Indirect development with an intermediate larva exists in all major animal lineages1, which makes larvae central to most scenarios of animal evolution2,3,4,5,6,7,8,9,10,11. Yet how larvae evolved remains disputed. Here we show that temporal shifts (that is, heterochronies) in trunk formation underpin the diversification of larvae and bilaterian life cycles. We performed chromosome-scale genome sequencing in the annelid Owenia fusiformis with transcriptomic and epigenomic profiling during the life cycles of this and two other annelids. We found that trunk development is deferred to pre-metamorphic stages in the feeding larva of O. fusiformis but starts after gastrulation in the non-feeding larva with gradual metamorphosis of Capitella teleta and the direct developing embryo of Dimorphilus gyrociliatus. Accordingly, the embryos of O. fusiformis develop first into an enlarged anterior domain that forms larval tissues and the adult head12. Notably, this also occurs in the so-called ‘head larvae’ of other bilaterians13,14,15,16,17, with which the O. fusiformis larva shows extensive transcriptomic similarities. Together, our findings suggest that the temporal decoupling of head and trunk formation, as maximally observed in head larvae, facilitated larval evolution in Bilateria. This diverges from prevailing scenarios that propose either co-option9,10 or innovation11 of gene regulatory programmes to explain larva and adult origins.
Many animal embryos develop into a larva that metamorphoses into a sexually competent adult1. Larvae are morphologically and ecologically diverse, and given their broad phylogenetic distribution, they are central to major scenarios of animal evolution2,3,4,5,6,7,8,9,10,11. However, these scenarios dissent on whether larvae are ancestral2,3,4,5,6 or secondarily evolved9,10, and on the mechanisms that facilitated the evolution of larvae2,9,10,11. Therefore, larval origins—and their importance to explain animal evolution—are still contentious.
The trochophore is a widespread larval type characterized by an apical sensory organ and a pre-oral locomotive ciliary band18 that is typically assigned to Annelida and Mollusca. Annelids, however, show diverse life cycles and larval morphologies, including species with direct and indirect development and either planktotrophic or lecithotrophic larvae19. Notably, the groups Oweniidae and Magelonidae—which form Oweniida, the sister taxon to all other annelids20—have distinctive planktotrophic larvae (Fig. 1a and Extended Data Fig. 1a). In particular, the larva of Oweniidae, referred to as ‘mitraria’12, has an enlarged pre-oral region and a bundle of posterior chaetae, as well as a pair of nephridia and a long monociliated ciliary band similar to those of phylogenetically distant larvae of echinoderms and hemichordates21,22. Yet oweniids show many developmental characteristics that are considered ancestral to Annelida and even Spiralia as a whole23,24, including similarities in larval molecular patterns with other trochophore and bilaterian larvae22,23,25,26. Therefore, the diversity of life cycles and larval forms but generally conserved early embryogenesis and adult body plans of Annelida is an excellent model to investigate how larval traits evolve. It is also an ideal model to formulate and assess hypotheses on the origin of larvae and animal life cycles.
O. fusiformis has a conserved genome
To investigate how larvae evolved in Annelida, we first generated a chromosome-scale reference assembly for the oweniid O. fusiformis (Fig. 1b, inset). The haploid assembly spans 505.8 Mb and has 12 chromosome-scale scaffolds (Supplementary Fig. 1). Almost half of the assembly (43.02%) consists of repeats (Extended Data Fig. 1b,c), and we annotated 26,966 protein-coding genes and 31,903 transcripts, which represent a nearly complete (97.5%) set of metazoan BUSCO genes (Supplementary Fig. 1). Gene family reconstruction and gene content analysis nested O. fusiformis with other non-annelid spiralians and taxa with slow-evolving genomes (Fig. 1b and Extended Data Fig. 1d,e). This result provides evidence that O. fusiformis has fewer gene family gains and losses and retains more ancestral metazoan orthogroups than other annelid taxa (Fig. 1c and Extended Data Fig. 1f,g). Indeed, O. fusiformis has a chordin orthologue, a bone morphogenetic protein inhibitor involved in dorsoventral patterning thought to be lost in annelids27 and is asymmetrically expressed around the blastopore of the gastrula and larval mouth in O. fusiformis (Extended Data Fig. 2). Moreover, O. fusiformis has globally retained the ancestral bilaterian linkage, exhibiting chromosomal fusions that are present in molluscs and even nemerteans, and fewer lineage-specific chromosomal rearrangements than other annelids (Fig. 1d and Extended Data Fig. 1h,i). Therefore, O. fusiformis shows a more complete gene repertoire and ancestral syntenic chromosomal organization than other annelids. Together with its phylogenetic position and conserved early embryogenesis23,24, O. fusiformis is a key lineage to reconstruct the evolution of Annelida, and of Spiralia generally.
Heterochronies in gene expression
Next, we sought to identify transcriptomic changes that underpin the distinct life cycles in Annelida. We compared temporal series of embryonic, larval and competent and juvenile transcriptomes of O. fusiformis and C. teleta, two indirect developers with planktotrophic and lecithotrophic28 larvae, respectively, and D. gyrociliatus, a direct developer29,30 (Fig. 2a). Transcriptional dynamics during early embryogenesis were overall similar among these species (Supplementary Fig. 3). C. teleta and D. gyrociliatus showed increasing transcriptomic divergence with each other as they develop into adult stages; however, the maximal transcriptomic divergence between these annelids and O. fusiformis occurred at the mitraria stage (Extended Data Fig. 3a,b). Soft clustering of all expressed transcripts produced 12 distinct groups of temporally co-regulated genes in O. fusiformis and C. teleta, and 9 clusters in D. gyrociliatus (Extended Data Fig. 3c–e), which were expressed gradually along the life cycle of all three species. Only one cluster in each species showed a bimodal activation at early embryogenesis and in the competent larva (juvenile or adult forms), consistently involving genes enriched for core cellular processes (Extended Data Fig. 3f). Indeed, translation and metabolism predominated in clusters of early development in the three annelids, whereas cell communication and signalling, morphogenesis and organogenesis were enriched in later stages of development (Extended Data Fig. 3f). Therefore, regardless of the life cycle, transcriptional dynamics are generally conserved during annelid development, yet adults and the planktotrophic larva are the most transcriptionally distinct stages.
To identify the genes that mediate the transcriptional differences at larval and adult stages, we performed pairwise inter-species comparisons of gene and transcription factor composition among clusters of temporally co-regulated genes (Fig. 2b,c and Extended Data Fig. 4a,b). Early clusters followed by late clusters were the most conserved in the three comparisons when all genes were considered (Extended Data Fig. 4c,d). However, transcription factors used in post-larval stages in indirect development were consistently shifted towards early embryogenesis in direct development (Fig. 2c and Extended Data Fig. 4c,e). In both O. fusiformis and C. teleta, this shift involved 28 transcription factors that function in various developmental processes, from nervous system (for example, pax6 (ref. 31)) and mesoderm (for example, foxF (ref. 26)) formation to axial patterning (for example, Hox1 and Hox4 (ref. 32)) (Supplementary Fig. 12). Notably, the overall expression of these 28 genes was also temporally shifted between indirect developing annelids, with the maximum level of expression occurring earlier in C. teleta than in O. fusiformis (Fig. 2d). Additionally, 2,583 genes also exhibited temporal shifts between the larvae of O. fusiformis and C. teleta (Fig. 2e), including 105 transcription factors, but mostly enzymes and structural genes that probably reflect the different biology of these two larvae (Extended Data Fig. 4f,g and Supplementary Figs. 13–16). Therefore, temporal shifts (that is, heterochronies) in the use of shared genetic programmes and regulatory genes correlate with and might account for life cycle and larval differences in Annelida.
Different timings of trunk development
Homeodomain transcription factors were the largest class among the 28 transcription factors with temporal expression shifts between direct and indirect developing annelids (Supplementary Fig. 12). Indeed, homeodomain genes were enriched in the competent larva in O. fusiformis but were prevalent from stage 5 larva onwards in C. teleta (Extended Data Fig. 4h). Accordingly, Hox genes, which regionalize the bilaterian trunk along the anteroposterior axis33, were strongly upregulated in the competent mitraria larva (Extended Data Fig. 5a,b). O. fusiformis had a conserved complement of 11 Hox genes—similar to C. teleta32—arranged as a compact, ordered cluster in chromosome 1, except for Post1, which was located downstream of this chromosome (Extended Data Fig. 5c,d). C. teleta and D. gyrociliatus started expressing Hox genes along their trunks30,32 during or soon after gastrulation (Extended Data Fig. 5e). O. fusiformis, however, did not express Hox genes during embryogenesis but in the trunk rudiment during larval growth, already in an anteroposterior staggered pattern, as later observed in the juvenile (Fig. 3a and Extended Data Fig. 5e–h). This late activation of Hox genes is not specific to O. fusiformis, as it also occurs for most Hox genes in the planktotrophic trochophore of the echiuran annelid Urechis unicinctus34 (Extended Data Fig. 5e). Therefore, the spatially collinear Hox code along the trunk is established at distinct developmental stages depending on the life cycle mode in Annelida.
To determine whether the difference in timings of trunk patterning is limited to the expression of Hox genes, we used tissue-specific adult transcriptomes to define a set of 1,655 anterior and 407 posterior and trunk genes in O. fusiformis (Extended Data Fig. 6a–d). Anterior genes were significantly more expressed during embryogenesis, whereas posterior and trunk genes were upregulated at the mitraria stage and significantly outweighed the expression dynamics of anterior genes from that stage onwards (Fig. 3b and Extended Data Fig. 6e,f). Moreover, anterior, trunk and posterior genes with spatially resolved expression followed different temporal dynamics in O. fusiformis, C. teleta and D. gyrociliatus. In O. fusiformis, trunk25 and posterior24,26 genes were concentrated in a small ventral area and around the anal opening of the larva and increased in spatial range and expression levels as the trunk formed (Extended Data Fig. 6g,h). By contrast, anterior genes26,35 patterned most of the mitraria, and their expression remained stable during development (Extended Data Fig. 6g,h). Posterior and anterior genes followed similar dynamics in C. teleta, and trunk genes were upregulated already post-gastrula in both C. teleta and D. gyrociliatus (Extended Data Fig. 6i–l). Therefore, trunk development, which initially occurs from lateral growth of the trunk rudiment12,28, is deferred to pre-metamorphic stages in planktotrophic annelid trochophores compared with annelids with lecithotrophic larvae and direct developers.
Heterochronies in Hox regulation
To investigate the genomic regulatory basis for the heterochronies in trunk development among annelid larvae, we profiled open chromatin regions at five equivalent developmental stages in O. fusiformis and C. teleta (Fig. 2a). This analysis identified 63,726 and 44,368 consensus regulatory regions, respectively. In both species, open chromatin was more abundant within gene bodies (Extended Data Fig. 7a). There was, however, a general increase in promoter peaks in O. fusiformis and distant intergenic regulatory elements in both species during development (Extended Data Fig. 7b). Moreover, the largest changes in peak accessibility occurred in the mitraria in O. fusiformis and stage 5 larva in C. teleta (Supplementary Fig. 18). In O. fusiformis, most regulatory regions acted before the start of trunk formation, whereas the numbers of accessible regions with a maximum of accessibility before and after the onset of trunk development were comparable in C. teleta (Extended Data Fig. 7c). Accordingly, the regulation of genes involved in morphogenesis and organogenesis, as well as neurogenesis, was concentrated in late clusters in O. fusiformis but unfolded more continuously in C. teleta (Supplementary Fig. 23). Therefore, different dynamics of chromatin accessibility occur during development and larva formation in these two annelids.
To investigate the regulatory programmes controlling larva development in O. fusiformis and C. teleta, we predicted transcription factor-binding motifs on peaks obtained from ATAC-seq data. This analysis identified 33 motifs common to both species that were strongly assigned to a known transcription factor class (Supplementary Fig. 29). Notably, the binding dynamics of these 33 motifs revealed a temporal shift in regulatory motifs acting between the mitraria and competent larva in O. fusiformis to the early post-gastrula (stage 4tt) larva of C. teleta (Fig. 3c and Extended Data Fig. 7d–f). Seven motifs followed this pattern (Extended Data Fig. 7g and Supplementary Fig. 29), including one with high similarity to the human HOX, CDX and EVX motif archetype (Fig. 3d,e) that is overrepresented and upregulated on the basis of its binding score at the competent stage in O. fusiformis (Extended Data Fig. 7h and Supplementary Fig. 30). Indeed, motif-binding dynamics in regulatory elements assigned to Hox genes supported a change in global regulation of the Hox cluster at the competent and early larval stages in O. fusiformis and C. teleta, respectively (Fig. 3f and Supplementary Fig. 31), which mirrored the transcriptional onset of these genes and the start of trunk development in the two species32. Motifs assigned to NKX and GATA factors, which are expressed in the developing trunk in both species25,36, were among the most abundant bound motifs in the Hox cluster in both species (Extended Data Fig. 7i). However, only 39 one-to-one orthologues with bound HOX, CDX and EVX motifs at the maximum of motif binding were common to O. fusiformis and C. teleta (Extended Data Fig. 7j). Therefore, different regulatory dynamics of the Hox cluster—possibly triggered by a reduced common set of upstream regulators—underpin temporal variability in Hox activity and downstream targets. These shifts probably promoted the developmental and morphological differences in trunk formation between planktotrophic and lecithotrophic annelid larvae.
Different dynamics of new genes
New, species-specific genes, which account for a significant proportion of some larval transcriptomes6,37, could also contribute to and explain the transcriptomic differences among annelid larvae. In O. fusiformis, C. teleta and D. gyrociliatus, genes of metazoan and pre-metazoan origin tended to peak, dominate and be enriched at early development, whereas younger genes were more highly expressed in competent and juvenile stages (Extended Data Fig. 8a–e). By contrast, species-specific genes followed lineage-specific dynamics (Supplementary Fig. 32). These genes, for instance, were more expressed in the juveniles of O. fusiformis and D. gyrociliatus, but in the blastula and gastrula of C. teleta (and to some extent also at the blastula stage in O. fusiformis; Extended Data Fig. 8a,c,d). Species-specific genes were only enriched and over-represented at larval stages in C. teleta (Extended Data Fig. 8f–h). Therefore, genes of different evolutionary origins contribute to the development of annelid larvae. This result suggests that the increased use of new genes in some lophotrochozoan larvae6,37 might be due to the evolution of lineage-specific larval traits.
Similarities between bilaterian larvae
To assess whether the transcriptional dynamics found in annelids are also observed in other metazoans, we extended our comparative transcriptomic approach to nine other animal lineages. In relative terms, global transcriptional dynamics between O. fusiformis and other animals tended to be more dissimilar at early development than at juvenile and adult stages (Fig. 4a and Extended Data Figs. 9a,b and 10a). The exception was the direct developer Danio rerio, for which the mitraria larva was the most dissimilar stage (Fig. 4a). This was also the case when comparing O. fusiformis with the direct-developing annelid D. gyrociliatus (Extended Data Fig. 3b). Notably, O. fusiformis shared maximal transcriptomic similarities during larval phases with bilaterian species with planktotrophic ciliated larvae and even cnidarian planulae (Fig. 4a and Extended Data Fig. 9a–e). Genes involved in core cellular processes directly contributed to these similarities, which probably reflects common structural and ecological needs of metazoan larvae (Extended Data Fig. 9f,g). However, transcription factor expression levels were also maximally similar between those species at larval phases (Extended Data Fig. 9a,b,e). Therefore, adult development is generally more similar9 than early embryogenesis across major animal lineages, but phylogenetically distant animal larvae also exhibit unexpected genome-wide transcriptional—and potentially regulative—similarities.
Our study provides a perspective on life cycle evolution in Bilateria. The planktotrophic larva of O. fusiformis defers trunk differentiation to late pre-metamorphic stages and largely develops from anterior ectodermal domains. This occurs in other feeding annelid larvae38 (Extended Data Fig. 5f), and probably in Chaetopteriformia39,40, and thus the late differentiation of the adult trunk might be an ancestral trait to Annelida (Extended Data Fig. 10b). Delaying trunk development to post-larval stages also occurs in phylogenetically distant clades within Spiralia16,17, Ecdysozoa14,41 and Deuterostomia15,42,43, the larvae of which are generally referred to as head larvae13,14. By contrast, non-feeding larvae32,44 and direct developers30 in both Annelida and other bilaterian taxa45,46 start to pattern their trunks with or immediately after the onset of anterior or head patterning, which always takes place before gastrulation in bilaterians47,48. Therefore, heterochronies in trunk development correlate with, and possibly account for, the evolution of different life cycles in animals (Fig. 4b). This differs from previously proposed mechanisms to explain the origins of animal life cycles, namely co-option of adult genes into larval-specific regulatory programmes9,10 and independent evolution of adult gene regulatory modules2,49.
Bilaterian head larvae could be lineage-specific innovations associated with the evolution of maximal indirect development13,14,16 that evolved convergently by delaying trunk differentiation and Hox patterning (Fig. 4c). The similarities in larval molecular patterns5,15,16 would then reflect ancient gene regulatory modules that were independently co-opted to develop analogous cell types and larval organs. Alternatively, the post-embryonic onset of trunk differentiation and Hox expression might be the most parsimonious ancestral state for Bilateria (Extended Data Fig. 10c,d and Supplementary Table 93). This could have facilitated the evolution of larvae, which would then originally share anterior genetic modules for their development (Fig. 4c). Regardless of the scenario and despite their limitations, our datasets highlight the importance of heterochronic changes for the diversification of bilaterian life cycles. The data also uncover a reduced set of candidate genes and regulatory motifs that might influence life cycle differences in Annelida and perhaps even Bilateria. In the future, comparative functional studies of these and other genes will reveal how temporal changes in gene expression and regulation have shaped the evolution of animal larvae and adults.
Adult culture, spawning and in vitro fertilization
Sexually mature O. fusiformis adults were collected from subtidal waters near the Station Biologique de Roscoff and cultured in the laboratory as previously described23. In vitro fertilization and collection of embryonic and larval stages were performed as previously described23. C. teleta Blake, Grassle & Eckelbarger, 2009 was cultured, grown and sifted, and its embryos and larvae were collected following established protocols28. Magelona spp. were collected in muddy sand from the intertidal of Berwick-upon-Tweed, Northumberland, NE England (around 55° 46′00.4″ N, 1° 59′04.5″ W) and kept initially in aquaria at the Museum Wales before their transfer to Queen Mary University of London, where they were kept in aquaria with artificial sea water.
Genome size measurements
To estimate the haploid DNA nuclear content of O. fusiformis, we used a flow cytometer Partex CyFlow Space fitted with a Cobalt Samba green laser (532 nm, 100 mW) and the built-in software FloMax (v.2.82) as described for the annelid D. gyrociliatus23, with adult individuals of Drosophila melanogaster as reference. Additionally, we used Jellyfish (v.2.3)50 to count and generate a 31-mer histogram from adaptor-cleaned, short-read Illumina reads (see section below) and GenomeScope (v.2.0)51 to obtain an in silico estimation of the genome size and heterozygosity of O. fusiformis.
Genome sequencing, assembly and quality check
Ultra-high molecular weight (UHMW) gDNA was extracted following the Bionano genomics IrysPrep agar-based, animal tissue protocol using sperm from a single O. fusiformis male. UHMW gDNA was cleaned up using a salt–chloroform wash following PacBio’s recommendations before long-read sequencing using PacBio (v.3.0) chemistry at the University of California Berkeley. A total of 16 SMRT cells of PacBio Sequel were used for sequencing with 600 min movie time, producing a total of 170.07 Gb of data (10.72 million reads, N50 read length between 25.75 kb and 30.75 kb). In addition, we used UHMW gDNA of that same individual to generate a 10x Genomics linked reads library, which we sequenced in an Illumina HiSeq4000 at the Okinawa Institute of Science and Technology to produce 28.62 Gb of data (141.66 million read pairs). PacBio reads were assembled with CANU (v.8.3rc2)52 assuming ‘batOptions=”−dg 3 −db 3 −dr 1 −ca 500 −cp 50’ and ‘correctedErrorRate = 0.065’. Pacbio reads were remapped using pbalign (v.0.3.2) and the assembly polished once using Arrow (genomicconsensus, v.2.3.2). Then Illumina paired-end reads generated with the 10x Genomics linked reads were extracted, remapped using bwa mem (v.0.7.17)53 and used for polishing with Racon (v.1.16)54. Bionano Genomics optical mapping data were used to scaffold the PacBio-based assembly, which was de-haploidized with purge_haplotigs (v.1.0.4)55 setting cut-off values at 35, 85 and 70× coverage to reconstruct a high-quality haploid reference assembly. HiC-based chromosome scaffolding was performed as described below. Merqury (v.1.1)56 and BUSCO (v.5)57 were used to assess genome completeness and to evaluate the quality of the assembly (Supplementary Fig. 1).
Fourteen samples spanning key developmental time points of the O. fusiformis life cycle, including active oocyte, zygote, 2-cell, 4-cell and 8-cell stages, 3 h post-fertilization (h.p.f.), 4 h.p.f., coeloblastula (5 h.p.f.), gastrula (9 h.p.f.), axial elongation (13 h.p.f.), early larva (18 h.p.f.), mitraria larva (27 h.p.f.), pre-metamorphic competent larva (3 weeks post-fertilization) and post-metamorphic juvenile were collected in duplicates (except for the latter), flash frozen in liquid nitrogen and stored at –80 °C for total RNA extraction. Samples within replicates were paired, with each one containing around 300 embryos or 150 larvae coming from the same in vitro fertilization process. Nine further samples from adult tissues and body regions (blood vessel, body wall, midgut, prostomium, head, ovary, retractor muscle, tail and testes) were also collected as described above. Likewise, an additional five samples spanning post-cleavage time points of C. teleta, including 64 cells and gastrula stages, and stage 4tt, stage 5 and stage 7 larval stages, were collected in duplicates. Total RNA was isolated using a Monarch Total RNA Miniprep kit (New England Biolabs) following the supplier’s recommendations. Total RNA samples from developmental stages from both O. fusiformis and C. teleta were used to prepare strand-specific mRNA Illumina libraries that were sequenced at the Oxford Genomics Centre (University of Oxford, UK) over three lanes of an Illumina NovaSeq6000 system in 2 × 150 bp mode to a depth of around 50 million reads (Supplementary Tables 13 and 16). Adult tissue samples were sequenced at BGI on a BGISeq-500 platform in 2 × 100 bp mode to a depth of about 25 million reads (Supplementary Table 49).
Annotation of repeats and transposable elements
RepeatModeler (v.2.0.1)58 and RepBase were used to construct a de novo repeat library for O. fusiformis, which was then filtered for bona fide genes using the predicted proteome of C. teleta. In brief, we used DIAMOND (v.0.9.22)59 with an e-value cut-off of 1 × 10–10 to identify sequences in the de novo repeat library with significant similarity to protein-coding genes in C. teleta that are not transposable elements (TEs). Sequences with a significant hit were manually inspected to verify they were not TEs; if they were, they were manually removed from the de novo repeat library. The filtered consensus repeat predictions were then used to annotate the genome assembly of O. fusiformis with RepeatMasker open-4.0. We next used LTR_finder (v.1.07)60, a structural search algorithm, to identify and annotate long tandem repeats (LTRs). Finally, we generated a consensus set of repeats by merging RepeatMasker and LTR_finder predictions with RepeatCraft61, using default parameters but a maximum LTR size of 25 kb (as derived from the LTR_finder annotation) (Supplementary Table 1). The general feature format (GFF) and fasta files with the annotation of TEs and repeats are available in the GitHub repository (see Data availability section).
Gene prediction and functional annotation
We used SAMtools (v.1.9)62 and the annotation of repeats to soft mask O. fusiformis genome assembly before gene prediction. We then mapped all embryonic and adult transcriptomes and a publicly available dataset63 (Sequence Read Archive (SRA) identifier: SRR1222288) with STAR (v.2.5.3a)64 after removing low-quality read pairs and read pairs containing Illumina sequencing adapters with trimmomatic (v.0.39)65. StringTie (v.1.3.6)66 was used to convert STAR alignments into gene transfer format (GTF) files and Portcullis (v.1.1.2)67 to generate a curated set of splice junctions. Additionally, we generated de novo transcriptome assemblies for all samples using Trinity (v.2.5.1)68 with default parameters, which were thereafter mapped to the soft-masked assembly with GMAP (v.2020-04-08)69. We then ran the default Mikado (v.2.1) pipeline70 to merge all transcriptomic evidence and reliable splice junctions into a single set of best-supported transcripts and gene models. From this merged dataset, we filtered full-length, non-redundant transcripts with a BLAST hit on at least 50% of their length and at least two exons to obtain a gene set that we used to train Augustus (v.3.2.3)71. Simultaneously, we used the Mikado gene annotation and Portcullis splice junctions to generate confident sets of exon and intron hints, respectively. We also ran Exonerate (v.2.4.0)72 to generate spliced alignments of the proteome of C. teleta proteome on O. fusiformis soft-masked genome assembly to obtain further gene hints. We then merged all exon and intron hints into a single dataset, which we passed into Augustus (v.3.2.3)71 for ab initio gene prediction. Finally, PASA (v.2.3.3)73 was used to combine RNA-seq and ab initio gene models into a final gene set, from which spurious predictions with in-frame stop codons (228 gene models), predictions that overlapped with repeats (5,779 gene models) and that had high similarity to TEs in the RepeatPeps.lib database (2,450 models) were removed. This filtered gene set included 26,966 genes, encompassing 31,903 different transcripts (Supplementary Fig. 1). To assess the completeness of this annotation, we ran BUSCO (v.5)57 in proteome mode, which resulted in 97.7% of the core genes present. Moreover, 31,678 out of the 31,903 (99.29%) filtered transcripts were supported by RNA-seq data, and 80.69% of the transcripts had a significant BLAST match (e-value cut-off < 0.001) to a previously annotated annelid gene (database containing non-redundant proteomes of the high-quality annelid genomes of C. teleta, D. gyrociliatus, Eisenia andrei, Lamellibrachia luymesi, Paraescarpia echinospica, Riftia pachyptila and Streblospio benedicti). A similar functional annotation approach was followed to re-annotate the genome of C. teleta with the new RNA-seq data, using as starting assembly the soft-masked version available at Ensembl Metazoa. This resulted in 41,221 transcripts, 39,814 of which had RNA-seq support (96.59%). Additionally, 80.47% of the transcripts had a significant BLAST match (e-value cut-off < 0.001) to other well-annotated annelid genomes (see above).
Protein homologies for the filtered transcripts of O. fusiformis and C. teleta were annotated using BLAST (v.2.2.31+)74 with the UniProt/SwissProt database provided with Trinotate (v.3.0)75. We used HMMER (v.2.3.2)76 to identify protein domains using Trinotate’s PFAM-A database and signalP (v.4.1)77 to predict signal peptides. These functional annotations were integrated into a Trinotate database, which retrieved Gene Ontology (GO), eggNOG and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms for each transcript. In addition, we ran the PANTHER HMM scoring tool to assign a PantherDB78 orthology identifier to each transcript. In total, we retrieved a functional annotation for 22,516 transcripts (63.86%). Functional annotation reports are provided in the GitHub repository (see Data Availability section).
Sperm from a single O. fusiformis worm and an entire sexually mature male were used as input material to construct two Omni-C Dovetail libraries following the manufacturer’s recommendations for marine invertebrates. These libraries were sequenced in an Illumina NovaSeq6000 at the Okinawa Institute of Science and Technology to a depth of 229 and 247 million reads. HiC reads were processed using the Juicer pipeline (r.e0d1bb7)79 to generate a list of curated contracts (‘merged no dups’) that was subsequently used to scaffold the assembly using 3d-dna (v.180419)80. The resulting assembly and contact map were visually inspected and curated using Juicebox (v.1.11.08)79, and adjustments were submitted for a subsequent run of optimization using 3d-dna. Finally, repeats and TEs were re-annotated in this chromosome-scale assembly as described above, and the annotation obtained for the PacBio-based assembly was lifted over with Liftoff (v.1.6.1)81 (Supplementary Fig. 1). All gene models but two were successfully re-annotated in the chromosome-scale assembly.
Gene family evolution analyses
We used the AGAT suite of scripts to generate non-redundant proteomes with only the longest isoform for a set of 21 metazoan proteomes (Supplementary Table 2). To reconstruct gene families, we used OrthoFinder (v.2.2.7)82 using MMSeqs2 (ref. 83) to calculate sequence similarity scores and an inflation value of 2. OrthoFinder gene families were parsed and mapped onto a reference species phylogeny to infer gene family gains and losses at different nodes and tips using the ETE 3 library84, as well as to estimate the node of origin for each gene family. Gene expansions were computed for each species using a hypergeometric test against the median gene number per species for a given family using previously published code30 (Supplementary Tables 3–7). Principal component analysis was performed on the orthogroups matrix by metazoan lineage, given that orthogroups were present in at least three of the 22 analysed species, to eliminate taxonomically restricted genes. All single copy orthologue files derived from this analysis used throughout the study are available in the GitHub repository (see Data Availability section).
Single-copy orthologues obtained using the mutual best hit approach generated using MMseqs2 (ref. 83) using the annotations of Branchiostoma floridae85, P. maximus86, S. benedictii87 and Lineus longissimus88,89 were used to generate Oxford synteny plots comparing sequentially indexed orthologue positions. Plotting order was determined by hierarchical clustering of the shared orthologue content using the complete linkage method as originally proposed. Comparison of the karyotype of all four species was performed using the Rideogram package by colouring pairwise orthologues according to the ALG assignment in comparisons with P. maximus and B. floridae.
Evolutionary analysis of chordin in annelids
The identification of chordin (chrd) and chordin-like (chrdl) genes in O. fusiformis was based on the genome functional annotation (see above). To mine chrd orthologues, 81 annelid transcriptomic datasets were downloaded from the SRA (Supplementary Table 8) and assembled using Trinity (v.2.5.1)68 to create BLAST local nucleotide databases. We also created a nucleotide database for C. teleta using its annotated genome90 (European Nucleotide Archive (ENA) accession number: GCA_000328365.1). Human and O. fusiformis CHRD proteins were used as queries to find chrd orthologues following the mutual best hit approach (e-value ≤ 10-3), obtaining 103 distinct candidate chrd transcripts that were then translated (Supplementary Table 9). A single candidate CHRD protein for Themiste lageniformis (M. J. Boyle, unpublished data) was included ad hoc at this step. In addition, 15 curated CHRD and CHRDL protein sequences (and an outgroup) were obtained from various sources (Supplementary Table 10) and aligned together with O. fusiformis CHRD and CHRDL sequences in MAFFT (v.7)91 with the G-INS-I iterative refinement method and default scoring parameters. From this mother alignment, further daughter alignments were obtained using “mafft --addfragments”92, the accurate “--multipair” method, and default scoring parameters. For orthology assignment, two phylogenetic analyses were performed on selected candidate sequences, which included the longest isoform for each species–gene combination, given that it included a 10-residue or longer properly aligned fragment in either the CHRD domains or the von Willebrand factor type C (VWFC) domains. vWFC and CHRD domains were trimmed and concatenated using domain boundaries defined by ProSITE domain annotation for the human chordin precursor protein (UniProt: Q9H2X0). Either all domains or the VWFC domains only were used for phylogenetic inference (Extended Data Fig. 2c,d and Supplementary Tables 11 and 12) with a WAG amino acid replacement matrix93 to account for transition rates, the FreeRate heterogeneity model (R4)94 to describe sites evolution rates, and an optimization of amino acid frequencies using maximum likelihood using IQ-TREE (v.2.0.3)95. 1,000 ultrafast bootstraps96 were used to extract branch support values. Bayesian reconstructions in MrBayes (v.3.2.7a)97 were also performed using the same WAG matrix but substituting the R4 model for the discrete gamma model98, with 4 rate categories (G4). All trees were composed in FigTree (v.1.4.4). Alignment files are available in the GitHub repository (see Data availability section).
Gene expression profiling
We profiled gene expression dynamics from blastula to juvenile stages for O. fusiformis, from 64-cell to competent larva stages for C. teleta (Supplementary Fig. 2), from early development to female adult stages for D. gyrociliatus, and across the 9 adult tissues samples of O. fusiformis. Sequencing adaptors were removed from raw reads using trimmomatic (v.0.39)65. Cleaned reads were pseudo-aligned to the filtered gene models using kallisto (v.0.46.2)99, and genes with an expression level above an empirically defined threshold of 2 transcripts per million (TPM) were deemed expressed. For each species, the DESeq2 (v.1.30.1) package100 was used to normalize read counts across developmental stages (Supplementary Tables 13–21) and adult tissues (Supplementary Tables 49–51) and to perform pairwise differential gene expression analyses between consecutive developmental stages. P values were adjusted using the Benjamini–Hochberg method for multiple testing correction. We defined a gene as significantly upregulated for a log2(fold-change) (LFC) > 1 or downregulated for a LFC < 1, given an adjusted P value < 0.05. Principal component analyses were performed on the variance stabilizing-transformed matrices of the normalized DESeq2 matrices. For the O. fusiformis adult tissues samples, genes specifically expressed (TPM > 2) only in both the head and head plus two anterior-most segment samples were classified as adult anterior genes, and those expressed only in both the tail and the body wall were classified as adult trunk and posterior genes (Supplementary Tables 52 and 53). For all three annelid taxa, anterior, trunk and posterior markers were defined as genes for which their spatial expression pattern has been validated through in situ hybridization in the literature (Supplementary Tables 54–56). TPM and DESeq2 gene expression matrices of developmental and adult tissue samples are also available in the GitHub repository (see Data availability section).
Gene clustering and co-expression network analyses
Transcripts were clustered according to their normalized DESeq2 expression dynamics through soft k-means clustering (or soft clustering) using the mfuzz (v.2.52) package101 (Supplementary Tables 23–26). Out of the total number of transcripts, we discarded those that were not expressed at any developmental stage (225 out of 31,903 for O. fusiformis, 1,407 out of 41,221 for C. teleta, and 200 out of 17,388 for D. gyrociliatus). We then determined an optimal number of 12 clusters (O. fusiformis and C. teleta) and 9 clusters (D. gyrociliatus) for our datasets by applying the elbow method to the minimum centroid distance as a function of the number of clusters. For construction of the gene co-expression networks for O. fusiformis and C. teleta, we used the WGCNA package (v.1.70-3)102. All transcripts expressed at any developmental stage were used to build a signed network with a minimum module size of 300 genes and an optimized soft-thresholding power of 16 and 8 for O. fusiformis and C. teleta, respectively. Block-wise network construction returned 15 gene modules for O. fusiformis, from which 1 module was dropped owing to poor intramodular connectivity, and 19 gene modules for C. teleta (Supplementary Tables 23 and 24). The remaining 14 gene modules of O. fusiformis (A–N) and 19 gene modules of C. teleta (A–O, W–Z) were labelled with distinct colours, with unassigned genes labelled in grey. Random subsets consisting of the nodes and edges of 30% of the transcripts were fed into Cytoscape (v.3.8.2)103 for network visualization (Supplementary Fig. 9). Module eigengenes were chosen to summarize the gene expression profiles of gene modules. GO enrichment analysis of each gene cluster and gene module was performed using the topGO (v.2.44) package. We performed a Fisher’s exact test and listed the top 30 (soft k-means clusters) or top 15 (WGCNA modules) significantly enriched GO terms of the class biological process (Supplementary Tables 27–31, Supplementary Figs. 4–6, 10 and 11). To ease visualization, all 486 non-redundant enriched GO terms from the 33 soft k-means clusters from all 3 species were clustered through k-means clustering by semantic similarity using the simplifyEnrichment (v.1.2.0) package104 (Supplementary Figs. 7 and 8). Full network nodes and edges files and the random 30% network subset files are available in the GitHub repository (see Data availability section).
Transcription factor repertoire analysis
We selected a custom set of 36 transcription factor classes from all 9 transcription factor superclasses from the TFClass database105. Transcripts in O. fusiformis, C. teleta and D. gyrociliatus were deemed transcription factors and classified into one or more of the 36 classes if they were a match for any of the corresponding PANTHER identifiers (Supplementary Tables 32–33 and Supplementary Fig. 3). Over-representation and under-representation of the different transcription factor classes in the gene expression clusters was tested through pairwise two-tailed Fisher’s exact tests, for which we then adjusted the P values using Benjamini–Hochberg correction for multiple testing.
Orthogroup overlap analysis
We performed pairwise comparisons between each possible combination of soft k-means clusters of all three annelid taxa. The numbers of overlapped orthogroups between either the full clusters or the transcription factors belonging only to each cluster were subjected to upper-tail hypergeometric tests. P values were then adjusted using the Benjamini–Hochberg method for multiple testing correction. For the simplified analyses by quadrants, clusters were classed as early/pre-larval (O. fusiformis: 1–6; C. teleta: 1–5; D. gyrociliatus: 1–3) or late/pre-larval (O. fusiformis: 8–12; C. teleta: 7–12; D. gyrociliatus: 5–7), thus rendering 4 different quadrants for each species pairwise comparison: earlyspecies A–earlyspecies B, earlyspecies A–latespecies B, latespecies A–earlyspecies B and latespecies A–latespecies B. Clusters corresponding to female adult expression in D. gyrociliatus (8 and 9) were discarded for comparison purposes. Relative similarity (RS) values for each of the four quadrants were computed as the following ratio:
Values above 1 indicate a higher orthogroup overlap than average, whereas values below 1 represent a lower overlap than average. For genes under heterochronic shifts—that is, with distinct temporal expression dynamics—between indirect and direct development, a gene set was constructed with the genes with a single-copy orthologue in both O. fusiformis and C. teleta, for which expression was shifted from post-larval clusters (O. fusiformis: 7–12; C. teleta: 8–12) to early clusters 2 and 3 in D. gyrociliatus (Fig. 2b, Supplementary Tables 34 and 35 and Supplementary Fig. 12). For the characterization of genes under heterochronic shifts between planktotrophic and lecithotrophic larvae, two gene sets were generated with the genes with earlyO. fusiformis–lateC. teleta and lateO. fusiformis–earlyC. teleta dynamics, as described above (Supplementary Tables 36–39 and Supplementary Figs. 13 and 14). GO enrichment analysis of both gene sets was performed using the topGO (v.2.44) package. We performed a Fisher’s exact test and listed the top 15 significantly enriched GO terms of the class biological process (Supplementary Table 40). BlastKOALA106 server was used to assign a KEGG orthology number to one-to-one orthologues showing heterochronic sifts and KEGG mapper107 to analyse the annotations (Supplementary Tables 41 and 42).
Human genes involved in the animal autophagy pathway (map04140) were obtained from the KEGG pathway database108. D. melanogaster and Saccharomyces cerevisiae genes involved in the chitin synthesis pathway were fetched from FlyBase109 and SGD110, respectively, based on the enzyme nomenclature numbers of the pathway enzymatic activities111. Orthology in O. fusiformis and C. teleta for the autophagy pathway genes was determined from the single-copy orthologue sets to the human genes, for which one for both species existed (Supplementary Tables 43 and 44). For the chitin synthesis pathway, and owing to the high number of paralogues and expansions and losses of enzymatic activities of the chitin synthesis pathway, orthology was inferred from PANTHER family and subfamily identifiers to the corresponding enzymatic activities (Supplementary Tables 45 and 46). We then used this orthology to reconstruct the chitin synthesis pathway in annelids. Timing across both species and the presence or lack thereof of heterochronic shifts between O. fusiformis and C. teleta were determined as described above (Supplementary Figs. 15 and 16).
Hox genes orthology assignment
A total of 129 curated Hox sequences were retrieved from various databases (Supplementary Table 47) and aligned with O. fusiformis HOX proteins with MAFFT (v.7) in automatic mode. Poorly aligned regions were removed with gBlocks (v.0.91b)112 to produce the final alignments. Maximum likelihood trees were constructed using RAxML (v.188.8.131.52)113 with an LG substitution matrix114 and 1,000 ultrafast bootstraps. All trees were composed in FigTree (v.1.4.4). Alignment files are available in the GitHub repository (see Data availability section).
Whole-mount in situ hybridization and immunohistochemistry
Fragments of chordin and Hox genes were isolated as previously described24 using gene-specific oligonucleotides and a T7 adaptor. Riboprobes were synthesized using a T7 MEGAscript kit (ThermoFisher, AM1334) and stored at a concentration of 50 ng µl–1 in hybridization buffer at –20 °C. Whole-mount in situ hybridization in embryonic, larval and juvenile stages were conducted as described elsewhere24,26. Antibody staining in larval stages of O. fusiformis, Magelona spp. and C. teleta was carried out as previously described23,115 using the following antibodies: mouse anti-acetyl-α-tubulin antibody, clone 6-11B-1, 1:800 dilution (Sigma-Aldrich, MABT868, RRID: AB_2819178) and goat anti-mouse IgG (H+L) cross-adsorbed secondary antibody, Alexa Fluor 647, 1:800 dilution (Thermo Fisher Scientific, A-21235, RRID: AB_2535804). Differential interface contrast images of the colorimetric in situ were obtained using a Leica 560 DMRA2 upright microscope equipped with an Infinity5 camera (Lumenera). Fluorescently stained samples were scanned using a Nikon CSU-W1 spinning disk confocal microscope.
We performed two replicates of ATAC-seq from samples containing around 50,000 cells at the blastula (about 900 embryos), gastrula (around 500), elongation (about 300), mitraria larva (around 150 larvae) and competent larva (about 40) stages for O. fusiformis, and the 64-cells stage (about 500 embryos), gastrula (around 200), stage 4tt larva (about 120 larvae), stage 5 larva (around 90) and stage 8 larva (around 50) for C. teleta following the omniATAC protocol116, but gently homogenizing the samples with a pestle in lysis buffer and incubating them on ice for 3 min. Tagmentation was performed for 30 min at 37 °C with an in-house purified Tn5 enzyme117. After DNA clean-up, ATAC-seq libraries were amplified as previously described116. Primers used for both PCR and quantitative PCR are listed in Supplementary Tables 57 and 59. Amplified libraries were purified using ClentMag PCR Clean Up beads as indicated by the supplier and quantified and quality checked on a Qubit 4 fluorometer (ThermoFisher) and an Agilent 2200 TapeStation system before pooling at equal molecular weight. Sequencing was performed on an Illumina HiSeq4000 platform in 2 × 75 bp mode at the Oxford Genomics Centre (blastula, elongation and mitraria larva stages, and one replicate of the gastrula sample of O. fusiformis, as well as the 64-cells, gastrula and stage 4tt larva stages of C. teleta) and on an Illumina NovoSeq6000 in 2 × 150 bp mode at Novogene (one replicate of gastrula and the two replicates of competent larva stages of O. fusiformis and the two replicates of stage 5 and stage 8 larva of C. teleta).
Chromatin accessibility profiling
We used cutadapt (v.2.5)118 to remove sequencing adaptors and trim reads from libraries sequenced in 2 × 150 bp mode to 75 bp reads. Quality filtered reads were mapped using NextGenMap (v.0.5.5)119 in paired-end mode, duplicates were removed using samtools (v.1.9)120 and mapped reads were shifted using deepTools (v.3.4.3)121 (Supplementary Tables 58 and 60). Fragment size distribution was estimated from resulting BAM files and transcription start site enrichment analysis was computed using computeMatrix and plotHeatmap commands in deepTools (v.3.4.3). Peak calling was done using MACS2 (v.184.108.40.206)122,123 (-f BAMPE --min-length 100 --max-gap 75 and -q 0.01). Reproducible peaks were identified by irreproducible discovery rates (values <0.05) (v.2.0.4) at each developmental stage. Peaks from repetitive regions were filtered using BEDtools (v.2.28.0)124 at each developmental stage. Next we used DiffBind (v.3.0.14)125 to generate a final consensus peak set of 63,732 peaks in O. fusiformis and 46,409 peaks in C. teleta, which were normalized using DESeq2 (Supplementary Fig. 17). Peak clustering according to accessibility dynamics was performed as described above for RNA-seq, using the same number of 12 clusters to make both profiling techniques comparable. Principal component analysis and differential accessibility analyses between consecutive developmental stages were also performed as described above. An LFC > 0 and a LFC < 0 indicates whether a peak opens or closes, respectively, given an adjusted P value < 0.05. Stage-specific and constitutive peaks were determined using UpSetR (v.1.4.0)126, and both the consensus peak set and the stage-specific peak sets were classified by genomic region using HOMER (v.4.11)127 and further curated. Visualization of peak tracks and gene structures was conducted using pyGenomeTracks (v.2.1)128 and deepTools (v.3.4.3)121. To correlate chromatin accessibility and gene expression, this genomic region annotation was used to assign peaks to their closest gene (63,726 peaks were assigned to 23,025 genes in O. fusiformis and 44,368 peaks were assigned to 23,382 genes in C. teleta). Pearson correlation coefficient between chromatin accessibility and gene expression was computed individually by peak using two-sided tests (Supplementary Fig. 18). GO enrichment analysis of the gene sets regulated by peak clusters was performed using the topGO (v.2.44) package. We performed Fisher’s exact test and listed the top 30 significantly enriched GO terms of the class biological process (Supplementary Figs. 19 and 20). To ease visualization, all 242 non-redundant enriched GO terms were clustered through k-means clustering by semantic similarity using the simplifyEnrichment (v.1.2.0) package104 (Supplementary Tables 61–71 and Supplementary Figs. 21–23). Coverage files and peak set files are available in the GitHub repository (see Data availability section).
Motif identification, clustering, matching and curation
To identify transcription-factor-binding motifs in chromatin accessible regions in the two species, we first used HOMER127 (v.4.1) to identify known and de novo motifs in the consensus peak sets, which produced 456 motifs for O. fusiformis and 364 motifs for C. teleta (Supplementary Tables 72 and 73). Significance of motifs was derived from binomial tests from cumulative binomial distributions. We then used GimmeMotifs (v.0.16.1)129 with a 90% similarity cut-off to cluster the motifs predicted in O. fusiformis and C. teleta into 141 consensus motifs, which we matched against four motif databases to assign their putative identity (Gimme vertebrate (5.0)129, HOMER127, CIS-BP130 and a custom JASPAR2022 (ref. 131) core motifs without plant and fungi motifs; Supplementary Fig. 24). We then used the human non-redundant TF motif database (https://resources.altius.org/~jvierstra/projects/motif-clustering-v2.0beta/) to manually curate the annotation. After removing motifs that probably represented sequence biases, we finally obtained 95 motif archetypes for O. fusiformis and 91 for C. teleta (Supplementary Table 74), which we then used to perform motif counts in peaks (Supplementary Tables 75 and 76) and motif accessibility estimation (Supplementary Tables 77 and 78) with GimmeMotifs (v.0.16.1)129. Data clustering was performed with mfuzz (v.2.52)101 (Supplementary Figs. 25 and 27). Over-representation and under-representation of counts of the common curated motif archetypes in the peak accessibility soft clusters (see above) was tested through pairwise two-tailed Fisher’s exact tests, for which we then adjusted the P values using the Bonferroni correction for multiple testing.
Transcription factor footprinting and Hox gene regulatory network exploration
To predict transcription factor binding, as a proxy of activity, we conducted footprinting analysis using TOBIAS (v.0.12.0)132 during development in the 95 and 91 motif archetypes for O. fusiformis and C. teleta, respectively (Supplementary Tables 79 and 80). Bound and unbound sites were first estimated by fitting a two-component Gaussian-mixture model, and significance was then tested using a one-tail test from the right-most normal distribution. Transcription factor binding scores (TFBSs) were clustered using mfuzz (v.2.52)101. Pearson correlation coefficients of motif accessibility and TFBSs were calculated by stage and by motif separately on the basis of 33 common, curated motif archetypes (Supplementary Figs. 26 and 28–30). To reconstruct potential upstream regulators and downstream effectors of the Hox genes, we first subset ATAC-seq peaks annotated to the Hox genes in the Hox cluster (that is, all except Post1) in O. fusiformis and C. teleta and extracted the bound motifs on those peaks (Supplementary Tables 81 and 82). TFBSs were summed for each motif to obtain global dynamics, and their temporal dynamics were then clustered using mfuzz (v.2.52)101 (Supplementary Fig. 31). For the downstream genes regulated by Hox, we obtained genes annotated to ATAC-seq peaks with a bound HOX, EVX and CDX motif at the competent stage in O. fusiformis and stage 4tt larva in C. teleta (Supplementary Tables 83 and 84). One-to-one orthologues were used to identified shared targets and PANTHER identifiers to obtain their functional annotation.
To evaluate gene expression dynamics by phylostratum and developmental stage in all three annelid lineages, we used the OrthoFinder gene families and their inferred origins. We deemed all genes originating before and with the Cnidarian–Bilaterian ancestor of pre-metazoan and metazoan origin (Supplementary Tables 85–87). We then applied a quantile normalization onto the DESeq2-normalized matrices of gene expression. The 75th percentile of the quantile-normalized gene expression levels was used as the summarizing measure of the gene expression distribution by developmental stage. Over-representation and under-representation of the different phylostrata in the gene expression clusters were tested through pairwise two-tailed Fisher’s exact tests, for which we then adjusted the P values using Bonferroni correction for multiple testing. Gene expression dynamics of new genes and genes of pre-metazoan and metazoan origin across selected metazoan lineages (see ‘Comparative transcriptomics’ section below) were also evaluated as described above (Supplementary Fig. 32).
Publicly available RNA-seq developmental time courses for the development of Amphimedon queenslandica, Clytia hemisphaerica, N. vectensis, S. purpuratus, Branchiostoma lanceolatum, D. rerio, D. melanogaster, Caenorhabditis elegans, C. gigas, D. gyrociliatus, and two stages of C. teleta were downloaded from the SRA using SRA-Toolkit (v.2.11.3) (Supplementary Table 88), cleaned for adaptors and low-quality reads with trimmomatic (v.0.39)65 and pseudo-aligned to their respective non-redundant genome-based gene repertoires—that is, with a single transcript isoform, the longest, per gene model—using kallisto (v.0.46.2)99. We then performed a quantile transformation of TPM values using scikit-learn (v.1.0.2)133 and calculated the Jensen–Shannon divergence (JSD) value from (1) all single-copy orthologues, (2) the set single-copy transcription factor orthologues and (3) the set of common single-copy orthologues across all lineages, either between all possible one-to-one species comparisons (1) or between all species and O. fusiformis (2 and 3), using the philentropy (v.0.5.0) package134 as follows:
Transcriptomic divergences were calculated on the basis of 250 bootstrap replicates, from which statistically robust mean values and standard deviations were obtained. Raw mean JSD values (JSDraw) were adjusted (JSDadj) by dividing by the number of single-copy orthologues (1), single-copy transcription factor orthologues (2) or common single-copy orthologues (3) of each comparison (Supplementary Tables 22, 89 and 90) and normalized using the minimum and maximum adjusted JSD values from all one-to-one species comparisons as follows:
Relative JSD values were obtained equally, using minimum and maximum adjusted JSD values from each one-to-one species comparison instead. Gene-wise JSD (gwJSD) between five key one-to-one larval stages comparisons was computed as follows:
Similarity-driving genes—that is, those with very low gwJSD—were subset as those below the threshold defined as 25% of the point of highest probability density of the gwJSD distributions. GO enrichment analysis of the similarity-driving gene sets was performed using the topGO (v.2.44) package. We performed Fisher’s exact test and listed the top 30 significantly enriched GO terms of the class biological process (Supplementary Table 91). To ease visualization, all 51 non-redundant enriched GO terms from the 5 gene sets were clustered through k-means clustering by semantic similarity using the simplifyEnrichment (v.1.2.0) package104. The subsets of similarity-driven transcription factors of each pairwise comparison are listed in Supplementary Table 92. For comparative Hox gene expression dynamics profiling in metazoan lineages, the same non-redundant gene expression matrices were normalized using the DESeq2 (v.1.30.1) package100 (Supplementary Fig. 33), unless Hox gene models were missing, in which case they were manually added ad hoc to the non-redundant genome-based gene repertoires (Supplementary Table 94). Hox gene expression profiling in U. unicinctus was performed as described for the rest of taxa but using the available reference transcriptome135 instead (Supplementary Table 48). All gene expression matrices are available in the GitHub repository (see Data availability section).
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Accession codes and unique identifiers to previously publicly available datasets we used for this study are listed in Supplementary Table 2 (genome files used in gene family evolution analyses), Supplementary Table 8 (transcriptomes used in the evolutionary analysis of chordin in annelids), Supplementary Tables 41 and 43 (gene identifiers used in pathway analyses), Supplementary Table 47 (sequence identifiers used in the orthology assignment of Hox genes), Supplementary Table 48 (RNA-seq datasets used for Hox gene expression profiling in U. unicinctus) and Supplementary Table 88 (RNA-seq datasets used for comparative annelid and metazoan transcriptomics and Hox gene expression profiling). Repetitive elements database RepBase can be accessed at https://www.girinst.org/repbase/. Transcription factor public database TFClass can be found at http://tfclass.bioinf.med.uni-goettingen.de/. All sequence data associated with this project are available at the European Nucleotide Archive (project PRJEB38497) and Gene Expression Omnibus (accession numbers GSE184126, GSE202283, GSE192478, GSE210813 and GSE210814). Genome assemblies, TE annotations, genome annotation files used for RNA-seq and ATAC-seq analyses, WGCNA nodes and edges files, alignment files used in orthology assignment and other additional files are publicly available at GitHub (https://github.com/ChemaMD/OweniaGenome).
All code used in this study is available at GitHub (https://github.com/ChemaMD/OweniaGenome).
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We thank A. de Mendoza, D. Gavriouchkina and S. Rossiter for their support and valuable comments on the manuscript; staff at Station Biologique de Roscoff for their help with collection and animal supplies; staff at the Oxford Genomics Centre at the Wellcome Centre for Human Genetics (funded by Wellcome Trust grant reference 203141/Z/16/Z) for the generation and initial processing of RNA-seq and ATAC-seq sequencing data; M. J. Boyle for providing the chordin sequence for T. lageniformis; J. Deane for initial help with Hox gene characterization in O. fusiformis; and core technical staff at the Department of Biology at Queen Mary University of London for their constant support. This work used computing resources from Queen Mary University of London’s Apocrita HPC facilities. This work was funded by the Horizon 2020 Framework Programme to J.M.M.-D. (European Research Council Starting Grant action number 801669) and A.H. (European Research Council Consolidator Grant action number 648861), a Royal Society University Research Fellowship (URF\R1\191161) and a Japan Society for the Promotion of Science Kakenhi grant (JP 19K06620) to F.M., and a Biotechnology and Biological Sciences Research Council LIDo iCASE PhD studentship (BB/T008709/1) to J.M.M.-D. and B.E.D.
The authors declare no competing interests.
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Extended data figures and tables
Extended Data Fig. 1 The genome of Owenia fusiformis is conservatively evolving.
a, Differential interface contrast (DIC) images and z-stack confocal laser scanning views of a C. teleta trochophore larva stained for DAPI and acetylated α-tubulin. b,c, Pie charts of the transposable element content and Kimura substitution plots of transposable element divergence for O. fusiformis and other selected annelid species belonging to different annelid clades as depicted in c. Unlike H. robusta and L. luymesi, which show bursts of transposable elements, O. fusiformis shows more steady rates of expansion. d, Gene family evolution analysis across 22 metazoan lineages under a consensus tree topology. Gains are shown in green, losses in violet. Gene family losses in O. fusiformis are like those of slow-evolving lineages. e, Principal component analysis from Fig. 1b, showing the full set of species. f,g, O. fusiformis has the lowest number of gene losses of all sampled annelids (e), and the least gene expansions (f) after the extremely compact genome of D. gyrociliatus. h, Macrosynteny analysis between O. fusiformis, and from top to bottom, the cephalochordate Branchiostoma floridae, the bivalve Pecten maximus, and the annelid Streblospio benedicti. Owenia fusiformis retains ancestral linkage groups but also exhibits annelid- and species-specific chromosomal arrangements. However, the karyotype of O. fusiformis is more conserved than that of the annelid S. benedicti. i, Macrosynteny analysis between the bivalve P. maximus and the nemertean worm L. longissimus. Lineus longissimus exhibits conserved ancestral bilaterian linkage groups, including three potential lophotrochozoan-specific chromosomal rearrangements (H+Q, J2+L and K+O2), plus a nemertean-specific fusion (G+C1). Scale bar in a, 50 µm.
Extended Data Fig. 2 chordin was lost multiple times in annelids.
a, Domain organisation of Chordin (CHRD) and Chordin-like (CHRDL1/2) proteins, as inferred from human orthologs. b, Public AlphaFold protein structure prediction for human Chordin (UniProt: Q9H2X0) and Chordin-like 1 (UniProt: Q9BU40) revealed a previously unknown and uncharacterised domain in CHRDL1 and CHRDL2 (also depicted in a). c,d, Orthology assignment of chordin annelid candidates. From the multiple sequence alignment, candidate annelid sequences with a 10-residue or longer fragment aligned against either the CHRD (c; i.e., bona fide chordin genes) or the vWFC domains (d; i.e., putative chordin genes) were kept for further analysis. CHRDL cluster is shaded in blue; CHRD cluster, in red. Bootstrap support values (top) and posterior probabilities (bottom) are shown at both key nodes. Sequences in red and blue are curated CHRD and CHRDL sequences, respectively. e,f, Summary phylogenetic trees of presence or absence of chordin (red) or putative chordin (light brown) across Annelida. g, RNA-seq expression levels of chordin in O. fusiformis, which peaks at the blastula and gastrula stages, after the specification and inductive activity of the embryonic organiser. Curve is a locally estimated scatterplot smoothing, coloured shaded area represents standard error of the mean. h, Whole mount in situ hybridisation of chordin at the blastula (5 h post fertilisation, hpf), gastrula (9 hpf), and mitraria larva (27 hpf) stages of O. fusiformis. Asterisks mark the animal/anterior pole. gp: gastral plate; bp: blastopore, mo: mouth. Representative results of three independent analyses. Scale bar in h, 50 µm.
Extended Data Fig. 3 Gene expression dynamics during annelid life cycles.
a,b, Heatmaps of average pairwise transcriptomic Jensen–Shannon Divergence (JSD) between O. fusiformis and C. teleta (a), and between D. gyrociliatus and either O. fusiformis (b, left) or C. teleta (b, right). Average relative JSD of the C. teleta or O. fusiformis stages of minimal divergence to each corresponding stage is shown on top. Confidence intervals represent standard deviation from 250 bootstrap resamplings of the ortholog sets. c–e, Soft k-means clustered heatmap of all transcripts whose expression was not null in at least one developmental stage into an optimal number of 12 clusters (O. fusiformis, c; and C. teleta, d) and 9 clusters (D. gyrociliatus, e). Soft clustering considerably increased temporal resolution for the RNA-seq time course of D. gyrociliatus. On the right of each heatmap, gene-wise expression dynamics (grey lines) and locally estimated scatterplot smoothing (coloured lines) for each cluster. Coloured shaded areas represent standard error of the mean. f, Enrichment analysis of biological process gene ontology (GO) terms for RNA-seq clusters. Each line represents a single GO term, for which the −log10(p–value) for each RNA-seq cluster is shown in a colour-coded scale. GO terms were clustered into 15 distinct clusters based on semantic similarity (see Supplementary Figs. 7, 8). Clusters are shown on the bottom of the heatmaps. For the full list of GO terms and clusters, see Supplementary Figs. 4–6. P-values were derived from upper-tail Fisher’s exact tests.
Extended Data Fig. 4 Heterochronic shifts in gene regulatory programmes between annelid life cycles.
a,b, Similarity heatmaps showcasing the orthogroup overlap between the clusters of co-regulated genes (see Extended Data Fig. 3c–e), between the three annelids. P-values were derived from upper-tail hypergeometric tests and Benjamini-Hochberg-adjusted. c, Explanation of the orthogroup overlap analysis by quadrants. Clusters were classed as “early” (before dotted lines) or “late” (after dotted lines). Clusters of the female adult of D. gyrociliatus were disregarded. d,e, Heatmaps of relative similarity by quadrants of the orthogroup overlap analyses of the whole genomes (d) and transcription factors only (e). Colour scale in d and e is the same as in c. f, KEGGbrite characterisation of the gene sets under heterochronic shifts (surrounded by dotted black lines in Fig. 2e) between O. fusiformis and C. teleta. g, Bar plots depicting p-values of top biological process GO terms of genes shifted from late expression in O. fusiformis to early expression in C. teleta. P-values were derived from upper-tail Fisher’s exact tests. Full list is available in Supplementary Fig. 13. h, Enrichment analysis of the number of transcription factors per class in clusters of co-transcribed genes of O. fusiformis (left), C. teleta (centre) and D. gyrociliatus (right). For each cluster and class combination, the Bonferroni-adjusted p–value from the two-sided Fisher’s exact test is shown. Cells in red represent overrepresented classes (odds ratio, OR > 1; adjusted p–value < 0.05); cells in blue, underrepresented classes (OR < 1, adjusted p–value < 0.05). Dotted lines highlight clusters of maximal enrichment of the homeodomain class. n.s.: not significant.
Extended Data Fig. 5 The Hox gene complement and expression in O. fusiformis.
a, Orthology assignment of O. fusiformis Hox genes through maximum likelihood phylogenetic inference. Bootstrap support values are shown for major gene groups. Of: O. fusiformis. b, Volcano plot of the mitraria to competent larva transition, highlighting the marked upregulation of Hox genes. LFC: log2(fold-change). P-values were derived from the described DESeq2 pipeline and Benjamini-Hochberg-adjusted. c, Chromosomal location of the Hox cluster and Post1 gene in O. fusiformis (top) and schematic comparison of Hox cluster organisation in annelids and a mollusc (bottom). Arrows denote direction of transcription. d, Schematic representation to scale of the genomic loci and intron–exon composition of Hox genes in O. fusiformis. e, Heatmaps of Hox gene expression during the development of C. teleta, O. fusiformis and the echiuran annelid Urechis unicinctus. In the two annelid species with planktotrophic larvae, Hox genes only become expressed at the larval stage (dotted vertical line), and not during embryogenesis, as observed in C. teleta. f, Whole mount in situ hybridisation of Hox genes in the gastrula (lateral views) and in the mitraria larva, pre-competent larva, and juvenile stages of O. fusiformis (ventral views). The area encircled by a dotted white line at the pre-competent stage highlights a region of probe trapping from ingested food content. bp: blastopore; mo: mouth. Representative results of three independent analyses. g,h Schematic representations of the expression of Hox genes in the trunk rudiment of the competent larva (g) and juvenile trunk (h). A: anterior; P: posterior. Drawings are not to scale, and schematic expression domains are approximate. Scale bars in f, 50 µm in gastrulae and larvae, and 100 µm in juvenile.
Extended Data Fig. 6 Transcriptomic dynamics of anteroposterior genes.
a, Schematic drawing of the adult body regions used to define anterior and posterior and trunk genes. b, Correlation matrix of RNA-seq experiments from all nine adult tissues, calculated from a variance stabilising-transformed matrix of the normalised DESeq2 matrix. c, Venn diagram showing the number of tissue-specific and shared expressed genes (TPM > 2). Gene sets highlighted with red text were defined as adult anterior, and adult posterior and trunk genes. d, Phylostratigraphic classification of adult anterior, and adult posterior and trunk genes, compared to the whole genome and a random subset of 1,000 genes. e,f, Expression dynamics of each phylostratum by developmental stage in the adult anterior (e), and adult posterior and trunk gene sets (f), calculated from the 75 % percentile of a quantile-normalised matrix of gene expression levels. Adult anterior genes of most phylostrata peak at the blastula, while the maximum expression of adult trunk/posterior genes of most phylostrata peak at post-larval stages. g–l, Average expression dynamics of in situ hybridisation-validated anterior, trunk, and posterior markers throughout O. fusiformis (g,h), C. teleta (i,j), and D. gyrociliatus (k,l) development. For boxplots in g,i, and k, centre lines, median; box, interquartile range (IQR); whiskers, first or third quartile ± 1.5 × IQR. Lower whiskers are sometimes not apparent due to the distribution skewness towards zero. Curves in h,j, and l are locally estimated scatterplot smoothings. Coloured shaded areas represent standard error of the mean. n = 23, 8, and 17 anterior markers, 10 and 3 posterior markers, and 15, 10, and 8 trunk markers, for O. fusiformis, C. teleta, and D. gyrociliatus, respectively. Key stages where expression of trunk markers is incipient are shown for both O. fusiformis and C. teleta.
Extended Data Fig. 7 Chromatin dynamics during annelid development.
a, Genomic feature annotation of the consensus ATAC-seq peaks. b, Stacked bar plots showing the proportion of called peaks per developmental stage classified by genomic feature. c, Heatmap of normalised peak accessibility of the soft clustered consensus ATAC-seq peak sets. d, Self-correlation matrices of normalised motif accessibility and transcription factor binding score, revealing distinct chromatin regulatory dynamics throughout development. e, Correlation matrices of normalised motif accessibility to transcription factor binding score during annelid development. f, Correlation matrix of normalised motif accessibility between both species. d–f further validate the non-triviality of the results obtained in Fig. 3c. Pearson correlation coefficients in d–f were derived from two-tailed tests. g, Heatmap of normalised motif accessibility and transcription factor binding dynamics for each of the common annotated annelid motif archetypes during O. fusiformis and C. teleta development. Colour scale denotes transcription factor binding score dynamics, bubble size represents motif accessibility dynamics, both in a z-score scale. Motif archetypes highlighted in red are representative examples of the heterochronic shifts shown in bulk in Fig. 3c. h, Enrichment analysis of the number of occurrences of the common annotated annelid motif archetypes in the peak clusters inferred through soft k-means clustering and shown in c, for O. fusiformis (top) and C. teleta (bottom). For each cluster and motif combination, the Bonferroni-adjusted p–value of the two-tailed Fisher’s exact test is shown. Red cells represent significantly overrepresented lineages (odds ratio, OR > 1, adjusted p–value < 0.05). Blue cells denote significantly underrepresented lineages (OR < 1, adjusted p–value < 0.05). i, Most abundant bound motifs in peaks of the Hox clusters. j, Downstream regulated genes by transcription factors bound to the HOX/CDX/EVX motif archetype.
Extended Data Fig. 8 Phylostratigraphy analyses in annelid life cycles.
a,b Expression dynamics (a) and expression contribution (b) of each phylostratum by developmental stage in all three annelids, calculated from the 75% percentile of a quantile-normalised matrix of gene expression levels. Older genes are expressed at the highest levels across annelid development. c–e, Boxplots of quantile-normalised expression levels of genes classified by phylostratum across O. fusiformis (c), C. teleta (d), and D. gyrociliatus (e) development. A random subset of 2,000 genes is shown as a negative control. n denotes number of genes per phylostratum. f–h, Enrichment analysis of the number of genes per phylostratum in clusters of co-transcribed genes as inferred through soft k-means clustering and shown in Extended Data Fig. 3c–e, for O. fusiformis (f), C. teleta (g), and D. gyrociliatus (h). For each cluster and phylostratum combination, the Bonferroni-adjusted p–value of the two-tailed Fisher’s exact test is shown. Upper tables include significantly overrepresented lineages (odds ratio, OR > 1, adjusted p–value < 0.05). Lower tables include significantly underrepresented lineages (OR < 1, adjusted p–value < 0.05). Shaded grey areas indicate clusters of genes with peak expression at the mitraria larva, for O. fusiformis; and stage 4tt through stage 7 larval stages, for C. teleta.
Extended Data Fig. 9 Bilaterian planktotrophic larvae and cnidarian larvae share maximal transcriptional similarity.
a, Heatmaps of normalised transcriptomic Jensen–Shannon divergence (JSD) from pairwise comparisons of all single copy one-to-one orthologs (left), the set of common orthologs to all species (centre), and all single copy one-to-one transcription factor orthologs (right), between O. fusiformis and ten other metazoan lineages with different life cycles. Larval stages are highlighted in green. b, Average relative JSD for the datasets shown in a, from stages of minimal JSD to each O. fusiformis stage. Confidence intervals represent the standard deviation from 250 bootstrap resamplings of the ortholog sets. c–e, Stages of minimal JSD to each O. fusiformis stage, calculated from the one-to-one ortholog set (c), the common ortholog set (d), and the one-to-one transcription factor ortholog set (e). Larval stages are highlighted in green. f, Violin plots of the gene-wise Jensen Shannon divergence (gwJSD) distributions for the pairwise comparisons of the one-to-one ortholog sets between the mitraria larva of O. fusiformis and the stages of minimal transcriptomic divergence as in c. for C. gigas (n = 6,737 single copy orthologs), C. hemisphaerica (n = 4,691), C. teleta (n = 7,651), N. vectensis (n = 5,254), and S. purpuratus (n = 5,015). Boxes represent mean estimate ± standard deviation. Dotted lines mark the point of highest probability density. Genes below ¼ of this point were subset as similarity-driving genes. g, Biological process GO terms enrichment of the five similarity-driving gene sets. GO terms were clustered by semantic similarity into 4 clusters. Each row represents a single GO term, for which the −log10(p–value) for each gene set is shown in a colour-coded scale.
Extended Data Fig. 10 Comparative transcriptomic analysis of metazoan life cycles.
a, Matrix of heatmaps of normalised transcriptomic Jensen–Shannon divergence (JSD) from pairwise comparisons of all single copy one-to-one orthologs between all eleven metazoan lineages. From top to bottom and left to right: the annelids O. fusiformis and C. teleta, the bivalve C. gigas, the nematode C. elegans, the insect D. melanogaster, the vertebrate D. rerio, the cephalochordate B. lanceolatum, the sea urchin S. purpuratus, the cnidarians N. vectensis and C. hemisphaerica, and the poriferan A. queenslandica. b, Proposed evolutionary scenario for larval and life cycle evolution in Annelida. Post-embryonic trunk patterning is likely an ancestral condition with the convergent pre-displacement of trunk differentiation to embryogenesis concurring with the evolution of indirect development with feeding larva and direct development. Drawings are not to scale. c, Expression dynamics of Hox genes across the developmental RNA-seq time courses of all eleven species from a and the echiuran annelid U. unicinctus. Heatmaps were vertically aligned at the blastula, gastrula, and juvenile stages for all species. Lophotrochozoan lineages with trochophore larvae were also vertically aligned at the trochophore stage. Dotted lines encompass the larval stages of species with ciliated larvae. See Extended Data Fig. 5e and Supplementary Fige. 33 for the fully labelled and non-deformed heatmaps. d, Alternative evolutionary scenarios for the deployment of Hox genes (as proxy for trunk patterning and assuming the staggered expression along the directive axis of cnidarians and anteroposterior axis of bilaterians is homologous, which does not necessarily imply homology of the two axes). Given our current understanding of Hox gene deployment in cnidarian and bilaterian taxa, a late post-embryonic Hox patterning ancestral to Bilateria and Cnidaria, as seen in extant lineages with maximal indirect development, is a more parsimonious scenario (on the right).
This file contains 33 Supplementary Figs. and legends for 94 Supplementary Tables.
Supplementary Tables 1–94.
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Martín-Zamora, F.M., Liang, Y., Guynes, K. et al. Annelid functional genomics reveal the origins of bilaterian life cycles. Nature 615, 105–110 (2023). https://doi.org/10.1038/s41586-022-05636-7
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