Mitochondrial Genomics & Disease: mtDNA Variant Analysis and Precision Medicine

Aim

Workshop Objectives

Workshop Structure

📅 Day 1: Mitochondrial Genomics & mtDNA Variant Analysis

Focus: Understand mitochondrial genome biology and identify genetic variation from mitochondrial sequencing datasets.

Topics Covered

• Mitochondrial genome structure, genes, and genetic organisation
• Maternal inheritance and mitochondrial genetic variation
• Mitochondrial diseases and disease-associated phenotypes
• mtDNA mutations: SNVs, indels, and structural variation concepts
• Homoplasmy, heteroplasmy, and variant allele frequency
• mtDNA sequencing data and quality-control concepts
• Reference-based mitochondrial genome analysis
• Variant detection, annotation, and filtering
• Population frequency and mitochondrial variation

🛠️ Hands-on

• Analyse a curated mtDNA sequencing dataset
• Identify and annotate mitochondrial variants
• Calculate/interpret heteroplasmy levels
• Filter variants using quality and frequency criteria

🧰 Tools Covered

Python, R, pandas, Biopython, SAMtools/BCFtools concepts, Google Colab, mitochondrial genomic datasets

📅 Day 2: mtDNA Pathogenicity, Haplogroups & Disease Association

Focus: Evaluate mitochondrial variants and connect genetic variation with disease and population evidence.

Topics Covered

• Mitochondrial variant annotation and clinical interpretation
• Pathogenicity assessment and evidence classification
• Population databases and allele-frequency analysis
• Disease and phenotype databases
• Functional consequences of mtDNA variants
• Conservation and sequence-based evidence
• Mitochondrial haplogroups and phylogenetic relationships
• Haplogroup assignment and population variation
• Variant–disease association analysis
• Integrating computational and clinical evidence

🛠️ Hands-on

• Investigate candidate mtDNA variants
• Compare population frequencies and clinical evidence
• Explore haplogroups and mitochondrial phylogeny
• Rank variants according to disease relevance

🧰 Tools Covered

MITOMAP, MSeqDR, ClinVar, NCBI, Ensembl, BLAST, Python/R, phylogenetic and variant-analysis resources

📅 Day 3: Mitochondrial Disease Profiling & Precision Medicine

Focus: Integrate mtDNA variation, heteroplasmy, clinical evidence, and computational analysis for precision-medicine applications.

Topics Covered

• Integrating mtDNA variants with disease phenotypes
• Heteroplasmy and disease-risk interpretation
• Variant prioritisation for mitochondrial disorders
• Mitochondrial genotype–phenotype relationships
• Multi-variant and haplogroup-based interpretation
• Mitochondrial variant visualisation and reporting
• Biomarker and disease-signature concepts
• Computational approaches for patient stratification
• Mitochondrial genomics in rare-disease research
• Applications in cancer, ageing, metabolic and neurodegenerative diseases
• Precision-medicine workflows and clinical interpretation
• Limitations of computational predictions and need for validation

🛠️ Hands-on

• Integrate variant, heteroplasmy, population, and clinical information
• Prioritise candidate disease-associated mtDNA variants
• Build a mitochondrial disease variant profile
• Generate visual summaries and a research-oriented interpretation report

🧰 Tools Covered

Python, R, MITOMAP, ClinVar, MSeqDR, NCBI, pandas, matplotlib/Plotly, Google Colab

Who Should Enrol?

Important Dates

Workshop Outcomes

Fee Structure