Ensembl Database

Overview

Access and query the Ensembl genome database, a comprehensive resource for vertebrate genomic data maintained by EMBL-EBI. The database provides gene annotations, sequences, variants, regulatory information, and comparative genomics data for over 250 species. The classic REST API serves release 116 (released 9 June 2026; GET /info/software → {"release": 116}).

Heads-up (verified 2026-09-23): Release 116 is the final release on the classic platform. https://rest.ensembl.org (and grch37.rest.ensembl.org) stay online with no announced sunset date but receive no further data updates; the classic website lives on as the archive https://jun2026.archive.ensembl.org. New data now appear on the new Ensembl platform at https://www.ensembl.org (formerly beta.ensembl.org, 5,200+ genomes), whose programmatic access is GraphQL (POST https://www.ensembl.org/data/graphql) plus GA4GH refget for sequences. The REST API documented here still works and is the simplest route for GRCh38/GRCh37 human work; use GraphQL for genomes or annotation updates added after release 116, and plan migration for long-lived pipelines.

When to Use This Skill

This skill should be used when:

• Querying gene information by symbol or Ensembl ID
• Retrieving DNA, transcript, or protein sequences
• Analyzing genetic variants using the Variant Effect Predictor (VEP)
• Finding orthologs and paralogs across species
• Accessing regulatory features and genomic annotations
• Converting coordinates between genome assemblies (e.g., GRCh37 to GRCh38)
• Performing comparative genomics analyses
• Integrating Ensembl data into genomic research pipelines

Does NOT Trigger

Core Capabilities

1. Gene Information Retrieval

Query gene data by symbol, Ensembl ID, or external database identifiers.

Common operations:

• Look up gene information by symbol (e.g., "BRCA2", "TP53")
• Retrieve transcript and protein information
• Get gene coordinates and chromosomal locations
• Access cross-references to external databases (UniProt, RefSeq, etc.)

Using the ensembl_rest package:

from ensembl_rest import EnsemblClient

client = EnsemblClient()

# Look up gene by symbol
gene_data = client.symbol_lookup(
    species='human',
    symbol='BRCA2'
)

# Get detailed gene information (method is lookup, NOT lookup_id)
gene_info = client.lookup(
    'ENSG00000139618',  # BRCA2 Ensembl ID
    expand=True
)

Direct REST API (no package):

import requests

server = "https://rest.ensembl.org"

# Symbol lookup
response = requests.get(
    f"{server}/lookup/symbol/homo_sapiens/BRCA2",
    headers={"Content-Type": "application/json"}
)
gene_data = response.json()

2. Sequence Retrieval

Fetch genomic, transcript, or protein sequences in various formats (JSON, FASTA, plain text).

Operations:

• Get DNA sequences for genes or genomic regions
• Retrieve transcript sequences (cDNA)
• Access protein sequences
• Extract sequences with flanking regions or modifications

Example:

# Using ensembl_rest package
sequence = client.sequence_id(
    id='ENSG00000139618',  # Gene ID
    content_type='application/json'
)

# Get sequence for a genomic region
region_seq = client.sequence_region(
    species='human',
    region='7:140424943-140624564'  # chromosome:start-end
)

3. Variant Analysis

Query genetic variation data and predict variant consequences using the Variant Effect Predictor (VEP).

Capabilities:

• Look up variants by rsID or genomic coordinates
• Predict functional consequences of variants
• Access population frequency data
• Retrieve phenotype associations

VEP example:

# Predict variant consequences (GET variant is vep_hgvs_get; POST batch is vep_hgvs_post)
vep_result = client.vep_hgvs_get(
    species='human',
    hgvs_notation='ENST00000380152.7:c.803C>T'
)

# Query variant by rsID
variant = client.variation_id(
    species='human',
    id='rs699'
)

4. Comparative Genomics

Perform cross-species comparisons to identify orthologs, paralogs, and evolutionary relationships.

Operations:

• Find orthologs (same gene in different species)
• Identify paralogs (related genes in same species)
• Access gene trees showing evolutionary relationships
• Retrieve gene family information

Example:

import requests

# Find orthologs for a human gene. The species segment is required:
# GET /homology/id/:species/:id (the old /homology/id/:id path now returns 404,
# and so does ensembl_rest's homology_ensemblgene(), which still calls it).
orthologs = requests.get(
    "https://rest.ensembl.org/homology/id/human/ENSG00000139618",  # Human BRCA2
    params={"target_species": "mouse", "type": "orthologues", "format": "condensed"},
    headers={"Content-Type": "application/json"},
    timeout=60,
).json()
# -> data[0]["homologies"][0]["id"] == "ENSMUSG00000041147" (ortholog_one2one)

# Get gene tree (GET /genetree/member/symbol/:species/:symbol; large and slow)
gene_tree = client.genetree_member_symbol(
    species='human',
    symbol='BRCA2'
)

5. Genomic Region Analysis

Find all genomic features (genes, transcripts, regulatory elements) in a specific region.

Use cases:

• Identify all genes in a chromosomal region
• Find regulatory features (promoters, enhancers)
• Locate variants within a region
• Retrieve structural features

Example:

# Find all features in a region
features = client.overlap_region(
    species='human',
    region='7:140424943-140624564',
    feature='gene'
)

6. Assembly Mapping

Convert coordinates between different genome assemblies (e.g., GRCh37 to GRCh38).

Important: Use https://grch37.rest.ensembl.org for GRCh37/hg19 queries and https://rest.ensembl.org for current assemblies.

Example:

from ensembl_rest import AssemblyMapper

# Map coordinates from GRCh37 to GRCh38.
# AssemblyMapper prefetches the whole-assembly mapping on init (slow once,
# then fast for repeated point lookups). map() takes a single position.
mapper = AssemblyMapper(
    from_assembly='GRCh37',
    to_assembly='GRCh38',
    species='human'
)

mapped_pos = mapper.map(chrom='7', pos=140453136)
# For one-off lookups, the direct REST endpoint is simpler:
#   GET /map/human/GRCh37/7:140453136..140453136/GRCh38

API Best Practices

Rate Limiting

The Ensembl REST API has rate limits. Follow these practices:

1. Respect rate limits: Maximum 15 requests per second for anonymous users
2. Handle 429 responses: When rate-limited, check the Retry-After header and wait
3. Use batch endpoints: When querying multiple items, use batch endpoints where available
4. Cache results: Store frequently accessed data to reduce API calls

Error Handling

Always implement proper error handling:

import requests
import time

def query_ensembl(endpoint, params=None, max_retries=3):
    server = "https://rest.ensembl.org"
    headers = {"Content-Type": "application/json"}

    for attempt in range(max_retries):
        response = requests.get(
            f"{server}{endpoint}",
            headers=headers,
            params=params
        )

        if response.status_code == 200:
            return response.json()
        elif response.status_code == 429:
            # Rate limited - wait and retry
            retry_after = int(response.headers.get('Retry-After', 1))
            time.sleep(retry_after)
        else:
            response.raise_for_status()

    raise Exception(f"Failed after {max_retries} attempts")

Installation

Python Package (optional convenience)

uv pip install 'ensembl_rest==0.3.4'   # latest release: Oct 2023

The ensembl_rest package (Ad115/EnsemblRest) wraps the REST endpoints, but it is a thin, unmaintained-since-2023 wrapper. The bundled scripts/ensembl_query.py uses plain requests instead and is the recommended path — it adds rate limiting and retry handling the package lacks.

Method-naming gotcha: the package auto-generates each method name from the last segment of the endpoint's documentation URL, which is often reversed from the REST path. This trips people up:

When unsure, prefer the direct REST call — the path is unambiguous.

Direct REST API

No installation needed - use standard HTTP libraries like requests:

uv pip install requests

Resources

references/

• api_endpoints.md: Comprehensive documentation of all 17 API endpoint categories with examples and parameters

scripts/

• ensembl_query.py: Reusable Python script for common Ensembl queries with built-in rate limiting and error handling

Common Workflows

Workflow 1: Gene Annotation Pipeline

1. Look up gene by symbol to get Ensembl ID
2. Retrieve transcript information
3. Get protein sequences for all transcripts
4. Find orthologs in other species
5. Export results

Workflow 2: Variant Analysis

1. Query variant by rsID or coordinates
2. Use VEP to predict functional consequences
3. Check population frequencies
4. Retrieve phenotype associations
5. Generate report

Workflow 3: Comparative Analysis

1. Start with gene of interest in reference species
2. Find orthologs in target species
3. Retrieve sequences for all orthologs
4. Compare gene structures and features
5. Analyze evolutionary conservation

Species and Assembly Information

To query available species and assemblies:

# List all available species (method is species, for GET /info/species)
species_list = client.species()

# Get assembly information for a species (method is assembly_info, for GET /info/assembly/:species)
assembly_info = client.assembly_info(species='human')

Common species identifiers:

• Human: homo_sapiens or human
• Mouse: mus_musculus or mouse
• Zebrafish: danio_rerio or zebrafish
• Fruit fly: drosophila_melanogaster

Additional Resources

• Official Documentation: https://rest.ensembl.org/documentation
• Python Package Docs: https://ensemblrest.readthedocs.io
• EBI Training: https://www.ebi.ac.uk/training/online/courses/ensembl-rest-api/
• Ensembl (new platform): https://www.ensembl.org — GraphQL help: https://www.ensembl.org/help/articles/getting-started-with-ensembl-graph-ql-services
• Release 116 archive (classic browser): https://jun2026.archive.ensembl.org
• GitHub Examples: https://github.com/Ensembl/ensembl-rest/wiki