The Human Genome

Significance of the Human Genome Project:
- Timeline:
  - 1953: Proposed double helix model of DNA by Watson and Crick.
  - 1990-2003: Launch and completion of the Human Genome Project.
  - 1997: E.coli genome fully sequenced.
  - 1999: Full sequencing of Chromosome 22 in humans.
  - 2001: 90% completion of Human Genome Project in February.
Post-project goals include determining gene functions, locating genes associated with diseases, and improving medical science.

Genomics: Study of an organism’s genome.
Bioinformatics: Interface of biology and computer science to manage data.
Pharmacogenomics: Study of how genetics influence drug response.
DNA Typing/Fingerprinting: Analyzing DNA for unique patterns.
Haplotype: Combination of genetic variations inherited together.
Gene Therapy: Technique for correcting dysfunctional genes.
DNA Microarray: Tool to study gene expression.
Proteomics: Study of proteins and their functions.
SNP (Single Nucleotide Polymorphism): Variations in a single nucleotide in the genome.
Codon: Triplet bases in DNA or mRNA.

Genomics: Enabled identification of human genes and functions.
Sequencing: Completed sequencing of around 3 billion nucleotides in human DNA and identified all human genes.

Steps:
- Human chromosomes fragmented with restriction enzymes.
- Combined with vectors and clawed for DNA replication.
- Automated machines used for sequencing.
Findings:
- Only 2% of nucleotides code for proteins (~22,300 genes).
- 98% consists of noncoding sequences (Junk DNA) with no known function.

Ongoing study of the data collected will continue across decades.
Comparison with genomes of non-human organisms (e.g., fruit flies, mice, E.coli) to enhance understanding of human gene functions.

Post-sequencing gene identification through computer analysis and recombinant DNA technology.
For nonhuman organisms, gene identification focused on Open Reading Frames (ORFs).
ORFs: Stretches of DNA with codon sequences, aiding in gene identification in simpler organisms.
Human genes require advanced algorithms utilizing data from various organisms.

Emerged from data volumes necessitating structured storage and analysis.
Involves creating databases for biological information using biology, computing, math, and engineering methods.
Enables comparison and prediction of newly identified proteins' structure and function.

Definition: Process of isolating an individual's DNA fragments revealing unique patterns.
Protein coding regions are almost universally identical; unique patterns arise from noncoding regions.
Forensic applications include identification in criminal cases and paternity testing.

Challenges with small samples (e.g., blood or hair) resolved using PCR to amplify DNA.
Subsequent DNA cutting with restriction enzymes, separated by gel electrophoresis.
Unique patterns are compared against known DNA samples.

Task involves teamwork to solve a fictitious murder case using DNA fingerprinting.
Process includes gathering data, answering questions, and earning clues from the instructor.

Analyze gene expression: some genes active while others remain silent.
Tool: DNA microarrays (slides/chips with many DNA fragments).
Can analyze thousands of genes simultaneously, understanding expression patterns and influences (genetic/enviro).

Isolate mRNA from two cell populations.
Use reverse transcriptase for cDNA strand building, labeling with fluorescent dyes.
Analyzing expression on a microarray slide shows unique patterns indicating gene activity.

Over 99% of DNA sequences are constant among individuals, with variations (SNPs) linked to diseases.
SNP Mapping: Key in identifying genes associated with genetic disorders.

Aims at compiling common genetic variations to find linked variations (haplotypes).
Studies population-specific variations and their implications for linked gene inheritance.

Identification of SNP groups in specific DNA regions helps in understanding genotypes affecting diseases.
Aims to reveal how genetic variations influence drug responses.

Study of genetic influences on drug responses aims for personalized medicine.
Advantages of pharmacogenomics include customized drug dosing and improved safety.

Examines protein roles as cellular machines, linking protein functions to gene expression.
A large-scale cataloging of protein structures/functions is revolutionizing drug development.