bioinfoihb/Fish_GUE

FishGUE

FishGUE is a unified fish genomics benchmark developed for evaluating DNA foundation models and other sequence models on fish genomic prediction tasks.

It was introduced in the FishNALM study, where it was used to systematically benchmark fish-specific and general DNA language models across diverse regulatory sequence prediction tasks.

Dataset summary

FishGUE contains 17 supervised prediction tasks spanning four task groups:

• Histone mark prediction
• Transcription factor binding-site prediction
• Promoter prediction
• Splice-site prediction

The benchmark covers input sequence lengths from 300 bp to 2500 bp and includes both zebrafish-based datasets and multi-species cyprinid splice datasets.

Why FishGUE?

Fish genomic benchmarks remain limited compared with those available for human, plant, or broad multi-species genomic modeling. FishGUE was constructed to provide a unified benchmark for evaluating model performance on representative fish genomic sequence prediction problems, especially those relevant to regulatory sequence recognition and gene structure annotation.

Benchmark composition

The FishGUE benchmark includes the following 17 tasks.

Category	Task	Species	Sequence length (bp)	Train / Val / Test
Histone mark prediction	H3K4me1	Danio rerio	variable (≤2500)	48815 / 6102 / 6102
Histone mark prediction	H3K4me3	Danio rerio	variable (≤2500)	47482 / 5935 / 5936
Histone mark prediction	H3K9me3	Danio rerio	variable (≤2500)	40125 / 5016 / 5016
Histone mark prediction	H3K27ac	Danio rerio	variable (≤2500)	27611 / 3451 / 3452
Histone mark prediction	H3K27me3	Danio rerio	variable (≤2500)	27017 / 3377 / 3378
TF binding-site prediction	CTCF	Danio rerio	800	28526 / 3566 / 3566
TF binding-site prediction	Pou5f1	Danio rerio	800	11128 / 1391 / 1391
TF binding-site prediction	Sox2	Danio rerio	800	9717 / 1215 / 1215
Promoter prediction	Core promoter	Danio rerio	300	17222 / 2153 / 2153
Promoter prediction	Core promoter (TATA)	Danio rerio	300	3464 / 433 / 434
Promoter prediction	Core promoter (non-TATA)	Danio rerio	300	13757 / 1720 / 1720
Promoter prediction	Promoter	Danio rerio	1000	17222 / 2153 / 2153
Promoter prediction	Promoter (TATA)	Danio rerio	1000	3464 / 433 / 434
Promoter prediction	Promoter (non-TATA)	Danio rerio	1000	13757 / 1720 / 1720
Splice-site prediction	Splicing (acceptor)	Cyprinidae (5 species)	600	17200 / 2150 / 2150
Splice-site prediction	Splicing (donor)	Cyprinidae (5 species)	600	27600 / 3450 / 3450
Splice-site prediction	Splicing (both)	Cyprinidae (5 species)	600	1720 / 2150 / 2105

Data sources and construction overview

According to the FishNALM manuscript, FishGUE was assembled from the following sources:

• Histone mark datasets were derived from public zebrafish ChIP-seq peak datasets.
• Transcription factor binding-site datasets were built from public ChIP-seq peaks for CTCF, Pou5f1, and Sox2.
• Promoter datasets were constructed from zebrafish promoter annotations from the Eukaryotic Promoter Database (EPD).
• Splice-site datasets were compiled from annotated genomes of five cyprinid fish species.

For all tasks, positive and negative examples were constructed through task-specific processing, then split into training, validation, and test sets using an 8:1:1 ratio.

Suggested repository organization

If you plan to upload FishGUE as a single Hugging Face dataset repository, a clean structure is:

FishGUE/
├── README.md
├── histone/
│   ├── H3K4me1_train.tsv
│   ├── H3K4me1_val.tsv
│   ├── H3K4me1_test.tsv
│   └── ...
├── tfbs/
│   ├── CTCF_train.tsv
│   ├── CTCF_val.tsv
│   ├── CTCF_test.tsv
│   └── ...
├── promoter/
│   ├── core_promoter_300_train.tsv
│   └── ...
└── splice/
    ├── splice_acceptor_train.tsv
    └── ...

If your files are already packaged in another layout, you can keep that layout and simply explain it in this README.

Intended uses

FishGUE is intended for:

• benchmarking DNA foundation models on fish genomic sequence prediction tasks
• evaluating transfer learning performance in fish genomics
• comparing task robustness across promoter, chromatin, TFBS, and splice-site prediction settings
• developing new fish-specific sequence models and downstream classifiers

Limitations

• Most non-splice tasks are based on zebrafish data.
• The splice-site benchmark uses five cyprinid species, so broader phylogenetic coverage remains limited.
• FishGUE is designed as a research benchmark and should not be interpreted as a clinical or diagnostic dataset.
• Performance on FishGUE does not guarantee performance on all fish species or all regulatory genomics tasks.

Citation

If you use FishGUE in your work, please cite the FishNALM manuscript.

Manuscript:

FishNALM: A Foundation DNA Language Model for Fish Genomes

Project links

• GitHub: bioinfoihb/FishNALM

Contact

Xiao-Qin Xia
Institute of Hydrobiology, Chinese Academy of Sciences
Email: [email protected]
Email: [email protected]