Best Linear Unbiased Estimation and Prediction under a Selection Model

Henderson, Charles

doi:10.2307/2529430

Cited by 1,844 publications

(1,447 citation statements)

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“…11,12 Originally applied to animal and plant breeding, 13,14 LMMs have become a powerful method to estimate SNP-based heritability using GWAS data. 15,16 By assuming a common distribution that describes the allelic effects at all SNPs and focusing on the aggregated genetic effects rather than individual genetic effects, LMMs and BLUP are particularly attractive for modeling polygenic architecture.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations

Coram

Fang

Candille

et al. 2017

The American Journal of Human Genetics

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An essential component of precision medicine is the ability to predict an individual's risk of disease based on genetic and non-genetic factors. For complex traits and diseases, assessing the risk due to genetic factors is challenging because it requires knowledge of both the identity of variants that influence the trait and their corresponding allelic effects. Although the set of risk variants and their allelic effects may vary between populations, a large proportion of these variants were identified based on studies in populations of European descent. Heterogeneity in genetic architecture underlying complex traits and diseases, while broadly acknowledged, remains poorly characterized. Ignoring such heterogeneity likely reduces predictive accuracy for minority individuals. In this study, we propose an approach, called XP-BLUP, which ameliorates this ethnic disparity by combining trans-ethnic and ethnic-specific information. We build a polygenic model for complex traits that distinguishes candidate trait-relevant variants from the rest of the genome. The set of candidate variants are selected based on studies in any human population, yet the allelic effects are evaluated in a population-specific fashion. Simulation studies and real data analyses demonstrate that XP-BLUP adaptively utilizes trans-ethnic information and can substantially improve predictive accuracy in minority populations. At the same time, our study highlights the importance of the continued expansion of minority cohorts.

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Section: Introductionmentioning

confidence: 99%

Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations

Coram

Fang

Candille

et al. 2017

The American Journal of Human Genetics

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“…contributions or proportions of total offspring left by each candidate), g the vector of BLUP-EBVs (or the best estimate available of breeding values) of the candidates, A is the additive genetic relationship matrix (e.g. Henderson, 1975), C 5 F 1 (12F ) DF with F being the current level of inbreeding and DF being the desired rate of inbreeding, Q is a known incidence matrix for sex and 1 is a vector of ones of order 2. The first inequality ensures that the constraint on DF is met (note that, with fully random union of gametes, 1 2 c 0 Ac is the Genetic management of populations inbreeding coefficient of the next generation), whereas the second inequality ensures that half of the contributions come from males and half from females.…”

Section: Selection With Optimal Contributionsmentioning

confidence: 99%

Management of genetic diversity in small farm animal populations

Fernández

Meuwissen

Toro

et al. 2011

Animal

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Many local breeds of farm animals have small populations and, consequently, are highly endangered. The correct genetic management of such populations is crucial for their survival. Managing an animal population involves two steps: first, the individuals who will be permitted to leave descendants are to be chosen and the number offspring they will be permitted to produce has to be determined; second, the mating scheme has to be identified. Strategies dealing with the first step are directed towards the maximisation of effective population size and, therefore, act jointly on the reduction in the loss of genetic variation and in the increase of inbreeding. In this paper, the most relevant methods are summarised, including the so-called 'Optimum Contribution' methodology (contributions are proportional to the coancestry of each individual with the rest), which has been shown to be the best. Typically, this method is applied to pedigree information, but molecular marker data can be used to complete or replace the genealogy. When the population is subjected to explicit selection on any trait, the above methodology can be used by balancing the response to selection and the increase in coancestry/inbreeding. Different mating strategies also exist. Some of the mating schemes try to reduce the level of inbreeding in the short term by preventing mating between relatives. Others involve regular (circular) schemes that imply higher levels of inbreeding within populations in the short term, but demonstrate better performance in the long term. In addition, other tools such as cryopreservation and reproductive techniques aid in the management of small populations. In the future, genomic marker panels may replace the pedigree information in measuring the coancestry. The paper also includes the results of several experiments and field studies on the effectiveness and on the consequences of the use of the different strategies.

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“…When the offspring has received a recombinant marker haplotype a new gametic QTL effect was defined as the average of both gametes of the parent animal. Treating these two gametes as parents of the new gamete allows to set up a pedigree of gametic effects and to compute the conditional gametic relationship matrix and its inverse simply by applying the Henderson rules [7,8]. The condensing algorithm will, of course, lead to identical results, if desired: sire-and dam-blocks of progeny with non-recombinant parental haplotypes have to carry zeros and ones only, and in the recombinant case the corresponding sire-and dam-blocks are assembled by fifty-percent transition probabilities as in the case without markers.…”

Section: Discussionmentioning

confidence: 99%

Identification of gametes and treatment of linear dependencies in the gametic QTL-relationship matrix and its inverse

2004

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-The estimation of gametic effects via marker-assisted BLUP requires the inverse of the conditional gametic relationship matrix G. Both gametes of each animal can either be identified (distinguished) by markers or by parental origin. By example, it was shown that the conditional gametic relationship matrix is not unique but depends on the mode of gamete identification. The sum of both gametic effects of each animal -and therefore its estimated breeding value -remains however unaffected. A previously known algorithm for setting up the inverse of G was generalized in order to eliminate the dependencies between columns and rows of G. In the presence of dependencies the rank of G also depends on the mode of gamete identification. A unique transformation of estimates of QTL genotypic effects into QTL gametic effects was proven to be impossible. The properties of both modes of gamete identification in the fields of application are discussed. marker assisted selection / best linear unbiased prediction / linkage analysis / gametic relationship matrix

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Best Linear Unbiased Estimation and Prediction under a Selection Model

Cited by 1,844 publications

References 1 publication

Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations

Leveraging Multi-ethnic Evidence for Risk Assessment of Quantitative Traits in Minority Populations

Management of genetic diversity in small farm animal populations

Identification of gametes and treatment of linear dependencies in the gametic QTL-relationship matrix and its inverse

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