Indexed FASTA six-frame translation¶
The visible hg38 reference sequence is translated in all three reading frames on both strands and kept aligned with a base-level reference track.
Data use and provenance
The visualization uses a mirrored, indexed copy of UCSC’s hg38 / GRCh38 reference FASTA from goldenPath/hg38/bigZips/latest/hg38.fa.gz. UCSC states that its downloadable data files and database tables are freely available for public and commercial use, subject to any upstream restrictions noted for the original assembly data.
What to notice¶
The reference sequence and all six reading frames stay aligned while panning. Start codons are green, stop codons are red, and arrow direction distinguishes forward and reverse translations. Frame assignment remains stable across lazy data reloads.
Python implementation¶
The chart flattens sequence chunks into bases, constructs overlapping codons with window transforms, and maps them through lookup tables. A named template is imported for each strand and composed with the reference track.
See the official GenomeSpy example for the codon construction and frame calculations.
Code¶
"""Indexed FASTA six-frame translation.
The visible hg38 reference sequence is translated in all three reading frames
on both strands and kept aligned with a base-level reference track.
"""
import genome_spy as gs
# Choose the reading direction for each translation track.
strand = gs.param("strand", value="forward")
WIDTH = gs.Expression("width")
# Match each DNA base to its partner on the opposite strand.
COMPLEMENTS = [
{"base": base, "complement": complement}
for base, complement in zip("ACGTN", "TGCAN", strict=True)
]
# Translate each three-letter codon using the standard genetic code.
AMINO_ACIDS = {
"TTT": "F",
"TTC": "F",
"TTA": "L",
"TTG": "L",
"TCT": "S",
"TCC": "S",
"TCA": "S",
"TCG": "S",
"TAT": "Y",
"TAC": "Y",
"TAA": "STOP",
"TAG": "STOP",
"TGT": "C",
"TGC": "C",
"TGA": "STOP",
"TGG": "W",
"CTT": "L",
"CTC": "L",
"CTA": "L",
"CTG": "L",
"CCT": "P",
"CCC": "P",
"CCA": "P",
"CCG": "P",
"CAT": "H",
"CAC": "H",
"CAA": "Q",
"CAG": "Q",
"CGT": "R",
"CGC": "R",
"CGA": "R",
"CGG": "R",
"ATT": "I",
"ATC": "I",
"ATA": "I",
"ATG": "M",
"ACT": "T",
"ACC": "T",
"ACA": "T",
"ACG": "T",
"AAT": "N",
"AAC": "N",
"AAA": "K",
"AAG": "K",
"AGT": "S",
"AGC": "S",
"AGA": "R",
"AGG": "R",
"GTT": "V",
"GTC": "V",
"GTA": "V",
"GTG": "V",
"GCT": "A",
"GCC": "A",
"GCA": "A",
"GCG": "A",
"GAT": "D",
"GAC": "D",
"GAA": "E",
"GAG": "E",
"GGT": "G",
"GGC": "G",
"GGA": "G",
"GGG": "G",
}
# Give start and stop codons their own colors.
GENETIC_CODE = [
{
"codon": codon,
"aminoAcid": amino_acid,
"kind": (
"start" if codon == "ATG" else "stop" if amino_acid == "STOP" else "other"
),
}
for codon, amino_acid in AMINO_ACIDS.items()
]
base_colors = gs.Scale(
domain=["A", "C", "T", "G", "a", "c", "t", "g", "N"],
range=[
"#7BD56C",
"#FF9B9B",
"#86BBF1",
"#FFC56C",
"#7BD56C",
"#FF9B9B",
"#86BBF1",
"#FFC56C",
"#E0E0E0",
],
)
# Draw the reference DNA as colored tiles with letters on top.
reference_background = (
gs.Chart().mark_rect(tooltip=None).properties(name="reference-base-background")
)
reference_labels = (
gs.Chart()
.mark_text(
size=13,
fitToBand=True,
paddingX=1.5,
paddingY=1,
opacity=0.7,
flushX=False,
tooltip=None,
)
.encode(color=gs.value("black"), text=gs.Text("base"))
.properties(name="reference-base-labels")
)
reference = (
(reference_background + reference_labels)
.properties(name="reference-bases", height=20)
.encode(
x=gs.Locus("chrom", "pos"),
color=gs.Color("base:N").scale(base_colors).legend(None),
)
)
# Draw one arrow per codon, pointing in its reading direction.
amino_acids = (
gs.Chart()
.mark_arrow(
style="arrow-block-notch",
stroke="#C0C0C0",
headAngle=65,
strokeWidth=gs.expr(
1.0
- gs.expr.smoothstep(
0.2,
1,
gs.expr.span(gs.expr.domain("x")) / WIDTH,
)
),
tooltip=None,
)
.encode(
direction=gs.value(strand),
color=gs.Color("kind:N")
.scale(
domain=["start", "stop", "other", "?"],
range=["#40B050", "#F06060", "#F8F8F8", "#E0E0E0"],
)
.legend(None),
)
.properties(name="amino-acids")
)
# Label each codon with its translated amino acid.
amino_acid_labels = (
gs.Chart()
.mark_text(size=12, paddingX=1.5, tooltip=None)
.encode(color=gs.value("black"), text=gs.Text("aminoAcid"))
.properties(name="amino-acid-labels")
)
# Build one translation track that works in either reading direction.
translation_template = (
(amino_acids + amino_acid_labels)
.add_params(strand)
.transform_formula(
expr=gs.expr.if_(
strand == "reverse",
gs.datum.complement2 + gs.datum.complement1 + gs.datum.complement,
gs.datum.base + gs.datum.base1 + gs.datum.base2,
),
as_="codon",
)
.transform_lookup(from_={"name": "geneticCode"}, key="codon", default="?")
.transform_formula(expr=strand + " " + (gs.datum.pos % 3), as_="lane")
)
# Reuse the track for both strands, with three reading frames on each.
translation = (
(
gs.import_view(
template="amino-acid-translation",
name="forward-translation",
params={"strand": "forward"},
)
+ gs.import_view(
template="amino-acid-translation",
name="reverse-translation",
params={"strand": "reverse"},
)
)
.properties(
name="translation",
height=gs.step(17),
templates={"amino-acid-translation": translation_template},
)
.with_view(stroke="#c0c0c0")
.encode(
y=gs.Y("lane:O")
.scale(
domain=[
"forward 2",
"forward 1",
"forward 0",
"reverse 0",
"reverse 1",
"reverse 2",
]
)
.axis(title=None),
x=gs.Locus("chrom", "pos", band=0),
x2=gs.Locus("chrom", "end", band=0),
)
.transform_formula(expr=gs.expr.upper(gs.datum.base), as_="base")
.transform_lookup(
from_={"name": "nucleotideComplements"},
key="base",
values=["complement"],
default="N",
)
# Gather the next two bases to form each three-letter codon.
.transform_window(
sort=gs.compare("pos"),
ops=["lead", "lead", "lead", "lead"],
fields=["base", "base", "complement", "complement"],
params=[1, 2, 1, 2],
as_=["base1", "base2", "complement1", "complement2"],
)
.transform_filter(
gs.expr.isValid(gs.datum.base2) & gs.expr.isValid(gs.datum.complement2)
)
.transform_formula(expr=gs.datum.pos + 3, as_="end")
)
# Load the visible DNA and put its six translations directly below it.
chart = (
(reference & translation)
.properties(
assembly="hg38",
name="indexed-fasta-six-frame-translation",
description=(
"The visible hg38 reference is translated in three forward and "
"three reverse reading frames."
),
scales=gs.scales(
x=gs.Scale(
domain=[
{"chrom": "chr7", "pos": 20395929},
{"chrom": "chr7", "pos": 20395976},
]
)
),
datasets={
"nucleotideComplements": COMPLEMENTS,
"geneticCode": GENETIC_CODE,
},
data=gs.lazy.indexed_fasta("https://data.genomespy.app/genomes/hg38/hg38.fa"),
spacing=5,
)
# Give each base its own row and genomic position.
.transform_flatten_sequence(field="sequence", as_=["rawPos", "base"])
.transform_formula(expr=gs.datum.start + gs.datum.rawPos, as_="pos")
.resolve_axis(x="shared")
)