Genomic Analysis - Lecture Notes

Learning Objectives

• Genomic Analysis Before Modern Sequencing Methods
  • Classical genetics approaches and cloning for mapping genes
• Whole-Genome Sequencing (WGS)
  • Widely used for sequencing and assembling entire genomes
• DNA Sequence Analysis
  • Relies on bioinformatics applications and genomic databases
• Functional Genomics
  • Establishes gene functions and identifies regulatory elements
• The Human Genome Project (HGP)
  • Insights into genome organization in humans
• The "Omics" Revolution
  • New era of biological research
• Comparative Genomics
  • Analyzes genomes across different organisms
• Metagenomics
  • Applies genomic techniques to environmental samples
• Transcriptome Analysis
  • Reveals profiles of expressed genes
• Proteomics
  • Analyzes the protein composition in cells

Genomic Analysis Before Modern Sequencing

• Classical Genetics Approach
  • Identification of mutations induced by agents and mapping through linkage maps.
  • Techniques included spontaneous mutation detection and generation of mutant strains.

Genomics Overview

• Definitions:
  • Genome: Complete set of DNA in a single cell.
  • Genomics: Study of genomes encompassing structural, functional, comparative, and metagenomics.

Whole-Genome Sequencing (WGS)

• Shotgun Cloning:
  • Most common method; genomic DNA is fragmented, sequences aligned using computer programs.
  • Steps:
  1. Fragmentation: DNA is cut into overlapping fragments using restriction enzymes.
  2. Assembly: Fragments are aligned to create contigs, a continuous DNA structure within chromosomes.
  3. Contig Definition: Continuous fragments derived from aligned overlapping segments.

Algorithm-Based Software in Genomics

• Used for sequence alignment to reconstruct DNA sequence order based on overlaps.

High-Throughput Sequencing

• Computer-Automated Sequencers: Enable genome sequencing, critical for the Human Genome Project, generating millions of base pairs daily.

Functional Genomics

• Studies gene functions based on RNA outcomes and potential protein coding.
• BLAST Searches: Compare genomic DNA sequences to known gene functions; predict function based on similarity.

Human Genome Project (HGP)

• Aiming to map all human genes, revealed that:
  • Human genome has about 3.1 billion nucleotides; only 2% are coding.
  • 99.9% similarity in individuals of diverse backgrounds; SNPs and copy number variations introduce diversity.
  • At least 50% of the genome is from transposable elements.
  • Approximately 20,000 protein-coding genes with alternative splicing increasing functional diversity.
  • Distribution of genes is non-uniform across chromosomes.

Alternative Splicing

• Many genes can code for multiple proteins, significantly differing from the number of existing genes.

Genomic Techniques in Functional Genomics

• Examples like Chromatin Immunoprecipitation (ChIP) help map DNA-protein interactions for gene regulation studies.

Transcriptome Analysis

• Explores gene expression levels; qualitative (identifying expressed genes) and quantitative (measuring expression levels).
• DNA Microarray Analysis: Used to determine gene expression levels through hybridization, where labeled cDNA indicates expressed genes based on fluorescence.

Proteomics Overview

• Study of protein profiles, reconciling differences in gene counts versus actual protein diversity.
• Techniques include:
  • Two-Dimensional Gel Electrophoresis (2DGE): Separates thousand proteins by charge and mass.
  • SDS-PAGE: Further separates proteins by molecular weight.
  • Mass Spectrometry (MS): Identifies proteins based on mass-to-charge ratio.

Epidemiology of Gene Variations

• Most genetic differences in humans arise from SNPs and CNVs, with implications for diseases and traits.

Access to HGP Data

• HGP provides extensive databases mapping human chromosomes, aiding in disease gene identification and treatment development.