The Genom of Homo sapiens.pdf

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Genetics of Schizophrenia and Bipolar Affective Disorder:Strategies to Identify Candidate GenesD.J. PORTEOUS,* K.L. EVANS,* J.K. MILLAR ,* B.S. PICKARD,* P.A. THOMSON,* R. JAMES,*S. MACGREGOR, † N.R. WRAY,* P.M. VISSCHER, † W.J. MUIR, ‡ AND D.H. BLACKWOOD ‡*Medical Genetics Section, University of Edinburgh, Western General Hospital, Edinburgh, Scotland, EH4 2XU;† Institute of Cell, Animal and Population Biology, Ashworth Laboratories, School of Biology, The University ofEdinburgh, The King’s Buildings, Edinburgh, Scotland, EH9 3JT; ‡ Division of Psychiatry, University ofEdinburgh, Royal Edinburgh Hospital, Edinburgh, Scotland, EH10 5HFSchizophrenia (SCZ) and bipolar affective disorder(BPAD) (formerly termed manic-depressive illness) aresevere, disabling psychiatric illnesses that feature prominentlyin the top ten causes of disability worldwide (Lopezand Murray 1998). Each will affect about 1% of the populationin their lifetime. The cost of providing treatmentfor mental illness in the UK National Health Service is estimatedat 10% of total expenditure. The total costs (medical,social, economic) are estimated at £32 billion per annumfor the population of 50 million in England (Bird1999; see also www.mentalhealth.org.uk). World HealthOrganization predictions indicate that major depressionwill be second only to heart disease in terms of disabilityadjustedlife years (DALYs) by 2020 (Lopez and Murray1998). Research into the causes of these devastating disordersand the development of improved interventions is ahigh scientific, social, individual, and public health priority.Unfortunately, these remain Cinderella disorders comparedto cancer and heart disease, both in terms of governmentaland societal recognition and national andinternational research support. Despite their high prevalenceand, indeed, decades of neuroscience research, littleis known with certainty about their cellular and molecularbases. Consequently, treatments remain largely empiricaland palliative. This apparent impasse, however, justifiesneither complacency nor despondency, because the oneconsistent, replicable finding is that family, twin, andadoption studies demonstrate a major genetic componentin both SCZ and BPAD (Merikangas and Risch 2003). Adecade ago only a handful of genes for monogenic disordershad been positionally cloned through linkage studies.Over the past five years, as the Human Genome Projectand associated tools have developed, that number hassoared to over 1000. As the Human Genome Projectpasses from formal completion to full development as auniversal biological tool, we can expect acceleratedprogress in tackling the much more difficult task of geneticallydissecting the common complex disorders includingmajor mental illness.EVIDENCE FOR A GENETIC COMPONENTTO SCZ AND BPADThe risk to a first-degree relative of a person affectedby SCZ or BPAD is an order of magnitude higher thanthat of the general population (from ~1% to 10–15% lifetimerisk for each disorder) (Kendler and Diehl 1993;Merikangas and Risch 2003). Further evidence for thehigh heritability of SCZ and of BPAD comes from twinand adoption studies. Concordance rates for monozygotictwins are around 50% for SCZ and 60–80% for BPAD.Importantly, these concordance rates are much higherthan for dizygotic twins (10–15%), and the biological riskis unaffected by adoption. Several chromosomal regionsthat may harbor susceptibility genes for SCZ and forBPAD have been identified by a range of genetic strategies(Owen et al. 2000; Potash and DePaulo 2000; Rileyand McGuffin 2000). There is also growing evidence thatrelatives of sufferers are at higher risk of other psychiatricdiagnoses within the schizophrenia–affective disorderspectrum (Kendler et al. 1998; Wildenauer et al. 1999;Berrettini 2000; Valles et al. 2000). This suggests thatsome genetic risk factors may contribute to a range ofpsychotic symptoms that cross the traditional diagnosticboundaries of SCZ and affective disorders. In part, thismay reflect the fact that diagnosis of psychiatric illness isan imprecise science; psychiatric phenotypes are almostentirely based on profiles of behavioral indices and communicationpatterns. The use of standardized diagnosticcriteria (such as the Diagnostic and Statistical Manual ofMental Disorders, DSM-IV, published by the AmericanPsychiatric Association, and The ICD-10 Classificationof Mental Health and Behavioural Disorders, publishedby the World Health Organization) has ensured good reproducibilityof diagnoses between researchers, but thereis wide overlap of symptoms between the diagnostic categoriesof SCZ, BPAD, and recurrent, major (unipolar)depression. In the absence of reliable biological or geneticmarkers specific for SCZ or BPAD, the validity ofexisting classification remains uncertain. It would be amajor advance if genetic studies yielded molecular diagnosticmethods that could not only resolve some of thepresent uncertainties in psychiatric diagnosis, but also informtreatment choice and disease prognosis. Until suchtime, we can only speculate that variability in individualdiagnoses reflects a combination of genetic (and possiblyallelic) heterogeneity, polygenic inheritance, and variationin individual life trajectories/environmental exposures.Nevertheless, post-genome science most certainlyoffers the best hope for determining the biological basisCold Spring Harbor Symposia on Quantitative Biology, Volume LXVIII. © 2003 Cold Spring Harbor Laboratory Press 0-87969-709-1/04. 383
384 PORTEOUS ET AL.of these devastating conditions and for developing effective,evidence-based treatments.GENETICS OF COMPLEX DISEASE AND THEPARTICULAR CHALLENGES FORPSYCHIATRIC GENETICSThe most appropriate way forward in dissecting the geneticsof common disease is subject to much debate (Terwilligerand Weiss 1998; Evans et al. 2001a; Botstein andRisch 2003). The most pragmatic is to follow both mainschools of thought as they each have strengths pertainingto different underlying genetic models. The first focuseson variants, which may be rare in the population, butwhich have detectable, individual effects. For these, themethods that worked well for single-gene disorders, acombination of molecular cytogenetics, family linkagestudies, and candidate gene studies, can be transferred directly.It is, however, worth commenting on how problematicthe last of these options is for the psychiatric geneticist.Unlike the common genetic disorders of theother major organs, such as cancer or heart disease, cellularpathology in the brain of SCZ and BPAD patients ispoorly defined, and brain biopsies are rarely available.With perhaps a third of all known genes expressed in thebrain and a plethora of neurodevelopmental and neurophysiologicaltheoretical constructs to choose between,the number of possible candidates is perhaps greater thanfor any other class of organic disorder. Add to these considerableproblems the more general issue of incompletepenetrance, and the full magnitude of the task will be appreciated.The age at first diagnosis for SCZ is typicallyin late adolescence/young adulthood, slightly later forBPAD, indicating a biological (and genetically influenced)developmental window for expression or, possiblyand related to this, an age-dependent susceptibility tolife changes and exposures. The severity and individualresponse to illness are also highly variable. The history ofdrug medication will likewise be variable and may resultin pathological side effects. The field would benefitgreatly from a set of validated biomarkers.Linkage studies are dependent on the availability of informativefamilies, and application to complex traits canbe problematic, because it may be hard to define a geneticmodel that explains the observed inheritance pattern.Replication of linkage results is needed to provide credibilityto initial linkage reports, which are likely to overestimatethe size of effect, whereas subsequent studiesshould reflect the true size of effect (Lander and Kruglyak1995; Terwilliger and Weiss 1998; Botstein and Risch2003). Lander and Kruglyak (1995) provided a generallyaccepted yardstick by which to assess claims for genomewidelinkage. They recommended that a LOD of 3.3 betaken as primary evidence for significant linkage accountingfor multiple testing issues. Where that value wasmatched or exceeded, they argued that additional studieswith p values of 0.01 (or LOD = 1.2) can be taken as evidencefor replication (as testing is of a prior hypothesis).Failure to replicate does not necessarily imply an initialreport is a false positive; it may reflect lack of power inthe replication study, population heterogeneity, diagnosticdifferences, or statistical fluctuation (Lander andKruglyak, 1995). We explain below the extent to whichthese yardsticks have been matched.A second school of thought argues from a theoreticaland experimental perspective for a polygenic model toexplain the genetic variation in complex traits. By virtueof their frequency in the human population, the argumentgoes that the origins of common genetic disease in humansmost probably lie in common and ancient sequencevariants and in multiple variants of additive action. AsRisch and Merikangas (1996) pointed out, if the genotyperelative risk (GRR) is small (as predicted by the commonancient variant hypothesis), then unachievable numbersof simplex families (sib pairs or trios) would be requiredto reach genome-wide significance (see also Botstein andRisch 2003). On the other hand, association studies, theformal comparison of allele frequencies in cases andmatched controls, do have the power to detect even a verymodest GRR with realistic numbers of unrelated samples.The association mapping strategy is powerful and attractive,yet problematic. It relies on the scored variant, typicallya single-nucleotide polymorphism (SNP), of whichthere are some 3 million known examples to choose betweenin the public domain (http://www.ncbi.nlm.nih.gov/SNP; http://snp.cshl.org), being a functional (disease-causing)variant itself or, much more likely, in linkagedisequilibrium with a causative variant. It is becomingapparent that linkage disequilibrium is unevenly andunpredictably distributed across the genome (varying byover two orders of magnitude) and that although somestudies have shown that a limited number of commonhaplotypes occur across ethnically diverse populations(see, e.g., Gabriel et al. 2002), other studies have shownthat there are a limited number of haplotypes in any onepopulation, but that there is significant variation in haplotypesbetween populations (see, e.g., Kauppi et al.2003). This emphasizes the importance of case-matchingcontrol strategies that avoid the confounder of populationstratification (Clayton and McKeigue 2001). Of course, itis feasible to simply increase the number and density ofSNPs tested, but this raises both cost and the statisticalproblem of multiple testing. The problems inherent inmap-based association studies have prompted others topromote a sequence-based strategy that focuses on variationwithin coding elements as an empirical way to reducecost, a rational way to reduce the problem of multipletesting, and a logical way to maximize the probability thatcausal SNPs will be discovered and typed (Botstein andRisch 2003). We and others would extend the logic to includeregulatory elements, identified empirically or highlightedby virtue of comparative genome analysis. Thereis thus no doubt about the importance of association studiesas part of the end game in positional cloning in complextrait genetics, but the value of extended family-basedstudies should not be underestimated.As already alluded to, there are several alternative family-basedlinkage approaches, which typically test segregationin multiplex families (multiple affecteds in threeormore generation families), affected sib pairs or trios(one affected and both parents). To identify susceptibilityloci for highly heritable, genetically complex diseases
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ForewordIn 2001, as we considered t
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The Finished Genome Sequence of Hom
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4 ROGERSFigure 2. Accumulation of h
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6 ROGERSFigure 4. Sequencing center
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8 ROGERSabcFigure 5. Ensembl view o
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10 ROGERS2000. Analysis of vertebra
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The Human Genome: Genes, Pseudogene
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VARIATION ON CHROMOSOME 7 15rived f
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VARIATION ON CHROMOSOME 7 17DNAs an
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VARIATION ON CHROMOSOME 7 19expecte
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VARIATION ON CHROMOSOME 7 21Drosoph
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Mutational Profiling in the Human G
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HUMAN MUTATIONAL PROFILING 25Anothe
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HUMAN MUTATIONAL PROFILING 27Figure
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HUMAN MUTATIONAL PROFILING 29Rieder
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32 SCHMUTZ ET AL.algorithm itself,
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34 SCHMUTZ ET AL.Figure 2. Genomic
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36 SCHMUTZ ET AL.compared. Some of
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Human Subtelomeric DNAH. RIETHMAN,
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HUMAN SUBTELOMERIC SEQUENCES 41The
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HUMAN SUBTELOMERIC SEQUENCES 43cate
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HUMAN SUBTELOMERIC SEQUENCES 45Figu
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HUMAN SUBTELOMERIC SEQUENCES 47pres
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50 COLLINSand expand the genomics r
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52 COLLINSFigure 2. A public-sector
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54 COLLINSdefine all the parts of t
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56 BENTLEYmon over many generations
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58 BENTLEYTable 1. Genetic Disease
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60 BENTLEY(Clark et al. 1998; Reich
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62 BENTLEYACKNOWLEDGMENTSThe author
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SNP Genotyping and Molecular Haplot
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GENETIC ANALYSIS OF DNA POOLS 67gen
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70 FAN ET AL.matrix is then mated t
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72 FAN ET AL.Figure 3. Views of gen
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74 FAN ET AL.including 32 duplicate
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76 FAN ET AL.Figure 7. Allele-speci
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78 FAN ET AL.microsphere-based assa
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80 BERTRANPETIT ET AL.function, may
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82 BERTRANPETIT ET AL.diversity in
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84 BERTRANPETIT ET AL.gree of block
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86 BERTRANPETIT ET AL.Figure 1. Dec
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88 BERTRANPETIT ET AL.1999. Populat
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90 WINDEMUTH ET AL.Expression data.
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92 WINDEMUTH ET AL.Table 1. A Summa
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94 WINDEMUTH ET AL.Table 2. Signifi
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96 WINDEMUTH ET AL.Table 3. Summary
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98 WINDEMUTH ET AL.Table 6. List of
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100 WINDEMUTH ET AL.Table 6. (Conti
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102 WINDEMUTH ET AL.Table 6. (Conti
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104 WINDEMUTH ET AL.much of a surpr
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106 WINDEMUTH ET AL.Given our resul
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Genetic Variation and the Control o
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GENETIC CONTROL OF TRANSCRIPTION 11
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GENETIC CONTROL OF TRANSCRIPTION 11
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Genome-wide Detection and Analysis
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RECENT SEGMENTAL DUPLICATIONS 117Fi
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RECENT SEGMENTAL DUPLICATIONS 119St
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RECENT SEGMENTAL DUPLICATIONS 121Co
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RECENT SEGMENTAL DUPLICATIONS 123Ho
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The Effects of Evolutionary Distanc
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EVOLUTIONARY DISTANCE AND GENE PRED
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EVOLUTIONARY DISTANCE AND GENE PRED
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Lineage-specific Expansion of KRAB
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EVOLUTION OF ZNF GENES 133Figure 2.
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EVOLUTION OF ZNF GENES 135Figure 4.
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EVOLUTION OF ZNF GENES 137get gene,
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EVOLUTION OF ZNF GENES 139Y., Goodw
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Sequence Organization and Functiona
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CENTROMERE ANNOTATION 143THE CENTRO
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CENTROMERE ANNOTATION 145Figure 4.
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CENTROMERE ANNOTATION 147CONCLUSION
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CENTROMERE ANNOTATION 149Schueler M
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152 PARKHILL AND THOMSONFigure 1. T
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154 PARKHILL AND THOMSONshow very h
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156 PARKHILL AND THOMSONGene Loss a
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158 PARKHILL AND THOMSONYersinia ad
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160 MCKAY ET AL.Choosing Candidate
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162 MCKAY ET AL.new comparative too
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164 MCKAY ET AL.rich. Based on a th
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166 MCKAY ET AL.Embryonic Muscle an
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168 MCKAY ET AL.native polyadenylat
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Building Comparative Maps Using 1.5
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HUMAN CHROMOSOME 1p IN THE DOG 1731
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HUMAN CHROMOSOME 1p IN THE DOG 175(
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HUMAN CHROMOSOME 1p IN THE DOG 177l
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180 GEORGES AND ANDERSSON5. There i
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182 GEORGES AND ANDERSSONplied to r
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184 GEORGES AND ANDERSSONbe common
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186 GEORGES AND ANDERSSONin humans
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Evolving Methods for the Assembly o
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ASSEMBLING LARGE GENOMES 191Figure
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ASSEMBLING LARGE GENOMES 193tant ad
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Mouse Genome Encyclopedia ProjectY.
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MOUSE GENOME ENCYCLOPEDIA PROJECT 1
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DNA Sequence Assembly and Multiple
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EULERIAN ASSEMBLY AND MULTIPLE ALIG
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Ensembl: A Genome InfrastructureE.
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ENSEMBL 215projects often submit th
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218 ZHANGthe majority of these are
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220 ZHANGFigure 2. Demonstration of
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222 ZHANG(G.X. Chen et al., in prep
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224 ZHANGWe are waiting for experim
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Ontologies for Biologists: A Commun
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ONTOLOGIES FOR BIOLOGISTS 229al. 20
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ONTOLOGIES FOR BIOLOGISTS 231TOPIC
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ONTOLOGIES FOR BIOLOGISTS 233a.b.Fi
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ONTOLOGIES FOR BIOLOGISTS 2352003.
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238 JOSHI-TOPE ET AL.Figure 1. The
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240 JOSHI-TOPE ET AL.state of knowl
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242 JOSHI-TOPE ET AL.and co-immunop
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The Share of Human Genomic DNA unde
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DNA UNDER SELECTION FROM HUMAN-MOUS
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Detecting Highly Conserved Regions
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DETECTING MULTISPECIES CONSERVED SE
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266 ROE ET AL.noncoding regions. On
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268 ROE ET AL.a48 hpf embryos in Mi
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270 ROE ET AL.aNovel gene KIAA0819[
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272 ROE ET AL.aMouseRatAP00354.2 Hu
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274 ROE ET AL.Tautz D. and Pfeifle
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276 JAILLON ET AL.Detection of Evol
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278 JAILLON ET AL.Table 1. Distribu
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280 JAILLON ET AL.Table 3. Distribu
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282 JAILLON ET AL.ecotig is a resul
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284 OVCHARENKO AND LOOTSdivergent r
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286 OVCHARENKO AND LOOTSmodulation
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288 OVCHARENKO AND LOOTSsequencing
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290 OVCHARENKO AND LOOTSments of cl
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Evolution of Eukaryotic Gene Repert
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EVOLUTION OF EUKARYOTIC GENES AND I
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304 PENNACCHIO, BAROUKH, AND RUBINA
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306 PENNACCHIO, BAROUKH, AND RUBINh
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308 PENNACCHIO, BAROUKH, AND RUBINA
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High-Throughput Mouse Knockouts Pro
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314 FRIDDLE ET AL.screen to lines o
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Identification of Novel Functional
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100 bp ladder68G1168G1168H1168H6100
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FUNCTIONAL ELEMENTS IN HUMAN DNA 32
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High-resolution Human Genome Scanni
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HUMAN GENOME SCANNING 325false-posi
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HUMAN GENOME SCANNING 327affecting
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HUMAN GENOME SCANNING 329methods fo
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Page 351 and 352: 344 HARDISON ET AL.cific chromosoma
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432 JORGENSEN ET AL.tive small mole
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434 JORGENSEN ET AL.FLAG-tagged pro
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436 JORGENSEN ET AL.visualization t
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438 JORGENSEN ET AL.AArp2/3 Complex
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Pathway40S440 JORGENSEN ET AL.ANutr
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442 JORGENSEN ET AL.Giaever G., Chu
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Genomic Disorders: Genome Architect
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GENOME ARCHITECTURE AND GENOMIC DIS
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Human Versus Chimpanzee Chromosome-
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HUMAN VS. CHIMP CHROMOSOME COMPARIS
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HUMAN VS. CHIMP CHROMOSOME COMPARIS
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Novel Transcriptional Units and Unc
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TRANSCRIPTIONAL UNITS AND GENE PAIR
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mtDNA Variation, Climatic Adaptatio
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mtDNA VARIATION 473Figure 3. Region
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ANALYSIS OF ADAPTIVE SELECTION FORR
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mtDNA VARIATION 477Figure 8. Temper
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Positive Selection in the Human Gen
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HUMAN-SPECIFIC EVOLUTIONARY CHANGES
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488 UNDERHILLorigin episodes, each
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490 UNDERHILLhaplogroups C through
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492 UNDERHILLO (Fig. 2e) that share
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The New Quantitative BiologyM.V. OL
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NEW QUANTITATIVE BIOLOGY 497alone.
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NEW QUANTITATIVE BIOLOGY 499There w
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NEW QUANTITATIVE BIOLOGY 501ceded,
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