The Genom of Homo sapiens.pdf

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QUALITY ASSESSMENT OF FINISHED SEQUENCE 37quence of the malaria mosquito Anopheles gambiae. Science298: 129.Huson D.H., Reinert K., Kravitz S.A., Remington K.A., DelcherA.L., Dew I.M., Flanigan M., Halpern A.L., Lai Z., MobarryC.M., Sutton G.G., and Myers E.W. 2001. Design of a compartmentalizedshotgun assembler for the human genome.Bioinformatics (suppl. 1) 17: S132.Jaffe D.B., Butler J., Gnerre S., Mauceli E., Lindblad-Toh K.,Mesirov J.P., Zody M.C., and Lander E.S. 2003. Wholegenomesequence assembly for mammalian genomes:Arachne 2. Genome Res. 13: 91.Kirkness E.F., Bafna V., Halpern A.L., Levy S., Remington K.,Rusch D.B., Delcher A.L., Pop M., Wang W., Fraser C.M.,and Venter J.C. 2003. The dog genome: Survey sequencingand comparative analysis. Science 301: 1898.Mardis E., McPherson J., Martienssen R., Wilson R.K., and Mc-Combie W.R. 2002. What is finished, and why does it matter.Genome Res. 12: 669.Mullikin J.C. and Ning Z. 2003. The phusion assembler.Genome Res. 13: 81.Myers E.W., Sutton G.G., Smith H.O., Adams M.D., and VenterJ.C. 2002. On the sequencing and assembly of the humangenome. Proc. Natl. Acad. Sci. 99: 4145.Olson M.V. 2002. The human genome project: A player’s perspective.J. Mol. Biol. 319: 931.Richterich P. 1998. Estimation of errors in “raw” DNA sequences:A validation study. Genome Res. 8: 251.Waterston R.H., Lander E.S., and Sulston J.E. 2002a. On the sequencingof the human genome. Proc. Natl. Acad. Sci. 99:3712._______ . 2003. More on the sequencing of the human genome.Proc. Natl. Acad. Sci. 100: 3022.Waterston R.H., Lindblad-Toh K., Birney E., Rogers J., AbrilJ.F., Agarwal P., Agarwala R., Ainscough R., AlexanderssonM., An P., Antonarakis S.E., Attwood J., Baertsch R., BaileyJ., Barlow K., Beck S., Berry E., Birren B., Bloom T., BorkP., Botcherby M., Bray N., Brent M.R., Brown D.G., andBrown S.D., et al. (Mouse Genome Sequencing Consortium).2002b. Initial sequencing and comparative analysis of themouse genome. Nature 420: 520.
Page 6 and 7: ForewordIn 2001, as we considered t
Page 8: The Finished Genome Sequence of Hom
Page 11 and 12: 4 ROGERSFigure 2. Accumulation of h
Page 13 and 14: 6 ROGERSFigure 4. Sequencing center
Page 15 and 16: 8 ROGERSabcFigure 5. Ensembl view o
Page 17 and 18: 10 ROGERS2000. Analysis of vertebra
Page 20 and 21: The Human Genome: Genes, Pseudogene
Page 22 and 23: VARIATION ON CHROMOSOME 7 15rived f
Page 24 and 25: VARIATION ON CHROMOSOME 7 17DNAs an
Page 26 and 27: VARIATION ON CHROMOSOME 7 19expecte
Page 28 and 29: VARIATION ON CHROMOSOME 7 21Drosoph
Page 30 and 31: Mutational Profiling in the Human G
Page 32 and 33: HUMAN MUTATIONAL PROFILING 25Anothe
Page 34 and 35: HUMAN MUTATIONAL PROFILING 27Figure
Page 36: HUMAN MUTATIONAL PROFILING 29Rieder
Page 39 and 40: 32 SCHMUTZ ET AL.algorithm itself,
Page 41 and 42: 34 SCHMUTZ ET AL.Figure 2. Genomic
Page 43: 36 SCHMUTZ ET AL.compared. Some of
Page 47 and 48: 40 RIETHMAN ET AL.Figure 1. Example
Page 49 and 50: 42 RIETHMAN ET AL.Figure 2. Models
Page 51 and 52: 44 RIETHMAN ET AL.gions were unavai
Page 53 and 54: 46 RIETHMAN ET AL.leles are those w
Page 56 and 57: Genome Research: The Next Generatio
Page 58 and 59: GENOME RESEARCH: THE NEXT GENERATIO
Page 60 and 61: GENOME RESEARCH: THE NEXT GENERATIO
Page 62 and 63: DNA Sequence Variation of Homo sapi
Page 64 and 65: HUMAN SEQUENCE VARIATION 57(Rioux e
Page 66 and 67: HUMAN SEQUENCE VARIATION 59Figure 2
Page 68 and 69: HUMAN SEQUENCE VARIATION 61Figure 4
Page 70: HUMAN SEQUENCE VARIATION 63Li W.H.
Page 73 and 74: 66 KWOK AND XIAOvader assay (Lyamic
Page 76 and 77: Highly Parallel SNP GenotypingJ.-B.
Page 78 and 79: SNP GENOTYPING 71tem, consisting of
Page 80 and 81: SNP GENOTYPING 73ASSAY CONVERSION R
Page 82 and 83: SNP GENOTYPING 75double-labeled con
Page 84 and 85: SNP GENOTYPING 77date the genetic b
Page 86 and 87: Structure of Linkage Disequilibrium
Page 88 and 89: STRATIFICATION OF LINKAGE DISEQUILI
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STRATIFICATION OF LINKAGE DISEQUILI
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Genome-wide Association of Haplotyp
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HAPLOTYPE EXPRESSION ASSOCIATIONS 9
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110 COTSAPAS ET AL.that this might
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112 COTSAPAS ET AL.Figure 5. The de
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114 COTSAPAS ET AL.peat variation a
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116 BAILEY AND EICHLERthe extremes,
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118 BAILEY AND EICHLERFigure 2. Ove
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120 BAILEY AND EICHLERand other inv
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122 BAILEY AND EICHLERknown, but it
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124 BAILEY AND EICHLERRuault M., Tr
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126 WANG, BUHLER, AND BRENTTWINSCAN
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128 WANG, BUHLER, AND BRENTMETHODSS
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130 WANG, BUHLER, AND BRENTThomas J
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132 HAMILTON ET AL.family affected
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134 HAMILTON ET AL.Figure 3. Three-
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136 HAMILTON ET AL.Figure 6. Diagra
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138 HAMILTON ET AL.upon vision (Gil
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140 HAMILTON ET AL.Wilson M.J. 2001
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142 RUDD, SCHUELER, AND WILLARDDNA
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144 RUDD, SCHUELER, AND WILLARDFigu
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146 RUDD, SCHUELER, AND WILLARDdeta
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148 RUDD, SCHUELER, AND WILLARDray
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Evolutionary Strategies of Human Pa
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EVOLUTION OF HUMAN PATHOGENS 153Fig
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EVOLUTION OF HUMAN PATHOGENS 155rol
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EVOLUTION OF HUMAN PATHOGENS 157in
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Gene Expression Profiling of Cells,
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GENE EXPRESSION PROFILING IN C. ELE
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172 GUYON ET AL.Table 1. Map Statis
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174 GUYON ET AL.only in one of the
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176 GUYON ET AL.million reads (mean
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Positional Identification of Struct
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IDENTIFYING LIVESTOCK QTN 181initia
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IDENTIFYING LIVESTOCK QTN 183tation
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IDENTIFYING LIVESTOCK QTN 185The fa
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IDENTIFYING LIVESTOCK QTN 187Farnir
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190 GIBBS AND WEINSTOCKBACATLASWGSF
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192 GIBBS AND WEINSTOCKsentation of
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194 GIBBS AND WEINSTOCKCONCLUSIONSE
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196 HAYASHIZAKIFigure 1. Strategy f
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198 HAYASHIZAKIpasses per day. Ther
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200 HAYASHIZAKIto known genes. As s
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202 HAYASHIZAKIaged small amounts o
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204 HAYASHIZAKIanalysis of more tha
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206 ZHANG AND WATERMAN(a)Repeat Rep
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208 ZHANG AND WATERMAN501234301245(
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210 ZHANG AND WATERMANing and Green
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212 ZHANG AND WATERMANACKNOWLEDGMEN
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214 BIRNEY ET AL.Table 1. General I
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Prediction, Annotation, and Analysi
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ANALYSIS OF HUMAN PROMOTERS 219Inte
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ANALYSIS OF HUMAN PROMOTERS 221Figu
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ANALYSIS OF HUMAN PROMOTERS 223nacc
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ANALYSIS OF HUMAN PROMOTERS 225E2F
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228 ASHBURNER ET AL.cally meaningfu
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230 ASHBURNER ET AL.man protein ann
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232 ASHBURNER ET AL.associations be
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234 ASHBURNER ET AL.cabulary for th
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The Genome Knowledgebase: A Resourc
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THE GENOME KNOWLEDGEBASE 239Figure
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THE GENOME KNOWLEDGEBASE 241by the
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THE GENOME KNOWLEDGEBASE 243Karp P.
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246 CHIAROMONTE ET AL.We make no pa
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248 CHIAROMONTE ET AL.Figure 1. Smo
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250 CHIAROMONTE ET AL.can use this
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252 CHIAROMONTE ET AL.However, we c
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254 CHIAROMONTE ET AL.Ihaka R. and
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256 MARGULIES ET AL.HumanMouseFuguR
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258 MARGULIES ET AL.Base Position 1
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260 MARGULIES ET AL.Figure 4. Gener
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262 MARGULIES ET AL.CONCLUSIONSWith
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Comparative Analysis of Human Chrom
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COMPARATIVE GENOMIC ANALYSIS 267aBa
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COMPARATIVE GENOMIC ANALYSIS 269µg
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COMPARATIVE GENOMIC ANALYSIS 271aHu
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COMPARATIVE GENOMIC ANALYSIS 273___
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Genome-wide Analyses Based on Compa
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WHOLE-GENOME COMPARISONS 277Figure
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WHOLE-GENOME COMPARISONS 279Table 2
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WHOLE-GENOME COMPARISONS 281models
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Comparative Genomic Tools for Explo
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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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