topics in (nano) biotechnology human genome project lecture 9
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TOPICS IN (NANO) BIOTECHNOLOGYHuman Genome Project
Lecture 9
15th April, 2004
PhD Course
• Human Genome organisation – Human genome contains ~ 40,000 genes– Nuclear genome 3000 Mb– 30,000 to 40,000 structural genes– 24 different types of DNA duplex– 22 autosomes, 2 sex chromosomes
Remember what the genome is?
Human Genome
Nuclear
Mitochondrial
• DEFINITION: The entire genetic makeup of the human cell
nucleus.
Includes non-coding sequences located between genes, which makes up the vast majority of the DNA in the genome (~95%)
Let’s define it.
• DEFINITION: The Human Genome Project is a multi-year effort to find
all of the genes on every chromosome in the human body and to determine their biochemical nature.
• SPECIFIC GOALS: – Identify all the genes in human DNA– Determine the sequences of the 3 billion bps– Save the information in databases– Improve tools for data analysis– Transfer related technologies to the private sector– Address the ethical, legal and social issues that may arise from
the project
What is the Human Genome Project?
Sequencing the Human Genome
Why are genome projects important? – The key to continued development of molecular biology, genetics and
molecular life sciences– a catalogue containing a description of the sequence of every gene in
a genome is seen as immensely valuable, even if the function is not known
– aid in isolation and utilisation of new genes– stretch technology to its limits
What is the potential impact?– Improved diagnosis/therapy of disease– prokaryotic genomes: vaccine design, exploration of new microbial
energy sources– plant and animal genomes: enhance agriculture
Importance and Impact
• The Whitehead Institute for Biomedical Research (Eric Lander, Massachusetts, USA)
• The Sanger Centre (Cambridge, GB)• Baylor College of Medicine (Richard Gibbs, Houston,
USA)• Washington University (Robert Wayerston, St. Louis,
USA)• DoEs Joint Genome Institute, JGI (Trevor Hawkins,
Walnut Creek, California, USA)
• …and other genome centres worldwide...
The primary HGP sequencing sites
The Human Genome Project- Timelines -
1985
19861987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
1st HumanChromosomeSequenced
CongressRecommends15 year HGP
Project
HGPOfficiallyBegins
LowResolution
LinkageMap of HGPublished
High ResolutionMaps ofSpecific
ChromosomesAnnounced
E.coliGenome
Completed
CeleraGenomicsFormed
Conferenceon HGP
Feasibility
S. cerevisiaeGenome
CompletedC. elegansGenome
Completed
FlyGenome
Completed
HumanGenome
Published
President announcesgenome working draft completed
Science (Feb. 16, 2001) - CeleraNature (Feb. 15, 2001) - HGP
• 1983 Los Alamos Labs and Lawrence Livermore National Labs, both under the DOE, begin production of DNA cosmid libraries for single chromosomes
• 1986 DOE announces HUMAN GENOME PROJECT
• 1987 DOE advisory committee recommends a 15-year multi-disciplinary undertaking to map and sequence the human genome. NHS begins funding of genome projects
• 1988 Recognition of need for concerted effort. HUGO founded (Human Genome Organisation) to coordinate international efforts DOE and NIH sign the Memorandum of Understanding outlining plans for co-operation
History of Human Genome Project
• 1990 DOE and NIH present joint 5-year Human Genome Project to Congress. The 15 year project formally begins
• 1991 Genome Database (GDB) established
• 1992 Low resolution genetic linkage map of entire human genome published, High resolution map of Y and chromosome 21 published
• 1993 DOE and NIH revise 5-year goals– IMAGE consortium established to co-ordinate efficient mapping and
sequencing of gene-representing cDNAs (Integrated Molecular Analysis of Genomes and their Expression)
History of Human Genome Project
• 1994 Genetic-mapping 5-year goal achieved 1 year ahead of schedule – Genetic Privacy Act proposed to regulate collection, analysis, sorage and use
of DNA samples (endorsed by ELSI)– LLNL chromosome paints commercialised
• 1994-98 Tons of stuff happens that continues to advance the project
• 1998 Celera Genomics formed– New 5-year plan by DOE and NIH
• 1999 First chromosome completely sequenced (Chromosome 22)• 2000 June 6, HGP and Celera announce they had completed ~
97% of the human genome.
History of Human Genome Project
• James Watson Original Head of HGP
• Francis Collins
• Craig Venter
People of Human Genome Project
• The Sanger dideoxy termination method (remember?)– Nucleotide analogs (ddNTP) are incorporated into DNA during its synthesis
together with normal nucleotides (dNTP) - when a ddNTP is inserted, the reaction stops = chain termination
• Radioactively labeled ddNTPs– four different reactions are performed, each reaction contains ddA, ddG, ddC, ddT– Autoradiography enable analysis of different fragment lengths which correspond to
different termination points
• Fluorescently labeled ddNTPS– one reaction carried out, all four ddNTPs are incorporated but each ddNTP is
labelled with a different fluourescent dye– automated DNA sequencers interfaced with computers determine the order of the
dyes and hence the DNA sequence
DNA sequencing
• The Gene Linkage Map
• Identifies position of genes by locating marker base sequences associated with RFLPs
• Based on how close together two genes are– the closer together two genes are, the less likely they are to separate during
meiotic recombination in germ cells– the frequency of recombination between two genes can help to decipher the
distance between them on a gene linkage map– genes separated by more than 50cM (50 million bps) are not considered linked
• Studies of families affected by genetic disease have proven useful for genetic linkage analysis
Mapping the Human Genome: Low Resolution Mapping
• The Physical Map
• Provides the actual distances in bps between genes on a given chromosome
• Prepared by aligning the sequences of adjacent DNA fragments from small overlapping clones to form a contiguous map (a contig map)
• Sequence tag sites (STGs) mark sites on chromosomes and help to locate adjacent segments of DNA– if two DNA fragments share an STS they overlap and are contiguous
Mapping the Human Genome: High Resolution Mapping
• The aim, obviously, is to determine the entire genome sequence
• A sequence has to be constructed from a series of shorter fragments
• Shotgun technique– break molecule into smaller fragments– determine sequence of each one– use a computer to search for overlaps and build a master
sequence
Determining genome sequences
• Analysis of DNA sequences of chromosomes by extending the sequenced region a little bit further each time until the tips of the chromosome are reached
• The next round of sequencing is based on the results of the previous round by synthesising appropriate DNA primers to extend further
Chromosome walking
• The International Human Genome Sequencing Consortium published their results in Nature, 409(6822):860-921, 2001– Initial Sequencing and Analysis of the Human Genome
• Celera Genomics published their results in Science, 291(5507), 1304-1351, 2001– The Sequence of the Human Genome
Results of Human Genome Project
• The Human genome contains 3146.7 million bases
• The average gene size is 3,000 bases
• Total number of genes is between 30-40,000
• The order of 99.9% of the nucleotides is the same in all people
• Of the discovered genes, the function for more than half is unknown
• > 30 genes have already been associated with human disease (e.g. Cancer, blindness)
Results of Human Genome Project
• About 2% of the genome encodes instructions for the synthesis of proteins
• Repeated sequenes make up 50% of the genome
• There are urban centres that are gene rich: stretches of C and G bases repeats (CpG islands) occur adjacent to gene rich areas
• Chromosome 1 has 2,968 genes; the Y has 231
• Humans:– only twice number of genes of the fly– 3 times as many proteins as fly or worm– share the same gene families as fly or worm
Results of Human Genome Project
• Microbial genomes– Haemophilus influenzae– Escherichia coli– Bacillus subtilus– Helicobacter pylori– Streptococcus pneumonaie– Saacharomyces cerevisiae– Archaeglobus fulgidus– Methanbacterium thermoautotropicum– Methanococcus jannaschil– Mycobacterium tubercolosis– Staphylococcus aureus
• and more…..
• Insect genomes– Arabidopsis thaliana– Drosophilia melanogaster– Mus musculus
Completed genomes
Organism Genome Size (Bases) Estimated GenesHuman (Homo sapiens) 3 billion 30,000
Laboratory mouse (M. musculus) 2.6 billion 30,000
Mustard weed (A. thaliana) 100 million 25,000
Roundworm (C. elegans) 97 million 19,000
Fruit fly (D. melanogaster) 137 million 13,000
Yeast (S. cerevisiae) 12.1 million 6,000
Bacterium (E. coli) 4.6 million 3,200
Human immunodeficiency virus (HIV) 9700 9
Results of Human Genome Project
• The DOE and the NIH spend between 3-5% of their annual HGP budgets toward studying the ELSI associated with availability of genetic information
• This budget is the world’s largest bioethics program, and has become a worldwide model
• Examples of ELSI are:– privacy legislation– gene testing– patenting– forensics– behavioural genetics– genetics in the courtroom
Ethical, legal and societal issues
• Who should have access to this information?– Employers– Insurers– Schools– Courts– Adoption agencies– Military
• Philosophical Implications– Human responsibility– Free will versus genetic determinism
• Who owns and controls genetic information?– How is privacy and confidentiality managed?
• Psychological impact and stigmatisation– Effects on the individual– Effects on society’s perceptions and expectations of the individual
Societal Concerns
• Clinical Issues– Growing demand to educate health care workers – Public needs to gain scientific literary and understand the capabilities, limitations
and risks– Standards need to be established including quality controls to ensure accuracy
and reliability– Regulations?
• Genetic Counselling– Informed consent for complex procedures– Counseling about risks, limitations and reliability of genetic screening techniques– Reproductive decision making based on genetic information– Reproductive rights
• Multifactorial diseases and environmental factors– Genetic predispositions do not mandate disease development– Caution must be exercised when correlating genetic tests with predictions
Clinical Issues
• Who owns genes and DNA sequences?– The person (or company) who discovered it, or the
person whose body it came from– Should genetic information be the property of
humanity?– Is it ethical to charge someone for access to a
database of genetic information?
• Is it time to raise the bar concerning patents?– Will patent protection slow the advance of research
and be detrimental to society as a whole in the long run
Commercialisation and patents
Medicine
Bioinformatics
Biotechnology
DNA chip technology
Gene therapy applications
Diagnostic & therapeutic applications
Medicine & pharmaceutical industries
Agriculture & Bioremediation Industries
Microarray Technology
Proteomics
Pharmacogenomics
Preventative measures
Developmental Biology
Evolutionary & Comparative Biologists
Benefits of Human Genome Project
• These occur when a single nucleotide in the genome sequence is altered (1 bp difference)
• 66% of SNPs involve a C to T change and they occur every 100-300 bases in either coding or non-coding regions
• Evolutionary stable, there are between 2 and 3 million SNPs in the human genome
• Many SNPs have no effect on cell function, but: – some SNPs could be responsible for variations in how many humans
respond to disease, environmental factors, drugs and other therapies– SNPs may help identify multiple genes involved in complex diseases
Single nucleotide polymorphisms
• SNPs are NOT the same things as alleles (or so we believe so far)
• Researchers have found that most SNPs are not responsible for a disease state
– They serve as markers for pinpointing a disease on the human genome map, being located near a gene found to be associated with a certain disease
– Occasionally, SNPs may actually cause a disease and can to be used to search for and isolate the disease-causing gene
– SNPs travel together - i.e. Variations in DNA are linked
• To date, Celera & Orchid Biosciences have largest databases
Single nucleotide polymorphisms
• Goals:• Develop large scale technologies• Identify common variants in the coding regions• Create a SNP of at least 100,000 markers• Develop the intellectual foundation for studies of sequence variation• Create public resources of DNA samples and cell lines
• SNP Consortium:• Ten large pharmaceutical companies and the UK Wellcome Trust• Headed by Arthur Holden• Find and map 300,000 common SNPs• Generate a widely accepted, high-quality, publically available map
Single nucleotide polymorphisms
• High quality genome sequencing and annotation (2003)• Complete sequencing the genomes of other model organisms (e.g.
Mouse)
• The next step: Functional Genomics• Determine what our genes do through systematic studies of function
on a large scale– Transcriptomics - Comparative analysis of mRNA expression /splicing– Proteomics - Comparative analysis of protein expression and post-translational
modifications– Structural genomics - Determine 3-D structures of key family members– Intervention studies - Effects of inhibiting gene expression– Comparative genomics - Analysis of DNA sequence patterns of humans and
well studies model organisms
What next?
•Is it ethical for the government to invest such a large fraction of its research budget in the Human Genome Project when the result is denial of funding for other worthy projects?
•Do such possibilities as finding the cause of many genetic diseases and identifying criminals outweigh such concerns as the possibility of using the genetic information to renew the types of eugenics programs practiced before and during World War II or to deny health insurance coverage?
•Given the huge investment of public funds in the Human Genome project, is the government responsible to assure that the benefits will be equally available to people of all socioeconomic levels and ethnic or racial backgrounds?
•Should genetic testing be made available to people who have not received the genetics counseling they need in order to fully understand and respond to the results?
• Whole genome – Once the whole genome is truly known and the whole
genome sequences become available for an organism, the challenge turns from identifying parts to understanding function
• Functional genomics – The post-genomic era is defined as functional genomics– Assignation of function to identified genes– Organisation and control of genetic pathways that come
together to make up the physiology of an organism
Functional Genomics
• 42% of human genes of unknown function have been found in the human genome
• assigning function to these genes using systematic high throughput methods is required
Functional Genomics
The Periodic Table: Functional grouping of Chemical Elements
Biologist’s Periodic Table
Organism’s Gene
System for classifying
genes
• Will not be two-dimensional
• Will reflect similarities at diverse levels– Primary DNA sequence in coding and regulatory regions
– Polymorphic variation within a species or subgroup
– Time and place of expression of RNAs during development, physiological response and disease
– Subcellular localisation and intermolecular interaction of protein products
• Array of hope? Arrays offer hope for global views of biological
processes– Systematic way to study DNA and RNA variation– Standard tool for molecular biology research & clinical
diagnostics– Labelled nucleic acid molecules can be used to interrogate
nucleic acid molecules attached to solid support (remember Southern Blotting?)
(Refer to January 1999, Nature Genetics Supplement, Volume 21)
Gene Expression analysis
• DNA chips Also known as gene chips, biochips, microarrays…basically DNA-covered pieces of glass (or plastic) capable of simultaneously analysing thousands of genes at a time – they can be high density arrays of oligonucleotides or cDNA
• Chips allow the monitoring of mRNA expression on a big scale (i.e many many genes at the same time)
Gene Expression analysis
Pre-1995, Northern Blots used to look at gene expression
Gene Expression analysis
Incyte
Affymetrix
Gene Expression analysis
Determining gene function
sequence homology
sequence motif
tissue distribution
chromsme localisation
function . expression in disease
biochemical assays
proteomics .
expression in models
Protein synthesis
RNA synthesis and processing
Alternatively spliced mRNA
• DEFINITION: The mRNA collection content, present at any given
moment in a cell or a tissue, and its behaviour over time and cell states
(Adam Sartel, COMPUGEN).
The complete collection of mRNAs and their alternative splice forms is sometimes referred to as the trancriptome. The transcriptome is teh set of instructions for creating all of the different proteins found in an organism.
(From Genome to Transcriptome, Incyte)
The transcriptome
Genome, proteome and transcriptome
The Proteome
The Genome
- Index to a range of possible proteins - Useful as a map and for inter-organisms analysis
- Describes what actually happens in the cell - Complex tools, partial results
• Discovery of new proteins: – that are present in specific tissues– that have specific cell locations– that respond to specific cell states
• Discovery of new variants:– of important genes– that work to increase/decrease the activity of the ‘native’ protein
• The transcriptome reflects tissue source (cell type, organ) and also tissue activity and state such as the stage of development, growth and death, cell cycle, diseased or healthy, response to therapy or stress..
Use of transcriptome analysis
• Proteomics…where the genome hits the road – Proteomics refers to the simultaneous, large scale analysis of
all (or many) of the proteins made in a cell at one time to get a global picture of what proteins are made in cells and when
– Hopefully then we can determine the ‘whys’ and what we can thus do about it – very important for drug development
– The proteome is the protein complement encoded by a genome and the term was first proposed by an Australian post-doc, Marc Wilkins in 1994
Beyond genomics…proteomics
Beyond the genome: Proteomics• Genomics involves study of mRNA expression-the full set of
genetic information in an organism contains the recipes for making proteins
• Proteins constitute the “bricks and mortar” of cells and do most of the work
• Proteins distinguish various types of cells, since all cells have essentially the same “Genome” their differences are dictated by which genes are active and the corresponding proteins that are made
• Similarly, diseased cells may produce dissimilar proteins to healthy cells
• However task of studying proteins is often more difficult than genes (e.g. post-translational modifications can dramatically alter protein function)
• Identification of all the proteins made in a given cell, tissue or organism
• Identification of the intracellular networks associated with these proteins
• Identification of the precise 3D-structure of relevant proteins to enable researchers to identify potential drug targets to turn protein “on or off”
• Proteomics very much requires a coordinated focus involving physicists, chemists, biologists and computer scientists
Beyond the genome: Proteomics
• Major challenge-how do we go from the treasure chest of information yielded by genomics in understanding cellular function
• Genomics based approaches initially use computer-based similarity searches against proteins of known function
• Results may allow some broad inferences to be made about possible function
• However, a significant percentage (>30%) of the sequences thus far ascertained seem to code for proteins that are unrelated at this level to proteins of known function
Beyond the genome: Proteomics
• Beyond the genetic make-up of an individual or organism, many other factors determine gene and ultimately protein expression and therefore affect proteins directly
• These include environmental factors such as pH, hypoxia, drug treatment to name a few
• Examination of the genome alone can not take into account complex multigenic processes such as ageing, stress, disease or the fact that the cellular phenotype is influenced by the networks created by interaction between pathways that are regulated in a coordinated way or that overlap
Beyond the genome: Proteomics
• Genomic analysis has certainly provided us with much insight into the possible role of particular genes in disease
• However proteins are the functional output of the cell and their dynamic nature in specific biological contexts is critical
• The expression or function of proteins is modulated at many diverse points from transcription to post-translation and very little of this can be predicted from a simple analysis of nucleic acids alone
• There is generally poor correlation between the abundance of mRNA transcribed from the DNA and the respective proteins translated from that mRNA
• Furthermore, transcript splicing can yield different protein forms• Proteins can undergo extensive modifications such as glycosylation,
acetylation, and phosphorylation which can lead to multiple protein products from the same gene
Beyond the genome: Proteomics
Proteomics Tools• The core methodologies for displaying the proteome
are a combination of advanced separation techniques principally involving two-dimensional electrophoresis (2D-GE) and mass spectrometry
2D-GE: basic methodology• Sample (tissue, serum, cell extract) is solubilized and the
proteins are denatured into polypeptide components• This mixture is separated by isoelectric focusing (IEF); on the
application of a current, the charged polypeptide subunits migrate in a polyacrylamide gel strip that contains an immobilized pH gradient until they reach the pH at which their overall charge is neutral (isoelctric point or pI), hence producing a gel strip with distinct protein bands along its length
• This strip is applied to the edge of a rectangular slab of polyacrylamide gel containing SDS. The focused polypeptides migrate in an electric current into the second gel and undergo separation on the basis of their molecular size
• The resultant gel is stained (Coomassie, silver, fluorescent stains) and spots are visualized by eye or an imager. Typically 1000-3000 spots can be visualized with silver. Complementary techniques, e.g. immunoblotting allow greater sensitivity for specific molecules.
• Multiple forms of individual proteins can be visualized and the particular subset of proteins examined from the proteome is determined by factors such as initial solubilization conditions, pH range of the IPG and gel gradient
2D-GE: basic methodology
General schematic of 2D-PAGE for protein identification in Toxicology
Sample growth Sample solubilization
Isoelectric focusing (IPG)
2D-PAGE
Image analysisImmunoblot (Western)
Isolation of spots of interest
Trypsin digestion of proteins
MS analysis of tryptic fragments
Identification of proteins
General strategy for proteomic analysis
Nature of IPG determines spot location on 2D-PAGE
Limitations of 2D-GE
• In the large scale analysis of proteomics, 2D-GE has been the major workhorse over the last 20 years-its unique application in being able to distinguish post-translational modifications and is analytically quantitative
• However despite the significant improvements (e.g. immobilized pH gradients) to the technique and its coupling with MS analysis it is still difficult to automate
• Although at first glance the resolution of 2D seems very impressive, it still lags behind the enormous diversity of proteins and thus comigrating protein spots are not uncommon
• This is especially of concern when trying to distinguish between highly abundant proteins e.g. actin (108 molecules/cell) and low abundant like transcription factors (100-1000)-this is beyond the dynamic range of 2D
• Enrichment or prefractionation can often overcome such discrepancies
• Chemical heterogeneity of proteins also presents a major limitation
• Thus the full range of pIs and MWs of proteins exceeds what can routinely be analyzed on 2D-GE. However improvements to IPGs is expected to overcome some of these constraints and greatly imrpove the coverage of the entire proteome of the cell
• Problems liked with extraction and solubilization of proteins prior to 2D-GE present an even greater challenge-especially for extremely hydrophobic proteins, such as membrane and nuclear proteins. Again recent advances in buffer composition has diminished the scale of this problem
Limitations of 2D-GE
Protein identification and characterization
• Specialized imaging software allows for a more detailed analysis of spot identification and comparison between gels, and treatments
• By a process of subtraction, differences (e.g. presence, absence, or intensity of proteins or different forms) between healthy and diseased samples can be revealed
• Cross-references to protein databases allow assignment by known pIs and apparent molecular size. Ultimate protein identification requires spot digestion (enzymatic) and analysis of charge and mass by mass spectrometry (MS)
• Spot cutter tools can be coupled to image analysis tools and in gel tryptic digestion techniques in 96 or 384 well format can greatly reduce the bottle-neck in sample identification by MS
Protein analysis by MS• Compared to sequencing, MS is more sensitive (femtomole to
attomole concentrations) and is higher throughput• Digestion of excised spot with trypsin results in a mixture of peptides.
These are ionized by electrospray ionization from liquid state or matrix-assisted laser desorption ionization from solid state (MALDI-TOF) and the mass of the ions is measured by various coupled analyzers (e.g. time of flight measures the time for ions to travel from the source to the detector, resulting in a peptide fingerprint
• The resultant signature is compared with the peptide masses predicted from theoretical digestion of protein sequences found in databases-identification of protein!
• Tandem MS allows one to obtain actual protein sequence information-discrete peptide ions can be selected and further fragmented, and complex algorithms employed to correlate exp data with database derived peptide sequences
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