1. The Human Genome Project (Lecture 7)
What did they do?
Why did they do it?
What will it mean for humankind?

2. Brief history of the work…
Proposed in 1985
1988. Initiated and funded by NIH and US Dept. of Energy ($3 billion set aside)
1990. Work begins.
1998. Celera announces a 3-year plan to complete the project years early
Published in Science and Nature in February, 2001

3. The Human Genome Project Began in 1990
The Mission of the HGP: The quest to understand the human genome and the role it plays in both health and disease.
“The true payoff from the HGP will be the ability to better diagnose, treat, and prevent disease.”
--- Francis Collins, Director of the HGP and the National Human Genome Research Institute (NHGRI)

4. Goals of HGP
Create physical map of the 24 human chromosomes (22 autosomes, X & Y)
Identify the entire set of genes & map them all to their chromosomes
Determine the nucleotide sequence of the estimated 3 billion base pairs
Analyze genetic variation among humans
Map and sequence the genomes of model organisms

5. Model organisms Bacteria (E. coli, influenza, several others)
Yeast (Saccharomyces cerevisiae)
Plant (Arabidopsis thaliana)
Roundworm (Caenorhabditis elegans)
Fruit fly (Drosophila melanogaster)
Mouse (Mus musculus)

6. Goals of HGP (cont’d)
Develop new laboratory and computing technologies to make all this possible
Disseminate genome information
Consider ethical, legal, and social issues associated with this research

11. Brief history of the work…
Proposed in 1985
1988. Initiated and funded by NIH and US Dept. of Energy ($3 billion set aside)
1990. Work begins.
1998. Celera announces a 3-year plan to complete the project years early
Published in Science and Nature in February, 2001

12. The Beginning of the Project
Most the first 10 years of the project were spent improving the technology to sequence and analyze DNA.
Scientists all around the world worked to make detailed maps of our chromosomes and sequence model organisms, like worm, fruit fly, and mouse.

14. How they did it… DNA from 5 humans 2 males, 3 females
2 caucasians, one each of asian, african, hispanic
Cut up DNA with restriction enzymes
Ligated into BACs & YACs, then grew them up
Sequenced the BACs
Let a supercomputer put the pieces together

15. Cut segments inserted into BACs
DNA
Cut segments inserted into BACs
Lots of overlap
Known sequence

16. How they did it… DNA from 5 humans 2 males, 3 females
2 caucasians, one each of asian, african, hispanic
Cut up DNA with restriction enzymes
Ligated into BACs & YACs, then grew them up
Sequenced the BACs
Let a supercomputer put the pieces together

18. What did they find?

19. 5000 bases per page
CACACTTGCATGTGAGAGCTTCTAATATCTAAATTAATGTTGAATCATTATTCAGAAACAGAGAGCTAACTGTTATCCCATCCTGACTTTATTCTTTATG AGAAAAATACAGTGATTCC
AAGTTACCAAGTTAGTGCTGCTTGCTTTATAAATGAAGTAATATTTTAAAAGTTGTGCATAAGTTAAAATTCAGAAATAAAACTTCATCCTAAAACTCTGTGTGTTGCTTTAAATAATC
AGAGCATCTGC TACTTAATTTTTTGTGTGTGGGTGCACAATAGATGTTTAATGAGATCCTGTCATCTGTCTGCTTTTTTATTGTAAAACAGGAGGGGTTTTAATACTGGAGGAACAA
CTGATGTACCTCTGAAAAGAGA AGAGATTAGTTATTAATTGAATTGAGGGTTGTCTTGTCTTAGTAGCTTTTATTCTCTAGGTACTATTTGATTATGATTGTGAAAATAGAATTTATCC
CTCATTAAATGTAAAATCAACAGGAGAATAGCAAAAACTTATGAGATAGATGAACGTTGTGTGAGTGGCATGGTTTAATTTGTTTGGAAGAAGCACTTGCCCCAGAAGATACACAAT
GAAATTCATGTTATTGAGTAGAGTAGTAATACAGTGTGTTCCCTTGTGAAGTTCATAACCAAGAATTTTAGTAGTGGATAGGTAGGCTGAATAACTGACTTCCTATC ATTTTCAGGTT
CTGCGTTTGATTTTTTTTACATATTAATTTCTTTGATCCACATTAAGCTCAGTTATGTATTTCCATTTTATAAATGAAAAAAAATAGGCACTTGCAAATGTCAGATCACTTGCCTGTGGT
CATTCGGGTAGAGATTTGTGGAGCTAAGTTGGTCTTAATCAAATGTCAAGCTTTTTTTTTTCTTATAAAATATAGGTTTTAATATGAGTTTTAAAATAAAATTAATTAGAAAAAGGCAA
ATTACTCAATATATATAAGGTATTGCATTTGTAATAGGTAGGTATTTCATTTTCTAGTTATGGTGGGATATTATTCAGACTATAATTCCCAATGAAAAAACTTTAAAAAATGCTAGTGA
TTGCACACTTAAAACACCTTTTAAAAAGCATTGAGAGCTTATAAAATTTTAATGAGTGATAAAACCAAATTTGAAGAGAAAAGAAGAACCCAGAGAGGTAAGGATATAACCTTACC
AGTTGCAATTTGCCGATCTCTACAAATATTAATATTTATTTTGACAGTTTCAGGGTGAATGAGAAAGAAACCAAAACCCAAGACTAGCATATGTTGTCTTCTTAAGGAGCCCTCCCCT
AAAAGATTGAGATGACCAAATCTTATACTCTCAGCATAAGGTGAACCAGACAGACCTAAAGCAGTGGTAGCTTGGATCCACTACTTGGGTTTGTGTGTGGCGTGACTCAGGTAATCT
CAAGAATTGAACATTTTTTTAAGGTGGTCCTACTCATACACTGCCCAGGTATTAGGGAGAAGCAAATCTGAATGCTTTATAAAAATACCCTAAAGCTAAATCTTACAATATTCTCAAG
AACACAGTGAA ACAAGGCAAAATAAGTTAAAATCAACAAAAACAACATGAAACATAATTAGACACACAAAGACTTCAAACATTGGAAAATACCAGAGAAAGATAATAAATAT
TTTACTCTTTAAAAATTTAGTTAAAAGCTTAAACTAATTGTAGAGAAAA AACTATGTTAGTATTATATTGTAGATGAAATAAGCAAAACATTTAAAATACAAATGTGATTACTTAAAT
TAAATATAATAGATAATTTACCACCAGATTAGATACCATTGAAGGAATAATTAATATACTGAAATACAGGTCAGTAGAATTTTTTTCAATTCAGCATGGAGATGTAAAAAATGAAAA
TTAATGCAAAAAATAAGGGCACAAAAAGAAATGAGTAATTTTGATCAGAAATGTATTAAAATTAATAAACTGGAAATTTGACATTTAAAAAAAGCATTGTCATCCAAGTAGATGTG
TCTATTAAATAGTTGTTCTCATATCCAGTAATGTAATTATTATTCCCTCTCATGCAGTTCAGATTCTGGGGTAATCTTTAGACATCAGTTTTGTCTTTTATATTATTTATTCTGTTTACTAC
ATTTTATTTTGCTAATGATATTTTTAATTTCTGACATTCTGGAGTATTGCTTGTAAAAGGTATTTTTAAAAATACTTTATGGTTATTTTTGTGATTCCTATTCCTCTATGGACACCAAGGCT
ATTGACATTTTCTTTGGTTTCTTCTGTTACTTCTATTTTCTTAGTGTTTATATCATTTCATAGATAGGATATTCTTTATTTTTTATTTTTATTTAAATATTTGGTGATTCTTGGTTTTCTCAGCC
ATCTATTGTCAAGTGTTCTTATTAAGCATTATTATTAAATAAAGATTATTTCCTCTAATCACATGAGAATCTTTATTTCCCCCAAGTAATTGAAAATTGCAATGCCATGCTGCCATGTGG
TACAGCATGGGTTTGGGCTTGCTTTCTTCTTTTTTTTTTAACTTTTATTTTAGGTTTGGGAGTACCTGTGAAAGTTTGTTATATAGGTAAACTCGTGTCACCAGGGTTTGTTGTACAGATCA
TTTTGTCACCTAGGTACCAAGTACTCAACAATTATTTTTCCTGCTCCTCTGTCTCCTGTCACCCTCCACTCTCAAGTAGACTCCGGTGTCTGCTGTTCCATTCTTTGTGTCCATGTGTTCTC
ATAATTTAGTTCCCCACTTGTAAGTGAGAACATGCAGTATTTTCTAGTATTTGGTTTTTTGTTCCTGTGTTAATTTGCCCAGTATAATAGCCTCCAGCTCCATCCATGTTACTGCAAAGAA
CATGATCTCATTCTTTTTTATAGCTCCATGGTGTCTATATACCACATTTTCTTTATCTAAACTCTTATTGATGAGCATTGAGGTGGATTCTATGTCTTTGCTATTGTGCATATTGCTGCAAG
AACATTTGTGTGCATGTGTCTTTATGGTAGAATGATATATTTTCTTCTGGGTATATATGCAGTAATGCGATTGCTGGTTGGAATGGTAGTTCTGCTTTTATCTCTTTGAGGAATTGCCATG
CTGCTTTCCACAATAGTTGAACTAACTTACACTCCCACTAACAGTGTGTAAGTGTTTCCTTTTCTCCACAACCTGCCAGCATCTGTTATTTTTTGACATTTTAATAGTAGCCATTTTAACT
GGTATGAAATTATATTTCATTGTGGTTTTAATTTGCATTTCTCTAATGATCAGTGATATTGAGTTTGTTTTTTTTCACATGCTTGTTGGCTGCATGTATGTCTTCTTTTAAAAAGTGTCTGTT
CATGTACTTTGCCCACATTTTAATGGGGTTGTTTTTCTCTTGTAAATTTGTTTAAATTCCTTATAGGTGCTGGATTTTAGACATTTGTCAGACGCATAGTTTGCAAATAGTTTCTCCCATTC
TGTAGGTTGTCTGTTTATTTTGTTAATAGTTTCTTTTGCTATGCAGAAGCTCTTAATAAGTTTAATGAGATCCTGATATGTTAGGCTTTGTGTCCCCACCCAAATCTCATCTTGAATTATA
TCTCCATAATCACCACATGGAGAGACCAGGTGGAGGTAATTGAATCTGGGGGTGGTTTCACCCATGCTGTTCTTGTGATAGTGAATGAGTTCTCACGAGATCTAATGGTTTTATGAGG
GGCTCTTCCCAGCTTTGCCTGGTACTTCTCCTTCCTGCCGCTTTGTGAAAAAGGTGCATTGCGTCCCTTTCACCTTCTTCTATAATTGTAAGTTTCCTGAGGCCTTCCCAGCCATGCTGAA
CTTCAAGTCAATTAAACCTTTTTCTTTATAAATTACTCAGTCTCTGGTGGTTCTTTATAGCAGTGTGAAAATGGACTAATGAAGTTCCCATTTATGAATTTTTGCTTTTGTTGCAATTGCTT
TTGACATCTTAGTCATGAAATCCTTGCCTGTTCTAAGTACAGGACGGTATTGCCTAGGTTGTCTTCCAGGGTTTTTCTAATTTTGTGTTTTGCATTTAAGTGTTTAATCCATCTTGAGTTGA
TTTTTGTATATTGTGTAAGGAAGGGGTCCAGTTTCAATCTTTTGCATATGGCTAGTTAGTTATCCCAGTACCATTTATTGAAAAGACAGTCTTTTCCCCATCGCTCGTTTTTGTCAGTTTT
ATTGATGATCAGATAATCATAGCTGTGTGGCTTTATTTCTGGGTTCTTTATTCTGTTCTATTGGTTTATGTCCCTGTTTTTGTGCCAGTACCATGCTGTTTTGGTTAACATAGCCCTGTAGT
ATAGTTTGAGGTCAGATAGCCTGATGCTTCCAGCTTTGTTCTTTTTCTTAAGATTGCCTTGGCTATTTGGCCTCTTTTTTGGTTCCACATGAATTTTAAAACAGTTGTTTCTAGTTTTTGAA
GAATGTCATTGGTAGTTTGATAGAAATAGCATTTAATCTGTAAATTGATTTGTGCAGTATGGCCTTTTAATGATATTGATTCTTCCTATCCATGAGCATGATATGTTTTCCATTTTGTTTG
TATCCTCTCTGATTTCTTTGTGCAGTGTTTTGTAATTCTCAT TGTAGAGATTTTTCACCTCCCTGGTTAGTTGTATTTTACCCTAGATATTT TATTCTTTTTGTGAAAATTGTGAATGGGAT
TGCCTTCCTGATTTGACTGC CAGCTTGGTTACTGTTGGTTTATAGAAATGCTAGTGATTTTTGTACATTG ATTTTCTTTCTAAAACTTTGCTGAAGTTTTTTTTATTAGCAGAAGGAGCT
TTGGGGCTGAGACTATGGGGTTTTCTAGATATAGAATCATGTCAGCTTCAAATAGGGATAATTTTACTTCCTCTCTTCCTATTTGGATGCCCTTTATTTCTTTCTCTTGCCTGATTACTCTG
GCTGGGATTTCCTATGTTGAATAGGAGT CATGAGAGAGGGCATCAAATCTACACATATCAAATACTAACCTTGAATGTCTAGATATTT TATTCTTTTTGTGAAAATTGTGAATGGGAT

20. How much data make up the human genome?
3 pallets with 40 boxes per pallet x 5000 pages per box x 5000 bases per page = 3,000,000,000 bases!
To get accurate
sequence requires
6-fold coverage.
Now: Shred 18 pallets
and reassemble.

21. Human genome content 1-2 % codes for protein products
24% important for translation
75% “junk”
Repetitive elements
Satellites (regular, mini-, micro-)
Transposons
Retrotransposons
Parasites
BOOK THAT WROTE ITSELF

22. Comparative Genomics

23. Yeast 70 human genes are known to repair mutations in yeast
Nearly all we know about cell cycle and cancer comes from studies of yeast
Advantages:
fewer genes (6000)
few introns
31% of yeast genes give same products as human homologues

24. Drosophila
nearly all we know of how mutations affect gene function come from Drosophila studies
We share 50% of their genes
61% of genes mutated in 289 human diseases are found in fruit flies
68% of genes associated with cancers are found in fruit flies
Knockout mutants
Homeobox genes

25. C. elegans 959 cells in the nervous system
131 of those programmed for apoptosis
apoptosis involved in several human genetic neurological disorders
Alzheimers
Huntingtons
Parkinsons

26. Mouse known as “mini” humans Very similar physiological systems
Share 90% of their genes

27. The Human Genome Project at UC Santa Cruz
Phoenix Eagleshadow
November 9, 2004

28. The Challenges were Overwhelming
First there was the Assembly
The DNA sequence is so long that no technology can read it all at once, so it was broken into pieces.
There were millions of clones (small sequence fragments).
The assembly process included finding where the pieces overlapped in order to put the draft together.
Small sequence fragments reproduced so there was enough material to sequence.
3,200,000 piece puzzle anyone?

29. The “Working Draft” of the human genome
ACCTTGG
CCTGAAT
CTAGGCT
TTGCATC
CCTAGTC
CTGATCG
Freeze of sequence data
generated by NCBI
Clone layouts generated
By Washington University
sequence
Clone
maps
Assembly generated by
UCSC
Working draft assembly

30. UCSC put the human genome sequence on the web July 7, 2000
Cyber geeks
Searched for hidden
Messages, and
“GATTACA”
UCSC put the human genome sequence on CD in October 2000, with varying results

31. The Completion of the Human Genome Sequence
June 2000 White House announcement that the majority of the human genome (80%) had been sequenced (working draft).
Working draft made available on the web July 2000 at genome.ucsc.edu.
Publication of 90 percent of the sequence in the February 2001 issue of the journal Nature.
Completion of 99.99% of the genome as finished sequence on July 2003.

32. The Project is not Done…
Next there is the Annotation:
The sequence is like a topographical map, the annotation would include cities, towns, schools, libraries and coffee shops!
So, where are the genes?
How do genes work?
And, how do scientists use this information for scientific understanding and to benefit us?

33. What do genes do anyway?
We only have ~27,000 genes, so that means that each gene has to do a lot.
Genes make proteins that make up nearly all we are (muscles, hair, eyes).
Almost everything that happens in our bodies happens because of proteins (walking, digestion, fighting disease). OR OR
Eye Color and Hair Color
are determined by genes

34. Of Mice and Men: It’s all in the genes
Humans and Mice have about the same number of genes. But we are so different from each other, how is this possible?
One human gene can make many different proteins while a mouse gene can only make a few!
Did you say cheese?
Mmm, Cheese!

35. Genes are important
By selecting different pieces of a gene, your body can make many kinds of proteins. (This process is called alternative splicing.)
If a gene is “expressed” that means it is turned on and it will make proteins.

36. What we’ve learned from our genome so far…
There are a relatively small number of human genes, less than 30,000, but they have a complex architecture that we are only beginning to understand and appreciate.
-We know where 85% of genes are in the sequence.
-We don’t know where the other 15% are because we haven’t seen them “on” (they may only be expressed during fetal development).
-We only know what about 20% of our genes do so far.
So it is relatively easy to locate genes in the genome, but it is hard to figure out what they do.

37. How do scientists find genes?
The genome is so large that useful information is hard to find.
Researchers at UCSC decided to make a computational microscope to help scientists search the genome.
Just as you would use “google” to find something on the internet, researchers can use the “UCSC Genome Browser” to find information in the human genome.
Explore it at

38. The UCSC Genome Browser

39. The browser takes you from early maps of the genome . . .
First looked thru microscope. Geisma staining produced chromosome bands. Later Fluorescence In Situ Hybridization developed. Genetic map grew to 5000 markers (places where distinctive variation occurs, like those used in DNA fingerprinting).(picture shows chr 18, about 85 million bases. Order of the markers determined by studying family inheritance of variations. Studies also led to the identification of genes associated with some diseases: famous hunts for Huntington’s disease, Duchenne muscular distrophy, retinoblastoma, Cystic Fibrosis and other genes in the 80’s.

40. . . . to a multi-resolution view . . .
Ochre is mouse chr 5, yellow is mouse chr7

41. . . . at the gene cluster level . . .
HD = Huntington’s disease gene. First success of RFLP (restriction fragment length polymorphism) mapping. Found linkage in 1983 before the first RFLP map was even constructed. Disease claimed Woody Guthrie. Nancy Wexler, whose mother had died of the disease, became director of the Huntington’s commission (congressional) and of NIH project. Collected family data in Venezuela. “Lucky Jim” Gusella found a link between HD and one of the first RFLP markers he tested. Took another 10 years to actually locate the gene. Takes seconds on the browser.

42. . . . the single gene level . . .

43. . . . the single exon level . . .

44. . . . and at the single base level
caggcggactcagtggatctggccagctgtgacttgacaag
caggcggactcagtggatctagccagctgtgacttgacaag

45. The Continuing Project
Finding the complete set of genes and annotating the entire sequence. Annotation is like detailing; scientists annotate sequence by listing what has been learn experimentally and computationally about its function.
Proteomics is studying the structure and function of groups of proteins. Proteins are really important, but we don’t really understand how they work.
Comparative Genomics is the process of comparing different genomes in order to better understand what they do and how they work. Like comparing humans, chimpanzees, and mice that are all mammals but all very different.
Annotation: includes, for example, not only the genes, but the proteins the genes makes and what diseases they are associated with.
Proteins are really important for drug development and discovery.