Forensic DNA Phenotyping (FDP)

Forensic DNA Phenotyping (FDP) goes beyond identification and enters predictive genomics. Instead of matching DNA profiles (STR-based), FDP analyzes functional regions of DNA that influence observable traits (phenotypes).

Forensic DNA Phenotyping (FDP)

Genotype (DNA) → Biological pathways → Physical traits (Phenotype)

  • Traditional forensics = Who is this?
  • FDP = What might this person look like?

Genetic Basis (Deep Science)

A. SNPs (Single Nucleotide Polymorphisms)

  • FDP mainly relies on SNP markers, not STRs
  • SNP = variation at a single base (A, T, G, C)
  • Example: A → G change affecting pigmentation

 Why SNPs?

  • More stable than STRs
  • Better for degraded DNA
  • Directly linked to functional traits

B. Pigmentation Genetics

Key Genes:

  • OCA2 & HERC2 → Eye color (blue/brown variation)
  • MC1R → Red hair phenotype
  • SLC24A5, SLC45A2 → Skin pigmentation
  • TYR (Tyrosinase) → Melanin production

Mechanism:

  • Melanin types:
    • Eumelanin → Brown/black
    • Pheomelanin → Red/yellow

 Variation in these genes alters melanin production → visible traits

C. Polygenic Nature of Traits

  • Most traits are polygenic (controlled by many genes)
  • FDP uses statistical models combining multiple SNPs

Example:

  • Eye color prediction may use ~6–20 SNPs
  • Skin color may use >30 SNPs

Tracing the DNA

3. Laboratory Workflow (Technical Pipeline)

 Step 1: DNA Extraction

  • Methods: Organic extraction, Chelex, silica-based
  • Works even on:
    • Degraded samples
    • Trace DNA

Step 2: DNA Quantification

  • Using qPCR (Quantitative PCR)
  • Ensures enough DNA for sequencing

Step 3: Library Preparation

  • DNA fragmented + adapters added
  • Target SNP regions amplified

Step 4: Sequencing (NGS)

  • Platforms:
    • Illumina MiSeq
    • Ion Torrent

 Generates millions of reads covering SNP regions

Step 5: Bioinformatics Analysis

  • Raw data → cleaned → aligned to reference genome
  • SNP calling performed
  • Output: genotype (AA, AG, GG)

Step 6: Prediction Modeling

  • Algorithms used:
    • Logistic regression
    • Bayesian models
    • Machine learning

Step 7: Facial Approximation

  • Software converts predictions into:
    • 2D sketches
    • 3D models

BRIC-NIBMG | BRIC National Institute of Biomedical Genomics

Prediction Systems

 HIrisPlex System

  • Predicts eye & hair color
  • Accuracy:
    • Eye color: ~90%
    • Hair color: ~70–80%

 HIrisPlex-S

  • Adds skin color prediction

 SNAPSHOT (Parabon NanoLabs)

  • Generates facial composites

Accuracy & Reliability

Trait Accuracy Level
Eye Color ⭐⭐⭐⭐ (High)
Hair Color ⭐⭐⭐ (Moderate)
Skin Color ⭐⭐⭐⭐ (High)
Face Shape ⭐⭐ (Low–Developing)

Important: FDP gives probabilities, not certainty

Red Hair Genetics: 5 Things You May Not Know - AIM at Melanoma Foundation

Legal & Ethical Dimensions 

 Privacy Concerns

  • DNA reveals sensitive info:
    • Ancestry
    • Disease predisposition

 Risk of Bias

  • Misinterpretation → racial profiling

 Legal Status

  • Allowed (restricted use):
    • Netherlands, Germany, USA (case-based)
  • Not widely accepted in many countries

Integration with Other Forensic Fields

FDP is often combined with:

  • Forensic genealogy (family tree matching)
  • STR profiling
  • Anthropology
  • Facial recognition AI

Planes, Skulls & Suitcases: Solving the Perfect Crime Through 3D Printing | Formlabs

Advanced Research Areas

 Epigenetics in FDP

  • DNA methylation used to predict:
    • Age
    • Lifestyle (smoking, stress)

 AI-based Face Prediction

  • Deep learning models linking DNA → facial structure

 Microbiome Forensics

  • Skin bacteria may help identify individuals

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