bio-comparative-genomics-synteny-analysis

What this skill does

## 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 78526), 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 NAR 45:e108), ntSynt 1.0.4+ (2023), 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" (Fitch 1976 J Mol Evol 7:271 distinction; 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 78526) | 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 (2023) | Minimizer-based alignment-free synteny | Multi-genome macrosynteny blocks | Alignment-free; handles > 15% divergence | Macrosynteny only; misses microsynteny |
| SynNet (Zhao 2017 NAR 45:e108) | 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; Schwartz 2003 GR 13:103) | Pairwise WGA with chains and nets | Chains + nets in UCSC genome browser | Reference-anchored synteny; standard for UCSC tracks | See [[whole-genome-alignment]] |
| nucmer + dnadiff (MUMmer4; Marçais 2018 PLoS Comp Biol 14:e1005944) | MUM-anchored pairwise alignment | Whole-genome alignment with SV summary | Fast pairwise WGA for closely related | Sensitive only above ~70% identity |
| MashMap (Jain 2018 Bioinformatics 34:i748) | Approximate mapping for fragment-fragment synteny | Pairwise mappings with identity | Scales to thousands of genomes | Coarse (window-based); no SV inference |

Methodology evolves; GENESPACE has emerged as the de facto standard for plant comparative genomics (2022-2026). For non-plant clades, MCScanX or JCVI remain the workhorses. Whole-genome alignment for synteny is increasingly delegated to Cactus / Minigraph-Cactus and HAL toolkit (see [[whole-genome-alignment]]).

## Decision Tree by Experimental Scenario

| Scenario | Recommended approach | Why |
|----------|------------------------|-----|
| Plant comparative genomics, 2-20 species | GENESPACE | Integrated orthology + synteny + visualization; modern standard |
| Animal / fungal, 2 species comparison | JCVI/MCScan | Best plots; flexible; widely cited |
| Animal / fungal, 10+ species | OrthoFinder + MCScanX + custom plot OR JCVI multi-genome | Avoid plant-specific GENESPACE assumptions |
| Bacterial / prokaryote synteny | progressiveMauve OR MCScanX-bacterial | Tools designed for compact genomes |
| Chromosome-level rearrangement inventory | SyRI + plotsr | Comprehensive SV (INV/TRANS/DUP) with publication viz |
| Polyploid genome analysis | AnchorWave proali mode with ploidy | WGD-aware synteny; subgenome-aware |
| Closely related strains (>= 95% identity) | nucmer + dnadiff | Faster than chromosome-level WGA; appropriate sensitivity |
| Distantly related species (< 70% identity) | i-ADHoRe 3.0 or LASTZ chains/nets | Sequence-level approaches lose power; ordered-list methods retain it |
| Ancient WGD detection | See [[whole-genome-duplication]] | wgd v2, KsRates; Ks-based dating outside synteny scope |
| WGA at clade-level (10+ vertebrates) | Cactus / Minigraph-Cactus -> halSynteny | See [[whole-genome-alignment]]; multi-genome reference-free |
| Pan-genome of bacterial strains | See [[pangenome-analysis]] | Panaroo / PPanGGOLiN / PEPPAN; different problem |
| Synteny-aware ortholog disambiguation | ProteinOrtho `-synteny` or GENESPACE | Tandem duplicates collapsed; co-orthologs assigned to syntenic position |
| Reference-guided assembly bias check | DO NOT use synteny across reference-guided scaffolds | Reference-guided scaffolds propagate scaffold assumptions; circular reasoning |
| Microsynteny network analysis | SynNet | Network from many genomes; detects ancient micro-conserved clusters |
| Synteny across > 15% divergent genomes | ntSynt or i-ADHoRe | Alignment-free or ordered-list approaches |
| Identifying syntelogs (syntenic orthologs only) | GENESPACE `riparian()` output; or MCScanX filtered by chr-pair | Syntelog tracks