In the field of forensics, there is a critical need for genetic tests that can function in a predictive or inferential sense, before suspects have been identified, and/or for crimes for which DNA evidence exists but eye-witnesses do not. Molecular Photofitting fills this need by describing the process of generating a physical description of an individual from the analysis of his or her DNA. The molecular photofitting process has been used to assist with the identification of remains and to guide criminal investigations toward certain individuals within the sphere of prior suspects.
Molecular Photofitting provides an accessible roadmap for both the forensic scientist hoping to make use of the new tests becoming available, and for the human genetic researcher working to discover the panels of markers that comprise these tests. By implementing population structure as a practical forensics and clinical genomics tool, Molecular Photofitting serves to redefine the way science and history look at ancestry and genetics, and shows how these tools can be used to maximize the efficacy of our criminal justice system.
- Explains how physical descriptions of individuals can be generated using only their DNA
- Contains case studies that show how this new forensic technology is used in practical application
- Includes over 100 diagrams, tables, and photos to illustrate and outline complex concepts
Inhaltsverzeichnis
1;Front Cover;1 2;Molecular Photofitting;4 3;Copyright Page;5 4;Table of Contents;6 5;Foreword;12 6;Preface;14 7;Acknowledgments;16 8;Chapter 1: Forensic DNA Analysis: From Modest Beginnings to Molecular Photofitting, Genics, Genetics, Genomics, and the Pertinent Population Genetics Principles;17 8.1;Part I: Introduction: Brief History of DNA in Forensic Sciences;17 8.1.1;The Statistics of Forensic DNA Analysis;22 8.1.2;The Nature of Human Genetic Variation;26 8.1.3;Population Genetics and Population Genomics;27 8.1.4;The Promise of Molecular Photofitting as a Tool in Forensic Science;32 8.2;Part II: The Basic Principles;35 8.2.1;Lack of Human Diversity Relative to Other Species;48 9;Chapter 2: Ancestry and Admixture;51 9.1;What Are Ancestry and Admixture?;51 9.2;The Need for Molecular Tests for Ancestry;53 9.3;Ancestry Informative Markers;59 9.4;Biogeographical Ancestry Admixture as a Tool for Forensics and Physical Profiling;70 10;Chapter 3: Biogeographical Ancestry Admixture Estimation-Theoretical Considerations;73 10.1;Estimating by Anthropometric Trait Value;73 10.2;Admixture and Gene Flow Estimated from Single Loci;75 10.3;Admixture in Individual Samples;84 10.4;Using the Hanis Method on Population Models k>2;87 10.5;Parameter Uncertainty;91 10.6;Bayesian Methods for Accommodating Parameter Uncertainty;100 10.7;Sampling Error;104 10.8;Assumptions about Marker Linkage and Intensity of Admixture in Parents;106 10.9;Pritchards Structure Program;108 10.10;In Defense of a Simple Admixture Model;110 10.11;Practical Considerations for Building an Ancestry Admixture Test;111 10.12;Selecting AIMs from the Genome-How Many Are Needed?;119 10.13;Comparing the Power of Specific Loci for Specific Resolutions;126 10.14;Genomic Coverage of AIMs;130 10.15;More Elaborate Methods of Selecting Markers for Information Content;131 10.16;Shannon Information;132 10.17;Fischerian Information Content;134 10.18;Informativeness for Assignment;135 10.19;Type of Polymorphisms;139 10.20;Int
erpretation of Ancestry Estimates;141 10.21;Objective Interpretation;148 10.22;Genetic Mapping and Admixture;149 10.23;Appendix (Ancestry Frequency Table);153 11;Chapter 4: Biogeographical Ancestry Admixture Estimation-Practicality and Application;161 11.1;The Distribution of Human Genetic Variability and Choice of Population Model;162 11.2;Marker Selection;179 11.3;Sample Collection;180 11.4;Presenting Individual Biogeographical Ancestry (BGAA) Results;195 11.5;Conceptual Issues;206 12;Chapter 5: Characterizing Admixture Panels;219 12.1;Parental Sample Plots;219 12.2;Model Choices and Dimensionality;221 12.3;Size of Confidence Contours;226 12.4;Repeatability;229 12.5;Sensitivity;236 12.6;Analysis of Results for Genealogists;238 12.7;Analysis of Results for Nongenealogists;246 12.8;Blind Challenge of Concordance with Self-Assessed Race;248 12.9;Confidence Interval Warping;251 12.10;Sampled Pedigrees;253 12.11;Simulated Pedigrees;256 12.12;Comparing Different Algorithms with the Same AIM Panel;257 12.13;Analysis Using Subsets of Markers;259 12.14;Resolving Sample Mixtures;261 12.15;Sample Quantity;266 12.16;Nonhuman DNA;267 12.17;Performance with Altered Parental Allele Frequencies;269 12.18;Correlation with Anthropometric Phenotypes;273 12.19;Simulations;276 12.20;Creating Simulated Samples;278 12.21;Source of Error Measured with Simulations;279 12.22;Relationship between Error in Populations and within Individuals;281 12.23;Precision of the 71 AIM Panel from Simulations;284 12.24;Trends in Bias from the 71 AIM Panel;286 12.25;95% Confidence Threshold for 71 AIM Panel;289 12.26;Precision of the 171 AIM Panel from Simulations;291 12.27;MLE Thresholds for Assumption of Bona Fide Affiliation;293 12.28;Comparison of 71 and 171 AIM Panels;293 12.29;Observed and Expected Bias;293 12.30;What Do the Simulations Teach Us about Interpreting BGA Admixture Results?;295 12.31;Bias Symmetry;296 12.32;Impact of MLE Algorithm Dimensionality;298 12.33;Simulations of Admixed Individu
als;300 12.34;MLE Precision from the Triangle Plots;301 12.35;Confidence of Nonzero Affiliation;302 12.36;Standard Deviation from Confidence Intervals;302 12.37;Testing the Relation between Confidence Measures in Individuals and Populations;304 12.38;Space outside the Triangle Plot;305 12.39;Combined Sources Suggest an Average Error;310 13;Chapter 6: Apportionment of Autosomal Diversity With Continental Markers;313 13.1;The Need for Population Databases-Words Mean Less Than Data;313 13.2;Trends on an Ethnic Level: Autosomal Versus Sex Chromosome Pattern;315 13.3;What Do Continental Ancestry AIMs Say about Ethnicity?;319 13.4;The Significance of Fractional Affiliation Results on a Population Level;321 13.5;Reconstructing Human Histories from Autosomal Admixture Results;326 13.6;Shared Recent Ancestry Versus Admixture: What Does Fractional Continental Affiliation for an Ethnic Group Mean?;327 13.7;Returning Briefly to the Naming Problem-Relevance for Interpreting the Apportionment of Autosomal Diversity;329 13.8;A Sampling of Ethnicities Using the 171 AIM Panel;332 13.9;Interpretation of Ancestry Profiles for Ethnic Populations;338 13.10;East Asian Admixture in the Middle East and South Asia;353 13.11;Resolution within Continents Based on the Four-Population Model;367 13.12;Interpretation of Continental BGA Results in Light of What We Have Learned from Application to Ethnic Populations;368 13.13;Appropriateness of a Four-Population Model;371 13.14;Do Allele Frequency Estimation Errors Account for the Secondary Affiliations in Ethnic Subpopulations?;373 13.15;Indications of Cryptic Population Structure;375 14;Chapter 7: Apportionment of Autosomal Diversity with Subcontinental Markers;377 14.1;Subpopulation AIMs and Ethnic Stratification;377 14.2;Within the European BGA Group-A Brief History of Europeans;379 14.3;How Do We Subdivide Europeans for Forensics Use?;382 14.4;Development of a Within-European AIM Panel;383 14.5;The Euro 1.0 AIM Panel for a Four-Population Subc
ontinental Model;385 14.6;Establishing the Optimal Parental Representatives;386 14.7;Blind Challenge with Ethnically Admixed European-American Samples;394 14.8;Population Isolates and Transplants;396 14.9;Correlations with Anthropometric Traits;400 14.10;Test Error;403 14.11;Hierarchical Nature of Euro 1.0-Prior Information Required;413 14.12;Euro 1.0 Pedigrees as an Aid to Interpreting Results;419 14.13;Euro 1.0-Interpretation of Variation within Groups;423 14.14;An Historical Perspective;426 14.15;More Detailed Subpopulation Stratificationsk = 7;428 14.16;What Do the Groups NOR1, NOR2 . . . Mean?;430 14.17;Evaluating the Results from the k = 7 European Model;432 14.18;Comparison with Previous Studies Based on Gene Markers;433 14.19;Comparison with Results from Other Studies;435 14.20;Blind Challenge of the k = 7 Model Results with Ethnic Samples;436 14.21;Correlation with Anthropometric Traits;439 14.22;Pedigrees;441 14.23;Substantial Variation in Admixture within Ethnic Groups;441 14.24;Alternative Styles for Estimating Ethnic Admixture;443 15;Chapter 8: Indirect Methods for Phenotype Inference;445 15.1;Estimates of Genomic Ancestry Allows for Inference of Certain Phenotypes;445 15.2;Phenotype Variation as a Function of Human Population History and Individual Ancestry;446 15.3;Sources of Phenotypic Variation;448 15.4;Empirical Observation of Admixture-Based Correlation Enables Generalization;454 15.5;Empiricism as a Tool for the Indirect Method of Molecular Photofitting;456 15.6;Reverse Facial Recognition Using Genomic Ancestry Estimates;466 15.7;Estimating Phenotype from 2D Digital Photographs;470 15.8;Estimating Phenotype from 3D Digital Photographs;472 15.9;Examples of Database Queries-Global Characteristics from Digital Photographs;474 15.10;Examples of Database Queries-Ethnic Descriptors and Geopolitical Affiliations;477 15.11;Variation and Parameterization of Database Observations;480 15.12;Can Social Construct Such as Race Be Inferred from DNA?;484 15.13;I
ndirect Approach Using Finer Population Models;488 15.14;Indirect Inference of Skin Pigmentation;493 15.15;Sources of the Ancestry-Skin Pigmentation Correlation;501 15.16;Can We Infer M Knowing Genomic Ancestry?;504 15.17;Inferences of Composite Characteristics;506 15.18;Why Not Use the Direct Method Instead?;506 15.19;Indirect Inference of Iris Pigmentation;507 16;Chapter 9: Direct Method of Phenotype Inference;513 16.1;Pigmentation;516 16.2;History of Pigmentation Research;519 16.3;The Genetics of Human Pigmentation-A Complex Puzzle;520 16.4;Biochemical Methods of Quantifying Pigment;523 16.5;Iris Color;529 16.6;Iris Color Phenotyping: The Need for a Thoughtful Approach;530 16.7;Making Iris Color Measurements;533 16.8;Population Surveys of Iris Melanin Index (IMI) Values;539 16.9;Relation of IMI to Self-Described Iris Color;540 16.10;History of Genetic Research on Iris Color;543 16.11;Recent History of Association Mapping Results;546 16.12;OCA2-The Primary Iris Color Gene;550 16.13;An Empirical OCA2-Based Classifier for the Inference of Iris Color;559 16.14;The Empirical Method of Direct Phenotype Inference;569 16.15;Case Reports;574 16.16;Hair Color;578 16.17;Skin Pigmentation;599 16.18;Final Considerations for the Direct Inference of Skin Pigmentation;612 17;Chapter 10: The First Case Studies of Molecular Photofitting;615 17.1;Case Reports;615 17.2;Louisiana Serial Killer Multiagency Homicide Task Force Investigation;615 17.3;Operation Minstead;619 17.4;The Boulder, Colorado Chase Case;623 17.5;Other Cases;623 18;Chapter 11: The Politics and Ethics of Genetic Ancestry Testing;625 18.1;Resistance;626 18.2;Articles-Insight into Public Reaction;629 18.3;Molecular Eyewitness: DNA Gets a Human Face;629 18.4;DNA Tests Offer Clues to Suspects Race;634 18.5;Concerns of the Defense-Minded;642 18.6;Concerns of the Prosecution-Minded;645 18.7;Resistance in the Scientific Community;648 18.8;Racism and Genetic Ancestry Testing;663 18.9;Racism and the Common Racist Mantra;664
18.10;The Data Does Not and Probably Cannot Support the Racist Viewpoint;668 18.11;Subjective Nature of the Word Intelligence;671 18.12;According to Nature, Diversity Is a Good Thing;672 19;Bibliography;677 20;Index;693
