Download The Human Genome, impact in the biomedical

The Human Genome, impact in the
biomedical domain
Sonia ABDELHAK, PhD
Molecular Investigation of Genetic Orphan Disorders
Institut Pasteur de Tunis
Human Genome Project
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Historical context.
Goals of the HGP.
Strategy.
Results.
Impact on Biomedical domain.
Discussion.
February 2001
« Finished » sequence
April 1953-April 2003
Brief history of HGP
1984 to 1986 – first proposed at US DOE meetings
1988 – endorsed by US National Research Council
(Funded by NIH and US DOE $3 billion set aside)
1990 – Human Genome Project started (NHGRI)
Later – UK, France, Japan, Germany, China
1998. Celera announces a 3-year plan to complete
the project years early
First draft published in Science and Nature in
February, 2001
Finished Human Genome sequence published in
Nature 2003.
Challenges
• Genome Attributes
– Size
– Polymorphism
– Repeats (Smaller repeats are technically difficult to sequence,
some sequences are repeated all over the genome: How can these
be placed?).
• Available Technology
– 600 bp per “read”(Sequencing works by extension from a primer/
gel electrophoresis. Limited by resolution of gel).
– Error (~1 error per 600. Sequencing multiple times decreases error;
same error unlikely in multiple reads. 10x Coverage = error rate
~1/10,000).
– Relies on cloning (Some regions are difficult to clone
Heterochromatin; some sequences rearrange or are deleted when
cloned)
Goals of HGP
• Create a genetic and 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
Model organisms
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Bacteria (E. coli, influenza, several others)
Yeast (Saccharomyces cerevisiae)
Plant (Arabidopsis thaliana)
Roundworm (Caenorhabditis elegans)
Fruit fly (Drosophila melanogaster)
Mouse (Mus musculus)
Goals of HGP (II)
• Develop new laboratory and computing
technologies to make all this possible
• Disseminate genome information
• Consider ethical, legal, and social issues
associated with this research
Time-line large scale genomic analysis
Identification de Polymorphismes de type microsatellites par analyse de séquence:
IL-12p35AC F
tggtggcagaaatcattgtctgaaaagtaattgttttacttttattcttttcgtgtgtgtgtgtgt
gtgtgtgtgtgtgtgtgtgtgtgtgtgtgtgcatgtgccagatttcttgtttgaaaggcaat
gagcttcatccaagtatcaa
78.57%
IL-12p35AC R
IL-12p40AC F
atttcaggtgtgagccactgtgcctggccagaactttttcaatgaatattcaagataattgtata
cacattttatatatatatatatatatacacacacacacacacacacatatgtatacacaca
ttatatatataatccatgttatatacatctctacattatatatatccactatatatattttacttataca
tatagattttatttttatgaactaggatcaaattgta
69.23%
IL-12p40AC R
1
174
170
166
2
3
4
5
EST Division: Expressed Sequence Tags
>IMAGE:275615
5' mRNA sequence
dbEST http://www.ncbi.nlm.nih.gov/dbEST/
sequence1
ESTs
GACAGCATTCGGGCCGAGATGTCTCGCTCCGTGGCCTTAGCTGTGCTCGCGCTACTCTCTCTTTCTG
TGGAGGTATCCAGCGTACTCCAAAGATTCAGGTTTACTCACGTCATCCAGCAGAGAATGGAAAGTCA
TTCCTGAATTGCTATGTGTCTGGGTTTCATCCATCCGACATTGAAGTTGACTTACTGAAGAATGGAG
TAGTCA
GAATTGAAAAAGTGGAGCATTCAGACTTGTCTTTCAGCAAGGACTGGTCTTTCTATCTCTTGTACTA
TGAATTCACCCCCACTGAAAAAGATGAGTATGCCTGCCGTGTTGAACCATGTNGACTTTGTCACAGN
clone xyz
80-100,000
AAGTTNAGTTTAAGTGGGNATCGAGACATGTAAGGCAGGCATCATGGGAGGTTTTGAAGNATGCCGC
genes
TTGGATTGGGATGAATTCCAAATTTCTGGTTTGCTTGNTTTTTTAATATTGGATATGCTTTTG
nucleus
CGTACT
sequence2
>IMAGE:275615 3', mRNA sequence
80-100,000 RNA
NNTCAAGTTTTATGATTTATTTAACTTGTGGAACAAAAATAAACCAGATTAACCACAACCATGCCTT
- isolate unique clones
gene
products
TTATCAAATGTATAAGANGTAAATATGAATCTTATATGACAAAATGTTTCATTCATTATAACAAATT
- sequence once from each end
AATAATCCTGTCAATNATATTTCTAAATTTTCCCCCAAATTCTAAGCAGAGTATGTAAATTGGAAGT
CTTATGCACGCTTAACTATCTTAACAAGCTTTGAGTGCAAGAGATTGANGAGTTCAAATCTGACCAA
GTTGATGTTGGATAAGAGAATTCTCTGCTCCCCACCTCTANGTTGCCAGCCCTC
make cDNA
library
80-100,000 unique
cDNA clones in library
Chimie de séquençage
Dye Terminator (6)
amorce
ADN
A G C T A T ...
TCGATA
réaction de
séquence
Taq
Electrophorèse
Gel plat / capillaire
AGCTA T
Analyse automatique
AGCT A
AGC T
AG C
AG
A
A
dépot
détection
G
C
T
A
T
Two Competing Strategies for
Human Genome
• (Hierarchical shotgun) [Public human
genome project]
• Whole-genome Shotgun [Celera project]
Sequencing
BAC:
Bacterial Artificial
Chromosome clone
Contig: joined
overlapping collection
of sequences or clones.
Whole-genome shotgun sequencing
Private company Celera used to sequence whole human genome
• Whole genome randomly
sheared three times
– Plasmid library constructed
with ~ 2kb inserts
– Plasmid library with ~10 kb
inserts
– BAC library with ~ 200 kb
inserts
• Computer program assembles
sequences into chromosomes
• No physical map construction
• Only one BAC library
• Reduces problems of repeat
sequences
Différentes étapes d’analyse de séquence
Vérification de la qualité de séquence
A
G
C
T
A
T
Elimination des séquences contaminantes
Blastn contre des banques de vecteurs, de bactéries, levures,…
Assemblage, Phred, Phrap, Consed
Identification des séquences potentiellement codantes
Comparaison avec les banques de données,
Logiciels de prédictions d’exons.
Entrez
NIH
NCBI
GenBan
k
EMBL
•Submissions
•Updates
CIB
NIG
DDBJ
•Submissions
•Updates
getentry
•Submissions
•Updates
EBI
SRS
EMBL
HTG Division: High Throughput
Genome Records
phase 1
Acc = AC008701
gi = 6601005
phase 2
Acc = AC008701
gi = 6671909
HTG
HTG
PRI
phase 3
Acc = AC008701
gi = 7328720
40,000 to > 350,000 bp
2.88 Gbp
2,851,330,913
Gene prediction
• Easy for procaryotes (single cell) – one
gene, one protein
• More difficult for eukaryotes (multicell) –
one gene, many proteins
• Very difficult for Human – short exons
separated by non-coding long introns
Gene recognition
• Coding region and non-coding region have
different sequence profiles
– coding region is “protected” from mutation and
is less random
• Gene recognition by sequence alignment
• Gene prediction by Hidden Markov Model
trained by set of known genes
• Many genes are homologs – similar in
vastly different organisms
Two predictions disagree
John B. Hogenesch, et al
Cell, Vol. 106, 413–415
August 24, 2001
“…predicted transcripts
collectively contain partial
matches to nearly all know
genes, but the novel genes
predicted by both groups
are largely non-overlapping
The Human Genome
Human genome content
Total length 3000 Mb
~ 40,000 genes (coding seq)
Gene sequences < 5%
Exons ~ 1.5% (coding)
Introns ~ 3.5% (noncoding)
Intergenic regions (junk) > 95%
Repeats > 50%
Global properties
• Pericentromeric and subtelomeric regions of
chromosomes filled with large recent transposable
elements
• Marked decline in the overall activity of
transposable elements or transposons
• Male mutation rate about twice female
– most mutation occurs in males
• Recombination rates much higher in distal regions
of chromosomes and on shorter chromosome arms
– > one crossover per chromosome arm in each
meiosis
Interspersed repeats: fixed transposable
elements copied to non-homologous regions.
Fig 17 transposables
Total 45%
Classes of transposable elements. LINE, long interspersed
element. SINE short interspersed element.
Genes are sometimes protected from repeats
Fig 21
Two regions of about 1 Mb on chromosomes 2 and 22. Red bars,
interspersed repeats; blue bars, exons of known genes. Note the
deficit of repeats in the HoxD cluster, which contains a collection
of genes with complex, interrelated regulation.
Important features of Human proteome
• 30,000–40,000 protein-coding genes
• Proteome (full set of proteins) more complex than
those of invertebrates.
– pre-existing components arranged into a richer
architectures.
• Hundreds of genes seem to come from horizontal
transfer from bacteria questionable
• Dozens of genes seem to come from transposable
elements.
Noncoding RNA genes
• Transfer RNAs (tRNAs) – adaptors that translate
triplet code of RNA into amino acid sequence of
proteins
• Ribosomal RNAs (rRNAs) – components of
ribosome
• Small nucleolar RNAs (snoRNAs) – RNA
processing and base modification in nucleolus
• Small nuclear RNAs (sncRNAs) - spliceosomes
Human races have similar genes
• Genome sequence centers have sequenced
significant portions of at least three races
• Range of polymorphisms within a race can
be much greater than the range of
differences between any two individuals of
different race
• Very few genes are race specific
Genome Sizes (MegaBases)
3500
3000
2500
2000
Size
1500
1000
600000
500
500000
0
E.coli
Yeast
Worm
Fly
Fugu
Human
400000
300000
200000
100000
0
Fly
Fugu
Human
Wheat
Amoeba
Fig 35a
Size distributions of exons in Human, Worm
and Fly. Human have shorter exons.
Fig 35c
Size distributions
of intons in
Human, Worm
and Fly.
Human have
longer introns.
• Complexity of proteome increase from
yeast to humans
– More genes
– Shuffling, increase, or decrease of functional
modules
– Alternative RNA splicing – humans exhibit
significantly more
– Chemical modification of proteins is higher in
humans
Combinatorial strategies
• At DNA level – T-cell receptor genes are encoded by a multiplicity of
gene segments
Fig. 10.21
• At RNA level –
splicing of exons in
different orders
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
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
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
Mouse
• known as “mini” humans
•Very similar physiological systems
•Share 90% of their genes
Questions Remain about the
Human Genome
– Difficult to precisely estimate number of genes
at this time
• Small genes are hard to identify
• Some genes are rarely expressed and do not have
normal codon usage patterns – thus hard to detect
Impact of HG on Biomedical
domain
Applications to medicine and
biology
• Disease genes
– human genomic sequence in public databases
allows rapid identification of disease genes in
silico
• Drug targets
– pharmaceutical industry has depended upon a
limited set of drug targets to develop new
therapies
– now can find new target in silico
• Basic biology
– basic physiology, cell biology…
Hérédité liée au chromosome X
Hérédité autosomique dominante
Mm
A1A2
A2A2
MM
Mm
A1A2
A1A2
Mm
A1A1
mm
mm
A1A1
A1A1
mm
Hérédité autosomique récessive
Les mutations ponctuelles
Création de codon stop
CAG
Gln
TAG
Positional cloning of genes
Disease
hromosomal
calisation
Function/
Protein
Gene
Disease
Function/
Protein
Chromosomal
localisation
Gene
Recherche de familles
-détermination du phénotype
-collecte d'ADN
anomalie cytogénétique
Cartographie génétique
-localisation chromosomique
-localisation fine
Cartographie physique
et
Isolement de clones spécifiques
Isolement de gène (s)
normal
Recherche de mutations
Etude fonctionnelle
muté
... CCT GAG GAG...
... CCT GTG GAG...
... Pro Glu Glu ...
... Pro Val Glu ...
1 to 10 years!
11083
a)
-1
1 1'
-I
I
9480
2
3 4
5
4405
6 7
8 9
10910
12 14
11 13
15
10
16
b)
I'
II
III IV
V
VI
VII
VIII
IX
X
c)
EYA1 gene structure
Bronchio-Oto-Renal Syndrome
XI XII XIV
XIII
XV
Recherche de familles
-détermination du phénotype
-collecte d'ADN
anomalie cytogénétique
Cartographie génétique
-localisation chromosomique
-localisation fine
Cartographie physique
et
Isolement de clones spécifiques
Isolement de gène (s)
normal
Recherche de mutations
Etude fonctionnelle
muté
... CCT GAG GAG ...
... CCT GTG GAG...
... Pro Glu Glu ...
... Pro Val Glu ...
.... From in vivo to in vitro to in silico
Problème de pénétrance
Sous le mode dominant
Famille EBDD-I
I
II
III
4
3
3
m
7
7
3
3
M
8
IV
2
V
3
3
M
8
3
3
M
7
3 3
3 3
m M
7 10
3
3
M
8
3
3
M
7
3 3
3 3
M M
7 10
2 4
2 4
M M
11 5
4
3 3
3 3
m M
7 10
3
3
m
M
7
5
2
M
9
2 3
2 3
M M
11 8
3 3
3 3
m M
6 10
3 3
3 3
M M
10 8
3
3
m
6
3
3
3
M
8
Environnement?
Individu 1
G1 Malade
Individu 2
??
G1  Sain
Maladie à pénétrance incomplète et expressivité variable
G1/1
Epissage alternatif
Non Sens mRNA decay
Mécanisme de régulation
post-transcriptionnelle
G2
Gènes modificateurs
G1/2
G3
Complex /common disorders: multifactoriel
Environemental factors
Genetic factors
Complex Diseases : Genes & Environment
Environmental
Effect
Genetic
Component
The potential benefits of identifying genes/variations
involved in disease
Predisposition

Improve the understanding of disease
etiology and mechanism

Early disease risk assessment

Discover new drug targets

Disease prevention

population or ethnic group variability
Targeted screening
Prevention
Diagnosis
Therapy
Predictive
medicine
Pharmacogenomics:
The Promise of Personalized Medicine
O GOD!
CREDIT: JOE SUTLIFF. SCIENCE, 2001
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Acknowledgement: the following presentation has
been prepared on the basis of
Internet resources.
International Human Genome Sequencing
Consortium. Initial sequencing and analysis of the
human genome. Nature 409, 860–921 (2001).
Venter, J. C. et al. The sequence of the human
genome. Science 291, 1304–1351 (2001).
International Human Genome Sequencing
Consortium. Finishing the euchromatic sequence
of the human genome., Nature 431: 931-945
(2004).
Thank you