Genetic relationship between purebred and crossbred sow longevity

Abell, Caitlyn; Fernando, Rohan L.; Serenius, Timo; Rothschild, Max F.; Gray, Kent; Stalder, K. J.

doi:10.1186/s40104-016-0112-x

Cited by 12 publications

(13 citation statements)

References 16 publications

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“…Therefore, CB will mainly be kept based on their own performance in the previous litter rather than the performance of their parents or EBV. This agrees with the low genetic correlation between PB and CB longevity, where dam longevity was not indicative of CB longevity ( Abell et al, 2016 ).…”

Section: Discussionsupporting

confidence: 86%

“…Genetic correlations between PB and CB longevity (LGY12 and LGY15) were low, suggesting that PB and CB longevity are different traits similar to Abell et al (2016) . One reason why PB and CB performance may differ for a trait is due to genotype by environment interaction (G × E; Wientjes and Calus, 2017 ).…”

Section: Discussionmentioning

confidence: 99%

“…In addition, the recording of longevity in nucleus animals is compromised because these animals are mainly replaced based on their breeding values and high replacement rates and not due to their inability to produce. Several studies have investigated longevity traits, where the trait has either been analyzed with survival analysis models ( Ducrocq and Sölkner, 1998 ; Vollema and Groen, 1998 ; Vukasinovic, 1999 ; Heagerty and Zheng, 2005 ; Engblom et al, 2009 ), linear models ( Aasmundstad et al, 2014 ; Aasmundstad et al, 2015 ; Abell et al, 2016 ), or random regression models ( Veerkamp et al, 1999 ). Another approach is to model survival using a repeatability model, where survival to the next parity is indicated as a binary trait ( Meuwissen et al, 2002 ).…”

Section: Introductionmentioning

confidence: 99%

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Predicting survival and longevity of sows using purebred and crossbred data1

Iversen

Nordbø

Gjerlaug-Enger

et al. 2020

Translational Animal Science

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Survival and longevity are very important traits in pig breeding. From an economic standpoint, it is favorable to keep the sows for another parity instead of replacing them and, from the animal’s perspective, better welfare is achieved if they do not experience health problems. It is challenging to record longevity in purebred (PB) nucleus herds because animals are more likely to be replaced based on breeding value and high replacement rates rather than inability to produce. Crossbred (CB) sows are, however, submitted to lower replacement rates and are more likely to be kept in the farm longer if they can produce large and robust litters. Therefore, the objective of this study was to investigate whether the use of CB phenotypes could improve prediction accuracy of longevity for PBs. In addition, a new definition of survival was investigated. The analyzed data included phenotypes from two PB dam lines and their F1 cross. Three traits were evaluated: 1) whether or not the sow got inseminated for a second litter within 85 d of first farrowing (Longevity 1–2), 2) how many litters the sow can produce within 570 d of first farrowing [Longevity 1–5 (LGY15)], and 3) a repeatability trait that indicates whether or not the sow survived until the next parity (Survival). Traits were evaluated both as the same across breeds and as different between breeds. Results indicated that longevity is not the same trait in PB and CB animals (low genetic correlation). In addition, there were differences between the two PB lines in terms of which trait definition gave the greatest prediction accuracy. The repeatability trait (Survival) gave the greatest prediction accuracy for breed B, but LGY15 gave the greatest prediction accuracy for breed A. Prediction accuracy for CBs was generally poor. The Survival trait is recorded earlier in life than LGY15 and seemed to give a greater prediction accuracy for young animals than LGY15 (until own phenotype was available). Thus, for selection of young animals for breeding, Survival would be the preferred trait definition. In addition, results indicated that lots of data were needed to get accurate estimates of breeding values and that, if CB performance is the breeding goal, CB phenotypes should be used in the genetic evaluation.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Predicting survival and longevity of sows using purebred and crossbred data1

Iversen

Nordbø

Gjerlaug-Enger

et al. 2020

Translational Animal Science

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show abstract

“…The low correlation between the two methods does not identify which method is the best when choosing either the survival method or the linear model method to predict longevity breeding values for a population. Further, the genetic correlations have been very small to zero when examining crossbred and purebred reproductive traits (Abell et al, 2016). This suggests that improving the breeding objective, the crossbred female, requires that breeders obtain data from crossbred females that would be used in the calculation of the estimated breeding values for nucleus animals.…”

Section: Methods To Estimate Sow Longevity Breeding Valuesmentioning

confidence: 99%

“…Many studies investigating the survival or longevity for the purebred cows have a direct impact on the commercial dairy industry. A relatively recent study suggests that the genetic correlation between purebred and crossbred reproductive traits in sows were close to zero (Abell et al, 2016). Selection for improved longevity at the nucleus level may not result in improved longevity and lifetime performance at the crossbred level.…”

Section: Breeding Sourcementioning

confidence: 99%

Genetic improvement of sow longevity and its economic impact on commercial pork production

Mote¹,

Serenius²,

Supakorn³

et al. 2020

SA J. An. Sci.

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Sow longevity (sow productive lifetime) plays an important role in economically efficient piglet production. Direct selection for sow longevity is not commonly practiced in any pig-breeding program. In recent years, an increased number of peer reviewed articles addressing the economic impact, genetic parameter estimates, and genomic information (including markers and single nucleotide polymorphisms for sow longevity) have been published in the scientific literature. The studies in the literature indicate that sow longevity is a complex trait having economic value and is an animal well-being concern for commercial pork producers. Studies have concluded that sufficient genetic variation exists so that selection to improve sow longevity should be effective. Unlike the dairy industry, the primary parent animal used in the swine industry is a crossbred female, typically F1 (Landrace X Large White or Yorkshire). Sow longevity has shown to be genetically related with prolificacy and leg conformation traits. Sow longevity seems to be the ideal trait to utilize genomic selection when attempting to improve the trait. The genetic correlation between purebred and crossbred sow longevity is low. Since the crossbred sow is the breeding objective, phenotypic data from the crossbred females should ideally be used when estimating the breeding values for sow longevity that are used in the indexes to evaluate nucleus animals. Genomic selection is best suited for sex-limited traits, traits expressed later in life, and many animals do not reach some defined end-point parity, sow longevity seems ideally suited to be evaluated using the latest genome enabled selection technology. Keywords: heritability, leg conformation, selection, sow productive lifetime

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Functional genomics of reproduction in pigs: Are we there yet?

Nonneman

Lents

2022

Molecular Reproduction Devel

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Reproductive failure is the main reason for culling females in swine herds and is both a financial and sustainability issue. Because reproductive traits are complex and lowly to moderately heritable, genomic selection within populations can achieve substantial genetic gain in reproductive efficiency. A better understanding of the physiological components affecting the expression of these traits will facilitate greater understanding of the genes affecting reproductive traits and is necessary to improve and optimize management strategies to maximize reproductive success of gilts and sows. Large‐scale genotyping with single‐nucleotide polymorphism (SNP) arrays are used for genome‐wide association studies (GWAS) and have facilitated identification of positional candidate genes. Transcriptomic data can be used to weight SNP for GWAS and could lead to previously unidentified candidate genes. Resequencing and fine mapping of candidate genes are necessary to identify putative functional variants and some of these have been incorporated into new genotyping arrays. Sequence imputation and genotype by sequence are newer strategies that could reveal novel functional mutations. In this study, these approaches are discussed. Advantages and limitations are highlighted where additional research is needed.

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Genetic relationship between purebred and crossbred sow longevity

Cited by 12 publications

References 16 publications

Predicting survival and longevity of sows using purebred and crossbred data1

Predicting survival and longevity of sows using purebred and crossbred data1

Genetic improvement of sow longevity and its economic impact on commercial pork production

Functional genomics of reproduction in pigs: Are we there yet?

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