genome biology and biotechnology

Genome Biology and Genome Biology and BiotechnologyBiotechnology

3. The genome structures of vertebrates3. The genome structures of vertebrates

Prof. M. ZabeauProf. M. ZabeauDepartment of Plant Systems Biology Department of Plant Systems Biology

Flanders Interuniversity Institute for Biotechnology (VIB)Flanders Interuniversity Institute for Biotechnology (VIB)University of GentUniversity of Gent

International course 2005International course 2005

The Genome Sequences of The Genome Sequences of vertebratesvertebrates

¤ Fish genomes: “compact” vertebrate genomes– Fugu rubripes (2002)– Tetraodon nigroviridis (2004)

¤ Bird genome: Interesting evolutionary intermediate– Chicken - Gallus gallus (2004)

¤ Rodent genomes: the model organism for the human– Mouse - mus musculus (2002)– Rat – Rattus norvegicus (2004)

¤ Primate genomes: our closest relatives– Chimpanzee

¤ Human genome– Draft genome sequence (2001)– Finished genome sequence (2004)

vertebrate vertebrate evolution evolution

310 MY

450 MY

Reprinted from: ICGSC, Nature 432, 695 - 716 (2004)

Whole-Genome Shotgun Assembly and Whole-Genome Shotgun Assembly and Analysis of the Genome of Analysis of the Genome of Fugu rubripesFugu rubripes

¤ Paper presents– Low quality draft genome sequence of Fugu rubripes – the sequence provided a valuable reference for annotating

the human and mouse genomes• Small genome (350 Mb versus 3000 Mb)• low repetitive DNA content

Aparicio et al., Science, 297, 1301-1310 (2002)

Reprinted from: Aparicio et al., Science, 297, 1301-1310 (2002)

The Fugu Genome SequenceThe Fugu Genome Sequence

¤ The draft sequence covers a total of 332.5 Mb– Highly fragmented sequence (~30 Mb unassembled

sequences) – The total genome size is estimated at ~365 Mb

¤ The number of predicted genes: 31,059– similar to the number of human genes predicted from the

draft sequence

¤ Repetitive sequences– Density of <15% far below the 35 to 45% observed in

mammals • Transposable elements are still very active


Protein-coding genesProtein-coding genes

¤ The gene-containing fraction is a ~ 108 Mb (30%)– The average gene density: one gene per 10.9 kb– The Fugu genome is compact because introns are shorter

than in the human genome • Genome contains ~500 large introns (> 10 kb) compared >

12,000 large introns in human• Genes are scaled in proportion to the compact genome size

– The number of introns is roughly the same as in human• Both gain and loss of introns in the Fugu lineage are observed

¤ The compactness of the Fugu is accounted for by – Low abundance of repeated sequences– The small size of introns and intergenic regions


Comparison of Comparison of FuguFugu and Human and Human ProteomesProteomes

¤ 75% of predicted human proteins have a strong match to Fugu

Genome duplication in the teleost fish Genome duplication in the teleost fish Tetraodon nigroviridis reveals the early Tetraodon nigroviridis reveals the early

vertebrate proto-karyotypevertebrate proto-karyotype

¤ Paper presents – High quality draft genome sequence with long-range

linkage and chromosome anchoring of Tetraodon nigroviridis

• freshwater puffer fish with the smallest known vertebrate genome

Jaillon et. al., Nature 431, 946 - 957 (2004)

Reprinted from: Jaillon et. al., Nature 431, 946 - 957 (2004)

The Tetraodon genome sequenceThe Tetraodon genome sequence

¤ The draft genome sequence (8,3 x) spans 342 Mb– Largest scaffolds were mapped onto the chromosomes

• Draft is much less fragmented than that of Fugu

¤ Genome landscape – Transposable elements are very rare (<4000 copies)

• Fewer than Fugu (15% of the genome)

¤ Estimated 20,000–25,000 protein coding genes– Very similar to the recent (2004) human gene count – Much lower than reported for Fugu (current Fugu is also

lower)– Gene ontology (GO) classifications shows only subtle

differences between fish and mammals• Improved fish gene catalogue aids human gene predictions


Evidence For Whole-genome Evidence For Whole-genome Duplication Duplication

¤ Duplicated genes cluster on paralogous chromosomes– paralogous chromosomes arising from whole-genome duplication

each contain one member of duplicated gene pairs in the same order


Evidence For Whole-genome Evidence For Whole-genome Duplication Duplication

¤ Blocks of doubly conserved synteny – The synteny map typically associates two regions in

Tetraodon with one region in human Tni: TetraodonHsa: human


Ancestral genome of bony Ancestral genome of bony vertebratesvertebrates

¤ The patterns of doubly conserved synteny are consistent with – 12 ancestral chromosomes which have rearranged to form – the present day chromosomes of human and fish

Human Fish

Sequence and comparative analysis of the Sequence and comparative analysis of the chicken genome provide unique chicken genome provide unique

perspectives on vertebrate evolutionperspectives on vertebrate evolution

¤ Paper presents – a draft genome sequence of the red jungle fowl Gallus

gallus– The first genome of non-mammalian amniote

• provides a new perspective on vertebrate genome evolution

– The evolutionary distance between chicken and human provides an excellent signal-to-noise ratio to detect functional elements

• 310 MY since the divergence of birds and mammals

International Chicken Genome Sequencing Consortium, Nature 432, 695 - 716 (2004)


The chicken genome sequenceThe chicken genome sequence

¤ The draft genome sequence (6,6 x) spans 1.050 Mb– Draft represents ~96% of the euchromatic part of the genome– 23,212 chicken mRNAs and 485,000 ESTs

¤ Chicken genome is 3x smaller than mammalian genomes reflecting substantially fewer– interspersed repeats

• transposable elements make up <9% of the genome, markedly lower than the 40–50% observed in mammalian genomes

– Pseudogenes• 51 retrotransposed genes vs. > 15,000 in mammalian

genomes – segmental duplications

• Limited to very small (<10kb) intrachromosomal duplications


Gene content of the chicken genomeGene content of the chicken genome

¤ Protein-coding genes– Predict 20,000 to 23,000 protein-coding genes – Matches the current (2004) estimate for mammalian genomes

¤ Non-coding RNA genes– 571 ncRNA genes from >20 gene families

• Fewer than in human: many ncRNA genes are pseudogenes– Syntenic relationships for non-coding RNA genes differ from

those of protein-coding genes• implies a novel mode of evolution for some ncRNA genes• Only certain ncRNA genes are in regions of conserved

synteny – microRNAs (miRNAs) and small nucleolar RNAs

(snoRNAs) found in introns of protein-coding genes

Evolutionary conservation of gene Evolutionary conservation of gene components components

¤ Sequence conservation of chicken and human orthologs – highest in protein-coding exons – minimal in introns– Significant in the 5' and 3' flanking and untranslated

regions

exon 3’UTR5’UTR



Conservation of vertebrate protein Conservation of vertebrate protein content content

¤ 60% of chicken genes have a single human orthologue– also have a single orthologue

in the Fugu genome– Represent a conserved core

present in most vertebrates

Conserved core Conserved core orthologuesorthologues in in vertebratesvertebrates

¤ Core orthologues conserved in vertebrates have – Highly conserved protein sequences indicating that

• They have been subject to purifying selection



Expansion of multigene familiesExpansion of multigene families

¤ Expansion and contraction of multigene families were– major factors in the independent evolution of mammals and

birds


Chromosomal dynamicsChromosomal dynamics in the in the vertebratesvertebrates

¤ Maps of conserved synteny: orthologous chromosomal segments with conserved gene order show– slow rate of rearrangement in the human lineage

• 3-fold higher rate in the rodent lineage

– The human genome is closer to the chicken in terms of synteny


Ancestral Ancestral mammalian mammalian

genome genome ¤ Long blocks of

conserved chicken–human synteny

– Entire chromosomes

¤ Genome rearrangements

– Many intrachromosomal rearrangements

– Few translocations between chromosomes

– Chicken has a number of micro-chromosomes


Conserved sequencesConserved sequences in in chicken and chicken and human human

¤ High substitution rates between human and chicken– Can be used to detect functionally conserved sequences

¤ 70 Mb (2.5%) of human sequence aligns with chicken– 44% are in protein-coding regions - exons– 66% is non-coding: intronic (25%) and intergenic (31%)

¤ Conserved non-coding segments occur clustered and far from genes – Identified 57 segments with average length of 1,1 MB

• gene poor, G+C poor and have no interspersed repeats– the functional significance of these sequences is

completely unknown


ConclusionConclusion

¤ The chicken genome sequence– is a key resource for comparative genomics

• to distinguish derived or ancient features of mammalian biology

– mammalian innovation and adaptation• conserved non-coding sequences in particular

– Provides a framework for discovering the functional polymorphisms underlying

• interesting quantitative traits to further exploit the genetic potential of the chicken

Initial sequencing and comparative Initial sequencing and comparative analysis of the mouse genome analysis of the mouse genome

¤ Paper presents – Draft genome sequence of the mouse– comparative analysis of the mouse and human genomes

• 75 MY since the divergence of rodents and primates

• The two genome sequences diverge by nearly one substitution for every two nucleotides

– the insights that can be gleaned from the two sequences

Mouse Genome Sequencing Consortium, Nature 420, 520 - 562 (2002)

Reprinted from: Mouse Genome Sequencing Consortium, Nature 420, 520 - 562 (2002)

The Mouse Genome ProjectThe Mouse Genome Project

¤ The laboratory mouse is an experimental model system – for studying human disease and mammalian biology

¤ The Mouse Genome Project– International collaboration of centres in the US and the UK – Adopted mixed strategy for the draft genome sequencing

• a BAC-based physical map of the mouse genome• The initial draft genome sequence was generated by

– WGS sequencing to ~7-fold coverage – Hierarchical shotgun sequencing of BAC clones

– The finished sequence should be completed in 2005 • using the BAC clones for directed finishing


The draft mouse genome sequenceThe draft mouse genome sequence

¤ The euchromatic mouse genome is estimated ~2.5 Gb – The draft genome sequence covers ~96% of the genome

¤ Generation of the draft genome sequence– Sequencing

• 41.4 Mi paired-end sequence reads derived from various clone types

– Assembly• represents ~7.7-fold sequence coverage• 224,713 sequence contigs• total of 7,418 supercontigs• The 200 largest supercontigs span more than 98% of the

assembled sequence

– Anchoring to chromosomes • Anchored all supercontigs >500 kb with the mouse genetic map


The draft mouse genome sequenceThe draft mouse genome sequence

¤ The euchromatic mouse genome is estimated ~2.5 Gb – The draft genome sequence covers ~96% of the genome

¤ Comparative analysis of human and mouse genomes– The mouse genome is about 14% smaller than the human

genome – High degree of synteny

• >90% of the two genomes can be partitioned into corresponding regions of conserved synteny

– At the nucleotide level, approximately 40% of the human genome can be aligned to the mouse genome.

• represent orthologous sequences conserved from the common ancestor


Synteny between mouse and humanSynteny between mouse and human

¤ Regions containing orthologous sequence pairs define– Syntenic segments as regions in which

• Orthologous sequence pairs are in the same order on a chromosome in both species


Synteny between mouse and humanSynteny between mouse and human

¤ Conservation of orthologous sequence pairs shows – Each genome can be parsed into a total of 342 conserved

syntenic segments. • The segments vary greatly in length, from 303 kb to 64.9 Mb• In total, about 90.2% of the human genome and 93.3% of the

mouse genome reside within conserved syntenic segments

– The segments can be aggregated into a total of 217 conserved syntenic blocks

¤ The syntenic block and segment sizes are – consistent with the random breakage model of genome

evolution– the minimal number of rearrangements needed to

'transform' one genome into the other is 295 rearrangements


Blocks of conserved synteny in the human Blocks of conserved synteny in the human and mouse genomesand mouse genomes


Repetitive sequences in human and Repetitive sequences in human and mousemouse

¤ The most prevalent feature of mammalian genomes is their high content of repetitive sequences– Most of which are interspersed repeats representing 'fossils' of

transposable elements

¤ The repetitive sequences in mouse and human differ– Only 37.5% of the mouse genome– ~46% of the human genome is transposon-derived– Insertions of transposable elements occured in the last 150–

200 million years• The most notable difference is the rate of transposition over time

– in mouse the rate has remained fairly constant– in human the rate increased to a peak at ~40 Myr, and

then plummeted


Age distribution of interspersed repeats in the Age distribution of interspersed repeats in the mouse and human genomes mouse and human genomes

Human

Mouse


Protein-coding genes in mouse and Protein-coding genes in mouse and humanhuman

¤ Human and mouse gene catalogues– The current human gene catalogue (Ensembl build 29) contains

22,808 predicted genes– The current mouse gene catalogue contains 22,011 predicted genes

¤ Comparative analysis of protein coding genes shows– 80% of the mouse genes have orthologues in the human genome

• The proportion of mouse/human genes without any homologue is < 1%.– Many local gene family expansions have occurred in the mouse

lineage• Most seem to involve genes for reproduction, immunity and olfaction

– The rate of protein evolution• Most proteins evolve at fairly constant rate• Certain proteins evolve much more rapidly: positive selection

– Proteins implicated in reproduction, host defence and immune response seem to be under, which drives

ConclusionsConclusions

¤ The mouse genome provides a powerful resource to unravel the secrets of the human genome– Demonstrates the power of comparative genomics in

identifying relevant genetic elements– These findings inspired additional animal genome

sequencing projects to fully exploit the power of comparative genomics

• As illustrated in: Thomas et. al., Nature 423, 788 - 793 (2003)

– The sequence provides a comprehensive framework for functional genomics approaches to unravel gene functions in both human and mouse

Genome sequence of the Brown Norway Genome sequence of the Brown Norway rat yields insights into mammalian rat yields insights into mammalian

evolutionevolution

¤ Paper presents– a high-quality 'draft' sequence covering > 90% of the

genome– a three-way comparison with the human and mouse

genomes to study the mammalian genome evolution• Rat - mouse common ancestor: 12–24 Myr • Rodent - human common ancestor: 75 Myr

RGSPC, Nature 424: 493 - 521 (2004)

Reprinted from: RGSPC, Nature 424: 493 - 521 (2004)

TheThe rat rat genome sequencegenome sequence

¤ The draft genome sequence covers 2,75 Gb– A 'combined' sequencing strategy using

• WGS sequencing and light sequence coverage of BACs• Sequential assembly of 'enriched BACs' (eBACs) joined into

bactigs, superbactigs and ultrabactigs

eBAC


Rat – mouse – human genome Rat – mouse – human genome sequencessequences

¤ Sequence elements in human, mouse and rat genomes – 40% align in all 3 species

• 'ancestral core' of 1 Gb• 95% of the exons and

regulatory regions– 28% aligns only with

mouse• rodent-specific repeats

– 29% does not align• rat-specific repeats


Evolution of genesEvolution of genes

¤ Estimate that 90% of rat genes possess– strict orthologues in both mouse and human

• Intronic structures are well conserved

– Most of the non-orthologous genes• Arose by expansions of gene families in the different lineages• Rapidly evolving genes

– Rat-specific genes comprise novel genes for “life style”• pheromones, immunity, chemosensation, detoxification,

proteolysis


Rat – mouse – human syntenyRat – mouse – human synteny

¤ orthologous chromosome segments– 105 mouse–rat segments– 278 human-rat segments– 280 human-mouse

segments


Rat – mouse – human genome Rat – mouse – human genome rearrangementsrearrangements

¤ Reconstruction of the ancestral mammalian genome– Identified a total of 353 rearrangements

• 247 between the murid ancestor and human• 50 from the murid ancestor to mouse • 56 from the murid ancestor to rat

– much higher (3x) rearrangement rate in the rodent than in the human lineage

24750

56

The Human GenomeThe Human Genome

¤ The human genome project was launched in 1990– Phase I: generation of genetic and physical maps (1990-1995)

• Demonstration that large scale sequencing is feasible: yeast, worm

– Phase II: large scale sequencing (1995-2005)• Pilot phase: finished sequence with 99.99% accuracy and no gaps

of the human chromosomes 21 and 22 (published in ’98 and ‘99)• Draft phase : draft sequence covering >90% of the genome

completed in June 2000 (published in 20001 ) – took ~1 year• Finishing phase: “finished” covering 99% of the genome sequence,

completed in spring 2004 – took ~3 years• Aftermath: no end point projected

– closing the last couple of hundred gaps– Sequencing the centromeres

Reprinted from: International Human Genome Sequencing Consortium Nature 409, 860 (2001)

The Human Genome SequencesThe Human Genome Sequences

¤ Draft genome sequences (2001)– International Human Genome Sequencing Consortium

(Collaboration of 20 public sequencing centers in 6 countries)

• Used a hierarchical shotgun sequencing strategy • Sequence published in: Nature 409, 860 (2001)

– Celera Genomics - private initiative• Used a whole-genome shotgun approach • Assembly of the sequence combined their whole-genome

shotgun data and the public genome sequence data• Sequence published in: Venter et. al., Science, 291, 1304

(2001)

¤ Finished genome sequence (2004)– International Human Genome Sequencing Consortium

• Sequence published in: Nature 431, 931 - 945 (2004)

Finished Human Genome SequenceFinished Human Genome Sequence

¤ Finishing process: complex iterative process– Resolving problematic sequences

• From single nucleotide errors and gaps to the integrity of whole chromosomes

– The finishing process involved two distinct components• producing finished maps consisting of continuous and accurate

paths of overlapping large-insert clones• producing finished clone sequences, consisting of continuous

and accurate nucleotide sequences for each clone– generated shotgun sequence of ~59.000 BACs comprising

a total sequence (redundant) length of 5,8 Gb

– Assembled sequences of ~46.000 BACs

Reprinted from: International Human Genome Sequencing Consortium Nature 431, 931 - 945 (2004)


¤ Finished genome sequence– Build 35 comprises 2.851 Mbp– Interrupted by “only” 341 gaps

• 308 gaps in the euchromatic sequence: totalling ~28 Mb• 33 heterochromatic gaps (including 24 centromeres) : total ~198

Mb

– The total human genome size is estimated at ~3,080 Mb

¤ Comparison with draft sequence– Substantially fewer gaps (341 versus 147,821)– More accurate and complete sequence: error rate ~1 per 105

• Confirmed local order and orientation of the sequences• Corrected artefactual duplications resulting from mixups• Verified most of the sequence with

– BAC cloned overlap sequence, paired end sequence reads from fosmids, draft chimpanzee genome sequence



¤ Importance of a completely finished genome sequence – Accurate reference for identifying genetic variation in the human

population• Error rate of 10-5 << frequency of SNP of 10-3

– Identification of segmental duplications• Estimated to cover >5% of the genome sequence

– Located primarily in the pericentromeric and subtelomeric regions– much higher than in mouse and rat

• Great medical interest: predisposes to deletion or rearrangement– Williams syndrome region (7q)– Charcot–Marie–Tooth region (17p)– DiGeorge syndrome region (22q)

• Many remaining gaps involve unresolved segmental duplications

– Correct identification of all protein- coding genes structures• ~60% of the gene models were corrected compared to the draft


Estimates of the Number of Human GenesEstimates of the Number of Human Genes

¤ Reassociation kinetics (60s and 70s)– Early estimates based estimated the mRNA complexity of typical

vertebrate tissues to be 10,000–20,000, and were extrapolated to suggest around 40,000 genes for the entire genome

¤ Estimates from approximate gene and genome sizes – Calculation based on the size of a typical gene ( 3*104 bp) and the

size of the genome (3*109 bp) yielded 100,000 genes (W. Gilbert, pers. Com.)

¤ Number of CpG islands associated with known genes– An estimate of 70,000–80,000 genes was made

¤ Estimates based on ESTs– Estimates based on ESTs varied widely, from 35,000 to 120,000 genes – Discrepancy results from contaminating genomic sequences and

multiple ESTs from single genes

¤ Whole-genome shotgun sequence from the pufferfish – Suggested around 30,000 human genes


Identification of Protein Coding GenesIdentification of Protein Coding Genes

¤ Draft genome sequence– Initial estimate: 30.000–35.000 genes

¤ Finished genome sequence– The human gene catalogue contains 22,287 gene loci

consisting of 19,438 known genes and 2,188 predicted genes – Current estimate: 20.000–25.000 genes

• 25.000 is an upper limit, the actual number may be ~23.000• Consistent with gene counts in other vertebrates: fish and

chicken


Basic Characteristics of Gene StructuresBasic Characteristics of Gene Structures

¤ Mean and median values of gene structures– Based on the draft sequence

• In particular, the UTRs in the RefSeq database are incomplete


Protein Coding GenesProtein Coding Genes¤ General features of human genes

– average coding length of about 1,400 bp• Similar to al eukaryotic organisms

– average genomic extent of about 30 kb• Much larger than in lower eukaryotes

– The variation in gene and intron size• GC-rich regions: gene-dense with many compact genes• AT-rich regions: gene-poor with genes containing large introns

¤ Known and predicted exons: ~231.000– 1,2% of the human genome– Average of 10.4 exons per gene

¤ Pseudogenes– Current estimates: 20.000 processed and unprocessed

pseudogenes • The total number of pseudogenes is thus likely to exceed the

total number of functional genes • Only those of recent origin can be identified with confidence


Basic Characteristics of Gene StructuresBasic Characteristics of Gene Structures

¤ High variation in overall intron size– distribution has very long tails

• Many genes are over 100 kb long– Largest gene: dystrophin gene (DMD) 2.4 Mb– longest known coding sequence: titin gene 80,780 bp, 178 exons


Comparison with fly, worm and yeastComparison with fly, worm and yeast

¤ Apparent homologues of human proteins– 40% to 60% of the yeast, worm and fly proteomes

¤ Human genes differ from those in worm and fly– Spread out over much larger regions of genomic DNA– Have a substantially larger number of exons

• 4,5 to 5 in fly and worm compared to 10,4 in human

– Are used to construct more alternative transcripts• Larger number of proteins in human than in the worm or fly

¤ Increased complexity of the proteome – Complexity of the human proteome is a consequence of

large-scale protein innovation• Multi-domain proteins with multiple functions, and domain

architectures


Protein Coding Gene Evolution in HumanProtein Coding Gene Evolution in Human

¤ Gene birth in the human lineage– gene duplications that arose after divergence from the

mouse• Identified 1,183 gene clusters containing 3,300 recently

duplicated genes ( with a peak 3–4 million years ago ) enriched in genes with

– immune function– olfactory function– reproductive functions

– Duplicated genes are the raw material for adaptive evolution:

• extra copies are able to undergo functional divergence in response to positive selection

¤ Gene death in the human lineage– Recently inactivated genes include genes in olfactory

functionReprinted from: International Human Genome Sequencing Consortium Nature 431, 931 - 945

(2004)

Future PerspectivesFuture Perspectives

¤ Vertebrate genome sequencing projects ongoing or planned (currently totaling 25)– Fish: zebrafish, salmon, tilapia, stickleback and Japanese

medaka– Amphibians: Xenopus laevis and X. tropicalis – Birds: turkey– Mammals: ~15 additional species

• cow, pig, cat, dog, horse, rabbit, guinea pig, elephant, kangaroo, shrew,….

– Primates: chimp, orangutan, baboon and rhesus monkey

¤ Source: GOLDTM Genomes OnLine Database – http://www.genomesonline.org/

Genome Biology and Genome Biology and BiotechnologyBiotechnology

4. The variable human genome4. The variable human genome

International course 2005International course 2005

SummarySummary

¤ Sequence Variations in the Human Genome¤ Haplotype structure of the sequence

variations in the human genome– linkage disequilibrium in the human genome– haplotype blocks in the human genome

¤ The haplotype map of the human genome– Map of all the genetic variations in the human population

Sequence Variations in the Human Sequence Variations in the Human GenomeGenome

¤ Most human sequence variation (>90%) results from – SNPs (single nucleotide polymorphisms)– SNPs are the result of very rare replication errors in which

a wrong base remains incorporated in the newly synthesized strand

¤ Human sequence variation is responsible for – Phenotypic variation between individuals– Influencing the risk of common human diseases

The International HapMap Consortium et. al., Nature 437, 1299 (2005)

Root causes of common human Root causes of common human diseases diseases

¤ Causes of human diseases are largely unknown– preventative measures are generally inadequate– available treatments are seldom curative

¤ Family history is one of the strongest risk factors for nearly all diseases– cardiovascular disease, cancer, diabetes, autoimmunity,

psychiatric illnesses and many others– inherited genetic variation has an important role in the

pathogenesis of disease

¤ Identifying the causal genes and variants represents an important step towards – improved prevention, diagnosis and treatment of disease


Heritable human diseases Heritable human diseases

¤ Rare highly heritable 'mendelian' disorders– > 1000 genes have been identified– variation in a single gene causes disease

¤ Common human diseases– are thought to be due to the combined effect of

• many different susceptibility DNA variants• interacting with environmental factors

– have proven much more challenging to study


Common human diseasesCommon human diseases

¤ Studies of common diseases: 2 broad classes– family-based linkage studies across the entire genome

• linkage analysis has low power except when– a single locus explains a substantial fraction of disease

– population-based association studies of candidate genes • association studies examine only a small fraction of the

'universe' of sequence variation in each patient

¤ Comprehensive search for genetic influences – examining all genetic differences in a large number of

affected individuals and controls• complete genome resequencing • systematically test common genetic variants


Common genetic variants Common genetic variants

¤ Common genetic variants– explain much of the genetic diversity in our species– a consequence of the historically small size and shared

ancestry of the human population

¤ Common variants with an important role in disease

• HLA: autoimmunity and infection• APOE4: Alzheimer's disease, lipids• Factor VLeiden: deep vein thrombosis• PP: G: encoding PPAR; type 2 diabetes• KCNJ11: type 2 diabetes• PTPN22: rheumatoid arthritis and type 1 diabetes• CTLA4: autoimmune thyroid disease, type 1 diabetes• NOD2: inflammatory bowel disease• complement factor H: age-related macular degeneration• RET: Hirschsprung disease

Sequence Variations in the Human Sequence Variations in the Human GenomeGenome

¤ Most human sequence variation (>90%) results from – SNPs (single nucleotide polymorphisms)– SNPs occur on average every 1,000 bases when the

sequences of two human individuals are compared– Remainder of the human sequence variation is attributable to

• insertions or deletions of one or more bases• repeat length polymorphisms • Rearrangements

¤ SNPs are well suited to automated, high-throughput and low cost genotyping– SNPs are binary and can thus easily be typed – SNPs have a low rate of recurrent mutation– SNPs are present at sufficient density for comprehensive

genetic analysis

High throughput SNP Genotyping High throughput SNP Genotyping MethodsMethods

¤ Primer extension– Primer designed adjacent to the SNP, extended and the

extension product analyzed• Fluorescence• Mass spectrometry

¤ Oligonucleotide ligation– Ligation requires perfect base pairing of the terminal

nucleotides

¤ Array-based hybridization– high density Affymetrix microarrays

• 25-mer oligonucleotides are perfectly suited to discriminate SNP alleles

• Latest product 500.00 SNP array

A/C

T/G

Haplotype structure of the sequence Haplotype structure of the sequence variationsvariations

¤ Human genetic diversity appears to be– Limited: a small number of common polymorphisms explain

the bulk of the observed variation, • i.e. are found in most individuals in the population

– Structured: specific combinations of alleles – haplotypeshaplotypes – are observed at closely linked sites

recombinationHaplotype 1

Haplotype 2 SNP

Haplotype 3

Haplotype Structure of the Sequence Haplotype Structure of the Sequence VariationsVariations

¤ At a macroscopic scale (chromosome) – recurrent recombination results in complete linkage linkage

equilibriumequilibrium • random combinations of SNPs

Recombination1st generation

Random assortment of SNPs

N generations N recombination events

Haplotype Structure of the Sequence Haplotype Structure of the Sequence VariationsVariations

¤ At a microscopic scale (gene) – Non-random recombination results in linkage disequilibriumlinkage disequilibrium

• Non-random combinations of SNPs: haplotype blocks

1st generation

N generations

Haplotype blocks

Linkage disequilibrium in the human Linkage disequilibrium in the human genome genome

¤ Landmark paper presenting – a systematic analysis of the extent of linkage

disequilibrium in the human genome– a large-scale experiment to measure linkage disequilibrium

(LD) in 19 randomly selected genomic regions in• United States population of north-European descent • Nigerian population

Reich et. al., Nature 411, 199 (2001)

Reprinted from: Reich et. al., Nature 411, 199 (2001)

Experimental ApproachExperimental Approach

¤ Selected 19 high-frequency or common SNPs in genes as core SNPs– High-frequency SNPs tend to be common in all populations,

facilitating cross-population comparisons– Linkage disequilibrium around common alleles can be

measured with a modest sample size of 80–100 chromosomes

– Linkage disequilibrium around common alleles represents a 'worst case' scenario

• Such alleles are generally old and there has been ample historical opportunity for recombination to break down ancestral haplotypes



¤ High frequency SNPs were identified at various distances from the core SNPs– Re-sequenced regions of ~ 2 kb at 0, 5, 10, 20, 40, 80 and

160 kb from the core SNP in 44 unrelated individuals from Utah

• Identified a total of 272 'high frequency' polymorphisms

– Measured linkage disequilibrium between two SNPs using the classical statistic D‘

• D’ = observed linkage/maximal linkage: Pab/(Pa,Pb)

Core SNP

402010 80 160


Observed Linkage DisequilibriumObserved Linkage Disequilibrium

¤ Linkage disequilibrium has a half-length of ~ 60 kb – linkage disequilibrium extends much (10-fold) further than

previously predicted


Why does linkage disequilibrium extend Why does linkage disequilibrium extend so far?so far?

¤ Long-range linkage disequilibrium can be explained by– an extreme founder effect or population bottleneck

• A period when the population was so small that a few ancestral haplotypes gave rise to the present day haplotypes

¤ Linkage disequilibrium in different populations– short-range linkage disequilibrium is general in sub-Saharan

African populations– long-range linkage disequilibrium is typical for northern

Europeans• a severe bottleneck in the European population could have

generated the linkage disequilibrium

Origin of linkage disequilibrium?Origin of linkage disequilibrium?

¤ The bottleneck could be specific to northern Europe– Europe was substantially depopulated during the Last

Glacial Maximum (30,000–15,000 years ago), and subsequently recolonized by a small number of founders

• Long range linkage disequilibrium would be absent in other non-African populations

¤ The bottleneck is more global– Result of the dispersal of the modern humans from Africa

50,000 years ago• Long-range linkage disequilibrium would then be present in a

variety of non-African populations


High-resolution Haplotype Structure in High-resolution Haplotype Structure in the Human Genome the Human Genome

¤ Landmark paper presenting– High-resolution analysis of the haplotype structure across

500 kb region on chromosome 5q31 • Genotyped 103 common SNPs in 129 trios from a European-

derived population– Low marker density of 1 SNP roughly every 5 kb

– First high-resolution picture of the patterns of genetic variation across a large genomic region

Daly et. al., Nature Genet. 29, 229 (2001)

Block-like Haplotype Diversity at Block-like Haplotype Diversity at 5q315q31

¤ The common SNPs are arranged in haplotype blocks – span up to 100 kb – contain multiple (five or more) common SNPs – have only a few (2–4) haplotypes, which

• account for the majority of chromosomes (>90%) in the sample

• show no evidence of being derived from one another by recombination

Reprinted from: Daly et. al., Nature Genet. 29, 229 (2001)

Block-like Haplotype Diversity at Block-like Haplotype Diversity at 5q315q31

¤ The haplotype blocks are separated by intervals – in which several independent historical recombination

events seem to have occurred

¤ The historical recombination events are clustered– multiple exchanges between most blocks– little or no recombination within blocks. – The clustering of recombination events is suggestive of

local hotspots of recombination


Historical recombination events

Implications of Haplotype blocksImplications of Haplotype blocks

¤ Once the haplotype blocks are identified– they can be treated as alleles in genome-wide association

studies to find medically relevant variation• Holy grail of pharmacogenetics

– a subset of SNPs haplotype tag SNPs – htSNPs - can be used to uniquely distinguish the common haplotypes in each block

• A subset of all the SNPs is sufficient for whole-genome association anlysis


Blocks of Limited Haplotype Diversity Blocks of Limited Haplotype Diversity Revealed by High-Resolution Scanning of Revealed by High-Resolution Scanning of

Human Chromosome 21 Human Chromosome 21

¤ Landmark paper presenting– the haplotype structure of chromosome 21– Used high-density oligonucleotide arrays, in combination with

somatic cell genetics• To identify the common SNPs on human chromosome 21 • To directly observe the haplotype structure defined by these

SNPs• This structure reveals blocks of limited haplotype diversity in

which more than 80% of a global human sample can typically be characterized by only three common haplotypes

Patil et. al., Science, 294: 1719 (2001)


¤ Discovered chr 21 SNPs and determined the haplotype structure using– ultra high-density oligonucleotide arrays– in combination with somatic cell genetics

¤ SNPs discovery – Using a public panel of 24 ethnically diverse individuals

• African, Asian, and Caucasian

– Physically separated the two chr 21 copies from each individual

• using a rodent-human somatic cell hybrid technique

– Analyzed 20 independent copies of chromosome 21

¤ Since SNPs are characterized on haploid copies – they directly reveal haplotypes– The SNPs of chromosome 21 reveal numerous haplotype blocks

Reprinted from: Patil et. al., Science, 294: 1719 (2001)

Haplotype Block Defined by 14 Common Haplotype Block Defined by 14 Common SNPsSNPs

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15/20 individual chromosomesmajor allele

minor alleleHaplotype blocks 1 2 3 4 5 6


Haplotype Block: selection of tag SNPsHaplotype Block: selection of tag SNPs

haplotype patterns 1 2 3 4

SNPs for genotyping4 common haplotypes


Inventories of human genome sequence Inventories of human genome sequence variationvariation

¤ The first inventory of SNPs was made by – The public Human Genome Project (HGP)

• 971,077 candidate SNPs were identified as sequence differences in regions of sequence overlap between large-insert clones

– The SNP Consortium (TSC) – a public/private consortium• Discovered using a publicly available panel of 24 ethnically

diverse individuals• 1,023,950 candidate SNPs identified by shotgun sequencing of

genomic fragments and aligning to the genome sequence

¤ First inventory (2001) comprised 1,4 million SNPs– Average density of one SNP every 1.91 kb– SNPs primarily in regions surrounding genes

• estimate 60,000 exonic SNPs in the collection

The International SNP Map Working Group, Nature 409, 928 (2001)

Human genome sequence variationHuman genome sequence variation

¤ It is estimated that in the world's human population– about 10 million “common” SNPs

• With a minor allele frequency of 1% or more • one variant per 300 bases on average

– these 10 million common SNPs constitute 90% of the variation in the world population

– The remaining 10% of the variation is due • A large number of SNPs that are rare in the population• These may represent another 30 million SNPs

¤ Next frontier in the human genome– Complete inventory of the common SNPs– Complete map of the common SNPs: The HapMap project

The International SNP Map Working Group, Nature 409, 928 (2001)

The International HapMap ProjectThe International HapMap Project

¤ The goal of the International HapMap Project– determine the common patterns of DNA sequence variation

in the human genome and – make this information freely available in the public domain.

¤ The HapMap will – allow the discovery of sequence variants that affect

common disease– will facilitate development of diagnostic tools– will enhance our ability to choose targets for therapeutic

intervention

The International HapMap Consortium, Nature 426, 789 - 796 (2003)


¤ Determine haplotype patterns across the genome– 5 million common sequence variants

• genotyped in 270 DNA samples from populations of Africa, Asia and Europe

– Common SNPs are found in all populations • Project includes several populations from different geographic

locations– Yoruba, Japanese, Chinese individuals and individuals with

ancestry from Northern and Western Europe

¤ Genotyping strategy– Phase I

• initial round of genotyping of 1.00.000 SNPs in the 270 DNA samples– completed December 2004

– Phase II • genotyped 5 million SNPs at ~ 1-kilobase intervals in 270 individuals

– Completed November 2005


¤ The extent of association between nearby markers – varies dramatically across the genome – the patterns of association must be empirically determined

for efficient selection of tag SNPs.

¤ On the basis of empirical studies it is estimated that – most of the information about genetic variation represented

by the 10 million common SNPs in the population could be provided

• by genotyping 200,000 to 1,000,000 tag SNPs across the genome

– Thus, a substantial reduction in the amount of genotyping can be obtained with little loss of information, by

• using knowledge of the LD present in the genome.

PerspectivesPerspectives

¤ For the full potential of the HapMap to be realized – The genotyping technology must

• become more cost efficient, and the analysis methods must be improved

– Pilot studies with other populations must be completed • to confirm that the HapMap is generally applicable

¤ Genome-wide association projects must establish – carefully phenotyped sets of affected and unaffected individuals

for many common diseases in a way that • preserves confidentiality • retains detailed clinical and environmental exposure data

¤ Careful attention must also be paid to the ethical issues that– will be raised by the HapMap and the studies that will use it – challenge to avoid misinterpretations or misuses of results from

studies that use the HapMap

Whole-Genome Patterns of Common DNA Whole-Genome Patterns of Common DNA Variation in Three Human Populations Variation in Three Human Populations

¤ Paper presents– Whole-genome patterns of common human DNA variation

by genotyping 1,586,383 SNPs in 71 Americans of European, African, and Asian ancestry

– Different approach to represent the structure of genetic variation

• LD bins: clusters of tightly linked SNPs

Hinds et. al., Science. 307: 1072-1079 (2005)

Reprinted from: Hinds et. al., Science. 307: 1072-1079 (2005)

Extended LD bin and haplotype block structure Extended LD bin and haplotype block structure around the around the CFTRCFTR gene gene

ConclusionConclusion

¤ The 1,5 Million SNPs capture – most common human genetic variation as a result of

linkage disequilibrium• strong correlation among common SNP alleles that define

haplotypes

¤ Strong correlation between – extended regions of linkage disequilibrium – functional genomic elements

¤ First generation haplotype map provides a tool for – exploring the causal role of common human DNA variation

in complex human traits – investigating the nature of genetic variation within and

between human populations.

Reprinted from: Hinds et. al., Science. 307: 1072-1079 (2005)

A haplotype map of the human A haplotype map of the human genomegenome

¤ Paper presents– A map of >1 million SNPs for which accurate and complete

genotypes have been obtained in 269 DNA samples from four populations

– The data document the generality of • recombination hotspots• a block-like structure of linkage disequilibrium • low haplotype diversity• substantial correlations of SNPs with many of their neighbours



Number of SNPs in dbSNP over time Number of SNPs in dbSNP over time

¤ Public database dbSNP (http://www.ncbi.nlm.nih.gov/SNP/)

– October of 2005: 10,4 million RefSNP clusters– 4,8 million validated SNPs


Genealogical relationships among Genealogical relationships among haplotypeshaplotypes


Length of LD spans Length of LD spans


ConclusionsConclusions

¤ The phase I haplotype map documents the generality of – block-like structure of linkage disequilibrium – low haplotype diversity– recombination hotspots– substantial correlations of SNPs with many of their

neighbours

¤ Important application of the HapMap data is – make possible comprehensive, genome-wide association

studies– Identify the root causes of common diseases

genome biology and biotechnology

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