bio-comparative-genomics-comparative-annotation-projection

What this skill does

## Version Compatibility

Reference examples tested with: TOGA 1.1.7+ (hillerlab/TOGA; Kirilenko 2023 Science 380:eabn3107), CESAR 2.0 (Sharma & Hiller 2017 NAR 45:8369), LiftOff 1.6.3+ (Shumate & Salzberg 2021 Bioinformatics 37(12):1639-1643), Comparative Annotation Toolkit (CAT) 2.4+, GeMoMa 1.9+ (Keilwagen 2019 Methods Mol Biol 1962:161), UCSC liftOver 2024+, Cactus 2.9.1+ (for HAL input), HAL toolkit 2.3+, NextFlow 24+ for TOGA pipeline, BUSCO 5.7+ / Compleasm 0.2.7+ for QC, Snakemake 8.0+ for CAT, R 4.4+. The current TOGA expects HAL from Cactus 2.5+; older HAL formats may fail.

Before using code patterns, verify installed versions match. If versions differ:
- CLI: `toga.py --help`; `cesar --help`; `liftoff --version`
- Python: `pip show liftoff`
- Java: `gemoma --help` (Java 11+)

If code throws `TOGA chain file missing`, `CESAR fragment not found`, `LiftOff annotation not parsed`, the toolchain expects specific input formats: TOGA needs HAL or chain/net files from Cactus / LASTZ; CESAR needs exon-level GFF; LiftOff needs reference GFF and aligned FASTA. Pre-process with the appropriate format conversion.

# Comparative Annotation Projection

**"Annotate this new genome using my well-annotated reference"** -> Annotation projection from a reference is the modern alternative to de novo gene prediction; it produces high-quality, comparable annotations across genomes by leveraging evolutionary conservation. The 2023-era standard is **TOGA + CESAR 2.0** (Kirilenko 2023 Science 380:eabn3107), which uses whole-genome alignment chains + ML classification + codon-aware exon projection to scale to hundreds of genomes (Zoonomia: 488 mammals; Bird10000 Genomes: 501 birds). For ortholog-based projection (no WGA needed), **LiftOff** (Shumate & Salzberg 2021 Bioinformatics 37(12):1639) is the standard. The critical decision is **WGA-anchored (TOGA) vs ortholog-anchored (LiftOff)**: TOGA explicitly classifies gene intactness vs loss using the alignment chains, LiftOff relies on reciprocal-best-hit equivalents.

- CLI: `toga.py --chain chain.bb --bed ref.bed --tDB target.2bit --qDB query.2bit --pn project_name` -- WGA-based projection
- CLI: `cesar -i exons.fa -d 4 -o output.aln` -- codon-aware exon alignment (used internally by TOGA)
- CLI: `liftoff -g ref.gff query.fa ref.fa -o query.gff` -- ortholog-based projection
- CLI: `gemoma` -- evidence-based comparative annotation (Java)
- CLI: `cat` (Comparative Annotation Toolkit) -- multi-species annotation projection

## Algorithmic Taxonomy

| Tool | Approach | Output | Strength | Fails when |
|------|----------|--------|----------|------------|
| TOGA (Kirilenko 2023 Science 380:eabn3107) | Cactus HAL or LASTZ chains -> ML projection + intactness classifier | Per-gene I/PI/UL/L/M/PM codes; orthology classification; coding annotation via CESAR 2.0 | Modern paradigm; explicit gene-loss detection at scale; Zoonomia / Bird10000 standard | Requires Cactus WGA; not for prokaryotes |
| CESAR 2.0 (Sharma & Hiller 2017 NAR 45:8369) | HMM-based codon-aware exon projection | Aligned exons + frame preservation | Most accurate exon projection from WGA; preserves frame across indels | Used internally by TOGA; standalone use more rare |
| LiftOff (Shumate & Salzberg 2021 Bioinformatics 37(12):1639-1643) | Read-mapping-style ortholog detection + GFF transfer | Lifted GFF | Fast; no WGA required; standard for query-vs-reference pairs | Tandem duplicates ambiguous; not for gene loss detection |
| UCSC liftOver | Coordinate-based lift using chain files | Coordinate-lifted regions | Standard for coordinate transfers; not for gene annotations | Doesn't handle gene structure changes |
| Comparative Annotation Toolkit (CAT) | Snakemake workflow integrating Augustus + LiftOff + TransMap | Per-species comparative annotation | Integrates de novo + projection | Snakemake setup complex |
| GeMoMa (Keilwagen 2019 Methods Mol Biol 1962:161) | Reference protein homology + evidence integration | Comparative gene annotation | Combines multiple reference species evidence | Slower; less popular than TOGA / LiftOff |
| AUGUSTUS (Stanke 2008) | De novo prediction; not strictly projection | Per-genome annotation | Augments projection with de novo | Standalone de novo; lower comparative accuracy |
| BRAKER3 (Brůna 2024) | Augustus + GeneMark-ETP + RNA-Seq + protein | Comparative-aware de novo | Modern de novo with evidence | Not strictly projection |
| Funannotate (palmer lab) | Multi-evidence annotation including LiftOff | Funannotate annotations | Integrates evidence | Setup complex |
| Comparative Annotation Pipeline (CAP) | Earlier WGA-based annotation | Per-species per-gene | Historical; replaced by TOGA | Use TOGA |
| TransMap (Diekhans 2007) | UCSC genome browser annotation lifter | Per-locus lift | Tool for UCSC tracks | Tool-specific |
| Maker (Cantarel 2008) | Evidence-based de novo + projection | Per-genome annotation | Combines evidence | Maker is for novel genomes; LiftOff for transfer |

Methodology evolves; the Kirilenko 2023 TOGA paradigm (WGA-anchored + intactness classification) is the gold standard for vertebrate-scale comparative annotation. For pairwise transfers, LiftOff is the modern standard. Verify the current TOGA documentation (hillerlab/TOGA) before locking on a single approach.

## Decision Tree by Experimental Scenario

| Scenario | Recommended approach | Why |
|----------|------------------------|-----|
| Annotate hundreds of mammal / bird genomes | TOGA with Cactus HAL | Scales to Zoonomia / Bird10000 |
| Annotate single new genome from reference | LiftOff | Fast; no WGA required |
| Detect gene loss across mammals | TOGA intactness classification | Explicit I/PI/UL/L/M/PM codes |
| Project alternative isoforms | TOGA (preserves multiple transcripts) | Standard |
| Project annotations to assembly with high N50 + chromosome-level | TOGA | Requires good assembly |
| Project to fragmented draft assembly | LiftOff (more tolerant) | LiftOff works on draft assemblies |
| Multi-species annotation pipeline | CAT (Snakemake) | Integrated workflow |
| Annotate plant genome from Arabidopsis | LiftOff with plant-specific options | Standard for plant work |
| Pseudogenization detection at scale | TOGA + intactness analysis | Designed for this |
| Reference-free gene prediction | BRAKER3 or AUGUSTUS | De novo; not projection |
| Comparative annotation of multiple references | GeMoMa | Multi-reference evidence integration |
| UCSC genome browser coordinate transfer | liftOver tool | Coordinate-specific |
| Annotation transfer to closely related strain (>95% ANI) | LiftOff | High accuracy at close divergence |
| Annotation transfer to deep divergence (mammal to fish) | TOGA + manual review | Requires WGA; expect lower coverage |
| Project annotations with WGD-aware handling | AnchorWave + TOGA-like or custom workflow | WGD-aware tools |
| Annotate non-coding RNAs | Specialized tools (Rfam, ncRNA-specific) | RNA detection different problem |
| Annotate immune / repetitive genes (MHC, OR) | PGR-TK MAP graph or manual | Repetitive regions; use [[pangenome-analysis]] |
| Annotate transposable elements | RepeatMasker / RepeatModeler | TE annotation different problem |
| Validate projected annotations | RNA-Seq alignment to projected | RNA-Seq evidence is gold standard |

## Per-Tool Failure Modes

### TOGA chain file missing or incompatible

**Trigger:** Running TOGA on Cactus HAL without proper chain file extraction.

**Mechanism:** TOGA requires UCSC-style chain files derived from Cactus HAL or LASTZ chains/nets pipeline. Cactus HAL doesn't directly produce chain files; conversion via halSynteny + chainNet + axtChain is required.

**Symptom:** TOGA fails with "chain file not found" or "no syntenic blocks for query."

**Fix:** Use `halSynteny` (HAL toolkit) to extract syntenic blocks; convert to chain format via `axtChain` and `chainNet`. The TOGA Nextflow wrapper handles this automatically; for manual runs, see UCSC kentUtils chain