GCA: an R package for genetic connectedness analysis using pedigree and genomic data

Hyeong-keun, Yu; Morota, Gota

doi:10.1186/s12864-021-07414-7

Cited by 3 publications

(3 citation statements)

References 20 publications

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“…The VED is based on the variance of unit effects, which approximates the mean prediction error variance (PEV) over unities (Kennedy & Trus, 1993 ), and, as in the PEV, the lower the value the more connected are the units under consideration. The “GCA” r package (Yu & Morota, 2021 ) was used to calculate the VED, in which the choice for the VED statistic was done due to calculating the connectedness in a single‐step and being less computationally expensive than PEV of the difference. The VED for the individuals used to evaluate the genomic predictions for BWT, PWT, YWT, YFD, YGFW, and NLB were 0.046, 0.059, 0.031, 0.008, 0.017, and 0.282, respectively, suggesting sufficient connectedness as the values were low, especially for BWT, PWT, YWT, YFD, and YGFW.…”

Section: Methodsmentioning

confidence: 99%

SNP‐ and haplotype‐based single‐step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep

Araujo

Carneiro

Oliveira

et al. 2022

J Animal Breeding Genetics

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Rambouillet sheep are commonly raised in extensive grazing systems in the US, mainly for wool and meat production. Genomic evaluations in US sheep breeds, including Rambouillet, are still incipient. Therefore, we aimed to evaluate the feasibility of performing genomic prediction of breeding values for various traits in Rambouillet sheep based on single nucleotide polymorphisms (SNP) or haplotypes (fitted as pseudo-SNP) under a single-step GBLUP approach. A total of 28,834 records for birth weight (BWT), 23,306 for postweaning weight (PWT), 5,832 for yearling weight (YWT), 9,880 for yearling fibre diameter (YFD), 11,872 for yearling greasy fleece weight (YGFW), and 15,984 for number of lambs born (NLB) were used in this study. Seven hundred forty-one individuals were genotyped using a moderate (50 K; n = 677) or high (600 K; n = 64) density SNP panel, in which 32 K SNP in common between the two SNP panels (after genotypic quality control) were used for further analyses. Single-step genomic predictions using SNP (H-BLUP) or haplotypes (HAP-BLUP) from blocks with different linkage disequilibrium (LD) thresholds (0.15, 0.35, 0.50, 0.65, and 0.80) were evaluated. We also considered different blending parameters when constructing the genomic relationship matrix used to predict the genomic-enhanced estimated breeding values (GEBV), with alpha equal to 0.95 or 0.50. The GEBV were compared to the estimated breeding values (EBV) obtained from traditional pedigree-based evaluations (A-BLUP). The mean theoretical accuracy ranged from 0.499 (A-BLUP for PWT) to 0.795 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.35 and alpha equal to 0.95 for YFD). The prediction accuracies ranged from 0.143 (A-BLUP for PWT) to 0.330 (A-BLUP for YGFW) while the prediction bias ranged from −0.104 (H-BLUP for PWT) to 0.087 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.15 and alpha equal to 0.95 for YGFW).

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Section: Methodsmentioning

confidence: 99%

SNP‐ and haplotype‐based single‐step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep

Araujo

Carneiro

Oliveira

et al. 2022

J Animal Breeding Genetics

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“…These flocks have been subjected to regular milking controls and represent a base for previous and future selection work in this sheep breed. The "GCA" package [27] was used for connectedness analysis. Four genetic connectedness statistics were estimated:…”

Section: Connectedness Analysismentioning

confidence: 99%

“…Recently, genomic data have been used to assess connectedness [25,26]. A special tool for this purpose (R package "GCA") driven by either pedigree data or genomic data (SNPs) has recently become available [27].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Population-Specific Genetic Parameters Important for Long-Term Optimum Contribution Selection—Case Study on a Dairy Istrian Sheep Breed

Kasap

Ramljak

Špehar

2021

Animals

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The Istrian sheep breed has been subjected to selection for dairy traits for more than two decades. However, a detailed study of some important population-specific parameters such as effective population size (Ne) and connectedness between flocks has never been carried out. The aim of the study was to examine the above parameters in dairy Istrian sheep subjected to a national selection program. The Ne was estimated as the mean rate of increase in coancestry, and connectedness was determined using four different statistics. The Ne was estimated at 73 animals with pedigree constraints imposed on 4 equivalent generations and 3 full generations. Analysis of ΔNe (“sliding window approach”) revealed a negative ΔNe indicating a progressive loss of genetic variability (ΔNeNEG≥4 = −6.6, p < 0.01; ΔNeNFG≥3 = −4.9, p > 0.05). The overall connectedness (r¯ ~ 0.0001) was below the acceptable level for unbiased ranking of the animals belonging to different flocks (ri,j = 0.05). OCS appears to be the best option for the long-term survival (self-sufficiency) of the breed, but genetic links between flocks need to be strengthened to allow unbiased ranking of the animals based on the estimated breeding values.

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On the ability of the LR method to detect bias when there is pedigree misspecification and lack of connectedness

Pardo,

Legarra,

Vitezica

et al. 2024

Genet Sel Evol

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Background Cross-validation techniques in genetic evaluations encounter limitations due to the unobservable nature of breeding values and the challenge of validating estimated breeding values (EBVs) against pre-corrected phenotypes, challenges which the Linear Regression (LR) method addresses as an alternative. Furthermore, beef cattle genetic evaluation programs confront challenges with connectedness among herds and pedigree errors. The objective of this work was to evaluate the LR method's performance under pedigree errors and weak connectedness typical in beef cattle genetic evaluations, through simulation. Methods We simulated a beef cattle population resembling the Argentinean Brangus, including a quantitative trait selected over six pseudo-generations with a heritability of 0.4. This study considered various scenarios, including: 25% and 40% pedigree errors (PE-25 and PE-40), weak and strong connectedness among herds (WCO and SCO, respectively), and a benchmark scenario (BEN) with complete pedigree and optimal herd connections. Results Over six pseudo-generations of selection, genetic gain was simulated to be under- and over-estimated in PE-40 and WCO, respectively, contrary to the BEN scenario which was unbiased. In genetic evaluations with PE-25 and PE-40, true biases of − 0.13 and − 0.18 genetic standard deviations were simulated, respectively. In the BEN scenario, the LR method accurately estimated bias, however, in PE-25 and PE-40 scenarios, it overestimated biases by 0.17 and 0.25 genetic standard deviations, respectively. In herds facing WCO, significant true bias due to confounding environmental and genetic effects was simulated, and the corresponding LR statistic failed to accurately estimate the magnitude and direction of this bias. On average, true dispersion values were close to one for BEN, PE-40, SCO and WCO, showing no significant inflation or deflation, and the values were accurately estimated by LR. However, PE-25 exhibited inflation of EBVs and was slightly underestimated by LR. Accuracies and reliabilities showed good agreement between true and LR estimated values for the scenarios evaluated. Conclusions The LR method demonstrated limitations in identifying biases induced by incomplete pedigrees, including scenarios with as much as 40% pedigree errors, or lack of connectedness, but it was effective in assessing dispersion, and population accuracies and reliabilities even in the challenging scenarios addressed.

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GCA: an R package for genetic connectedness analysis using pedigree and genomic data

Cited by 3 publications

References 20 publications

SNP‐ and haplotype‐based single‐step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep

SNP‐ and haplotype‐based single‐step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep

Estimation of Population-Specific Genetic Parameters Important for Long-Term Optimum Contribution Selection—Case Study on a Dairy Istrian Sheep Breed

On the ability of the LR method to detect bias when there is pedigree misspecification and lack of connectedness

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