Synteny analysis

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 only same-chromosome-pair orthologs

Per-Tool Failure Modes

Repeat-derived false synteny

Trigger: Running BLAST input for MCScanX/JCVI without softmasking repeats; or weak softmasking.

Mechanism: Transposable elements occupy 30-80% of plant and animal genomes; unmasked TEs produce millions of paralogous BLAST hits forming "synteny" blocks that are TE-driven, not real ancestry. The dynamic programming sees long apparent collinear blocks of TE-encoded proteins.

Symptom: MCScanX/JCVI output dominated by short (5-10 anchor) blocks; blocks cluster in TE-rich regions (heterochromatin, centromeric); BLAST hit count > 10x what is expected for the divergence.

Fix: Softmask genomes with RepeatModeler2 (de novo TE library) + RepeatMasker before BLAST; report softmasking statistics. For MCScanX, set -e 1e-10 (stricter) for close species, -e 1e-5 for distant. JCVI --cscore 0.95 enforces near-reciprocal-best-hit, dramatically reducing TE-driven blocks. Always check that block size distribution drops at 5-10 anchors (TE-driven) vs proper > 20 anchor blocks (real synteny).

Reference-guided assembly creating circular synteny

Trigger: Comparing a de novo assembly with a reference-guided scaffold of the same / related species.

Mechanism: Reference-guided scaffolding orders contigs based on synteny to the reference. Comparing the resulting scaffold to that same reference produces "synteny" that is actually the imposed reference order, not biological gene order. The comparison is circular.

Symptom: Suspicious uniformity in synteny across most chromosomes; visualization shows reference and query as perfectly parallel; SyRI reports few SVs where divergence-time-appropriate counts would predict many.

Fix: Verify assembly method via metadata. For reference-guided assemblies, treat synteny inferences with the reference as suspect; use a sister species reference or pure de novo assembly. Hi-C-scaffolded assemblies are not "reference-guided" in this sense and are safe.

Fragmented assemblies underestimating macrosynteny

Trigger: Running synteny on draft assemblies with N50 < 1 Mb.

Mechanism: Macrosynteny detection requires that syntenic blocks be on single contigs; if contigs are short, blocks are artificially truncated. JCVI reports show artifactual "synteny loss" between species when one assembly is fragmented.

Symptom: Synteny "loss" correlates with assembly N50; per-chromosome dotplots show dotted lines where solid diagonals expected; SyRI reports excessive INVs / TRANS where the divergence is actually low.

Fix: Require minimum N50 of 1 Mb for cross-species synteny; chromosome-level assemblies preferred for SyRI. For fragmented assemblies, restrict analysis to long-contig regions or use SyRI's contig-level mode with caveats.

Tandem duplicate inflation

Trigger: Including tandemly duplicated genes in synteny anchor input.

Mechanism: Tandem duplicates produce many same-region BLAST hits between species; the dynamic programming includes them as multiple anchors per gene position, artificially inflating block size and confidence.

Symptom: "High-confidence" synteny blocks in regions known for tandem expansions (NLR clusters in plants, OR genes in mammals); blocks anchored largely on adjacent tandem duplicates of the same gene.

Fix: MCScanX automatically collapses tandem duplicates (within 5 genes by default; -w parameter). Verify in the output the tandem-collapse step ran. JCVI --tandem_Nmax 10 is more aggressive. For NLR / OR genes specifically, manual tandem filtering before BLAST is preferred.

Cross-genome chromosome name mismatch

Trigger: GFF and FASTA from different sources with different chromosome naming (chr1 vs Chr1 vs 1 vs NC_001234.5).

Mechanism: MCScanX requires chromosomes to be named consistently; mismatch causes empty output or partial blocks.

Symptom: MCScanX completes but .collinearity file is small or empty; warnings about unknown chromosome IDs.

Fix: Normalize chromosome names with awk or samtools faidx --regions to unify naming convention; verify GFF + FASTA share the same names. For NCBI assemblies, use datasets to download with consistent labels.

SyRI complaining about inversions in absence of true inversions

Trigger: Running SyRI on alignments with many small-scale rearrangements; or when one genome has been re-ordered (different convention for which strand is "+").

Mechanism: SyRI's syntenic-path algorithm penalizes any rearrangement; high-divergence pairs accumulate small-scale rearrangements that are not "real" inversions but inheritance differences.

Symptom: SyRI reports thousands of small "inversions" (< 1 kb); blocks dominate the SV count; total INV length unrealistic.

Fix: Filter SyRI output by size: real biologically-relevant INVs are typically > 5 kb. Tighten minimap2 sensitivity (-x asm5 for close species; -x asm10 or -x asm20 for more divergent). Reverse-complement one assembly's chromosomes if the strand convention differs.

GENESPACE OrthoFinder version mismatch

Trigger: Running GENESPACE with an outdated bundled OrthoFinder.

Mechanism: GENESPACE bundles a specific OrthoFinder version; if user's installed OrthoFinder is newer (v3 vs v2.5), the HOG output layout differs and GENESPACE parsing fails.

Symptom: GENESPACE reports "Phylogenetic_Hierarchical_Orthogroups not found" or similar; orthogroup table is empty.

Fix: Use the OrthoFinder version GENESPACE expects (currently OrthoFinder 2.5.4 for GENESPACE 1.4.x). Pin via conda env. Future GENESPACE versions will adapt to OrthoFinder 3 layout (Lovell update expected).

Microsynteny vs macrosynteny conflation

Trigger: Reporting "synteny" without specifying scale.

Mechanism: Macrosynteny (same chromosome) is detectable across hundreds of millions of years but decays as rearrangements accumulate; microsynteny (same order within local region) can be deeply conserved even when macrosynteny is lost. Conflating them produces misleading "synteny loss" claims.

Symptom: Reports of "synteny lost between species X and Y" when both share microsyntenic gene clusters; or vice versa.

Fix: Always specify scale. SynNet (Zhao 2017) explicitly separates the two. MCScanX -s parameter (minimum block anchors) at 5 = microsynteny; at 20+ = macrosynteny. Report block-size distribution.

Polyploid / WGD-affected genome ambiguity

Trigger: Running MCScanX on a polyploid (e.g. allohexaploid wheat) without subgenome assignment.

Mechanism: WGD doubles all genes; synteny is between subgenomes within the polyploid AND across to outgroup. Without subgenome assignment, all paralogs and orthologs collapse into the same blocks.

Symptom: Many "1:many" or "many:many" synteny relationships; per-chromosome synteny counts indicate doubled or tripled blocks; Ks distribution multimodal.

Fix: Use AnchorWave proali with explicit ploidy specification. Alternatively, run synteny twice: within polyploid (subgenome-vs-subgenome) and across to outgroup. See [[whole-genome-duplication]] for subgenome assignment workflow.

Quantitative Thresholds

Quantity	Threshold	Source / Rationale
Assembly N50 for synteny	>= 1 Mb	Below this, results tool-dependent and unreliable; chromosome-level strongly preferred
MCScanX -s (minimum anchors per block)	5 default; 10 stringent; 3 sensitive	Standard configuration; 5 is balance
MCScanX -m (maximum gaps between anchors)	25 default	Higher for distant species; lower for recent
MCScanX -k (match score per anchor)	50 default	Higher rewards longer blocks
MCScanX -e (BLAST e-value)	1e-5 default; 1e-10 for close species	Stricter for recent radiations
BLAST evalue threshold	1e-5 to 1e-10 typical	Depends on divergence
JCVI --cscore for reciprocal best	0.7 default; 0.95 near-RBH; 0.99 RBH-only	Higher = fewer false positives, fewer hits
Tandem duplicate window	5-10 genes (MCScanX default 5; JCVI 10)	Wang 2012; species-specific tuning
SyRI INV minimum size for biological significance	>= 5 kb	Below this, alignment noise dominates
SyRI TRANS minimum size	>= 1 kb	Standard convention
GENESPACE minimum syntenic block	5 orthogroups	Lovell 2022 default
Synteny block decay (macrosynteny half-life)	~150 Myr in vertebrates	Naruse 2004; Murat 2010
Microsynteny conservation	up to 1 Gyr for metabolic gene clusters	Slot & Rokas 2010
minimap2 preset for synteny	-x asm5 for < 5% divergence; asm10 for ~10%; asm20 for ~20%	minimap2 docs
MUMmer nucmer maxmatch	--maxmatch for SyRI; --mum default	MUMmer4 manual
Ks for syntenic block age (cross-references WGD)	Ks 0.1-0.5 recent; 0.5-1.5 older; > 1.5 saturated	See [[whole-genome-duplication]] for Ks plot interpretation
Repeat masking minimum	>= 90% of known TE families masked (RepeatMasker .tbl)	Below this, expect spurious synteny

MCScanX Standard Pipeline

Goal: Detect collinear gene blocks between two genomes.

Approach: Prepare 4-column BED with species prefix -> all-vs-all BLASTP -> run MCScanX -> parse .collinearity -> classify blocks.

# 1. Prepare MCScanX-format BED (species_chr  gene  start  end)
python -m jcvi.formats.gff bed --type=gene --key=ID species_A.gff > A.gff.tmp
python -m jcvi.formats.gff bed --type=gene --key=ID species_B.gff > B.gff.tmp
awk 'BEGIN{OFS="\t"}{print "A"$1, $4, $2, $3}' A.gff.tmp > work/A.gff
awk 'BEGIN{OFS="\t"}{print "B"$1, $4, $2, $3}' B.gff.tmp > work/B.gff
cat work/A.gff work/B.gff > work/A_B.gff

# 2. All-vs-all DIAMOND BLAST (faster than BLAST+)
diamond makedb --in species_A.faa --db work/A.dmnd
diamond makedb --in species_B.faa --db work/B.dmnd
diamond blastp --db work/A.dmnd --query species_A.faa --threads 16 \
    --outfmt 6 --evalue 1e-10 --max-target-seqs 5 --out work/AA.blast
diamond blastp --db work/B.dmnd --query species_B.faa --threads 16 \
    --outfmt 6 --evalue 1e-10 --max-target-seqs 5 --out work/BB.blast
diamond blastp --db work/B.dmnd --query species_A.faa --threads 16 \
    --outfmt 6 --evalue 1e-10 --max-target-seqs 5 --out work/AB.blast
diamond blastp --db work/A.dmnd --query species_B.faa --threads 16 \
    --outfmt 6 --evalue 1e-10 --max-target-seqs 5 --out work/BA.blast
cat work/AA.blast work/BB.blast work/AB.blast work/BA.blast > work/A_B.blast

# 3. Run MCScanX
cd work && MCScanX -s 5 -m 25 -k 50 -e 1e-10 A_B
# Output: A_B.collinearity (block table), A_B.tandem (tandem clusters), A_B.html (browsing)

'''Parse MCScanX .collinearity and classify synteny relationships.'''
import re
from collections import defaultdict


def parse_collinearity(path):
    '''Returns list of dicts: {block_id, n_anchors, e_value, score, gene_pairs: [(g1, g2), ...]}'''
    blocks = []
    current = None
    with open(path) as fh:
        for line in fh:
            if line.startswith('## Alignment'):
                if current:
                    blocks.append(current)
                m = re.match(r'## Alignment (\d+): score=([0-9.]+) e_value=([0-9.e\-]+) N=(\d+)', line)
                if m:
                    current = {
                        'block_id': int(m.group(1)),
                        'score': float(m.group(2)),
                        'e_value': float(m.group(3)),
                        'n_anchors': int(m.group(4)),
                        'gene_pairs': []
                    }
            elif current and ':' in line and '\t' in line:
                parts = line.strip().split()
                if len(parts) >= 3:
                    current['gene_pairs'].append((parts[1], parts[2]))
    if current:
        blocks.append(current)
    return blocks


def classify_chromosome_synteny(blocks, gene_to_chr):
    '''Classify syntenic chromosome relationships: 1-1, 1-many, many-many.'''
    a_partners = defaultdict(set)
    for blk in blocks:
        for g1, g2 in blk['gene_pairs']:
            c1, c2 = gene_to_chr.get(g1), gene_to_chr.get(g2)
            if c1 and c2:
                a_partners[c1].add(c2)
    result = {}
    for chr_a, partners in a_partners.items():
        n = len(partners)
        result[chr_a] = '1-1' if n == 1 else ('1-many' if n <= 3 else 'many-many')
    return result

GENESPACE Plant-Focused Pipeline

Goal: Build pan-gene tracks across N plant genomes with orthology-anchored synteny visualization.

Approach: Format input: per-species GFF + protein FASTA -> initialize -> run -> riparian plot.

library(GENESPACE)

dir.create('work_dir')
parsedPaths <- parse_annotations(
    rawGenomeRepo = 'raw_genomes/',
    genomeDirs = list.dirs('raw_genomes/', recursive = FALSE),
    headerEntryIndex = 1,
    gffString = 'gff',
    faString = 'protein.faa',
    genespaceWd = 'work_dir/'
)

gpar <- init_genespace(
    wd = 'work_dir/',
    nCores = 8,
    rawOrthofinderDir = NULL,  # GENESPACE bundles OrthoFinder 2.5.x
    onewayBlast = TRUE
)

out <- run_genespace(gsParam = gpar, overwrite = TRUE)

# Riparian plot for 5 genomes vs reference
ripDat <- plot_riparian(
    gsParam = out,
    refGenome = 'Reference_species',
    useOrder = FALSE,
    backgroundColor = 'white'
)

GENESPACE outputs include results/syntenicHits.txt (anchor pairs), results/pangenes.txt (pan-gene presence/absence matrix), and results/riparian.pdf (riparian visualization). Pan-gene tracks across species are particularly useful for identifying lineage-specific genes (cf. pangenome-analysis for bacterial scope).

SyRI for Structural Rearrangement Inventory

Goal: Identify INVs, TRANSs, DUPs, INS, DEL between two chromosome-level genome assemblies.

Approach: Align with minimap2 -x asm5 -> filter to chromosome-level mappings -> run SyRI -> visualize with plotsr.

# 1. Whole-genome alignment with minimap2
minimap2 -ax asm5 --eqx -t 16 reference.fa query.fa | \
    samtools sort -@ 8 -O bam - > work/aln.bam
samtools index work/aln.bam

# 2. SyRI on the alignment
syri -c work/aln.bam -r reference.fa -q query.fa -F B --prefix work/syri_out -k

# Outputs:
#   syri_out.syri.out      structural variant table (SYN/INV/TRANS/DUP/INS/DEL)
#   syri_out.syri.vcf      VCF-format variants
#   syri_out.syri.summary  block-level summary

# 3. Visualize with plotsr
echo "ref_species  query_species" > work/genome_pairs.txt
plotsr --sr work/syri_out.syri.out --genomes work/genome_pairs.txt \
    --output work/syri_plot.png --markers gene_markers.bed

For multi-genome rearrangement: run SyRI pairwise for each adjacent species in a phylogeny, then plotsr stacks the panel.

JCVI / MCScan Python for Publication Plots

Goal: Produce publication-grade dotplots, karyotype, and synteny visualization.

Approach: Use JCVI's catalog ortholog workflow to derive anchors -> generate dotplot or karyotype directly.

# 1. Detect orthologs and synteny
python -m jcvi.formats.gff bed --type=mRNA --key=Name species_A.gff > A.bed
python -m jcvi.formats.gff bed --type=mRNA --key=Name species_B.gff > B.bed
python -m jcvi.formats.fasta format species_A.faa A.fasta
python -m jcvi.formats.fasta format species_B.faa B.fasta

python -m jcvi.compara.catalog ortholog --no_strip_names A B
# Produces A.B.lifted.anchors and other files

# 2. Dotplot
python -m jcvi.graphics.dotplot A.B.anchors --dpi 300 --output dotplot.png

# 3. Karyotype (chromosome-level synteny)
# Layout file: each row = species  chr  start  end  reverse
cat > layout.csv << 'EOF'
A.chr1 species_A 1 50000000 1
B.chr2 species_B 1 60000000 1
EOF
python -m jcvi.graphics.karyotype seqids.txt layout.csv

# 4. Microsynteny block plot
python -m jcvi.graphics.synteny blocks.layout

Reconciliation: When Methods Disagree

Pattern	Likely cause	Action
MCScanX many blocks, GENESPACE few	GENESPACE uses orthogroup-constrained anchors (more conservative)	GENESPACE excludes non-orthogroup hits; MCScanX includes any high BLAST hit; trust GENESPACE for orthology-anchored synteny
GENESPACE 1:1 syntelog, MCScanX 1:many	Tandem duplicates in MCScanX collapsed at different granularity	Trust GENESPACE for clear syntelogs; MCScanX 1:many often reflects tandem expansions
SyRI reports many INVs, plotsr shows mostly SYN	Small INVs below biological-relevance threshold	Filter SyRI INVs < 5 kb; SyRI was correct, just noisy
MCScanX block on chromosomes that JCVI doesn't pair	JCVI --cscore 0.7 more restrictive	Lower JCVI cscore to 0.5 OR raise MCScanX -e to 1e-10
AnchorWave finds collinearity in WGD region, MCScanX doesn't	AnchorWave WGD-aware; MCScanX treats all anchors equally	AnchorWave correct for WGD lineages
ntSynt macrosynteny across genus, MCScanX microsynteny only	Different scales	Both correct at their scale; report both with explicit scale labels
SyRI calls "translocation" but it's a known chromosome split	Centromere break / Robertsonian translocation	Manual cytogenetic context; SyRI's mechanical detection is correct but may not be biologically novel
Recent species pair has > 1000 SVs in SyRI	Either real chromosome instability OR assembly errors	Check assembly QC (telomere completeness; BUSCO); cross-check with PacBio long-read SVs
Synteny on reference-guided scaffold	Circular reasoning	Discard synteny calls between scaffold and its reference

Operational rule for publication: Synteny block annotation requires (1) BUSCO/Compleasm > 90% complete on both genomes; (2) softmasked repeats verified; (3) at least one cross-validation tool (MCScanX vs JCVI or MCScanX vs GENESPACE); (4) microsynteny vs macrosynteny scale explicit; (5) for SV calls, plotsr / SyRI followed by manual review of large rearrangements with read-coverage support.

Cohort Gotchas

• Polyploid plants: WGD events confound 1:1 synteny; use AnchorWave or subgenome-assigned analysis
• Salmonids / fish 4R: Ts3R + Ss4R WGD events; ohnologs (WGD paralogs) appear as syntenic but not orthologous; cross-reference [[whole-genome-duplication]]
• Mammalian X chromosome: Massive recombination suppression; "synteny" sometimes inverted in opposite sex; verify strand convention
• Centromeric regions: generally unalignable; synteny tools may produce false breaks near centromeres
• Telomeres: assembly often incomplete; synteny calls near telomere boundaries unreliable
• Sex chromosomes: rapidly evolving; lower synteny signal than autosomes
• Plant B chromosomes: supernumerary; exclude from synteny analysis

Anticipated Reviewer Pushback

Pushback	Standard response
"Assembly completeness?"	BUSCO/Compleasm > 90%; N50 reported per assembly; chromosome-level (or scaffold N50 > 1 Mb)
"Repeat masking?"	RepeatModeler2 de novo TE library + RepeatMasker; > 90% of known TE families masked; softmasked, not hardmasked
"Reference-guided scaffolding?"	Verified de novo OR Hi-C scaffolded; no reference-guided steps
"Tandem duplicates?"	Collapsed by MCScanX automatic detection (window 5); JCVI tandem_Nmax 10
"Cross-validation?"	MCScanX results validated against JCVI (or GENESPACE) at consistent stringency
"Microsynteny vs macrosynteny?"	Reported both scales; minimum block size 5 anchors for microsynteny, 20+ for macrosynteny
"WGD-aware?"	AnchorWave proali with ploidy specification (for polyploids); or restricted to non-WGD lineages
"SV calling sensitivity?"	SyRI INVs > 5 kb; cross-validated with PacBio long-read SV calls where available
"Synteny block age (Ks)?"	Ks plotted per block; saturation threshold (Ks > 2) applied; see [[whole-genome-duplication]]
"Bacterial pangenome reference?"	Not applicable here; see [[pangenome-analysis]] for prokaryotes

Common Errors

Error / symptom	Cause	Solution
MCScanX produces empty .collinearity	4-column BED format wrong (extra columns, wrong delimiter, missing prefix)	Check exact 4-column format: species_prefix_chr gene_id start end; tabs only
MCScanX dumps "no matches" message	BLAST e-value too strict; or gene IDs don't match BED	Verify gene IDs in BED match BLAST input; relax e-value
GENESPACE "OrthoFinder version mismatch"	Bundled OrthoFinder version conflict	Pin OrthoFinder 2.5.x for GENESPACE 1.4.x; or update GENESPACE
JCVI dotplot empty	--cscore too strict; few anchors survive	Lower cscore to 0.5; or check BLAST hit count
SyRI "no chromosomes match"	Reference and query use different chromosome IDs	Normalize names: samtools faidx --regions to extract by name
SyRI INVs appear in all assemblies	Strand convention issue OR repeat-driven	Reverse-complement one assembly's chromosomes if convention differs; mask repeats
AnchorWave proali times out	Genome > 1 Gb with high TE density	Pre-mask repeats; consider GENESPACE / MCScanX alternative
GENESPACE riparian plot too crowded	> 10 genomes	Subset to representative species or use multi-page riparian
Per-chromosome BLAST hit count > 100,000	Unmasked repeats	Softmask before BLAST; verify by counting TE-encoded protein hits
Synteny blocks on Y chromosome appear absent	Y not assembled fully; or sex-specific	Document assembly limitation; exclude Y from synteny analysis

Tool Installation Notes

# MCScanX
git clone https://github.com/wyp1125/MCScanX && cd MCScanX && make
# JCVI / MCScan Python
pip install jcvi
# GENESPACE
remotes::install_github('jtlovell/GENESPACE')
# SyRI + plotsr
conda install -c bioconda syri plotsr
# AnchorWave
conda install -c bioconda anchorwave
# i-ADHoRe
git clone https://github.com/VIB-PSB/i-ADHoRe && cd i-ADHoRe && mkdir build && cd build && cmake .. && make
# ntSynt
pip install ntsynt
# minimap2 + MUMmer4
conda install -c bioconda minimap2 mummer4

# Repeat masking
conda install -c bioconda repeatmodeler repeatmasker

For GENESPACE, OrthoFinder 2.5.x must be pinned; install via conda install -c bioconda orthofinder=2.5.5. JCVI is the most generally useful Python toolkit; install per-project alongside specific synteny tools.

References

• Fitch WM 1976 J Mol Evol 7:271 (synteny vs collinearity)
• Wang Y et al 2012 NAR 40:e49 (MCScanX)
• Tang H et al 2008 GR 18:1944 (synteny / MCScan Python)
• Lovell JT et al 2022 eLife 11:78526 (GENESPACE)
• Proost S et al 2012 NAR 40:e11 (i-ADHoRe 3.0)
• Song B et al 2022 PNAS 119:e2113075119 (AnchorWave)
• Goel M et al 2019 Genome Biol 20:277 (SyRI)
• Goel M et al 2022 Bioinformatics 38:2922 (plotsr)
• Zhao T et al 2017 NAR 45:e108 (SynNet synteny network)
• Marçais G et al 2018 PLoS Comp Biol 14:e1005944 (MUMmer4)
• Schwartz S et al 2003 GR 13:103 (LASTZ chains and nets)
• Jain C et al 2018 Bioinformatics 34:i748 (MashMap)
• Li H 2018 Bioinformatics 34:3094 (minimap2)
• Slot JC & Rokas A 2010 GBE 2:362 (microsynteny conservation in metabolic clusters)
• Naruse K et al 2004 GR 14:820 (synteny block decay)
• Murat F et al 2010 GR 20:1545 (vertebrate macrosynteny)
• Holland PWH et al 1994 Development Suppl:125 (2R hypothesis)
• Vanneste K et al 2013 GR 23:1304 (Ks saturation)
• Freeling M 2007 PNAS 104:8723 (gene balance)
• Force A et al 1999 Genetics 151:1531 (subfunctionalization)
• Zhao T & Schranz ME 2017 NAR 45:e108 (synteny network for phylogeny)
• Smith MR & Hahn MW 2021 PNAS 118:e2103725118 (gene-tree-aware synteny)

Related Skills

• comparative-genomics/whole-genome-duplication - Ks-based WGD detection, paranome construction, KsRates
• comparative-genomics/whole-genome-alignment - Cactus / Minigraph-Cactus / LASTZ chains-and-nets for sequence-level synteny
• comparative-genomics/ortholog-inference - GENESPACE depends on OrthoFinder; synteny verifies orthology in WGD lineages
• comparative-genomics/pangenome-analysis - Bacterial pangenome (different problem; for prokaryotes)
• comparative-genomics/comparative-annotation-projection - TOGA + CESAR project genes through WGA-derived synteny
• comparative-genomics/positive-selection - Selection on syntenic gene pairs (1:1 syntelogs)
• phylogenetics/modern-tree-inference - Phylogenetic context for synteny block dating
• genome-assembly/assembly-qc - BUSCO / Compleasm assembly completeness check before synteny
• alignment/structural-alignment - Sequence-level alignment underlying SyRI
• variant-calling/structural-variant-calling - SV detection from short reads (orthogonal to SyRI WGA-based)