Estimating heritability using family-pooled phenotypic and genotypic data: a simulation study applied to aquaculture

Khalilisamani, Nima; Thomson, Peter; Raadsma, Herman W.; Khatkar, Mehar S.

doi:10.1038/s41437-022-00502-8

Cited by 3 publications

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References 25 publications

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“…In breeding programs and predicting response to selection, the accurate estimation of heritability and other genetic parameters is of particular importance ( Falconer and Mackay, 1996 ). The parameters are estimated using either pedigree or genomic information ( Khalilisamani et al, 2022 ). To date, the use of pedigree for estimating the genetic parameter of quantitative traits has been widely used in various studies ( Sasaki et al, 2006 ; Hoque et al, 2009 ; Takeda et al, 2018 ).…”

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confidence: 99%

Genomic heritability and correlation between carcass traits in Japanese Black cattle evaluated under different ceilings of relatedness among individuals

Mahdabi

Tian

et al. 2023

Front. Genet.

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The investigation of carcass traits to produce meat with high efficiency has been in focus on Japanese Black cattle since 1972. To implement a successful breeding program in carcass production, a comprehensive understanding of genetic characteristics and relationships between the traits is of paramount importance. In this study, genomic heritability and genomic correlation between carcass traits, including carcass weight (CW), rib eye area (REA), rib thickness (RT), subcutaneous fat thickness (SFT), yield rate (YI), and beef marbling score (BMS) were estimated using the genomic data of 9,850 Japanese Black cattle (4,142 heifers and 5,708 steers). In addition, we investigated the effect of genetic relatedness degree on the estimation of genetic parameters of carcass traits in sub-populations created based on different GRM-cutoff values. Genome-based restricted maximum likelihood (GREML) analysis was applied to estimate genetic parameters. Using all animal data, the heritability values for carcass traits were estimated as moderate to relatively high magnitude, ranging from 0.338 to 0.509 with standard errors, ranging from 0.014 to 0.015. The genetic correlations were obtained low and negative between SFT and REA [−0.198 (0.034)] and between SFT and BMS [−0.096 (0.033)] traits, and high and negative between SFT and YI [−0.634 (0.022)]. REA trait was genetically highly correlated with YI and BMS [0.811 (0.012) and 0.625 (0.022), respectively]. In sub-populations created based on the genetic-relatedness ceiling, the heritability estimates ranged from 0.212 (0.131) to 0.647 (0.066). At the genetic-relatedness ceiling of 0.15, the correlation values between most traits with low genomic correlation were overestimated while the correlations between the traits with relatively moderate to high correlations, ranging from 0.380 to 0.811, were underestimated. The values were steady at the ceilings of 0.30–0.95 (sample size of 5,443–9,850) for most of the highly correlated traits. The results demonstrated that there is considerable genetic variation and also favorable genomic correlations between carcass traits. Therefore, the genetic improvement for the traits can be simultaneously attained through genomic selection. In addition, we observed that depending on the degree of relationship between individuals and sample size, the genomic heritability and correlation estimates for carcass traits may be different.

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