GREGOR is an AI-assisted platform for plant trait genomics. It provides an integrated pipeline that takes researchers from scientific literature all the way to a ranked list of candidate genes in their organism of interest — supporting both gene editing target selection and broader biological process exploration.
GREGOR is designed for plant biologists, genomic selection researchers, and crop developers working with model and non-model plant species. It integrates text mining, orthology mapping, gene regulatory network analysis, and genomic annotation into a single collaborative environment.
Open the User ManualThe Trait Design module guides users through a linear, AI-assisted workflow that converts a description of a trait or biological process into a prioritized list of candidate genes. It supports two complementary research objectives:
Identify high-confidence candidate genes associated with a specific trait in your plant of interest. Prioritize editing targets backed by literature evidence, orthology, and network connectivity.
Explore genes associated with a biological process or set of terms — without a predefined editing goal. Useful for understanding trait architecture, identifying key regulators, and hypothesis generation.
Automatically mines thousands of PubMed articles to identify genes associated with your trait or biological process of interest. GREGOR surfaces the evidence from published research.
Genes found in literature often come from model species like Arabidopsis. GREGOR maps them directly to your target organism's genome via NCBI RefSeq orthology — so you work with the exact genes in your species of interest, not just surrogates.
GREGOR constructs the Gene Regulatory Network (GRN) of your trait, revealing functional interactions and regulatory relationships between genes. Genes with lower network centrality often represent the most promising intervention targets, with more specific effects and lower pleiotropy risk.
A prioritized list of candidate genes ranked by integrated evidence from literature mining, orthology mapping, network centrality, and tissue-specific expression patterns. Results are designed for collaborative review, enabling multi-user annotation, validation, and selection.
GREGOR provides four search modes to explore plant genomic data across multiple organisms and assemblies:
Find genes by their identifier or name across all supported organisms and assemblies. Optionally extend the search to gene descriptions for broader results.
The most powerful search mode in GREGOR. Annotations are generated by a proprietary deep learning model, enabling accurate functional annotation across all supported organisms — including non-model species that lack well-curated reference annotations.
Unlike databases that rely on annotation transfer from model organisms like Arabidopsis thaliana, GREGOR's annotations are computed directly for each genome, ensuring reliability even for newly assembled or understudied species.
Supported annotation vocabularies:
Browse all genes within a specific plant species or assembly. Explore genomic diversity and access the complete gene catalog for any supported organism.
Submit an amino acid or nucleotide sequence and identify matching genes across the full GREGOR database or within a specific organism using BLAST-based alignment. Ideal for identifying genes from experimental data or cross-species comparisons.
From the gene information panel in Explore Genes, researchers can access integrated tools for precision genome editing design:
Access CRISPR tools by searching for your gene of interest in Explore Genes and opening the gene information panel. Go to Explore Genes →
GREGOR currently supports the following plant species and assemblies:
Need a different organism? Contact us at gregor@meristem.bio to discuss adding support for your species of interest.
If you use GREGOR in your research, please cite:
GREGOR v3. Meristem.bio. https://gregor.meristem.bio
For questions, access requests, or collaboration inquiries: