The genomes of living organisms vary enormously in size

Four classes of DNA polymorphisms

Single nucleotide polymorphism (SNP)
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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
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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
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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

Fig. 10.27
Mass spectrometer

Fig. 11.12
Microsatellite allele detection analysis of size differences

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
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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

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(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
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Linkage maps used to derive a physical map
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 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
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Overlapping clones aligned by restriction mapping
Sequence tag segments (STSs)

Fig. 10.8
High density linkage mapping to build overlapping set of genomic clones

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

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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
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Whole genome randomly sheared three times
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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)

Fig. 10.23
High-throughput DNA sequencing

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

Fig. 11.16 a
Cloning human genes
A pedigree of the royal family descended from Queen Victoria
In which hemophilia A is segregating

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
 RNA expression assayed by Northern blot or RT-PCR with primers specific to candidate transcript
 Look for misexpression (no expression, underexpression, overexpression)
 Sequence differences
 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

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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