Prediction of heterosis using genome-wide SNP-marker data: application to egg production traits in white Leghorn crosses

Amuzu-Aweh, Esinam Nancy; Bijma, P.; Kinghorn, Brian; Vereijken, Addie; Visscher, J.; Arendonk, J.A.M. van; Bovenhuis, H.

doi:10.1038/hdy.2013.77

Cited by 16 publications

(21 citation statements)

References 37 publications

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“…Phenotypic records of ~210 000 crossbred hens that originated from nine purebred White Leghorn layer lines (three sire-lines and six dam-lines) were obtained from the Institut de Sélection Animale (ISA) B.V. These data are a subset of the population of chickens described in [ 1 ] since only records of crossbred hens for which sires had been genotyped were retained here. Following [ 1 ], sire-lines were coded as S1, S4 and S5, and dam-lines were D1, D2, D3, D4, D5 and D6.…”

Section: Methodsmentioning

confidence: 99%

“…These data are a subset of the population of chickens described in [ 1 ] since only records of crossbred hens for which sires had been genotyped were retained here. Following [ 1 ], sire-lines were coded as S1, S4 and S5, and dam-lines were D1, D2, D3, D4, D5 and D6. A cross produced by an S1 sire and a D1 dam is referred to as S1*D1 and its reciprocal as D1*S1.…”

Section: Methodsmentioning

confidence: 99%

“…The development of a reliable method to predict heterosis would greatly improve the efficiency of these breeding schemes by reducing their dependency on time-consuming and expensive field-tests of multiple pure-line combinations. Using egg production records from White Leghorn crosses, Amuzu-Aweh et al [ 1 ] showed that heterosis can be predicted using the genome-wide average squared difference in allele frequency (SDAF) between the two parental lines, with an accuracy of ~0.5. With this method, one can predict which sire- and dam-line combinations have the highest potential for heterosis, and thus pre-select which crosses should be field-tested.…”

Section: Introductionmentioning

confidence: 99%

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Predicting heterosis for egg production traits in crossbred offspring of individual White Leghorn sires using genome-wide SNP data

et al. 2015

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BackgroundThe development of a reliable method to predict heterosis would greatly improve the efficiency of commercial crossbreeding schemes. Extending heterosis prediction from the line level to the individual sire level would take advantage of variation between sires from the same pure line, and further increase the use of heterosis in crossbreeding schemes. We aimed at deriving the theoretical expectation for heterosis due to dominance in the crossbred offspring of individual sires, and investigating how much extra variance in heterosis can be explained by predicting heterosis at the individual sire level rather than at the line level. We used 53 421 SNP (single nucleotide polymorphism) genotypes of 3427 White Leghorn sires, allele frequencies of six White Leghorn dam-lines and cage-based records on egg number and egg weight of ~210 000 crossbred hens.ResultsWe derived the expected heterosis for the offspring of individual sires as the between- and within-line genome-wide heterozygosity excess in the offspring of a sire relative to the mean heterozygosity of the pure lines. Next, we predicted heterosis by regressing offspring performance on the heterozygosity excess. Predicted heterosis ranged from 7.6 to 16.7 for egg number, and from 1.1 to 2.3 grams for egg weight. Between-line differences accounted for 99.0% of the total variance in predicted heterosis, while within-line differences among sires accounted for 0.7%.ConclusionsWe show that it is possible to predict heterosis at the sire level, thus to distinguish between sires within the same pure line with offspring that show different levels of heterosis. However, based on our data, variation in genome-wide predicted heterosis between sires from the same pure line was small; most differences were observed between lines. We hypothesise that this method may work better if predictions are based on SNPs with identified dominance effects.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predicting heterosis for egg production traits in crossbred offspring of individual White Leghorn sires using genome-wide SNP data

et al. 2015

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“…The extent of heterosis depends on the genetic distance between the parental populations, the number of involved parental populations and the type of cross-breeding programme. The genetic mechanisms underlying heterosis are favourable non-additive gene effect due to dominance and overdominance which is attributed to advantageous combinations of alleles at heterozygous loci and epistasis as a result of interaction among loci (Amuzu-Aweh et al, 2013;Lynch & Walsh, 1998).…”

Section: Introductionmentioning

confidence: 99%

Effects of breed proportion and components of heterosis for semen traits in a composite cattle breed

Khayatzadeh

Mészáros

Utsunomiya

et al. 2017

J Animal Breeding Genetics

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SummaryThe aim of this study was to estimate the non-additive genetic effects of the dominance component of heterosis as well as epistatic loss on semen traits in admixed Swiss Fleckvieh, a composite of Simmental (SI) and Red Holstein Friesian (RHF) cattle. Heterosis is the additional gain in productivity or fitness of cross-bred progeny over the mid-purebred parental populations. Intralocus gene interaction usually has a positive effect, while epistatic loss generally reduces productivity or fitness due to lack of evolutionarily established interactions of genes from different breeds. Genotypic data on 38,205 SNP of 818 admixed, as well as 148 RHF and 213 SI bulls as the parental breeds were used to predict breed origin of alleles. The genomewide locus-specific breed ancestries of individuals were used to calculate effects of breed difference as well as the dominance component of heterosis, while proxies for two definitions of epistatic loss were derived from 100,000 random pairs of loci. The average Holstein Friesian ancestry in admixed bulls was estimated 0.82. Results of fitting different linear mixed models showed including the dominance component of heterosis considerably improved the model adequacy for three of the four traits. Inclusion of epistatic loss increased the accuracy of the models only for our new definition of the epistatic effect for two traits, while the other definition was so highly correlated with the dominance component that statistical separation was impossible. K E Y W O R D Sbreed composition, dominance, heterosis, epistatic loss, semen traits, Swiss Fleckvieh

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“…Thus, understanding the genetic architecture in the presence of dominance effects is helpful for planning breeding strategies and increasing genetic gain. For example, dominance effects can be utilized by designing mating schemes that optimize favorable allele combinations, especially for crossbreeding which benefit from heterosis 13 .…”

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confidence: 99%

Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle

Mao

Sahana

Johansson

et al. 2020

Sci Rep

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Exploring dominance variance and loci contributing to dominance variation is important to understand the genetic architecture behind quantitative traits. The objectives of this study were i) to estimate dominance variances, ii) to detect quantitative trait loci (QTL) with dominant effects, and iii) to evaluate the power and the precision of identifying loci with dominance effect through post-hoc simulations, with applications for female fertility in Danish Holstein cattle. The female fertility records analyzed were number of inseminations (NINS), days from calving to first insemination (ICF), and days from the first to last insemination (IFL), covering both abilities to recycle and to get pregnant in the female reproductive cycle. There were 3,040 heifers and 4,483 cows with both female fertility records and Illumina BovineSNP50 BeadChip genotypes (35,391 single nucleotide polymorphisms (SNP) after quality control). Genomic best linear unbiased prediction (BLUP) models were used to estimate additive and dominance genetic variances. Linear mixed models were used for association analyses. A post-hoc simulation study was performed using genotyped heifers' data. In heifers, estimates of dominance genetic variances for female fertility traits were larger than additive genetic variances, but had large standard errors. The variance components for fertility traits in cows could not be estimated due to nonconvergence of the statistical model. In total, five QTL located on chromosomes 9, 11 (2 QTL), 19, and 28 were identified and all of them showed both additive and dominance genetic effects. Among them, the SNP rs29018921 on chromosome 9 is close to a previously identified QTL in Nordic Holstein for interval between first and last insemination. This SNP is located in the 3' untranslated region of gene peptidylprolyl isomerase like 4 (PPIL4), which was shown to be associated with milk production traits in US Holstein cattle but not known for fertility-related functions. Simulations indicated that the current sample size had limited power to detect QTL with dominance effects for female fertility probably due to low QTL variance. More females need to be genotyped to achieve reliable mapping of QTL with dominance effects for female fertility. Intensive selection on milk yield in dairy cattle has led to a decline in female fertility, due to unfavorable genetic correlations between milk yield and female fertility 1. Declining female fertility increases the costs for dairy farm management due to extra inseminations, veterinary treatments, and involuntary replacements 2. Moreover, poor female fertility has been showed to be genetically correlated with increased methane production and negative climate impact 3. Female fertility in dairy cattle can be generally divided into two component 4,5. The first component is the ability to return to cycling and to go into heat after calving, which can be measured by the time interval from calving to first insemination. The second component is the ability to conceive and become pregnant, which

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Prediction of heterosis using genome-wide SNP-marker data: application to egg production traits in white Leghorn crosses

Cited by 16 publications

References 37 publications

Predicting heterosis for egg production traits in crossbred offspring of individual White Leghorn sires using genome-wide SNP data

Predicting heterosis for egg production traits in crossbred offspring of individual White Leghorn sires using genome-wide SNP data

Effects of breed proportion and components of heterosis for semen traits in a composite cattle breed

Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle

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