling time calculated from the different fitting curves from each replicate.

DNA content measurement

Cells were washed in PBS and fixed in 70% ethanol in PBS, then incubated in RNAse A (Sigma-Aldrich, #R6148) (one volume in three volumes of 1xPBS) for 24 hours at 37 °C. Cells were then incubated in a final concentration of 20μg/ml propidium iodide (Sigma-Aldrich, #P4170-25MG) for 72 hours at 4 °C. Samples were analyzed by flow cytometry using a BD LSR Fortessa analyser (Becton Dickinson, Franklin Lakes, NJ, USA). SSC-A and FSC-A were used to detect populations of stained cells. Single cells were gated by FSC-H and FSC-A. An average of 10,000 events per sample were recorded. PI-positive cells were detected using a 561 nm laser with a 610/20 band pass filter (red fluorescence). To estimate the cell count, Texas Red-A was plotted as histograms using FlowJo 9.9.3 (FlowJo LLC, Ashland, OR, USA).

Cell microscopy and image analysis

Microscopy pictures were taken using a Zeiss Axio Observer Z.1 Epifluorescence inverted microscope equipped with Colibri LED illumination system and Axiocam 503 mono camera (Carl Zeiss microscopy, Oberkochen, Germany). A Plan-Apochromat 100X/1.4 oil objective (Nikon Corporation, Tokyo, Japan) was used for imaging fixed cells. For the live imaging, we used an EC Plan-Neofluar 40x/0.75 air objective (Carl Zeiss microscopy).

Image analysis was done using ImageJ software [106]. For fixed cells, we used the oval selection tool to draw the contour of each cell and measured cell perimeter. As cells are spherical, we computed cell area using ImageJ. We estimated the relative cell area of every pair of daughter cells by dividing each measurement by the sum of the two daughter cells areas. All the calculation and data plotting was done in R Software ver. 3.4.4 [107].

RNA isolation and sequencing

Time point samples were washed in 1xPBS, poured in Trizol, and frozen at -80°C. Total RNA was purified using Zymo RNA miniprep kit (Zymo Research, Irvine, CA, USA, #R2050). mRNA libraries were prepared using the TruSeq Stranded mRNA Sample Prep kit (Illumina, San Diego, CA, USA, Cat. No. RS-122-2101). Paired-end 50bp read length sequencing was carried out at the CRG genomics core unit on an Illumina HiSeq v4 sequencer, with all samples from the same replicate being pooled in the same lane.

Capsaspora adherent cultures cDNA was obtained by RT-PCR using SuperScript III Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA, #18080044) following the manufacturer’s instructions. PCR was performed using Phusion High-Fidelity DNA Polymerase (New England Biolabs, Ipswich, MA, USA, #M0530L) following the manufacturer’s instructions.

Transcriptomic analysis

RNA reads were mapped using Kallisto v0.43.1 [82] using default parameters onto a set of the largest isoforms of the Capsaspora transcriptome [62]. The resulting time-series transcriptome in transcript-per-million (tpm) units is available in S4 Text. We retrieved only the transcripts whose average expression level is above 1 tpm in the whole time series.

Gene expression level was normalized by subtracting the mean over time and dividing by the standard deviation. Normalized datasets were clustered according to their Spearman correlation values using hierarchical clustering (R gplots library [107,108]). All the supporting information and raw datasets can be found in FigShare: https://figshare.com/s/4d642c9854efe6d879a7.

Identification of periodically expressed genes

Periodic genes were detected in Capsaspora by ranking using JTK_CYCLE [83] and RAIN [84] on the time-series transcriptomes and an average of the two replicates. We set JTK_CYCLE parameters to periods = 14:16 time points (please note that they do not correspond to hours) and sampling interval = 0.75, and ranked every gene by their BH.Q value. We set RAIN parameters to period = 16 and delta = 0.75, and ranked every gene by their Benjamini-Hochberg corrected p-value. We set a cutoff of the genes ranked below 2000 on each separate replicate and simultaneously ranked below 800 in the average dataset (see S3 Fig, S5 Text).

Clustering analysis

Periodic genes were hierarchically clustered according to similarity of gene expression over time (averaged between two replicates), and clustered by k-means clustering [107] using standard parameters and k = 5. Agreement between clustering methods was calculated as the number of genes belonging to the same pair of clusters divided by the size of the smallest cluster in the pair. Cluster membership can be found at S5 Text.

Calculation of Gene ontology enrichment

Gene ontology enrichment was calculated using Ontologizer [86] using the–c “Parent-Child-Union”–m “Bonferroni” options. Bonferroni-corrected p-values were taken as significant when below 0.05.

Identification of microtubule organizing center proteins in unicellular Holozoa

We used a list of MTOC proteins from [109,110] to retrieve the respective H. sapiens and yeast sequences from UNIPROT. We used BLAST+ v2.3.0 [111,112] best reciprocal hit with parameter -evalue 10e-5 using this list as a query to identify putative homologous proteins in the proteomes of Salpingoeca rosetta (Sros), Monosiga brevicolis (Mbre), Ministeria vibrans (Mvib), Capsaspora owczarzaki (Cowc), Creolimax fragrantissima (Cfra), Sphaeroforma arctica (Sarc), Corallochytrium limacisporum (Clim), S. cerevisiae (Scer), Neurospora crassa (Ncra), and Dictyostelium discoideum (Ddis). Hits were considered significant when the e-value score was below 10E-5 for both searches. Sequences and BLAST matches can be found in S1, S2 and S3 Text. All the supporting information can be found in FigShare: https://figshare.com/s/4d642c9854efe6d879a7.

Phylogenetic classification of CDKs and Cyclins from early-Holozoa taxa

Annotated sequences of cyclins and CDKs from H. sapiens and S. cerevisiae were retrieved from Cao et al. [4] and Swissprot [113], and A. thaliana sequences were taken from [113115]. These sequences were used as queries to detect potential CDKs and cyclins orthologues in our dataset (S7 Text) using BLAST+ v2.3.0 [111,112]. Those sequences that aligned were BLASTed against a database including all proteins from H. sapiens, S. cerevisiae and A. thaliana. We only included in our phylogeny those sequences whose best hit against this database matched the original sequences used in the detection step. Proteins were aligned with MAFFT v7.123b. [116], using the -einsi option, and alignments were trimmed using trimAl v1.4.rev15 [117] with the -gappyout option. Trimmed alignments were manually inspected and cleaned of poorly informative sequences except if that sequences corresponded to early-branching holozoa (ebH) taxa. Cleaned alignment were used as inputs for phylogenetic inference with IQ-TREE v1.6.7 [118], using the -bb 1000 and -mset LG options. For CDKs, since the tree topology did not show any ebH sequences belonging to CDK families without orthologues in Metazoa, we performed a second phylogenetic inference using only the ebH and metazoan proteins to reduce the potential phylogenetic noise that may be introduced with the addition of non-informative divergence.

Sequences were classified into CDK/Cyclins families taking into account the tree topology and the UFBoot nodal support values [119]. Families were named according to the orthology relationship between the ebH protein and the H. sapiens sequence. For example, Sarc_g11690T was classified as CDK10 because its position in the tree suggests an orthology relationship to this H. sapiens protein (S9 Fig), whereas Cowc_CAOG_08444T0 was classified as CDK11-CDK11B because it is orthologue to both H. sapiens proteins (S9 Fig). We found three ebH cyclin subfamilies without orthologues in Metazoa, which were named accordingly to the corresponding orthologue in S. cerevisiae (PCL1, PCL2, PCL9; PCL5, CLG1; and PCL6-PCL7). Those ebH sequences showing ambiguous or poorly supported branching patterns were classified as uncertain.

We found that the current Capsaspora sequence reported by [59] as a CDK1 orthologue (CAOG_07905) is considerably shorter in length than other CDK orthologues. This could explain why it was not detected in the work by Cao et al. [4], if an e-value constraint was taken into consideration. By inspection of the genomic sequence from [120], we detected an assembly gap of 1kb neighboring the 3’ end of the predicted annotation of CAOG_07905 (S10A Fig). In silico translation of the surroundings of this gap revealed protein domains conserved in H. sapiens and S. cerevisiae CDK1 proteins (S10A–S10C Fig). Upon realization that the gene annotation of Capsaspora CDK1-3 was incomplete, we designed forward and reverse primers (S10 Text) to PCR-amplify the unknown sequence from both genomic DNA and cDNA (S10A and S10B Fig). Sanger sequencing of the amplified products revealed one more intron and one more exon, which were used to reconstruct the missing sequence in the assembly. We mapped the transcriptome of Replicate 2 –timepoint 9 against this reconstructed sequence using tophat2 [121] with standard parameters. Identification of paired-end overlapping reads in the reconstructed exons using Tablet [122] verified the results of Sanger sequencing (S10A Fig). The updated cDNA and protein sequence of Capsaspora CDK1-3, which aligns much better with human and yeast sequences (S10C Fig), can be found in S10 Text.

Real-time quantitative PCR

Three independent cultures of Capsaspora were treated with or without hydroxyurea (10mM) over 13 hours. Upon HU release, all cultures were seeded at a cell density of ~1M cells/ml. Samples were taken every two hours for a total period of twelve hours, taking one ml for DNA content measurement (see above) and another ml for RNA extraction (see above). cDNA preparation was adapted from a protocol on Sphaeroforma arctica (http://dx.doi.org/10.17504/protocols.io.wqdfds6). Briefly, cells were lysed on 400 uL TRIzol (Ambion) and RNA was isolated using a protocol of 1-bromo-3-chloropropane for phase separation and Isopropanol for precipitation, followed by DNAseI treatment (Roche) and LiCl-ethanol precipitation to eliminate traces of genomic DNA. cDNA was produced using oligo dT primer and SuperScript III retrotranscriptase (Invitrogen) following the manufacturer’s instructions. cDNA was quantified using AceQ SYBR qPCR Master Mix (Vazyme Biotech) in a iQ cycle and iQ5 Multi-color detection system (Bio-Rad). Primer sequences are available at S9 Text. The total reaction volume was 20 μL. All reactions were run in duplicate. The program used for amplification was: (i) 95°C for 3 min; (ii) 95°C for 10 s; (iii) 60°C for 30 s; and (iv) repeat steps (ii) and (iii) for 40 cycles. Real-time data was collected through the iQ5 optical system software v. 2.1 (Bio-Rad). Gene expression levels are expressed as number of copies relative to the transcript CAOG_09639T0, used as housekeeping. For visualization, expression across time-points was normalized as a z-score. Ct data from each experiment can be found at S11 Text.

Identification of orthologous genes

Groups of orthologs were generated using OrthoFinder v2.1.2 [94] using default parameters (evalue 10e-3, MCL clustering) on a dataset of proteomes found in Table ‘Orthofinder’ in S8 Text [113,123125].

One-to-one orthologues were taken from a phylome of 6598 genes of Capsaspora reconstructed in [61] using the algorithm by [126] (http://phylomedb.org/phylome_100).

Determining cell cycle-regulated genes in H. sapiens, S. cerevisiae, S. pombe and A. thaliana

We downloaded the lists of cell cycle regulated genes which can be found at [32,43,46,48,49,85]. We translated the gene and probe names of their datasets using BioMart [127] and Uniprot [113] tools (S15 Text).

Gene age enrichment analysis

We used Count software [102] to assign the emergence of every orthogroup–and therefore every Capsaspora gene- to a given ancestor in common between species by Dollo Parsimony. We defined six different ages for Capsaspora: 0 “Capsaspora-specific”, 1 “Filozoa”, 2 “Holozoa”, 3 “Opisthokonta”, 4 “Unikonta”, and 5 “Paneukaryotic”. All Capsaspora genes unassigned to any orthogroup were defined as “Capsaspora-specific”. Gene age enrichment was calculated using contingency tables and significance by Fisher exact test using R software ver. 3.4.4. [107], and was corrected for multi-test hypothesis using Bonferroni correction.

Comparative analysis

Every periodic and non-periodic gene of each of the seven datasets were assigned to their respective orthogroup, if any. We obtained seven lists of orthogroups containing periodic genes of each species or cell type, and also defined lists of orthogroups containing genes (regardless of periodic) of each of the five species. A subset of periodic orthogroups (those containing at least one periodic gene from at least one of the seven datasets) was generated, and plotted for periodicity, presence, or absence, in all the datasets using R gplots library [108].

Numbers and ratios of periodic shared orthogroups and one-to-one orthologues, as well as binomial test p-values (see Fig 6D, S14, S16, S17 and S18 Text), were calculated using R software ver. 3.4.4. [125]. For each pair-wise comparison of species, e.g. Capsaspora and Homo sapiens HeLa cells (Fig 6C), we took the number of orthogroups they have in common as a total population, C. Then we looked at the number of periodic orthogroups from each species that are within this total population, p1 and p2, and calculated the null expectation (Aexp) as a product of the ratios of these two subpopulations within the population of orthogroups in common.

Characterization of the core set of periodic genes

For each investigated species in Fig 6B, we retrieved all the genes belonging to orthogroups with periodic genes in all the five species (measured as present in all and periodic in at least one dataset from every species) (named set-1). We also retrieved, for each species, all genes belonging to orthogroups present in all the five species (named set-2). For each species, we performed separate Gene Ontology enrichment analyses of set-1 against set-2, using Ontologizer with Bonferroni correction (see above). The significantly, most enriched p-values in all the species were retrieved and visualized using R (The R core team, 2018) (S18 Text). In parallel, we used an EggNOG v4.5.1 [128] annotation of the Capsaspora genome to retrieve the putative identity of the Capsaspora genes belonging to the orthogroups periodic in all the five species (S19 Text).

Reanalysis of cell cycle datasets using JTK_CYCLE and RAIN

We reanalyzed the datasets of gene expression of [49] (HU treatment dataset), [85] (three replicates of elutriation), [48] (two replicates of wildtype synchronous yeast cultures), [46] (one replicate, thymidine block), [32] (four replicates of double thymidine block), and [43] (a dataset of ~8000 genes matching filtering criteria by the authors) using the same pipeline used in our Capsaspora datasets. For those with replicates, periodicity ranks were calculated for each replicate independently and summed at the end.

As every experiment comprised different numbers of cell cycles of different length, we set up JTK and RAIN parameters to look for periodicity in time lapses according to the author’s reports (S15 Text). We corrected for the number of genes by setting a threshold of less than 10% of genes to be periodic. Overlap between datasets of periodic genes was calculated using R Software ver. 3.4.4. [107].

Supporting information

S1 Fig. Capsaspora owczarzaki doubling time.

A: Cell density curve (optical density, OD = 600 nm) at different cell concentrations of Capsaspora (three replicates per condition). Values of cell concentration around OD600 = 0.1 were used to seed cultures and calculate the doubling time of Capsaspora in B. B: Growth curve (logarithmic scale) of non-synchronized Capsaspora cell cultures (three replicates). Doubling time is calculated from three independent replicates.

(TIF)

S2 Fig. Conservation of microtubule organizing proteins in unicellular Holozoa.

Presence/absence matrix of the animal and yeast microtubule organizing proteins across Salpingoeca rosetta (Sros), Monosiga brevicolis (Mbre), Ministeria vibrans (Mvib), Capsaspora owczarzaki (Cowc), Creolimax fragrantissima (Cfra), Sphaeroforma arctica (Sarc), Corallochytrium limacisporum (Clim), Saccharomyces cerevisiae (Scer), Neurospora crassa (Ncra), and Dictyostelium discoideum (Ddis). List of proteins from Carvalho-Santos et al., 2011, Hodges et al., 2010, and Uniprot. Classification adapted from Carvalho-Santos et al., 2011, and Hodges et al., 2010.

(TIF)

S3 Fig. Computational pipeline used to detect periodic genes in Capsaspora.

A: Pipeline for ranking the transcripts on each experiment. RNA reads were processed using Kallisto, noise transcripts were filtered out, and JTK and RAIN were run in parallel with the indicated setup. Bonferroni-corrected p-values were ranked, and the sum of ranks was used as a final rank. B: Pipeline used to detect periodic transcripts in Capsaspora. Samples were treated separately to detect periodic transcripts with a loose cutoff. This gene set was used to filter periodic genes ranked from an average dataset of the two replicates, out of which the top 800 (10% of the number of genes in Capsaspora) were selected.

(TIF)

S4 Fig. Clustering of time points of each replicate and the unsynchronized culture sampled as a control, based on a dissimilarity matrix of Pearson correlation.

All the genes with an average expression level above 1 tpm in both replicates were used.

(TIF)

S5 Fig. Reproducibility and informative value of Capsaspora periodic genes.

A: Distributions of Pearson correlation between replicates of a set of randomly chosen 801 genes and the 801 genes defined as periodic. B: Fraction of variance explained by the different relative eigenvalues of the principal coordinate analysis (see Fig 3D).

(TIF)

S6 Fig. Details on the hierarchical clustering of Capsaspora periodic genes.

A: Hierarchical clustering of the expression profiles of the 801 periodic genes found in Capsaspora, and the color equivalences with the final clusters shown at Fig 4A. B: Average expression level of Capsaspora periodic genes grouped by hierarchical clustering. C: t-SNE plot of all 801 genes in the periodic transcriptional program of Capsaspora, showing circle pattern as in Fig 3D. Color code in both figures follows the color code in Fig 4.

(TIF)

S7 Fig. K-means clustering of the periodic transcriptional program of Capsaspora.

A: Average expression level of Capsaspora periodic genes grouped by k-means clustering. B: Top ten enriched GO terms of each cluster of periodic genes generated by k-means clustering. GO terms were considered significant when Bonferroni-corrected p-value was lower than 0.05. Full list available at S3 Fig. C: Agreement between clustering methods. Heatmap showing the percentage of overlap between clusters by two methods. Overlap is calculated as the number of genes belonging to the same pair of clusters divided by the size of the smallest cluster in the pair.

(TIF)

S8 Fig. Unrooted maximum likelihood phylogenetic tree (IQ-TREE) inferred from cyclins sequences of 30 eukaryotic species (see Methods).

Nodal support values (1000- bootstrap replicates by UFBoot) are shown in all nodes. Eukaryotic sequence names are abbreviated with the four-letter code (see Methods) and colored according to their major taxonomic group (see panel).

(PDF)

S9 Fig. Maximum likelihood phylogenetic tree (IQ-TREE) inferred from CDK sequences of early-branching holozoan species and animals (see Methods).

Statistical support values (1000-replicates UFBoot) are shown in all nodes. Eukaryotic sequence names are abbreviated with the four-letter code (see Methods) and colored according to their major taxonomic group (see panel).

(PDF)

S10 Fig. Re-annotation of the coding sequence of Capsaspora CDK1/2/3.

A: Schematic representation of the genomic locus of Capsaspora CDK1-3 gene showing exons, splicing sites, non-annotated regions of predicted sequence, and mapping of mRNA reads. B: PCR amplifications of Capsaspora CDK1 using primers detailed in Methods and A, using genomic DNA and cDNA as templates. Arrows indicate size of the products sent for sequencing. C: Alignment of H. sapiens and S. cerevisiae CDK1 genes, and the Capsaspora updated CDK1-3 sequence, using Geneious v8.1.9.

(TIF)

S11 Fig. Expression of cyclins and CDKs in Capsaspora.

A: Gene expression profile of cyclin G/I and an unidentified cyclin gene (CAOG_01199) found in Capsaspora. B: Total amount of Capsaspora CDK1/2/3 throughout the cell cycle. C: Dynamics of the cyclin-CDK system using real-time PCR. Normalized gene expression profiles of cyclins B, E, and CDK1/2/3 in two independent biological replicates of synchronized Capsaspora cultures.

(TIF)

S12 Fig. List of all enriched GO terms of the core cell cycle regulated gene set from each species used in Fig 6B.

(PDF)

S13 Fig. Analysis of the periodic transcriptional program of Capsaspora using a cutoff of 20% of the total transcriptome.

A: Scatter plot replicating Fig 3B, showing in blue all the genes additionally taken into account. Colored dots represent the 1600 genes that were finally taken as periodic in this reanalysis. B: Principal coordinate analysis using the dataset of 1600 genes. C: heatmap of gene expression level depicting six clusters detected by Euclidean distance hierarchical clustering. Clusters were rearranged to visually represent their expression peaks over time. Black arrow and dividing cell indicate time of cell division (see Fig 2). D: Gene ontology enrichment analysis of the six clusters represented in C. E: Bar plots indicating the amount of shared periodic orthogroups and/or periodic one-to-one orthologues between pairs of cell types or species, using the dataset of 1600 periodic genes in Capsaspora.

(TIF)

S14 Fig. Reanalysis of previous cell cycle datasets in model organisms.

A: Scatter plots of ranks by JTK and RAIN for each dataset of each species used in the comparative analysis (see Fig 6D and Results section). Datasets were processed as indicated in S15 Text, and Material and methods. Depending on the dataset, we could recover between one third and more than half of the originally described periodic genes, except Arabidopsis where the agreement was very low. B: Bar plots indicating the amount of shared periodic orthogroups and/or periodic one-to-one orthologues between pairs of cell types or species, using our own lists of periodic genes. P-values of all the binomial tests are provided in S17 Text.

(TIF)

S15 Fig. A possible reconstruction of the evolution of the cyclin-CDK system regulating the cell cycle in animals.

Phylogenetic tree of eukaryotes displaying the different expansions, gains and losses of the main cyclin and CDK subfamilies with a known role in cell cycle regulation, in different eukaryotic groups. Events within groups refers to some species within the group showing additional expansions, gains or losses beside those depicted in the figure. Note that LECA cyclin G/I likely gave rise to plant cyclin D and share a common ancestor to the metazoan cyclins D and G/I. Gain of other cyclin families are depicted as regular letters at different stems.

(TIF)

S1 Text. FASTA formatted sequences of human and yeast MTOC proteins used as query in S2 Fig.

(FASTA)

S2 Text. FASTA formatted sequences of the putative MTOC proteins from the organisms shown in S2 Fig.

(FASTA)

S3 Text. Tables of BLAST matches of human and yeast MTOC proteins in the proteomes of the organisms shown in S2 Fig.

(TXT)

S4 Text. Tables of transcript per million of each replicate.

(TSV)

S5 Text. List of periodic genes in Capsaspora, containing information for each gene about cluster membership, gene age, and orthologs in other species.

(TSV)

S6 Text. List of significant (Bonferroni p-value < 0.05) GeneOntology enrichments of each hierarchical cluster of periodic genes in Capsaspora.

(XLSX)

S7 Text. FASTA formatted sequences of cyclins and CDKs used in the phylogenetic analyses (see S8 and S9 Figs).

(FASTA)

S8 Text. List of species used in the phylogenetic analyses and in the generation of groups of orthologues.

(XLSX)

S9 Text. FASTA formatted sequences of the primers used in the sequencing of CDK1 and in the qPCR experiments.

(FASTA)

S10 Text. FASTA formatted sequences of newly annotated Capsaspora CDK1-2-3 CDS and protein translation.

(FASTA)

S11 Text. Data from the qPCR experiments.

(XLSX)

S12 Text. List of cell cycle regulators in humans (described in [32,44,45,93]), and their respective orthologs in Capsaspora defined by OrthoFinder and/or phylome data (see Results and Methods).

Bold indicates genes that have been plotted in Fig 5C or 5D.

(XLSX)

S13 Text. List of cell cycle regulators in humans (described in [32,44,45,93]), that also have at least one periodic co-ortholog in Capsaspora, defined by OrthoFinder (see Results and Methods).

(XLSX)

S14 Text. Metrics of gene age enrichment and depletion for the gene clusters of the periodic transcriptional program of Capsaspora, and their corresponding Fisher Test p-values.

(XLSX)

S15 Text. Procedure used to retrieve identifiers for the datasets of H. sapiens, S. cerevisiae, S. pombe, and A. thaliana, and parameters used to set up JTK_CYCLE and RAIN in the reanalysis.

(XLSX)

S16 Text. Metrics of shared periodic orthogroups (OG) and one-to-one orthologues between Capsaspora and the rest of cell types and species.

(XLSX)

S17 Text. Metrics of shared periodic orthogroups (OG) for all comparisons between pairs of species, using periodic genes from the literature and using our own sets of periodic genes.

(XLSX)

S18 Text. GO enrichment of human, yeasts, plants and Capsaspora gene sets belonging to the core conserved set of orthogroups in Fig 6B.

(TXT)

S19 Text. List of Capsaspora genes belonging to the core set of periodic orthogroups in Fig 6B, annotated using eggNOG (See Methods).

(TXT)

S1 Video. Synchronized cells of Capsaspora undergoing cell division.

Time interval between frames is 1 minute. The movie is played at 7fps. Scale bar = 5μm. Available on Figshare: https://figshare.com/s/4d642c9854efe6d879a7.

(AVI)

Acknowledgments

We thank all the members of Iñaki Ruiz-Trillo’s lab for discussion and comments on the manuscript, Sebastián Najle and Núria Ros for helpful advice and guidance with the Propidium Iodide staining and the qPCR experiments, Daniel Richter for discussion on the statistical tests, Xavier Grau-Bové for helpful discussions on the data analysis and for providing guidance in the Principal Coordinate analysis, Arnau Sebé-Pedrós for providing resources of the Capsaspora phylome, and Meritxell Antó-Subirats for technical and logistics support. We also acknowledge the UPF Flow Cytometry Core Facility for assistance with flow cytometry, and the CRG Genomics Unit for mRNA library preparation and Illumina sequencing.

Data Availability

All relevant data are within the manuscript and its Supporting Information files. RNAseq reads are deposited in the Gene Expression Omnibus (GEO) under the accession number GSE141156 and will be available after acceptance. The Supporting Information files are also available from figshare: https://figshare.com/s/4d642c9854efe6d879a7.

Funding Statement

This work was funded by a European Research Council Consolidator Grant (ERC-2012-Co-616960) to IRT; and a grant from the Spanish Ministry for Economy and Competitiveness (MINECO; BFU2017-90114-P, with European Regional Development Fund support) to IRT. AP was supported by a “la Caixa” Foundation (ID 100010434) fellowship, whose code is LCF/BQ/ES16/11570008. OD was supported by a Swiss National Science Foundation Early PostDoc Mobility fellowship (P2LAP3_171815) and a Marie Sklodowska-Curie individual fellowship (MSCA-IF 746044). EOP was supported by a pre-doctoral FPI grant from MINECO. AO was supported by a Marie Sklodowska-Curie individual fellowship (MSCA-IF 747086). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Morgan DO. Cell Cycle: Principles of Control. Yale J Biol Med. 2007. 10.1093/icb/icm066 [DOI] [Google Scholar]
  • 2.Medina EM, Turner JJ, Gordân R, Skotheim JM, Buchler NE. Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi. Elife. 2016;5: 1–23. 10.7554/eLife.09492 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Cross FR, Buchler NE, Skotheim JM. Evolution of networks and sequences in eukaryotic cell cycle control. Philos Trans R Soc B Biol Sci. 2011;366: 3532–3544. 10.1098/rstb.2011.0078 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Cao L, Chen F, Yang X, Xu W, Xie J, Yu L. Phylogenetic analysis of CDK and cyclin proteins in premetazoan lineages. BMC Evol Biol. 2014. 10.1186/1471-2148-14-10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Li Z. Regulation of the Cell Division Cycle in Trypanosoma brucei. Eukaryot Cell. 2012;11: 1180–1190. 10.1128/EC.00145-12 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Gutierrez C. The Arabidopsis Cell Division Cycle. Arab B. 2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Nieduszynski CA, Murray J, Carrington M. Whole-genome analysis of animal A- and B-type cyclins. Genome Biol. 2002. 10.1186/gb-2002-3-12-research0070 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Satyanarayana A, Kaldis P. Mammalian cell-cycle regulation: Several cdks, numerous cyclins and diverse compensatory mechanisms. Oncogene. 2009. 10.1038/onc.2009.170 [DOI] [PubMed] [Google Scholar]
  • 9.Matsushime H, Roussel MF, Ashmun RA, Sherr CJ. Colony-stimulating factor 1 regulates novel cyclins during the G1 phase of the cell cycle. Cell. 1991;65: 701–713. 10.1016/0092-8674(91)90101-4 [DOI] [PubMed] [Google Scholar]
  • 10.Matsushime H, Quelle DE, Shurtleff SA, Shibuya M, Sherr CJ, Kato JY. D-type cyclin-dependent kinase activity in mammalian cells. Mol Cell Biol. 2015;14: 2066–2076. 10.1128/mcb.14.3.2066 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Klein EA, Assoian RK. Transcriptional regulation of the cyclin D1 gene at a glance. J Cell Sci. 2008;121: 3853–3857. 10.1242/jcs.039131 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Cook JG, Park CH, Burke TW, Leone G, DeGregori J, Engel A, et al. Analysis of Cdc6 function in the assembly of mammalian prereplication complexes. Proc Natl Acad Sci U S A. 2002;99: 1347–1352. 10.1073/pnas.032677499 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Coverley D, Laman H, Laskey RA. Distinct roles for cyclins E and A during DNA replication complex assembly and activation. Nat Cell Biol. 2002. 10.1038/ncb813 [DOI] [PubMed] [Google Scholar]
  • 14.Pomerening JR, Sontag ED, Ferrell JE. Building a cell cycle oscillator: Hysteresis and bistability in the activation of Cdc2. Nat Cell Biol. 2003. 10.1038/ncb954 [DOI] [PubMed] [Google Scholar]
  • 15.Pomerening JR, Sun YK, Ferrell JE. Systems-level dissection of the cell-cycle oscillator: Bypassing positive feedback produces damped oscillations. Cell. 2005;122: 565–578. 10.1016/j.cell.2005.06.016 [DOI] [PubMed] [Google Scholar]
  • 16.Mendenhall MD, Hodge aE. Regulation of CDC28 cyclin-dependent protein kinase activity during the cell cycle of the yeast Saccharomyces cerevisiae. Microbiol Mol Biol Rev. 1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Bloom J, Cross FR. Multiple levels of cyclin specificity in cell-cycle control. Nature Reviews Molecular Cell Biology. 2007. 10.1038/nrm2105 [DOI] [PubMed] [Google Scholar]
  • 18.Cross FR, Tinkelenberg AH. A potential positive feedback loop controlling CLN1 and CLN2 gene expression at the start of the yeast cell cycle. Cell. 1991;65: 875–883. 10.1016/0092-8674(91)90394-e [DOI] [PubMed] [Google Scholar]
  • 19.Nasmyth K, Dirick L. The role of SWI4 and SWI6 in the activity of G1 cyclins in yeast. Cell. 1991;66: 995–1013. 10.1016/0092-8674(91)90444-4 [DOI] [PubMed] [Google Scholar]
  • 20.Richardson HE, Wittenberg C, Cross F, Reed SI. An essential G1 function for cyclin-like proteins in yeast. Cell. 1989;59: 1127–1133. 10.1016/0092-8674(89)90768-x [DOI] [PubMed] [Google Scholar]
  • 21.Skotheim JM, Di Talia S, Siggia ED, Cross FR. Positive feedback of G1 cyclins ensures coherent cell cycle entry. Nature. 2008;454: 291–296. 10.1038/nature07118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Epstein CB, Cross FR. CLB5: A novel B cyclin from budding yeast with a role in S phase. Genes Dev. 1992;6: 1695–1706. 10.1101/gad.6.9.1695 [DOI] [PubMed] [Google Scholar]
  • 23.Schwob E, Nasmyth K. CLB5 and CLB6, a new pair of B cyclins involved in DNA replication in Saccharomyces cerevisiae. Genes Dev. 1993;7: 1160–1175. 10.1101/gad.7.7a.1160 [DOI] [PubMed] [Google Scholar]
  • 24.Surana U, Robitsch H, Price C, Schuster T, Fitch I, Futcher AB, et al. The role of CDC28 and cyclins during mitosis in the budding yeast S. cerevisiae. Cell. 1991;65: 145–161. 10.1016/0092-8674(91)90416-v [DOI] [PubMed] [Google Scholar]
  • 25.Richardson H, Lew DJ, Henze M, Sugimoto K, Reed SI. Cyclin-B homologs in Saccharomyces cerevisiae function in S phase and in G2. Genes Dev. 1992;6: 2021–2034. 10.1101/gad.6.11.2021 [DOI] [PubMed] [Google Scholar]
  • 26.Martin-Castellanos C, Labib K, Moreno S. B-type cyclins regulate G1 progression in fission yeast in opposition to the p25rum1 cdk inhibitor. EMBO J. 1996;15: 839–49. Available: http://www.ncbi.nlm.nih.gov/pubmed/8631305%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC450282 [PMC free article] [PubMed] [Google Scholar]
  • 27.Mondesert O, McGowan CH, Russell P. Cig2, a B-type cyclin, promotes the onset of S in Schizosaccharomyces pombe. Mol Cell Biol. 2015;16: 1527–1533. 10.1128/mcb.16.4.1527 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Booher R, Beach D. Involvement of cdc13+ in mitotic control in Schizosaccharomyces pombe: possible interaction of the gene product with microtubules. EMBO J. 1988. 10.1002/j.1460-2075.1988.tb03075.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Booher RN, Alfa CE, Hyams JS, Beach DH. The fission yeast cdc2/cdc13/suc1 protein kinase: Regulation of catalytic activity and nuclear localization. Cell. 1989. 10.1016/0092-8674(89)90429-7 [DOI] [PubMed] [Google Scholar]
  • 30.Coudreuse D, Nurse P. Driving the cell cycle with a minimal CDK control network. Nature. 2010. 10.1038/nature09543 [DOI] [PubMed] [Google Scholar]
  • 31.Goodrich DW, Wang NP, Qian YW, Lee EYHP, Lee WH. The retinoblastoma gene product regulates progression through the G1 phase of the cell cycle. Cell. 1991. 10.1016/0092-8674(91)90181-W [DOI] [PubMed] [Google Scholar]
  • 32.Grant GD, Brooks L, Zhang X, Mahoney JM, Martyanov V, Wood TA, et al. Identification of cell cycle-regulated genes periodically expressed in U2OS cells and their regulation by FOXM1 and E2F transcription factors. Mol Biol Cell. 2013;24: 3634–3650. 10.1091/mbc.E13-05-0264 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Ishida S, Huang E, Zuzan H, Spang R, Leone G, West M, et al. Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis. Mol Cell Biol. 2001;21: 4684–4699. 10.1128/MCB.21.14.4684-4699.2001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Iyer VR, Horak CE, Scafe CS, Botstein D, Snyder M, Brown PO. Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF. Nature. 2001;409: 533–538. 10.1038/35054095 [DOI] [PubMed] [Google Scholar]
  • 35.Gefeng Z, Spellman PT, Volpe T, Brown PO, Botstein D, Davis TN, et al. Two yeast forkhead genes regulate the cell cycle and pseudohyphal growth. Nature. 2000;406: 90–94. 10.1038/35017581 [DOI] [PubMed] [Google Scholar]
  • 36.Reynolds D, Shi BJ, McLean C, Katsis F, Kemp B, Dalton S. Recruitment of Thr 319-phosphorylated Ndd1p to the FHA domain of Fkh2p requires C1b kinase activity: A mechanism for CLB cluster gene activation. Genes Dev. 2003;17: 1789–1802. 10.1101/gad.1074103 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Pramila T, Wu W, Miles S, Noble WS, Breeden LL. The Forkhead transcription factor Hcm1 regulates chromosome segregation genes and fills the S-phase gap in the transcriptional circuitry of the cell cycle. Genes Dev. 2006. 10.1101/gad.1450606 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Laoukili J, Kooistra MRH, Brás A, Kauw J, Kerkhoven RM, Morrison A, et al. FoxM1 is required for execution of the mitotic programme and chromosome stability. Nat Cell Biol. 2005. 10.1038/ncb1217 [DOI] [PubMed] [Google Scholar]
  • 39.Iyer VR, Eisen MB, Ross DT, Schuler G, Moore T, Lee JCF, et al. The transcriptional program in the response of human fibroblasts to serum. Science (80-). 1999;283: 83–87. 10.1126/science.283.5398.83 [DOI] [PubMed] [Google Scholar]
  • 40.Kelliher CM, Leman AR, Sierra CS, Haase SB. Investigating Conservation of the Cell-Cycle-Regulated Transcriptional Program in the Fungal Pathogen, Cryptococcus neoformans. PLoS Genet. 2016;12: 1–23. 10.1371/journal.pgen.1006453 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Zones JM, Blaby IK, Merchant SS, Umen JG. High-Resolution Profiling of a Synchronized Diurnal Transcriptome from Chlamydomonas reinhardtii Reveals Continuous Cell and Metabolic Differentiation. Plant Cell. 2015;27: 2743–2769. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Peña-Diaz J, Hegre SA, Anderssen E, Aas PA, Mjelle R, Gilfillan GD, et al. Transcription profiling during the cell cycle shows that a subset of Polycomb-targeted genes is upregulated during DNA replication. Nucleic Acids Res. 2013;41: 2846–2856. 10.1093/nar/gks1336 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Dominguez D, Tsai YH, Gomez N, Jha DK, Davis I, Wang Z. A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer. Cell Res. 2016;26: 946–962. 10.1038/cr.2016.84 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Whitfield ML, Sherlock G, Saldanha AJ, Murray JI, Ball CA, Alexander KE, et al. Identification of Genes Periodically Expressed in the Human Cell Cycle and Their Expression in Tumors. Mol Biol Cell. 2002;13: 1977–2000. 10.1091/mbc.02-02-0030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Cho RJ, Huang M, Campbell MJ, Dong H, Steinmetz L, Sapinoso L, et al. Transcriptional regulation and function during the human cell cycle. Nat Genet. 2001. 10.1038/83751 [DOI] [PubMed] [Google Scholar]
  • 46.Bar-Joseph Z, Siegfried Z, Brandeis M, Brors B, Lu Y, Eils R, et al. Genome-wide transcriptional analysis of the human cell cycle identifies genes differentially regulated in normal and cancer cells. Proc Natl Acad Sci. 2008. 10.1073/pnas.0704723105 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, et al. Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization. Mol Biol Cell. 1998. 10.1091/mbc.9.12.3273 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Orlando DA, Lin CY, Bernard A, Wang JY, Socolar JES, Iversen ES, et al. Global control of cell-cycle transcription by coupled CDK and network oscillators. Nature. 2008;453: 944–947. 10.1038/nature06955 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Menges M, Hennig L, Gruissem W, Murray JAH. Genome-wide gene expression in an Arabidopsis cell suspension. Plant Mol Biol. 2003;53: 423–442. 10.1023/B:PLAN.0000019059.56489.ca [DOI] [PubMed] [Google Scholar]
  • 50.Breyne P, Dreesen R, Vandepoele K, De Veylder L, Van Breusegem F, Callewaert L, et al. Transcriptome analysis during cell division in plants. Proc Natl Acad Sci. 2002;99: 14825–14830. 10.1073/pnas.222561199 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Jensen LJ, Jensen TS, De Lichtenberg U, Brunak S, Bork P. Co-evolution of transcriptional and post-translational cell-cycle regulation. Nature. 2006;443: 594–597. 10.1038/nature05186 [DOI] [PubMed] [Google Scholar]
  • 52.Giotti B, Joshi A, Freeman TC. Meta-analysis reveals conserved cell cycle transcriptional network across multiple human cell types. BMC Genomics. 2017. 10.1186/s12864-016-3435-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Rhind N, Russell P. Chk1 and Cds1: linchpins of the DNA damage and replication checkpoint pathways. J Cell Sci. 2000;113 (Pt 2: 3889–96. Available: http://www.ncbi.nlm.nih.gov/pubmed/11058076%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2863124 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Cooper K. Rb, whi it’s not just for metazoans anymore. Oncogene. 2006;25: 5228–5232. 10.1038/sj.onc.1209630 [DOI] [PubMed] [Google Scholar]
  • 55.Kearsey SE, Cotterill S. Enigmatic variations: Divergent modes of regulating eukaryotic DNA replication. Molecular Cell. 2003. pp. 1067–1075. 10.1016/S1097-2765(03)00441-6 [DOI] [PubMed] [Google Scholar]
  • 56.Ferrer-Bonet M, Ruiz-Trillo I. Capsaspora owczarzaki. Current Biology. 2017. 10.1016/j.cub.2017.05.074 [DOI] [PubMed] [Google Scholar]
  • 57.Hertel LA, Bayne CJ, Loker ES. The symbiont Capsaspora owczarzaki, nov. gen. nov. sp., isolated from three strains of the pulmonate snail Biomphalaria glabrata is related to members of the Mesomycetozoea. Int J Parasitol. 2002;32: 1183–1191. 10.1016/s0020-7519(02)00066-8 [DOI] [PubMed] [Google Scholar]
  • 58.Ruiz-Trillo I, Inagaki Y, Davis LA, Sperstad S, Landfald B, Roger AJ. Capsaspora owczarzaki is an independent opisthokont lineage. Curr Biol. 2004;14: R946–R947. 10.1016/j.cub.2004.10.037 [DOI] [PubMed] [Google Scholar]
  • 59.Suga H, Chen Z, de Mendoza A, Sebé-Pedrós A, Brown MW, Kramer E, et al. The Capsaspora genome reveals a complex unicellular prehistory of animals. Nat Commun. 2013;4: 1–9. 10.1038/ncomms3325 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Sebé-Pedrós A, Ballaré C, Parra-Acero H, Chiva C, Tena JJ, Sabidó E, et al. The Dynamic Regulatory Genome of Capsaspora and the Origin of Animal Multicellularity. Cell. 2016;165: 1224–1237. 10.1016/j.cell.2016.03.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Sebé-Pedrós A, Peña MI, Capella-Gutiérrez S, Antó M, Gabaldón T, Ruiz-Trillo II, et al. High-Throughput Proteomics Reveals the Unicellular Roots of Animal Phosphosignaling and Cell Differentiation. Dev Cell. 2016;39: 186–197. 10.1016/j.devcel.2016.09.019 [DOI] [PubMed] [Google Scholar]
  • 62.Sebé-Pedrós A, Irimia M, del Campo J, Parra-Acero H, Russ C, Nusbaum C, et al. Regulated aggregative multicellularity in a close unicellular relative of metazoa. Elife. 2013;2: 1–20. 10.7554/eLife.01287 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Parra-Acero H, Ros-Rocher N, Perez-Posada A, Kożyczkowska A, Sánchez-Pons N, Nakata A, et al. Transfection of Capsaspora owczarzaki, a close unicellular relative of animals. Dev. 2018;145 10.1242/dev.162107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Banfalvi G. Cell Cycle Synchronization Methods and Protocols. Methods in molecular biology (Clifton, N.J.). 2011. [Google Scholar]
  • 65.Blajeski AL, Phan VA, Kottke TJ, Kaufmann SH. G1 and G2 cell-cycle arrest following microtubule depolymerization in human breast cancer cells. J Clin Invest. 2002. 10.1172/JCI13275 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Jackman J, O’Connor PM. Methods for Synchronizing Cells at Specific Stages of the Cell Cycle. Current Protocols in Cell Biology. 2001. [DOI] [PubMed] [Google Scholar]
  • 67.Slater ML. Effect of reversible inhibition of deoxyribonucleic acid synthesis on the yeast cell cycle. J Bacteriol. 1973. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Fox MH, Read RA, Bedford JS. Comparison of synchronized Chinese hamster ovary cells obtained by mitotic shake-off, hydroxyurea, aphidicolin, or methotrexate. Cytometry. 1987. 10.1002/cyto.990080312 [DOI] [PubMed] [Google Scholar]
  • 69.Singh A, Agarwal A, Xu Y jie. Novel Cell-killing mechanisms of hydroxyurea and the implication toward combination therapy for the treatment of fungal infections. Antimicrob Agents Chemother. 2017. 10.1128/AAC.00734-17 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Aubin JE, Weber K, Osborn M. Analysis of actin and microfilament-associated proteins in the mitotic spindle and cleavage furrow of PtK2 cells by immunofluorescence microscopy. A critical note. Exp Cell Res. 1979. 10.1016/0014-4827(79)90260-X [DOI] [PubMed] [Google Scholar]
  • 71.Cadart C, Zlotek-Zlotkiewicz E, Le Berre M, Piel M, Matthews HK. Exploring the function of cell shape and size during mitosis. Dev Cell. 2014;29: 159–169. 10.1016/j.devcel.2014.04.009 [DOI] [PubMed] [Google Scholar]
  • 72.Cramer LP, Mitchison TJ. Investigation of the mechanism of retraction of the cell margin and rearward flow of nodules during mitotic cell rounding. Mol Biol Cell. 1997. 10.1091/mbc.8.1.109 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Harris A. Location of cellular adhesions to solid substrata. Dev Biol. 1973. 10.1016/0012-1606(73)90009-2 [DOI] [PubMed] [Google Scholar]
  • 74.Kunda P, Pelling AE, Liu T, Baum B. Moesin Controls Cortical Rigidity, Cell Rounding, and Spindle Morphogenesis during Mitosis. Curr Biol. 2008. 10.1016/j.cub.2007.12.051 [DOI] [PubMed] [Google Scholar]
  • 75.Luxenburg C, Amalia Pasolli H, Williams SE, Fuchs E. Developmental roles for Srf, cortical cytoskeleton and cell shape in epidermal spindle orientation. Nat Cell Biol. 2011. 10.1038/ncb2163 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76.Mcconnell CH. The mitosis found in hydra. Science (80-). 1930. 10.1126/science.72.1859.170-b [DOI] [PubMed] [Google Scholar]
  • 77.Zang JH, Cavet G, Sabry JH, Wagner P, Moores SL, Spudich JA. On the role of myosin-II in cytokinesis: division of Dictyostelium cells under adhesive and nonadhesive conditions. Mol Biol Cell. 1997. 10.1091/mbc.8.12.2617 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.Fukui Y, Inoue S. Cell division in Dictyostelium with special emphasis on actomyosin organization in cytokinesis. Cell Motil Cytoskeleton. 1991;18: 41–54. 10.1002/cm.970180105 [DOI] [PubMed] [Google Scholar]
  • 79.Azimzadeh J. Exploring the evolutionary history of centrosomes. Philosophical Transactions of the Royal Society B: Biological Sciences. 2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Mahoney NM, Goshima G, Douglass AD, Vale RD. Making microtubules and mitotic spindles in cells without functional centrosomes. Curr Biol. 2006;16: 564–569. 10.1016/j.cub.2006.01.053 [DOI] [PubMed] [Google Scholar]
  • 81.Jaspersen SL, Winey M. THE BUDDING YEAST SPINDLE POLE BODY: Structure, Duplication, and Function. Annu Rev Cell Dev Biol. 2004. 10.1146/annurev.cellbio.20.022003.114106 [DOI] [PubMed] [Google Scholar]
  • 82.Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016. 10.1038/nbt.3519 [DOI] [PubMed] [Google Scholar]
  • 83.Hughes ME, Hogenesch JB, Kornacker K. JTK-CYCLE: An efficient nonparametric algorithm for detecting rhythmic components in genome-scale data sets. J Biol Rhythms. 2010;25: 372–380. 10.1177/0748730410379711 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84.Thaben PF, Westermark PO. Detecting rhythms in time series with rain. J Biol Rhythms. 2014;29: 391–400. 10.1177/0748730414553029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85.Rustici G, Mata J, Kivinen K, Lió P, Penkett CJ, Burns G, et al. Periodic gene expression program of the fission yeast cell cycle. Nat Genet. 2004;36: 809–817. 10.1038/ng1377 [DOI] [PubMed] [Google Scholar]
  • 86.Bauer S, Grossmann S, Vingron M, Robinson PN. Ontologizer 2.0—A multifunctional tool for GO term enrichment analysis and data exploration. Bioinformatics. 2008. 10.1093/bioinformatics/btn250 [DOI] [PubMed] [Google Scholar]
  • 87.Popow J, Jurkin J, Schleiffer A, Martinez J. Analysis of orthologous groups reveals archease and DDX1 as tRNA splicing factors. Nature. 2014. 10.1038/nature13284 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 88.Chen M, Gartenberg MR. Coordination of tRNA transcription with export at nuclear pore complexes in budding yeast. Genes Dev. 2014. 10.1101/gad.236729.113 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 89.Herrera MC, Chymkowitch P, Robertson JM, Eriksson J, Bøe SO, Alseth I, et al. Cdk1 gates cell cycle-dependent tRNA synthesis by regulating RNA polymerase III activity. Nucleic Acids Res. 2018. 10.1093/nar/gky846 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90.White RJ, Gottlieb TM, Downes CS, Jackson SP. Cell Cycle Regulation of RNA Polymerase III Transcription. Mol Cell Biol. 1995. 10.1128/MCB.15.12.6653 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91.Schieke SM, McCoy JP, Finkel T. Coordination of mitochondrial bioenergetics with G1phase cell cycle progression. Cell Cycle. 2008. 10.4161/cc.7.12.6067 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92.Obaya AJ, Sedivy JM. Regulation of cyclin-Cdk activity in mammalian cells. Cell Mol Life Sci. 2002;59: 126–142. 10.1007/s00018-002-8410-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Santos A, Wernersson R, Jensen LJ. Cyclebase 3.0: A multi-organism database on cell-cycle regulation and phenotypes. Nucleic Acids Res. 2015. 10.1093/nar/gku1092 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94.Emms DM, Kelly S. OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol. 2015;16: 157 10.1186/s13059-015-0721-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 95.Burkhart DL, Sage J. Cellular mechanisms of tumour suppression by the retinoblastoma gene. Nat Rev Cancer. 2008;8: 671–682. 10.1038/nrc2399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96.Aksoy O, Chicas A, Zeng T, Zhao Z, McCurrach M, Wang X, et al. The atypical E2F family member E2F7 couples the p53 and RB pathways during cellular senescence. Genes Dev. 2012;26: 1546–1557. 10.1101/gad.196238.112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97.Di Stefano L, Jensen MR, Helin K. E2F7, a novel E2F featuring DP-independent repression of a subset of E2F-regulated genes. EMBO J. 2003;22: 6289–6298. 10.1093/emboj/cdg613 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 98.Fu J, Bian M, Jiang Q, Zhang C. Roles of Aurora Kinases in Mitosis and Tumorigenesis. Mol Cancer Res. 2007. 10.1158/1541-7786.MCR-06-0208 [DOI] [PubMed] [Google Scholar]
  • 99.Li J, Dallmayer M, Kirchner T, Musa J, Grünewald TGP. PRC1: Linking Cytokinesis, Chromosomal Instability, and Cancer Evolution. Trends in Cancer. 2018. 10.1016/j.trecan.2017.11.002 [DOI] [PubMed] [Google Scholar]
  • 100.Li M, Zhang P. The function of APC/CCdh1 in cell cycle and beyond. Cell Div. 2009. 10.1186/1747-1028-4-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101.Wang R, Burton JL, Solomon MJ. Transcriptional and post-transcriptional regulation of Cdc20 during the spindle assembly checkpoint in S. cerevisiae. Cell Signal. 2017. 10.1016/j.cellsig.2017.02.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102.Csurös M. Count: Evolutionary analysis of phylogenetic profiles with parsimony and likelihood. Bioinformatics. 2010. 10.1093/bioinformatics/btq315 [DOI] [PubMed] [Google Scholar]
  • 103.Forth S, Kapoor TM. The mechanics of microtubule networks in cell division. Journal of Cell Biology. 2017. 10.1083/jcb.201612064 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104.Wu J, Akhmanova A. Microtubule-Organizing Centers. Annu Rev Cell Dev Biol. 2017. 10.1146/annurev-cellbio-100616-060615 [DOI] [PubMed] [Google Scholar]
  • 105.Santamaría D, Barrière C, Cerqueira A, Hunt S, Tardy C, Newton K, et al. Cdk1 is sufficient to drive the mammalian cell cycle. Nature. 2007;448: 811–815. 10.1038/nature06046 [DOI] [PubMed] [Google Scholar]
  • 106.Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012. 10.1038/nmeth.2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107.The R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. 2018.
  • 108.Warnes GR, Bolker B, Bonebakker L, Gentleman R, Liaw WHA, Lumley T, et al. Package “gplots”: Various R programming tools for plotting data. R Packag version 2170. 2016.
  • 109.Carvalho-Santos Z, Azimzadeh J, Pereira-Leal JB, Bettencourt-Dias M. Tracing the origins of centrioles, cilia, and flagella. J Cell Biol. 2011;194: 165–175. 10.1083/jcb.201011152 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 110.Hodges ME, Scheumann N, Wickstead B, Langdale JA, Gull K. Reconstructing the evolutionary history of the centriole from protein components. J Cell Sci. 2010;123: 1407–1413. 10.1242/jcs.064873 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 111.Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990. 10.1016/S0022-2836(05)80360-2 [DOI] [PubMed] [Google Scholar]
  • 112.Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: Architecture and applications. BMC Bioinformatics. 2009. 10.1186/1471-2105-10-421 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 113.Bateman A, Martin MJ, O’Donovan C, Magrane M, Alpi E, Antunes R, et al. UniProt: The universal protein knowledgebase. Nucleic Acids Res. 2017. 10.1093/nar/gkw1099 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 114.Vandepoele K. Genome-Wide Analysis of Core Cell Cycle Genes in Arabidopsis. PLANT CELL ONLINE. 2002. 10.1105/tpc.010445 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 115.Wang G. Genome-Wide Analysis of the Cyclin Family in Arabidopsis and Comparative Phylogenetic Analysis of Plant Cyclin-Like Proteins. PLANT Physiol. 2004. 10.1104/pp.104.040436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 116.Katoh K. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002. 10.1093/nar/gkf436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 117.Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T. trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009. 10.1093/bioinformatics/btp348 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 118.Nguyen LT, Schmidt HA, Von Haeseler A, Minh BQ. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015. 10.1093/molbev/msu300 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 119.Minh BQ, Nguyen MAT, Von Haeseler A. Ultrafast approximation for phylogenetic bootstrap. Mol Biol Evol. 2013. 10.1093/molbev/mst024 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 120.Denbo S, Aono K, Kai T, Yagasaki R, Ruiz-Trillo I, Suga H. Revision of the Capsaspora genome using read mating information adjusts the view on premetazoan genome. Dev Growth Differ. 2019;61: 34–42. 10.1111/dgd.12587 [DOI] [PubMed] [Google Scholar]
  • 121.Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013. 10.1186/gb-2013-14-4-r36 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 122.Milne I, Stephen G, Bayer M, Cock PJA, Pritchard L, Cardle L, et al. Using tablet for visual exploration of second-generation sequencing data. Brief Bioinform. 2013. 10.1093/bib/bbs012 [DOI] [PubMed] [Google Scholar]
  • 123.Bhattacharya D, Price DC, Xin Chan C, Qiu H, Rose N, Ball S, et al. Genome of the red alga Porphyridium purpureum. Nat Commun. 2013. 10.1038/ncomms2931 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 124.Nordberg H, Cantor M, Dusheyko S, Hua S, Poliakov A, Shabalov I, et al. The genome portal of the Department of Energy Joint Genome Institute: 2014 updates. Nucleic Acids Res. 2014. 10.1093/nar/gkt1069 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 125.Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, et al. Ensembl 2018. Nucleic Acids Res. 2018. 10.1093/nar/gkx1098 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 126.Huerta-Cepas J, Capella-Gutiérrez S, Pryszcz LP, Marcet-Houben M, Gabaldón T. PhylomeDB v4: Zooming into the plurality of evolutionary histories of a genome. Nucleic Acids Res. 2014. 10.1093/nar/gkt1177 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 127.Smedley D, Haider S, Durinck S, Pandini L, Provero P, Allen J, et al. The BioMart community portal: An innovative alternative to large, centralized data repositories. Nucleic Acids Res. 2015. 10.1093/nar/gkv350 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 128.Huerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D, Walter MC, et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016;44: D286–D293. 10.1093/nar/gkv1248 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Bret Payseur, Joseph Heitman

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

21 Aug 2019

Dear Iñaki,

Thank you very much for submitting your Research Article entitled 'Gradual evolution of cell cycle regulation during the transition to animal multicellularity' to PLOS Genetics. Your manuscript was fully evaluated at the editorial level and by independent peer reviewers all of whom are experts in the area. The reviewers appreciated the attention to an important problem, but raised a series of points about the submitted manuscript. Based on the reviews, we will not be able to accept this version of the manuscript, but we will be happy to review again a revised version responsive to the reviews. On balance, this is between a minor revision and a major revision decision.

Should you decide to revise the manuscript for further consideration here, your revisions should address the specific points made by each reviewer. We will also require a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript.

If you decide to revise the manuscript for further consideration at PLOS Genetics, please aim to resubmit within the next 60 days, unless it will take extra time to address the concerns of the reviewers, in which case we would appreciate an expected resubmission date by email to plosgenetics@plos.org.

If present, accompanying reviewer attachments are included with this email; please notify the journal office if any appear to be missing. They will also be available for download from the link below. You can use this link to log into the system when you are ready to submit a revised version, having first consulted our Submission Checklist.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see our guidelines.

Please be aware that our data availability policy requires that all numerical data underlying graphs or summary statistics are included with the submission, and you will need to provide this upon resubmission if not already present. In addition, we do not permit the inclusion of phrases such as "data not shown" or "unpublished results" in manuscripts. All points should be backed up by data provided with the submission.

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool.  PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

PLOS has incorporated Similarity Check, powered by iThenticate, into its journal-wide submission system in order to screen submitted content for originality before publication. Each PLOS journal undertakes screening on a proportion of submitted articles. You will be contacted if needed following the screening process.

To resubmit, use the link below and 'Revise Submission' in the 'Submissions Needing Revision' folder.

[LINK]

We look forward to receiving your revised manuscript. Please do not hesitate to contact us if you have any concerns or questions.

Yours sincerely,

Joe

Joseph Heitman, MD, PhD

Associate Editor

PLOS Genetics

Bret Payseur

Section Editor: Evolution

PLOS Genetics

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Synopsis: There is a growing interest in the cell biology of early-diverging holozoans (Monosiga, Salpingoeca, Sphaeroforma, and Capsaspora) because they provide insights on the early ancestor of animals. Here, the authors used hydroxyurea to block the cell cycle of Capsaspora and then synchronously release the population upon wash out (Fig. 1). They used microscopy to analyze cell division, tubulin staining, DNA straining of synchronized cells (Fig. 2) to quantify the synchrony and timing of the cell cycle (mitosis is 10.5 hours after release, total cell cycle period is ~12 hours). The authors then used RNA-seq to identify ~800 cell cycle regulated genes (10% of the genome) after synchronous block-release; Figs. 3-4. This dataset forms the basis of their bioinformatic analysis. The main claims are that Capsaspora cyclins E, A, B have similar timing to their animal counterparts (Fig. 5) and Capsaspora cell cycle transcription program resembles humans more than yeasts and plant (Fig. 6). Knowing the timing of cyclin and CDK gene expression in early-diverging holozoa is important for understanding the principles of cell cycle regulation and its conservation across eukaryotes.

Strengths: This work is novel because it is (to my knowledge) the first cell cycle expression dataset in an early-diverging holozoan. If so, the authors should state this more explicitly and put their work in context. I think the manuscript will be of broad interest to the cell cycle and evolutionary genomics community. The authors worked with a non-model organism and made great use of genomics, which should inspire other groups working with early-diverging holozoa or non-model organisms.

Weaknesses: The analysis of RNA-seq replicates is well done. The density of time sampling was high (45 minutes for 12 hours). The use of two methods for identifying periodic genes with 11 to 13-hour period (already known from Fig. 2) is good, and the circular structure in the two principle components (Fig. 3D) is reassuring. However, I could not find experiments that validate the timing of Cyclin E, A, B and Cdk1 expression observed in RNA-seq experiments, e.g. Fig. 5. The authors also make some claims regarding the expansion of cyclins and CDKs that are inaccurate and, thus, should be rewritten; see Comments below. Both of these weaknesses are relatively straightforward to address.

Major comments:

** Lines 197-201 and Discussion: Although it is exciting to see a mitotic spindle in the absence of a canonical MTOC, the absence of gamma-tubulin ring complex genes (i.e. evidence for lack of MTOC) could also be due to poor annotation or an incomplete genome? How confident are the authors that Capsaspora genome does not encode for canonical MTOC? Are Sphaeroforma, Monosiga, and Salpingoeca genomes also missing these components? If so, this would suggest that these genes are missing. Please elaborate and rewrite.

** One of the main conclusions is the conservation of gene expression timing of Cyclin E, A, B and CDK expression between Capsaspora and humans. However, I could not find experiments to validate the timing of Cyclin E, A, B and CDK expression observed in RNA-seq experiments. At a minimum, some alternative method to validate transcript levels (RT-qPCR, Northern blot) is needed. More ambitiously, one could measure Cyclin E, A, B protein levels using Western blot. This would really emphasize similarities between Capsaspora and humans, and improve significance and impact.

** According to the phylogenetic tree, Capsaspora lacks a Cyclin D, but it has a Cyclin F and two Cyclins G (which cluster with Cyclin E). Have the authors analyzed the expression profile of these cyclins in Capsaspora compared to humans? This would improve significance and impact.

** Ref. 2 has a Cyclin and CDK phylogeny (Figure 2-Figsupp2, Figsupp6) with a broad number of eukaryotic outgroups (including Capsaspora, Salpingoeca, Sphaeroforma, Monosiga). This reference will be helpful in two ways:

(i) Lines 318-332: The CDK phylogeny of Ref. 2 places holozoa CDK1/2/3 with "CDKA" (the ancestral CDK1/2/3 found in plants and deep protists). This provides better evidence in support of scenario 2 (CDK1 and CDK2/3 are metazoan-specific gene duplications).

(ii) Lines 482-486: LECA already had one CDK and several Cyclins (A, B, D/E/F/G/etc..). The evolutionary intermediate state (of multiple cyclins) is found in many other eukaryotes, not just Capsaspora; see Ref. 2. The sub-functionalization of cyclins happened between FECA (first common ancestor) and LECA. The authors should rewrite their discussion accordingly.

Minor comments:

** Line 187: I find this comparison awkward and meaningless (especially when comparing to yeast).

** Why is the JTK Rank clustered into vertical bands in Figure 3B? Please clarify.

** Line 254, Fig. 4: Are cells that are blocked in DNA replication due to hydroxyurea and then released still in G1/S? I ask because the GO enrichment categories are more consistent with S phase. Perhaps you could clarify in the main text how you arrived at these classifications. Is it based on DNA content and cell cycle events in Figs. 1-2 and/or GO categories? Perhaps label the inferred phases in Figs. 1-2?

** Line 297: "Cdc2" (old name, based on homology to Pombe) should be "CDK1"? The authors use CDK1,2,3,4,etc.. throughout their manuscript.

** Line 375: Could the authors add a sentence to describe how they calculate "gene age", i.e. gene found only in Capsaspora is youngest, gene found in all species is oldest?

** Line 419: Can you elaborate on the core set of genes of conserved oscillatory expression? This is novel and interesting.

** Line 1144: "Seven" should be "five".

Reviewer #2: The manuscript by Perez-Posada and colleagues describes the transcriptional regulation of the cell cycle in the unicellular protist Capsaspora and compares its cell cycle-related gene content (especially the CDK-cyclin part) between Capsaspora, two yeasts (Saccharomyces cerevisiae and Schizosaccharomyces pombe) and humans. The manuscript is clearly written and the results are well described. I am not an expert in the molecular biology of the cell cycle, but from an outsider's perspective it appears that the ability to obtain synchronized Capsaspora cell cultures and study the molecular biology of the cell cycle seems a considerable step toward studying the evolution of the cell cycle in animals and their relatives, but also more broadly in eukaryotes.

My main issue with the manuscript is the simplistic evolutionary comparisons and interpretations. I simply don't buy on the basis of the evidence presented the authors' evolutionary inference that the Capsaspora cyclin-CDK system "could represent an intermediate state in the evolution of animal-like cyclin-CDK regulation". Although that may end up being the case, my issue is that the authors' analyses haven't shown this. This is so because all their inferences are based on comparisons between Capsaspora and humans. But as the authors well know, there are many more animals than humans (what about Drosophila, non-vertebrate chordates or non-bilaterians?) and many more protists than Capsaspora (choanoflagellates, Ministeria, etc.). Similarly, there are many more outgroups than just fungi (the authors briefly mention Dictyostelium and plants) that would be very informative.

To address this issue, i believe the authors should greatly expand their search of CDK-cyclin genes in a broader sample of representative eukaryotes and add a figure that summarizes the distribution of these genes in these organisms.

Minor comments:

L26: "are present in all eukaryotes" -> "are widely / highly conserved in eukaryotes"

L31: "in a more representative opisthokont" - what is a "representative"opisthokont is highly subjective

L42-43: "could represent an intermediate state" - how can you distinguish this hypothesis from secondary simplification in Capsaspora?

L55: "yeasts" -> "fungi"

L140-141: This sentence should be stated as a hypothesis and not as an inference

L229-231: Can you rephrase? not sure i understand what you mean here

L326-327: how do you find this hypothesis to be "more parsimonious"?

L341: "ancient" -> "conserved" (the genes present in the Capsaspora genome are modern but conserved, they are not ancient)

L465-467: Which study was this? Please include a citation. And how much more limited was their sampling? All you've added is Capsaspora, which may or may not turn out to be a good model

Figure 7: i would definitely add more representative eukaryotic species here

Reviewer #3: The manuscript titled “Gradual evolution of cell cycle regulation by cyclin-dependent kinases during the transition to animal multicellularity” provides useful and important insights into the diversity and evolution of cell cycle control within the opisthokonts. The strength of the work lies in the development of a clean and reversible cell cycle synchronization protocol for vegitative Capsaspora cultures. The authors have capitalized on this achievement to identify cyclically regulated genes. They then go on to repurpose their analysis pipeline to identify cyclically expressed genes using published yeast, and both human Arabidopsis cell culture experiments to explore overlap in genes that are cyclically expressed.

Although the work presented in this manuscript is correlative, the experiments and analyses are appropriate first steps given how little is known about the biology of the system. Obvious next steps will be to prove that cyclical expression is dependent on transcription, identify transcriptional regulators (the transcription factor binding sites and proteins they bind), and/or show that the proposed regulators are actually controlling the cell cycle. Although it is tempting to ask for these analyses in the present paper, each item in the above list would require months (or years) of work to in a non-model system, are unnecessary to support the core claims made by the authors, and would drastically alter the scope of the paper and therefore necessitate multiple rounds of peer review.

The following points, however, should be addressed to ensure that the claims made in the paper are supported by the provided evidence, as well as to enhance the value of the reported data through discussion and comparison of existing literature.

Major points:

Major Point 1: In my opinion, the title is unnecessarily hyperbolic, and echos the oversimplification depicted in Figure 7 that depicts Capsaspora as an intermediate between human cells and yeast (which has been, as the authors describe, shown to be divergent relative to other fungi and protists). The data in the paper does indicate that aspects of human cell cycle regulation were already in place before the last common ancestor of animals. However, to extend that finding to claim that there was a gradual accumulation of cell cycle complexity associated with the evolution of animal multicellularity requires analysis of multiple animal lineages (Drosophila might be one to look at, among others) and additional non-opisthokonts are needed (Dictyostelium comes to mind). This may be possible to do by adding a paragraph discussion section that compares the new analyses to previous analyses of cell cycle regulation in additional lineages. If this is not feasible, the text and title should be edited to align with the findings of the paper.

Major Point 2: The sequencing and cytometry results are based on two replicate experiments. Given the number of timepoints involved, 3 biological replicates (as is customary in the field) may not have been feasible. However, this makes it even more important to describe in detail how distinct the two replicates are. The methods as described beginning on Line 522 suggest a scenario wherein a culture was split into 2 flasks, and were later treated treated in parallel. If this is correct, it should be stated as such. Furthermore, it may be more accurate to call these technical replicates as sister flasks may not display the biological variability needed for biological replicates (biological replicates should, if at all possible, be separated in time to ensure robust data).

Major Point 3: The decision to select genes for further analysis by ranking of P-values and then selection of a specific number genes should be justified (in contrast to analyzing all genes that meet a certain threshold p-value). For each analysis where this approach was taken, the maximum p-values included for the analysis should be reported, including the appropriate multiple-testing correction.

Major Point 4: Because this organism is diverged from model organisms, the behavior of Capsaspora cells after release from HU should be compared to what happens in other organisms. Is the 2 hour lag from wash out of HU typical (normalizing for total cell cycle time)? If not, what might be going on?

Major Point 5: The method section for synchronization does not have enough detail to replicate the experiments. How many times were cells washed? With what volume of media? It may be useful to others in this and related fields to include a step-by-step protocol as a supplemental document.

Minor Points:

Minor Point 1: In the abstract, it is stated that Capsaspora is “more representative” of opisthokonts. Without a large sample size across a large diversity of lineages, it is impossible to say whether a particular phenotype or genotype is “more representative”. Most likely, the authors simply mean that we need to broaden our perspective (which is clearly true and an important point) and can clarify the language here.

Minor Point 2: In the initial description of cell cycle synchronization (paragraph that begins on Line 159), it would be useful to state the doubling time of untreated adherent Capsaspora cells. This would provide context with which to evaluate the timing of cell cycle synchronization with hydroxyurea. If this number is unknown, it should be calculated and reported here.

Minor Point 3: In line 198, it states that it has been previously reported that Capsaspora has no gamma-tubulin ring complex, and cites a review on the evolution of MTOCs. I was not able to find reference to a lack of gamma-tubulin ring complexes in Capsaspora in the indicated paper (Figure 1 of the cited paper indicates Capsaspora does not have a SPD-2/CEP192 homolog, but this is not part of the gamma tubulin ring complex). Moreover, lack of Gamma tubulin and GCP2, 3, 4, 5, and 6 would be very surprising as this complex typically is used to nucleate microtubules in species whether or not they have MTOCs. But, more to the point, the presence or absence of the gamma-turc complex is a separate question from whether or not cells display centrosomes. The authors should clarify exactly what they mean here and ensure that the citations are what they intend.

Minor Point 4: The manuscript would benefit from copy editing for clarity. In particular, the sentence beginning on Line 344 is very confusing.

Minor Point 5: The cells in the panels of Fig. 2A are too small. Over half of each image could be cropped, and the remaining portion enlarged to allow the reader to see the dividing cell. Also, a time point before the cells round up should be included. Finally, the most common term is alpha-tubulin (not tubulin-alpha).

Minor Point 6: Fig. 2C axis units should be %age of cells in mitosis (the methods indicate that 100 cells were analyzed per time point).

Minor Point 7: Fig. 6: A, right panel AND Fig 6 B: These charts are not intuitive, nor are they well described in the figure legend. These panel need to be redesigned to be understandable and/or the figure legend written to walk the reader step-by-step through what is contained in the panel.

Minor Point 8: Fig 6C: the three colors are too close in hue to be easily discerned.

Reviewer #4: PGENETICS-D-19-01130 Perez-Posada et al.

The authors present a beautiful cell-cycle analysis of the unicellular, non-model organism Capsaspora owczarzaki, a species related to animal cells. They developed a synchrony/release time-series protocol using HU as a synchronization agent and analyzed cell-cycle progression by microscopy, flow cytometry, and RNA-seq. The punchline of the study from the abstract, summary and text appears to be that C. owczarzaki is likely an intermediate between yeasts and animal cells where orthologs of cyclins A, E, and B are binding to a single CDK. As well, the authors suggest that the cell cycle transcriptional program in C. owczarzaki is more similar to humans than yeasts.

The data presented are beautiful and are a very welcome addition to the burgeoning collection of high quality cell-cycle-time-series data in the community. However, a punchline that C. owczarzaki is an intermediate species with cyclin A, B, and E orthologs but only one CDK is a bit confusing, as that evidence comes largely from genome sequence data, and not the transcriptome (or microscopy/cytometry) data presented. Expansion of the CDK genes in animal cell lineages could also be observed directly from genome sequence. Thus, the major conclusion stemming from the transcriptome data analysis seems to be that the cell-cycle transcriptional program is more similar to humans than yeast. Comparing these programs is an important and difficult task as the underlying gene regulatory networks controlling the program in yeast has been suggested to function as the central cell-cycle oscillator. As presented, the conclusion that the program is more similar to humans is not obvious and needs to be specified further. As well, it is not clear that the conclusion is robust to the analytical methods, so some sensitivity testing should be done.

Specific comments:

1) On line 422 the authors state; “Overall, our cross-species comparison of the periodic gene expression programs revealed that the Capsaspora periodic gene expression program is more similar to human cells that to current unicellular model systems for the cell cycle…”. It is not clear what the authors mean by “more similar”. What precisely is the similarity metric they are using? Number of orthologs? Number of periodic orthologs? Ordering of orthologous genes? Number of genes in each cluster?

There are numerous comparisons one could make, especially in higher dimensions. These metrics need to be specified. Any metric that involves making calls on orthologs or making calls on periodic gene lists may be sensitive to the choices made by the methods. Thus, care needs to be made to test the sensitivity of these calls (See below).

The authors reference the work of Buchler, Skotheim, and Cross, who discovered that although the sequences of the genes making up the gene regulatory network controlling cell cycle transcription are unrelated in yeast and humans, the network topology is identical. This finding should be discussed as it suggests an additional way to measure evolutionary similarity beyond sequence homology.

2) There is no clear or obvious way to define cell-cycle regulated genes. There are many algorithmic methods that produce rank-ordered lists using a variety of definitions of “periodic”. The tricky part is always setting a sensible cut-off because these lists tend not to be bimodal (cell-cycle-regulated and not cell-cycle-regulated). The authors set a cut-off for their comparisons at 10% of the total genome, and it seems like this could influence their measure of periodic orthology. For the S. cerevisiae, the estimates of multiple studies suggest that ~ 20% of the genome appears to be under substantial cell cycle control. It makes sense that a single cell organism may have a greater part of its genome dedicated to cell division. The authors should broaden that cut-off and once the define similarity metrics precisely, they can ask whether their conclusions are robust to the choice of the size of the periodic gene sets they are querying.

3) Although there is no right or wrong way to define a periodic gene set, the method used by the authors is somewhat confusing. JTK cycle requires the user to input an expected period length or range of period lengths. Although I have no experience with RAIN, it appears it has a similar requirement. In Figures 1, 3, and 4 the authors make the case for the fact that in the 13.25-hour time-series experiment, they see cells return to the initial G1 (G1/S) state (By the way, the flow cytometry data says 13.25 in figure1 and Figure 4a the RNA-seq data says 13.15). The return to G1 can be observed in the flow cytometry data (Fig. 1) and the RNA-seq data (Fig. 4), arguing the cell-cycle period is in the 13-hour range. Yet, in the JTK analysis, the authors used a range of periods from 14 to 16 hours, and for the RAIN algorithm, they used a period of 16 hours. The authors need to justify these choices as they do not fit the data presented. Again, they should demonstrate that their choice of periods does not influence their final conclusions.

4) I don’t have the expertise to evaluate their methods for making calls on orthology, but it also seems like a complex and tricky business that could substantially influence the conclusions.

5) There is growing evidence that evolutionary distance or mechanism can be determined simply by orthology is short-sighted. Given the findings of Buchler, Skotheim, and Cross on the evolution of cell cycle transcription in humans and fungal lineages, it would be nice to see the work presented here in a broader context. Are there E2F/SBF/MBF and Rb/Whi5 orthologs? Any evidence they are controlling G1/S transcription or acting in similar network motifs?

Small comments:

On line 225, the authors state; “ we confirmed that top-ranked genes showed oscillatory behavior”. How exactly was oscillatory behavior confirmed? I’m guessing it was visual inspection? The eyeball test is certainly a legitimate method for checking, but whatever the method is should be specified.

For Figure 4A, the authors show normalized expression values. From the description in the methods I think what they are presenting is a Z-score. If it is, it should be labeled as such in the figure. If it’s not, then some rationale for the normalization method should be stated.

**********

Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Genetics data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

Decision Letter 1

Bret Payseur, Joseph Heitman

23 Dec 2019

Dear Iñaki,

We are pleased to inform you that your revised PLOS Genetics manuscript entitled "Cell cycle transcriptomics of Capsaspora provides insights into the evolution of cyclin-CDK machinery" has been editorially accepted for publication in PLOS Genetics. Congratulations!  The manuscript was reviewed again by the same three reviewers who reviewed the original version, and all three found the revised version to be acceptable as submitted with no further revisions.  We very much appreciate your careful attention to detail and responsiveness in the revised manuscript. All three reviewers also commented on the importance of the work, and the quality.

Before your submission can be formally accepted and sent to production you will need to complete our formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Please note: the accept date on your published article will reflect the date of this provisional accept, but your manuscript will not be scheduled for publication until the required changes have been made.

Once your paper is formally accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you’ve already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosgenetics@plos.org.

In the meantime, please log into Editorial Manager at https://www.editorialmanager.com/pgenetics/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production and billing process. Note that PLOS requires an ORCID iD for all corresponding authors. Therefore, please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field.  This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager.

If you have a press-related query, or would like to know about one way to make your underlying data available (as you will be aware, this is required for publication), please see the end of this email. If your institution or institutions have a press office, please notify them about your upcoming article at this point, to enable them to help maximise its impact. Inform journal staff as soon as possible if you are preparing a press release for your article and need a publication date.

Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Genetics!  We thank you for entrusting your best work with us, and look forward to future submissions from you as your research program in this exciting field continues to advance.

All best wishes for the holidays!

Yours sincerely,

Joe

Joseph Heitman, MD, PhD

Associate Editor

PLOS Genetics

Bret Payseur

Section Editor: Evolution

PLOS Genetics

www.plosgenetics.org

Twitter: @PLOSGenetics

----------------------------------------------------

Comments from the reviewers (if applicable):

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Great revision. Authors addressed my critiques with extra experiments, analysis, and rewriting sections of the manuscript.

Reviewer #2: The authors have improved the manuscript and toned down the evolutionary speculation, which was my major concern.

Reviewer #3: In this revised version of their manuscript, the authors have addressed all of the major and minor points I had raised about the first version of the paper, and also addressed most points raised by other referees. The result is an interesting contribution from an emerging model system with insights supported by the evidence and methods that should allow for the work to be built up on by other laboratories.

**********

Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Genetics data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

----------------------------------------------------

Data Deposition

If you have submitted a Research Article or Front Matter that has associated data that are not suitable for deposition in a subject-specific public repository (such as GenBank or ArrayExpress), one way to make that data available is to deposit it in the Dryad Digital Repository. As you may recall, we ask all authors to agree to make data available; this is one way to achieve that. A full list of recommended repositories can be found on our website.

The following link will take you to the Dryad record for your article, so you won't have to re‐enter its bibliographic information, and can upload your files directly: 

http://datadryad.org/submit?journalID=pgenetics&manu=PGENETICS-D-19-01130R1

More information about depositing data in Dryad is available at http://www.datadryad.org/depositing. If you experience any difficulties in submitting your data, please contact help@datadryad.org for support.

Additionally, please be aware that our data availability policy requires that all numerical data underlying display items are included with the submission, and you will need to provide this before we can formally accept your manuscript, if not already present.

----------------------------------------------------

Press Queries

If you or your institution will be preparing press materials for this manuscript, or if you need to know your paper's publication date for media purposes, please inform the journal staff as soon as possible so that your submission can be scheduled accordingly. Your manuscript will remain under a strict press embargo until the publication date and time. This means an early version of your manuscript will not be published ahead of your final version. PLOS Genetics may also choose to issue a press release for your article. If there's anything the journal should know or you'd like more information, please get in touch via plosgenetics@plos.org.

Acceptance letter

Bret Payseur, Joseph Heitman

4 Mar 2020

PGENETICS-D-19-01130R1

Cell cycle transcriptomics of Capsaspora provides insights into the evolution of cyclin-CDK machinery

Dear Dr Ruiz-Trillo,

We are pleased to inform you that your manuscript entitled "Cell cycle transcriptomics of Capsaspora provides insights into the evolution of cyclin-CDK machinery" has been formally accepted for publication in PLOS Genetics! Your manuscript is now with our production department and you will be notified of the publication date in due course.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript.

Soon after your final files are uploaded, unless you have opted out or your manuscript is a front-matter piece, the early version of your manuscript will be published online. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting PLOS Genetics and open-access publishing. We are looking forward to publishing your work!

With kind regards,

Kaitlin Butler

PLOS Genetics

On behalf of:

The PLOS Genetics Team

Carlyle House, Carlyle Road, Cambridge CB4 3DN | United Kingdom

plosgenetics@plos.org | +44 (0) 1223-442823

plosgenetics.org | Twitter: @PLOSGenetics

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Capsaspora owczarzaki doubling time.

    A: Cell density curve (optical density, OD = 600 nm) at different cell concentrations of Capsaspora (three replicates per condition). Values of cell concentration around OD600 = 0.1 were used to seed cultures and calculate the doubling time of Capsaspora in B. B: Growth curve (logarithmic scale) of non-synchronized Capsaspora cell cultures (three replicates). Doubling time is calculated from three independent replicates.

    (TIF)

    S2 Fig. Conservation of microtubule organizing proteins in unicellular Holozoa.

    Presence/absence matrix of the animal and yeast microtubule organizing proteins across Salpingoeca rosetta (Sros), Monosiga brevicolis (Mbre), Ministeria vibrans (Mvib), Capsaspora owczarzaki (Cowc), Creolimax fragrantissima (Cfra), Sphaeroforma arctica (Sarc), Corallochytrium limacisporum (Clim), Saccharomyces cerevisiae (Scer), Neurospora crassa (Ncra), and Dictyostelium discoideum (Ddis). List of proteins from Carvalho-Santos et al., 2011, Hodges et al., 2010, and Uniprot. Classification adapted from Carvalho-Santos et al., 2011, and Hodges et al., 2010.

    (TIF)

    S3 Fig. Computational pipeline used to detect periodic genes in Capsaspora.

    A: Pipeline for ranking the transcripts on each experiment. RNA reads were processed using Kallisto, noise transcripts were filtered out, and JTK and RAIN were run in parallel with the indicated setup. Bonferroni-corrected p-values were ranked, and the sum of ranks was used as a final rank. B: Pipeline used to detect periodic transcripts in Capsaspora. Samples were treated separately to detect periodic transcripts with a loose cutoff. This gene set was used to filter periodic genes ranked from an average dataset of the two replicates, out of which the top 800 (10% of the number of genes in Capsaspora) were selected.

    (TIF)

    S4 Fig. Clustering of time points of each replicate and the unsynchronized culture sampled as a control, based on a dissimilarity matrix of Pearson correlation.

    All the genes with an average expression level above 1 tpm in both replicates were used.

    (TIF)

    S5 Fig. Reproducibility and informative value of Capsaspora periodic genes.

    A: Distributions of Pearson correlation between replicates of a set of randomly chosen 801 genes and the 801 genes defined as periodic. B: Fraction of variance explained by the different relative eigenvalues of the principal coordinate analysis (see Fig 3D).

    (TIF)

    S6 Fig. Details on the hierarchical clustering of Capsaspora periodic genes.

    A: Hierarchical clustering of the expression profiles of the 801 periodic genes found in Capsaspora, and the color equivalences with the final clusters shown at Fig 4A. B: Average expression level of Capsaspora periodic genes grouped by hierarchical clustering. C: t-SNE plot of all 801 genes in the periodic transcriptional program of Capsaspora, showing circle pattern as in Fig 3D. Color code in both figures follows the color code in Fig 4.

    (TIF)

    S7 Fig. K-means clustering of the periodic transcriptional program of Capsaspora.

    A: Average expression level of Capsaspora periodic genes grouped by k-means clustering. B: Top ten enriched GO terms of each cluster of periodic genes generated by k-means clustering. GO terms were considered significant when Bonferroni-corrected p-value was lower than 0.05. Full list available at S3 Fig. C: Agreement between clustering methods. Heatmap showing the percentage of overlap between clusters by two methods. Overlap is calculated as the number of genes belonging to the same pair of clusters divided by the size of the smallest cluster in the pair.

    (TIF)

    S8 Fig. Unrooted maximum likelihood phylogenetic tree (IQ-TREE) inferred from cyclins sequences of 30 eukaryotic species (see Methods).

    Nodal support values (1000- bootstrap replicates by UFBoot) are shown in all nodes. Eukaryotic sequence names are abbreviated with the four-letter code (see Methods) and colored according to their major taxonomic group (see panel).

    (PDF)

    S9 Fig. Maximum likelihood phylogenetic tree (IQ-TREE) inferred from CDK sequences of early-branching holozoan species and animals (see Methods).

    Statistical support values (1000-replicates UFBoot) are shown in all nodes. Eukaryotic sequence names are abbreviated with the four-letter code (see Methods) and colored according to their major taxonomic group (see panel).

    (PDF)

    S10 Fig. Re-annotation of the coding sequence of Capsaspora CDK1/2/3.

    A: Schematic representation of the genomic locus of Capsaspora CDK1-3 gene showing exons, splicing sites, non-annotated regions of predicted sequence, and mapping of mRNA reads. B: PCR amplifications of Capsaspora CDK1 using primers detailed in Methods and A, using genomic DNA and cDNA as templates. Arrows indicate size of the products sent for sequencing. C: Alignment of H. sapiens and S. cerevisiae CDK1 genes, and the Capsaspora updated CDK1-3 sequence, using Geneious v8.1.9.

    (TIF)

    S11 Fig. Expression of cyclins and CDKs in Capsaspora.

    A: Gene expression profile of cyclin G/I and an unidentified cyclin gene (CAOG_01199) found in Capsaspora. B: Total amount of Capsaspora CDK1/2/3 throughout the cell cycle. C: Dynamics of the cyclin-CDK system using real-time PCR. Normalized gene expression profiles of cyclins B, E, and CDK1/2/3 in two independent biological replicates of synchronized Capsaspora cultures.

    (TIF)

    S12 Fig. List of all enriched GO terms of the core cell cycle regulated gene set from each species used in Fig 6B.

    (PDF)

    S13 Fig. Analysis of the periodic transcriptional program of Capsaspora using a cutoff of 20% of the total transcriptome.

    A: Scatter plot replicating Fig 3B, showing in blue all the genes additionally taken into account. Colored dots represent the 1600 genes that were finally taken as periodic in this reanalysis. B: Principal coordinate analysis using the dataset of 1600 genes. C: heatmap of gene expression level depicting six clusters detected by Euclidean distance hierarchical clustering. Clusters were rearranged to visually represent their expression peaks over time. Black arrow and dividing cell indicate time of cell division (see Fig 2). D: Gene ontology enrichment analysis of the six clusters represented in C. E: Bar plots indicating the amount of shared periodic orthogroups and/or periodic one-to-one orthologues between pairs of cell types or species, using the dataset of 1600 periodic genes in Capsaspora.

    (TIF)

    S14 Fig. Reanalysis of previous cell cycle datasets in model organisms.

    A: Scatter plots of ranks by JTK and RAIN for each dataset of each species used in the comparative analysis (see Fig 6D and Results section). Datasets were processed as indicated in S15 Text, and Material and methods. Depending on the dataset, we could recover between one third and more than half of the originally described periodic genes, except Arabidopsis where the agreement was very low. B: Bar plots indicating the amount of shared periodic orthogroups and/or periodic one-to-one orthologues between pairs of cell types or species, using our own lists of periodic genes. P-values of all the binomial tests are provided in S17 Text.

    (TIF)

    S15 Fig. A possible reconstruction of the evolution of the cyclin-CDK system regulating the cell cycle in animals.

    Phylogenetic tree of eukaryotes displaying the different expansions, gains and losses of the main cyclin and CDK subfamilies with a known role in cell cycle regulation, in different eukaryotic groups. Events within groups refers to some species within the group showing additional expansions, gains or losses beside those depicted in the figure. Note that LECA cyclin G/I likely gave rise to plant cyclin D and share a common ancestor to the metazoan cyclins D and G/I. Gain of other cyclin families are depicted as regular letters at different stems.

    (TIF)

    S1 Text. FASTA formatted sequences of human and yeast MTOC proteins used as query in S2 Fig.

    (FASTA)

    S2 Text. FASTA formatted sequences of the putative MTOC proteins from the organisms shown in S2 Fig.

    (FASTA)

    S3 Text. Tables of BLAST matches of human and yeast MTOC proteins in the proteomes of the organisms shown in S2 Fig.

    (TXT)

    S4 Text. Tables of transcript per million of each replicate.

    (TSV)

    S5 Text. List of periodic genes in Capsaspora, containing information for each gene about cluster membership, gene age, and orthologs in other species.

    (TSV)

    S6 Text. List of significant (Bonferroni p-value < 0.05) GeneOntology enrichments of each hierarchical cluster of periodic genes in Capsaspora.

    (XLSX)

    S7 Text. FASTA formatted sequences of cyclins and CDKs used in the phylogenetic analyses (see S8 and S9 Figs).

    (FASTA)

    S8 Text. List of species used in the phylogenetic analyses and in the generation of groups of orthologues.

    (XLSX)

    S9 Text. FASTA formatted sequences of the primers used in the sequencing of CDK1 and in the qPCR experiments.

    (FASTA)

    S10 Text. FASTA formatted sequences of newly annotated Capsaspora CDK1-2-3 CDS and protein translation.

    (FASTA)

    S11 Text. Data from the qPCR experiments.

    (XLSX)

    S12 Text. List of cell cycle regulators in humans (described in [32,44,45,93]), and their respective orthologs in Capsaspora defined by OrthoFinder and/or phylome data (see Results and Methods).

    Bold indicates genes that have been plotted in Fig 5C or 5D.

    (XLSX)

    S13 Text. List of cell cycle regulators in humans (described in [32,44,45,93]), that also have at least one periodic co-ortholog in Capsaspora, defined by OrthoFinder (see Results and Methods).

    (XLSX)

    S14 Text. Metrics of gene age enrichment and depletion for the gene clusters of the periodic transcriptional program of Capsaspora, and their corresponding Fisher Test p-values.

    (XLSX)

    S15 Text. Procedure used to retrieve identifiers for the datasets of H. sapiens, S. cerevisiae, S. pombe, and A. thaliana, and parameters used to set up JTK_CYCLE and RAIN in the reanalysis.

    (XLSX)

    S16 Text. Metrics of shared periodic orthogroups (OG) and one-to-one orthologues between Capsaspora and the rest of cell types and species.

    (XLSX)

    S17 Text. Metrics of shared periodic orthogroups (OG) for all comparisons between pairs of species, using periodic genes from the literature and using our own sets of periodic genes.

    (XLSX)

    S18 Text. GO enrichment of human, yeasts, plants and Capsaspora gene sets belonging to the core conserved set of orthogroups in Fig 6B.

    (TXT)

    S19 Text. List of Capsaspora genes belonging to the core set of periodic orthogroups in Fig 6B, annotated using eggNOG (See Methods).

    (TXT)

    S1 Video. Synchronized cells of Capsaspora undergoing cell division.

    Time interval between frames is 1 minute. The movie is played at 7fps. Scale bar = 5μm. Available on Figshare: https://figshare.com/s/4d642c9854efe6d879a7.

    (AVI)

    Attachment

    Submitted filename: 20191128_REVIEWERS_COMMENTS.docx

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files. RNAseq reads are deposited in the Gene Expression Omnibus (GEO) under the accession number GSE141156 and will be available after acceptance. The Supporting Information files are also available from figshare: https://figshare.com/s/4d642c9854efe6d879a7.


    Articles from PLoS Genetics are provided here courtesy of PLOS

    RESOURCES