The Genom of Homo sapiens.pdf

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HAPLOTYPE EXPRESSION ASSOCIATIONS 105track 69 (Ttk69) protein are important for Ttk69 activity;single amino acid changes in the domain abolish transcriptionalrepression activity (Wen et al. 2000). Furthermore,the zinc fingers in the carboxyl terminus of theTtk69 protein were also important for DNA binding andfunction. ZNF295 is expressed in a wide variety of tissues(Unigene cluster Hs.157079) and is also conserved inmouse (ZNP295, 83.7% identity, Homologene) and in rat(LOC304056, 85.1% identity, Homologene).One interesting observation (Fig. 2) is that the directionof change of the expression levels is not the same for allgenes. In some cases, the Marker(+) group has higher expressionlevels than the Marker(–) group, whereas in others,the opposite is seen. One can speculate that the codingchanges seen in this marker are directly responsiblefor altering the activity of a transcription complex that includesZNF295. If this is the case, one would assume thatthe sign of this activity change would be consistent acrosstranscripts regulated by the complex. However, it couldalso be true that some of these associations are secondordereffects; i.e., ZNF295 is responsible for the transcriptionof some number of the associated genes, but theremaining associated genes are themselves induced bythe directly transcribed genes. We prefer the second explanationbecause, as discussed below, many associationsof ZNF295 haplotypes are with transcription factors,coactivators and genes involved in transcriptional regulation.This induction could be positively or negatively affectedby changes in expression levels of the originalgenes.There are several interesting observations to be made inthe set of genes whose expression levels are associatedwith markers in ZNF295. There is a statistically significantexcess of observed genes on Chromosomes 17 and22. Of the transcripts on Chromosome 22, several clusteron sub-band 22q13.1. As shown in Table 6, ZNF295 haplotypemarkers are associated with 36 genes that are involvedin transcriptional regulation; have DNA-bindingproperties; or are involved in DNA repair and metabolism.Expression levels of 14 genes that are involved in RNAprocessing or that have RNA-binding properties are alsoassociated to markers within the ZNF295 gene. Furthermore,expression levels of several members of very importantclasses of genes such as GTPases (10 genes), immuneresponse genes (10 genes), ATPase or ATP-binding(9 genes), genes involved in cell cycle or cell division orcell–cell signaling (10 genes), protein kinases (13 genes),protein trafficking (11 genes), genes involved in proteinbinding and folding (13 genes), genes involved in signaltransduction (11 genes), and genes involved in apoptosis(5 genes) are highly significantly and reproducibly associatedwith markers within the ZNF295 gene. One examplethat illustrates the impact of ZNF295 haplotypes on expressionlevels of potential target genes is the associationthat links ZNF295 with expression levels of the transcriptionfactor SP100. The 7 individuals in the Marker(+)group have a mean expression level for SP100 of 90.8,whereas the 82 individuals in the Marker(–) group have amean expression level of 52.8. The raw and permutationadjustedp values for the association are 0.00024 and0.0034, respectively. In the replication experiment, theMarker(+) and Marker(–) groups had 6 and 61 individuals,respectively. The respective means were 65.6 and21.2, and the adjusted p value was 0.00016. Three otherinstances are noteworthy because of the involvement ofgenes that have the POZ domain; the association betweenmarkers in the ZNF295 gene and expression levels in theENIGMA, BTBD2, and TAZ genes (Guy et al. 1999;Kanai et al. 2000; Carim-Todd et al. 2001). The BTBD2and the TAZ genes are involved in transcriptional regulation,whereas the ENIGMA gene is involved in receptormediatedendocytosis.Another noteworthy feature of our data is that the twoamino acid changes (Asn181Ser and Lys218Gln) fall outsideof the POZ and the zinc finger domains. Classic mutationalapproaches (such as the changes in the POZ domainof the Tramtrack protein mentioned above) usuallyabolish transcriptional activity such that subtle relationshipsbetween members of the transcriptional machineryare not revealed. By exploiting the naturally occurringvariants in ZNF295, we have not only obtained clues tothe biological function of ZNF295 itself, but also to howit is networked into the larger transcriptional machineryand the extent of its influence on the different cellularprocesses. These results demonstrate the utility of combiningexpression analyses with genetic analyses (such asthe use of haplotype markers) to unravel gene networksand discover gene functions.Figure 4. Fraction of associations withZNF295 that are confirmed (p ≤0.05 in thereplication experiment) as a function of p value(adjusted) in the original experiment. Thedashed line represents the expectation underthe null hypothesis of no confirmation.Fraction Confirmed70%60%50%40%30%20%10%0%10 15 20 25 30 35 40 45 50-10 log(p)
106 WINDEMUTH ET AL.Given our results and all the evidence discussed above,it is highly likely that ZNF295 is a general transcriptionfactor and is a very good candidate for more detailed experimentalapproaches to investigate its transcriptionalactivity, target genes, and possible role in cellular growthand differentiation.Use of Genetic Associations for the Inference ofRegulatory NetworksThere have been many attempts to deduce regulatorynetworks from expression data (Gat-Viks and Shamir2003; Johansson et al. 2003; Kwon et al. 2003; Segal etal. 2003). A major reason for this being such a hard taskis that correlated expression levels do not provide informationon the causality of the correlation. If gene A andgene B are found to be correlated, this could be due to anyof the five following mechanisms: (1) A regulates B, (2)B regulates A, (3) A regulates X which regulates B, (4) Bregulates X which regulates A, (5) X regulates both A andB. To resolve the resulting ambiguities, it is necessary tocollect expression data as time series, on a sample that isnot in a steady state. Alternatively, causality informationcan be obtained by actively disturbing the system; e.g., byknocking out genes or interfering with transcription inother ways. Both of these methods require many measurementsunder carefully controlled conditions, followedby complex analysis.Genetic associations with expression provide a muchmore direct picture of the causality of regulation, sincecausation has to go from genotype to phenotype. In thesame terms as above, if the genotype of gene A is foundassociated with the expression of gene B, there are nowonly two possibilities: (1) A regulates B and (2) A regulatesX regulates B. Furthermore, only one measurementis needed, and the sample can be in a steady state. Oneway of looking at it is that the role of the perturbation necessaryfor deducing causality is played by the naturallyoccurring variations in the genome. This opens the possibilitythat studies such as the one described here will be auseful tool for the discovery of gene–gene interactions inthe emerging field of Systems Biology.ACKNOWLEDGMENTSWe thank the entire team at Genaissance Pharmaceuticalsfor their valuable contributions to building the Hapdatabase that made this work possible.REFERENCESAyoubi T.A. and Van De Ven W.J. 1996. Regulation of gene expressionby alternative promoters. FASEB J. 10: 453.Beaufrere L., Rieu S., Hache J.C., Dumur V., Claustres M., andTuffery S. 1998. Altered rep-1 expression due to substitutionat position +3 of the IVS13 splice-donor site of the choroideremia(CHM) gene. Curr. Eye Res. 17: 726.Brem R.B., Yvert G., Clinton R., and Kruglyak L. 2002. Geneticdissection of transcriptional regulation in budding yeast. Science296: 752.Brookes A.J., Lehvaslaiho H., Siegfried M., Boehm J.G., YuanY.P., Sarkar C.M., Bork P., and Ortigao F. 2000. HGBASE:A database of SNPs and other variations in and around humangenes. Nucleic Acids Res. 28: 356.Brown C.C. and Fears T.R. 1981. Exact significance levels formultiple binomial testing with application to carcinogenicityscreens. Biometrics 37: 763.Carim-Todd L., Sumoy L., Andreu N., Estivill X., and EscarcellerM. 2001. Identification and characterization of BTBD1,a novel BTB domain containing gene on human chromosome15q24. Gene 262: 275.Cavalieri D., Townsend J.P., and Hartl D.L. 2000. Manifoldanomalies in gene expression in a vineyard isolate of Saccharomycescerevisiae revealed by DNA microarray analysis.Proc. Natl. Acad. Sci. 97: 12369.Cheung V.G. and Spielman R.S. 2002. The genetics of variationin gene expression. Nat. Genet. (suppl.) 32: 522.Cheung V.G., Conlin L.K., Weber T.M., Arcaro M., Jen K.Y.,Morley M., and Spielman R.S. 2003. Natural variation in humangene expression assessed in lymphoblastoid cells. Nat.Genet. 33: 422.Couderc J.L., Godt D., Zollman S., Chen J., Li M., Tiong S.,Cramton S.E., Sahut-Barnola I., and Laski F.A. 2002. Thebric a brac locus consists of two paralogous genes encodingBTB/POZ domain proteins and acts as a homeotic and morphogeneticregulator of imaginal development in Drosophila.Development 129: 2419.Cramer P., Caceres J.F., Cazalla D., Kadener S., Muro A.F.,Baralle F.E., and Kornblihtt A.R. 1999. Coupling of transcriptionwith alternative splicing: RNA pol II promotersmodulate SF2/ASF and 9G8 effects on an exonic splicing enhancer.Mol. Cell 4: 251.Deweindt C., Albagli O., Bernardin F., Dhordain P., Quief S.,Lantoine D., Kerckaert J.P., and Leprince D. 1995. TheLAZ3/BCL6 oncogene encodes a sequence-specific transcriptionalinhibitor: A novel function for the BTB/POZ domainas an autonomous repressing domain. Cell Growth Differ.6: 1495.Dhordain P., Albagli O., Lin R.J., Ansieau S., Quief S., Leutz A.,Kerckaert J.P., Evans R.M., and Leprince D. 1997. CorepressorSMRT binds the BTB/POZ repressing domain of theLAZ3/BCL6 oncoprotein. Proc. Natl. Acad. Sci. 94: 10762.Dupont A., Fontana P., Bachelot-Loza C., Reny J.L., Bieche I.,Desvard F., Aiach M., and Gaussem P. 2003. An intronicpolymorphism in the PAR-1 gene is associated with plateletreceptor density and the response to SFLLRN. Blood 101:1833.Fredman D., Siegfried M., Yuan Y.P., Bork P., Lehvaslaiho H.,and Brookes A.J. 2002. HGVbase: A human sequence variationdatabase emphasizing data quality and a broad spectrumof data sources. Nucleic Acids Res. 30: 387.Gabellini N. 2001. A polymorphic GT repeat from the humancardiac Na+Ca2+ exchanger intron 2 activates splicing. Eur.J. Biochem. 268: 1076.Gat-Viks I. and Shamir R. 2003. Chain functions and scoringfunctions in genetic networks. Bioinformatics (suppl. 1) 19:I108.Grantham R. 1974. Amino acid difference formula to help explainprotein evolution. Science 185: 862.Guy P.M., Kenny D.A., and Gill G.N. 1999. The PDZ domain ofthe LIM protein enigma binds to beta-tropomyosin. Mol. Biol.Cell 10: 1973.Hariharan N., Kelley D.E., and Perry R.P. 1991. Delta, a transcriptionfactor that binds to downstream elements in severalpolymerase II promoters, is a functionally versatile zinc fingerprotein. Proc. Natl. Acad. Sci. 88: 9799.Heyse J. and Rom D. 1988. Adjusting for multiplicity of statisticaltests in the analysis of carcinogenicity studies. Biom. J.30: 883.Iuchi S. 2001. Three classes of C2H2 zinc finger proteins. CellMol. Life Sci. 58: 625.Jansen R.C. and Nap J.P. 2001. Genetical genomics: The addedvalue from segregation. Trends Genet. 17: 388.Jin W., Riley R.M., Wolfinger R.D., White K.P., Passador-Gurgel G., and Gibson G. 2001. The contributions of sex,
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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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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
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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 87 and 88: 80 BERTRANPETIT ET AL.function, may
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Page 91 and 92: 84 BERTRANPETIT ET AL.gree of block
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Page 99 and 100: 92 WINDEMUTH ET AL.Table 1. A Summa
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Page 122 and 123: Genome-wide Detection and Analysis
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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
Page 148 and 149: Sequence Organization and Functiona
Page 150 and 151: CENTROMERE ANNOTATION 143THE CENTRO
Page 152 and 153: CENTROMERE ANNOTATION 145Figure 4.
Page 154 and 155: CENTROMERE ANNOTATION 147CONCLUSION
Page 156: CENTROMERE ANNOTATION 149Schueler M
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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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