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: