Motif and Pattern Search

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Three kinds of "motif" hide in sequences: a literal pattern (TATA box), an IUPAC consensus (RRRYYCC, the poly-A signal), or a statistical profile (a JASPAR PWM for a TF). Each demands a different tool. This skill covers regex / IUPAC exact search, position weight matrix scanning, and the modern 2026 open databases.

When to use

• Finding a known regulatory element in a sequence (TATA box, Kozak, poly-A).
• Scanning a promoter for a transcription factor binding site.
• Confirming an enzyme recognition site in a designed construct.
• Searching for a protein motif (PROSITE, Pfam) with a regex.

When NOT to use

• De novo motif discovery from ChIP-seq → use MEME / STREME.
• Genome-wide PWM scan → use MOODS, FIMO, or pyMOODS.
• Protein domain detection → use pyhmmer or InterProScan.

Prerequisites

• biopython>=1.83
• For advanced regex: regex package (supports fuzzy matching, IUPAC natively).
• For JASPAR motifs: pyjaspar (modern replacement for Biopython's JASPAR module).
• For genome-wide scans: MOODS (C++) or FIMO (MEME Suite).

Core workflow

1. Decide the motif type: literal, IUPAC, or PWM.
2. For literal/IUPAC: regex is fastest.
3. For PWM: convert to a log-odds matrix, scan with a sliding window.
4. Validate hits biologically (one perfect match in a 10 kb promoter is suspicious; a 7/8 match with a known co-factor is meaningful).

Code patterns

Literal motif (regex)

import re
from Bio import SeqIO

seq = str(next(SeqIO.parse("promoter.fasta", "fasta")).seq)
for m in re.finditer(r"TATAAA", seq):
    print(f"TATA box at {m.start()}")

IUPAC consensus

IUPAC codes are valid regex characters except a few that collide with regex syntax (*, ?, (, )). Use Biopython's IUPAC-to-regex helper:

from Bio.Data.IUPACData import ambiguous_dna_values

def iupac_to_regex(motif: str) -> str:
    """Convert IUPAC DNA to a regex character class."""
    return "".join(f"[{ambiguous_dna_values[c]}]" for c in motif.upper())

pat = re.compile(iupac_to_regex("RRRYYCC"))  # poly-A signal
for m in pat.finditer(seq):
    print(m.start(), m.group())

Reverse-strand search

Many regulatory motifs are on the antisense strand:

def find_on_both_strands(seq: str, motif_regex):
    rc = str(Seq(seq).reverse_complement())
    for strand, s in (("+", seq), ("-", rc)):
        for m in motif_regex.finditer(s):
            print(f"{strand}\t{m.start()}\t{m.group()}")

PROSITE-style protein motif

psp = re.compile(r"G.{1,2}GV[AGST]G[AGILV]KT")  # P-loop NTP-binding
for m in psp.finditer(str(protein.seq)):
    print(m.start(), m.group())

Fuzzy matching (sequencing errors)

regex package supports approximate matching with e<=N for up to N edits:

import regex
for m in regex.finditer(r"(TATAAA){e<=1}", seq):
    print(m.start(), m.group(), m.fuzzy_counts)

Position Weight Matrix (PWM) from a JASPAR-style count matrix

import numpy as np
from Bio import motifs

counts = motifs.CountsMatrix(
    [
        [10,  3,  1,  2],   # A
        [ 2,  8,  1,  3],   # C
        [ 1,  2,  9,  2],   # G
        [ 1,  2,  3,  7],   # T
    ],
    alphabet="ACGT",
)
pwm = counts.normalize(pseudocounts=0.5)
pssm = pwm.log_odds()    # log2 odds vs uniform

Scan a sequence with a PSSM

threshold = 5.0
for pos, score in pssm.search(seq, threshold=threshold, both=True):
    print(f"hit at {pos}, score={score:.2f}")

Load a JASPAR motif (modern, 2026)

import pyjaspar

# pyjaspar 2.x supports JASPAR 2024 releases
motif = pyjaspar.get_motif_by_id("MA0006.1")  # Arnt
pwm = motif.profile_matrix   # 4 x len

Reverse-complement-aware PWM scan (TF binding is double-stranded)

# Biopython's `search(both=True)` already does this
hits = list(pssm.search(seq, threshold=6.0, both=True))

Find all occurrences of restriction sites

from Bio.Restriction import EcoRI, BamHI, HindIII

sites = []
for enz in (EcoRI, BamHI, HindIII):
    for hit in enz.search(seq):
        sites.append((hit, enz))

Common pitfalls

• IUPAC in regex breaks silently. [ACGT] works, but R alone is just a literal R. Always use the Biopython IUPAC-to-regex helper.
• PWM scan without background correction gives wrong scores. Always use log-odds (PWM), not raw frequencies.
• JASPAR 2024 release restructured motif IDs — old MA0006.1 may be MA0006.2. pyjaspar handles aliases.
• TATA box at position 0 is a false positive. It's probably the start of a sequence header; offset by 50+ bp from a TSS.
• Single PWM hit ≠ functional binding site. Combine with chromatin accessibility (ATAC-seq), conservation (phastCons), and co-factor motifs for credible predictions.

Validation

• For known motifs, the hit count is in the expected ballpark (e.g., a TATA box should appear in ~30-50% of vertebrate Pol II promoters, not 100%).
• For a PSSM, scan a known positive sequence first to confirm the threshold.
• Forward- and reverse-strand hits should be roughly equal in a random sequence (motif symmetry test).

Open alternatives

References

• Biopython Bio.motifs: https://biopython.org/docs/latest/api/Bio.motifs.html
• JASPAR 2024: https://jaspar.genereg.net/
• MEME Suite: https://meme-suite.org/meme/
• pyjaspar: https://github.com/asntech/pyjaspar
• Companion: ors-bioinformatics-sequence-seq-objects, ors-bioinformatics-functional-motif-* skills.

Changelog

• 1.0.0 (2026-06-10): Initial adaptation by Pradyumna Jayaram from bio-motif-search (bioSkills-main/sequence-manipulation/motif-search).