Rhodnius prolixus Population Genetics Analysis Pipeline

Evolutionary Genetics Assignment

Overview

This pipeline extracts and analyzes DNA sequences for population structure and genetic differentiation analysis of Rhodnius prolixus populations across Colombia, Brazil, and Venezuela. The analysis follows methods from the reference paper (Nature Scientific Reports, 2025).

Files in this Package

• sequence_extraction_script.py - Main script to extract sequences from NCBI GenBank
• population_genetics_analyzer.py - Basic population genetics analysis script
• requirements.txt - Python package dependencies
• Metadata.csv - Sample metadata with accession numbers
• README.md - This instruction file

Gene Loci Analyzed

Based on your metadata, the following 8 loci will be extracted:

1. 28S - Nuclear ribosomal RNA gene
2. CISP - Nuclear protein-coding gene
3. TRNA - Transfer RNA gene
4. CYTB - Mitochondrial cytochrome b gene
5. UPMETAL - Nuclear protein-coding gene
6. UPCA - Nuclear protein-coding gene
7. PJH - Nuclear protein-coding gene
8. LSM - Nuclear protein-coding gene

Installation & Setup

1. Install Required Software

# Install Python packages
pip install -r requirements.txt

2. Configure NCBI Access

Edit the sequence_extraction_script.py file and replace "[email protected]" with your actual email address (required by NCBI):

extractor = SequenceExtractor(email="[email protected]")

Running the Analysis

Step 1: Extract Sequences from NCBI GenBank

python sequence_extraction_script.py

What this does:

• Reads accession numbers from Metadata.csv
• Downloads sequences from NCBI GenBank for all 8 gene loci
• Organizes sequences by gene type
• Creates mapping files and summary reports

Expected Output:

• sequences/ directory with FASTA files for each gene
• sample_sequence_mapping.csv - Shows which sequences were retrieved per sample
• extraction_summary.txt - Summary statistics
• sequence_extraction.log - Detailed log file

Step 2: Basic Population Analysis

python population_analysis_script.py

What this does:

• Calculates basic genetic diversity statistics
• Groups samples by country and region
• Generates summary visualizations
• Prepares data for advanced analyses

Expected Output:

• population_analysis_summary.txt - Comprehensive analysis summary
• population_analysis_overview.png - Visualization plots

Key Results Expected

Based on the methods in your reference paper, you should obtain:

1. Sequence Statistics (per gene)

Metric	Description
Number of sequences	Total sequences retrieved per locus
Sequence length	Base pairs per aligned locus
Segregating sites (S)	Variable nucleotide positions
Nucleotide diversity (π)	Average pairwise differences
Haplotype diversity (h)	Genetic variation measure

2. Population Structure Results

• Sample distribution: Colombia (~94 samples), Venezuela (~29 samples), Brazil (~6 samples)
• Geographic clustering: Samples grouped by country/state
• Population differentiation: FST values between populations
• Gene flow patterns: Connectivity between regions

3. Files for Advanced Analysis

The extracted sequences can be used for:

• MAFFT alignment (as mentioned in your methods)
• STRUCTURE/ADMIXTURE clustering analysis
• IQ-Tree/PhyML phylogenetic reconstruction
• DnaSP neutrality tests (Tajima's D, Fu & Li's D)

Next Steps for Complete Analysis

After running these scripts, you'll need specialized software for advanced analyses:

1. Multiple Sequence Alignment

# Using MAFFT (online or local installation)
mafft --auto sequences/28S_sequences.fasta > 28S_aligned.fasta

2. Population Structure (STRUCTURE software)

• Input: Concatenated nuclear loci alignment
• Parameters: K=1-20, 100,000 MCMC iterations
• Use STRUCTURE HARVESTER to determine optimal K

3. Phylogenetic Analysis (IQ-Tree)

iqtree -s concatenated_alignment.fasta -bb 1000 -alrt 1000

4. Population Genetics (DnaSP)

• Calculate FST, neutrality tests
• Estimate divergence times
• Analyze gene flow patterns

Expected Key Results Summary

Your analysis should reveal:

1. Population Structure:

   • Primary clustering by country (Colombia, Venezuela, Brazil)
   • Secondary structure by geographic regions within countries
   • Possible isolation-by-distance patterns

2. Genetic Differentiation:

   • Highest FST between Brazil and other countries
   • Moderate differentiation between Colombian regions
   • Gene flow corridors along major river systems

3. Diversity Patterns:

   • Higher diversity in Colombian populations
   • Reduced diversity in peripheral populations
   • Different patterns between nuclear and mitochondrial loci

4. Evolutionary Implications:

   • Recent population expansion
   • Historical bottlenecks in some regions
   • Adaptation to different ecotopes (sylvatic/domestic)

Troubleshooting

Common Issues:

1. NCBI connection errors: Add delays between requests, check internet connection
2. Missing sequences: Some accession numbers may be invalid or restricted
3. Memory issues: Process genes separately if dataset is too large

Error Logs:

Check sequence_extraction.log for detailed error messages and failed accessions.

Citation & Methods Statement

Methods Summary for Paper: "DNA sequences were retrieved from NCBI GenBank using accession numbers for 8 nuclear and mitochondrial loci. Sequences were aligned using MAFFT v7 and analyzed using custom Python scripts based on BioPython. Population structure was assessed using [specify methods used], genetic differentiation calculated via FST estimation, and phylogenetic relationships reconstructed using maximum likelihood in IQ-Tree."

Contact & Support

For questions about this pipeline or evolutionary genetics analysis, consult:

• BioPython documentation: https://biopython.org/
• NCBI E-utilities: https://www.ncbi.nlm.nih.gov/books/NBK25501/
• Population genetics textbooks for theoretical background

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Analysis pipeline for Rhodnius prolixus population genetics - November 2025