The Genom of Homo sapiens.pdf

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THE GENOME KNOWLEDGEBASE 243Karp P.D., Riley M., Saier M., Paulsen I.T., Collado-Vides J., PaleyS.M., Pellegrini-Toole A., Bonavides C., and Gama-CastroS. 2002. The EcoCyc database. Nucleic Acids Res. 30: 56.Lander E.S., Linton L.M., Birren B., Nusbaum C., Zody M.C.,Baldwin J., Devon K., Dewar K., Doyle M., FitzHugh W.,Funke R., Gage D., Harris K., Heaford A., Howland J., KannL., Lehoczky J., LeVine R., McEwan P., McKernan K.,Meldrim J., Mesirov J.P., Miranda C., Morris W., and NaylorJ., et al. (International Human Genome Sequencing Consortium).2001. Initial sequencing and analysis of the humangenome. Nature 409: 860.Li J., Ning Y., Hedley W., Saunders B., Chen Y., Tindill N.,Hannay T., and Subramanian S. 2002. The Molecule Pagesdatabase. Nature 420: 716.Noy N.F., Sintek M., Decker S., Crubezy M., Fergerson R.W.,and Musen M.A. 2001. Creating semantic web contents withProtégé-2000. IEEE Intelligent Systems 16: 60.Pruitt K.D. and Maglott D.R. 2001. RefSeq and LocusLink:NCBI gene-centered resources. Nucleic Acid Res. 29: 137.Pruitt K.D., Katz K.S., Sicotte H., and Maglott D.R. 2000. IntroducingRefSeq and LocusLink: Curated human genome resourcesat the NCBI. Trends Genet. 16: 44.Safran M., Solomon I., Shmueli O., Lapidot M., Shen-Orr S.,Adato A., Ben-Dor U., Esterman N., Rosen N., Peter I., OlenderT., Chalifa-Caspi V., and Lancet D. 2002. GeneCards2002: Towards a complete, object-oriented, human gene compendium.Bioinformatics 18: 1542.Zanzoni A., Montecchi-Palazzi L., Quondam M., Ausiello G.,Helmer-Citterich M., Cesareni G. 2002. MINT: A MolecularINTeraction database. FEBS Lett. 513: 135.
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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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Page 202 and 203: Mouse Genome Encyclopedia ProjectY.
Page 204 and 205: MOUSE GENOME ENCYCLOPEDIA PROJECT 1
Page 212 and 213: DNA Sequence Assembly and Multiple
Page 214 and 215: EULERIAN ASSEMBLY AND MULTIPLE ALIG
Page 220 and 221: Ensembl: A Genome InfrastructureE.
Page 222: ENSEMBL 215projects often submit th
Page 225 and 226: 218 ZHANGthe majority of these are
Page 227 and 228: 220 ZHANGFigure 2. Demonstration of
Page 229 and 230: 222 ZHANG(G.X. Chen et al., in prep
Page 231 and 232: 224 ZHANGWe are waiting for experim
Page 234 and 235: Ontologies for Biologists: A Commun
Page 236 and 237: ONTOLOGIES FOR BIOLOGISTS 229al. 20
Page 238 and 239: ONTOLOGIES FOR BIOLOGISTS 231TOPIC
Page 240 and 241: ONTOLOGIES FOR BIOLOGISTS 233a.b.Fi
Page 242: ONTOLOGIES FOR BIOLOGISTS 2352003.
Page 245 and 246: 238 JOSHI-TOPE ET AL.Figure 1. The
Page 247 and 248: 240 JOSHI-TOPE ET AL.state of knowl
Page 249: 242 JOSHI-TOPE ET AL.and co-immunop
Page 253 and 254: 246 CHIAROMONTE ET AL.We make no pa
Page 255 and 256: 248 CHIAROMONTE ET AL.Figure 1. Smo
Page 257 and 258: 250 CHIAROMONTE ET AL.can use this
Page 259 and 260: 252 CHIAROMONTE ET AL.However, we c
Page 261 and 262: 254 CHIAROMONTE ET AL.Ihaka R. and
Page 263 and 264: 256 MARGULIES ET AL.HumanMouseFuguR
Page 265 and 266: 258 MARGULIES ET AL.Base Position 1
Page 267 and 268: 260 MARGULIES ET AL.Figure 4. Gener
Page 269 and 270: 262 MARGULIES ET AL.CONCLUSIONSWith
Page 272 and 273: Comparative Analysis of Human Chrom
Page 274 and 275: COMPARATIVE GENOMIC ANALYSIS 267aBa
Page 276 and 277: COMPARATIVE GENOMIC ANALYSIS 269µg
Page 278 and 279: COMPARATIVE GENOMIC ANALYSIS 271aHu
Page 280 and 281: COMPARATIVE GENOMIC ANALYSIS 273___
Page 282 and 283: Genome-wide Analyses Based on Compa
Page 284 and 285: WHOLE-GENOME COMPARISONS 277Figure
Page 286 and 287: WHOLE-GENOME COMPARISONS 279Table 2
Page 288 and 289: WHOLE-GENOME COMPARISONS 281models
Page 290 and 291: Comparative Genomic Tools for Explo
Page 292 and 293: COMPUTATIONAL TOOLS FOR ANALYZING G
Page 298: COMPUTATIONAL TOOLS FOR ANALYZING G
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294 ROGOZIN ET AL.BeTs are combined
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296 ROGOZIN ET AL.Dm Hs Ce Sc Sp Ec
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298 ROGOZIN ET AL.Dm Ag Hs Ce Sc Sp
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300 ROGOZIN ET AL.gene lossgene gai
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Human-Mouse Comparative Genomics: S
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HUMAN-MOUSE COMPARATIVE GENOMICS 30
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MOUSE KNOCKOUTS ILLUSTRATE FUNCTION
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MOUSE KNOCKOUTS ILLUSTRATE FUNCTION
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318 LIAN ET AL.0 12 34 5 6 78 9 101
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320 LIAN ET AL.90 minutes and the c
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322 LIAN ET AL.Iyer V.I., Horak C.A
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324 LI ET AL.Figure 1. Array-based
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326 LI ET AL.Figure 4. Test of quan
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328 LI ET AL.Figure 5. Comparison o
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Annotation of Novel Proteins Utiliz
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FUNCTIONAL SHOTGUN SEQUENCING 333Fi
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Global Predictions and Tests of Ery
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PREDICTING GENE REGULATORY REGIONS
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Systems Approaches Applied to the S
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SYSTEMS BIOLOGY IN S. CEREVISIAE AN
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360 MERIKANGASidentification of gen
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362 MERIKANGASDay 1984; Ottman 1990
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364 MERIKANGASPrevention Research G
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366 DRAYNA ET AL.Figure 1. Distribu
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368 DRAYNA ET AL.Table 1. Summary o
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370 DRAYNA ET AL.Figure 5. Predicte
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Genomic Variation in Multigenic Tra
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GENOMIC VARIATION IN MULTIGENIC TRA
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384 PORTEOUS ET AL.of these devasta
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386 PORTEOUS ET AL.Figure 2. The t(
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388 PORTEOUS ET AL.Figure 3. DISC1
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390 PORTEOUS ET AL.cgi-bin/hgGatewa
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392 PORTEOUS ET AL.REFERENCESAshers
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394 PORTEOUS ET AL.Valles V., Van O
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396 GOLDSTEIN, CAVALLERI, AND AHMAD
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Genetics of Quantitative Variation
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HUMAN GENE EXPRESSION VARIATION 405
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HUMAN GENE EXPRESSION VARIATION 407
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410 CHIBA-FALEK AND NUSSBAUMconcent
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412 CHIBA-FALEK AND NUSSBAUMTable 4
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414 CHIBA-FALEK AND NUSSBAUMclein i
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Genomic Perspective and CancerD. BO
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GENOMIC PERSPECTIVE AND CANCER 419F
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GENOMIC PERSPECTIVE AND CANCER 421F
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GENOMIC PERSPECTIVE AND CANCER 423f
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Chromosome 21 and Down Syndrome: Th
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DOWN SYNDROME AND HUMAN CHROMOSOME
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DOWN SYNDROME AND HUMAN CHROMOSOME
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Harvesting the Genome’s Bounty: I
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INTEGRATIVE GENOMICS 433with high-d
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INTEGRATIVE GENOMICS 435497 baits3,
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INTEGRATIVE GENOMICS 437In contrast
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INTEGRATIVE GENOMICS 439Fly19,912Ye
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INTEGRATIVE GENOMICS 441IMPLICATION
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INTEGRATIVE GENOMICS 443gene intera
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446 STANKIEWICZ ET AL.Table 1. Sele
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448 STANKIEWICZ ET AL.al. 2002; Wal
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450 STANKIEWICZ ET AL.ate DNA rearr
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452 STANKIEWICZ ET AL.Figure 5. Sch
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454 STANKIEWICZ ET AL.Legius E. 200
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456 SAKAKI ET AL.determined. We pai
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458 SAKAKI ET AL.Table 2. Base Subs
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460 SAKAKI ET AL.D.R. 2003. Genomic
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462 LIPOVICH AND KINGtions that cre
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464 LIPOVICH AND KINGto-tail antise
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466 LIPOVICH AND KINGFigure 2. Perl
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468 LIPOVICH AND KINGtions. In inte
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470 LIPOVICH AND KINGOlson M.V. and
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472 WALLACE, RUIZ-PESINI, AND MISHM
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480 CLARK ET AL.Table 1. Derivation
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482 CLARK ET AL.Table 3. Biological
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484 CLARK ET AL.be under adaptive e
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Inferring Human History: Clues from
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Y-CHROMOSOME HAPLOTYPES AND GEOGRAP
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496 OLSONTable 1. Talks Grouped by
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498 OLSONbacterial lineages prosper
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500 OLSONwill respond to perturbati
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502 OLSONIn short, much remained to
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