Julia HenningBiology Senior SeminarApril 22, 2013
THE HUMAN GENOME PROJECT:
ANALYSIS AND IMPLICATIONS
“Initial Sequencing and Analysis of the
Human Genome”
Project: 1990-2003Published: 2001
Goal: Generate a map that covered over 96% of
the human genome
HISTORICAL CONTEXT: 1980S
AND 1990S• Fall of the Soviet Union and the
Berlin Wall
• AIDS epidemic
• Personal computers and mobile
phones become popular
• The World Wide Web is invented and
release to the public
• Dolly the sheep is cloned
• DNA is first used to solve crimes
1970s – Fred Sanger developed methods to sequence the genomes of virus and mitochondrion
1980 – The fi rst complete genome of a bacteriophage of E. coli is published by the Sanger group
1986 – The fi rst automated DNA sequencer is released
1987 – Eric Langers develops the computer program MAPMAKER that can create genetic linkage maps from molecular marker data
A COUPLE THINGS THAT MADE THE HUMAN GENOME PROJECT
POSSIBLE:
Francis Collins
Invented the method of chromosome jumping
Director of the National Center for Human Genome Research from 1993-2008
Director of the National Institutes of Health
Aristides Patrinos
Founded the DOE Joint Genome Institute
Launched the DOE’s Genomics to Life program Currently serves as the
vice president of Synthetic Genomics Inc.
PROJECT LEADERS
THE GENOME WAS MARKED AND SPLIT UP
Genome
Clone
Sequence – Tagged Site (STS)
CREATING BAC LIBRARIES
SEQUENCING THE DNA FRAGMENTS (THE SANGER METHOD)
READING THE SEQUENCE
FINISHING THE PROJECT
The initial draft covered 90% of the genome
The draft was 99.99% accurate
All data was placed into public databases within 24 hours
The project was completed ahead of schedule and under budget
30,000 to 40,000 protein coding genes in the human genome
Recombination rates tend to be much higher in distal regions of chromosome and on shorter chromosome arms in general
More than 1.4 million single nucleotide polymorphisms (SNPs) were identified in the human genome
Over 1400 disease genes were identified
A COUPLE MAJOR CONCLUSIONS:
1. We better understand our genomic
landscape
2. We better understand genetic
diseases
3. There are new social, ethical, and
legal implications to be considered
BROAD INFLUENCES:
Current Article
GENETIC WARFARIN
DOSING: TABLES VERSUS
ALGORITHMS
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
PUBLISHED: 2011
The Researchers
Brian Finkelman
Brian Gage
Julie Johnson
Colleen
Brensinger
Stephen Kimmel
Anticoagulation Clinics
Philadelphia,
Pennsylvania
St. Louis, Missouri
Gainsville, Florida
WHO? WHERE?
Warfarin: Blood thinner that prevents blood clots from
forming
Dosage in patients must be carefully monitored
Initially, patients must go to a clinic to be have
their blood tested on a regular basis
Researchers want to use genomic information to
better predict warfarin dosage for patients
WHY?
1,378 patients who had achieved their INR
values were studied
Warfarin dose was predicted with:
Empiric Dose
Clinical Algorithm
FDA Warfarin Label
Genomic Mean Table
Pharmacogentic Algorithm
PROCEDURE
RESULTS: PHARMACOGENTICS = GREATER ACCURACY!
Accurate dosing was achieved 52% of the time
The pharmacogenetic algorithm had lower rates of dose overestimation and underestimation than the other methods
HOW DOES THIS RELATE TO THE HUMAN GENOME PROJECT?
Map of Human Genome
Genetic Algorithm
Accurate Dose
Predications
IDE
AS
FO
R T
HE
FU
TU
RE
A Realistic Idea…
Target drugs and better dosing predictions for people of different ethnicities and for people with genetic diseases and disabilities
An Awesome Idea…
Target drugs for the withdrawal of people who are genetically predisposed to different addictions
What to look for in the future… Mapped genomes of other organisms
New Target Drugs
Individualized medicine
New Drug Therapies
“Designer Drugs”
More social and ethical controversies
regarding genetic privacy
CONCLUSIONS: