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Books on the topic 'Haplotypes'

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Author: Grafiati

Published: 4 June 2021

Last updated: 3 March 2023

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1

New mathematical methods in human gene mapping. [New York]: [Columbia University], 1993.

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2

Perry, Claire Louise. A search for novel MHC-encoded IDDM susceptibility genes using oriental haplotypes. Birmingham: University of Birmingham, 1997.

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3

Iliadis, Alexandros. Haplotype Inference through Sequential Monte Carlo. [New York, N.Y.?]: [publisher not identified], 2013.

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4

Istrail, Sorin, Michael Waterman, and Andrew Clark, eds. Computational Methods for SNPs and Haplotype Inference. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/b96286.

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5

Pound, Michelle C. Deletion screening and haplotype analysis in the Fraxe region at Xq28. [Portsmouth]: [University of Portsmouth], 2000.

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6

Svensson, Ann-Cathrin. Molecular analyses of human endogenous retrovirus ERV9: Marker for HLA-DR haplotype evolution. Uppsala: Sveriges Lantbruksuniversitet, 1996.

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7

Sorin, Istrail, Waterman Michael S, and Clark Andrew G. 1954-, eds. Computational methods for SNPs and Haplotype inference: DIMACS/RECOMB satellite workshop, Piscataway, NJ, USA, November 21-22, 2002 : revised papers. Berlin: Springer-Verlag, 2004.

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8

Kay, Chris, Emily Fisher, and Michael R. Hayden. Epidemiology. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199929146.003.0007.

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The prevalence and persistence of Huntington’s disease (HD) is crucially informed by the causative mutation. Diagnostic and predictive testing has enabled a new era of epidemiologic study of HD, whereby only those who carry an expanded CAG repeat are included in such measures. In Western populations, estimated prevalence of the disease is higher following the introduction of genetic testing, and prevalence may also be increasing in absolute terms. There are worldwide differences in the prevalence of HD by ethnicity and population, which may be accounted for in part by genetic diversity of the CAG repeat and the surrounding haplotype. HD is endemic to all populations, but is most common in populations of European ancestry in which specific disease haplotypes are found. New mutations maintain HD in a population, and genetic differences by population may contribute to differences in the de novo mutation rate.

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9

Morell-Ducos, Fausto. COMT and morphine use in cancer pain. Edited by Paul Farquhar-Smith, Pierre Beaulieu, and Sian Jagger. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198834359.003.0082.

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The landmark paper discussed in this chapter is ‘Genetic variation in the catechol-O-methyltransferase (COMT) gene and morphine requirements in cancer patients with pain’, published by Rakvåg et al. in 2008. Genetic variation contributes to differences in pain sensitivity and response to analgesics. Catecholamines are involved in the modulation of pain and are metabolized by catchol-O-methyltransferase (COMT). Genetic variability in the COMT gene may therefore contribute to differences in pain sensitivity and response to analgesics. It has been shown that a polymorphism in the COMT gene, Rs4680 (val158met), influences pain sensitivity and efficacy for morphine in cancer pain treatment. This study investigated whether the variability in other regions in the COMT gene also contributes to the inter-individual variability of morphine efficacy by mapping 11 single nucleotide polymorphisms, constructing haplotypes from them, and then comparing genotypes and haplotypes against pharmacological, demographic, and patient symptom measurements in patients receiving morphine for cancer pain.

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10

Mészáros, Gábor, Marco Milanesi, Paolo Ajmone Marsan, and Yuri Tani Utsunomiya, eds. Haplotype Analysis Applied to Livestock Genomics. Frontiers Media SA, 2021. http://dx.doi.org/10.3389/978-2-88966-968-4.

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11

(Editor), Sorin Istrail, Michael Waterman (Editor), and Andrew Clark (Editor), eds. Computational Methods for SNPs and Haplotype Inference. Springer, 2004.

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12

Lewis, Myles, and Tim Vyse. Genetics of connective tissue diseases. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0042.

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The advent of genome-wide association studies (GWAS) has been an exciting breakthrough in our understanding of the genetic aetiology of autoimmune diseases. Substantial overlap has been found in susceptibility genes across multiple diseases, from connective tissue diseases and rheumatoid arthritis (RA) to inflammatory bowel disease, coeliac disease, and psoriasis. Major technological advances now permit genotyping of millions of single nucleotide polymorphisms (SNPs). Group analysis of SNPs by haplotypes, aided by completion of the Hapmap project, has improved our ability to pinpoint causal genetic variants. International collaboration to pool large-scale cohorts of patients has enabled GWAS in systemic lupus erythematosus (SLE), systemic sclerosis and Behçet's disease, with studies in progress for ANCA-associated vasculitis. These 'hypothesis-free' studies have revealed many novel disease-associated genes. In both SLE and systemic sclerosis, identified genes map to known pathways including antigen presentation (MHC, TNFSF4), autoreactivity of B and T lymphocytes (BLK, BANK1), type I interferon production (STAT4, IRF5) and the NFκ‎B pathway (TNIP1). In SLE alone, additional genes appear to be involved in dysregulated apoptotic cell clearance (ITGAM, TREX1, C1q, C4) and recognition of immune complexes (FCGR2A, FCGR3B). Future developments include whole-genome sequencing to identify rare variants, and efforts to understand functional consequences of susceptibility genes. Putative environmental triggers for connective tissue diseases include infectious agents, especially Epstein-Barr virus; cigarette smoking; occupational exposure to toxins including silica; and low vitamin D, due to its immunomodulatory effects. Despite numerous studies looking at toxin exposure and connective tissue diseases, conclusive evidence is lacking, due to either rarity of exposure or rarity of disease.

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13

The structure of haplotype blocks in the human genome. 2002.

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14

Sun, Shuying. Haplotype inference using a hidden Markov model with efficient Markov chain sampling. 2007, 2007.

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15

Waterman, Michael, Clark Andrew, and Sorin Istrail. Computational Methods for SNPs and Haplotype Inference: DIMACS/RECOMB Satellite Workshop, Piscataway, NJ, USA, November 21-22, 2002, Revised Papers. Springer London, Limited, 2004.

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16

Walsh, Bruce, and Michael Lynch. Using Molecular Data to Detect Selection: Signatures from Recent Single Events. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0009.

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Different types and phases of a selective sweep (hard, soft, partial, polygenic) generate different patterns of departures from neutrality, and hence require different tests. It is thus not surprising that a large number of tests have been proposed that use sequence information to detect ongoing, or very-recently completed, episodes of selection. This chapter critically reviews over 50 such tests, which use information on allele-frequency change, linkage disequilibrium patterns, spatial allele-frequency patterns, site-frequency spectrum data, allele-frequency spectrum data, and haplotype structure. This chapter discusses the domain of applicability for each test, and their strengths and weaknesses. Finally, this chapter examines application of these methods in the search for recent, or ongoing, selection in humans and for genes involved in the domestication process in plants and animals.

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17

Crawford, Michael, and Rohina C. Rubicz. Molecular Genetic Evidence from Contemporary Populations for the Origins of Native North Americans. Edited by Max Friesen and Owen Mason. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199766956.013.4.

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An overview of the current molecular genetic evidence for the origins of North American populations is presented, including specific examples from the authors’ work with the Aleutian Island inhabitants. Shared mitochondrial DNA and Y-chromosome DNA markers among Siberians and Native Americans point to a Pleistocene migration from Siberia into the Americas via Beringia. There was likely a later migration from Siberia to Alaska, based on the analysis of whole-genome sequence data from a Greenland Paleoeskimo that clusters this individual with Siberian populations. Coalescence date estimates for Native American mitochondrial DNA and Y-chromosome DNA haplogroups indicate that there was a population expansion approximately 15,000–18,000 that was associated with a pre-Clovis settlement of the Americas and coastal migration, and then a later expansion of circum-Arctic populations. Settlement of the Aleutian Archipelago took place via east-to-west migration of Aleut kin groups, accompanied by a clinal loss in mitochondrial DNA haplotype diversity.

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