The Genom of Homo sapiens.pdf

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HAPLOTYPE EXPRESSION ASSOCIATIONS 91nificance of the result in the face of multiple testing ofmany markers. For this purpose, the omnibus statistic isrecalculated for up to 6,250 randomly permuted data setsrepresenting the null hypothesis of no true association.The permutation was done in such a way that the expressionvalues were randomly redistributed among the subjects,whereas the genetic assignments were left alone.The fraction of these instances of the null hypothesis thatresult in a more extreme omnibus statistic is a direct measurefor the probability of the observed statistic havingarisen by chance, and is called the p value. More specifically,if N random permutations are performed, and M ofthe permutations yield an omnibus statistic more extremethan that of the original data, the probability of the nullhypothesis is p = M/N. This procedure is nonparametric,meaning it makes no assumptions about the distributionof the expression values. In addition, because of the useof the omnibus statistic, the testing of multiple markers isfully accounted for. In fact, most other methods used toadjust for multiple comparisons would result in a largeloss of sensitivity, since there is no way to accurately accountfor the high degree of correlation between themarkers, many of which differ only slightly from eachother. For efficiency, the permutation testing was done onsuccessively larger sets of permutations N = (50, 250,1250, 6250), and the next higher set of permutations wasskipped when the number of false positives M was 10 ormore in the previous set.After the full association analysis was run, we furtherfiltered the results based on the quality of the expressiondata. Each expression level for each sample is associatedwith both a quantitative expression value and binary present/absentlabel. This label is calculated by a statisticalalgorithm in the MAS 5.0 software, and a present labelmeans that there is a probability of less than 5% that thereis no signal and what is measured is only noise. For mostanalyses, we excluded fragments for which there werefewer than 10 present calls out of 89 total. Additionally,for some analyses, we excluded fragments for which themaximum fold change was less than two. This is calculatedby taking the maximum and minimum expressionvalues for the expression level in the subset of samplewith “present” calls and taking the ratio. In addition, weexcluded in the analysis the genes that showed more thantwofold of mRNA expression levels within the three samplesfrom the same individual.RESULTSAssociation analysis was carried out examining 6,184gene loci by 22,242 expression levels. At a significancelevel of p ≤ 0.001, we found 66,141 significant associationsbetween gene loci and expression levels. Becausethis is such a large and rich data set, we have concentratedour analysis on two interesting subsets of associations.The first of these analyses concentrates on a set of cis-actingSNPs; i.e., SNPs that affect the expression levels ofthe genes they reside in. The second example examines agene coding for a largely uncharacterized zinc finger protein(ZNF295), which likely forms part of a transcriptionfactor complex. Two amino acid-changing SNPs in thislocus are strongly associated with expression levels in alarge number of other genes. Finally, we examine theglobal statistics of the data set and attempt to compare ourresults to some reported previously.cis-Acting Genetic VariationsNot all of the gene loci for which we have haplotypedata are represented by expression probes, and, viceversa, not all of the genes represented by expressionprobes have known haplotypes associated with them. Inour experiment, there were 4,762 gene loci and 7,553 expressionprobes where each of the loci belonged to thesame gene as one or more of the probes. We identified 22genes from our initial screen that have candidate cis-associationssignificant at a level of p
92 WINDEMUTH ET AL.Table 1. A Summary of the cis-AssociationsSig. Adj. Sig. Sig. Sig. Best Count Count Mean MeanGene Best marker (Orig.) (Orig.) (Rep.) (Rep.) marker(+) marker(–) marker(+) marker(–)AIM1 (Rec 5) -28G, 38695G, 53185T, 53784C, 54768C 75 26 43* 54* 16 73 529.5 365.3ARTS-1 (Rec 3) -4495C, 380C, 9947T 58 25 x 29* 29 60 53.8 106.6ATP5O (Rec 2) -491G, 6675C 44 27 4 13* 23 66 1788.9 1552.6CHKL (Dom 2) 1142C, 3734C 48 23 15* 31* 13 76 161.8 120.0DDX17 (Dom 1) 11625G 112 45 66* 66* 6 83 177.2 32.0DDX3 (Dom 2) 9964A, 10171T 44 33 20* 34* 52 37 812.2 616.6DNM1L (Dom 1) -272A 40 29 22* 32* 19 70 171.7 140.7ENTPD1 (Dom 2) -860G, -409T 44 26 x 15* 66 23 585.6 694.7FLJ11342 (Rec 3) -470T, -216A, 12232T 37 25 NA NA 53 36 226.4 201.3HBS1L (Rec 1) 86620T 57 33 x 30* 53 36 255.0 210.2HMG14 (Rec 3) 3366G, 5677T, 6047G 144 45 x 44* 33 56 818.4 1494.5HSPC023 (Dom 1) 18T 42 28 NA NA 46 43 549.4 616.8LOC51082 (Rec 2) -110C, 1316C 65 45 NA NA 35 54 513.8 425.4LOC51103 (Dom 1) -5154A 49 32 10 19* 51 38 139.2 160.3MUT (Dom 1) -407T 40 38 15* 19* 50 39 43.6 35.1PEX6 (Rec 2) 15386G, 16710G 63 42 x 64* 16 73 45.7 63.0PLEK (Dom 2) 18267T, 31404G 59 30 35* 40* 66 23 448.7 296.3PPP1R11 (Rec 2) 1084A, 1148G 46 31 3 18* 73 16 371.3 313.1RNAHP (Dom 2) 5159T, 23042G 58 32 6 14* 38 51 252.9 205.7RNPS1 (Dom 2) -3132A, 9107T 103 45 x 14* 72 17 284.5 148.1UROD (Rec 1) 1562G 40 33 12 12 78 11 114.1 150.8VAMP8 (Dom 1) 1497T 127 45 10 15* 52 37 434.0 619.1For each gene, the best marker column gives a shorthand description of the most significant marker. “Dom” indicates a dominant marker and “Rec” a recessive marker. The following numberis the number of SNPs used in the marker. The remaining information provides the position and allele of each SNP in the haplotype marker. Positions are relative to the transcription startsite, with the A of the ATG at position 1. Sig. (Orig.) indicates the raw significance of the marker in the original data set. All significance scores are given as –10 log (p). A score >12 indicates ap value of 0.05. The Count and Mean columns give the number of subjects and the mean values of the expression levels in the Marker(+) and Marker(–) groups.
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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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Page 57 and 58: 50 COLLINSand expand the genomics r
Page 59 and 60: 52 COLLINSFigure 2. A public-sector
Page 61 and 62: 54 COLLINSdefine all the parts of t
Page 63 and 64: 56 BENTLEYmon over many generations
Page 65 and 66: 58 BENTLEYTable 1. Genetic Disease
Page 67 and 68: 60 BENTLEY(Clark et al. 1998; Reich
Page 69 and 70: 62 BENTLEYACKNOWLEDGMENTSThe author
Page 72 and 73: SNP Genotyping and Molecular Haplot
Page 74: GENETIC ANALYSIS OF DNA POOLS 67gen
Page 77 and 78: 70 FAN ET AL.matrix is then mated t
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Page 81 and 82: 74 FAN ET AL.including 32 duplicate
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Page 85 and 86: 78 FAN ET AL.microsphere-based assa
Page 87 and 88: 80 BERTRANPETIT ET AL.function, may
Page 89 and 90: 82 BERTRANPETIT ET AL.diversity in
Page 91 and 92: 84 BERTRANPETIT ET AL.gree of block
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Page 111 and 112: 104 WINDEMUTH ET AL.much of a surpr
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Page 116 and 117: Genetic Variation and the Control o
Page 118 and 119: GENETIC CONTROL OF TRANSCRIPTION 11
Page 120 and 121: GENETIC CONTROL OF TRANSCRIPTION 11
Page 122 and 123: Genome-wide Detection and Analysis
Page 124 and 125: RECENT SEGMENTAL DUPLICATIONS 117Fi
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Page 130 and 131: RECENT SEGMENTAL DUPLICATIONS 123Ho
Page 132 and 133: The Effects of Evolutionary Distanc
Page 134 and 135: EVOLUTIONARY DISTANCE AND GENE PRED
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Page 138 and 139: Lineage-specific Expansion of KRAB
Page 140 and 141: EVOLUTION OF ZNF GENES 133Figure 2.
Page 142 and 143: EVOLUTION OF ZNF GENES 135Figure 4.
Page 144 and 145: EVOLUTION OF ZNF GENES 137get gene,
Page 146 and 147: 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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332 MALEK ET AL.Figure 1. The bacte
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334 MALEK ET AL.J., Vincent S., and
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336 HARDISON ET AL.reflect blocks o
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338 HARDISON ET AL.plain the region
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340 HARDISON ET AL.CALIBRATION OF T
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342 HARDISON ET AL.PositionRP2.3noE
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344 HARDISON ET AL.cific chromosoma
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346 WESTON ET AL.these differences
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348 WESTON ET AL.els controlled by
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350 WESTON ET AL.ures prominently i
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352 WESTON ET AL.nal and Bop, which
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354 WESTON ET AL.ablp 1466 bopbcrtB
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356 WESTON ET AL.like fold (Fig. 6)
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Implications of Genomics for Public
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GENETIC EPIDEMIOLOGY 361lytic epide
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GENETIC EPIDEMIOLOGY 363curate risk
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A Model System for Identifying Gene
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PTC TASTE GENETICS 367Figure 2. Hap
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PTC TASTE GENETICS 369Table 2. Hapl
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PTC TASTE GENETICS 371the emergence
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374 MCCALLION ET AL.Figure 1. Schem
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376 MCCALLION ET AL.lier (Carrasqui
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378 MCCALLION ET AL.Table 3. HSCR A
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380 MCCALLION ET AL.Figure 3. Trans
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Genetics of Schizophrenia and Bipol
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SCHIZOPHRENIA AND BIPOLAR AFFECTIVE
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The Genetics of Common Diseases: 10
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GENETICS OF COMMON DISEASES 397with
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GENETICS OF COMMON DISEASES 399SELE
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GENETICS OF COMMON DISEASES 401F.,
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404 CHEUNG ET AL.netic analysis. Ex
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406 CHEUNG ET AL.Figure 3. The expr
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Regulation of α-Synuclein Expressi
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α-SYNUCLEIN EXPRESSION AND PD 411T
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1. The levels of α-synuclein prote
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α-SYNUCLEIN EXPRESSION AND PD 415g
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418 BOTSTEINFigure 1. (A) Blectron
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420 BOTSTEINFigure 3. Cluster diagr
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422 BOTSTEINFigure 6. Kaplan-Meier
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424 BOTSTEINGarber M.E., Troyanskay
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426 ANTONARAKIS ET AL.1316192225283
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428 ANTONARAKIS ET AL.Figure 5. Sam
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430 ANTONARAKIS ET AL.POPULATION VA
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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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