Gene expression analysis: teaching students to do 30,000 experiments at once with microarray.

Area of Science:

• Genomics Education
• Computational Biology
• Molecular Biology Techniques

Background:

• Genome-scale experiments generate vast datasets requiring computational analysis.
• Limited student-based laboratory exercises exist for designing and executing these experiments.
• Undergraduate education needs accessible labs for hands-on genomic data generation and analysis.

Purpose of the Study:

• To present a microarray-based gene expression analysis experiment suitable for undergraduate students.
• To provide a practical laboratory module for learning about large-scale genomic data.
• To adapt the experiment for comparative genomic hybridization (CGH) and single nucleotide polymorphism (SNP) analyses.

Main Methods:

• A two-session teaching laboratory module was designed.
• Session 1: Introductory wet bench exercise focusing on fundamental technical skills.
• Session 2: Students acquire and analyze microarray data, building on foundational concepts.

Main Results:

• The designed experiment is tailored for undergraduate skill levels, considering technical difficulty, duration, cost, and material availability.
• Students gain practical experience in generating and analyzing large-scale genomic datasets.
• The lab familiarizes students with initial steps of microarray data analysis.

Conclusions:

• This microarray teaching lab effectively introduces undergraduates to genome-scale data analysis.
• The experimental design provides a foundation for understanding and participating in genomic research.
• The methodology is adaptable for other genomic applications like CGH and SNP analysis.