HUMAN MUTATIONAL PROFILING 27Figure 4. Results from our pilot study <strong>of</strong> AML suspect genes in42 patient samples, indicating the gene sequences (left column),and the synonomous and nonsynonomous amino acid-alteringmutations found. In the case <strong>of</strong> the FLT3 gene, we found theexon 11 ITD in 20% <strong>of</strong> patients as well as the exon 17 (D835Y)mutation in 10% <strong>of</strong> the patients studied.mouse model and patient samples. Overall, the validationphase will serve as a means <strong>of</strong> increasing the size <strong>of</strong> ourAML data set <strong>of</strong> mutational pr<strong>of</strong>iles centered on a smallernumber <strong>of</strong> candidate genes. Following on, a second round<strong>of</strong> correlation <strong>of</strong> these pr<strong>of</strong>iles back to AML subtypes andclinical outcomes should serve to further focus our attentionon a handful <strong>of</strong> genes now highly suspect for their involvementin AML pathogenesis.Our preliminary findings from this study, using 13genes, have been described elsewhere (Ley et al. 2003)and are summarized in Figure 4. Briefly, for the 13 genesstudied in 46 patient samples (tumor and somatic/controlDNA samples) representing different AML subtypes(M0/M1, M2, M3/APL, and M4), we found that previouslydescribed mutations in CBF-β, FLT3, c-KIT,c-MYC, N-RAS, PML, and RARα were also found in ourpatient samples, as indicated. Most notably, in FLT3 wedetected the previously described internal tandem duplication(ITD) in exon 11 but also found another FLT3 mutationcausing a nonsynonomous amino acid change(D835Y) in 10% <strong>of</strong> the patient samples sequenced.FUTURE DIRECTIONSSequence-based mutational pr<strong>of</strong>iling represents an immediateapplication <strong>of</strong> the human genome sequence, andthe technology developed to produce it, toward the study<strong>of</strong> human health and disease. In the near term, we can utilizemutational pr<strong>of</strong>iling to better understand the molecularbasis <strong>of</strong> many human diseases for which there are candidategenes, or at least a reasonable number <strong>of</strong> suspectedcandidates. For genes such as SPB that play a role in bothmoderate and severe forms <strong>of</strong> a disease, such an understandingwill be critical to improved diagnosis, treatment,and management <strong>of</strong> patients who carry these sequencechanges. Likewise, as we begin to discover and study theinterplay <strong>of</strong> sequence changes and mutations in the bevy<strong>of</strong> genes that underlie various human cancers, we willcreate new opportunities for earlier diagnosis that willsubstantially save lives and decrease health care costseven with current state-<strong>of</strong>-the-art cancer treatments. Ultimately,a better understanding <strong>of</strong> the genes involved incancer and other diseases will allow the development <strong>of</strong>targeted therapeutics (such as Gleevec) that are aimeddirectly at the molecular flaw.Although the technology and its associated expensecurrently require that we focus our efforts and sequencingpipelines nearly exclusively on the exons <strong>of</strong> candidategenes, it is clear that we must in the future develop mutationalpr<strong>of</strong>iling strategies and methods that will allow usto cast a broader net, aimed at discovering causal mutationsand sequence changes that lie outside <strong>of</strong> coding sequenceand candidate genes. Ideally, we would prefer tosequence a patient’s complete genome (both “germ line”and from the affected tissue), cross-reference all sequencevariations and discovered mutations, and characterizeany epigenomic changes as well. 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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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SCHIZOPHRENIA AND BIPOLAR AFFECTIVE
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SCHIZOPHRENIA AND BIPOLAR AFFECTIVE
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SCHIZOPHRENIA AND BIPOLAR AFFECTIVE
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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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GENOME ARCHITECTURE AND GENOMIC DIS
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GENOME ARCHITECTURE AND GENOMIC DIS
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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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TRANSCRIPTIONAL UNITS AND GENE PAIR
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TRANSCRIPTIONAL UNITS AND GENE PAIR
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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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HUMAN-SPECIFIC EVOLUTIONARY CHANGES
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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,