Epigenomics & Gene Regulation Analysis

Comprehensive analysis of the regulatory genome integrating functional genomics experiments, transcription factor binding data, cis-regulatory element catalogs, chromatin conformation, and variant regulatory scoring. Generates structured regulatory landscape reports with evidence grading.

When to Use This Skill

Triggers:

"What regulates [gene]?" / "Show the regulatory landscape of [gene]"
"What transcription factors bind to [gene/region]?"
"Find enhancers near [gene]"
"What is the regulatory impact of variant [rsID]?"
"Find ENCODE experiments for [histone mark/TF] in [cell type]"
"What is the chromatin structure around [gene/region]?"
"Analyze the epigenetic regulation of [gene]"
"Find transcription factor binding motifs for [TF]"
"Regulatory element analysis for [genomic region]"

Use Cases:

Gene Regulatory Landscape: Comprehensive view of all regulatory elements, TF binding, and chromatin around a gene
Transcription Factor Profiling: TF binding motifs (JASPAR), binding sites (ReMap), and target gene identification
Regulatory Variant Interpretation: Assess non-coding variant impact using RegulomeDB, SCREEN, and ENCODE
Functional Genomics Data Discovery: Find ChIP-seq, ATAC-seq, Hi-C experiments from ENCODE and 4DN
Enhancer/Promoter Cataloging: Identify and characterize cis-regulatory elements using SCREEN
Chromatin Conformation: 3D genome organization from 4D Nucleome Hi-C data
Epigenetic Profiling: Histone modification patterns, DNA methylation, chromatin accessibility

KEY PRINCIPLES

Report-first approach - Create report file FIRST, then populate progressively
Tool parameter verification - Verify params via
```
get_tool_info
```
before calling unfamiliar tools
Evidence grading - Grade all regulatory findings by evidence strength (T1-T4)
Citation requirements - Every finding must have inline source attribution (database, experiment ID)
Mandatory completeness - All sections must exist with data minimums or explicit "No data" notes
Gene disambiguation first - Resolve gene symbol/coordinates before analysis
Cell-type context - Always note cell type specificity of regulatory data
Negative results documented - "No enhancers found in region" is data; empty sections are failures
English-first queries - Always use English gene names and standard nomenclature in tool calls

Evidence Grading System (MANDATORY)

Grade every regulatory finding by evidence strength:

Tier	Symbol	Criteria	Examples
T1	[T1]	Direct experimental validation, functional assay	CRISPR-validated enhancer, reporter assay, luciferase
T2	[T2]	High-quality experimental data, curated	ENCODE ChIP-seq peak, SCREEN cCRE, ReMap binding site
T3	[T3]	Computational prediction, motif match	JASPAR motif score, RegulomeDB score, Ensembl regulatory prediction
T4	[T4]	Association, text-mined, low confidence	Literature mention, low-score motif match, inferred regulation

Core Strategy: 7 Research Dimensions

Gene / Region / Variant Query
|
+-- PHASE 0: Gene/Region Resolution (ALWAYS FIRST)
|   +-- Resolve gene symbol -> Ensembl ID, coordinates, aliases
|   +-- Define genomic region of interest (+/- 500kb flanking)
|
+-- PHASE 1: Cis-Regulatory Elements (SCREEN)
|   +-- Candidate enhancers, promoters, insulators
|   +-- cCRE activity by cell type
|   +-- CTCF binding sites
|
+-- PHASE 2: Transcription Factor Binding
|   +-- JASPAR: TF binding motifs and PWMs
|   +-- ReMap: ChIP-seq validated TF binding sites
|   +-- ENCODE: TF ChIP-seq experiments
|
+-- PHASE 3: Regulatory Variant Scoring
|   +-- RegulomeDB: Variant regulatory evidence score
|   +-- Functional annotations from multiple data types
|
+-- PHASE 4: ENCODE Functional Genomics
|   +-- Histone modification ChIP-seq
|   +-- ATAC-seq / DNase-seq accessibility
|   +-- RNA-seq expression context
|   +-- Available experiments and datasets
|
+-- PHASE 5: Chromatin Conformation (4D Nucleome)
|   +-- Hi-C contact maps
|   +-- TAD boundaries
|   +-- Chromatin loops and compartments
|
+-- PHASE 6: Ensembl Regulatory Annotation
|   +-- Regulatory build features
|   +-- Promoter/enhancer/CTCF site annotations
|   +-- Activity states across cell types
|
+-- SYNTHESIS: Integrated Regulatory Model
    +-- Aggregate regulatory evidence
    +-- Build gene regulation model
    +-- Identify key regulatory elements and TFs
    +-- Data gaps and experimental recommendations

Phase 0: Gene/Region Resolution (ALWAYS FIRST)

CRITICAL: Resolve gene identity and genomic coordinates before any analysis.

Input Types Handled

Input Format	Resolution Strategy
Gene symbol (e.g., "BRCA1")	Ensembl lookup -> coordinates, Ensembl ID
Genomic region (e.g., "chr17:43044295-43170245")	Use directly; identify overlapping genes
Ensembl ID (e.g., "ENSG00000012048")	Ensembl lookup -> symbol, coordinates
rsID (e.g., "rs12345")	RegulomeDB/Ensembl -> coordinates, nearby genes

Resolution Tools

Tool	Purpose	Parameters
`ensembl_lookup_gene`	Gene symbol to Ensembl ID + coordinates	`id` : str, `species` : str
`HGNC_get_gene_info`	Official gene symbol, aliases	`symbol` : str
`ensembl_get_xrefs`	Cross-references to external databases	`id` : str

Disambiguation Output

markdown

## Gene Identity

| Property | Value |
|----------|-------|
| **Gene Symbol** | TP53 |
| **Ensembl ID** | ENSG00000141510 |
| **Chromosome** | 17 |
| **Start** | 7661779 |
| **End** | 7687550 |
| **Strand** | - |
| **Region of Interest** | 17:7161779-8187550 (+/- 500kb) |
| **Aliases** | p53, TRP53, LFS1 |

Phase 1: Cis-Regulatory Elements (SCREEN)

When: Gene name or genomic region available

Objective: Catalog candidate cis-regulatory elements (cCREs) from the ENCODE SCREEN database

Tools Used

Tool	Function	Parameters
`SCREEN_get_regulatory_elements`	Get cCREs for a gene	`gene_name` : str, `element_type` : str, `limit` : int

Workflow

Query enhancers:

SCREEN_get_regulatory_elements(gene_name=gene, element_type="enhancer", limit=20)

Query promoters:

SCREEN_get_regulatory_elements(gene_name=gene, element_type="promoter", limit=20)

Query insulators:

SCREEN_get_regulatory_elements(gene_name=gene, element_type="insulator", limit=10)

For each element: extract coordinates, activity scores, cell type specificity

Decision Logic

Multiple element types: Always query enhancers AND promoters (insulators optional)
Empty results: Some genes have fewer regulatory elements; note counts
Cell type specificity: SCREEN data is cell-type annotated; report top active cell types
All findings graded [T2]: SCREEN cCREs are experimentally derived from ENCODE data

Output Format

markdown

### Cis-Regulatory Elements (SCREEN) [T2]

#### Enhancers (15 found)
| Element ID | Coordinates | Activity Score | Top Cell Types |
|-----------|-------------|---------------|----------------|
| EH38E1234567 | chr17:7650000-7651000 | 0.95 | HepG2, K562 |
| ... | ... | ... | ... |

#### Promoters (3 found)
| Element ID | Coordinates | Activity Score | Top Cell Types |
|-----------|-------------|---------------|----------------|
| EH38E9876543 | chr17:7687000-7688000 | 0.99 | Ubiquitous |
| ... | ... | ... | ... |

#### Insulators (2 found)
| Element ID | Coordinates | CTCF Binding |
|-----------|-------------|-------------|
| EH38E5555555 | chr17:7700000-7701000 | Yes |

Phase 2: Transcription Factor Binding

When: Gene symbol available

Objective: Identify transcription factors that regulate the gene through motif analysis and ChIP-seq binding data

Tools Used

JASPAR - TF Binding Motifs

Tool	Function	Parameters
`jaspar_search_matrices`	Search TF binding motifs	`search` : str, `collection` : str, `tax_group` : str, `species` : str
`jaspar_get_matrix`	Get PWM for specific TF	`matrix_id` : str
`JASPAR_get_transcription_factors`	List TFs in collection	`collection` : str, `page` : int, `page_size` : int

ReMap - Validated TF Binding Sites

Tool	Function	Parameters
`ReMap_get_transcription_factor_binding`	Get TF binding sites near gene	`gene_name` : str, `cell_type` : str, `limit` : int

ENCODE - ChIP-seq Experiments

Tool	Function	Parameters
`ENCODE_search_experiments`	Search TF ChIP-seq experiments	`assay_title` : str, `target` : str, `organism` : str, `limit` : int

Workflow

JASPAR motif search: Search for known TF binding motifs
- ```
jaspar_search_matrices(search=gene_symbol, collection="CORE", species="9606")
```
- If gene IS a TF: get its PWM binding motif
- If gene is NOT a TF: identify TFs known to bind its promoter
ReMap binding data: Get experimentally validated TF binding sites
- ```
ReMap_get_transcription_factor_binding(gene_name=gene, cell_type="HepG2", limit=20)
```
- Try multiple cell types: "HepG2", "K562", "MCF-7", "GM12878"

ENCODE ChIP-seq: Find available ChIP-seq experiments for key TFs

ENCODE_search_experiments(assay_title="ChIP-seq", target=top_tf, organism="Homo sapiens", limit=5)

Decision Logic

Gene is a TF: Show its binding motif (JASPAR PWM) + target genes + ENCODE ChIP-seq experiments
Gene is NOT a TF: Show TFs that bind its promoter/enhancers (ReMap) + relevant motifs
Multiple cell types for ReMap: Query at least 2-3 common cell types
JASPAR grades [T3]: Motif predictions are computational
ReMap grades [T2]: Based on experimental ChIP-seq data
ENCODE grades [T2]: Direct experimental data

Output Format

markdown

### Transcription Factor Binding

#### JASPAR Binding Motifs [T3]
| Matrix ID | TF Name | Score | Sequence Logo |
|-----------|---------|-------|---------------|
| MA0106.3 | TP53 | 0.92 | RRRCWWGYYY |
| ... | ... | ... | ... |

#### ReMap ChIP-seq Validated Binding [T2]
| Transcription Factor | Cell Type | Binding Score | Coordinates |
|---------------------|-----------|--------------|-------------|
| SP1 | HepG2 | 850 | chr17:7687200-7687500 |
| CTCF | K562 | 920 | chr17:7700100-7700400 |
| ... | ... | ... | ... |

#### ENCODE ChIP-seq Experiments Available [T2]
| Experiment | Target | Cell Type | Files | Status |
|-----------|--------|-----------|-------|--------|
| ENCSR000BNT | TP53 | HepG2 | 12 | released |
| ... | ... | ... | ... | ... |

Phase 3: Regulatory Variant Scoring

When: rsID or variant provided, OR gene has known regulatory variants

Objective: Assess the regulatory impact of genetic variants in the region

Tools Used

Tool	Function	Parameters
`RegulomeDB_query_variant`	Get regulatory evidence score for variant	`rsid` : str

Workflow

If rsID provided: Query RegulomeDB directly
- ```
RegulomeDB_query_variant(rsid=rsid)
```
Parse RegulomeDB score (1a-7): lower = more regulatory evidence
Extract supporting evidence types (eQTL, TF binding, chromatin state, etc.)
Cross-reference with SCREEN and ENCODE data from other phases

RegulomeDB Score Interpretation

Score	Meaning	Evidence Level
1a	eQTL + TF binding + DNase + motif	Very likely regulatory [T2]
1b	eQTL + TF binding + DNase	Likely regulatory [T2]
1c	eQTL + TF binding + motif	Likely regulatory [T2]
1d	eQTL + TF binding	Likely regulatory [T2]
1e	eQTL + DNase	Likely regulatory [T3]
1f	eQTL only	Possible regulatory [T3]
2a-2c	TF binding + DNase/motif	Likely affects TF binding [T3]
3a-3b	DNase or ChIP-seq evidence	Some evidence [T3]
4-7	Minimal or no evidence	Limited evidence [T4]

Decision Logic

Score 1a-1d: Flag as likely functional regulatory variant; high confidence
Score 2a-3b: Moderate evidence; recommend experimental validation
Score 4-7: Low regulatory evidence; likely benign regulatory impact
No rsID provided: Skip this phase gracefully; note "no variant specified"

Output Format

markdown

### Regulatory Variant Impact [T2/T3]

| Variant | RegulomeDB Score | Interpretation | Evidence Types |
|---------|-----------------|---------------|----------------|
| rs12345 | 1b | Likely regulatory | eQTL, TF binding, DNase |
| rs67890 | 3a | Some evidence | DNase peak |

Phase 4: ENCODE Functional Genomics

When: Gene or region available

Objective: Discover functional genomics experiments and datasets from ENCODE

Tools Used

Tool	Function	Parameters
`ENCODE_search_experiments`	Search experiments by assay/target	`assay_title` , `target` , `organism` , `status` , `limit`
`ENCODE_get_experiment`	Get detailed experiment metadata	`accession` : str
`ENCODE_list_files`	List available data files	`file_type` , `assay_title` , `limit`
`ENCODE_search_biosamples`	Search available cell types	`organism` , `biosample_type` , `treatment` , `limit`

Workflow

Histone marks: Search for H3K4me3 (promoter), H3K27ac (enhancer), H3K4me1 (enhancer), H3K27me3 (repressive)
- ```
ENCODE_search_experiments(assay_title="ChIP-seq", target="H3K27ac", organism="Homo sapiens", limit=5)
```

Chromatin accessibility: Search ATAC-seq and DNase-seq

ENCODE_search_experiments(assay_title="ATAC-seq", organism="Homo sapiens", limit=5)

If gene is a TF: Search for ChIP-seq of that TF

ENCODE_search_experiments(assay_title="ChIP-seq", target=gene, organism="Homo sapiens", limit=5)

RNA-seq context: Search for expression experiments

ENCODE_search_experiments(assay_title="RNA-seq", organism="Homo sapiens", limit=5)

Decision Logic

Prioritize by relevance: Histone marks and accessibility most informative for regulatory analysis
Cell type matching: When possible, focus on cell types relevant to user's question
Experiment quality: Prefer "released" status and recent experiments
Data volume: ENCODE has thousands of experiments; limit results and highlight most relevant
All ENCODE data graded [T2]: High-quality experimental data

Output Format

markdown

### ENCODE Functional Genomics [T2]

#### Histone Modification Experiments
| Experiment | Mark | Cell Type | Status | Files |
|-----------|------|-----------|--------|-------|
| ENCSR000AKP | H3K27ac | HepG2 | released | 8 |
| ENCSR000ALA | H3K4me3 | K562 | released | 6 |

#### Chromatin Accessibility
| Experiment | Assay | Cell Type | Status |
|-----------|-------|-----------|--------|
| ENCSR889WQX | ATAC-seq | GM12878 | released |

#### TF ChIP-seq (for [gene] if TF)
| Experiment | Target | Cell Type | Status |
|-----------|--------|-----------|--------|
| ENCSR000BNT | TP53 | HepG2 | released |

Phase 5: Chromatin Conformation (4D Nucleome)

When: Gene or region available

Objective: Explore 3D genome organization data from the 4D Nucleome project

Tools Used

Tool	Function	Parameters
`FourDN_search_data`	Search Hi-C data	`operation` : "search_data", `assay_title` , `biosource_name` , `limit`
`FourDN_get_experiment_metadata`	Get experiment details	`operation` : "get_experiment_metadata", `experiment_accession` : str

Workflow

Search Hi-C experiments:

FourDN_search_data(operation="search_data", assay_title="Hi-C", limit=10)

Search Micro-C data:

FourDN_search_data(operation="search_data", assay_title="Micro-C", limit=5)

For relevant experiments: get metadata for top results
Note available cell types and data types

Decision Logic

IMPORTANT: 4DN tools require
operation
parameter - This is a SOAP-style tool
Hi-C vs Micro-C: Micro-C has higher resolution for local interactions
Cell type matching: Note which cell types have chromatin data
Data availability: 4DN may not cover all cell types of interest
Grade [T2]: High-quality experimental chromatin conformation data

Output Format

markdown

### Chromatin Conformation (4D Nucleome) [T2]

#### Available Hi-C Datasets
| Experiment | Cell Type | Assay | Resolution | Status |
|-----------|-----------|-------|-----------|--------|
| 4DNESXXXXXXX | H1-hESC | Hi-C | 10kb | released |
| 4DNESYYYYYYY | GM12878 | Micro-C | 1kb | released |

#### Chromatin Organization Context
- **TAD**: Gene located within TAD spanning chr17:7.1-8.2Mb
- **Compartment**: A compartment (active)
- **Nearby CTCF sites**: 3 CTCF sites within 100kb (from SCREEN Phase 1)

Phase 6: Ensembl Regulatory Annotation

When: Genomic region coordinates available

Objective: Get regulatory feature annotations from the Ensembl Regulatory Build

Tools Used

Tool	Function	Parameters
`ensembl_get_regulatory_features`	Get regulatory features in region	`region` : str (chr:start-end), `feature` : str, `species` : str

Workflow

Get regulatory features:

ensembl_get_regulatory_features(region="17:7661779-7687550", feature="regulatory", species="human")

Parse feature types: promoter, enhancer, CTCF_binding_site, TF_binding_site, open_chromatin_region
Note activity states across cell types when available

Decision Logic

Region format: Use chromosome:start-end without "chr" prefix
Feature parameter: Must be "regulatory" for this endpoint
Cross-reference with SCREEN: Compare Ensembl regulatory build with SCREEN cCREs
Grade [T3]: Ensembl regulatory build is computationally derived

Output Format

markdown

### Ensembl Regulatory Build [T3]

| Feature ID | Type | Coordinates | Activity State |
|-----------|------|-------------|----------------|
| ENSR00000123456 | Promoter | 17:7687200-7688000 | Active (most cell types) |
| ENSR00000789012 | Enhancer | 17:7650000-7651500 | Active (liver, lung) |
| ENSR00000345678 | CTCF_binding_site | 17:7700000-7700500 | Active |

Synthesis: Integrated Regulatory Model (MANDATORY)

Always the final section. Integrates all evidence into a coherent regulatory model.

Synthesis Template

markdown

## Integrated Regulatory Model

### Regulatory Architecture Summary

**Gene**: [GENE] ([Ensembl ID])
**Region analyzed**: [coordinates] ([size]kb)

### Key Regulatory Elements
1. **Proximal promoter** [T2/T3]: Located at [coords], active in [cell types]
   - TFs binding: SP1, CTCF, [others from ReMap]
   - Histone marks: H3K4me3 (ENCODE), H3K27ac (ENCODE)
   - SCREEN cCRE: [element ID]

2. **Distal enhancer 1** [T2]: Located at [coords], [distance] from TSS
   - Active in [cell types] (SCREEN)
   - TF binding: [TFs from ReMap/ENCODE]
   - Hi-C contact with promoter: [Yes/No/Unknown]

3. **CTCF insulator** [T2]: Located at [coords]
   - Defines TAD boundary
   - CTCF motif score: [from JASPAR]

### Transcription Factor Regulatory Network
| TF | Binding Evidence | Motif Match | Cell Types | Role |
|----|-----------------|-------------|-----------|------|
| SP1 | ReMap ChIP-seq [T2] | JASPAR 0.92 [T3] | HepG2, K562 | Activator |
| CTCF | ENCODE ChIP-seq [T2] | JASPAR 0.98 [T3] | Ubiquitous | Insulator |

### Regulatory Variants (if applicable)
| Variant | RegulomeDB Score | Regulatory Impact | Affected Element |
|---------|-----------------|-------------------|-----------------|
| rs12345 | 1b | Disrupts SP1 binding | Proximal promoter |

### Evidence Quality Assessment
| Dimension | Data Available | Evidence Tier | Confidence |
|-----------|---------------|--------------|------------|
| cCREs (SCREEN) | 15 enhancers, 3 promoters | [T2] | High |
| TF Binding (ReMap) | 8 TFs validated | [T2] | High |
| Motifs (JASPAR) | 12 motif matches | [T3] | Medium |
| ENCODE experiments | 25 relevant datasets | [T2] | High |
| Chromatin (4DN) | Hi-C in 3 cell types | [T2] | Medium |
| Regulatory Build | 5 features annotated | [T3] | Medium |

### Data Gaps
- [ ] No single-cell ATAC-seq data available for this region
- [ ] Chromatin conformation data limited to 3 cell types
- [ ] No CRISPR-validated enhancers (would be needed for [T1])
- [ ] Regulatory variant impact is predictive (needs experimental validation)

### Experimental Recommendations
1. **Validate key enhancers**: CRISPR deletion or reporter assays for top 3 enhancers
2. **Confirm TF binding**: ChIP-qPCR for SP1, CTCF at predicted sites
3. **Test regulatory variants**: Allele-specific reporter assays for rs12345

Mandatory Completeness Checklist

Before finalizing any report, verify:

Phase 0: Gene/region fully resolved (symbol, Ensembl ID, coordinates)
Phase 1: SCREEN queried for enhancers AND promoters (counts reported)
Phase 2: At least 2 TF data sources queried (JASPAR + ReMap or ENCODE)
Phase 3: RegulomeDB queried for variants OR "no variant specified" noted
Phase 4: At least 2 ENCODE assay types searched (histone marks + accessibility)
Phase 5: 4DN queried for Hi-C/Micro-C data OR "no chromatin data" noted
Phase 6: Ensembl regulatory build queried OR "no regulatory features" noted
Synthesis: Regulatory model provided with element catalog and TF network
Evidence Grading: All findings have [T1]-[T4] annotations
Cell-type context: Cell type specificity noted for all binding/activity data
Data gaps: Explicitly listed in synthesis section

Tool Parameter Reference

Critical Parameter Notes (verified from source code):

Tool	Parameter Name	Type	Notes
`SCREEN_get_regulatory_elements`	`gene_name` , `element_type` , `limit`	str, str, int	element_type: "enhancer", "promoter", "insulator"
`ReMap_get_transcription_factor_binding`	`gene_name` , `cell_type` , `limit`	str, str, int	cell_type default: "HepG2"
`RegulomeDB_query_variant`	`rsid`	str	rsID format (e.g., "rs12345")
`jaspar_search_matrices`	`search` , `name` , `collection` , `tax_group` , `species`	str (all optional)	species="9606" for human
`jaspar_get_matrix`	`matrix_id`	str	JASPAR matrix ID (e.g., "MA0106.3")
`JASPAR_get_transcription_factors`	`collection` , `page` , `page_size`	str, int, int	collection="CORE" default
`ENCODE_search_experiments`	`assay_title` , `target` , `organism` , `status` , `limit`	str (all optional)	status="released" default
`ENCODE_get_experiment`	`accession`	str	ENCODE accession (e.g., "ENCSR000BNT")
`ENCODE_list_files`	`file_type` , `assay_title` , `limit`	str, str, int	All optional
`ENCODE_search_biosamples`	`organism` , `biosample_type` , `treatment` , `limit`	str (all optional)
`FourDN_search_data`	`operation` , `query` , `item_type` , `assay_title` , `biosource_name` , `limit`	operation REQUIRED	operation="search_data"
`FourDN_get_experiment_metadata`	`operation` , `experiment_accession`	operation REQUIRED	operation="get_experiment_metadata"
`ensembl_get_regulatory_features`	`region` , `feature` , `species`	str, str, str	feature="regulatory", region="17:start-end"

CRITICAL: SOAP-style Tools

The following tools require an

operation

parameter:

FourDN_search_data:
```
operation="search_data"
```
FourDN_get_experiment_metadata:
```
operation="get_experiment_metadata"
```
FourDN_get_file_metadata:
```
operation="get_file_metadata"
```
FourDN_get_download_url:
```
operation="get_download_url"
```

Response Format Notes (verified from testing)

SCREEN: Returns dict with
```
@context
```
,
```
@graph
```
,
```
@id
```
,
```
@type
```
,
```
all
```
keys (JSON-LD format)
ReMap: Returns dict with TF binding records
RegulomeDB: Returns
```
{status, data, url}
```
with regulatory score and evidence in
```
data
```
JASPAR search: Returns
```
{count, next, previous, results}
```
with matrix objects in
```
results
```
JASPAR get_matrix: Returns dict with matrix details (name, PFM, sequence logo)
ENCODE: Returns dict with experiment/file objects (structure varies by endpoint)
4DN: Returns dict with search results
Ensembl: Returns
```
{status, data, url, content_type}
```
with regulatory features in
```
data
```

Fallback Strategies

Regulatory Elements

Primary: SCREEN cCREs by gene name
Fallback: Ensembl Regulatory Build by coordinates
If both empty: Note "limited regulatory annotation in this region"

TF Binding

Primary: ReMap binding sites + JASPAR motifs
Fallback: ENCODE ChIP-seq experiments
If all empty: Gene may have limited TF binding data; note and continue

Chromatin Data

Primary: 4DN Hi-C experiments
Fallback: ENCODE Hi-C experiments
If empty: Note "no chromatin conformation data available for this region"

Variant Scoring

Primary: RegulomeDB for rsID
Fallback: SCREEN + ENCODE overlap analysis at variant position
If no variant: Skip gracefully

Common Use Patterns

Pattern 1: Gene-Centric Regulatory Landscape

Input: Gene symbol (e.g., "TP53")
Workflow: All phases (0-6 + Synthesis)
Output: Complete regulatory atlas for the gene locus

Pattern 2: Transcription Factor Target Analysis

Input: TF name (e.g., "CTCF")
Workflow: Phase 0 -> Phase 2 (JASPAR motif + ENCODE ChIP-seq) -> Phase 1 (target gene cCREs)
Output: TF binding motif, genome-wide binding data, target gene catalog

Pattern 3: Non-Coding Variant Interpretation

Input: rsID (e.g., "rs6983267")
Workflow: Phase 0 -> Phase 3 (RegulomeDB) -> Phase 1 (nearby cCREs) -> Phase 2 (TF binding) -> Synthesis
Output: Regulatory impact assessment with functional context

Pattern 4: Cell-Type Specific Regulation

Input: Gene + cell type (e.g., "MYC in HepG2")
Workflow: Phase 0 -> Phase 1 (SCREEN) -> Phase 2 (ReMap in HepG2) -> Phase 4 (ENCODE in HepG2)
Output: Cell-type specific regulatory landscape

Pattern 5: Epigenetic Data Discovery

Input: Histone mark or assay type (e.g., "H3K27ac ChIP-seq in liver")
Workflow: Phase 4 (ENCODE search) -> Phase 5 (4DN chromatin) -> Summary
Output: Available datasets and download information

Limitations & Known Issues

Database-Specific

SCREEN: Limited to ENCODE-defined cCREs; may miss tissue-specific regulatory elements
JASPAR: Motif predictions have false positive rate; binding =/= function
ReMap: Coverage varies by TF and cell type; ~1000 TFs covered
RegulomeDB: Scoring based on available data; novel variants may lack evidence
ENCODE: Primarily human and mouse; limited other organisms
4DN: Focused on chromatin conformation; limited cell type coverage
Ensembl: Regulatory build is computationally predicted; may miss novel elements

Analysis

Cell-type specificity: Regulatory elements are highly cell-type specific; data from one cell type may not generalize
Functional validation gap: Most findings are [T2]-[T3]; [T1] validation requires experimental follow-up
Non-coding complexity: Regulatory mechanisms are complex; catalog does not capture all interactions
3D genome: TAD and loop data available for limited cell types

Technical

4DN operation parameter: Must include
```
operation
```
for all 4DN tools (SOAP-style)
Region format: Ensembl uses "17:start-end" (no "chr" prefix); SCREEN/ENCODE may use "chr17:start-end"
Large gene loci: Genes spanning >1Mb may require multiple queries

Summary

Epigenomics & Gene Regulation Skill provides comprehensive regulatory landscape analysis by integrating:

Cis-regulatory elements (SCREEN) - Enhancers, promoters, insulators from ENCODE cCRE catalog
Transcription factor binding (JASPAR + ReMap + ENCODE) - Motifs, validated binding sites, ChIP-seq data
Regulatory variant scoring (RegulomeDB) - Evidence-based variant regulatory impact
Functional genomics (ENCODE) - Histone marks, chromatin accessibility, expression
Chromatin conformation (4D Nucleome) - Hi-C, TADs, chromatin loops
Regulatory annotation (Ensembl) - Computational regulatory build features

Outputs: Structured markdown report with regulatory element catalog, TF network, variant scoring, and integrated regulatory model

Best for: Gene regulation analysis, non-coding variant interpretation, enhancer/promoter identification, TF binding profiling, epigenetic data discovery

Total tools integrated: 21 tools across 7 databases

tooluniverse-epigenomics

NPX Install

Tags

SKILL.md Content

Epigenomics & Gene Regulation Analysis

When to Use This Skill

KEY PRINCIPLES

Evidence Grading System (MANDATORY)

Core Strategy: 7 Research Dimensions

Phase 0: Gene/Region Resolution (ALWAYS FIRST)

Input Types Handled

Resolution Tools

Disambiguation Output

Phase 1: Cis-Regulatory Elements (SCREEN)

Tools Used

Workflow

Decision Logic

Output Format

Phase 2: Transcription Factor Binding

Tools Used

JASPAR - TF Binding Motifs

ReMap - Validated TF Binding Sites

ENCODE - ChIP-seq Experiments

Workflow

Decision Logic

Output Format

Phase 3: Regulatory Variant Scoring

Tools Used

Workflow

RegulomeDB Score Interpretation

Decision Logic

Output Format

Phase 4: ENCODE Functional Genomics

Tools Used

Workflow

Decision Logic

Output Format

Phase 5: Chromatin Conformation (4D Nucleome)

Tools Used

Workflow

Decision Logic

Output Format

Phase 6: Ensembl Regulatory Annotation

Tools Used

Workflow

Decision Logic

Output Format

Synthesis: Integrated Regulatory Model (MANDATORY)

Synthesis Template

Mandatory Completeness Checklist

Tool Parameter Reference

CRITICAL: SOAP-style Tools

Response Format Notes (verified from testing)

Fallback Strategies

Regulatory Elements

TF Binding

Chromatin Data

Variant Scoring

Common Use Patterns

Pattern 1: Gene-Centric Regulatory Landscape

Pattern 2: Transcription Factor Target Analysis

Pattern 3: Non-Coding Variant Interpretation

Pattern 4: Cell-Type Specific Regulation

Pattern 5: Epigenetic Data Discovery

Limitations & Known Issues

Database-Specific

Analysis

Technical

Summary