🪸 Coral Multi-'Omics Explorer

Multi-'Omic analyses of reef-building corals

P. acutathermal stress
P. acutatemp. × pCO₂
P. acutatrans-gen
S. hystrixvariable temp.
P. acutareference genome
S. fittireference genome
A. cervicornisresilience
O. faveolatableaching resilience
Symbiodiniaceaemerged endosymbionts
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Select a species tab to load a built-in dataset, or click Load JSON to import your own.

Need to generate the JSON? Run prep_transcriptome_data.py on your NGS folder.

Volcano Plot
Differential expression
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Showing top 5,000 most-variable contigs. Hover a point to see its ID.
Expression Heatmap
Top 50 most-variable contigs across all samples
🧬 Custom gene set — paste your own contig IDs
Expression Table
All filtered contigs — search, sort, and filter
Contig Log2FC p-value Mean A Mean B Top BLAST hit KEGG / GO qPCR
Cross-experiment ortholog search
Find the same gene across PDLTTE, PDpCO2, SHVTS, and the P. acuta genome — linked by KEGG ortholog (KO) or eggNOG gene name
🔗

Enter a gene name or KEGG ortholog ID.

GO / KEGG Enrichment
Over-representation of GO terms & KEGG orthologs among the differentially expressed genes
ℹ Glossary — what the abbreviations mean
DEG / DE = differentially expressed gene(s) (here, |Log2FC| ≥ 1 and p < 0.05)  ·  bg = background (all annotated genes the DEGs are compared against)  ·  Log2FC = log2 fold change between the two conditions  ·  p = p-value (hypergeometric test)  ·  FDR = false-discovery rate (Benjamini–Hochberg-corrected p)  ·  fold = enrichment fold (observed ÷ expected DEGs for that term)  ·  expected = DEGs expected by chance  ·  GO = Gene Ontology term  ·  KO = KEGG Ortholog (K-number)  ·  FPKM = fragments per kb per million reads (expression unit)
Hypergeometric test vs the annotated dataset background · BH-FDR.
📈

Select a comparison with DE results.

KEGG Pathways
Differentially expressed contigs grouped by KEGG pathway
No KEGG annotation in the current dataset. Add a "kegg_ids" field (semicolon-separated) per contig in your JSON to enable this view.
Global metabolism map (KEGG map01100)

Open the KEGG global metabolic-pathways map with this dataset's KEGG orthologs (KOs) overlaid — shaded by representation (darker = more genes mapped to that reaction). Rendered on KEGG; for the complete KO set, download the list and paste it into KEGG Mapper's "Search&Color Pathway".

BLAST Search
Nucleotide/protein sequence search against this transcriptome
BLAST requires a server-side backend. To enable: install NCBI BLAST+ locally and run transcriptome_server.py --make-blast-db.

Sequence files:
 • ~/Documents/Bioinformatics and MS/Symbiodiniaceae/Symbiodinium SHVTS nucleic acids.fa
 • ~/Documents/Bioinformatics and MS/Symbiodiniaceae/Symbiodinium PDLTTE nucleic acids.fa
Query sequence (FASTA format)
Or use NCBI BLAST ↗
blastn: paste a nucleotide sequence to find matching transcripts.
What gets searched: your query runs against only the current tab's compartment, and the program picks the molecule:
 • blastn / tblastx / tblastn → that compartment's nucleotide sequences
 • blastp / blastx → that compartment's protein sequences
Switch the host / endosymbiont / holobiont tab to target a different compartment (e.g. P. acuta · host → host transcripts/proteins only).
Proteomics search (MS-GF+)
Identify peptides/proteins in your mass-spec data against the curated sequence databases
Upload spectra and choose a database
Accepts .mzML / .mzML.gz (recommended) or Thermo .raw (if ThermoRawFileParser is installed). Results are filtered to a 1% false-discovery rate. First search per database is slower (MS-GF+ builds its index).
Download Data
Export expression tables and DE results
Current dataset

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FASTA & TSV honor the filters set on the Expression Table tab (compartment, molecule, DE, and search) and the active comparison. The client export covers the contigs loaded in the browser (top by variance + all DE). For the complete filtered set (e.g. every host mRNA), use the server export when the backend is online:

Download full sequence subsets (FASTA)

Complete, gzipped nucleotide FASTA for an entire compartment of an experiment — e.g. every Symbiodiniaceae (endosymbiont) sequence from S. hystrix. Hosted directly; no backend needed.

loading available files…
Reference data & help
🧬 PDLTTE host genotype (mORF alignment, FASTA) 📖 Help / README 🧫 qPCR assay files
Cleaned data (CSV): 📄 PDLTTE qPCR data 📄 SHVTS iTRAQ proteins 📊 SHVTS iTRAQ (xlsx)

The host genotype is the PDLTTE mitochondrial ORF (mORF) alignment vs P. damicornis mitogenomes. qPCR primer/sequence files are also linked inline (🧫 qPCR) from the Expression Table for genes with a designed assay.

Reference sequences (predicted proteomes, FASTA)

Complete predicted-protein FASTA for each reference genome/transcriptome (gzipped) — the full genome-derived sets, including proteins not detected by MS.

🧬 P. acuta genome proteome 🧬 A. cervicornis genome proteome (33,322) 🧬 S. fitti genome proteome (37,621) 🧬 O. faveolata host proteome (73,093) 🧬 O. faveolata symbiont · SYMBOF (76,145)

Nucleotide transcriptomes (mRNA):

🧬 O. faveolata host transcriptome (87,440) 🧬 O. faveolata symbiont transcriptome (114,424)

Nucleotide genome assemblies are at their original sources: P. acutaVidal-Dupiol et al. 2019; S. fittiReich et al. 2021; A. cervicornis — Baums lab.

Proteomic raw data — external repositories

Raw mass-spectrometry files are large and are archived in public proteomics repositories rather than re-hosted here:

SHVTS iTRAQ — MassIVE MSV000085863 ↗ SHVTS — NOAA NCEI ↗ PDpCO₂ iTRAQ — MassIVE MSV000085868 ↗

O. faveolata deposits (linked as those tabs are added): 2017 shotgun MSV000086098, 2017 iTRAQ MSV000086530, FKNMS MSV000089240. The A. cervicornis TMT data are unpublished.

JSON schema

Each JSON file should have this top-level structure. Per-contig fields:

{
  "species": "Seriatopora hystrix",
  "study": "SHVTS",
  "comparison": "Variable vs. Stable thermal regime",
  "total_contigs": 209481,
  "samples": ["HBH_V_1","HBH_V_2","HBH_V_3","HWN_S_1","HWN_S_2","HWN_S_3"],
  "sample_meta": [{"name":"HBH_V_1","site":"Houbihu","condition":"Variable","rep":1}, ...],
  "contigs": [
    {
      "id": "comp12345_c0_seq1",
      "lfc": 2.34,          // log2 fold change (Variable / Stable)
      "pval": 0.0012,        // p-value (Welch t-test or DESeq2 padj)
      "nlp": 2.92,           // -log10(pval) — for volcano y-axis
      "ms": 12.4,            // mean FPKM in Stable condition
      "mv": 55.1,            // mean FPKM in Variable condition
      "var": 180.2,          // variance across all samples
      "fpkm": [44,60,62, 10,14,15],  // per-sample FPKM (order matches "samples")
      "top_blast_hit": "heat shock protein 70 [Acropora digitifera]",
      "blast_evalue": 1.2e-45,
      "gene_name": "hsp70",
      "kegg_ids": "K04043",  // semicolon-separated if multiple
      "go_terms": "GO:0006950;GO:0051082",
      "annotation": "Stress response / chaperone"
    }
  ],
  // Optional: multiple DE contrasts (e.g. PDLTTE 2×2 factorial)
  "contrasts": [
    {
      "name": "High vs. Control — Week 2",
      "comparison": "30°C vs. 27°C at week 2",
      "contigs": [ ...same schema... ]
    },
    {
      "name": "High vs. Control — Week 36",
      "comparison": "30°C vs. 27°C at week 36",
      "contigs": [ ... ]
    }
  ]
}
About
Coral Multi-'Omics Explorer — datasets and methods
SHVTS — Seriatopora hystrix Variable Temperature Study

Corals were collected from two sites in Nanwan Bay, southern Taiwan in 2010 and maintained at the National Museum of Marine Biology & Aquarium (NMMBA):

  • Houbihu (HBH) — naturally thermally variable site, influenced by upwelling (23–29°C cycles in situ)
  • Houwan (HWN) — naturally thermally stable site, no upwelling influence (~26°C in situ)

In a 2×2 factorial design, corals from each site were assigned to either a stable 26°C or a variable 23–29°C (6-hour cycle) treatment for one week (n=3 tanks per group). Host and Symbiodiniaceae (endosymbiont) compartments were separated by BLAST taxonomy assignment. Assembly: Trinity, 209,481 total contigs; 118,772 with stable expression (FPKM>0). Annotation: TransDecoder ORFs → BLASTp nr (e < 1×10⁻⁵) → 41,175 annotated proteins. Composition: ~53% host coral, ~30% Symbiodiniaceae, ~10% bacteria, ~7% intermediate.

DOI: 10.1111/mec.13896

PDLTTE — Pocillopora acuta Long-Term Thermal Experiment

Coral nubbins (P. acuta) from Houbihu, Nanwan Bay, Taiwan (21°56′18″N, 120°44′45″E) were maintained in mesocosm tanks at control 27°C or high 30°C for up to 36 weeks. Sampling at weeks 2 and 36 produced a 2×2 factorial design (temperature × time; n=3 tanks × 2 nubbins per tank). Sample naming: {temp}{week}T{tank}S{nubbin} — e.g. C2T1S2 = Control 27°C, Week 2, Tank 1, Nubbin 2.

Assembly: Trinity + MIRA → 236,435 contigs (≥200 bp after cd-hit-est 95% clustering). Composition: ~60% host anthozoan, ~40% Symbiodiniaceae by mRNA. Annotation: TransDecoder ORFs → BLASTp nr (e < 1×10⁻¹⁰) → KEGG (52,768 proteins annotated) → GO via Pfam-HMM. Expression: RSEM FPKM.

DOI: 10.1111/mec.12982

Methods

Expression values are FPKM (Fragments Per Kilobase of transcript per Million reads mapped), quantified with RSEM. Differential expression in this explorer uses Welch two-sample t-tests between user-selected conditions; log₂ fold change uses a pseudocount of 0.1 to handle zero-FPKM values. KEGG annotations via KOBAS; functional annotations via Pfam-HMM and HMMER. Protein sequences from TransDecoder ORF prediction (6-frame translation fallback when .pep unavailable). BLAST search (blastn, blastp, blastx, tblastn, and tblastx) requires the local server to be running with pre-built databases.

Citations

Mayfield AB, Wang Y-B, Chen C-S, Chen S-H, Lin C-Y (2014) Compartment-specific transcriptomics in a reef-building coral exposed to elevated temperatures. Molecular Ecology 23: 5816–5830. DOI: 10.1111/mec.12982

Mayfield AB, Fan T-Y, Chen C-S (2016) Dual-compartmental transcriptomics of a reef-building coral exposed to a thermally variable and thermally stable reef environment. Molecular Ecology 25: 2899–2919. DOI: 10.1111/mec.13896

Mayfield AB, Chen Y-J, Lu C-Y, Chen C-S (2018) The proteomic response of the reef coral Pocillopora acuta to experimentally elevated temperatures (PDLTTE proteomics). PLOS ONE 13: e0192001. DOI: 10.1371/journal.pone.0192001

Mayfield AB, et al. (in prep.) Pocillopora acuta adult pCO₂ × temperature transcriptome (PDpCO₂). For details on a sister study performed with the larvae released from these adult corals, see Putnam et al. (2013), Marine Biology.

Mayfield AB (2020) Proteomic signatures of corals from thermodynamic reefs (SHVTS iTRAQ proteomics). Microorganisms 8: 1171. DOI: 10.3390/microorganisms8081171

Data Access

This explorer was built by Coral Reef Diagnostics. The original interactive websites for these datasets (hosted at the Institute of Information Science, Academia Sinica, Taiwan) are no longer online. This site aims to restore full queryability of both transcriptomes. Source data are from the published supplementary materials and original sequencing files.

Analysis methods in this explorer
  • Differential expression: main effects by Welch two-sample t-test on log₂(FPKM+0.1); the temperature×time / site×treatment / temperature×CO₂ interaction term by two-way ANOVA (balanced designs) or an OLS interaction t-test (unbalanced PDpCO₂). "DEG" = |Log₂FC|≥1 and p<0.05.
  • Compartment classification (host / Symbiodiniaceae / microbe): every contig is binned by sequence homology — eggNOG / NCBI-nr best-hit lineage (host = Metazoa; symbiont = Alveolata, Stramenopiles, or green plants, sensu Mayfield et al. 2014; microbe = Bacteria/Archaea/Virus) supplemented by DIAMOND blastx against species-matched host + Symbiodiniaceae proteomes for contigs lacking an annotation. Contigs with no homology default to host.
  • Host : Symbiodiniaceae normalization (toggle): each sample's values are scaled so its compartment total equals the cross-sample mean, controlling for differing symbiont load (sensu Mayfield et al. 2014).
  • GO / KEGG enrichment: hypergeometric over-representation of the DEG set against the annotated dataset background, Benjamini–Hochberg FDR.
  • Sample ordination (PCA): principal components of the top-variance genes (log₂ FPKM, gene-centered).
  • Cross-experiment orthologs: genes linked across experiments by shared KEGG ortholog (KO) and eggNOG gene name.
  • Proteomics: iTRAQ abundances normalized to the pooled reference channel; qPCR normalized to Solaris & genome-copy-proportion spikes; on-the-fly peptide search via MS-GF+ (1% FDR).
Understanding the protein numbers
  • Hypothetical proteome — every protein the organism is predicted to make: the full conceptually-translated reference (e.g. O. faveolata host 73,093; in-hospite Symbiodiniaceae 76,145). For the corals/symbionts assembled de novo, these are ORFs translated from the reference transcriptome; for A. cervicornis / S. fitti they come from the Baums reference genomes.
  • Sequenced — proteins actually identified by mass spectrometry (master protein at High/Medium FDR), pooled across all iTRAQ/TMT batches of a study. This is the headline count on each proteome panel.
  • iTRAQ-quantified only (toggle) — the far smaller subset of sequenced proteins that additionally carry quantitative iTRAQ reporter-ion ratios. Ticking the box filters the table and headline count to these.
  • Composite Symbiodiniaceae reference: the in-hospite Symbiodiniaceae proteome is a composite, conceptually translated from multiple co-assembled transcriptomes — the symbiont community spans more than one genus (e.g. Breviolum + Durusdinium in O. faveolata), so transcripts from several Symbiodiniaceae are represented together.
How to cite

Please cite the original study for any dataset you use (DOIs above), and you may additionally acknowledge this explorer:

Coral Multi-'Omics Explorer, Coral Reef Diagnostics (coralreefdiagnostics.com), accessed [date].

Data availability: PDLTTE assembly & expression — NCBI BioProject PRJNA227785 and Dryad 10.5061/dryad.rh04m; SHVTS — Mol. Ecol. 2016 supplements; SHVTS iTRAQ proteome — MassIVE MSV000085863 (cross-listed at NOAA NCEI); PDpCO₂ adult-coral iTRAQ proteome — MassIVE MSV000085868; P. acuta reference genome — Vidal-Dupiol et al. 2019 (bioRxiv 698688); S. fitti genome — Reich et al. 2021 (Mol. Ecol.)