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Genome

Genome. Lesk, Introduction to Bioinformatics, Chapter 2. Organisms and cells. All organisms consist of small cells Human body has approx 6x10 13 cells of about 320 different types Cell size can vary greatly Human red blood cell  5 microns (0.005 mm) Neuron from spinal cord  1m long

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Genome

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  1. Genome Lesk, Introduction to Bioinformatics, Chapter 2

  2. Organisms and cells • All organisms consist of small cells • Human body has approx 6x1013 cells of about 320 different types • Cell size can vary greatly • Human red blood cell  5 microns (0.005 mm) • Neuron from spinal cord 1m long • Two types of organisms • Prokaryotes - Bacteria for example • Eukaryotes - most other organisms • Archaea – few organisms living in hostile environments

  3. Genomes and Genes: Not all DNA codes for genes

  4. Genetic information • Genes as discovered by Mendel entirely abstract entities • Chromosomes are physical entities and their banding patterns their landmarks • Chromosomes are numbered in size (1=largest) • Human chromome: p (petite=short), q (queue) arm, e.g. 15q11.1 • DNA sequences = hereditary information in physical form

  5. Locating genes • The disease cystic fibrosis is known since middle ages, the relevant protein was not • Folklore: „Children with excessive salt in sweat - noticable when kissing them on forehead - were short lived“ • Implication: Chloride channel in epithelial tissues • Search in family pedrigrees identified various genetic markers (Variable Number Tandem Repeat), which limited the genomic region first from 1-2 Mio bp to 300kb • Finally the deletion 508Phe in the CFTR gene was identified as cause

  6. Chromosome

  7. Chromosome banding pattern map

  8. Chromosome banding pattern map

  9. 2 Types of Maps: Physical Map • Genome sequencing projects supply the DNA sequence of each chromosome • The physical distance is the number of base pairs that separate two genes 180 Mbp 110 100 Gene B Gene A …ACTGTATGACTGGCATGGCACTGGGGCAAATGTGCACTC… 5 0 C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  10. 2 Types of Maps: Genetic Map • Chromosomes are carriers of genetic information • Genetic information is linked and linearly arranged inside the chromosome • This linkage is sometimes broken: recombination (crossing-over) Genetic Maps C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  11. 110 cM 78 70 2 0 2 Types of Maps: Genetic Maps • Genes located far from each other are more likely to be uncoupled during a crossing-over • A Morgan is the genetic distance in which 1 crossing-over is expected to occur C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  12. Why 2 Types of Maps? • Historical background • Genetic markers may be mapped in only one system (conversions needed) • Genetic markers may be ambiguous • Different systems provide us with complementary information (not completely redundant) C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  13. Expected Map Conversion bps / cM Linear relationship bps / cM C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  14. Observed Map Conversion • Non linear relationship (Yu A, et al. 2001. Nature, 409:951-3 • Outliers • Marker abiguity • Local marker density • Inversions bps / cM / cR Linear relationship bps Human chromosome 12 bps / cM / cR cM C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  15. General Properties • Gene density and recombination • Recombination is mostly higher in areas with a high gene density. bps Yao, et al. (2002) Proc Natl Acad Sci 99(9):6157 high gene density high recombination Human chromosome 12 cM C. Voigt, S. Ibrahim, S. Möller, P. Serrano Fernández. Non-linear map conversions. German Conference on Bioinformatics, 2003

  16. How to Detect Genes? • Detecting of regions similar to known coding regions from other organisms • Gene expressed (in another organism)  mRNA  cDNA = EST (Expressed Sequence Tags) • search for start of EST • Ab initio: derive gene from sequence itself • Bacteria easy as genes are contiguous • Eucaryotes problem: alternative splicing • Initial exon: • Search for TATA box ~30bp upstream, • no in-frame stop codon, • ends before GT splice signal • Internal exon: • AG splice signal, • no in-frame stop codons, • ends before GT splice signal • Final exon followed by polyadenylation

  17. Brent, Nat Biotech, 2007 By Michael Schroeder, Biotec, 2004 18

  18. How to detect genes: De novo prediction • GenScan (late 90s) • predicts 10% of ORFs in human genome • Overprediction of 45,000 genes (~22,000 current estimate) • TwinScan (ealry 2000s): • Use alignment between target and a related genome: detect one third of ORFs in human genome • N-Scan • Includes pseudo gene detection • Predicts 20,138 genes By Michael Schroeder, Biotec, 2004 19

  19. Applications • Genetic diversity and anthropology • Cheetahs very closely related to each other pointing to a population bottleneck 10,000 years ago • Humans: mitochondrial DNA passed on through maternal line, Y chromosome from father to son • Variation in mitochondrial DNA in humans suggests single maternal ancestor 140,000-200,000 years ago • Population of Iceland (first inhabited 1100 years ago) descended from Scandinavian males and femals from Scandinavia and the British Isles • Basques linguistically and genetically isolated

  20. Evolution of Genomes • Phylogenetic profiles • What genes do different phyla share? • What homologous proteins do different phyla share • What functions to different phyla share?

  21. Shared functions of bacteria, archaea, and eucarya • Functions shared by Haemophilus influenza (bacteria), Methanococus jannaschii (archaea), Saccharomyces cerevisiae (eucarya) • Energy: • Biosyntehsis of cofactors, amino acids • Central and intermediary metabolism • Energy metabolism • Fatty acids and phospholipids • Nucleotide biosynthesis • Transport • Information: • Replication • Transcription • Translation • Communication and regulation • Regulatory functions • Cell envelope/cell wall • Cellular processes • Can we construct a minimal organism?

  22. Summary • Relation of DNA, genes and chromosomes • Relationship of distance in Morgan and basepairs • How to find genes in DNA • By similarity • Ab initiov with Introns, exons, alternative splicing • Read Lesk, chapter 2

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