Adapting to Other Species

ancify works with any focal species for which you have pairwise net AXT alignments. This guide teaches you how to think about outgroup selection and walks through examples from across the tree of life.

A framework for choosing outgroups

Before configuring ancify, you need to make one key decision: which species are your inner outgroups and which are your outer outgroups?

Step 1: Draw the phylogeny

Sketch (or look up) the phylogenetic relationships around your focal species. You need at least three species total: your focal, one inner outgroup, and one outer outgroup.

  Example for human:

                 6 Mya         9 Mya              25 Mya
                  ┌─── Bonobo
            ┌─────┤                          ┌ INNER tier
            │     └─── Chimp                 │ (closely related)
     ┌──────┤                                │
     │      └──────── Gorilla               ─┘
  ───┤
     │
     └──────────────────── Macaque          ── OUTER tier
                                               (distantly related)

Step 2: Assign tiers

Inner outgroups should be:

Closely related to the focal species (same genus or family)
Diverged more recently than the outer outgroup
Ideally 2 or more species (enables majority voting)

Outer outgroups should be:

Clearly outside the inner clade
Diverged at least 2-3x further than the inner outgroups
Far enough that convergent mutations with the inner group are extremely rare

Step 3: Check data availability

For each candidate outgroup, check if UCSC has a pairwise net AXT alignment to your focal assembly:

https://hgdownload.soe.ucsc.edu/goldenPath/<focal_assembly>/

Look for directories named vs<Outgroup>. If the alignment exists, you are in business.

Decision flowchart

  Do you have ≥2 inner outgroups with AXT alignments?
    │
    ├─ YES → Great! Majority voting will be robust.
    │
    └─ NO → Do you have 1 inner + 1 outer?
              │
              ├─ YES → Still works. The outer outgroup provides
              │        the independent check. Consider adding more
              │        inner species if available.
              │
              └─ NO → You need at least 1 inner + 1 outer.
                      Check UCSC or generate your own alignments.

Worked examples

Tip

Quick test: The repo includes one-chromosome example scripts for human (chr22), mouse (chr19), Drosophila (chr4), and Brassica rapa (A01). From the repo root run e.g. ./scripts/examples/human/run.sh. See Quickstart and scripts/README.md.

Human (hg38) — the gold standard

focal_species: human
chromosome_lengths: chromoLens.txt

outgroups:
  inner:
    - name: bonobo      # ~6 Mya
      alignment: hg38.panPan3.net.axt.gz
    - name: chimp       # ~6 Mya
      alignment: hg38.panTro6.net.axt.gz
    - name: gorilla     # ~9 Mya
      alignment: hg38.gorGor6.net.axt.gz
  outer:
    - name: macaque     # ~25 Mya
      alignment: hg38.rheMac10.net.axt.gz

output_dir: ./human_ancestral
num_cpus: 24

Why this works well: Three inner outgroups provide redundancy. The inner-outer divergence ratio (~6-9 Mya vs. ~25 Mya) is large enough that convergent errors between tiers are negligible. Alignment coverage is excellent for all four species.

Mouse (mm39) — minimal setup

focal_species: mouse
chromosome_lengths: mm39.chromLens.txt

outgroups:
  inner:
    - name: rat            # ~12 Mya
      alignment: mm39.rn7.net.axt.gz
  outer:
    - name: rabbit         # ~90 Mya
      alignment: mm39.oryCun2.net.axt.gz

output_dir: ./mouse_ancestral
num_cpus: 8

With only one inner species, the majority vote is trivially that species’ allele. The outer outgroup still provides the independent confirmation. To strengthen the inner tier, consider adding hamster or other rodents if alignments are available.

Drosophila melanogaster (dm6) — non-chr naming

focal_species: drosophila_melanogaster
chromosome_lengths: dm6.chromLens.txt
chromosomes: [2L, 2R, 3L, 3R, 4, X]

outgroups:
  inner:
    - name: simulans       # ~2.5 Mya
      alignment: dm6.droSim2.net.axt.gz
    - name: sechellia      # ~2.5 Mya
      alignment: dm6.droSec1.net.axt.gz
  outer:
    - name: yakuba         # ~6 Mya
      alignment: dm6.droYak3.net.axt.gz

output_dir: ./dmel_ancestral
num_cpus: 6

Note: The chromosome names (2L, 3R, etc.) do not have a chr prefix — ancify handles any naming convention. The explicit chromosomes list excludes heterochromatic scaffolds.

Brassica rapa (plant) — beyond animals

focal_species: brassica_rapa
chromosome_lengths: braRap1.chromLens.txt

outgroups:
  inner:
    - name: brassica_oleracea   # close relative, same genus
      alignment: braRap1.braOleracea.net.axt.gz
  outer:
    - name: arabidopsis_thaliana  # ~20 Mya, same family Brassicaceae
      alignment: braRap1.araTha1.net.axt.gz

output_dir: ./brassica_rapa_ancestral
num_cpus: 4

Plant genomes often use chromosome naming like A01, A02. Omit the chromosomes key to process all entries in the lengths file. Plant genome alignments may be more fragmented due to whole-genome duplications — expect higher N rates than in mammals.

Zebrafish (danRer11) — fish

focal_species: zebrafish
chromosome_lengths: danRer11.chromLens.txt

outgroups:
  inner:
    - name: medaka
      alignment: danRer11.oryLat2.net.axt.gz
  outer:
    - name: fugu
      alignment: danRer11.fr3.net.axt.gz

output_dir: ./zebrafish_ancestral
num_cpus: 4

Fish have high substitution rates compared to mammals, so the divergence between inner and outer outgroups needs to be carefully considered. Medaka and fugu provide a reasonable tier separation for zebrafish.

Getting the input data

Net AXT alignments from UCSC

Download from:

https://hgdownload.soe.ucsc.edu/goldenPath/<focal_assembly>/vs<Outgroup>/

Example for human vs. chimp:

wget https://hgdownload.soe.ucsc.edu/goldenPath/hg38/vsPanTro6/hg38.panTro6.net.axt.gz

Chromosome lengths

From a FASTA index:

samtools faidx reference.fa
cut -f1,2 reference.fa.fai > chromoLens.txt

From UCSC MySQL:

mysql --user=genome --host=genome-mysql.soe.ucsc.edu -A \
  -e "SELECT chrom, size FROM chromInfo" hg38 > chromoLens.txt

Tips for outgroup selection

More inner species is better

Even 2 inner species is a major improvement over 1. With 1 inner species, a single alignment error or lineage-specific substitution produces a wrong call. With 2+, the majority vote provides robustness.

  1 inner species:   accuracy ≈ alignment quality
  2 inner species:   accuracy ≈ max(alignment quality)
  3+ inner species:  accuracy ≈ consensus of multiple independent signals

The outer outgroup must be clearly outside the inner clade

If the outer outgroup is too closely related to the inner species, ILS can affect both tiers together, producing false high-confidence calls:

  BAD: outer is too close to inner

       ┌── Focal
    ┌──┤
    │  └── Inner 1             ILS can affect all three
  ──┤
    └──── Outer (barely        species → false agreement
          more distant)

  GOOD: outer is clearly distant

       ┌── Focal
    ┌──┤
    │  └── Inner 1
  ──┤
    │
    │
    └────────── Outer (deep   ILS between tiers is
                divergence)    negligible

Stringency vs. coverage tradeoff

Increasing min_inner_freq requires more species to agree:

Setting	Coverage	Accuracy
`min_inner_freq=1`	Highest	Lower (but still >99%)
`min_inner_freq=2` (with 3 inner)	Moderate	High
`min_inner_freq=3` (with 3 inner)	Lowest	Highest

For most demographic analyses, min_inner_freq=1 is fine — the SFS shape is robust to rare misassignments.

Sex chromosomes and other special cases

chrY has very poor alignment coverage due to massive repetitive content. Expect >80% N (missing).
chrX may have lower coverage than autosomes, especially in regions of reduced synteny.
Mitochondrial genomes are not handled by standard UCSC pairwise alignments. For mtDNA polarization, consider using a multiple sequence alignment approach instead.

Species catalogue

The tables below list 100 commonly studied species with suggested outgroup configurations for ancestral allele polarization. Each entry shows:

Assembly — the UCSC genome browser identifier (where one exists).
Suggested inner outgroups — closely related species for the inner tier.
Suggested outer outgroup — a more distant species for independent confirmation.
Divergence — approximate divergence times (inner / outer) in millions of years ago (Mya).

Tip

These are starting-point suggestions. Always verify that pairwise net AXT alignments exist for your chosen focal assembly at https://hgdownload.soe.ucsc.edu/goldenPath/<assembly>/. If a pre-computed alignment is not available, you can generate your own with lastz and the UCSC axtChain/chainNet pipeline.

Important

Disclaimer — verify divergence times independently. The divergence times and outgroup configurations in this catalogue are approximate, drawn from molecular clock estimates in the published literature. They are provided as a convenience and may contain errors. Molecular divergence estimates vary substantially between studies depending on calibration fossils, clock models, and gene sets used. Before relying on any entry for your analysis, please cross-check the divergence times against an authoritative source such as TimeTree or the primary literature for your taxon. The authors of ancify make no guarantee of the accuracy of these values and accept no responsibility for downstream results based on incorrect tier assignments.

Primates

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
1	Homo sapiens	Human	hg38	Chimp, bonobo, gorilla	Macaque	6–9 / 25 Mya
2	Pan troglodytes	Chimpanzee	panTro6	Bonobo, human	Macaque	2–6 / 25 Mya
3	Pan paniscus	Bonobo	panPan3	Chimp, human	Macaque	2–6 / 25 Mya
4	Gorilla gorilla	Gorilla	gorGor6	Human, chimp	Macaque	9 / 25 Mya
5	Pongo abelii	Orangutan	ponAbe3	Human, chimp, gorilla	Macaque	13 / 25 Mya
6	Nomascus leucogenys	Gibbon	nomLeu3	Human, macaque	Marmoset	18–25 / 40 Mya
7	Macaca mulatta	Rhesus macaque	rheMac10	Crab-eating macaque, baboon	Human	3–8 / 25 Mya
8	Macaca fascicularis	Crab-eating macaque	macFas5	Rhesus macaque, baboon	Human	3–8 / 25 Mya
9	Papio anubis	Baboon	papAnu4	Rhesus macaque, green monkey	Human	5–8 / 25 Mya
10	Chlorocebus sabaeus	Green monkey	chlSab2	Rhesus macaque, baboon	Human	8 / 25 Mya
11	Nasalis larvatus	Proboscis monkey	nasLar1	Green monkey, rhesus macaque	Human	10 / 25 Mya
12	Callithrix jacchus	Marmoset	calJac4	Squirrel monkey	Macaque	15 / 40 Mya
13	Saimiri boliviensis	Squirrel monkey	saiBol1	Marmoset	Macaque	15 / 40 Mya
14	Carlito syrichta	Tarsier	tarSyr2	Human, macaque	Mouse lemur, bushbaby	58 / 64 Mya
15	Microcebus murinus	Mouse lemur	micMur2	Bushbaby	Marmoset	58 / 70 Mya
16	Otolemur garnettii	Bushbaby	otoGar3	Mouse lemur	Marmoset	58 / 70 Mya

Rodents & Lagomorphs

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
17	Mus musculus	Mouse	mm39	Rat	Rabbit	12 / 90 Mya
18	Rattus norvegicus	Rat	rn7	Mouse	Rabbit	12 / 90 Mya
19	Cricetulus griseus	Chinese hamster	criGriChoV2	Mouse, rat	Rabbit	20 / 90 Mya
20	Cavia porcellus	Guinea pig	cavPor3	Chinchilla	Mouse	35 / 70 Mya
21	Chinchilla lanigera	Chinchilla	chiLan1	Guinea pig	Mouse	35 / 70 Mya
22	Heterocephalus glaber	Naked mole-rat	hetGla2	Guinea pig	Mouse	35 / 70 Mya
23	Ictidomys tridecemlineatus	Squirrel	speTri2	Mouse, rat	Rabbit	50 / 90 Mya
24	Dipodomys ordii	Kangaroo rat	dipOrd1	Mouse, rat	Rabbit	50 / 90 Mya
25	Oryctolagus cuniculus	Rabbit	oryCun2	Pika	Mouse	30 / 90 Mya
26	Ochotona princeps	Pika	ochPri3	Rabbit	Mouse	30 / 90 Mya

Carnivores

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
27	Canis lupus familiaris	Dog	canFam6	Ferret, cat	Horse	50–55 / 80 Mya
28	Felis catus	Cat	felCat9	Ferret, dog	Horse	50–55 / 80 Mya
29	Mustela putorius furo	Ferret	musFur1	Dog, cat	Horse	50–55 / 80 Mya
30	Ailuropoda melanoleuca	Giant panda	ailMel1	Dog, ferret	Horse	50 / 80 Mya
31	Neomonachus schauinslandi	Hawaiian monk seal	neoSch1	Dog, ferret	Horse	50 / 80 Mya

Ungulates & Cetaceans

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
32	Bos taurus	Cow	bosTau9	Sheep	Pig	20 / 60 Mya
33	Ovis aries	Sheep	oviAri4	Cow	Pig	20 / 60 Mya
34	Sus scrofa	Pig	susScr11	Cow, dolphin	Horse	60 / 80 Mya
35	Tursiops truncatus	Dolphin	turTru2	Cow	Horse	55 / 80 Mya
36	Balaenoptera acutorostrata	Minke whale	balAcu1	Dolphin, cow	Horse	35–55 / 80 Mya
37	Equus caballus	Horse	equCab3	White rhinoceros	Dog	55 / 80 Mya
38	Ceratotherium simum	White rhinoceros	cerSim1	Horse	Dog	55 / 80 Mya
39	Vicugna pacos	Alpaca	vicPac2	Pig, cow	Horse	55–60 / 80 Mya

Bats

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
40	Myotis lucifugus	Microbat	myoLuc2	Megabat	Dog	55 / 80 Mya
41	Pteropus vampyrus	Megabat	pteVam1	Microbat	Dog	55 / 80 Mya

Insectivores & other Laurasiatheria

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
42	Erinaceus europaeus	Hedgehog	eriEur2	Shrew	Dog	75 / 90 Mya
43	Sorex araneus	Shrew	sorAra2	Hedgehog	Dog	75 / 90 Mya
44	Manis pentadactyla	Chinese pangolin	manPen1	Dog, cat	Horse	75 / 85 Mya

Afrotheria & Xenarthra

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
45	Loxodonta africana	African elephant	loxAfr3	Manatee, rock hyrax	Armadillo	60–65 / 100 Mya
46	Trichechus manatus	Manatee	triMan1	Elephant	Armadillo	60 / 100 Mya
47	Procavia capensis	Rock hyrax	proCap1	Elephant, manatee	Armadillo	60 / 100 Mya
48	Echinops telfairi	Tenrec	echTel2	Elephant	Armadillo	75 / 100 Mya
49	Dasypus novemcinctus	Armadillo	dasNov3	Sloth	Elephant	65 / 100 Mya
50	Choloepus hoffmanni	Sloth	choHof1	Armadillo	Elephant	65 / 100 Mya

Marsupials & Monotremes

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
51	Monodelphis domestica	Opossum	monDom5	Tasmanian devil, wallaby	Platypus	69 / 190 Mya
52	Sarcophilus harrisii	Tasmanian devil	sarHar1	Wallaby	Opossum	62 / 69 Mya
53	Macropus eugenii	Wallaby	macEug2	Tasmanian devil	Opossum	62 / 69 Mya
54	Ornithorhynchus anatinus	Platypus	ornAna2	Opossum	Chicken	190 / 320 Mya

Birds

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
55	Gallus gallus	Chicken	galGal6	Turkey	Zebra finch	30 / 80 Mya
56	Meleagris gallopavo	Turkey	melGal5	Chicken	Zebra finch	30 / 80 Mya
57	Anas platyrhynchos	Mallard duck	anaPla1	Chicken, turkey	Zebra finch	55–70 / 80 Mya
58	Taeniopygia guttata	Zebra finch	taeGut2	Medium ground finch, flycatcher	Chicken	15–45 / 80 Mya
59	Geospiza fortis	Medium ground finch	geoFor1	Zebra finch	Chicken	15 / 80 Mya
60	Ficedula albicollis	Collared flycatcher	ficAlb2	Zebra finch	Chicken	45 / 80 Mya
61	Melopsittacus undulatus	Budgerigar	melUnd1	Falcon, eagle	Chicken	50–60 / 80 Mya
62	Falco peregrinus	Peregrine falcon	falPer1	Budgerigar, eagle	Chicken	50–55 / 80 Mya
63	Aquila chrysaetos	Golden eagle	aquChr2	Falcon, budgerigar	Chicken	50–55 / 80 Mya
64	Columba livia	Rock pigeon	colLiv1	Flycatcher, zebra finch	Chicken	70 / 80 Mya
65	Apteryix mantelli	Brown kiwi	aptMan1	Chicken, turkey	Zebra finch	60–70 / 80 Mya

Reptiles & Amphibians

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
66	Anolis carolinensis	Green anole	anoCar2	Garter snake	Painted turtle	150 / 275 Mya
67	Chrysemys picta	Painted turtle	chrPic2	Softshell turtle	Alligator	70 / 255 Mya
68	Pelodiscus sinensis	Chinese softshell turtle	pelSin2	Painted turtle	Alligator	70 / 255 Mya
69	Alligator mississippiensis	American alligator	allMis1	Painted turtle, softshell turtle	Green anole	255 / 275 Mya
70	Thamnophis sirtalis	Garter snake	thaSir1	Green anole	Painted turtle	150 / 275 Mya
71	Xenopus tropicalis	Western clawed frog	xenTro10	X. laevis	Coelacanth	50 / 370 Mya
72	Xenopus laevis	African clawed frog	xenLae2	X. tropicalis	Coelacanth	50 / 370 Mya
73	Rana temporaria	Common frog	—	Xenopus spp.	Coelacanth	200 / 370 Mya

Fish

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
74	Danio rerio	Zebrafish	danRer11	Medaka, stickleback	Fugu	110–150 / 180 Mya
75	Oryzias latipes	Medaka	oryLat2	Stickleback, Nile tilapia	Zebrafish	70–100 / 150 Mya
76	Gasterosteus aculeatus	Stickleback	gasAcu1	Medaka, Nile tilapia	Zebrafish	70–100 / 150 Mya
77	Takifugu rubripes	Fugu	fr3	Tetraodon	Stickleback	30 / 100 Mya
78	Tetraodon nigroviridis	Tetraodon	tetNig2	Fugu	Stickleback	30 / 100 Mya
79	Oreochromis niloticus	Nile tilapia	oreNil3	Stickleback, medaka	Zebrafish	70–100 / 150 Mya
80	Gadus morhua	Atlantic cod	gadMor1	Stickleback, medaka	Zebrafish	100–110 / 150 Mya
81	Salmo salar	Atlantic salmon	—	Rainbow trout	Zebrafish	25 / 200 Mya
82	Oncorhynchus mykiss	Rainbow trout	—	Atlantic salmon	Zebrafish	25 / 200 Mya
83	Latimeria chalumnae	Coelacanth	latCha1	Xenopus	Spotted gar	410 / 440 Mya
84	Lepisosteus oculatus	Spotted gar	lepOcu1	Zebrafish	Coelacanth	340 / 440 Mya
85	Petromyzon marinus	Sea lamprey	petMar3	Elephant shark	Lancelet	500 / 550 Mya
86	Callorhinchus milii	Elephant shark	calMil1	Zebrafish	Lamprey	450 / 500 Mya

Insects — Drosophila & relatives

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
87	D. melanogaster	Fruit fly	dm6	D. simulans, D. sechellia	D. yakuba	2.5 / 6 Mya
88	D. simulans	—	droSim2	D. sechellia, D. melanogaster	D. yakuba	0.5–2.5 / 6 Mya
89	D. sechellia	—	droSec1	D. simulans, D. melanogaster	D. yakuba	0.5–2.5 / 6 Mya
90	D. yakuba	—	droYak3	D. erecta	D. melanogaster	6 / 12 Mya
91	D. erecta	—	droEre2	D. yakuba	D. melanogaster	6 / 12 Mya
92	D. ananassae	—	droAna3	D. melanogaster	D. pseudoobscura	25 / 40 Mya
93	D. pseudoobscura	—	dp4	D. persimilis	D. melanogaster	2 / 25 Mya
94	D. virilis	—	droVir3	D. mojavensis, D. grimshawi	D. melanogaster	20 / 40 Mya

Insects — other orders

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
95	Anopheles gambiae	Malaria mosquito	anoGam3	Aedes aegypti	D. melanogaster	150 / 250 Mya
96	Apis mellifera	Honeybee	apiMel4	Bombus spp.	Nasonia (jewel wasp)	70 / 150 Mya
97	Tribolium castaneum	Red flour beetle	triCas2	D. melanogaster	Honeybee	250 / 300 Mya
98	Bombyx mori	Silkworm	—	Manduca sexta (tobacco hornworm)	D. melanogaster	100 / 250 Mya

Worms & other invertebrates

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
99	C. elegans	Nematode	ce11	C. briggsae, C. remanei	C. japonica	80–100 / 100–200 Mya
100	C. briggsae	—	cb4	C. remanei, C. elegans	C. japonica	80–100 / 100–200 Mya
101	Strongylocentrotus purpuratus	Purple sea urchin	strPur2	Lancelet	C. elegans	520 / 650 Mya
102	Branchiostoma floridae	Lancelet	braFlo1	Sea urchin	Lamprey	520 / 550 Mya
103	Ciona intestinalis	Sea squirt	ci3	Lancelet	Lamprey	520 / 550 Mya
104	Aplysia californica	Sea hare	aplCal1	C. elegans	Sea urchin	600 / 650 Mya

Plants

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
105	Arabidopsis thaliana	Thale cress	araTha1†	A. lyrata	Brassica rapa	5 / 20 Mya
106	Brassica rapa	Turnip / Chinese cabbage	braRap1†	B. oleracea	Arabidopsis thaliana	4 / 20 Mya
107	Oryza sativa	Rice	—	O. rufipogon, O. glaberrima	Brachypodium distachyon	1–2 / 50 Mya
108	Zea mays	Maize	—	Sorghum bicolor	Oryza sativa	12 / 50 Mya
109	Solanum lycopersicum	Tomato	—	S. tuberosum (potato)	Coffea canephora	8 / 80 Mya
110	Glycine max	Soybean	—	Phaseolus vulgaris (common bean)	Arabidopsis thaliana	20 / 100 Mya
111	Vitis vinifera	Grape	—	Coffea canephora	Arabidopsis thaliana	80 / 110 Mya
112	Populus trichocarpa	Poplar	—	Salix spp. (willow)	Arabidopsis thaliana	8 / 100 Mya

Fungi

#	Focal species	Common name	Assembly	Suggested inner outgroups	Suggested outer outgroup	Div. (inner / outer)
113	Saccharomyces cerevisiae	Baker’s yeast	sacCer3	S. paradoxus	S. pombe	5 / 600 Mya
114	Schizosaccharomyces pombe	Fission yeast	—	S. japonicus	Neurospora crassa	150 / 500 Mya
115	Neurospora crassa	Red bread mold	—	N. tetrasperma	S. cerevisiae	30 / 500 Mya

Note

Assemblies marked with † are not part of the core UCSC Genome Browser but may be available through UCSC’s GenArk or via Ensembl/Phytozome. Entries with — in the assembly column have public genome assemblies but typically no UCSC pairwise alignments; you will need to generate AXT alignments yourself (see below).

Warning

Entries with poor inner/outer divergence ratios. The guidelines above recommend the outer outgroup diverge ≥2–3× further than the inner outgroup. Several entries in the catalogue have much lower ratios due to the phylogenetic structure of the group. Use these configurations with caution — the outer tier provides limited additional confirmation:

#14 Tarsier (58 / 64 Mya, ratio 1.1×). Tarsiers are haplorhines, sister to anthropoids. The haplorhine–strepsirrhine split (64 Mya) barely exceeds the tarsier–anthropoid split (58 Mya). Consider using a non-primate outgroup (e.g. mouse, ~85 Mya) for a better outer tier.
#52–53 Tasmanian devil & Wallaby (62 / 69 Mya, ratio 1.1×). Australidelphian inter-ordinal divergences are close in time to the Didelphimorphia–Australidelphia split. Consider platypus (~190 Mya) as the outer outgroup for a ratio of ~3×.
#69 Alligator (255 / 275 Mya, ratio 1.08×). Turtles and lepidosaurs are nearly equidistant from crocodilians in deep time. Consider using a bird (e.g. chicken, ~240 Mya) as an inner outgroup to improve tiering.
#83 Coelacanth (410 / 440 Mya, ratio 1.07×). The Sarcopterygii–Actinopterygii split is only slightly deeper than the coelacanth–tetrapod split. Consider lamprey (~500 Mya) as an alternative outer outgroup.
#99–100 Caenorhabditis — divergence times in nematodes are poorly constrained due to the absence of a reliable fossil record. Published molecular clock estimates range widely (some studies give 18–30 Mya, others 80–110 Mya for the C. elegans–C. briggsae split). The values shown (80–100 Mya) reflect the most commonly cited molecular estimates.

Generating your own alignments

For species not covered by UCSC’s pre-computed pairwise alignments, you can produce net.axt.gz files from any pair of genome assemblies. This section walks through the full process using Brassica rapa as a concrete example.

Prerequisites

You need two command-line toolkits:

Tool	Purpose	Install
lastz	Pairwise genome alignment	`conda install -c bioconda lastz` or build from source
UCSC Kent utilities	Chaining, netting, format conversion	Download pre-compiled binaries for your platform

The specific Kent utilities you need are: faToTwoBit, twoBitInfo, axtChain, chainSort, chainNet, netToAxt, and axtSort.

# Example: download Kent tools on Linux x86_64
KENT=https://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64
for tool in faToTwoBit twoBitInfo axtChain chainSort chainNet netToAxt axtSort; do
    wget -q "$KENT/$tool" -O "$tool" && chmod +x "$tool"
done
export PATH="$PWD:$PATH"

Step 1: Obtain genome assemblies

Download FASTA files for your focal species and each outgroup. For Brassica rapa the genomes are available from Ensembl Plants (or NCBI/Phytozome):

# Focal: Brassica rapa v1.0
wget https://ftp.ensemblgenomes.org/pub/plants/release-57/fasta/brassica_rapa/dna/Brassica_rapa.Brapa_1.0.dna.toplevel.fa.gz
gunzip Brassica_rapa.Brapa_1.0.dna.toplevel.fa.gz
mv Brassica_rapa.Brapa_1.0.dna.toplevel.fa braRap1.fa

# Inner outgroup: Brassica oleracea (same genus, ~4 Mya)
wget https://ftp.ensemblgenomes.org/pub/plants/release-57/fasta/brassica_oleracea/dna/Brassica_oleracea.BOL.dna.toplevel.fa.gz
gunzip Brassica_oleracea.BOL.dna.toplevel.fa.gz
mv Brassica_oleracea.BOL.dna.toplevel.fa braOle1.fa

# Outer outgroup: Arabidopsis thaliana (~20 Mya, same family Brassicaceae)
wget https://ftp.ensemblgenomes.org/pub/plants/release-57/fasta/arabidopsis_thaliana/dna/Arabidopsis_thaliana.TAIR10.dna.toplevel.fa.gz
gunzip Arabidopsis_thaliana.TAIR10.dna.toplevel.fa.gz
mv Arabidopsis_thaliana.TAIR10.dna.toplevel.fa araTha1.fa

Step 2: Convert to 2bit format

lastz and the Kent chaining tools require .2bit format:

faToTwoBit braRap1.fa braRap1.2bit
faToTwoBit braOle1.fa braOle1.2bit
faToTwoBit araTha1.fa araTha1.2bit

# Generate chromosome sizes (needed for chaining/netting)
twoBitInfo braRap1.2bit braRap1.chrom.sizes
twoBitInfo braOle1.2bit braOle1.chrom.sizes
twoBitInfo araTha1.2bit araTha1.chrom.sizes

You also need the ancify chromosome lengths file (tab-separated name + length):

cp braRap1.chrom.sizes braRap1.chromLens.txt

Step 3: Run lastz pairwise alignment

Run lastz once for each outgroup. The target is always your focal species:

# B. rapa vs B. oleracea (inner outgroup)
lastz braRap1.2bit braOle1.2bit \
    --format=axt \
    --ambiguous=iupac \
    > braRap1_braOle1_raw.axt

# B. rapa vs A. thaliana (outer outgroup)
lastz braRap1.2bit araTha1.2bit \
    --format=axt \
    --ambiguous=iupac \
    > braRap1_araTha1_raw.axt

Tip

For large genomes, lastz can take many hours. Speed it up with --step=20 --seed=match12 for a coarser but faster initial search, or split chromosomes into separate jobs and run in parallel. See the lastz documentation for all tuning flags.

Step 4: Chain and net the alignment

Chaining groups co-linear alignment blocks; netting selects the single best chain at each target position (removing tandem-duplication noise):

# --- B. rapa vs B. oleracea ---
axtChain braRap1_braOle1_raw.axt braRap1.2bit braOle1.2bit braOle1.chain
chainSort braOle1.chain braOle1.sorted.chain
chainNet braOle1.sorted.chain braRap1.chrom.sizes braOle1.chrom.sizes \
    braOle1_target.net braOle1_query.net
netToAxt braOle1_target.net braOle1.sorted.chain braRap1.2bit braOle1.2bit stdout \
    | axtSort stdin braRap1.braOleracea.net.axt

# --- B. rapa vs A. thaliana ---
axtChain braRap1_araTha1_raw.axt braRap1.2bit araTha1.2bit araTha1.chain
chainSort araTha1.chain araTha1.sorted.chain
chainNet araTha1.sorted.chain braRap1.chrom.sizes araTha1.chrom.sizes \
    araTha1_target.net araTha1_query.net
netToAxt araTha1_target.net araTha1.sorted.chain braRap1.2bit araTha1.2bit stdout \
    | axtSort stdin braRap1.araTha1.net.axt

Step 5: Compress and verify

gzip braRap1.braOleracea.net.axt
gzip braRap1.araTha1.net.axt

# Quick sanity check: each file should contain alignment blocks
zcat braRap1.braOleracea.net.axt.gz | head -20

Step 6: Run ancify

The resulting files plug straight into an ancify config:

focal_species: brassica_rapa
chromosome_lengths: braRap1.chromLens.txt

outgroups:
  inner:
    - name: brassica_oleracea
      alignment: braRap1.braOleracea.net.axt.gz
  outer:
    - name: arabidopsis_thaliana
      alignment: braRap1.araTha1.net.axt.gz

output_dir: ./brassica_rapa_ancestral
num_cpus: 4

ancify run -c brassica_rapa_config.yaml

The repo also includes a ready-made runner script at scripts/examples/brassica_rapa/run.sh (single-chromosome test on A01).

Quick-reference: generic pipeline

For any species pair, the minimal pipeline is:

# 1. Convert FASTA to 2bit
faToTwoBit target.fa target.2bit
faToTwoBit query.fa query.2bit
twoBitInfo target.2bit target.chrom.sizes
twoBitInfo query.2bit query.chrom.sizes

# 2. Align
lastz target.2bit query.2bit \
    --format=axt --ambiguous=iupac \
    > raw.axt

# 3. Chain and net
axtChain raw.axt target.2bit query.2bit chain.txt
chainSort chain.txt sorted.chain
chainNet sorted.chain target.chrom.sizes query.chrom.sizes target.net query.net
netToAxt target.net sorted.chain target.2bit query.2bit stdout \
    | axtSort stdin net.axt

# 4. Compress
gzip net.axt

Notes on plant genomes

Whole-genome duplications are common in plants (Brassica underwent a lineage-specific triplication). The netting step handles this by picking the single best chain per target position, but expect lower alignment coverage and more fragmented blocks than mammalian comparisons.
Chromosome naming varies widely (A01-A10 in B. rapa, Chr1-Chr5 in Arabidopsis). ancify does not assume a chr prefix — any naming works. Omit the chromosomes key in your config to process every entry in the lengths file.
Alignment coverage for the outer outgroup (Arabidopsis, ~20 Mya) will be substantially lower than the inner outgroup (B. oleracea, ~4 Mya). This is normal and means more positions will receive low-confidence (lowercase) calls rather than high-confidence ones.
If the Ensembl FASTA contains scaffold/contig names you do not want, filter your chromosome lengths file first:
```
grep -E '^A[0-9]+' braRap1.chrom.sizes > braRap1.chromLens.txt
```

For more details see the lastz documentation and the UCSC Kent utilities.