Candidate studies to curate
A screened shortlist of real, public M. gigas datasets to register after HESSER2024_VCOR. Every accession here was verified against NCBI BioProject and the ENA read-run API on 2026-08-28; sample counts and group structures come from the deposited run metadata, not from paper text.
This is a working backlog, not a commitment. Update it as studies are curated or rejected.
The selection criterion that actually matters
The obvious filter — “does the paper publish full statistics?” — is the wrong one to lead with.
HESSER2024_VCOR harmonizes cleanly, resolves 87.2% of its identifiers, and contributes nothing to any meta-analysis, because its supplementary table reports only log2FoldChange and padj. No standard error, no unadjusted p-value, so no inverse-variance weight. That is not an unlucky draw: a significance-filtered table with adjusted p-values only is the normal format for supplementary DE tables in this literature. Selecting studies by hoping their supplementary files are richer will mostly reproduce the same dead end.
The reliable route to poolable evidence is raw reads in SRA. When AREE reanalyzes raw data itself, its own DESeq2 run produces lfcSE and an unadjusted p-value by construction — the study becomes poolable regardless of what the authors chose to publish. It also finally exercises the raw_reanalysis Nextflow path, which has never been run against real data (see implementation_status.md).
So the screen applied here, in priority order:
- Raw reads deposited and public (SRA/ENA), not just a supplementary table.
- Replicated design, n ≥ 3 per group. See the rejected candidate below — this is not a formality.
- Resilience-relevant contrast. Prefer a tolerance/resistance phenotype (resistant vs susceptible lineages) over pure exposure (treated vs control), per resilience_vs_exposure.md. Judge this on whether a phenotype was measured, not on how the title is worded — see the correction above.
- RNA-seq first, because the intake converter currently handles only differential-expression tables and the RNA-seq workflow is the most complete.
- Stressor and phenotype spread, so that pooled groups have more than one study in them. Two studies of the same stressor beat five of five different ones — a meta-analysis of k=1 is not a meta-analysis.
Tier 1 — curate these first
#1 is registered as
CALLA2026_OSHV— design verified, sample sheet and FASTQ manifest generated, reanalysis not yet run. See first_raw_reanalysis.md.#3 is registered as
IOCAS2022_OA_ENERGY(2026-09-30) — design verified (18 animals, n=3 per group, time-matched controls), tissue is hepatopancreas (digestive gland), and reanalysis has not been run. No publication cites the BioProject, so the OA dose is unknown and all three comparisons areexposure_only. The same-lab PGC-1α paper (doi:10.1016/j.cirep.2026.200308) uses gonad and qPCR, not these data.Correction from the first draft of this page. #1 was listed here as a study whose “contrast is a resilience phenotype, not an exposure”, on the strength of its BioProject title (“Evaluating Pacific oyster lineages for tolerance to Ostreid herpesvirus”). Curating it showed that is not what the deposited data contains: there is no survival, mortality, or viral-load measurement for these animals, and the publication frames its results as groundwork for future tolerance breeding. It is registered as
disease_susceptibility, notdisease_resistance. A resilience-sounding project title is not a resilience phenotype — check for a measured outcome before promising one.
| # | BioProject | Runs | Design (from run metadata) | Resilience context | Why first |
|---|---|---|---|---|---|
| 1 ✅ | PRJNA1329250 |
42 RNA-seq | 2 populations × 4 viral-strain levels (Control/Australia/France/USA), n=5 challenged / n=6 control | OsHV-1 challenge in two hatchery populations | Well replicated across all eight groups, and the same stressor class as the study already registered, so the two can eventually pool. Calla et al. 2026 (10.1016/j.fsi.2026.111154). |
| 2 | PRJNA593309 |
43 RNA-seq | OsHV-1 × temperature (21/26/29 °C) × timepoint, n=3 | Disease resistance under thermal modulation | Multi-stressor, well replicated, and published open access — Delisle et al. 2020, J Exp Biol (10.1242/jeb.226233). Pairs with #1 on pathogen challenge. |
| 3 ✅ | PRJNA826964 |
18 RNA-seq | control vs OA × 3 timepoints (7/28/56 d), n=3 | Ocean acidification, energy metabolism | Clean 2×3 factorial, small enough to reanalyze quickly, and opens a second stressor class. |
Doing #1 and #2 together is the point: they give the pathogen-challenge group k ≥ 2 with real standard errors, which is the first time random-effects pooling would run on anything but simulated data.
Tier 2 — good candidates, specific caveats
| # | BioProject | Runs | Design | Context | Caveat |
|---|---|---|---|---|---|
| 4 | PRJNA678408 |
10 WGBS | 5 diploid + 5 triploid | Desiccation + acute heat | Would be AREE’s first real methylation study. But the intake converter does not handle region tables yet, and coordinate-based evidence is exposed to the assembly change described in handling_genome_versions.md. |
| 5 | PRJNA762441 |
18 RNA-seq | diploid/triploid × 3 timepoints, n=3 | Thermal stress, ploidy contrast | Clean design; ploidy is a useful resilience covariate. No linked publication confirmed. |
| 6 | PRJNA913164 |
72 | diploid/triploid, marine heatwave | Thermal tolerance | Tag-seq (3′ counts), not standard RNA-seq — quantification differs from the salmon-based workflow. Largest n on the list. No publication found; treat as unpublished data. |
| 7 | PRJNA735889 |
76 (RNA-seq + amplicon) | individually labelled, ~n=5/group | OA “tipping point” | Mixed assay project; the amplicon runs are a separate microbiome experiment and must be excluded at intake. |
| 8 | PRJNA1196326 |
6 RNA-seq | 2 groups × n=3 | Transgenerational OA | Very small, but transgenerational designs are directly relevant to breeding and rare in the public record. |
| 9 | PRJNA877226 |
6 RNA-seq | run labels blank in ENA | Vibrio × high temperature | Multi-stressor and cheap, but the deposited metadata does not describe groups — the design must be recovered from the paper before it is worth registering. |
Adjacent, but a different evidence type
PRJNA1190893— low-salinity adaptation, 102 WGS runs. Population genomics, not differential expression. Registering it would mean a new harmonizer for variant/selection-scan evidence and a newfeature_type. Worth doing eventually — salinity tolerance is a real breeding target and AREE currently has no real salinity evidence — but it is a feature, not a curation task.Heat-resistant vs heat-susceptible families (CIBNOR breeding program, Baja California Sur), Arredondo-Espinoza et al. 2023, Comp Biochem Physiol Part D Genomics Proteomics 47:101089 (10.1016/j.cbd.2023.101089, PMID 37269757). Earlier drafts of this page cited it as “Escobedo-Fregoso et al.” — she is the last and corresponding author; the first author is Arredondo-Espinoza. Author list and journal name verified against PubMed on 2026-09-05.
The framing is exactly what AREE wants — RR vs SS phenotypes from a breeding program under an oscillatory thermal challenge (26–34 °C, 30 days, sampled at day 0 and day 30). It would be AREE’s first real study with a measured resilience outcome, and its first thermal stressor; every real candidate in the current pool is
disease_associatedfor want of exactly this. Per-group replication is not stated in the abstract and must be confirmed before registration.No public raw-data accession could be located as of 2026-09-05: BioProject searches on organism plus thermal-challenge terms and on author/CIBNOR both returned nothing, and the Europe PMC record reports no associated data or supplement with no open-access full text to read the availability statement from. Note that
sr320is a co-author, so lab storage and a direct ask to the corresponding author are better first moves than cold outreach. Tracked in issue #6.
Rejected, and why it matters
PRJNA623063 — “Transcriptome of the Pacific Oyster, Crassostrea gigas Larvae after Vibrio alginolyticus Challenge”, 12 RNA-seq runs.
On title alone this looked like the ideal second study: same life stage, same stressor class, and nearly the same phenotype as HESSER2024_VCOR. The run metadata says otherwise — all 12 runs share a single sample_alias (Oyster_M49) across 12 timepoints (T01–T12). It is an unreplicated time course, so no valid differential-expression contrast can be computed from it.
Recording this because the failure is invisible from the abstract, and because a curator working from titles would have spent real effort before finding out. Check sample_alias before downloading anything.
Sourcing notes
- 93 candidate BioProjects were found for C. gigas / M. gigas across the stressor terms in AREE’s ontology (thermal, acidification, pathogen, salinity, hypoxia, desiccation). The shortlist above is the subset passing the screen.
- GEO holds only 10 oyster expression series and is largely pre-2015; the useful corpus is in SRA/ENA. Do not treat a GEO search as sufficient.
- Hypoxia is badly underrepresented: exactly one BioProject matched, and it has no reads in ENA. AREE’s phenotype ontology carries
hypoxia_tolerance, but there may be no public transcriptomic dataset to populate it.
Bibliographic metadata for every cited paper was retrieved from PubMed — including the author order, which one of them had wrong until 2026-09-05.