GENOMICS AND PROTEOMICS ANALYSES ......GENOMICS Genetics: the science of genes , heredity , and the variation of organisms. In modern research, genetics provides tools in the investigation

Dr J Boateng BIOT 1011 Bioinformatics

GENOMICS AND PROTEOMICS ANALYSES

Dr Joshua Boateng

21 /11 / 2011


The biotechnology/IT

market will increase

at a compound annual

growth rate (CAGR) of

24% to nearly $38

billion by 2006.

– Source: IDC Research

Biotech and pharmaceutical companies

spent $10 billion on hardware, software,

and services in 2002.

–Source: Gartner

Reference: Prof. A.S. Kolaskar Vice Chancellor, University of Pune


GENOMICSGenetics: the science of genes, heredity, and the variation of organisms. In modern research, genetics provides tools in the investigation of the function of a particular gene, e.g. analysis of genetic interactions.

Genomics: the study of large-scale genetic patterns across the genome for a given species. It deals with the systematic use of genome information to provide answers in biology, medicine, and industry.

The study of sequences, gene organization & mutations at the DNA level i.e. the study of information flow within a cell

Genomics has the potential of offering new therapeutic methods for the treatment of some diseases, as well as new diagnostic methods.

Major tools and methods related to genomics are bioinformatics, genetic analysis, measurement of gene expression, and determination of gene function.



GENOME COMPARISONS

Species Chrom. Genes Base pairs

Humans 46 28-35,000 3.1 billion

Mouse 40 22.5-30000 3.1 billion

Puffer fish 44 31000 2.7 million

Malaria Mosquito 6 14000 365 million

Fruit Fly 8 14000 137 million

Roundworm 12 19000 97 million

E. Coli 1 5000 4.1 million


GENOMIC ANALYSIS• Many diverse studies require the determination

of the abundance of large numbers of specific DNA or RNA molecules in complex mixtures, including, for example, the determination of the changes in mRNA levels of many genes

– Genome analysis entails the prediction of genes in uncharacterized genomic sequences.

– The 21st century has seen the announcement of the draft version of the human genome sequence. Model organisms have been sequenced in both the plant and animal kingdoms.


GENOMIC ANALSIS• However, the pace of genome annotation is not

matching the pace of genome sequencing.

• Experimental genome annotation is slow and time consuming. The demand is to be able to develop computational tools for gene prediction.

• Computational gene prediction is relatively simple for the prokaryotes where all the genes are converted into the corresponding mRNA and then into proteins.

• The process is more complex for eukaryotic cells where the coding DNA sequence is interrupted by random sequences called introns.


BIOLOGICAL QUESTIONSSome of the questions biologists want to answer

today are:

• What part of and DNA sequence codes for a protein and what part of it is junk DNA?

• Classify the junk DNA as intron, untranslated region, transposons, dead genes, regulatory elements.

• Divide a newly sequenced genome into the genes (coding) and the non-coding regions.


Biological Research in 21st Century

“The new paradigm, now emerging is that all the 'genes' will be known (in the sense of being resident in databases available electronically), and that the starting "point of a biological investigation will be theoretical.”

- Walter Gilbert


IMPORTANCE OF GENOME ANALYSIS

• The importance of genome analysis can be understood by comparing the human and chimpanzee genomes.

• The chimp and human genomes vary by an average of just 2% i.e. just about 160 enzymes. A complete genome analysis of the two genomes would give a strong insight into the various mechanisms responsible for the differences.


COMPLEXITY IS AN UNDERSTATEMENT?


GENOMIC ANALYSIS_ basics• Techniques used to estimate the relative

abundance of two or more sets of mRNA

– differential screening of cDNA libraries,

– subtractive hybridization,

– differential display,

• However, more advanced methods have been recently developed.


GENOMICS ANALYSIS_Advances

• Advanced methods are particularly amenable to organisms whose entire genome sequences are known, such as S. cerevisiae.

• It is now practicable to investigate changes of mRNA levels of all yeast open reading frames (ORFs) in one experiment.


Advanced genomic analysis techniques• DNA sequencing

• DNA microarray technology– analysis of gene expression profiles at the mRNA level

• Bioinformatic tools to organize and analyze such data

• Chip-based analysis of samples

• Models of gene networks


Microarray Technology


Post-genomic Era• Series of “omics”

– Comparative genomics

– Structural and functional genomics

– Transriptomics

– Proteomics

– Metabolomics


Bioinformatics tools needed for analysis of

data from these “omics”…


Data Mining

Development of new tools for data mining

– Sequence alignment

– Genome sequencing

– Genome comparison

– Micro array data analysis

– Proteomics data analysis

– Small molecular array analysis

To derive “information” and gain “knowledge” from the data



COMPARATIVE GENOMICS

• Analyzing & comparing genetic material from different species to study evolution, gene function, and inherited disease

• Understand the uniqueness between different species

• Comparative genomics involves the use of computer programs that can line up multiple genomes and look for regions of similarity among them.


When we BLAST a sequence is that comparative genomics?

Difference is in Scale and Direction

• One or several genes

compared against all

other known genes.

• Use genome to

inform us about the

entire organism.

• Use information from

many genomes to learn

more about the

individual genes.

• Entire Genome

compared to other

entire genomes.

Other “omics” Comparative


Background on Comparative Genomic Analysis

• Sequencing the genomes of the human, the mouse and a wide variety of other organisms - from yeast to chimpanzees –

• Driving force for the development of new field of biological research called -comparative genomics.



BACKGROUND• Comparing the human genome with the

genomes of different organisms helps to better understand gene structure and function and thereby develop new strategies in the battle against human disease.

• Comparative genomics also provides a powerful new tool for studying evolutionary changes among organisms.

• This helps to identify the genes that are conserved among species along with the genes that give each organism its own unique characteristics.

• Using computer-based analysis to zero in on the genomic features that have been preserved in multiple organisms over millions of years, researchers will be able to pinpoint the signals that control gene function.

• This should in turn translate into innovative approaches for treating human disease and improving human health.



BACKGROUND

• The evolutionary perspective may prove extremely helpful in understanding disease susceptibility. For example, chimpanzees do not suffer from some of the diseases that strike humans, such as malaria and AIDS.

• A comparison of the sequence of genes involved in disease susceptibility may reveal the reasons for this species barrier, thereby suggesting new pathways for prevention of human disease.


BACKGROUND• Although living creatures look and behave in

many different ways, all of their genomes consist of DNA, the chemical chain that makes up the genes that code for thousands of different kinds of proteins.

• Precisely which protein is produced by a given gene is determined by the sequence in which four chemical building blocks - adenine (A), thymine (T), cytosine (C) and guanine (G) - are laid out along DNA's double-helix structure.


BACKGROUND• In order for researchers to most efficiently use an

organism's genome in comparative studies, data about its DNA must be in large, contiguous segments, anchored to chromosomes and, ideally, fully sequenced.

• Furthermore, the data needs to be organized for easy access and high-speed analysis by sophisticated computer software.

• Organisms that have been completely sequenced include: mouse (Mus musculus), human (Homo sapiens), fruit fly (Drosophila melanogaster); and ....................


BACKGROUND

• The fledgling field of comparative genomics has already yielded some dramatic results.

• For example, a March 2000 study comparing the fruit fly genome with the human genome discovered that about 60 percent of genes are conserved between fly and human.

• Simply put, the two organisms appear to share a core set of genes. Researchers have found that two-thirds of human cancer genes have counterparts in the fruit fly.


BACKGROUND• More surprisingly, when scientists inserted a

human gene associated with early-onset Parkinson's disease into fruit flies, they displayed symptoms similar to those seen in humans with the disorder.

• This raises the possibility that the tiny insects could serve as a new model for testing therapies aimed at Parkinson's.


Comparative GenomicsWhat one should look for?

Human

P. falciparum

Mosquito

Proteins that are shared by –

•All genomes

•Exclusively by Human & P.f.

•Exclusively by Human &

Mosquito

•Exclusively by P.f. & Mosquito

Unique proteins in –

Human

P.f. Targets for

anti-malarial drugs

Mosquito


Comparative Gene Prediction• GenScan : ab initio gene prediction.

• GeneWise, Procrustes : homology guided.

• Rosseta, SGP1 (Syntetic Gene Prediction), CEM (Conserved Exon Method) : gene prediction and sequence alignment are clearly separated.

• GenomeScan : Ab Initio modified by BLAST homologies.

• SGP-2, TwinScan, SLAM, DoubleScan : modification of GenScan scoring schema to incorporate similarity to known proteins.


•The term proteome, coined in 1994.A linguistic equivalent to the concept of genome

Proteome - complete set of proteins that is

expressed, and modified by the entire genome in the lifetime of a cell.

Practical: the complement of proteins expressed

by a cell at any one time.

Proteome – by the dictionary


Proteomics (Practical) - the study of the proteome using technologies of large-scale protein separation and identification.

Large scale separation : 2DE Liquid Chromatography

Identification : MALDI MSTandem MS/MSFT-MS …..

Proteomics – by the dictionary

• http:www.bio-itworld.com/archive/031704/horizons_horizons_comm.html



Proteomics according to MedlineDevelopment of Proteomics

1730

From 220 publications in the previous millennium (‘94-’99)To 21,350 (!!!) publications in this millennium (‘00-’05)

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1997 1998 1999 2000 2001 2002 2003 2004

Papers

Reviews


Proteomics –by GoogleTHE REALISTIC TRUTH.

Proteomics 886,000 hits (2004)4,700,000 hits (2005)

Genomics 2,070,000 hits (2004)16,000,000 hits (2005)


Comparing Proteomics & Genomics

Genome Genomics

analysis

proteome Proteome

analysis

DNA

Nc-RNA

mRNA Coding DNA Proteins

Peptides

Glyco, other modifications

linear Dynamic

Up/down

3D Dynamic

Up/ down

variants

Completion

Archived

(EST, cDNA, GEO

No notion of completion

Poorly archived


Proteomics – GenomicsMore differences…

Gene/ RNA

dynamic

Protein

dynamic

Stable molecules

Handling cheap/ easy

Minimal modification

Works in isolation

Fragile molecules

Handling dependent

Labile modification

Protein-interaction

Localization dependent

Handle

Tech

HTP

Sequencing (established) MS related (not yet)

DNA array / genotyping/ expression / CGH/

Protein Chip (not yet)

Antibodies array (not yet)


Proteomics:– Original definition: study of the proteins

encoded by the genome of a biological sample

– Current definition: study of the whole protein complement of a biological sample (cell, tissue, animal, biological fluid [urine, serum])

– Usually involves high resolution separation of polypeptides at front-end, followed by mass spectrometry identification and analysis


Challenges facing Proteomic TechnologiesChallenges facing Proteomic Technologies

• Limited/variable sample material

• Sample degradation (occurs rapidly, even during sample preparation)

• Vast dynamic range required

• Post-translational modifications (often skew results)

• Specificity among tissue, developmental and temporal stages

• Perturbations by environmental (disease/drugs) conditions

• Researchers have deemed sequencing the genome “easy,” as PCR was able to assist in overcoming many of these issues in genomics.


The Proteomics Tool Kit• technologies for separating and

visualizing proteins and peptides

• technologies for assessing protein-protein interactions

• technologies for identifying proteins*

• technologies for quantifying protein expression*

• bioinformatic tools for assessment and communication


Proteomic TechnologiesProteomic Technologies

• Amino Acid Composition

• Array-based Proteomics

• 2D PAGE

• Mass Spectrometry

• Structural Proteomics

• Informatics (and the challenges facing the

Human Proteome Project)


Amino Acid Composition (Edmund)Amino Acid Composition (Edmund)

• Pioneering method of obtaining information from proteins.

• Cumbersome and tedious by today’s standards.

• Requires the use of terrible smelling ß-mercaptoethanol.

• Not “high-throughput” by today’s standards, hence, comp is no longer the most widely used technique.


Protein Sequencingstep 1, fragmenting into peptides

Protein Sequencingstep 1, fragmenting into peptides


Protein Sequencingstep 2, sequencing the peptides by Edmund degradation.

Separation by HPLC and detect by absorbance at 269nm.


Array-based ProteomicsArray-based Proteomics

• Employ two-hybrid assays

• Use GFP, FRET, and GST– GFP = green florescent protein

– FRET = florescence resonance energy transfer

– GST = glutathione S-transferase, a well characterized protein used as a marker protein.





• Offer a high-throughput technique for proteome analysis.

• These small plates are able to hold many different samples at a time.

• Current research is ongoing in an attempt to interface array methodologies with Mass Spectrometry at ORNL.


2D PAGE2D PAGE• 2-D gel electrophoresis is a multi-step procedure that

can be used to separate hundreds to thousands of proteins with extremely high resolution.

• It works by separation of proteins by their pI's in one dimension using an immobilized pH gradient (first dimension: isoelectric focusing) and then by their MW's in the second dimension.

• The core technology of proteomics is 2-DE

• At present, there is no other technique that is capable of simultaneously resolving thousands of proteins in one separation procedure. (sited in 2000)


Traditional IEF procedure:

• Iso electric focusing (IEF) in run in thin polyacrylamide gel rods in glass or plastic tubes.

• Gel rods containing: 1. urea, 2. detergent, 3. reductant, and 4. carrier ampholytes (form pH gradient).

• Problem: 1. tedious. 2. not reproducible.

Evolution of 2-DE methodology

In the past


SDS-PAGE Gel size:

• This “O’Farrell” techniques has been used for 20 years without major modification.

• 20 x 20 cm have become a standard for 2-DE.

• Assumption: 100 bands can be resolved by 20 cm long 1-DE.

• Therefore, 20 x 20 cm gel can resolved 100 x 100 = 10,000 proteins, in theory.


100

100


Problems with traditional 1st dimension IEF

• Works well for native protein, not good for denaturing proteins, because:

1. Takes longer time to run.

2. Techniques are cumbersome. (the soft, thin, long gel rods needs excellent experiment technique)

3. Batch to batch variation of carrier ampholytes.

4. Patterns are not reproducible enough.

5. Lost of most basic proteins and some acidic protein.


OPERATOR DEPENDENT


2D PAGE2D PAGE

• 2-D gel electrophoresis process consists of these steps:

• Sample preparation

– First dimension: isoelectric focusing

– Second dimension: gel electrophoresis

• Staining

• Imaging analysis via software


Challenges for 2-DE

1. Spot number:

– 10,000-150,000 gene products in a cell.

– PTM makes it difficult to predict real number.

– Sensitivity and dynamic range of 2-DE must be adequate.

– It’s impossible to display all proteins in one single gels.


Challenges for 2-DE

2. Isoelectric point spectrum:

– pI of proteins: range from pH 3-13. (by in vitro translated ORF)

– PTM would not alter the pI outside this range.

– pH gradient from 3-13 dose not exist.

– For proteins which pI > 11.5, they need to be handed separately.


Challenges for 2-DE

3. molecular weights:

– Small proteins or peptides can be analysed by modifying the gel and buffer condition of SDS-PAGE.

– Protein > 250 kDa do not enter 2nd SDS-PAGE properly.

– 1-DE (SDS-PAGE) can be run in a lane at the side of 2-DE.


Challenges for 2-DE

4. hydrophobic proteins:

–Some very hydrophobic proteins do not go in solution.

–Some hydrophobic proteins are lost during sample preparation and iso electric focusing (IEF).

–More chemical developments are required.


Challenges for 2-DE

5. Sensitivity of detection:

– Low copy number proteins are very difficult to detect, even employing most sensitive staining methods.

– Sensitivity of staining methods:1. Silver staining

2. Fluorescent staining

3. Dye binding staining (CBR)


Challenges for 2-DE

6. Loading capacity:

– For detection of low abundant proteins, more sample needs to be loaded.

– A wide dynamic range of the SDS-PAGE is required to prevent merging of highly abundant protein.

– Loading capacity: IEF > SDS-PAGE.


Challenges for 2-DE

7. Quantitation:

– The detection method must give reliable quantitative information.

– Silver staining does not give reliable quantitative data.


Challenges for 2-DE

8. Reproducibility:

– Highest importance in 2-DE experiment.

– Immobilized pH gradient strip have improved a lot for 1st dimension consistency

– Variation most comes from sample preparation.


“A good-looking spot pattern –streak and smear free – is not a guarantee for best 2-DE protocol”


Technologies for identifying proteins

• Western blotting

• Chemical (Edman) sequencing of proteins

• mass spectrometry

– peptide mass fingerprint

– mass spec decay

– databases and search engines


Mass SpectrometryMass Spectrometry

• Mass Spectrometry is another tool to analyze the proteome.

• In general a Mass Spectrometer consists of:– Ion Source

– Mass Analyzer

– Detector

• Mass Spectrometers are used to quantify the mass-to-charge (m/z) ratios of substances.

• From this quantification, a mass is determined, proteins are identified, and further analysis is performed.


MASS SPECTROMETRY

MORE DETAILED MASS SPECTROMETRY

APPLICATIONS IN MORNING LECTURE ON 28TH NOVEMBER 2011


application of bioinformatics in the fields of genomics and proteomics


What is Bioinformatics?

Conceptualizing biology in terms of molecules and then applying

“informatics” techniques from math, computer science, and statistics to

understand and organize the information associated with these molecules on a

large scale


How do we use Bioinformatics?

• Store/retrieve biological information (databases)

• Retrieve/compare gene sequences

• Predict function of unknown genes/proteins

• Search for previously known functions of a gene

• Compare data with other researchers

• Compile/distribute data for other researchers


National Center for Biotechnology Information

GenBank and other genome databases

Sequence retrieval:

Protein Structure:

3D modeling programs –RasMol, Protein Explorer

Sequence comparison programs:

BLAST GCG MacVector



Similarity Search: BLAST

A tool for searching gene or protein sequence databases for related genes of interest

The structure, function, and evolution of a gene may be determined by such comparisons

Alignments between the query sequence and any given database sequence, allowing for mismatches and gaps, indicate their degree of similarity

http://www.ncbi.nlm.nih.gov/BLAST/


MRCKTETGAR

MRCGTETGAR

% identity

90%

CATTATGATA

GTTTATGATT

70%


Strengths:

• Accessibility

• Growing rapidly

• User friendly

Weaknesses:

• Sometimes not up-to-date

• Limited possibilities

• Limited comparisons and information

• Not accurate


Need for improved BioinformaticsGenomics:• Human Genome Project• Gene array technology• Comparative genomics• Functional genomics

Proteomics:

• Global view of protein function/interactions

• Protein motifs

• Structural databases


Data Mining

Handling enormous amounts of data

Sort through what is important and what is not

Manipulate and analyze data to find patterns and variations that correlate with biological

function


Proteomics• Uses information determined by biochemical/crystal structure methods

• Visualization of protein structure

• Make protein-protein comparisons

• Used to determine:

- conformation/folding

- antibody binding sites

- protein-protein interactions

- computer aided drug design


bioinformatics

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GENOMICS AND PROTEOMICS ANALYSES ......GENOMICS Genetics: the science of genes , heredity , and the variation of organisms. In modern research, genetics provides tools in the investigation