Mesodinium spp transcriptomes and associated data
Data files
Jun 11, 2026 version files 1.20 GB
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KN_data.zip
64.62 MB
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Mesodinium_data.zip
882.22 MB
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Prey_data.zip
251.03 MB
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README.md
21.46 KB
Abstract
Ciliates are a plastid-less phylum of alveolates but numerous members practice various forms of kleptoplasty. Members of the Mesodinium genus span a near-complete gradient of reliance on prey plastids, from the nearly exclusively photosynthetic M. rubrum to the heterotrophic M. pulex. The more photosynthetic the Mesodinium lineage, the fewer prey it ingests, the more efficient it is at retaining kleptoplastids, the higher its photosynthetic rate, and the more complex its handling of stolen organelles. In the heterotrophic M. pulex, a diversity of prey (including cryptophyte algae and dinoflagellates) are placed inside food vacuoles and digested immediately. The mixotrophic M. chamaeleon prefers a subset of cryptophyte algae, which lose their flagella and cell wall upon ingestion but remain inside a vacuole with their endomembrane system, nucleus, and photosynthetic capability otherwise intact. M. rubrum specializes on cryptophytes from a single genus. In M. rubrum, most of the ingested cryptophyte prey (cytoplasm, plastid, mitochondria, endomembrane system) is also maintained within a vacuole, but the nucleus is removed and positioned in close association with the ciliate’s own nuclei. This transcriptionally active prey nucleus (termed “kleptokaryon”) not only regulates prey organelle metabolism, but facilitates plastid repair and replication. We take a comparative approach to identify transcriptomic changes along this ecological gradient. We hypothesized that increasing reliance on photosynthesis would be accompanied by increased integration of ciliate and cryptophyte metabolic pathways, especially in M. rubrum where the kleptokaryon provides a proximal source of prey genetic material.
https://doi.org/10.5061/dryad.1jwstqk4x
Description of the data and file structure
Files and variables
File: Mesodinium_data.zip
Description: This zipped folder contains four sub-directories of transcriptome-related data for seven Mesodinium species/strains.
Sub-directories:
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transcriptomes_and_predicted_coding_sequences
Fasta files of transcriptome assemblies and predicted coding sequences -
clustered_proteins_and_ko_assignments
Fasta files of proteins clustered at 95 % identity with respective KEGG annotation (KO numbers assigned to proteins) -
blast_results
Diamond blastp results for annotated proteins queried against NCBI's non-redundant (nr) database and a custom database -
ssu_quantification_data
Data used to estimate rRNA content of RNASeq libraries. Files contain quantification results for 18s rRNA expression.Each sub-directory contains a README.txt file with additional information.
Mesodinium spp./strains contain separate folders within each sub-directory.
| Species folder name | Species | Data source |
|---|---|---|
| mchamaeleon_NRMC1802 | Mesodinium chamaeleon NRMC1802 | This study |
| mcahmaeleon_NRMC1501 | Mesodinium chamaeleon NRMC1501 | NCBI BioProject: PRJNA560220 |
| mpulex | Mesodinium pulex EPMP20B2 | This study |
| mrubrum_nantes | Mesodinium rubrum nantes | NCBI BioProject: PRJEB53438 |
| mrubrum_DK2009 | Mesodinium rubrum DK2009 | NCBI BioProject: PRJNA880267 |
| mrubrum_CCMP2563 | Mesodinium rubrum CCMP2563 | NCBI BioProject: PRJNA560206 |
| mrubrum_CBJR05 | Mesodinium rubrum CBJR05 | This study |
File: Prey_data.zip
Description: This zipped folder contains transcriptome assembly data for the cryptophyte prey of Mesodinium spp.
Sub-directories:
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transcriptomes_and_predicted_proteins
Fasta files of transcriptome assemblies and predicted codings sequences for cryptophyte prey species -
gc_content
The GC content for cryptophyte coding sequences generated in this studyEach sub-directory contains a README.txt text file with additional information.
| Prey species | Abbreviation | Data source |
|---|---|---|
| Geminigerna cryophila (prey of M. rubrum CCMP2563) | gc | NCBI BioProject: PRJNA560206 |
| Storeatula major (prey of M. pulex and M. chamaeleon NRMC1802 and NRMC1501) | sm | This study |
| Teleaulax amphioxeia (prey of M. rubrum CBJR05 and M. rubrum DK2009) | ta | This study |
File: KN_data.zip
Description: This zipped folder contains transcriptome assembly and related data for the kleptokaryons (stolen cryptophyte nuclei sequestered by the ciliate host) of M. chamaeleon NRMC1802 and M. rubrum CBJR05.
Sub-directories:
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annotated_proteins_and_ko_assignments
Fasta files of KN predicted proteins and their respective KO assignments by KEGG -
blast_results
Diamond blastp results for KN proteins queried against the nr databaseEach sub-directory contains a README.txt text file with additional information.
| File naming convention | Description |
|---|---|
| mchamaeleon_NRMC1802_KN | kleptokaryon of M. chamaeleon NRMC1802 |
| mrubrum_CBJR05_KN | kleptokaryon of M. rubrum CBJR05 |
Code/software
File types and data formats:
- .sf: Tab-delimited text file of Salmon v.1.10.3 (Patro et al 2017) 18s read quantification results
- nr-euk-tophits.txt: Tab-delimited text files of Diamond v.2.1.8.162 (Buchfink et al. 2021) blastp results, using searches against nr and custom databases
- ko.txt: Tab-delimited text files of protein KO assignments by GhostKOALA of KEGG (Kanehisa et al. 2016)
- transcriptome.fasta: Fasta-formatted text file of transcriptome nucleotide sequences (contigs) assembled by Megahit v.1.2.9 (Li et al 2015)
- transdecoder.cds: Fasta-formatted text file of nucleotide coding sequences predicted by Transdecoder v.5.7.1 (Haas, BJ. https://github.com/TransDecoder/TransDecoder)
- transdecoder.pep: Fasta-formatted text file of translated coding sequences (protein) predicted by Transdecoder
- transdecoder.bed: Tab-delimited text file of contig information produced by Transdecoder
- transdecoder.gff: Tab-delimited text file of contig information produced by Transdecoder
- transcriptome.faa: Fasta-formatted text file of protein sequences clustered at 95 % identity by CD-HIT v.4.8.1 (Li and Godzik 2006; Li et al. 2012)
- cds_gc.txt: Text file of prey coding sequences GC content generated by the geecee function of EMBOSS v.6.6.0.0 (Longden and Bleasby 2000)
- README.txt: Text file describing the contents of each sub-directory in further detail
Blast result column IDs
| Column ID | Description |
|---|---|
| ko | KEGG KO assignment of query sequence |
| query | Query sequence name |
| taxon | Lineage assignment of nr best blast hit |
| group | General taxonomic grouping of nr best blast hit |
| pid | Percent identity between query and nr best blast hit |
| qcov | Percent query coverage to nr best blast hit |
| evalue | E-value of nr best blast hit |
| num_tophits | Number of hits returned from nr database that match taxonomic group of best blast hit |
| total_hits | Total number of hits returned from blastp search against nr database |
| per_tophit | Percentage of hits returned that share same taxonomic grouping as best blast hit to nr database |
| per_bacteria | Percentage of hits returned from nr database that are classified as Bacteria |
| alien_index | Alien index: calculated as log10(E-value of alveolate tophit + 1e-200) - log10(E-value of best blast hit + 1e-200) if the best blast hit from the nr database is not alveolate. If no alveolate hits exist, the alien index is calculated between the E-value of the best blast hit and the E-value of the first hit that is not from the same taxonomic group |
| ai_type | Alien index type: "a" = calculated with alveolate hit; "o" = calculated with a non-alveolate hit; "na" = alien index cannot be calculated |
| gc_content | GC content of corresponding coding sequence of query |
| c_taxon | Taxonomic classification of best blast hit to custom database |
| c_pid | Percent identity to best blast hit of custom database |
| c_qcov | Percent query coverage to best blast hit of custom database |
| c_alen | Alignment length of query and custom database best blast hit |
| c_qlen | Query length |
| c_slen | Length of best blast hit in custom database |
| c_evalue | E-value of best blast hit in custom database |
| c_alien_index | Alien index of best blast hit in custom database to top alveolate hit returned |
| c_num_tophits | Number of hits returned from custom database that share the same taxonomic assignment as the best blast hit |
| c_total_hits | Total number of hits returned by the custom database |
| c_per_tophit | Percentage of hits returned that share taxonomic classification of best blast hit |
Mesodinium** spp./strain sequence naming conventions**
| Mesodinium strain | Naming convention (sequence name starts with this pattern) |
|---|---|
| M. pulex | MP[0-9]_ |
| M. chamaeleon NRMC1802 | [0-9][a-z]_ |
| M. chamaeleon NRMC1501 | mc2[a-z]_ |
| M. rubrum CBJR05 | mrt[0-9][a-z]_ |
| M. rubrum DK2009 | mrta[0-9]_ |
| M. rubrum nantes | mrn[0-9]_ |
| M. rubrum CCMP2563 | mrp[0-9]*_ |
File: metadata.zip
Description: This zipped folder contains the combined blast results for Mesodinium spp/strains after applying three filtering strategies to remove contamination and metadata pertaining to RNASeq libraries. Blast results files column IDs and Mesodinium naming conventions follow those listed in the tables above.
File types and data formats:
- meso-final-tophit-strategy1.xlsx: Excel document of nr and custom database blast results for Mesodinium sequences after applying filtering strategy 1. Strategy 1 removed any sequence with an alien index >= 25 in either database and sequences that failed to return any hit to an alveolate sequence as contamination.
- meso-final-tophit-strateg2.xlsx: Excel document of nr and custom database blast results for Mesodinium sequences after applying filtering strategy 2. Strategy 2 removed any sequences with an alien index >= 25 in either database but further evaluated sequences without any alveolate hits. These sequences were considered contamination if they returned a best blast hit to bacteria, archaea, or algae (defined here as stramenopiles, dinoflagellates, cryptophytes, the archaeplastida, rhizaria, euglenids, and viridiplantae) with a pid and percent query coverage (qcov) >= 70 % or with a GC content >= 0.60. Sequences were also removed if the nr and custom databases concordantly returned bacteria or cryptophyte best blast hits.
- meso-final-tophit-strateg3.xlsx: Excel document of nr and custom database blast results for Mesodinium sequences after applying filtering strategy 3. Strategy 3 removed any sequences with an alien index >= 25 but further evaluated sequences without alveolate hits. These sequences were removed if they returned a best blast hit to an algal sequence with pid and qcov >= 70 %, a best blast hit to a cryptophyte in both databases, or if the sequence had a GC content >= 0.60 with a top hit to a bacterial or algal sequence. Additional prokaryotic contamination was filtered when sequences returned best blast hits to bacteria/archaea in either database with a pid >= 50 % or when 100 % of the blast results or one less than the total number of blast results returned for both databases were to bacteria/archaea. Sequences that returned a best blast hit to bacteria in the nr database but a non-algal hit in the custom database were also removed if the pid of the bacterial hit was >= 25 % that of the hit from the custom database. Entries in red type indicate unfiltered contaminants.
- RNASeq-library-metadata.xlsx: Excel document of RNASeq library treatments and naming conventions.
References
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods.
Buchfink B, Reuter K, Drost HG, "Sensitive protein alignments at tree-of-life scale using DIAMOND", Nature Methods 18, 366–368 (2021). doi:10.1038/s41592-021-01101-x
Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences. J Mol Biol. 2016 Feb 22;428(4):726-731. doi: 10.1016/j.jmb.2015.11.006. Epub 2015 Nov 14. PMID: 26585406.
Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015 May 15;31(10):1674-6. doi: 10.1093/bioinformatics/btv033. Epub 2015 Jan 20. PMID: 25609793.
"CD-HIT: a fast program for clustering and comparing large sets of protein or nucleotide sequences", Weizhong Li & Adam Godzik. Bioinformatics, (2006) 22:1658-1659
"CD-HIT: accelerated for clustering the next generation sequencing data", Limin Fu, Beifang Niu, Zhengwei Zhu, Sitao Wu & Weizhong Li. Bioinformatics, (2012) 28:3150-3152
Rice P., Longden I. and Bleasby A. EMBOSS: The European Molecular Biology Open Software Suite. Trends in Genetics. 2000 16(6):276-277
Access information
Other publicly accessible locations of the data:
- JGI: The role of acquired phototrophy in phytoplankton blooms: Insights from the Mesodinium rubrum genome (Proposal ID: 503035)
Data was derived from the following sources:
- This study and NCBI (see tables above)
RNASeq libraries
We assembled seven Mesodinium lineage transcriptomes: three from RNA-Seq data that we generated for M. pulex strain EPMP20B2, M. chamaeleon strain NRMC1802, and M. rubrum strain CBJR05, and four from data obtained from NCBI’s Sequence Read Archive (SRA) for M. chamaeleon strain NRMC1501 (PRJNA560220) and M. rubrum strains MBL-DK2009 (PRJNA560206), Nantes (PRJEB53438), and CCMP 2563 (PRJNA560206).
Transcriptome assembly
Transcriptome assemblies from Illumina data were generated for three Mesodinium species Mesodinium pulex, Mesodinium chamaeleon, and Mesodinium rubrum, which included one strain of M. pulex, two different cultures of M. chamaeleon, and four strains of M. rubrum for a total of 7 transcriptomes
All Mesodinium libraries were processed and assembled by an in-house Nextflow v.2 workflow. TrimGalore v.0.6.7 (https://github.com/FelixKrueger/TrimGalore) removed adapters from raw reads, excluded reads < 75 bp in length, and trimmed the ends of reads with a PHRED quality score < 20. Bacterial contamination was removed by Kraken2 v.2.1.3 with the standard-8 database (Wood et al. 2019). Prey contamination was removed by mapping bacteria-filtered reads to the prey transcriptome with BBmap v.39.01 and the following parameters: minration = 0.9, maxindel = 3, bwr = 0.16, bw = 12, minhits = 2, qtrim = r, trimq = 10, kfilter = 25, maxsites = 1 and k = 14. Reads were assembled with Megahit v.1.2.9 (Li et al 2015) using the “meta-large” parameter. CD-hit-est v.4.8.1 (Li and Godzik 2006; Li et al. 2012) clustered transcripts at 97 % identify.
Prey contamination at the transcript level was removed by Blastn v.2.14.0+ (Camacho et al 2009) searches against a cryptophyte database containing transcripts from all prey assemblies generated during this study as well as all cryptomonad genomes available from NCBI’s GenBank as of 2022. Mesodinium transcripts with > = 75 identity and > = 75 query coverage to a hit in the cryptomonad database were excluded. Transcripts from each library/treatment were concatenated into a single file for each Mesodinium sample and redundancy was reduced by performing another round of clustering with CD-hit-est at 97 % identity.
Coding sequence prediction
Transdecoder v.5.7.1 (Haas, BJ. https://github.com/TransDecoder/TransDecoder) identified putative coding regions using both the TransDecoder.LongOrfs and TransDecoder.Predict functions and the Mesodinium genetic code. Final protein predictions were clustered at 95 % identity by CD-HIT.
Annotation
All proteomes were annotated by the KEGG server (https://www.kegg.jp/kegg/)using the GhostKOALA option ((Kanehisa et al. 2016).
Ciliate proteome
Bacteria and prey contamination were removed at the protein level by Diamond v.2.1.8.162 blastp (Buchfink et al 2021) searches against a the NCBI non-redundant (nr) database (downloaded 2024-04-24) and a custom database containing proteomes from representatives of major eukaryotic lineages as well as from bacterial and archaeal lineages to produce a final set of ciliate sequences. Three filtering strategies were evaluated to determine their influence on KEGG pathway completeness (see README files associated with supplementary data).
References
Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015 May 15;31(10):1674-6. doi: 10.1093/bioinformatics/btv033. Epub 2015 Jan 20. PMID: 25609793.
"CD-HIT: a fast program for clustering and comparing large sets of protein or nucleotide sequences", Weizhong Li & Adam Godzik. Bioinformatics, (2006) 22:1658-1659
"CD-HIT: accelerated for clustering the next generation sequencing data", Limin Fu, Beifang Niu, Zhengwei Zhu, Sitao Wu & Weizhong Li. Bioinformatics, (2012) 28:3150-3152
Wood, D.E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol 20, 257 (2019). [https://doi.org/10.1186/s13059-019-1891-0](https://www.google.com/url?q = https://doi.org/10.1186/s13059-019-1891-0&sa = D&source = docs&ust = 1739214057084404&usg = AOvVaw0cHPI_XYpRMSTwtY-OSblI)
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., and Madden, T.L. 2009. BLAST+: architecture and applications. BMC Bioinformatics, 10, 421.
Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences. J Mol Biol. 2016 Feb 22;428(4):726-731. doi: 10.1016/j.jmb.2015.11.006. Epub 2015 Nov 14. PMID: 26585406.
Buchfink B, Reuter K, Drost HG, "Sensitive protein alignments at tree-of-life scale using DIAMOND", Nature Methods 18, 366–368 (2021). doi:10.1038/s41592-021-01101-x
