Fig Chapter 12: Genomics

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

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)

Fig Overview of genome sequencing

Fig Sequencing the ends of clones in a library

Fig Overview of genome sequencing

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Fig Overview of genome sequencing

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

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)

Fig Inheritance of an RFLP:

Fig Inheritance of an RFLP: Determining linkage to a known gene

Fig Inheritance of an RFLP: Determining linkage to a known gene

Fig Linkage analysis of a gene and VNTR markers

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)

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

Variable number tandem repeats (VNTRs) “minisatellite” DNA 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)

Fig Using a SSLP marker to map a disease

Fig Using a SSLP marker to map a disease Unlinked Linked to P Linked to p Unlinked

Fig Polymorphism markers can provide a high resolution map Linkage map of human chromosome 1

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

Fig FISH analysis using a probe for a muscle protein gene

Fig Survey clones from the region of the break to determine one that spans the break

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

Fig Cytogenetic map of human chromosome 7

Fig Determining the sequence map sites of rearrangement breakpoints and other mutations

Mapping & determining a gene of interest Fig

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

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)

Fig Genes and their components have characteristic sequences Bioinformatic analysis of raw sequences can suggest possible features

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

Fig High-resolution genomics arises through the combination of bioinformatics and experimentation

Fig Using bioinformatics to make detailed gene predictions

Fig Complete sequence and partial interpretation of a complete human chromosome

Fig Comparative genomics reveals ancestral chromosome rearrangements

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

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