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Fig. 12-1

Chapter 12: Genomics. Fig. 12-1. Genomics: the study of whole-genome structure, organization, and function Structural genomics: the physical genome; whole genome mapping Functional genomics: the proteome, expression patterns, networks.

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Fig. 12-1

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  1. Chapter 12: Genomics Fig. 12-1

  2. Genomics: the study of whole-genome structure, organization, and function Structural genomics: the physical genome; whole genome mapping Functional genomics: the proteome, expression patterns, networks

  3. Creating a physical map of the genome • Create a comprehensive genomic library • (use a vector that incorporates huge fragments) • Order the clones by identifying overlapping groups • (e.g., sequencing ends to determine “contigs”) • Sequence each contig • Identify genes and chromosomal rearrangements • within each contig (correlates the genetic and • physical maps)

  4. Overview of genome sequencing Fig. 12-2

  5. Sequencing the ends of clones in a library Fig. 12-4

  6. Overview of genome sequencing Fig. 12-2

  7. Fig. 12-5

  8. Fig. 12-6

  9. Overview of genome sequencing Fig. 12-3

  10. Fig. 12-7

  11. Fig. 12-8

  12. Several orders of magnitude resolution separates cytogenetic from gene-level understanding Fig. 12-9

  13. Creating a high-resolution genetic map • of the genome requires many “markers” • Classic mutations and allelic variations (too few) • Molecular polymorphisms; selectively neutral DNA • sequence variations are common in genomes • Example: Restriction Fragment Length Polymorphisms • (RFLP markers)

  14. Inheritance of an RFLP: Fig. 12-10

  15. Inheritance of an RFLP: Determining linkage to a known gene Fig. 12-10

  16. Inheritance of an RFLP: Determining linkage to a known gene Fig. 12-10

  17. Linkage analysis of a gene and VNTR markers Fig. 12-11

  18. Creating a high-resolution genetic map • of the genome requires many “markers” • Classic mutations and allelic variations • Molecular polymorphisms; selectively neutral DNA • sequence variations are common in genomes • Example: Restriction Fragment Length Polymorphisms • (RFLP markers) • Example: Simple Sequence Length Polymorphisms • (SSLP markers)

  19. SSLP: Simple sequence length • polymorphism • VNTR repeat clusters (minisatellite markers) • dinucleotide repeats (microsatellite markers) • VNTRs can be detected by restriction/Southern blot • analysis; both detected by PCR using primers for • each end of the repeat tract

  20. Variable number tandem repeats (VNTRs) • “minisatellite” DNA • 15-100 bp units; repeated in 1-5 kb blocks • expansion/contraction of the block due to • meiotic unequal crossingover • crossingover so frequent that each individual • has unique pattern (revealed by genomic • Southern blot/hybridization analysis)

  21. Using a SSLP marker to map a disease Fig. 12-12

  22. Using a SSLP marker to map a disease Unlinked Linked to P Linked to p Unlinked Fig. 12-12

  23. Polymorphism markers can provide a high resolution map Linkage map of human chromosome 1 Fig. 12-13

  24. High-resolution cytogenetic mapping • is based on: • In situ hybridization: hybridization of known • sequences directly to chromosome preparations • Rearrangement break mapping • Radiation hybrid mapping

  25. FISH analysis using a probe for a muscle protein gene Fig. 12-14

  26. Survey clones from the region of the break to determine one that spans the break Fig. 12-16

  27. Survey clones from the region of the break to determine one that spans the break FISH analysis locates the sequence and the breakpoint cytogenetically Fig. 12-16

  28. Cytogenetic map of human chromosome 7 Fig. 12-24

  29. Determining the sequence map sites of rearrangement breakpoints and other mutations Fig. 12-17

  30. Mapping & determining a gene of interest Fig. 12-18

  31. Genome sequencing projects • Sequence individual clones and subclones • (extensive use of robotics) • Identify overlaps to assemble sequence • contigs (extensive use of computer-assisted • analysis) • Identify putative genes by identifying open • reading frames, consensus sequences and • other bioinformatic tools

  32. Once a genomic sequence is obtained, it is subjected to • bioinformatic analysis to determine structure and function • Identify apparent ORFs and consensus regulatory sequences • to identify potential genes • Identify corresponding cDNA (and EST) sequences to identify • genuine coding regions • Polypeptide similarity analysis (similarity to polypeptides • encoded in other genomes)

  33. Genes and their components have characteristic sequences Bioinformatic analysis of raw sequences can suggest possible features Fig. 12-19

  34. Confirmation of genes and their architecture is obtained by analysis of cDNAs cDNA subprojects are key facets of a genome project Fig. 12-20

  35. High-resolution genomics arises through the combination of bioinformatics and experimentation Fig. 12-21

  36. Using bioinformatics to make detailed gene predictions Fig. 12-22

  37. Complete sequence and partial interpretation of a complete human chromosome Fig. 12-23

  38. Comparative genomics reveals ancestral chromosome rearrangements Fig. 12-26

  39. Microarray analysis – a form of functional genomics Arrays hybridized to cDNAs prepared from total RNA Relative intensity (color-coded) reflects abundance of individual RNAs 1046 cDNA array 65,000 oligo array (representing 1641 genes) Fig. 12-27

  40. Fig. 12-

  41. Fig. 12-

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