Synteny Analysis

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha c8c1fc3a2b13 · 19 Oct 2026Report an issue or request a re-scan

• PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
• Source folderGPTomics/bioSkills/comparative-genomics/synteny-analysisThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdictc8c1fc3a2b13A new audit runs when the source changes
• Repository statusArchivedLast push 65 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Detect syntenic blocks and structural rearrangements between genomes using MCScanX (Wang 2012), JCVI/MCScan (Tang 2008 Python), GENESPACE (Lovell 2022) for orthology-anchored riparian visualization, SyRI for structural…

---
name: bio-comparative-genomics-synteny-analysis
description: Detect syntenic blocks and structural rearrangements between genomes using MCScanX (Wang 2012), JCVI/MCScan (Tang 2008 Python), GENESPACE (Lovell 2022) for orthology-anchored riparian visualization, SyRI for structural variation, AnchorWave for sequence-level synteny, i-ADHoRe 3.0 for highly diverged species, SynNet for synteny networks, and ntSynt for multi-genome macrosynteny. Use when identifying collinear gene blocks across species, distinguishing macrosynteny from microsynteny, detecting inversions/translocations/duplications, anchoring orthology in WGD lineages, producing publication riparian plots, computing synteny block age via Ks (cross-references whole-genome-duplication), or running synteny-aware ortholog inference in polyploids.
tool_type: mixed
primary_tool: MCScanX
---

## Version Compatibility

Reference examples tested with: MCScanX 1.0+ (wyp1125/MCScanX commit 2020+), JCVI 1.4.21+ (Python port of MCScan), GENESPACE 1.4.0+ (Lovell 2022 eLife 11:e78526), SyRI 1.7.1+ (Goel 2019 Genome Biol 20:277), plotsr 1.1.1+, AnchorWave 1.2.5+ (Song 2022 PNAS 119:e2113075119), i-ADHoRe 3.0.01+, SynNet (Zhao 2017 Plant Cell 29:1278), ntSynt 1.0.4+ (2024), minimap2 2.28+, MUMmer 4.0.0+, OrthoFinder 3.0+, R 4.4+. plotsr requires pysam 0.22+ and seaborn 0.13+.

Before using code patterns, verify installed versions match. If versions differ:
- CLI: `MCScanX -h`; `syri --version`; `python -m jcvi.compara.catalog ortholog --help`
- R: `packageVersion('GENESPACE')`; `?run_genespace`
- Python: `pip show jcvi`

If code throws `MCScanX: argument bad format`, `syri: input alignment file missing required columns`, or `GENESPACE: GFF parse error`, these tools have brittle input parsing: MCScanX requires 4-column `species_chr  gene  start  end` BED (non-standard), JCVI expects 4-column simple BED, GENESPACE requires GFF3 with `gene` feature type. Pre-process with `jcvi.formats.gff bed` or custom AWK.

# Synteny Analysis

**"Compare genome architecture between these species"** -> Detect conserved gene order (synteny) and infer rearrangement history. Synteny is NOT the same as collinearity: synteny is "genes on same chromosome", collinearity is "same order on same chromosome" (modern usage often conflates them). The choice of tool depends on whether the question is **gene-level co-linearity** (MCScanX, JCVI), **whole-genome structural rearrangements** (SyRI, AnchorWave), **multi-genome macrosynteny** (GENESPACE, ntSynt), or **synteny-aware orthology** (GENESPACE, ProteinOrtho-synteny). Repeat-masking quality is the dominant determinant of result reliability -- unmasked TEs produce ~100x more false anchor pairs than real syntenic anchors.

- CLI: `MCScanX` for collinear gene blocks via dynamic programming
- CLI: `python -m jcvi.compara.catalog ortholog A B` for JCVI/MCScan Python pipeline
- R: `run_genespace()` (Lovell 2022) for orthology-anchored riparian plots + pan-gene tracks
- CLI: `syri` for inversion / translocation / duplication detection
- CLI: `anchorwave proali` for sequence-level WGD-aware synteny

## Algorithmic Taxonomy

| Tool | Approach | Output | Strength | Fails when |
|------|----------|--------|----------|------------|
| MCScanX (Wang 2012 NAR 40:e49) | Dynamic programming on BLAST hits with collinearity scoring | `.collinearity` blocks; tandem duplications collapsed | Most widely used; 14 downstream tools; well-benchmarked | Repeat-derived false BLAST hits; brittle 4-column input |
| MCScanX-h | Within-genome variant for WGD detection | Self-comparison blocks | Standard for paranome construction; WGD-aware | Same input fragility |
| JCVI / MCScan Python (Tang 2008 GR 18:1944) | Re-implementation of MCScanX with anchor stringency control | Publication-grade dotplots, karyotype, riparian | Best plotting; `--cscore` reciprocal-hit control | Slower than MCScanX C version on huge genomes |
| GENESPACE (Lovell 2022 eLife 11:e78526) | OrthoFinder + MCScanX orthogroup-constrained synteny | Riparian plots; pan-gene tracks; CNV across genomes | Modern standard for plant comparative; integrates orthology | Slow at > 30 genomes; less rigorous for non-plant clades |
| i-ADHoRe 3.0 (Proost 2012 NAR 40:e11) | Iterative ordered-gene-list detection | Ghost gene families; deeply diverged synteny | Catches ancient synteny obscured by rearrangements | Computationally heavy at genome scale |
| AnchorWave (Song 2022 PNAS 119:e2113075119) | CDS/exon anchors -> wave-front alignment | Whole-genome alignment with WGD awareness; SVs | Best for plant WGD analyses with known ploidy | CDS-anchored only; intergenic resolution limited |
| SyRI (Goel 2019 GB 20:277) | Pairwise WGA -> syntenic-path identification -> SV calls | INV / TRANS / DUP / SYN / INS / DEL annotated | Comprehensive SV detection; works on chromosome-level assemblies | Requires chromosome-level assemblies; pairwise only |
| plotsr (Goel 2022 Bioinformatics 38:2922) | Multi-genome SyRI visualization | Stacked synteny + SV maps across N genomes | Best for visualizing 3-10 genome rearrangement histories | Inherits SyRI's pairwise input limitation |
| ntSynt (2024) | Minimizer-based alignment-free synteny | Multi-genome macrosynteny blocks | Alignment-free; handles > 15% divergence | Macrosynteny only; misses microsynteny |
| SynNet (Zhao 2017 Plant Cell 29:1278) | Synteny block adjacency graphs | Synteny networks across many genomes | Phylogenetic network from synteny; detects deep ancestry | Less standard than block-based methods |
| Satsuma / progressive Cactus | Reference-free WGA | Whole-genome alignment (HAL format) | Underlies large-scale orthology; sequence-level synteny | See [[whole-genome-alignment]] |
| LASTZ chain/net (UCSC; Kent 2003 PNAS 100:11484 chains/nets; Schwartz 2003 GR 13:103 BLASTZ) | Pairwise WGA with chains and nets | Chains + nets in UCSC genome browser | Reference-anchored synteny; standard for UCSC tracks | See [[whole-genome-alignment]] |
| nucmer + dnadif

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/wyp1125/MCScanX && cd MCScanX && make
pip install jcvi
git clone https://github.com/VIB-PSB/i-ADHoRe && cd i-ADHoRe && mkdir build && cd build && cmake .. && make
pip install ntsynt

git clone https://github.com/GPTomics/bioSkills
git -C bioSkills checkout c8c1fc3a2b13

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source c8c1fc3a2b13

Questions about Synteny Analysis

• github.com/GPTomics/bioSkills/tree/main/comparative-genomics/syn — the audited source at commit c8c1fc3a2b13 and every finding aboveObserved · 19 Oct 2026

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