Julia Henning Biology Senior Seminar April 22, 2013 THE HUMAN GENOME PROJECT: ANALYSIS AND IMPLICATIONS

“Initial Sequencing and Analysis of the Human Genome” Project: Published: 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 first complete genome of a bacteriophage of E. coli is published by the Sanger group  1986 – The first 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  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 LIBRARIE S

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

IDEAS FOR THE FUTURE 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: