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Dengue Virus Genomic Diversity Workflow, Pakistan 2023

DOI Smoke test

Reproducible code and workflow that mirror the analysis in the Journal of Medical Virology article.

Published paper: Jamal Z, Haider SA, Hakim R, Humayun F, Farooq MU, Ammar M, Afrough B, Inamdar L, Salman M, Umair M. Serotype and genomic diversity of dengue virus during the 2023 outbreak in Pakistan reveals the circulation of genotype III of DENV-1 and cosmopolitan genotype of DENV-2. Journal of Medical Virology. 2024. https://doi.org/10.1002/jmv.29727

Abbreviations

Term Meaning
DENV Dengue virus
DENV-1 Dengue virus serotype 1
DENV-2 Dengue virus serotype 2
NGS Next-generation sequencing
SPAdes Genome assembler used for contig generation
BWA Burrows-Wheeler Aligner for read mapping
MAFFT Multiple-sequence alignment program
IQ-TREE Maximum-likelihood phylogenetic tree program
QC Quality control

Workflow overview

This repository documents the DENV-1 and DENV-2 analysis path from metagenomic serum sequencing reads to contig validation, serotype-specific reference selection, masked consensus generation, phylogeny, and protein-level mutation summaries.

flowchart LR
  A["Serum metagenomic FASTQ"] --> B["QC and trimming"]
  B --> C["De novo assembly"]
  C --> D["BLAST contig validation"]
  D --> E["DENV-1/DENV-2 reference selection"]
  E --> F["Reference mapping"]
  F --> G["Masked consensus"]
  G --> H["Whole-genome alignment"]
  H --> I["IQ-TREE phylogeny"]
  G --> J["Polyprotein mutation summary"]
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Program summary

End to end analysis of DENV-1 and DENV-2 using metagenomic NGS. Steps match the study design and are fully scripted to allow reviewers and collaborators to reproduce the results.

  1. Inputs

    • Paired end FASTQ from serum RNA libraries sequenced on Illumina MiSeq 2x150.

  2. Quality control and trimming

    • FastQC for initial QC.
    • Trimmomatic for adapter and quality trimming with the parameters reported in the paper.
    • Picard MarkDuplicates to remove PCR duplicates.

  3. De novo assembly and contig validation

    • Assemble with SPAdes.
    • Contig QC: length, percent Ns, GC, N50.
    • BLAST remote against NCBI nt to identify closest matches.
    • Download selected GenBank sequences for context trees and for mapping references.

  4. Reference based mapping and masked consensus

    • For each sample, choose the best reference from BLAST hits and map with BWA MEM.
    • Sort, mark duplicates, compute per base depth.
    • Mask sites below a coverage threshold to N and call variants with bcftools.
    • Build a masked consensus per sample. The default minimum depth is 10, matching the study.

  5. Phylogeny

    • MAFFT alignment of sample consensus plus context genomes.
    • IQ-TREE with 1000 ultrafast bootstraps.
    • Default substitution model is GTR+G+I to match the manuscript. You can switch to ModelFinder with -m MFP in config if desired.
    • Trees saved in Newick format with logs for review.

  6. Mutation analysis by protein

    • Trim to the single polyprotein ORF using the annotated reference and translate.
    • Compare amino acids against reference DENV-1 polyprotein AAW64436.1 and DENV-2 reference NC_001474.1.
    • Report differences per protein region including E, M, C, NS1 to NS5. Output is a tidy TSV.

  7. Outputs

    • Per sample consensus: results/consensus/<sample>.fa
    • Combined consensus: results/consensus/all_consensus.fasta
    • Alignments: results/aln/wg_alignment.fasta
    • Phylogeny: results/iqtree/wg.treefile and .log
    • Mutation tables: results/mutations/<sample>_aa_diffs.tsv
    • QC, BLAST tables, and reference selection under results/

  8. Repro and compliance

    • MIT LICENSE, CITATION.cff.
    • CI sanity check for plotting.
    • Never commit restricted or clinical data. Set NCBI_EMAIL once for Entrez based steps.

Requirements

  • Python 3.11 or newer
  • Option A: pip and virtualenv
  • Option B: conda or mamba
  • Snakemake for the full pipeline
  • BLAST+ with remote enabled, Entrez Direct

NCBI usage note

Set a contact email once per shell for E-utilities. Optional API key improves rate limits.

export NCBI_EMAIL="you@example.com"
export NCBI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxx"   # optional

Quick verification

python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
python -m pip install -r env/requirements.txt
python analysis/scripts/example_qc_plot.py --in data-example/example_counts.tsv --out results-example/example_plot.png

One command end to end run

export NCBI_EMAIL="you@example.com"
conda env create -f env/environment.yml
conda activate denv-2023-env
snakemake -s workflow/Snakefile -c 4 --printshellcmds

Configuration

Edit config/config.yaml. Example:

pairs:
  - sample: DENV1_001
    r1: data-private/DENV1_001_R1.fastq.gz
    r2: data-private/DENV1_001_R2.fastq.gz
  - sample: DENV2_001
    r1: data-private/DENV2_001_R1.fastq.gz
    r2: data-private/DENV2_001_R2.fastq.gz

reference_preference:
  denv1_ref_accessions:
    - OR936753.1
    - OR936754.1
    - OR936755.1
    - OR936756.1
    - OR936757.1
    - OR936758.1
    - OR936759.1
    - OR936760.1
    - OR936761.1
    - OR936762.1
    - OR936763.1
    - OR936764.1
    - OR936765.1
    - OR936766.1
    - OR936767.1
    - OR936768.1
    - OR936769.1
    - OQ445883.1
    - ON908217.1
    - ON873938.1
    - OP898557.1
    - OP898558.1
    - NC_001477.1

  denv2_ref_accessions:
    - OR936752.1
    - OP811977.1
    - OP811984.1
    - MK543472.1
    - MW186240.1
    - NC_001474.1

context_accessions:
  - OR936753.1
  - OR936754.1
  - OR936755.1
  - OR936756.1
  - OR936757.1
  - OR936758.1
  - OR936759.1
  - OR936760.1
  - OR936761.1
  - OR936762.1
  - OR936763.1
  - OR936764.1
  - OR936765.1
  - OR936766.1
  - OR936767.1
  - OR936768.1
  - OR936769.1
  - OR936752.1
  - ON908217.1
  - ON873938.1
  - OP898557.1
  - OP898558.1
  - MK543472.1
  - MW186240.1

params:
  threads: 4
  trim_adapters: env/TruSeq3-PE.fa
  min_depth_consensus: 10
  min_qual: 20
  iqtree_model_wg: GTR+G+I
  bootstrap: 1000
  max_blast_hits: 50

Apptainer/Singularity container

HPC-friendly Apptainer/Singularity support is available at containers/Apptainer.def. Build it from the repository root:

apptainer build containers/denv-2023-pakistan-analysis.sif containers/Apptainer.def

Use the image on systems where Apptainer or Singularity is preferred over Docker.

Data governance

See DATA_GOVERNANCE.md for public-data, restricted-data, and sample-identifier handling rules.

How to cite

  • Paper: Jamal Z, Haider SA, Hakim R, Humayun F, Farooq MU, Ammar M, Afrough B, Inamdar L, Salman M, Umair M. Serotype and genomic diversity of dengue virus during the 2023 outbreak in Pakistan reveals the circulation of genotype III of DENV-1 and cosmopolitan genotype of DENV-2. Journal of Medical Virology. 2024. 96(6):e29727. https://doi.org/10.1002/jmv.29727
  • Software: Haider SA. Dengue Virus Genomic Diversity Workflow, Pakistan 2023. Version 1.0.0. Zenodo. https://doi.org/10.5281/zenodo.20257749
  • All-version software DOI: https://doi.org/10.5281/zenodo.20257748

References

  • Andrews S. 2010. FastQC. Babraham Bioinformatics.
  • Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114-2120.
  • Broad Institute. Picard Toolkit. GitHub repository.
  • Bankevich A, et al. 2012. SPAdes: a new genome assembly algorithm and its applications to single cell sequencing. J Comput Biol 19:455-477.
  • Li H. 2013. Aligning sequence reads with BWA-MEM. arXiv:1303.3997.
  • Li H, et al. 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078-2079.
  • Danecek P, et al. 2021. Twelve years of SAMtools and BCFtools. GigaScience 10:giab008.
  • Katoh K, Standley DM. 2013. MAFFT multiple sequence alignment software version 7. Mol Biol Evol 30:772-780.
  • Minh BQ, et al. 2020. IQ-TREE 2: new models and efficient methods for phylogenetic inference. Mol Biol Evol 37:1530-1534.
  • Larkin MA, et al. 2007. Clustal W and Clustal X version 2.0. Bioinformatics 23:2947-2948.
  • Shen W, Xiong J. 2016. SeqKit: a cross platform toolkit for FASTA and FASTQ. PLoS One 11:e0163962.
  • Camacho C, et al. 2009. BLAST+: architecture and applications. BMC Bioinformatics 10:421.
  • Kans J. Entrez Programming Utilities Help. NCBI.
  • Cock PJ, et al. 2009. Biopython: freely available Python tools for computational molecular biology. Bioinformatics 25:1422-1423.
  • Köster J, Rahmann S. 2012. Snakemake: a scalable bioinformatics workflow engine. Bioinformatics 28:2520-2522.

Contributing

Contributions are welcome. See CONTRIBUTING.md. Open an issue for questions. Do not commit restricted data.

License

MIT. See LICENSE for details.

About

End to end Snakemake workflow for DENV-1 and DENV-2. FastQC, Trimmomatic, Picard, SPAdes, BWA, bcftools masked consensus at depth 10, MAFFT, IQ-TREE with GTR+G+I, BLAST driven context fetching, polyprotein translation and mutation tables. Includes full references and citation.

doi.org/10.1002/jmv.29727

Topics

arbovirusbioinformaticsdenguedenvgenomic-epidemiologynext-generation-sequencingoutbreakpakistanpathogen-genomicsphylogeneticspublic-healthsnakemake

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