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Libri sul tema "Linkage disequilibrium"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 6 luglio 2024

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1

Andrew, Collins R. Linkage Disequilibrium and Association Mapping. New Jersey: Humana Press, 2007. http://dx.doi.org/10.1385/1597453897.

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2

Collins, Andrew R., a cura di. Linkage Disequilibrium and Association Mapping. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-389-9.

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3

Collins, Andrew R. Linkage Disequilibrium and Association Mapping. Gardners Books, 2010.

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4

A, Collins, a cura di. Linkage disequilibrium and association mapping: Analysis and applications. Totowa, N.J: Humana Press, 2007.

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5

Linkage disequilibrium and association mapping: Analysis and applications. Totowa, NJ: Humana Press, 2008.

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6

Xie, Fang. Simultaneous detection of linkage and linkage disequilibrium for families with an affected sib-pair. 2003.

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7

Collins, Andrew R. Linkage Disequilibrium and Association Mapping: Analysis and Applications (Methods in Molecular Biology). Humana Press, 2007.

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8

Walsh, Bruce, e Michael Lynch. Short-term Changes in the Variance: 1. Changes in the Additive Variance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0016.

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Abstract (sommario):

Selection changes the additive-genetic variance (and hence the response in the mean) by both changing allele frequencies and by generating correlations among alleles at different loci (linkage disequilibrium). Such selection-induced correlations can be generated even between unlinked loci, and (generally) are negative, such that alleles increasing trait values tend to become increasingly negative correlated under direction or stabilizing selection, and positively correlated under disruptive selection. Such changes in the additive-genetic variance from disequilibrium is called the Bulmer effects. For a large number of loci, the amount of change can be predicted from the Bulmer equation, the analog of the breeder's equation, but now for the change in the variance. Upon cessation of selection, any disequilibrium decays away, and the variances revert back to their additive-genic variances (the additive variance in the absence of disequilibrium). Assortative mating also generates such disequilibrium.

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9

Walsh, Bruce, e Michael Lynch. Selection Under Inbreeding. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0023.

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When dominance is presence, the selection response equations under inbreeding can become rather complex, they require additional variance components beyond the additive-genetic variance. Further, both transient and permanent components of response can arise. This chapter examines the theory of both the covariance of relatives under general inbreeding, as well as the expected selection response under inbreeding. Due to the decrease in the effective recombination rate under selfing, the Bulmer effect can be rather dramatic, as any linkage disequilibrium generated by selection is only weakly removed by recombination. Finally, this chapter also examines the evolutionary forces that interact to determine the selfing rate for a given population.

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10

Walsh, Bruce, e Michael Lynch. Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0019.

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When the full pedigree of individuals whose values (records) were used in the selection decisions during an experiment (or breeding program) is known, LS analysis can be replaced by mixed models and their Bayesian extensions. In this setting, REML can be used to estimate genetic variances and BLUP can be used to estimate the mean breeding value in any given generation. The latter allows for genetic trends to be separated from environmental trends without the need for a control population. Under the infinitesimal model setting (wherein selection-induced allele-frequency changes are small during the course of the experiment), the use of the relationship matrix in a BLUP analysis accounts for drift, nonrandom mating, and linkage disequilibrium.

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11

Walsh, Bruce, e Michael Lynch. The Infinitesimal Model and Its Extensions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0024.

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Abstract (sommario):

One standard approximation in quantitative genetics is the infinitesimal model, which assumes a large number of loci, each of small effect. In such a setting, the distribution of breeding values in unselected descendants is roughly multivariate normal and most of the (short-term) change in the additive variance under selection is through Bulmer effects (the generation of linkage disequilibrium) rather than by allele-frequency change. A variety of different infinitesimal models are found in the literature, and this chapter examines these different versions and the connections between them. It also examines the theory for moving beyond the infinitesimal approximation. Finally, this chapter shows that the much-debated worry over “missing heritability” simply follows under the infinitesimal setting.

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12

Kan, Carol, e Ma-Li Wong. Genetics. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198789284.003.0004.

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An association between type 2 diabetes mellitus (T2DM) and depression has been reported in epidemiological studies. Finding a genetic overlap between T2DM and depression will provide evidence to support a common biological pathway to both disorders. Genetic correlations observed from twin studies indicate that a small magnitude of the variance in liability can be attributed to genetic factors. However, no genetic overlap has been observed between T2DM and depression in genome-wide association studies using both the polygenic score and the linkage disequilibrium score regression approaches. Clarifying the shared heritability between these two complex traits is an important next step towards better therapy and treatment. Another area that needs to be explored is gene–environment interaction, since genotypes can affect an individual’s responses to the environment and environment can differentially affect genotypes expression.

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13

Walsh, Bruce, e 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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Abstract (sommario):

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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14

Purcell, Shaun M. Genetic Methodologies and Applications. A cura di Dennis S. Charney, Eric J. Nestler, Pamela Sklar e Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0001.

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Abstract (sommario):

Mental illness is highly heritable, yet it has been difficult historically to identify the specific genes that comprise that risk. This difficulty resides in the fact that the genetic risk for all common mental disorders is polygenic, with perhaps hundreds of genetic variations, each of small effect, contributing to the overall risk. Despite these challenges, the field has made dramatic advances over the past decade in beginning to understand the genetic basis of mental illness. This chapter provides an overview of the experimental approaches used, beginning with epidemiology and population genetics to define the heritability of an illness, to classic studies of large families and linkage disequilibrium analysis, to genome-wide investigations including genome-wide association studies (GWAS), exome sequencing, and whole genome sequencing. Increasingly, these genetic advances are being understood within the biological context of disease pathophysiology.

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15

Walsh, Bruce, e 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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Abstract (sommario):

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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