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The genomes of living organisms vary enormously in size Four classes of DNA polymorphisms Single nucleotide polymorphism (SNP) Single base-pair substitutions Arise by mutagenic chemicals or mistakes in replication Biallelic – only two alleles 2001 – over 5 million human SNPs identified Most occur at anonymous loci Useful as DNA markers Fig. 11.2 Microsatellites 1 every 30,000 bp Repeated units 2 – 5 bp in length Mutate by replication error Useful as highly polymorphic DNA markers Fig. 11.3 Minisatellites Repeating units 20-100 bp long Total length of 0.5 – 20 kb 1 per 100,000 bp, or about 30,000 in whole genome Fig. 11.4 Deletions, duplications, and insertions Expand or contract the length of nonrepetitive DNA Small deletions and duplications arise by unequal crossing over Small insertions can also be caused by transposable elements Much less common than other polymorphisms Figure 11.5 Formation of haplotypes over time SNP detection using southern blots Restriction fragment length polymorphisms (RFLPs) are size changes in fragments due to the loss or gain of a restriction site Fig. 11.6 SNP detection by PCR Must know sequence on either side of polymorphism Amplify fragment Expose to restriction enzyme Gel electrophoresis e.g., sickle-cell genotyping with a PCR based protocol Fig. 11.7 SNP detection by ASO Very short probes (<21 bp) that hybridize to one allele or other Such probes are allele-specific oligonucleotides (ASOs) Fig. 11.8 ASOs can determine genotype at any SNP locus Fig. 11.9 a-c Hybridized and labeled with ASO for allele 1 Hybridized and labeled with ASO for allele 2 Fig. 11.9 d, e Preimplantation embryo diagnosis of CF using ASO analysis Fig. 11.1 Fig. 11.1 Fig. 11.1 High-throughput instruments e.g, microarrays Fig. 10.24 Large-scale multiplex ASO analysis with microarrays can detect BRCA1 mutations Each column contains an ASO differing only at the nucleotide position under analysis BRCA1 DNA from any one allele can only be one of four ASOs in a column Heterozygotes are easily deteted Fig. 11.10 Primer extension to detect SNPs Mass spectrometer Fig. 10.27 Microsatellite allele detection analysis of size differences Fig. 11.12 Huntington’s disease is an example of a microsatellite triplet repeat in a coding region Fig. 11.13 Minisatellite detection and DNA fingerprinting 1985 – Alec Jeffreys made two key findings Each minisatellite locus is highly polymorphic Most minisatellites occur at multiple sites around the genome DNA fingerprint – pattern of simultaneous genotypes at a group of unlinked loci Use restriction enzymes and southern blots to detect length differences at minisatellite loci Most useful minisatellites have 10 – 20 sites around genome and can be analyzed on one gel Fig. 11.14 Minisatellite analysis Fig. 11.15 DNA fingerprints can identify individuals and determine parentage E.g., DNA fingerprints confirmed Dolly the sheep was cloned from an adult udder cell Donor udder (U), cell culture from udder (C), Dolly’s blood cell DNA (D), and control sheep 1-12 Human Karyotype (a) complete set of human chromosomes stained with Giemsa dye shows bands (b) Ideograms show idealized banding pattern Fig. 10.5 a Chromosome 7 at three levels of resolution Fig. 10. 5 b FISH protocol for top-down approach DNA hybridization and restriction mapping – a bottom-up approach Fig. 10.7 Identifying and isolating a set of overlapping fragments from a library Two approaches Linkage maps used to derive a physical map set of markers less than 1 cM apart Use markers to retrieve fragments from library by hybridization Construct contigs – two or more partially overlapping cloned fragments Chromosome walk by using ends of unconnected contigs to probe library for fragments in unmapped regions Physical mapping techniques Direct analysis of DNA Overlapping clones aligned by restriction mapping Sequence tag segments (STSs) High density linkage mapping to build overlapping set of genomic clones Fig. 10.8 Physical mapping of overlapping genomic clones without linkage information Fig. 10.10 Physical mapping by analysis of STSs Fig. 10.11 Each STS represents a unique segment of the genome amplified by PCR. Sequence maps show the order of nucleotides in a cloned piece of DNA Two strategies for sequence human genome Hierarchical shotgun approach Whole-genome shotgun approach Shotgun – randomly generated overlapping insert fragments Fragments from BACs Fragments from shearing whole genome Shearing DNA with sonication Partial digestion with restriction enzymes Hierarchical shotgun strategy Used in publicly funded effort to sequence human genome Shear 200 kb BAC clone into ~2 kb fragments Sequence ends 10 times Need about 1700 plasmid inserts per BAC and about 20,000 BACs to cover genome Data from linkage and physical maps used to assemble sequence maps of chromosomes Significant work to create libraries of each BAC and physically map BAC clones Fig. 10.12 Whole-genome shotgun sequencing Private company Celera used to sequence whole human genome Whole genome randomly sheared three times Plasmid library constructed with ~ 2kb inserts Plasmid library with ~10 kb inserts BAC library with ~ 200 kb inserts Computer program assembles sequences into chromosomes No physical map construction Only one BAC library Overcomes problems of repeat sequences Fig. 10.13 Sequencing of the human genome Most of draft took place during last year of project Intruments improvements – 345,600 bp/day Automated factory-like production line generated sufficient DNA to supply sequencers on a daily basis Large sequencing centers with 100-300 instruments – 103,680,000 bp/day (10-fold coverage in 30 days) High-throughput DNA sequencing Fig. 10.23 Integration of linkage, physical, and sequence maps Provides check on the correct order of each map against other two SSR and SNP DNA linkage markers readily integrated into physical map by PCR analysis across insert clones in physical map SSR, SNP (linkage maps), and STS markers (physical maps) have unique sequences 20 bp or more allowing placement on sequence map Cloning human genes A pedigree of the royal family descended from Queen Victoria In which hemophilia A is segregating Fig. 11.16 a Blood-clotting cascade in which vessel damage causes a cascade of inactive factors to be converted to active factors Fig. 11.16 b Blood tests determine if active form of each factor in the cascade is present Fig. 11.16 c Techniques used to purify Factor VIII and clone the gene Fig. 11.16 d Positional Cloning – Step 1 Find extended families in which disease is segregating Use panel of polymorphic markers spaced at 10 cM intervals across all chromosomes About 300 markers total Determine genotype for all individuals in families for each DNA marker Look for linkage between a marker and disease phenotype Once region of chromosome is identified, a high resolution mapping is performed with additional markers to narrow down region where gene may lie Fig. 11.17 Positional cloning – Step 2 identifying candidate genes Once region of chromosome has been narrowed down by linkage analysis to 1000 kb or less, all genes within are identified Candidate genes Usually about 17 genes per 1000 kb fragment Identify coding regions Computational analysis to identify conserved sequences between species Computational analysis to identify exon-like sequences by looking for codon usage, ORFs, and splice sites Appearance in one or more EST databases Computational analysis of genomic sequences to identify candidate genes Fig. 11.19 Gene expression patterns can pinpoint candidate genes Look in public database of EST sequences representing certain tissues Northern blot RT-PCR Northern blot example showing SRY candidate for testes determining factor is expressed in testes, but not lung, ovary, or kidney Fig. 11.20 Positional cloning – Step 3 Find the gene responsible for the phenotype Expression patterns in affected individuals Sequence differences RNA expression assayed by Northern blot or RT-PCR with primers specific to candidate transcript Look for misexpression (no expression, underexpression, overexpression) Missense mutations identified by sequencing coding region of candidate gene from normal and abnormal individuals Transgenic modification of phenotype Insert the mutant gene into a model organism Transgenic analysis can prove candidate gene is disease locus Fig. 11.21 Example: Positional Cloning of Cystic Fibrosis Gene Linkage analysis places CF on chromosome 7 Fig. 11.22 a Northern blot analysis reveals only one of candidate genes is expressed in lungs and pancreas Fig. 11.22 b Every CF patient has a mutated allele of the CFTR gene on both chromosome 7 homologs Location and number of mutations indicated under diagram of chromosome Fig. 11.22 c CFTR is a membrane protein. TMD-1 and TMD-2 are transmembrane domains. Fig. 11.22 d Proving CFTR is the right gene Phenotype eliminates gene function Cannot use transgenic technology Instead perform CFTR gene “knockout” in mouse to examine phenotype without CFTR gene Targeted mutagenesis Genetic dissection of complex traits Incomplete penetrance – when a mutant genotype does not always cause a mutant phenotype No environmental factor associated with likelihood of breast cancer Positional cloning identified BRCA1 as one gene causing breast cancer. Only 66% of women who carry BRCA1 mutation develop breast cancer by age 55 Incomplete penetrance hampers linkage mapping and positional cloning Solution – exclude all nondisease individuals form analysis Requires many more families for study Phenocopy Disease phenotype is not caused by any inherited predisposing mutation Decreases power to detect correlation between inheritance of disease locus and expression of the disease Genetic heterogeneity Mutations at more than one locus cause same phenotype Multiple families used in most studies If different families have different gene mutations, power of statistics to detect linkage will drop significantly Polygenic inheritance Two or more genes interact in the expression of phenotype QTLs, or quantitative trait loci Unlimited number of transmission patterns for QTLs Discrete traits – penetrance may increase with number of mutant loci Expressivity may vary with number of loci Many other factors complicate analysis Some mutant genes may have large effect Mutations at some loci may be recessive while others are dominant or codominant