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1

Edwards, Sara Joanne. Genetic analysis of the Treacher Collins syndrome locus. Manchester: University of Manchester, 1995.

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2

Gladwin, Amanda Jane. The molecular genetic analysis of the Treacher Collins syndrome locus. Manchester: University of Manchester, 1996.

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3

Perveen, Rahat. Genetic and physical mapping around the Treacher Collins syndrome locus. Manchester: University of Manchester, 1994.

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4

Heather, Lisa Jane. Physical and genetic mapping around a candidate locus for orofacial clefting. Manchester: University of Manchester, 1994.

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5

Plätke, Rosemarie. Die Entstehung von Supergenen in unterteilten Populationen: Ein theoretischer Ansatz anhand eines Zwei-Locus-Modells. Krefeld: Marchal und Matzenbacher, 1986.

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6

Miller, Carey S. Molecular genetic studies of the cytochrome f locus in Vicia faba L. Ottawa: National Library of Canada, 1990.

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7

Crosby, Andrew Harry. Genetic and physical mapping of the dentinogenesis imperfecta type II locus: The exclusion of three candidate genes from a causative role in the pathogenesis of this disorder. Manchester: University of Manchester, 1995.

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8

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes (Genetic Maps) (Genetic Maps). 5th ed. Cold Spring Harbor Laboratory Press, 1990.

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9

Walsh, Bruce, and Michael Lynch. The Population Genetics of Selection. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0005.

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Анотація:
This chapter examines models of one- and two-locus selection in the absence of drift and mutation. Expressions for the per-generation rate of allele-frequency change and the expected time for a specified amount of change are developed for single-locus models, and their equilibrium structure is examined for those settings where selection retains more than one allele. The presence of selection-generated linkage disequilibrium greatly complicates the extension of single-locus results to two loci, and the chapter examines some of the resulting complications. Finally, it examines the nature of selection on a locus that underlies a trait under selection, and then uses this to develop the breeder's equation for the single-generation response in a trait under selection. One important result is that the loci for a trait under stabilizing selection experience fitness underdominance, and thus trait selection removes, rather than retains, genetic variation.
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10

Iyamabo, Odianosen E. Effects of selection, recombination and plot type on phenotypic and quantitative trait locus analyses in barley (Hordeum vulgare L.). 1993.

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11

Eyre, Steve, and Jane Worthington. Genetics of rheumatoid arthritis. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0040.

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Анотація:
A range of epidemiological studies have clearly established that susceptibility to rheumatoid arthritis (RA) is determined by both genetic and environmental factors. Studies over the last five decades have used a variety of approaches to identify the genetic variants associated with disease. HLA DRB1 was the first RA susceptibility locus to be discovered and has the largest effect size. We describe current understanding of the complexities of HLA association for RA. Linkage and small-scale association studies prior to 2007 provided convincing evidence for only one more RA susceptibility locus, PTPN22. Major breakthroughs in high-throughput genotyping and systematic discovery and mapping of hundreds of thousands of single nucleotide polymorphisms (SNPs) led to large-scale genome-wide association studies used for the first time for RA in 2007. This approach has had a dramatic impact on our knowledge of the susceptibility loci for RA, such that over 60 risk variants have now been robustly identified. We present an overview of these studies and the loci that have been identified. We consider how this knowledge is contributing to a greater understanding of the aetiology and pathology of the disease and in turn how this can influence management of patients presenting with an inflammatory arthritis. We consider some of the unanswered questions and the approaches that will need to be taken to address them.
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12

Eyre, Steve, Jane Worthington, and Sebastien Viatte. Genetics of rheumatoid arthritis. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199642489.003.0040_update_003.

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Анотація:
A range of epidemiological studies have clearly established that susceptibility to rheumatoid arthritis (RA) is determined by both genetic and environmental factors. Studies over the last five decades have used a variety of approaches to identify the genetic variants associated with disease. HLA DRB1 was the first RA susceptibility locus to be discovered and has the largest effect size. We describe current understanding of the complexities of HLA association for RA. Linkage and small-scale association studies prior to 2007 provided convincing evidence for only one more RA susceptibility locus, PTPN22. Major breakthroughs in high-throughput genotyping, and systematic discovery and mapping of hundreds of thousands of single nucleotide polymorphisms (SNPs) led to large-scale genome-wide association studies used for the first time for RA in 2007. Widespread utilization of this approach has had a dramatic impact on our knowledge of the susceptibility loci for RA, such that over 100 risk variants have now been robustly identified. We present an overview of these studies and the loci that have been identified. We consider how this knowledge is contributing to a greater understanding of the aetiology and pathology of the disease, and in turn how this can influence management of patients presenting with an inflammatory arthritis. We consider some of the unanswered questions and the approaches that will need to be taken to address them.
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13

J, O'Brien Stephen, ed. Genetic maps: Locus maps of complex genomes. 5th ed. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory, 1990.

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14

Genetic maps: Locus maps of complex genomes. 6th ed. Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory, 1993.

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15

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes. 6th ed. Cold Spring Harbor Laboratory Press, 1993.

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16

J, O'Brien Stephen, and Cold Spring Harbor Laboratory, eds. Genetic maps: Locus maps of complex genomes. 5th ed. Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory, 1990.

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17

Jeter, John Mark. Molecular analysis of the nar1 locus in barley. 1987.

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18

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes : Book 6 : Plants (Genetic Maps Book 6) (Genetic Maps Book 6). 6th ed. Cold Spring Harbor Laboratory Pr, 1993.

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19

Blech-Hermoni, Yotam N. Studies on a conserved genetic locus for chronic pain. 2006.

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20

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes : Book 4 Nonhuman Vertebrates (Genetic Maps Book 4) (Genetic Maps Book 4). 6th ed. Cold Spring Harbor Laboratory Pr, 1993.

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21

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes : Book 3 : Lower Eukaryotes (Genetic Maps Book 3) (Genetic Maps Book 3). 6th ed. Cold Spring Harbor Laboratory Pr, 1993.

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22

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes : Book 2 : Bacteria, Algae, and Protozoa (Genetic Maps Book 2) (Genetic Maps Book 2). 6th ed. Cold Spring Harbor Laboratory Pr, 1993.

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23

O'Brien, Stephen J. Genetic Maps: Locus Maps of Complex Genomes : Bacteria, Algae, and Protozoa, Book 2 (Genetic Maps Book 2) (Genetic Maps Book 2). 5th ed. Cold Spring Harbor Laboratory Press, 1990.

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24

Traore, Abdoulaye. Quantitative trait locus mapping of yield and yield components in barley (Hordeum vulgare L.). 1993.

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25

Pavlus, Janice Elaine. Characterization of two lethal mutations induced by chromosomal rearrangements involving the 4f-rnp locus of Drosophila melanogaster. 1996.

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26

Price, Susan. Genetic bone and joint disease. Edited by Patrick Davey and David Sprigings. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199568741.003.0276.

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Анотація:
Genetic conditions affecting the skeleton and supporting structures are individually rare and heterogeneous. This chapter presents an approach to assessing patients with suspected skeletal dysplasia, osteogenesis imperfecta, Marfan syndrome, and Ehlers–Danlos syndrome. Skeletal dysplasias are caused by abnormalities of bone growth and modelling; the commonest non-lethal type is achondroplasia, with an incidence of 1/10 000 to 1/30 000. The typical presentation of osteogenesis imperfecta is with multiple fractures, sometimes prenatally. There may be associated short stature, bone deformity, dentogenesis imperfecta, blue sclera, and hearing loss. Most patients with osteogenesis imperfecta have mutations in COL1A1 or COL1A2. Marfan syndrome is a connective tissue disease with a pattern of symptoms related to the presence of fibrillin in tissues. Typically, affected individuals are of tall, thin stature, with long fingers and toes (arachnodactyly), a pectus deformity, and scoliosis. Between 66% and 91% of individuals with Marfan syndrome have a mutation in fibrillin-1 (FBN1; locus: 15q21). All forms of Ehlers–Danlos syndrome present with variable thinning and fragility of skin, leading to easy bruising and poor scar formation. There is skin and joint laxity. In severe forms, blood vessels and internal organs are affected.
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27

Goldman, David, Zhifeng Zhou, and Colin Hodgkinson. The Genetic Basis of Addictive Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0042.

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Анотація:
Addictive disorders are moderately to highly heritable, indicating that alleles transmitted from parents are protective, or enhance risk by whatever mechanisms. However, the inheritance of addictive disorders is complex, involving hundreds of genes and variants that are both common and rare, and that vary in effect size and context of action. Genes altering risk for addictions have been identified by pathway and candidate gene studies in humans and model organisms, and genomic approaches including genome-wide association, meiotic linkage, and sequencing. Genes responsible for shared liability to different addictive disorders have been identified, as well as genes that are relatively specific in altering risk of addiction to one agent. An impediment to overarching conclusions is that most of the heritability of addictions is unexplained at the level of gene or functional locus. However, new analytic approaches and tools have created new potentials for resolution of the “missing heritability.”
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28

Walsh, Bruce, and Michael Lynch. Neutral Evolution in One- and Two-Locus Systems. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0002.

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Анотація:
This chapter reviews the population-genetic theory of neutral alleles in finite populations, examining the probabilities and times to loss or fixation, summary statistics for molecular variation, coalescent theory (the distribution of times back to common ancestry for a sample of alleles), and both mutation-drift and mutation-drift-migration equilibrium models.
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29

Serres, F. J. De. Utilization of Mammalian Specific Locus Studies in Hazard Evaluation and Estimation of Genetic Risk. Springer, 2011.

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30

Ivakine, Evgueni. Genetic and molecular analysis of the insulin dependent diabetes 4 locus in the NOD mouse. 2004.

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31

Zhang, Yuan-Ming, Zhenyu Jia, and Jim M. Dunwell, eds. The Applications of New Multi-Locus GWAS Methodologies in the Genetic Dissection of Complex Traits. Frontiers Media SA, 2019. http://dx.doi.org/10.3389/978-2-88945-834-9.

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32

Popovic, Maja. Genetic and physical mapping of the Shwachman-Diamond syndrome locus at the pericentromeric region of chromosome 7. 2003.

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33

A Review of the Genetics of Alcoholism and a Confirmatory Study of an Acute Alcohol Withdrawal Quantitative Trait Locus in Mice. Storming Media, 1999.

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34

Poel, Sheryl Ziemin Van der. Identification of a tumor suppressor gene locus by recognition of interferon gene deletions within human chromosome band 9P22 in human leukemias and identification and isolation of sequences which recognize a previously undiscovered gene MLL, whose transcripts span the human chromosome band 11Q23 translocation breakpoint junctions in human leukemia and whose sequences share homology with the Drosophila trithorax regulatory gene. 1993.

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35

Grams, Morgan E., and Josef Coresh. Chronic kidney disease in the developed world. Edited by David J. Goldsmith. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0095.

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Анотація:
Chronic kidney disease is common, increasing in prevalence, and associated with significant morbidity and mortality. A disease of multiple and complex aetiologies, chronic kidney disease is more prevalent among elderly, hypertensive, and diabetic persons—all growing segments of the developed world. This chapter discusses trends in and determinants of chronic kidney disease prevalence, incidence, and prognosis. In addition, advances in chronic kidney disease staging and reporting as well as the discovery of a major genetic locus for hypertensive kidney disease in populations of African ancestry are examined.
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36

Aikhenvald, Alexandra Y. Polysynthetic Structures of Lowland Amazonia. Edited by Michael Fortescue, Marianne Mithun, and Nicholas Evans. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199683208.013.18.

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Lowland Amazonia is the locus of substantial linguistic diversity in terms of genetic affiliation, language structure, and numbers of languages. This chapter will focus on the distribution of types of polysynthetic patterns within Lowland Amazonia, with special attention to the spread, and the types, of noun incorporation. The highest concentration of polysynthetic languages in Amazonia is the region south of the Amazon River, spanning adjacent regions of Peru, Brazil, and Bolivia. Polysynthetic patterns can be reconstructed for the protolanguages of some families, such as Panoan, Harakmbet, and possibly Arawá. Polysynthetic patterns in Arawak family (by far the largest in terms of its geographical spread) are often due to areal diffusion. We will focus on a number of mechanisms for the development of polysynthesis in established linguistic areas, for example the Vaupés River Basin linguistic area, and on a number of established instances of intensive language contact.
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37

Cattran, Daniel C., and Heather N. Reich. Membranous glomerulonephritis. Edited by Neil Turner. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0064_update_001.

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Анотація:
It has been clear for several decades from comparison with the rodent model disease Heymann nephritis that membranous glomerulonephritis (MGN) is an immune condition in which antibodies, usually autoantibodies, bind to targets on the surface of podocytes. However, the antigen in Heymann nephritis, megalin, is not present on human podocytes. The first potential antigen was identified by studying rare examples of maternal alloimmunization, leading to congenital membranous nephropathy in the infant caused by antibodies to neutral endopeptidase. More recently, the target of autoantibody formation in most patients with primary MGN has been identified to be the phospholipase A2 receptor, PLA2R. Genome-wide association studies identify predisposing genetic loci at HLADQ and at the locus encoding the autoantigen itself. So antibodies to at least two different molecular targets can cause MGN, and it seems likely that there may be other targets in secondary types of MGN, and possibly haptenized or otherwise modified molecules are implicated in drug- and toxin-induced MGN. Once antibodies are fixed, animal models and human observations suggest that complement is involved in mediating tissue damage. However, immunoglobulin G4, not thought to fix complement, is the predominant isotype in human MGN, and the mechanisms are not fully unravelled. Podocyte injury is known to cause proteinuria. In MGN, antibody fixation or cell damage may stimulate production of extracellular matrix to account for the increased GBM thickness with ‘podocyte type’ basement membrane collagen isoforms, and ultimately cell death and glomerulosclerosis.
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38

Budimirovic, Dejan B., and Megha Subramanian. Neurobiology of Autism and Intellectual Disability. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199937837.003.0052.

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Анотація:
Fragile X syndrome (FXS) is a neurodevelopmental disorder that manifests with a range of cognitive, behavioral, and social impairments. It is a monogenetic disease caused by silencing of the FMR1 gene, in contrast to autism spectrum disorder (ASD) that is a behaviorally-defined set of complex disorders. Because ASD is a major and growing public health concern, current research is focused on identifying common therapeutic targets among patients with different molecular etiologies. Due to the prevalence of ASD in FXS and its shared neurophysiology with ASD, FXS has been extensively studied as a model for ASD. Studies in the animal models have provided breakthrough insights into the pathophysiology of FXS that have led to novel therapeutic targets for its core deficits (e.g., mGluR theory of fragile X). Yet recent clinical trials of both GABA-B agonist and mGluR5 antagonist revealed a lack of specific and sensitive outcome measures capturing the full range of improvements of patients with FXS. Recent research shows promise for the mapping of the multitude of genetic variants in ASD onto shared pathways with FXS. Nonetheless, in light of the huge level of locus heterogeneity in ASD, further effort in finding convergence in specific molecular pathways and reliable biomarkers is required in order to perform targeted treatment trials with sufficient sample size. This chapter focuses on the neurobehavioral phenotype caused by a full-mutation of the FMR1 gene, namely FXS, and the neurobiology of this disorder of relevance to the targeted molecular treatments of its core symptoms.
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39

(Editor), T. Kumazawa, L. Kruger (Editor), and K. Mizumura (Editor), eds. The Polymodal Receptor - A Gateway to Pathological Pain (Progress in Brain Research). Elsevier Science, 1996.

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40

Takao, Kumazawa, Kruger Lawrence, and Mizumura Kazue, eds. The polymodal receptor: A gateway to pathological pain. Amsterdam: Elsevier, 1996.

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