Heritability for growth traits in giant freshwater prawn, Macrobrachium rosenbergii (de Mann 1879) based on best linear unbiased prediction methodology

Genomic selection study (GS) focusing on nonadditive genetic effects of dominance and the first order of epistatic effects, in a full-sib family population of 695 Scots pine (Pinus sylvestris L.) trees, was undertaken for growth and wood quality traits, using 6,344 single nucleotide polymorphism markers (SNPs) generated by genotyping-by-sequencing (GBS). Genomic marker-based relationship matrices offer more effective modeling of nonadditive genetic effects than pedigree-based models, thus increasing the knowledge on the relevance of dominance and epistatic variation in forest tree breeding. Genomic marker-based models were compared with pedigree-based models showing a considerable dominance and epistatic variation for growth traits. Nonadditive genetic variation of epistatic nature (additive × additive) was detected for growth traits, wood density (DEN), and modulus of elasticity (MOEd) representing between 2.27 and 34.5% of the total phenotypic variance. Including dominance variance in pedigree-based Best Linear Unbiased Prediction (PBLUP) and epistatic variance in genomic-based Best Linear Unbiased Prediction (GBLUP) resulted in decreased narrow-sense heritability and increased broad-sense heritability for growth traits, DEN and MOEd. Higher genetic gains were reached with early GS based on total genetic values, than with conventional pedigree selection for a selection intensity of 1%. This study indicates that nonadditive genetic variance may have a significant role in the variation of selection traits of Scots pine, thus clonal deployment could be an attractive alternative for the species. Additionally, confidence in the role of nonadditive genetic effects in this breeding program should be pursued in the future, using GS.

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Genetic association among feeding behavior, feed efficiency, and growth traits in growing indicine cattle

Journal of Animal Science ◽

10.1093/jas/skaa350 ◽

2020 ◽

Vol 98 (11) ◽

Author(s):

Lorena Ferreira Benfica ◽

Leandro Sannomiya Sakamoto ◽

Ana Fabrícia Braga Magalhães ◽

Matheus Henrique Vargas de Oliveira ◽

Lúcia Galvão de Albuquerque ◽

...

Keyword(s):

Feeding Behavior ◽

Genetic Gain ◽

Feed Efficiency ◽

Growth Traits ◽

Genetic Correlations ◽

Best Linear Unbiased Prediction ◽

Likelihood Method ◽

Linear Unbiased Prediction ◽

Best Linear Unbiased ◽

Unbiased Prediction

Abstract This study aimed to estimate genetic parameters, including genomic data, for feeding behavior, feed efficiency, and growth traits in Nellore cattle. The following feeding behavior traits were studied (861 animals with records): time spent at the feed bunk (TF), duration of one feeding event (FD), frequency of visits to the bunk (FF), feeding rate (FR), and dry matter intake (DMI) per visit (DMIv). The feed efficiency traits (1,543 animals with records) included residual feed intake (RFI), residual weight gain (RWG), and feed conversion (FC). The growth traits studied were average daily gain (ADG, n = 1,543 animals) and selection (postweaning) weight (WSel, n = 9,549 animals). The (co)variance components were estimated by the maximum restricted likelihood method, fitting animal models that did (single-step genomic best linear unbiased prediction) or did not include (best linear unbiased prediction) genomic information in two-trait analyses. The direct responses to selection were calculated for the feed efficiency traits, ADG, and WSel, as well as the correlated responses in feed efficiency and growth by direct selection for shorter TF. The estimated heritabilities were 0.51 ± 0.06, 0.35 ± 0.06, 0.27 ± 0.07, 0.34 ± 0.06, and 0.33 ± 0.06 for TF, FD, FF, FR, and DMIv, respectively. In general, TF and FD showed positive genetic correlations with all feed efficiency traits (RFI, RWG, and FC), ADG, DMI, and WSel. Additionally, TF showed high and positive genetic and phenotypic correlations with RFI (0.71 ± 0.10 and 0.46 ± 0.02, respectively) and DMI (0.56 ± 0.09 and 0.48 ± 0.03), and medium to weak genetic correlations with growth (0.32 ± 0.11 with ADG and 0.14 ± 0.09 with WSel). The results suggest that TF is a strong indicator trait of feed efficiency, which exhibits high heritability and a weak positive genetic correlation with growth. In a context of a selection index, the inclusion of TF to select animals for shorter TF may accelerate the genetic gain in feed efficiency by reducing RFI but with zero or slightly negative genetic gain in growth traits.

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Correction: Weighted Genomic Best Linear Unbiased Prediction for Carcass Traits in Hanwoo Cattle. Genes 2019, 10, 1019

Genes ◽

10.3390/genes11091013 ◽

2020 ◽

Vol 11 (9) ◽

pp. 1013

Author(s):

Bryan Irvine Lopez ◽

Seung-Hwan Lee ◽

Jong-Eun Park ◽

Dong-Hyun Shin ◽

Jae-Don Oh ◽

...

Keyword(s):

Carcass Traits ◽

Best Linear Unbiased Prediction ◽

Linear Unbiased Prediction ◽

Best Linear Unbiased ◽

Hanwoo Cattle ◽

Unbiased Prediction

The authors wish to make the following corrections to this paper [...]

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A method for reducing inbreeding with Best Linear Unbiased Prediction

Proceedings of the British Society of Animal Production (1972) ◽

10.1017/s030822960002362x ◽

1993 ◽

Vol 1993 ◽

pp. 33-33

Author(s):

B Grundy ◽

WG Hill

Keyword(s):

Best Linear Unbiased Prediction ◽

Breeding Value ◽

Best Linear Unbiased Predictor ◽

Linear Unbiased Prediction ◽

Genetic Merit ◽

Selection Decisions ◽

Best Linear Unbiased ◽

Estimated Breeding Value ◽

Commercial Environment ◽

Unbiased Prediction

An optimum way of selecting animals is through a prediction of their genetic merit (estimated breeding value, EBV), which can be achieved using a best linear unbiased predictor (BLUP) (Henderson, 1975). Selection decisions in a commercial environment, however, are rarely made solely on genetic merit but also on additional factors, an important example of which is to limit the accumulation of inbreeding. Comparison of rates of inbreeding under BLUP for a range of hentabilities highlights a trend of increasing inbreeding with decreasing heritability. It is therefore proposed that selection using a heritability which is artificially raised would yield lower rates of inbreeding than would otherwise be the case.

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