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Bibliografická citace

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0 (hodnocen0 x )
BK
2nd ed.
New York : Garland Science, c2014
xviii, 670 s. : il ; 28 cm

ISBN 978-0-8153-4148-2 (brož.)
Obsahuje slovníček
Obsahuje bibliografické odkazy a rejstřík
000248935
DETAILED CONTENTS // CHAPTER 1 AN INTRODUCTION TO HUMAN EVOLUTIONARY GENETICS 1 // 1.1 WHAT IS HUMAN EVOLUTIONARY GENETICS? 1 // 1.2 INSIGHTS INTO PHENOTYPES AND DISEASES 2 // A shared evolutionary history underpins our understanding of biology 2 // Understanding evolutionary history is essential to understanding human biology today 4 // Understanding evolutionary history shapes our expectations about the future 5 // 1.3 COMPLEMENTARY RECORDS OF THE HUMAN PAST 6 // Understanding chronology allows comparison of evidence from different scientific approaches 8 // It is important to synthesize different records of the past 10 None of the different records represents an unbiased picture of the past 10 // 1.4 WHAT CAN WE KNOW ABOUTTHE PAST? 11 // 1.5 THE ETHICS OF STUDYING HUMAN POPULATIONS 12 // SUMMARY 14 // REFERENCES 14 // CHAPTER 2 ORGANIZATION AND INHERITANCE OFTHE HUMAN GENOME 17 // 2.1 THE BIG PICTURE: AN OVERVIEW OF THE HUMAN // GENOME 17 // 2.2 STRUCTURE OF DNA 20 // 2.3 GENES, TRANSCRIPTION, AND TRANSLATION 22 // Genes are made up of introns and exons, and include elements to initiate and regulate transcription 22 // The genetic code allows nucleotide sequences to be translated into amino acid sequences 24 // Gene expression is highly regulated in time and space 26 // 2.4 NONCODING DNA 26 // Some DNA sequences in the genome are repeated in multiple copies 27 //
2.5 HUMAN CHROMOSOMES AND THE HUMAN // KARYOTYPE 28 // The human genome is divided into 46 chromosomes 29 // Size, centromere position, and staining methods // allow chromosomes to be distinguished 31 // 2.6 MITOSIS, MEIOSIS, AND THE INHERITANCE OF // THE GENOME 31 // 2.7 RECOMBINATION—THE GREAT RESHUFFLER 34 // 2.8 NONRECOMBINING SEGMENTS OF THE GENOME 36 // The male-specific Y chromosome escapes crossing over for most of its length 37 // Maternally inherited mtDNA escapes from recombination 37 // SUMMARY 40 // QUESTIONS 41 // REFERENCES 41 // CHAPTER 3 HUMAN GENOME VARIATION 43 // 3.1 GENETIC VARIATION AND THE PHENOTYPE 43 // Some DNA sequence variation causes Mendelian genetic disease 44 // The relationship between genotype and phenotype is usually complex 46 // Mutations are diverse and have different rates and mechanisms 46 // 3.2 SINGLE NUCLEOTIDE POLYMORPHISMS (SNPS) IN THE NUCLEAR GENOME 47 // Base substitutions can occur through base misincorporation during DNA replication 49 // Base substitutions can be caused by chemical and physical mutagens 51 // Sophisticated DNA repair processes can fix much genome damage 52 // The rate of base substitution can be estimated indirectly or directly 53 // Because of their low mutation rate, SNPs usually show identity by descent 55 // The CpG dinucleotide is a hotspot for mutation 55 // Base substitutions and indels can affect the functions of genes 57 // Synonymous base substitutions 57 // Nonsynonymous base substitutions 58 // Indels within genes 59 // Base substitutions outside ORFs 60 // Whole-genome resequencing provides an unbiased picture of SNP diversity 61 //
3.3 SEQUENCE VARIATION IN MITOCHONDRIAL DNA 62 // mtDNA has a high mutation rate 62 // The transmission of mtDNA mutations between generations is complex 64 // 3.4 VARIATION IN TANDEMLY REPEATED DNA SEQUENCES 65 // Microsatellites have short repeat units and repeat arrays, and mutate through replication slippage 66 // Microsatellite mutation rates and processes 67 // Minisatellites have longer repeat units and arrays, and mutate through recombination mechanisms 69 // Minisatellite diversity and mutation 70 // Telomeres contain specialized and functionally important repeat arrays 71 // Satellites are large, sometimes functionally important, repeat arrays 72 // 3.5 TRANSPOSABLE ELEMENT INSERTIONS 73 // 3.6 STRUCTURAL VARIATION IN THE GENOME 75 // Some genomic disorders arise from recombination between segmental duplications 76 // KKру-number variation is widespread in the human genome 77 // Cytogenetic examination of chromosomes can reveal large-scale structural variants 78 // 3.7 THE EFFECTS OF AGE AND SEX ON MUTATION RATE 78 // 3.8 THE EFFECTS OF RECOMBINATION ON GENOME VARIATION 81 // Genomewide haplotype structure reveals past recombination behavior 84 // Recombination behavior can be revealed by direct studies in pedigrees and sperm DNA 87 // The process of gene conversion results in nonreciprocal exchange between DNA sequences 88 // SUMMARY 90 // QUESTIONS 91 // REFERENCES 92 //
CHAPTER 4 FINDING AND ASSAYING GENOME DIVERSITY 95 // 4.1 FIRST, FIND YOUR DNA 96 // 4.2 THE POLYMERASE CHAIN REACTION (PCR) 98 // 4.3 SANGERSEQUENCING,THE HUMAN REFERENCE SEQUENCE, AND SNP DISCOVERY 100 // 4.4 A QUANTUM LEAP IN VARIATION STUDIES: NEXT-GENERATION SEQUENCING 101 // Illumina sequencing is a widely used NGS method 102 // Sequencing can be targeted to regions of specific interest or the exome 105 // NGS data have to be processed and interpreted 106 // Third-generation methods use original, unamplified DNA 107 // 4.5 SNPTYPING: LOW-, MEDIUM-, AND HIGH-THROUGHPUT METHODS FOR ASSAYING VARIATION 108 // PCR-RFLP typing is a simple low-throughput method 108 // Primer extension and detection by mass // spectrometry is a medium-throughput method 109 // High throughput SNP chips simultaneously analyze // more than 1 million SNPs 110 // Whole-genome SNP chips are based on a tag SNP // design 110 // 4.6 DATABASES OF SEQUENCE VARIATION 112 // 4.7 DISCOVERING AND ASSAYING VARIATION AT MICROSATELLITES 112 // 4.8 DISCOVERING AND ASSAYING STRUCTURAL VARIATION ON DIFFERENT SCALES 114 // Discovering and assaying variation at minisatellites 114 // Discovering and assaying variation at well-defined indels, including A/u/LINE polymorphisms 115 // Discovering and assaying structural polymorphisms and сKру-number variants 115 // 4.9 PHASING: FROM GENOTYPES TO HAPL0TYPES 119 // Haplotypes can be determined by physical separation 120 // Haplotypes can be determined by statistical methods 120 // Haplotypes can be determined by pedigree analysis 122 // 4.10 STUDYING GENETIC VARIATION IN ANCIENT SAMPLES 123 // DNA is degraded after death 123 // Contamination is a major problem 125 // Application of next-generation sequencing to aDNA analysis 127 // SUMMARY 129 // QUESTIONS 130 // REFERENCES 130 //
CHAPTER 5 PROCESSES SHAPING DIVERSITY 133 // 5.1 BASIC CONCEPTS IN POPULATION GENETICS 133 // Why do we need evolutionary models? 133 // The Hardy-Weinberg equilibrium is a simple model in population genetics 134 // 5.2 GENERATING DIVERSITY BY MUTATION // AND RECOMBINATION 136 // Mutation changes allele frequencies 137 // Mutation can be modeled in different ways 137 // Meiotic recombination generates new combinations of alleles 139 // Linkage disequilibrium is a measure of recombination at the population level 140 // Recombination results in either crossing over or gene conversion, and is not uniform across the genome 140 // 5.3 ELIMINATING DIVERSITY BY GENETIC DRIFT 141 // The effective population size is a key concept in population genetics 142 // xii DETAILED CONTENTS // Different parts of the genome have different effective population sizes 143 // Genetic drift causes the fixation and elimination of new alleles 143 // Variation in census population size and reproductive success influence effective population size 144 // Population subdivision can influence effective population size 147 // Mate choice can influence effective population size 148 // Genetic drift influences the disease heritages of isolated populations 149 //
5.4 THE EFFECT OF SELECTION ON DIVERSITY 149 // Mate choice can affect allele frequencies by sexual selection 153 // 5.5 MIGRATION 154 // There are several models of migration 154 // There can be sex-specific differences in migration 155 // 5.6 INTERPLAY AMONG THE DIFFERENT FORCES OF EVOLUTION 156 // There are important equilibria in population genetics 157 // Mutation-drift balance 157 // Recombination-drift balance 157 // Mutation-seleclion balance 158 // Does selection or drift determine the future of an allele? 159 // 5.7 THENEUTRALTHE0RY0FM0LECULAR EVOLUTION 160 // The molecular clock assumes a constant rate of mutation and can allow dating of speciation 160 // There are problems with the assumptions of the molecular clock 161 // SUMMARY 163 // QUESTIONS 164 // REFERENCES 164 // CHAPTER 6 MAKING INFERENCES FROM DIVERSITY 167 // 6.1 WHAT DATA CAN WE USE? 167 // 6.2 SUMMARIZING GENETIC VARIATION 168 // Heterozygosity is commonly used to measure genetic diversity 168 // Nucleotide diversity can be measured using the population mutation parameter theta (Ѳ) 169 // The mismatch distribution can be used to represent genetic diversity 172 // 6.3 MEASURING GENETIC DISTANCE 173 // Genetic distances between populations can be measured using Fsi or Nei’s D statistics 173 // Distances between alleles can be calculated using models of mutation 175 // Genomewide data allow calculation of genetic distances between individuals Complex population structure can be analyzed statistically
// Population structure can be analyzed using genomic data // Genetic distance and population structure can be represented using multivariate analyses // 6.4 PHYLOGENETICS // Phylogenetic trees have their own distinctive terminology // There are several different ways to reconstruct phylogenies // Trees can be constructed from matrices of genetic distances // Trees can be generated using character-based methods // How confident can we be of a particular phylogenetic tree? // Networks are methods for displaying multiple equivalent trees // 6.5 COALESCENT APPROACHES TO RECONSTRUCTING POPULATION HISTORY // The genealogy of a DNA sequence can be described mathematically // Neutral mutations can be modeled on the gene genealogy using Poisson statistics Coalescent analysis can be a simulation tool for hypothesis testing // Coalescent analysis uses ancestral graphs to model // selection and recombination // Coalescent models of large datasets are approximate // 6.6 DATING EVOLUTIONARY EVENTS USING GENETIC DATA // Dating population splits using Fst and Nei’s D statistics is possible, but requires a naive view of human evolution // Evolutionary models can include the timing of evolutionary events as parameters Evolutionary models and effective population size An allele can be dated using diversity at linked loci Interpreting TMRCA //
Estimations of mutation rate can be derived from direct measurements in families or indirect comparisons of species An estimate of generation time is required to convert some genetic date estimates into years // 6.7 HAS SELECTION BEEN ACTING? // Differences in gene sequences between species can be used to detect selection Comparing variation between species with variation within a species can detect selection Selection tests can be based on the analysis of allele frequencies at variant sites // Comparing haplotype frequency and haplotype // diversity can reveal positive selection 209 // Analysis of frequency differences between // populations can indicate positive selection 209 // Other methods can be used to detect ongoing // or very recent positive selection 214 // How can we combine information from different // statistical tests? 214 // Tests for positive selection have severe limitations 215 // 6.8 ANALYZING GENETIC DATA IN A GEOGRAPHICAL // CONTEXT 216 // Genetic data can be displayed on maps 217 // Genetic boundary analysis identifies the zones of greatest aliele frequency change within a genetic landscape 219 // Spatial autocorrelation quantifies the relationship of allele frequency with geography 219 // Mantel testing is an alternative approach to examining a relationship between genetic distance and other distance measures 220 // SUMMARY 220 // QUESTIONS 221 // REFERENCES 222 //
CHAPTER 7 HUMANS AS APES 225 // Which nonhuman animals are the closest living // relatives of humans? 225 // Are humans typical apes? 225 // 7.1 EVIDENCE FROM MORPHOLOGY 226 // Primates are an Order of mammals 226 // Hominoids share a number of phenotypic // features with other anthropoids 228 // Ancestral relationships of hominoids are difficult // to resolve on morphological evidence 230 // 7.2 EVIDENCE FROM CHROMOSOMES 232 // Human and great ape karyotypes look similar, but // not identical 232 // Molecular cytogenetic analyses support the picture // from karyotype comparisons 233 // 7.3 EVIDENCE FROM MOLECULES 236 // Molecular data support a recent date of the // ape-human divergence 237 // Genetic data have resolved the gorilla-chimpanzee- // human trichotomy 237 // Sequence divergence is different among great apes // across genetic loci 239 // Great apes differ by gains and losses of genetic // material 241 // The DNA sequence divergence rates differ in // hominoid lineages 241 // 7.4 GENETIC DIVERSITY AMONG THE GREAT APES 242 // How many genera, species, and subspecies are there? 247 // Intraspecific diversity in great apes is greater than in humans 247 // Signatures of lineage-specific selection can be detected in ape genomes 250 // SUMMARY 254 // QUESTIONS 254 // REFERENCES 254 //
CHAPTER 8 WHAT GENETIC CHANGES HAVE MADE US HUMAN? 257 // 8.1 MORPHOLOGICAL AND BEHAVIORAL CHANGES // EN ROUTE TO HOMO SAPIENS 258 // Some human traits evolved early in hominin history 260 // The human mind is unique 263 // Only a few phenotypes are unique to modern humans 265 // 8.2 GENETIC UNIQUENESS OF HUMANS AND H0MININS 265 // The sequence and structural differences between // humans and other great apes can be cataloged 265 // Humans have gained and lost a few genes // compared with other great apes 266 // Humans differ in the sequence of genes compared // with other great apes 269 // Humans differ from other apes in the expression // levels of genes 270 // Genome sequencing has revealed a small number // of fixed genetic differences between humans and // both Neanderthals and Denisovans 272 // 8.3 GENETIC BASIS OF PHENOTYPIC DIFFERENCES BETWEEN APES AND HUMANS 273 // Mutations causing neoteny have contributed to the evolution of the human brain 273 // The genetic basis for laterality and language remains unclear 275 // What next? 278 // SUMMARY 278 // QUESTIONS 279 // REFERENCES 279 // CHAPTER 9 ORIGINS OF MODERN HUMANS 283 // 9.1 EVIDENCE FROM FOSSILS AND MORPHOLOGY 284 // Some fossils that may represent early hominins from // 4-7 MYA are known from Africa 285 // Fossils of australopithecines and their contemporaries // are known from Africa 287 // The genus Homo arose in Africa 290 // The earliest anatomically modern human fossils // are found in Africa 294 // The morphology of current populations suggests // an origin in Africa 295 //
9.2 EVIDENCE FROM ARCHAEOLOGY AND LINGUISTICS 295 // Paleolithic archaeology has been studied extensively 298 // Evidence from linguistics suggests an origin of // language in Africa 299 // 9.3 HYPOTHESES TO EXPLAIN THE ORIGIN OF // MODERN HUMANS 300 // 9.4 EVIDENCE FROM THE GENETICS OF PRESENT-DAY POPULATIONS 301 // Genetic diversity is highest in Africa 301 // Genetic phylogenies mostly root in Africa 304 // Mitochondrial DNA phytogeny 304 // Y-chromosomal phytogeny 305 // Other phylogenies 305 // Insights can be obtained from demographic models 306 // 9.5 EVIDENCE FROM ANCIENT DNA 307 // Ancient mtDNA sequences of Neanderthals and Denisovans are distinct from modern human variation 308 A Neanderthal draft genome sequence has been generated 309 // A Denisovan genome sequence has been generated 310 // SUMMARY 313 // QUESTIONS 315 // REFERENCES 315 // CHAPTER 10 THE DISTRIBUTION OF DIVERSITY 319 // 10.1 STUDYING HUMAN DIVERSITY 319 // The history and ethics of studying diversity are complex 319 // Linnaeus’ classification of human diversity 320 // Galton’s "Comparative worth of different races" 320 // Modern attitudes to studying diversity 320 // Who should be studied? 323 // A few large-scale studies of human genetic variation have made major contributions to human evolutionary genetics 323 // What is a population? 326 // How many people should be analyzed? 327 //
10.2 APPORTIONMENT OF HUMAN DIVERSITY 328 // The apportionment of diversity shows that most variation is found within populations 328 // The apportionment of diversity can differ between segments of the genome 329 // Patterns of diversity generally change gradually from place to place 330 // The origin of an individual can be determined surprisingly precisely from their genotype 331 // The distribution of rare variants differs from that of common variants 332 // 10.3 THE INFLUENCE OF SELECTION ON THE APPORTIONMENT OF DIVERSITY 333 // The distribution of levels of differentiation has been studied empirically 334 // Low differentiation can result from balancing selection 334 // High differentiation can result from directional selection 335 // Positive selection at EDAR 336 // SUMMARY 338 // QUESTIONS 339 // REFERENCES 339 // CHAPTER 11 THE COLONIZATION OF THE OLD WORLD AND AUSTRALIA 341 // 11.1 A COLDER AND MORE VARIABLE ENVIRONMENT 15-100 KYA 341 // 11.2 FOSSIL AND ARCHAEOLOGICAL EVIDENCE FOR TWO EXPANSIONS OF ANATOMICALLY MODERN HUMANS OUT OF AFRICA IN THE LAST -130 KY 344 // Anatomically modern, behaviorally pre-modern // humans expanded transiently into the Middle East // -90-120 KYA 345 // Modern human behavior first appeared in Africa // after 100 KYA 346 // Fully modern humans expanded into the Old World // and Australia -50-70 KYA 347 // Modern human fossils in Asia, Australia, and Europe 347 // Initial colonization of Australia 349 // Upper Paleolithic transition in Europe and Asia 352 // 11.3 A SINGLE MAJOR MIGRATION OUT OF AFRICA // 50-70 KYA 353 // Populations outside Africa carry a shared subset of African genetic diversity with minor Neanderthal admixture 353 // mtDNA and Y-chromosomal studies show the descent of all non-African lineages from a single ancestor for each who lived 55-75 KYA 355 //
11.4 EARLY POPULATION DIVERGENCE BETWEEN AUSTRALIANS AND EURASIANS 357 // SUMMARY 360 // QUESTIONS 361 // REFERENCES 361 // CHAPTER 12 AGRICULTURAL EXPANSIONS 363 // 12.1 DEFINING AGRICULTURE 363 // 12.2 THE WHERE, WHEN, AND WHY OF AGRICULTURE 365 // Where and when did agriculture develop? 365 // Why did agriculture develop? 366 // Which domesticates were chosen? 368 // 12.3 OUTCOMES OF AGRICULTURE 369 // Agriculture had major impacts on demography and disease 369 // Rapid demographic growth 369 // DETAILED CONTENTS xv // Malnutrition and infectious disease 369 // Agriculture led to major societal changes 371 // 12.4 THE FARMING-LANGUAGE CO-DISPERSAL HYPOTHESIS 372 // Some language families have spread widely and rapidly 372 Linguistic dating and construction of protolanguages have been used to test the hypothesis 373 // What are the genetic implications of language spreads? 373 // 12.5 OUT OF THE NEAR EAST INTO EUROPE 374 // Nongenetic evidence provides dates for the European Neolithic 374 // Different models of expansion give different expectations for genetic patterns 377 // Models are oversimplifications of reality 378 // Principal component analysis of classical genetic polymorphisms was influential 379 // Interpreting synthetic maps 379 // mtDNA evidence has been controversial, but ancient DNA data are transforming the field 380 // Data from ancient mtDNA 382 //
Y-chromosomal data show strong dines in Europe 384 // New developments for the Y chromosome 384 // Biparentally inherited nuclear DNA has not yet contributed much, but important ancient DNA data are now emerging 386 // Ancient DNA data 387 // What developments will shape debate in the future? 388 // 12.6 OUT OF TROPICAL WEST AFRICA INTO SUB-EQUATORIAL AFRICA 388 // There is broad agreement on the background to African agricultural expansion 388 // Rapid spread of farming economies 389 // Bantu languages spread far and rapidly 390 // Genetic evidence is broadly consistent, though ancient DNA data are lacking 392 // Genomewide evidence 392 // Evidence from mtDNA and theY chromosome 393 // 12.7 GENETIC ANALYSIS OF DOMESTICATED // ANIMALS AND PLANTS 394 // Selective regimes had a massive impact on phenotypes and genetic diversity 395 // Key domestication changes in crops 396 // Effects on crop genetic diversity 398 // Phenotypic and genetic change in animals 399 // How have the origins of domesticated plants been identified? 400 // How have the origins of domesticated animals been identified? 401 // Cattle domestication 403 // SUMMARY 404 // QUESTIONS 405 // REFERENCES 405 //
CHAPTER 13 INTO NEW FOUND LANDS 409 // 13.1 SETTLEMENT OF THE NEW TERRITORIES 409 // Sea levels have changed since the out-of-Africa migration 409 // What drives new settlement of uninhabited lands? 411 // 13.2 PEOPLING OF THE AMERICAS 412 // The changing environment has provided several opportunities for the peopling of the New World 413 // Fossil and archaeological evidence provide a range of dates for the settlement of the New World 415 // Fossils 415 // Archaeological remains 416 // Clovis and the Paleoindians 416 // Pre-Clovis sites 416 // Unresolved issues 417 // Did the first settlers go extinct? 418 // A three-migration hypothesis has been suggested on linguistic grounds 419 // Genetic evidence has been used to test the single-and the three-wave migration scenarios 419 // Mitochondrial DNA evidence 420 // Interpretation of the mtDNA data 422 // Evidence from the Ychromosome 422 // Evidence from the autosomes 424 // Conclusions from the genetic data 425 // 13.3 PEOPLING OF THE PACIFIC 425 // Fossil and archaeological evidence suggest that Remote Oceania was settled more recently than Near Oceania 427 Two groups of languages are spoken in Oceania 428 // Several models have been proposed to explain the spread of Austronesian speakers 430 // Austronesian dispersal models have been tested with genetic evidence 431 // Classical polymorphisms 431 // Globin gene mutations 432 // Mitochondrial DNA 433 // TheY chromosome 436 // Autosomal evidence 437 // Evidence from other species has been used to test the Austronesian dispersal models 438 // SUMMARY 440 // QUESTIONS 441 // REFERENCES 441 //
CHAPTER 14 WHAT HAPPENS WHEN POPULATIONS MEET 443 // 14.1 WHAT IS GENETIC ADMIXTURE? 443 // Admixture has distinct effects on genetic diversity 445 // 14.2 THE IMPACT OF ADMIXTURE 447 // Different sources of evidencecan inform us about admixture 447 // Consequences of admixture for language 447 // Archaeological evidence for admixture 448 // The biological impact of admixture 449 // 14.3 DETECTING ADMIXTURE 450 // Methods based on allele frequency can be used to detect admixture 450 // Admixture proportions vary among individuals and populations 453 // Calculating individual admixture levels using multiple loci 453 // Calculating individual admixture levels using genomewide data 454 // Calculating admixture levels from estimated ancestry components 456 // Problems of measuring admixture 457 // Natural selection can affect the admixture proportions of individual genes 458 // 14.4 LOCAL ADMIXTURE AND LINKAGE DISEQUILIBRIUM 460 // How does admixture generate linkage disequilibrium? 461 // Admixture mapping 462 // Admixture dating 463 // 14.5 SEX-BIASED ADMIXTURE 464 // What is sex-biased admixture? 464 // Detecting sex-biased admixture 465 // Sex-biased admixture resulting from directional mating 465 // The effect of admixture on our genealogical ancestry 467 // 14.6 TRANSNATIONAL ISOLATES 467 // Roma and Jews are examples of widely spread transnational isolates 468 // European Roma 468 // The Jews 469 // SUMMARY 471 // QUESTIONS 472 // REFERENCES 473 // CHAPTER 15 UNDERSTANDING THE PAST, PRESENT, AND FUTURE OF PHENOTYPIC VARIATION 477 // 15.1 NORMAL AND PATHOGENIC VARIATION IN AN EVOLUTIONARY CONTEXT 477 //
15.2 KNOWN VARIATION IN HUMAN PHENOTYPES 478 // What is known about human phenotypic variation? 478 // Morphology and temperature adaptation 479 // Facial features 479 // Tooth morphology and cranial proportions 480 // Behavioral differences 481 // How do we uncover genotypes underlying phenotypes? 483 // What have we discovered about genotypes underlying phenotypes? 485 // 15.3 SKIN PIGMENTATION AS AN ADAPTATION TO ULTRAVIOLET LIGHT // Melanin is the most important pigment influencing skin color // Variable ultraviolet light exposure is an adaptive explanation for skin color variation Several genes that affect human pigmentation are known // Genetic variation in human pigmentation genes is consistent with natural selection Does sexual selection have a role in human phenotypic variation? // 15.4 LIFE AT HIGH ALTITUDE AND ADAPTATION TO HYPOXIA // Natural selection has influenced the overproduction of red blood cells // High-altitude populations differ in their adaptation to altitude // 15.5 VARIATION IN THE SENSE OF TASTE // Variation in tasting phenylthiocarbamide is mostly due to alleles of the TAS2R38 gene There is extensive diversity of bitter taste receptors in humans // Sweet, umami, and sour tastes may show genetic polymorphism // 15.6 ADAPTING TO A CHANGING DIET BY DIGESTING MILK AND STARCH // There are several adaptive hypotheses to explain lactase persistence // Lactase persistence is caused by SNPs within an enhancer of the lactase gene Increased copy number of the amylase gene reflects an adaptation to a high-starch diet //
15.7 THE FUTURE OF HUMAN EVOLUTION // Have we stopped evolving? // Natural selection acts on modern humans // Can we predict the role of natural selection in the // future? // Climate change Dietary change Infectious disease // What will be the effects of future demographic changes? // Increasing population size Increased mobility Differential fertility Differential generation time Will the mutation rate change? // SUMMARY // QUESTIONS // REFERENCES // CHAPTER 16 EVOLUTIONARY INSIGHTS INTO SIMPLE GENETIC DISEASES 517 // 16.1 GENETIC DISEASE AND MUTATION—SELECTION BALANCE 520 // Variation in the strength of purifying selection can affect incidence of genetic disease 520 // Variation in the deleterious mutation rate can affect incidence of genetic disease 522 // 16.2 GENETIC DRIFT, FOUNDER EFFECTS, AND CONSANGUINITY 523 // Jewish populations have a particular disease heritage 524 // Finns have a disease heritage very distinct from // other Europeans 525 // Consanguinity can lead to increased rates of // genetic disease 526 // 16.3 EVOLUTIONARY CAUSES OF GENOMIC DISORDERS 526 // Segmental duplications allow genomic // rearrangements with disease consequences 527 // Duplications accumulated in ancestral primates 529 //
16.4 GENETIC DISEASES AND SELECTION BY MALARIA 529 // Sickle-cell anemia is frequent in certain populations // due to balancing selection 531 // a-Thalassemias are frequent in certain populations // due to balancing selection 534 // Glucose-6-phosphate dehydrogenase deficiency // alleles are maintained at high frequency in // malaria-endemic populations 535 // What can these examples tell us about natural // selection? 537 // SUMMARY 538 // QUESTIONS 538 // REFERENCES 539 // CHAPTER 17 EVOLUTION AND COMPLEX DISEASES 541 // 17.1 DEFINING COMPLEX DISEASE 541 // The genetic contribution to variation in disease risk varies between diseases 544 // Infectious diseases are complex diseases 544 // 17.2 THE GLOBAL DISTRIBUTION OF COMPLEX DISEASES 546 Is diabetes a consequence of a post-agricultural // change in diet? 546 // The drifty gene hypothesis 547 // Evidence from genomewide studies 548 // The thrifty phenotype hypothesis 549 // 17.3 IDENTIFYING ALLELES INVOLVED IN COMPLEX DISEASE 549 // Genetic association studies are more powerful than linkage studies for detecting small genetic effects 549 // Candidate gene association studies have not generally been successful in identifying susceptibility alleles for complex disease 552 // Genomewide association studies can reliably identify susceptibility alleles to complex disease 552 // GWAS data have been used for evolutionary genetic analysis 556 //
17.4 WHAT COMPLEX DISEASE ALLELES DO WE EXPECT // TO FIND IN THE POPULATION? 557 // Negative selection acts on disease susceptibility alleles 557 // Positive selection acts on disease resistance alleles 560 // Severe sepsis and CASPI2 560 // Malaria and the Duffy antigen 560 // HIV-1 and CCR5A32 562 // Unexpectedly, some disease susceptibility alleles with large effects are observed at high frequency 562 // Susceptibility to kidney disease, APOL1, and resistance to sleeping sickness 562 // Implications for other GWAS results 563 // 17.5 GENETIC INFLUENCE ON VARIABLE RESPONSE // TO DRUGS 563 // Population differences in drug-response genes exist, but are not well understood 564 // SUMMARY 567 // QUESTIONS 568 // REFERENCES 569 // CHAPTER 18 IDENTITY AND IDENTIFICATION 571 // 18.1 INDIVIDUAL IDENTIFICATION 572 // The first DNA fingerprinting and profiling methods relied on minisatellites 573 // PCR-based microsatellite profiling superseded minisatellite analysis 574 // How do we interpret matching DNA profiles? 574 // Complications from related individuals, and DNA mixtures 576 Large forensic identification databases are powerful tools in crime-fighting 577 // Controversial aspects of identification databases 577 // The Y chromosome and mtDNA are useful in specialized cases 578 // Ychromosomes in individual identification 579 // mtDNA in individual identification 580 // 18.2 WHAT DNA CAN TELL US ABOUT JOHN OR // JANE DOE 580 // DNA-based sex testing is widely used and generally reliable 580 // Sexreversal 581 // Deletions oflheAMELY locus in normal males 582 // Some other phenotypic characteristics are predictable from DNA 582 //
Reliability of predicting population of origin depends on what DNA variants are analyzed 583 // Prediction from forensic microsatellite multiplexes 583 // Prediction from other systems 584 // The problem of admixed populations 584 // 18.3 DEDUCING FAMILY AND GENEALOGICAL RELATIONSHIPS 585 // The probability of paternity can be estimated confidently 586 // Other aspects of kinship analysis 588 // The Y chromosome and mtDNA are useful in genealogical studies 588 // The Thomas Jefferson paternity case 588 // DNA-based identification of the Romanovs 590 // Y-chromosomal DNA has been used to trace // modern diasporas 591 // Y-chromosomal haplotypes tend to correlate with patrilineal surnames 592 // 18.4 THE PERSONAL GENOMICS REVOLUTION 593 // The first personal genetic analysis involved the Y chromosome and mtDNA 593 // Personal genomewide SNP analysis is used for ancestry and health testing 593 // Personal genome sequencing provides the ultimate resolution // Personal genomics offers both promise and // problems 596 // SUMMARY 597 // QUESTIONS 597 // REFERENCES 598 // What genes are encoded within the mitochondrial genome? // What diseases are caused by mutations within mtDNA? // How has the study of mtDNA diversity developed? How is information from the mtDNA variants in an individual combined? // Why are all the deep-rooting dades called L? // Why is mtDNA so useful for exploring the human past? // What about possible selection pressures? //
THEY CHROMOSOME // How has it evolved? // What does the chromosome contain? // How similar are Y chromosomes within and between species? // What molecular polymorphisms are found on the // Y chromosome? // How should the polymorphic information from different variants be combined? // What are the applications of studying Y-chromosomal diversity? // Is there any evidence of selection on the // Y chromosome? // 593 REFERENCES // GLOSSARY INDEX // APPENDIX // HAPLOGR0UP NOMENCLATURE THE MITOCHONDRIAL GENOME // What are its origins?

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