Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families

Wittenburg, Dörte; Teuscher, F.; Klosa, Jan; Reinsch, Norbert

doi:10.1534/g3.116.032409

Cited by 7 publications

(6 citation statements)

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“…We investigated two different methods for predicting the genetic variance of newly generated crosses. Method VPM, the sample variance of the GEBVs, has been used for this and similar purposes by other authors (Bernardo 2014;Segelke et al 2014;Mohammadi et al 2015;Tiede et al 2015;Wittenburg et al 2016). As VPM is known to underestimate the true genetic variance as it is based on shrunken marker effect estimates (Cole and VanRaden 2011;Lian et al 2015), we investigated its performance for obtaining accurate and precise progeny variance estimates under different training population properties.…”

Section: Discussionmentioning

confidence: 99%

Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses

Teyssèdre²,

2017

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A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs.

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Section: Discussionmentioning

confidence: 99%

Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses

Teyssèdre²,

2017

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“…sire-specific, covariance between SNP k and l of individual j is, according to Bonk et al . (2016) and Wittenburg et al . (2016), a function of maternal and paternal contribution and depends on the sire diplotype 𝒮 s .…”

Section: Supplemental Figuresmentioning

confidence: 97%

Design of Experiments for Fine-Mapping Quantitative Trait Loci in Livestock Populations

Wittenburg

Bonk

Doschoris

et al. 2019

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22Single nucleotide polymorphisms (SNPs) which capture a significant impact on 23 a trait can be identified with genome-wide association studies. High linkage disequi-24 librium (LD) among SNPs makes it difficult to identify causative variants correctly. 25Thus, often target regions instead of single SNPs are reported. Sample size has not 26 only a crucial impact on the precision of parameter estimates, it also ensures that a 27 desired level of statistical power can be reached. We study the design of experiments 28 for fine-mapping of signals of a quantitative trait locus in such a target region. 29A multi-locus model allows to identify causative variants simultaneously, to state 30 their positions more precisely and to account for existing dependencies. Based on 31 the commonly applied SNP-BLUP approach, we determine the z-score statistic for 32 locally testing non-zero SNP effects and investigate its distribution under the al-33 ternative hypothesis. This quantity employs the theoretical instead of observed 34 dependence between SNPs; it can be set up as a function of paternal and maternal 35 LD for any given population structure. 36 We simulated multiple paternal half-sib families and considered a target region of 37 1 Mbp. A bimodal distribution of estimated sample size was observed, particu-38 larly if more than two causative variants were assumed. The median of estimates 39 constituted the final proposal of optimal sample size; it was consistently less than 40 sample size estimated from single-SNP investigations which was used as a baseline 41 approach. The second mode pointed to inflated sample sizes and could be explained 42 by blocks of varying linkage phases leading to negative correlations between SNPs. 43Optimal sample size increased almost linearly with number of signals to be identified 44 but depended much stronger on the assumption on heritability. For instance, three 45 times as many samples were required if heritability was 0.1 compared to 0.3. These 46 results enable the resource-saving design of future experiments for fine-mapping of 47

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“…Another strategy that can be used is the reciprocal recurrent selection (Nasim et al 2014). The reciprocal recurrent selection strategy can be used on two ways: obtaining half-sib family (Wittenburg et al 2016) or full-sib family, and GWS can be applied for both strategies. Five steps are need to use GWS in the reciprocal recurrent selection for obtaining half-sib family in canola as described below and also in Figure 10.…”

Section: Strategies To Use Genome Wide Selection Into Traditional Canola Breedingmentioning

confidence: 99%

Breeding strategies to consolidate canola among the main crops for biofuels

et al. 2021

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Canola is a product of traditional plant breeding techniques to remove from rapeseed the antinutritional components erucic acid. This crop proves to be a promising crop due to the diverse purposes of its oil, especially by its potential for biofuel production. This paper aimed to integrate the information available in the literature and report the most promising strategies for genetic and biotechnological progress in canola. Thus, we carried out a detailed review of the origin and uses of canola, its socioeconomic importance in the global and Brazilian aspects, tropicalization, with emphasis on genetic breeding. We demonstrate the main breeding strategies that can be used to increase your oil production.We propose here a breeding strategy for canola, in which some strategies previously mentioned are integrated. The purpose of this strategy is to enhance the selection and efficiency at the beginning of a breeding program. Among these, genome wide selection (GWS) is a suitable tool to help breeders to improve the efficiency selection in a canola breeding program increasing the selection accuracy or even reducing the cycle time. The proposed strategies must be analyzed for each situation, adjusting the GWS model to obtain highest selection accuracy.

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Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families

Cited by 7 publications

References 37 publications

Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses

Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses

Design of Experiments for Fine-Mapping Quantitative Trait Loci in Livestock Populations

Breeding strategies to consolidate canola among the main crops for biofuels

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