OmniEdge Scientific
Next Batch — Admissions Open
Intermediate to Advanced

Molecular Breeding Data Analytics

Molecular Breeding Data Analytics

Hands-on course covering Molecular Markers, QTL Mapping, Marker-Assisted Selection, SNP/HapMap data, Population Structure (STRUCTURE), GWAS with TASSEL & GAPIT (R), Haplotype Analysis, and KASP Assay design for crop improvement and trait mapping.

Course Overview

Molecular Breeding Data Analytics is a hands-on, application-driven course that equips plant breeders, geneticists, and agri-research students with end-to-end skills for marker-assisted selection, QTL mapping, GWAS, and KASP-based genotyping. The curriculum spans wet-lab data preparation, software-based analysis, statistical interpretation, and reproducible R-based pipelines.

Module I — Molecular Breeding Data Handling and Analysis

Basics of Molecular Markers, QTL Mapping & Marker-Assisted Selection (MAS)

  • Overview of molecular markers — SSR, SNP, AFLP, and others
  • Principles and workflow of marker-assisted selection in crop improvement
  • Applications of molecular markers in trait mapping and breeding programs
  • QTL Mapping — Linkage Mapping, Association Mapping, and Linkage Disequilibrium

Genotyping of SSR Markers, Scoring & Data Generation

  • Experimental design and protocol overview for SSR genotyping
  • Allele scoring from gel or capillary electrophoresis
  • Preparing data matrices for downstream analysis

Genetic Diversity Studies

  • Estimating allelic diversity, heterozygosity, and PIC (Polymorphism Information Content)
  • Construction and interpretation of dendrograms

Population Structure Analysis using STRUCTURE

  • Bayesian clustering for genetic structure determination
  • Preparing input files, parameter setting, and output interpretation
  • Visualisation of population clusters and admixture

SNP Data Analysis — HapMap, Imputation, Filtering

  • SNP data formats — HapMap and VCF
  • Quality control — MAF, missing data, heterozygosity filters
  • Imputation of missing genotypes — preparing data for GWAS

Module II — GWAS, Haplotypes & KASP Assay

GWAS using TASSEL Software

  • GWAS principles — population structure correction, kinship matrix
  • Step-by-step execution of GWAS in TASSEL with example datasets
  • Interpreting Manhattan plots, Q-Q plots, and significant marker-trait associations

GWAS using GAPIT in R Studio

  • Installing and working with the GAPIT R package
  • Data formatting; model selection — GLM, MLM, FarmCPU
  • Reproducible and automated GWAS pipelines in R

Candidate Gene-Based Association Studies

  • Targeted association studies using known trait-related genes
  • Strategies to pinpoint candidate genes near associated markers
  • Genome browsers, gene annotations, and functional databases
  • Prioritising candidate genes for validation and functional studies

Haplotype Analysis

  • Definition and significance of haplotypes in genetic analysis
  • Identifying haplotypes within LD regions
  • Associating haplotypes with phenotypic traits

KASP Assay for SNP Marker Genotyping

  • Overview of Kompetitive Allele-Specific PCR (KASP) technology
  • Designing KASP assays for SNP markers and trait-linked alleles
  • KASP data analysis and interpretation

Who Should Enrol

Plant breeders, agri-genomics researchers, MSc/PhD students in plant biotechnology, and crop scientists planning marker-assisted breeding programs or GWAS-driven trait discovery.

Next Batch Begins Soon — Admissions Open.

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