SlideShare a Scribd company logo
1 of 29
Download to read offline
www.

.uni-rostock.de

Bioinformatics
Introduction to genomics and proteomics II

ulf.schmitz@informatik.uni-rostock.de

Bioinformatics and Systems Biology Group
www.sbi.informatik.uni-rostock.de

Ulf Schmitz, Introduction to genomics and proteomics II

1
www.

Outline

.uni-rostock.de

1. Proteomics
•
•
•
•

Motivation
Post -Translational Modifications
Key technologies
Data explosion

2. Maps of hereditary information
3. Single nucleotide polymorphisms

Ulf Schmitz, Introduction to genomics and proteomics II

2
www.

Protomics

.uni-rostock.de

Proteomics:
• is the large-scale study of proteins, particularly their structures
and functions
• This term was coined to make an analogy with genomics, and
is often viewed as the "next step",
• but proteomics is much more complicated than genomics.
• Most importantly, while the genome is a rather constant entity,
the proteome is constantly changing through its biochemical
interactions with the genome.
• One organism will have radically different protein expression in
different parts of its body and in different stages of its life cycle.
Proteome:
The entirety of proteins in existence in an organism are
referred to as the proteome.

Ulf Schmitz, Introduction to genomics and proteomics II

3
www.

Proteomics

.uni-rostock.de

If the genome is a list of the instruments in an orchestra, the
proteome is the orchestra playing a symphony.
R.Simpson

Ulf Schmitz, Introduction to genomics and proteomics II

4
www.

Proteomics
•
•

.uni-rostock.de

Describing all 3D structures of proteins in the cell is called Structural
Genomics
Finding out what these proteins do is called Functional Genomics

DNA Microarray

GENOME

Genetic Screens

PROTEOME
Protein – Protein
Interactions

Protein – Ligand
Interactions

Structure

Ulf Schmitz, Introduction to genomics and proteomics II

5
www.

Proteomics

.uni-rostock.de

Motivation:
• What kind of data would we like to measure?
• What mature experimental techniques exist to
determine them?
• The basic goal is a spatio-temporal description of
the deployment of proteins in the organism.

Ulf Schmitz, Introduction to genomics and proteomics II

6
www.

Proteomics

.uni-rostock.de

Things to consider:

• the rates of synthesis of different proteins vary among
different tissues and different cell types and states of activity
• methods are available for efficient analysis of transcription
patterns of multiple genes
• because proteins ‘turn over’ at different rates, it is also
necessary to measure proteins directly
• the distribution of expressed protein levels is a kinetic
balance between rates of protein synthesis and degradation

Ulf Schmitz, Introduction to genomics and proteomics II

7
www.

Ulf Schmitz, Introduction to genomics and proteomics II

.uni-rostock.de

8
Why do Proteomics?
•

www.

.uni-rostock.de

are there differences between amino acid sequences determined
directly from proteins and those determined by translation from
DNA?
– pattern recognition programs addressing this questions have following
errors:
•
•
•
•
•

a genuine protein sequence may be missed entirely
an incomplete protein may be reported
a gene may be incorrectly spliced
genes for different proteins may overlap
genes may be assembled from exons in different ways in different tissues

– often, molecules must be modified to make a mature protein that differs
significantly from the one suggested by translation
• in many cases the missing post-translational- modifications are quite
important and have functional significance
• post-transitional modifications include addition of ligands, glycosylation,
methylation, excision of peptides, etc.

– in some cases mRNA is edited before translation, creating changes in
the amino acid sequence that are not inferrable from the genes

•

a protein inferred from a genome sequence is a hypothetical object
until an experiment verifies its existence

Ulf Schmitz, Introduction to genomics and proteomics II

9
Post-translational modification

www.

.uni-rostock.de

•

a protein is a polypeptide chain composed of 20 possible amino acids

•

there are far fewer genes that code for proteins in the human genome than there
are proteins in the human proteome (~33,000 genes vs ~200,000 proteins).

•

each gene encodes as many as six to eight different proteins
– due to post-translational modifications such as phosphorylation, glycosylation or cleavage
(Spaltung)

•

posttranslational modification extends the range of possible functions a protein can
have
– changes may alter the hydrophobicity of a protein and thus determine if the modified
protein is cytosolic or membrane-bound
– modifications like phosphorylation are part of common mechanisms for controlling the
behavior of a protein, for instance, activating or inactivating an enzyme.

Ulf Schmitz, Introduction to genomics and proteomics II

10
Post-translational modification

www.

.uni-rostock.de

Phosphorylation
•
•
•
•

phosphorylation is the addition of a phosphate (PO4) group to a protein
or a small molecule (usual to serine, tyrosine, threonine or histidine)
In eukaryotes, protein phosphorylation is probably the most important
regulatory event
Many enzymes and receptors are switched "on" or "off" by
phosphorylation and dephosphorylation
Phosphorylation is catalyzed by various specific protein kinases,
whereas phosphatases dephosphorylate.

Acetylation
•

Is the addition of an acetyl group, usually at the N-terminus of the protein

Farnesylation
•

farnesylation, the addition of a farnesyl group

Glycosylation
•

the addition of a glycosyl group to either asparagine, hydroxylysine,
serine, or threonine, resulting in a glycoprotein
Ulf Schmitz, Introduction to genomics and proteomics II

11
www.

Proteomics

Ulf Schmitz, Introduction to genomics and proteomics II

.uni-rostock.de

12
Key technologies for proteomics

www.

.uni-rostock.de

1. 1-D electrophoresis and 2-D electrophoresis
•

are for the separation and visualization of proteins.

2. mass spectrometry, x-ray crystallography, and NMR
(Nuclear magnetic resonance )
•

are used to identify and characterize proteins

3. chromatography techniques especially affinity
chromatography
•

are used to characterize protein-protein interactions.

4. Protein expression systems like the yeast twohybrid and FRET (fluorescence resonance energy
transfer)
•

can also be used to characterize protein-protein interactions.

Ulf Schmitz, Introduction to genomics and proteomics II

13
Key technologies for proteomics

www.

.uni-rostock.de

High-resolution two-dimensional polyacrylamide gel
electrophoresis (2D PAGE) shows the pattern of
protein content in a sample.

Reference map of lympphoblastoid
cell linePRI, soluble proteins.
• 110 µg of proteins loaded
• Strip 17cm pH gradient 4-7, SDS
PAGE gels 20 x 25 cm, 8-18.5% T.
• Staining by silver nitrate method
(Rabilloud et al.,)
• Identification by mass spectrometry.
The pinks labels on the spots indicate
the ID in Swiss-prot database
browse the SWISS-2DPAGE database for more 2d PAGE images
Ulf Schmitz, Introduction to genomics and proteomics II

14
www.

Proteomics

.uni-rostock.de

X-ray crystallography is a means to
determine the detailed molecular
structure of a protein, nucleic acid or
small molecule.
With a crystal structure we can explain the
mechanism of an enzyme, the binding of an
inhibitor, the packing of protein domains, the
tertiary structure of a nucleic acid molecule
etc..

Typically, a sample is purified to
homogeneity, crystallized, subjected to an Xray beam and diffraction data are collected.

Ulf Schmitz, Introduction to genomics and proteomics II

15
High-throughput Biological Data

www.

.uni-rostock.de

• Enormous amounts of biological data are being
generated by high-throughput capabilities; even
more are coming
–
–
–
–
–
–

genomic sequences
gene expression data (microarrays)
mass spec. data
protein-protein interaction (chromatography)
protein structures (x-ray christallography)
......

Ulf Schmitz, Introduction to genomics and proteomics II

16
Protein structural data explosion

www.

.uni-rostock.de

Protein Data Bank (PDB): 33.367 Structures (1 November 2005)
28.522 x-ray crystallography, 4.845 NMR

Ulf Schmitz, Introduction to genomics and proteomics II

17
Maps of hereditary information

www.

.uni-rostock.de

Following maps are used to find out how hereditary information is
stored, passed on, and implemented.

1.

Linkage maps of
genes
mini- / microsatellites

2.

Banding patterns of chromosomes
physical objects with visible landmarks called banding patterns

3.

DNA sequences
Contig maps (contigous clone maps)
Sequence tagged site (STS)
SNPs (Single nucloetide polymorphisms)

Ulf Schmitz, Introduction to genomics and proteomics II

18
www.

.uni-rostock.de

Linkage map
Ulf Schmitz, Introduction to genomics and proteomics II

19
Maps of hereditary information

www.

.uni-rostock.de

Variable number tandem repeats (VNTRs, also minisatellites)
• regions, 8-80bp long, repeated a variable number of times
• the distribution and the size of repeats is the marker
• inheritance of VNTRs can be followed in a family and
mapped to a pathological phenotype
• first genetic data used for personal identification
– Genetic fingerprints; in paternity and in criminal cases

Short tandem repeat polymorphism (STRPs, also microsatellites)

• Regions of 2-7bp, repeated many times
– Usually 10-30 consecutive copies

Ulf Schmitz, Introduction to genomics and proteomics II

20
www.

.uni-rostock.de

centromere

3bp

CGTCGTCGTCGTCGTCGTCGTCGT...
GCAGCAGCAGCAGCAGCAGCAGCA...
Ulf Schmitz, Introduction to genomics and proteomics II

21
Maps of hereditary information

www.

.uni-rostock.de

Banding patterns of
chromosomes

Ulf Schmitz, Introduction to genomics and proteomics II

22
Maps of hereditary information

www.

.uni-rostock.de

Banding patterns of chromosomes
petite – arm
centromere
queue - arm

Ulf Schmitz, Introduction to genomics and proteomics II

23
Maps of hereditary information

www.

.uni-rostock.de

Contig map (also contiguous clone map)
•

•
•

Series of overlapping DNA clones of known
order along a chromosome from an organism
of interest, stored in yeast or bacterial cells as
YACs (Yeast Artificial Chromosomes) or
BACs (Bacterial Artificial Chromosomes)
A contig map produces a fine mapping (high
resolution) of a genome
YAC can contain up to 106bp, a BAC about
250.000bp

Sequence tagged site (STS)
•
•

Short, sequenced region of DNA, 200-600bp
long, that appears in a unique location in the
genome
One type arises from an EST (expressed
sequence tag), a piece of cDNA

Ulf Schmitz, Introduction to genomics and proteomics II

24
Maps of hereditary information

www.

.uni-rostock.de

Imagine we know that a disease results from a specific
defective protein:

1. if we know the protein involved, we can pursue
rational approaches to therapy
2. if we know the gene involved, we can devise
tests to identify sufferers or carriers
3. wereas the knowledge of the chromosomal
location of the gene is unnecessary in many
cases for either therapy or detection;
• it is required only for identifying the gene, providing a
bridge between the patterns of inheritance and the
DNA sequence
Ulf Schmitz, Introduction to genomics and proteomics II

25
Single nucleotide polymorphisms (SNPs)

•
•
•

www.

.uni-rostock.de

SNP (pronounced ‘snip’) is a genetic
variation between individuals
single base pairs that can be substituted,
deleted or inserted
SNPs are distributed throughout the
genome
– average every 2000bp

•
•

provide markers for mapping genes
not all SNPs are linked to diseases

Ulf Schmitz, Introduction to genomics and proteomics II

26
Single nucleotide polymorphisms (SNPs)

www.

.uni-rostock.de

• nonsense mutations:
– codes for a stop, which can truncate the
protein

• missense mutations:
– codes for a different amino acid

• silent mutations:
– codes for the same amino acid, so has no
effect

Ulf Schmitz, Introduction to genomics and proteomics II

27
Outlook – coming lecture

www.

.uni-rostock.de

• Bioinformatics Information Resources And Networks
– EMBnet – European Molecular Biology Network
• DBs and Tools

– NCBI – National Center For Biotechnology Information
• DBs and Tools

–
–
–
–
–
–

Nucleic Acid Sequence Databases
Protein Information Resources
Metabolic Databases
Mapping Databases
Databases concerning Mutations
Literature Databases

Ulf Schmitz, Introduction to genomics and proteomics II

28
www.

.uni-rostock.de

Thanks for your
attention!

Ulf Schmitz, Introduction to genomics and proteomics II

29

More Related Content

What's hot

A Review on the role of Wnt-4 in Stem Cell Biology
A Review on the role of Wnt-4 in Stem Cell BiologyA Review on the role of Wnt-4 in Stem Cell Biology
A Review on the role of Wnt-4 in Stem Cell Biology
Gayathri Vijayakumar
 

What's hot (20)

A Review on the role of Wnt-4 in Stem Cell Biology
A Review on the role of Wnt-4 in Stem Cell BiologyA Review on the role of Wnt-4 in Stem Cell Biology
A Review on the role of Wnt-4 in Stem Cell Biology
 
Functional proteomics, and tools
Functional proteomics, and toolsFunctional proteomics, and tools
Functional proteomics, and tools
 
Gene regulatory networks
Gene regulatory networksGene regulatory networks
Gene regulatory networks
 
Introduction to Proteogenomics
Introduction to Proteogenomics Introduction to Proteogenomics
Introduction to Proteogenomics
 
Techniques in proteomics
Techniques in proteomicsTechniques in proteomics
Techniques in proteomics
 
autophagy- survival and cell death.
autophagy- survival and cell death.autophagy- survival and cell death.
autophagy- survival and cell death.
 
Proteomics
ProteomicsProteomics
Proteomics
 
genomic comparison
genomic comparison genomic comparison
genomic comparison
 
Overview Radboudumc Center for Proteomics, Glycomics and Metabolomics april 2015
Overview Radboudumc Center for Proteomics, Glycomics and Metabolomics april 2015Overview Radboudumc Center for Proteomics, Glycomics and Metabolomics april 2015
Overview Radboudumc Center for Proteomics, Glycomics and Metabolomics april 2015
 
Proteome analysis
Proteome analysisProteome analysis
Proteome analysis
 
Translation in eukaryotes
Translation in eukaryotesTranslation in eukaryotes
Translation in eukaryotes
 
Autophagy Research
Autophagy ResearchAutophagy Research
Autophagy Research
 
Apoptosis definition, mechanism , Apoptosis vs necrosis, Assays of apoptosis,...
Apoptosis definition, mechanism , Apoptosis vs necrosis, Assays of apoptosis,...Apoptosis definition, mechanism , Apoptosis vs necrosis, Assays of apoptosis,...
Apoptosis definition, mechanism , Apoptosis vs necrosis, Assays of apoptosis,...
 
Protein protein interaction
Protein protein interactionProtein protein interaction
Protein protein interaction
 
Microbial proteomics
Microbial proteomicsMicrobial proteomics
Microbial proteomics
 
Proteomics
ProteomicsProteomics
Proteomics
 
Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...
Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...
Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...
 
Proteomic and metabolomic
Proteomic and metabolomicProteomic and metabolomic
Proteomic and metabolomic
 
Salisha ppt (1) (1)
Salisha ppt (1) (1)Salisha ppt (1) (1)
Salisha ppt (1) (1)
 
Proteins – Basics you need to know for Proteomics
Proteins – Basics you need to know for ProteomicsProteins – Basics you need to know for Proteomics
Proteins – Basics you need to know for Proteomics
 

Similar to Genomicsandproteomicsii

Genomics and proteomics II
Genomics and proteomics IIGenomics and proteomics II
Genomics and proteomics II
Nikolay Vyahhi
 
proteomics and genomics-1
proteomics and genomics-1proteomics and genomics-1
proteomics and genomics-1
Shyam Kodi
 
PROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICS
PROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICSPROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICS
PROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICS
PoobalanRajan2
 
Protein protein interactions
Protein protein interactionsProtein protein interactions
Protein protein interactions
Prianca12
 
Comparative genomics and proteomics
Comparative genomics and proteomicsComparative genomics and proteomics
Comparative genomics and proteomics
Nikhil Aggarwal
 
Why Proteins Are Essential For Cellular Function
Why Proteins Are Essential For Cellular FunctionWhy Proteins Are Essential For Cellular Function
Why Proteins Are Essential For Cellular Function
Beth Salazar
 
Prion Protein
Prion ProteinPrion Protein
Prion Protein
mazraara
 
OMICS.pptx
OMICS.pptxOMICS.pptx
OMICS.pptx
PagudalaSangeetha
 

Similar to Genomicsandproteomicsii (20)

Genomics and proteomics II
Genomics and proteomics IIGenomics and proteomics II
Genomics and proteomics II
 
proteomics and genomics-1
proteomics and genomics-1proteomics and genomics-1
proteomics and genomics-1
 
Proteomics ppt
Proteomics pptProteomics ppt
Proteomics ppt
 
Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.Proteomics: types, protein profiling steps etc.
Proteomics: types, protein profiling steps etc.
 
Biotech 2011-01-intro
Biotech 2011-01-introBiotech 2011-01-intro
Biotech 2011-01-intro
 
protein-protein interaction
protein-protein  interactionprotein-protein  interaction
protein-protein interaction
 
Proteomics in VSC for crop improvement programme
Proteomics in VSC for crop improvement programmeProteomics in VSC for crop improvement programme
Proteomics in VSC for crop improvement programme
 
proteomics scope and its importance by aniqa atta
proteomics scope and its importance by aniqa attaproteomics scope and its importance by aniqa atta
proteomics scope and its importance by aniqa atta
 
PROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICS
PROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICSPROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICS
PROTEOMICS IN BLOOD BANKING. DIFFERENT TYPES OF PROTEOMICS
 
Protein protein interactions
Protein protein interactionsProtein protein interactions
Protein protein interactions
 
Intro to in silico drug discovery 2014
Intro to in silico drug discovery 2014Intro to in silico drug discovery 2014
Intro to in silico drug discovery 2014
 
Comparative genomics and proteomics
Comparative genomics and proteomicsComparative genomics and proteomics
Comparative genomics and proteomics
 
Biotech 2011-01-intro
Biotech 2011-01-introBiotech 2011-01-intro
Biotech 2011-01-intro
 
Why Proteins Are Essential For Cellular Function
Why Proteins Are Essential For Cellular FunctionWhy Proteins Are Essential For Cellular Function
Why Proteins Are Essential For Cellular Function
 
Prion Protein
Prion ProteinPrion Protein
Prion Protein
 
GENOMICS
GENOMICSGENOMICS
GENOMICS
 
OMICS.pptx
OMICS.pptxOMICS.pptx
OMICS.pptx
 
Lecture 1 Introduction to Bioinformatics BCH 433.ppt
Lecture 1 Introduction to Bioinformatics BCH 433.pptLecture 1 Introduction to Bioinformatics BCH 433.ppt
Lecture 1 Introduction to Bioinformatics BCH 433.ppt
 
Genes, Genomics and Proteomics
Genes, Genomics and Proteomics Genes, Genomics and Proteomics
Genes, Genomics and Proteomics
 
Introduction to biocomputing
 Introduction to biocomputing Introduction to biocomputing
Introduction to biocomputing
 

Recently uploaded

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Recently uploaded (20)

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
A Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusA Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source Milvus
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot ModelNavi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu SubbuApidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 

Genomicsandproteomicsii

  • 1. www. .uni-rostock.de Bioinformatics Introduction to genomics and proteomics II ulf.schmitz@informatik.uni-rostock.de Bioinformatics and Systems Biology Group www.sbi.informatik.uni-rostock.de Ulf Schmitz, Introduction to genomics and proteomics II 1
  • 2. www. Outline .uni-rostock.de 1. Proteomics • • • • Motivation Post -Translational Modifications Key technologies Data explosion 2. Maps of hereditary information 3. Single nucleotide polymorphisms Ulf Schmitz, Introduction to genomics and proteomics II 2
  • 3. www. Protomics .uni-rostock.de Proteomics: • is the large-scale study of proteins, particularly their structures and functions • This term was coined to make an analogy with genomics, and is often viewed as the "next step", • but proteomics is much more complicated than genomics. • Most importantly, while the genome is a rather constant entity, the proteome is constantly changing through its biochemical interactions with the genome. • One organism will have radically different protein expression in different parts of its body and in different stages of its life cycle. Proteome: The entirety of proteins in existence in an organism are referred to as the proteome. Ulf Schmitz, Introduction to genomics and proteomics II 3
  • 4. www. Proteomics .uni-rostock.de If the genome is a list of the instruments in an orchestra, the proteome is the orchestra playing a symphony. R.Simpson Ulf Schmitz, Introduction to genomics and proteomics II 4
  • 5. www. Proteomics • • .uni-rostock.de Describing all 3D structures of proteins in the cell is called Structural Genomics Finding out what these proteins do is called Functional Genomics DNA Microarray GENOME Genetic Screens PROTEOME Protein – Protein Interactions Protein – Ligand Interactions Structure Ulf Schmitz, Introduction to genomics and proteomics II 5
  • 6. www. Proteomics .uni-rostock.de Motivation: • What kind of data would we like to measure? • What mature experimental techniques exist to determine them? • The basic goal is a spatio-temporal description of the deployment of proteins in the organism. Ulf Schmitz, Introduction to genomics and proteomics II 6
  • 7. www. Proteomics .uni-rostock.de Things to consider: • the rates of synthesis of different proteins vary among different tissues and different cell types and states of activity • methods are available for efficient analysis of transcription patterns of multiple genes • because proteins ‘turn over’ at different rates, it is also necessary to measure proteins directly • the distribution of expressed protein levels is a kinetic balance between rates of protein synthesis and degradation Ulf Schmitz, Introduction to genomics and proteomics II 7
  • 8. www. Ulf Schmitz, Introduction to genomics and proteomics II .uni-rostock.de 8
  • 9. Why do Proteomics? • www. .uni-rostock.de are there differences between amino acid sequences determined directly from proteins and those determined by translation from DNA? – pattern recognition programs addressing this questions have following errors: • • • • • a genuine protein sequence may be missed entirely an incomplete protein may be reported a gene may be incorrectly spliced genes for different proteins may overlap genes may be assembled from exons in different ways in different tissues – often, molecules must be modified to make a mature protein that differs significantly from the one suggested by translation • in many cases the missing post-translational- modifications are quite important and have functional significance • post-transitional modifications include addition of ligands, glycosylation, methylation, excision of peptides, etc. – in some cases mRNA is edited before translation, creating changes in the amino acid sequence that are not inferrable from the genes • a protein inferred from a genome sequence is a hypothetical object until an experiment verifies its existence Ulf Schmitz, Introduction to genomics and proteomics II 9
  • 10. Post-translational modification www. .uni-rostock.de • a protein is a polypeptide chain composed of 20 possible amino acids • there are far fewer genes that code for proteins in the human genome than there are proteins in the human proteome (~33,000 genes vs ~200,000 proteins). • each gene encodes as many as six to eight different proteins – due to post-translational modifications such as phosphorylation, glycosylation or cleavage (Spaltung) • posttranslational modification extends the range of possible functions a protein can have – changes may alter the hydrophobicity of a protein and thus determine if the modified protein is cytosolic or membrane-bound – modifications like phosphorylation are part of common mechanisms for controlling the behavior of a protein, for instance, activating or inactivating an enzyme. Ulf Schmitz, Introduction to genomics and proteomics II 10
  • 11. Post-translational modification www. .uni-rostock.de Phosphorylation • • • • phosphorylation is the addition of a phosphate (PO4) group to a protein or a small molecule (usual to serine, tyrosine, threonine or histidine) In eukaryotes, protein phosphorylation is probably the most important regulatory event Many enzymes and receptors are switched "on" or "off" by phosphorylation and dephosphorylation Phosphorylation is catalyzed by various specific protein kinases, whereas phosphatases dephosphorylate. Acetylation • Is the addition of an acetyl group, usually at the N-terminus of the protein Farnesylation • farnesylation, the addition of a farnesyl group Glycosylation • the addition of a glycosyl group to either asparagine, hydroxylysine, serine, or threonine, resulting in a glycoprotein Ulf Schmitz, Introduction to genomics and proteomics II 11
  • 12. www. Proteomics Ulf Schmitz, Introduction to genomics and proteomics II .uni-rostock.de 12
  • 13. Key technologies for proteomics www. .uni-rostock.de 1. 1-D electrophoresis and 2-D electrophoresis • are for the separation and visualization of proteins. 2. mass spectrometry, x-ray crystallography, and NMR (Nuclear magnetic resonance ) • are used to identify and characterize proteins 3. chromatography techniques especially affinity chromatography • are used to characterize protein-protein interactions. 4. Protein expression systems like the yeast twohybrid and FRET (fluorescence resonance energy transfer) • can also be used to characterize protein-protein interactions. Ulf Schmitz, Introduction to genomics and proteomics II 13
  • 14. Key technologies for proteomics www. .uni-rostock.de High-resolution two-dimensional polyacrylamide gel electrophoresis (2D PAGE) shows the pattern of protein content in a sample. Reference map of lympphoblastoid cell linePRI, soluble proteins. • 110 µg of proteins loaded • Strip 17cm pH gradient 4-7, SDS PAGE gels 20 x 25 cm, 8-18.5% T. • Staining by silver nitrate method (Rabilloud et al.,) • Identification by mass spectrometry. The pinks labels on the spots indicate the ID in Swiss-prot database browse the SWISS-2DPAGE database for more 2d PAGE images Ulf Schmitz, Introduction to genomics and proteomics II 14
  • 15. www. Proteomics .uni-rostock.de X-ray crystallography is a means to determine the detailed molecular structure of a protein, nucleic acid or small molecule. With a crystal structure we can explain the mechanism of an enzyme, the binding of an inhibitor, the packing of protein domains, the tertiary structure of a nucleic acid molecule etc.. Typically, a sample is purified to homogeneity, crystallized, subjected to an Xray beam and diffraction data are collected. Ulf Schmitz, Introduction to genomics and proteomics II 15
  • 16. High-throughput Biological Data www. .uni-rostock.de • Enormous amounts of biological data are being generated by high-throughput capabilities; even more are coming – – – – – – genomic sequences gene expression data (microarrays) mass spec. data protein-protein interaction (chromatography) protein structures (x-ray christallography) ...... Ulf Schmitz, Introduction to genomics and proteomics II 16
  • 17. Protein structural data explosion www. .uni-rostock.de Protein Data Bank (PDB): 33.367 Structures (1 November 2005) 28.522 x-ray crystallography, 4.845 NMR Ulf Schmitz, Introduction to genomics and proteomics II 17
  • 18. Maps of hereditary information www. .uni-rostock.de Following maps are used to find out how hereditary information is stored, passed on, and implemented. 1. Linkage maps of genes mini- / microsatellites 2. Banding patterns of chromosomes physical objects with visible landmarks called banding patterns 3. DNA sequences Contig maps (contigous clone maps) Sequence tagged site (STS) SNPs (Single nucloetide polymorphisms) Ulf Schmitz, Introduction to genomics and proteomics II 18
  • 19. www. .uni-rostock.de Linkage map Ulf Schmitz, Introduction to genomics and proteomics II 19
  • 20. Maps of hereditary information www. .uni-rostock.de Variable number tandem repeats (VNTRs, also minisatellites) • regions, 8-80bp long, repeated a variable number of times • the distribution and the size of repeats is the marker • inheritance of VNTRs can be followed in a family and mapped to a pathological phenotype • first genetic data used for personal identification – Genetic fingerprints; in paternity and in criminal cases Short tandem repeat polymorphism (STRPs, also microsatellites) • Regions of 2-7bp, repeated many times – Usually 10-30 consecutive copies Ulf Schmitz, Introduction to genomics and proteomics II 20
  • 22. Maps of hereditary information www. .uni-rostock.de Banding patterns of chromosomes Ulf Schmitz, Introduction to genomics and proteomics II 22
  • 23. Maps of hereditary information www. .uni-rostock.de Banding patterns of chromosomes petite – arm centromere queue - arm Ulf Schmitz, Introduction to genomics and proteomics II 23
  • 24. Maps of hereditary information www. .uni-rostock.de Contig map (also contiguous clone map) • • • Series of overlapping DNA clones of known order along a chromosome from an organism of interest, stored in yeast or bacterial cells as YACs (Yeast Artificial Chromosomes) or BACs (Bacterial Artificial Chromosomes) A contig map produces a fine mapping (high resolution) of a genome YAC can contain up to 106bp, a BAC about 250.000bp Sequence tagged site (STS) • • Short, sequenced region of DNA, 200-600bp long, that appears in a unique location in the genome One type arises from an EST (expressed sequence tag), a piece of cDNA Ulf Schmitz, Introduction to genomics and proteomics II 24
  • 25. Maps of hereditary information www. .uni-rostock.de Imagine we know that a disease results from a specific defective protein: 1. if we know the protein involved, we can pursue rational approaches to therapy 2. if we know the gene involved, we can devise tests to identify sufferers or carriers 3. wereas the knowledge of the chromosomal location of the gene is unnecessary in many cases for either therapy or detection; • it is required only for identifying the gene, providing a bridge between the patterns of inheritance and the DNA sequence Ulf Schmitz, Introduction to genomics and proteomics II 25
  • 26. Single nucleotide polymorphisms (SNPs) • • • www. .uni-rostock.de SNP (pronounced ‘snip’) is a genetic variation between individuals single base pairs that can be substituted, deleted or inserted SNPs are distributed throughout the genome – average every 2000bp • • provide markers for mapping genes not all SNPs are linked to diseases Ulf Schmitz, Introduction to genomics and proteomics II 26
  • 27. Single nucleotide polymorphisms (SNPs) www. .uni-rostock.de • nonsense mutations: – codes for a stop, which can truncate the protein • missense mutations: – codes for a different amino acid • silent mutations: – codes for the same amino acid, so has no effect Ulf Schmitz, Introduction to genomics and proteomics II 27
  • 28. Outlook – coming lecture www. .uni-rostock.de • Bioinformatics Information Resources And Networks – EMBnet – European Molecular Biology Network • DBs and Tools – NCBI – National Center For Biotechnology Information • DBs and Tools – – – – – – Nucleic Acid Sequence Databases Protein Information Resources Metabolic Databases Mapping Databases Databases concerning Mutations Literature Databases Ulf Schmitz, Introduction to genomics and proteomics II 28
  • 29. www. .uni-rostock.de Thanks for your attention! Ulf Schmitz, Introduction to genomics and proteomics II 29