Ulf Schmitz, Introduction to genomics and proteomics I 1
www. .uni-rostock.de
BioinformaticsBioinformatics
Introduction to...
Ulf Schmitz, Introduction to genomics and proteomics I 2
www. .uni-rostock.de
Outline
Genomics/Genetics
1. The tree of lif...
Ulf Schmitz, Introduction to genomics and proteomics I 3
www. .uni-rostock.de
Genomics - Definitions
Genetics: is the scie...
Ulf Schmitz, Introduction to genomics and proteomics I 4
www. .uni-rostock.deGenes
• a gene coding for a protein correspon...
Ulf Schmitz, Introduction to genomics and proteomics I 5
www. .uni-rostock.de
Genomics
Genome size comparison
4.1 million5...
Ulf Schmitz, Introduction to genomics and proteomics I 6
www. .uni-rostock.de
Genes
exon:
A section of DNA which carries t...
Ulf Schmitz, Introduction to genomics and proteomics I 7
www. .uni-rostock.de
Genes
exon intron
Globin gene – 1525 bp: 622...
Ulf Schmitz, Introduction to genomics and proteomics I 8
www. .uni-rostock.de
Picking out genes in genomes
• Computer prog...
Ulf Schmitz, Introduction to genomics and proteomics I 9
www. .uni-rostock.de
Picking out genes in genomes
• Regions may e...
Ulf Schmitz, Introduction to genomics and proteomics I 10
www. .uni-rostock.de
Picking out genes in genomes
• The initial ...
Ulf Schmitz, Introduction to genomics and proteomics I 11
www. .uni-rostock.de
Picking out genes in genomes
5' splice sign...
Ulf Schmitz, Introduction to genomics and proteomics I 12
www. .uni-rostock.de
Picking out genes in genomes
• Internal exo...
Ulf Schmitz, Introduction to genomics and proteomics I 13
www. .uni-rostock.de
Picking out genes in genomes
• The final (3...
Ulf Schmitz, Introduction to genomics and proteomics I 14
www. .uni-rostock.de
Humans have
spliced genes…
Ulf Schmitz, Introduction to genomics and proteomics I 15
www. .uni-rostock.de
DNA makes RNA makes Protein
Ulf Schmitz, Introduction to genomics and proteomics I 16
www. .uni-rostock.de
Tree of life
Prokaryotes
Ulf Schmitz, Introduction to genomics and proteomics I 17
www. .uni-rostock.de
Genomics – Prokaryotes
• the genome of a pr...
Ulf Schmitz, Introduction to genomics and proteomics I 18
www. .uni-rostock.de
Genomics - Plasmids
• Plasmids are circular...
Ulf Schmitz, Introduction to genomics and proteomics I 19
www. .uni-rostock.de
Prokaryotic model organisms
E.coli (Escheri...
Ulf Schmitz, Introduction to genomics and proteomics I 20
www. .uni-rostock.de
Genomics
• DNA of higher organisms is organ...
Ulf Schmitz, Introduction to genomics and proteomics I 21
www. .uni-rostock.de
Genomes of eukaryotes
• majority of the DNA...
Ulf Schmitz, Introduction to genomics and proteomics I 22
www. .uni-rostock.de
Eukaryotic model organisms
• Saccharomyces ...
Ulf Schmitz, Introduction to genomics and proteomics I 23
www. .uni-rostock.de
The human genome
• ~3.2 x 109 bp (thirty ti...
Ulf Schmitz, Introduction to genomics and proteomics I 24
www. .uni-rostock.de
0.03Enzyme activator
20.6
2.9
2.5
5.3
1.8
3...
Ulf Schmitz, Introduction to genomics and proteomics I 25
www. .uni-rostock.de
The human genome
• Repeated sequences compr...
Ulf Schmitz, Introduction to genomics and proteomics I 26
www. .uni-rostock.de
The human genome
• All people are different...
Ulf Schmitz, Introduction to genomics and proteomics I 27
www. .uni-rostock.de
TERTIARY STRUCTURE (fold)
TERTIARY STRUCTUR...
Ulf Schmitz, Introduction to genomics and proteomics I 28
www. .uni-rostock.de
DNA makes RNA makes Protein:
Expression dat...
Ulf Schmitz, Introduction to genomics and proteomics I 29
www. .uni-rostock.de
Ulf Schmitz, Introduction to genomics and proteomics I 30
www. .uni-rostock.de
Genes and regulatory regions
regulatory mec...
Ulf Schmitz, Introduction to genomics and proteomics I 31
www. .uni-rostock.de
Expression data
Ulf Schmitz, Introduction to genomics and proteomics I 32
www. .uni-rostock.de
Outlook – coming lecture
Proteomics
– Prote...
Ulf Schmitz, Introduction to genomics and proteomics I 33
www. .uni-rostock.de
Thanks for your
attention!
Ulf Schmitz, Introduction to genomics and proteomics II 1
www. .uni-rostock.de
BioinformaticsBioinformatics
Introduction t...
Ulf Schmitz, Introduction to genomics and proteomics II 2
www. .uni-rostock.de
Outline
1. Proteomics
• Motivation
• Post -...
Ulf Schmitz, Introduction to genomics and proteomics II 3
www. .uni-rostock.de
Protomics
Proteomics:
• is the large-scale ...
Ulf Schmitz, Introduction to genomics and proteomics II 4
www. .uni-rostock.de
Proteomics
If the genome is a list of the i...
Ulf Schmitz, Introduction to genomics and proteomics II 5
www. .uni-rostock.de
Proteomics
• Describing all 3D structures o...
Ulf Schmitz, Introduction to genomics and proteomics II 6
www. .uni-rostock.de
Proteomics
• What kind of data would we lik...
Ulf Schmitz, Introduction to genomics and proteomics II 7
www. .uni-rostock.de
Proteomics
• the rates of synthesis of diff...
Ulf Schmitz, Introduction to genomics and proteomics II 8
www. .uni-rostock.de
Ulf Schmitz, Introduction to genomics and proteomics II 9
www. .uni-rostock.de
Why do Proteomics?
• are there differences ...
Ulf Schmitz, Introduction to genomics and proteomics II 10
www. .uni-rostock.de
Post-translational modification
• a protei...
Ulf Schmitz, Introduction to genomics and proteomics II 11
www. .uni-rostock.de
Post-translational modification
• phosphor...
Ulf Schmitz, Introduction to genomics and proteomics II 12
www. .uni-rostock.de
Proteomics
Ulf Schmitz, Introduction to genomics and proteomics II 13
www. .uni-rostock.de
Key technologies for proteomics
1. 1-D ele...
Ulf Schmitz, Introduction to genomics and proteomics II 14
www. .uni-rostock.de
Key technologies for proteomics
Reference ...
Ulf Schmitz, Introduction to genomics and proteomics II 15
www. .uni-rostock.de
Proteomics
Typically, a sample is purified...
Ulf Schmitz, Introduction to genomics and proteomics II 16
www. .uni-rostock.de
High-throughput Biological Data
• Enormous...
Ulf Schmitz, Introduction to genomics and proteomics II 17
www. .uni-rostock.de
Protein structural data explosion
Protein ...
Ulf Schmitz, Introduction to genomics and proteomics II 18
www. .uni-rostock.de
Maps of hereditary information
1. Linkage ...
Ulf Schmitz, Introduction to genomics and proteomics II 19
www. .uni-rostock.de
Linkage map
Ulf Schmitz, Introduction to genomics and proteomics II 20
www. .uni-rostock.de
Maps of hereditary information
• regions, ...
Ulf Schmitz, Introduction to genomics and proteomics II 21
www. .uni-rostock.de
centromere
CGTCGTCGTCGTCGTCGTCGTCGT...
GCA...
Ulf Schmitz, Introduction to genomics and proteomics II 22
www. .uni-rostock.de
Maps of hereditary information
Banding pat...
Ulf Schmitz, Introduction to genomics and proteomics II 23
www. .uni-rostock.de
Maps of hereditary information
Banding pat...
Ulf Schmitz, Introduction to genomics and proteomics II 24
www. .uni-rostock.de
Maps of hereditary information
• Series of...
Ulf Schmitz, Introduction to genomics and proteomics II 25
www. .uni-rostock.de
Maps of hereditary information
1. if we kn...
Ulf Schmitz, Introduction to genomics and proteomics II 26
www. .uni-rostock.de
Single nucleotide polymorphisms (SNPs)Sing...
Ulf Schmitz, Introduction to genomics and proteomics II 27
www. .uni-rostock.de
Single nucleotide polymorphisms (SNPs)
• n...
Ulf Schmitz, Introduction to genomics and proteomics II 28
www. .uni-rostock.de
Outlook – coming lecture
• Bioinformatics ...
Ulf Schmitz, Introduction to genomics and proteomics II 29
www. .uni-rostock.de
Thanks for your
attention!
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Biotech 2011-01-intro

  1. 1. Ulf Schmitz, Introduction to genomics and proteomics I 1 www. .uni-rostock.de BioinformaticsBioinformatics Introduction to genomics and proteomics IIntroduction to genomics and proteomics I Ulf Schmitz ulf.schmitz@informatik.uni-rostock.de Bioinformatics and Systems Biology Group www.sbi.informatik.uni-rostock.de
  2. 2. Ulf Schmitz, Introduction to genomics and proteomics I 2 www. .uni-rostock.de Outline Genomics/Genetics 1. The tree of life • Prokaryotic Genomes – Bacteria – Archaea • Eukaryotic Genomes – Homo sapiens 2. Genes • Expression Data
  3. 3. Ulf Schmitz, Introduction to genomics and proteomics I 3 www. .uni-rostock.de Genomics - Definitions Genetics: is the science of genes, heredity, and the variation of organisms. Humans began applying knowledge of genetics in prehistory with the domestication and breeding of plants and animals. In modern research, genetics provides tools in the investigation of the function of a particular gene, e.g. analysis of genetic interactions. Genomics: attempts 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. 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.
  4. 4. Ulf Schmitz, Introduction to genomics and proteomics I 4 www. .uni-rostock.deGenes • a gene coding for a protein corresponds to a sequence of nucleotides along one or more regions of a molecule of DNA • in species with double stranded DNA (dsDNA), genes may appear on either strand • bacterial genes are continuous regions of DNA bacterium: • a string of 3N nucleotides encodes a string of N amino acids • or a string of N nucleotides encodes a structural RNA molecule of N residues eukaryote: • a gene may appear split into separated segments in the DNA • an exon is a stretch of DNA retained in mRNA that the ribosomes translate into protein
  5. 5. Ulf Schmitz, Introduction to genomics and proteomics I 5 www. .uni-rostock.de Genomics Genome size comparison 4.1 million5,0001Bacterium (E. coli) 19,000 14,000 14,000 31,000 22.5-30,000 28-35,000 Genes 97 million12Roundworm (C. elegans) 137 million8Fruit Fly (Drosophila melanogaster) 289 million6Malaria mosquito (Anopheles gambiae) 365 million44Puffer fish (Fugu rubripes) 2.7 billion40Mouse (Mus musculus) 3.1 billion46 (23 pairs) Human (Homo sapiens) Base pairsChrom.Species
  6. 6. Ulf Schmitz, Introduction to genomics and proteomics I 6 www. .uni-rostock.de Genes exon: A section of DNA which carries the coding sequence for a protein or part of it. Exons are separated by intervening, non-coding sequences (called introns). In eukaryotes most genes consist of a number of exons. exon: A section of DNA which carries the coding sequence for a protein or part of it. Exons are separated by intervening, non-coding sequences (called introns). In eukaryotes most genes consist of a number of exons. intron: An intervening section of DNA which occurs almost exclusively within a eukaryotic gene, but which is not translated to amino-acid sequences in the gene product. The introns are removed from the pre-mature mRNA through a process called splicing, which leaves the exons untouched, to form an active mRNA. intron: An intervening section of DNA which occurs almost exclusively within a eukaryotic gene, but which is not translated to amino-acid sequences in the gene product. The introns are removed from the pre-mature mRNA through a process called splicing, which leaves the exons untouched, to form an active mRNA.
  7. 7. Ulf Schmitz, Introduction to genomics and proteomics I 7 www. .uni-rostock.de Genes exon intron Globin gene – 1525 bp: 622 in exons, 893 in introns Ovalbumin gene - ~ 7500 bp: 8 short exons comprising 1859 bp Conalbumin gene - ~ 10,000 bp: 17 short exons comprising ~ 2,200 bp Examples of the exon:intron mosaic of genes
  8. 8. Ulf Schmitz, Introduction to genomics and proteomics I 8 www. .uni-rostock.de Picking out genes in genomes • Computer programs for genome analysis identify ORFs (open reading frames) • An ORF begins with an initiation codon ATG (AUG) • An ORF is a potential protein-coding region • There are two approaches to identify protein coding regions…
  9. 9. Ulf Schmitz, Introduction to genomics and proteomics I 9 www. .uni-rostock.de Picking out genes in genomes • Regions may encode amino acid sequences similar to known proteins • Or may be similar to ESTs (correspond to genes known to be expressed) • Few hundred initial bases of cDNA are sequenced to identify a gene 1. Detection of regions similar to known coding regions from other organisms 2. Ab initio methods, seek to identify genes from the properties of the DNA sequence itself • Bacterial genes are easy to identify, because they are contiguous • They have no introns and the space between genes is small • Identification of exons in higher organisms is a problem, assembling them another…
  10. 10. Ulf Schmitz, Introduction to genomics and proteomics I 10 www. .uni-rostock.de Picking out genes in genomes • The initial (5´) exon starts with a transcription start point, preceded by a core promoter site such as the TATA box (~30bp upstream) – Free of stop codons – End immediately before a GT splice-signal Ab initio gene identification in eukaryotic genomes binds and directs RNA polymerase to the correct transcriptional start site
  11. 11. Ulf Schmitz, Introduction to genomics and proteomics I 11 www. .uni-rostock.de Picking out genes in genomes 5' splice signal 3' splice signal
  12. 12. Ulf Schmitz, Introduction to genomics and proteomics I 12 www. .uni-rostock.de Picking out genes in genomes • Internal exons are free of stop codons too – Begin after an AG splice signal – End before a GT splice signal Ab initio gene identification in eukaryotic genomes
  13. 13. Ulf Schmitz, Introduction to genomics and proteomics I 13 www. .uni-rostock.de Picking out genes in genomes • The final (3´) exon starts after a an AG splice signal – Ends with a stop codon (TAA,TAG,TGA) – Followed by a polyadenylation signal sequence Ab initio gene identification in eukaryotic genomes
  14. 14. Ulf Schmitz, Introduction to genomics and proteomics I 14 www. .uni-rostock.de Humans have spliced genes…
  15. 15. Ulf Schmitz, Introduction to genomics and proteomics I 15 www. .uni-rostock.de DNA makes RNA makes Protein
  16. 16. Ulf Schmitz, Introduction to genomics and proteomics I 16 www. .uni-rostock.de Tree of life Prokaryotes
  17. 17. Ulf Schmitz, Introduction to genomics and proteomics I 17 www. .uni-rostock.de Genomics – Prokaryotes • the genome of a prokaryote comes as a single double-stranded DNA molecule in ring-form – in average 2mm long – whereas the cells diameter is only 0.001mm – < 5 Mb • prokaryotic cells can have plasmids as well (see next slide) • protein coding regions have no introns • little non-coding DNA compared to eukaryotes – in E.coli only 11%
  18. 18. Ulf Schmitz, Introduction to genomics and proteomics I 18 www. .uni-rostock.de Genomics - Plasmids • Plasmids are circular double stranded DNA molecules that are separate from the chromosomal DNA. • They usually occur in bacteria, sometimes in eukaryotic organisms • Their size varies from 1 to 250 kilo base pairs (kbp). There are from one copy, for large plasmids, to hundreds of copies of the same plasmid present in a single cell.
  19. 19. Ulf Schmitz, Introduction to genomics and proteomics I 19 www. .uni-rostock.de Prokaryotic model organisms E.coli (Escherichia coli) Methanococcus jannaschii (archaeon) Mycoplasma genitalium (simplest organism known)
  20. 20. Ulf Schmitz, Introduction to genomics and proteomics I 20 www. .uni-rostock.de Genomics • DNA of higher organisms is organized into chromosomes (human – 23 chromosome pairs) • not all DNA codes for proteins • on the other hand some genes exist in multiple copies • that’s why from the genome size you can’t easily estimate the amount of protein sequence information
  21. 21. Ulf Schmitz, Introduction to genomics and proteomics I 21 www. .uni-rostock.de Genomes of eukaryotes • majority of the DNA is in the nucleus, separated into bundles (chromosomes) – small amounts of DNA appear in organelles (mitochondria and chloroplasts) • within single chromosomes gene families are common – some family members are paralogues (related) • they have duplicated within the same genome • often diverged to provide separate functions in descendants (Nachkommen) • e.g. human α and β globin – orthologues genes • are homologues in different species • often perform the same function • e.g. human and horse myoglobin – pseudogenes • lost their function • e.g. human globin gene cluster pseudogene
  22. 22. Ulf Schmitz, Introduction to genomics and proteomics I 22 www. .uni-rostock.de Eukaryotic model organisms • Saccharomyces cerevisiae (baker’s yeast) • Caenorhabditis elegans (C.elegans) • Drosophila melanogaster (fruit fly) • Arabidopsis thaliana (flower) • Homo sapiens (human)
  23. 23. Ulf Schmitz, Introduction to genomics and proteomics I 23 www. .uni-rostock.de The human genome • ~3.2 x 109 bp (thirty time larger than C.elegans or D.melongaster) • coding sequences form only 5% of the human genome • Repeat sequences over 50% • Only ~32.000 genes • Human genome is distributed over 22 chromosome pairs plus X and Y chromosomes • Exons of protein-coding genes are relatively small compared to other known eukaryotic genomes • Introns are relatively long • Protein-coding genes span long stretches of DNA (dystrophin, coding a 3.685 amino acid protein, is >2.4Mbp long) • Average gene length: ~ 8,000 bp • Average of 5-6 exons/gene • Average exon length: ~200 bp • Average intron length: ~2,000 bp • ~8% genes have a single exon • Some exons can be as small as 1 or 3 bp.
  24. 24. Ulf Schmitz, Introduction to genomics and proteomics I 24 www. .uni-rostock.de 0.03Enzyme activator 20.6 2.9 2.5 5.3 1.8 3242 457 403 839 295 Enzyme Peptidase Endopeptidase Protein kinase Protein phosphatase 3.8603Defense/immunity protein 0.8129Actin binding 0.585Motor 0.9154Chaperone 0.475Cell Cycle regulator 0.06Transcription factor binding 14.0 10.5 0.2 0.0 6.2 2.4 0.8 0.2 2207 1656 45 7 986 380 137 44 Nucleic acid binding DNA binding DNA repair protein DNA replication factor Transcription factor RNA binding Structural protein of ribosome Translation factor %NumberFunction 100.015683Total 30.64813Unclassified 0.05Tumor suppressor 9.7 0.2 0.3 1536 33 50 Ligand binding or carrier Electron transfer Cytochrome P450 4.3 1.7 0.1 682 269 19 Transporter Ion channel Neurotransmitter transporter 4.5 0.9 714 145 Structural protein Cytoskeletal structural protein 1.2189Cell adhesion 0.07Storage protein 11.4 8.4 7.6 3.1 0.0 1790 1318 1202 489 71 Signal transduction Receptor Transmembrane receptor G-protein link receptor Olfactory receptor 0.8132Apoptosis inhibitor %NumberFunction The human genomeThe human genome Top categories in a function classification:
  25. 25. Ulf Schmitz, Introduction to genomics and proteomics I 25 www. .uni-rostock.de The human genome • Repeated sequences comprise over 50% of the genome: – Transposable elements, or interspersed repeats include LINEs and SINEs (almost 50%) – Retroposed pseudogenes – Simple ‘stutters’ - repeats of short oligomers (minisatellites and microsatellites) – Segment duplication, of blocks of ~10 - 300kb – Blocks of tandem repeats, including gene families 3300.00080-3000DNA Transposon fossils 8450.00015.000 -110.000Long Terminal Repeats 21850.0006000-8000Long Interspersed Nuclear Elements (LINEs) 131.500.000100-300Short Interspersed Nuclear Elements (SINEs) Fraction of genome % Copy number Size (bp)Element
  26. 26. Ulf Schmitz, Introduction to genomics and proteomics I 26 www. .uni-rostock.de The human genome • All people are different, but the DNA of different people only varies for 0.2% or less. • So, only up to 2 letters in 1000 are expected to be different. • Evidence in current genomics studies (Single Nucleotide Polymorphisms or SNPs) imply that on average only 1 letter out of 1400 is different between individuals. • means that 2 to 3 million letters would differ between individuals.
  27. 27. Ulf Schmitz, Introduction to genomics and proteomics I 27 www. .uni-rostock.de TERTIARY STRUCTURE (fold) TERTIARY STRUCTURE (fold) Genome Expressome Proteome Metabolome Functional Genomics From gene to functionFrom gene to function
  28. 28. Ulf Schmitz, Introduction to genomics and proteomics I 28 www. .uni-rostock.de DNA makes RNA makes Protein: Expression data • More copies of mRNA for a gene leads to more protein • mRNA can now be measured for all the genes in a cell at ones through microarray technology • Can have 60,000 spots (genes) on a single gene chip • Color change gives intensity of gene expression (over- or under-expression)
  29. 29. Ulf Schmitz, Introduction to genomics and proteomics I 29 www. .uni-rostock.de
  30. 30. Ulf Schmitz, Introduction to genomics and proteomics I 30 www. .uni-rostock.de Genes and regulatory regions regulatory mechanisms organize the expression of genes – genes may be turned on or off in response to concentrations of nutrients or to stress – control regions often lie near the segments coding for proteins – they can serve as binding sites for molecules that transcribe the DNA – or they bind regulatory molecules that can block transcription
  31. 31. Ulf Schmitz, Introduction to genomics and proteomics I 31 www. .uni-rostock.de Expression data
  32. 32. Ulf Schmitz, Introduction to genomics and proteomics I 32 www. .uni-rostock.de Outlook – coming lecture Proteomics – Proteins – post-translational modification – Key technologies • Maps of hereditary information • SNPs (Single nucleotide polymorphisms) • Genetic diseases
  33. 33. Ulf Schmitz, Introduction to genomics and proteomics I 33 www. .uni-rostock.de Thanks for your attention!
  34. 34. Ulf Schmitz, Introduction to genomics and proteomics II 1 www. .uni-rostock.de BioinformaticsBioinformatics Introduction to genomics and proteomics IIIntroduction to genomics and proteomics II ulf.schmitz@informatik.uni-rostock.de Bioinformatics and Systems Biology Group www.sbi.informatik.uni-rostock.de
  35. 35. Ulf Schmitz, Introduction to genomics and proteomics II 2 www. .uni-rostock.de Outline 1. Proteomics • Motivation • Post -Translational Modifications • Key technologies • Data explosion 2. Maps of hereditary information 3. Single nucleotide polymorphisms
  36. 36. Ulf Schmitz, Introduction to genomics and proteomics II 3 www. .uni-rostock.de Protomics 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.
  37. 37. Ulf Schmitz, Introduction to genomics and proteomics II 4 www. .uni-rostock.de Proteomics If the genome is a list of the instruments in an orchestra, the proteome is the orchestra playing a symphony. R.Simpson
  38. 38. Ulf Schmitz, Introduction to genomics and proteomics II 5 www. .uni-rostock.de Proteomics • Describing all 3D structures of proteins in the cell is called Structural Genomics • Finding out what these proteins do is called Functional Genomics GENOME PROTEOME DNA Microarray Genetic Screens Protein – Ligand Interactions Protein – Protein Interactions Structure
  39. 39. Ulf Schmitz, Introduction to genomics and proteomics II 6 www. .uni-rostock.de Proteomics • 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. Motivation:
  40. 40. Ulf Schmitz, Introduction to genomics and proteomics II 7 www. .uni-rostock.de Proteomics • 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 Things to consider:
  41. 41. Ulf Schmitz, Introduction to genomics and proteomics II 8 www. .uni-rostock.de
  42. 42. Ulf Schmitz, Introduction to genomics and proteomics II 9 www. .uni-rostock.de Why do Proteomics? • 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
  43. 43. Ulf Schmitz, Introduction to genomics and proteomics II 10 www. .uni-rostock.de Post-translational modification • 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.
  44. 44. Ulf Schmitz, Introduction to genomics and proteomics II 11 www. .uni-rostock.de Post-translational modification • 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. Phosphorylation 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
  45. 45. Ulf Schmitz, Introduction to genomics and proteomics II 12 www. .uni-rostock.de Proteomics
  46. 46. Ulf Schmitz, Introduction to genomics and proteomics II 13 www. .uni-rostock.de Key technologies for proteomics 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 two- hybrid and FRET (fluorescence resonance energy transfer) • can also be used to characterize protein-protein interactions.
  47. 47. Ulf Schmitz, Introduction to genomics and proteomics II 14 www. .uni-rostock.de Key technologies for proteomics 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 High-resolution two-dimensional polyacrylamide gel electrophoresis (2D PAGE) shows the pattern of protein content in a sample.
  48. 48. Ulf Schmitz, Introduction to genomics and proteomics II 15 www. .uni-rostock.de Proteomics Typically, a sample is purified to homogeneity, crystallized, subjected to an X- ray beam and diffraction data are collected. 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..
  49. 49. Ulf Schmitz, Introduction to genomics and proteomics II 16 www. .uni-rostock.de High-throughput Biological Data • 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) – ......
  50. 50. Ulf Schmitz, Introduction to genomics and proteomics II 17 www. .uni-rostock.de Protein structural data explosion Protein Data Bank (PDB): 33.367 Structures (1 November 2005) 28.522 x-ray crystallography, 4.845 NMR
  51. 51. Ulf Schmitz, Introduction to genomics and proteomics II 18 www. .uni-rostock.de Maps of hereditary information 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) Following maps are used to find out how hereditary information is stored, passed on, and implemented.
  52. 52. Ulf Schmitz, Introduction to genomics and proteomics II 19 www. .uni-rostock.de Linkage map
  53. 53. Ulf Schmitz, Introduction to genomics and proteomics II 20 www. .uni-rostock.de Maps of hereditary information • 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 Variable number tandem repeats (VNTRs, also minisatellites) Short tandem repeat polymorphism (STRPs, also microsatellites) • Regions of 2-7bp, repeated many times – Usually 10-30 consecutive copies
  54. 54. Ulf Schmitz, Introduction to genomics and proteomics II 21 www. .uni-rostock.de centromere CGTCGTCGTCGTCGTCGTCGTCGT... GCAGCAGCAGCAGCAGCAGCAGCA... 3bp
  55. 55. Ulf Schmitz, Introduction to genomics and proteomics II 22 www. .uni-rostock.de Maps of hereditary information Banding patterns of chromosomes
  56. 56. Ulf Schmitz, Introduction to genomics and proteomics II 23 www. .uni-rostock.de Maps of hereditary information Banding patterns of chromosomes petite – arm centromere queue - arm
  57. 57. Ulf Schmitz, Introduction to genomics and proteomics II 24 www. .uni-rostock.de Maps of hereditary information • 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 Contig map (also contiguous clone map) 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
  58. 58. Ulf Schmitz, Introduction to genomics and proteomics II 25 www. .uni-rostock.de Maps of hereditary information 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 Imagine we know that a disease results from a specific defective protein:
  59. 59. Ulf Schmitz, Introduction to genomics and proteomics II 26 www. .uni-rostock.de Single nucleotide polymorphisms (SNPs)Single nucleotide polymorphisms (SNPs) • 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
  60. 60. Ulf Schmitz, Introduction to genomics and proteomics II 27 www. .uni-rostock.de Single nucleotide polymorphisms (SNPs) • 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
  61. 61. Ulf Schmitz, Introduction to genomics and proteomics II 28 www. .uni-rostock.de Outlook – coming lecture • 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
  62. 62. Ulf Schmitz, Introduction to genomics and proteomics II 29 www. .uni-rostock.de Thanks for your attention!

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