Two-stage selection strategies utilizing marker-quantitative trait locus information and individual performance.

Short- and long-term response to marker-assisted selection in two stages was studied using a stochastic simulation of a closed nucleus herd for beef production. First-stage selection was carried out within families based on information at a fully additive quantitative trait locus (QTL). Second-stage selection strategies were based on 1) individual phenotype, 2) individual phenotype precorrected for QTL, 3) a selection index incorporating phenotype and QTL information, 4) a standard animal model BLUP, and 5) a selection index incorporating marker-QTL information and standard animal model BLUP on records precorrected for QTL. All strategies were efficient in moving the favorable allele at the QTL to fixation, but they differed in the time to reach fixation. Mass selection was less efficient in changing allele frequencies than BLUP. Discounted accumulated response, accounting for the time response was realized and inflation rate, was proposed to rank strategies and to elude the conflict between short- and long-term response in marker-assisted selection. Discounted accumulated response at a time horizon of 20 yr for alternative two-stage selection strategies was compared with conventional BLUP carried out in second stage only. Within-family selection increased discounted accumulated response by more than 11% using Strategy 4 and by up to 12% using Strategy 5 at an inflation rate of 2%. The percentage increase in response was less for highly heritable traits and when the proportion of additive variance explained by the QTL was small. Strategy 5 gave larger response with reduced inbreeding. This strategy also resulted in the lowest cost-benefit ratio, requiring less genotyping per unit of response. Cost-benefit ratio for discounted genotyping and for discounted in vitro production of embryos for traits with low heritability was two to four times that for traits with high heritability. The use of first-stage selection slightly increased the level of inbreeding for both mass (Strategy 1) and BLUP selection (Strategies 4 and 5).     

There is room for selection in a small local pig breed when using optimum contribution selection: a simulation study

Selection progress must be carefully balanced against the conservation of genetic variation in small populations of local breeds. Well-defined breeding programs?with specified selection traits are rare in local pig breeds. Given the small population size,?the focus is often on the management of genetic diversity. However, in local breeds, optimum contribution selection can be applied to control the rate of inbreeding and to avoid reduced performance in traits with high market value. The aim of this study was to assess the extent to which a breeding program aiming for improved product quality in a small local breed would be feasible. We used stochastic simulations to compare 25 scenarios. The scenarios differed in?size of population, selection intensity of boars, type of selection (random selection, truncation selection based on BLUP breeding values, or optimum contribution selection based on BLUP breeding values), and heritability of?the selection trait. It was assumed that the local breed is used in an extensive system for a high-meat-quality market.?The?simulations showed that in the smallest population (300 female reproducers), inbreeding increased by 0.8% when selection was performed at random. With optimum contribution selection, genetic progress can be achieved that is almost as great as that with truncation selection based on BLUP breeding values (0.2 to 0.5 vs. 0.3 to 0.5 genetic SD, P < 0.05), but at a considerably decreased rate of inbreeding (0.7 to 1.2 vs. 2.3 to 5.7%, P < 0.01). This confirmation of the potential utilization of OCS even in small populations is important in the context of sustainable management and the use of animal genetic resources.     

A herd management survey on culling guidelines and actual culling practices in three herd groups based on reproductive productivity in Japanese commercial swine herds

The objective of the present study was to investigate culling guidelines for gilts and sows in Japanese commercial herds and to compare differences between culling guidelines and actual culling practices in different herd productivity groups. A questionnaire survey was undertaken to obtain information on culling guidelines in 115 commercial swine herds that participated in the PigCHAMP data-share program. The questionnaire included questions on guideline values for culling intervals and the number of conception failure occurrences that would trigger a culling decision to be made. Ninety-two of the 115 herds (80.0%) returned appropriate data for the study and were included in the present study. In addition to questionnaire data, culling data regarding the actual culling intervals and number of reservices for gilts and sows culled during 2007 to 2008 were also obtained for the same herds from a PigCHAMP database. Culled gilts and sows were divided into 4 female groups on the basis of the stages of their reproductive life when they were culled: unmated gilts, mated gilts, unmated sows, and mated sows. Culling intervals in unmated gilts and sows were defined as the number of days from birth or weaning to culling, respectively, whereas in mated gilts and sows culling intervals were the number of days from last service to culling. Three herd productivity groups were formed on the basis of the upper and lower 25th percentiles of pigs weaned mated female(-1)·yr(-1):high-,intermediate- or low-performing herds. For unmated gilts and sows actual culling intervals were 15 d shorter than the guideline culling intervals in the surveyed data submitted by producers (P < 0.05). This shorter actual culling period for unmated gilts and sows did not vary significantly between herd productivity groups in any parity. However, for mated gilts and sows the actual culling intervals were at least 30 d longer than the guideline culling intervals (P < 0.05). Guideline and actual culling intervals for mated gilts and sows were at least 10 d shorter in high-performing herds than in low-performing herds (P < 0.05). High-performing herds had lower proportions of sows culled after the second reservice than intermediate- or low-performing herds in parity groups 0 to 5 (P < 0.05). In conclusion, culling guidelines for mated sows differed between herd productivity groups, and culling guidelines for mated gilts and sows were not strictly followed in any herd group in the commercial herds.     

The effect of number of sows and service time of boars on selection response and inbreeding using an animal model in a closed nucleus herd(1)

SUMMARY: A simulation study was conducted to examine the influence of population size and number of boars in service per year on overall economic response which was predicted under an BLUP-animal model. The simulated populations should resemble a closed nucleus herd of a pig breeding company. With extension of the sow populations from 60 to 180 sows the overall economic response increased by 32% and the discounted net economic response increased by 53%. The main reason for the higher response in larger populations was the higher realized selection intensity which increased by 17% (24 boars/60 sows versus 24 boars/180 sows). For the same populations, the accuracy of predicted breeding values increased by 8.1% due to more information available from relatives. The reduction in additive genetic variance showed only a small difference between the populations with different sizes, but when selection response was calculated per 1% reduction in additive genetic variance the efficiency to exploit genetic variance in larger populations was up to 50% higher. When sequential culling of boars in the breeding stock was practised, also a reduction in generation interval was found with increased population size. Under an equal size of sow population, a higher number of boars per year led to an increase in selection response due to a low generation interval (e. g. 6% when 24 versus 12 boars per year were used in service in a population of 180 sows) and a lower reduction in additive genetic variance (1% higher genetic standard deviation when 24 boars were used) which more than offset the lower realized selection intensity (-1.5%) and accuracy of selection (-1.0). The expected one generation responses predicted by the conventional approach overestimated the overall genetic merit by 24% to 46%. Causes were 8%-19% overestimation of accuracy of selection, 13%-15% lower genetic standard deviation and 4%-13% overestimation of selection intensity under fixed service time of boars. The rate of inbreeding was very high with 1.36% to 2.04% and depends mainly on the number of boars and the selection strategy of boars. Sequential culling of boars resulted in a high rate of inbreeding due to an increase in variance of family size. In comparison to selection on selection index, under an animal model the use of more boars per year with short fixed service time in a large sow population was recommended. ZUSAMMENFASSUNG: Wirkung der Sauenzahl und Verwendungsdauer von Ebern auf Selektionserfolg und Inzucht bei Verwendung eines Tiermodells in einem geschlossenen Nukleus Eine Simulationsstudie wurde durchgeführt, um den Einflu? der Populationsgr??e und der Anzahl eingesetzter Eber je Jahr auf den Gesamtzuchtfortschritt, der mit einem BLUP-Tiermodell gesch?tzt wurde, zu untersuchen. Die simulierten Populationen sollten die geschlossene Nukleusherde eines Zuchtunternehmens wiedergeben. Durch die Erh?hung der Populationsgr??e von 60 auf 180 Sauen stieg der Gesamtzuchtfortschritt um 32% und der diskontierte Netto-Gesamtzuchtfortschritt um 53%. Der bedeutendste Grund für die Steigerung des Zuchtfortschritts bei Ausdehnung der Populationsgr??e war eine h?here realisierte Selektionsintensit?t (17% bei 24 Eber/60 Sauen im Vergleich zu 24 Eber/180 Sauen). Für die gleichen Populationen stieg die Genauigkeit der Zuchtwertsch?tzung um 8,1% durch einen Zuwachs an Verwandteninformationen. Die Verminderung der additiv genetischen Varianz zeigte nur geringe Unterschiede zwischen Populationen verschiedener Gr??e; wurde jedoch der Selektionserfolg je 1% Reduktion der additiv genetischen Varianz berechnet, war die Effizienz der Aussch?pfung der genetischen Varianz in gr??eren Populationen um bis zu 50% h?her. Bei Anwendung von sequentieller Merzung von Ebern in der Zuchtherde zeigte sich ebenfalls eine Reduktion des Generationsintervalls mit ansteigender Populationsgr??e. Bei gleicher Populationsgr??e von Sauen führte ein h?herer Einsatz von Ebern je Jahr zu einer Erh?hung des Zuchtfortschritts durch ein geringeres Generationsintervall (z. B. 6% wenn 24 anstatt 12 Ebern je Jahr in einer Population von 180 Sauen eingesetzt wurden) und durch eine geringere Reduktion der additiv genetischen Varianz (1% h?here genetische Standardabweichung, wenn 24 Eber eingesetzt wurden), die die geringere realisierte Selektionsintensit?t (-1,5%) und Genauigkeit der Zuchtwertsch?tzung (-1,0%) mehr als ausglichen. Der durch konventionelle Sch?tzmethoden ermittelte erwartete Einjahres-Zuchtfortschritt übersch?tzte den Gesamtzuchtfortschritt um 24% bis 46%. Die Gründe lagen in 8%-19% übersch?tzung der Genauigkeit der Zuchtwertsch?tzung, 13% bis 15% geringeren genetischen Standardabweichung und 4% bis 13% übersch?tzung der Selektionsintensit?t bei konstanter Einsatzdauer der Eber. Die festgestellten Inzuchtraten von 1,36% bis 2,04% sind sehr hoch und waren vorwiegend abh?ngig von der Anzahl der Eber und der Selektionsstrategie der Eber. Sequentielle Merzung der Eber bewirkte eine hohe Inzuchtrate aufgrund des Anstiegs der Varianz in der Familiengr??e. Bei Anwendung des Tiermodells wurde im Vergleich zum Selektionsindex eine h?here Einsatzzahl von Ebern über einen kurzen Zeitraum in einer gro?en Population empfohlen.     

A comparison of restricted selection procedures to control genetic gains

Using Monte Carlo simulation, two schemes of restricted selection were compared under various combinations of genetic parameters and constraints on the genetic gains. The first selection scheme is the combination of best linear unbiased prediction (BLUP) evaluation and linear programming technique (BLUP + LP), and the second one is based on the restricted BLUP selection (RBLUP). Selection for two traits was supposed, in which animals were selected to maximize the genetic gain in trait 2 (Δg₂) under a proportional restriction on the genetic gain in trait 1 (Δg₁) to satisfy the intended ratio (Δg₁:Δg₂). Little differences were found between the two selection schemes with respect to the genetic gains averaged over replicates. However, in all the cases studied, the variance of genetic gains among replicates under BLUP + LP selection was smaller and less sensitive to the genetic parameters and the intended restriction than RBLUP selection. Under the situations of antagonistic selection, the difference tended to be larger. When the heritabilities of the two traits were different, RBLUP selection remarkably increased the variance of genetic gain in a trait with a higher heritability. These results suggest that BLUP + LP selection should always be preferable to RBLUP selection because of the smaller risk of selection. This choice is especially important for the situation where the genetic parameters act as limiting factors for the achievement of intended genetic gains.     

The joint regulation of genetic gain and inbreeding under mate selection

SUMMARY: Stochastic simulation was used to evaluate a range of selection strategies with respect to both additive genetic response and inbreeding. Strategies involving selection on BLUP ebvs or individual phenotype, followed by random mating, were compared with mate selection strategies which used portfolio analysis to give joint consideration to genetic merit and inbreeding. An adapted Mean Of Total Absolute Deviations (MOTAD) method was used in a mate selection model to define optimal matings with regard to aggregate genetic merit and inbreeding for a base population h(2) of 0.2. Compared with random mating following selection on BLUP ebvs, inbreeding levels after 10 years of selection were able to be reduced under BLUP plus mate selection from ～.23 to as little as .11. Additive genetic gain was either little compromised or increased. The results suggest that information linking expected levels of genetic merit and inbreeding can be used to find the preferred selection strategy. ZUSAMMENFASSUNG: Gemeinsame Kontrolle von Zuchtfortschritt und Inzucht bei Partnerselektion Es wurde stochastische Simulation zur Auswertung einer Reihe von Selektionsstrategien hinsichtlich Zuchtwertzuwachs und Inzucht verwendet. Strategien mit Selektion auf der Basis von BLUP ebvs oder individuellem Ph?notyp mit nachfolgender Zufallspaarung wurden mit Partnerselektionsstrategien verglichen, die Portfolioanalyse zur gemeinsamen Beachtung von Zuchtwert und Inzucht verwendeten. Eine Methode adaptierter MITTELWERTE TOTALER ABSOLUTER ABWEICHUNGEN (MOTAD) Methode wurde beim Partnerselektionsmodell zur Definition optimaler Paarungen in Hinblick auf Gesamtzuchtwert und Inzucht bei einer Populationsheritabilit?t von 0,2 verwendet. Verglichen mit Zufallspaarung nach Selektion auf BLUP ebvs waren die Inzuchtgrade nach 10 Selektionsjahren von 0,23 auf 0,11 reduziert und additiver Zuchtfortschritt war dabei wenig beeintr?chtigt oder nahm sogar zu. Die Ergebnisse weisen darauf hin, da? Information, die Zuchtwert und Inzucht verbindet, zur Identifikation erwünschter Selektionsstrategien führen kann.     

Culling practices of Ontario cow-calf producers.

This study describes the distribution of herd culling rates for 123 Ontario cow-calf herds maintaining individual animal records. Associations between culling and factors at both the individual and herd level were examined. In addition, the relative importance of individual animal and herd level influences on culling were investigated. The following individual cow culling risk factors: nonpregnancy, age, weaning weight index, calf outcome, abortion, prolapsed vagina, prolapsed uterus, calving injury, lameness and mastitis or udder problems were significantly associated with culling (p less than 0.01). Two herd level factors were associated with increased culling rates: a higher than average proportion of heifers and a shorter than average calving season (p less than 0.01). The proportion of culling variation attributed to individual animal and herd level influences varied with model type. While simple models (one-way ANOVA) indicated that the herd variance component for culling was relatively minor, more complex models indicated larger herd-to-herd variability (mixed model ANOVA). Thus, it appeared that the probability of culling for a cow with a given set of risk factors depended to an important extent on manager decisions in the herd of origin.     

闭锁群体BLUP选择下遗传方差和近交系数的变化

采用计算机随机模拟方法模拟了在一个闭锁群体内连续对单个性状进行 1 5个世代选择的情况。选择过程中世代不重叠 ,每个世代的种畜根据动物模型最佳线性无偏预测 (BLUP)法估计的育种值进行选留 ,并在此基础上系统地比较了不同群体规模、公母比例和性状遗传力对群体遗传方差和近交系数变化的影响。结果表明 ,扩大育种群规模、增加公畜比例以及对低遗传力性状进行选择时 ,群体遗传方差降低的速度和近交系数上升的速度会更慢 ,在长期选择时可望获得更大的持续进展和适宜的近交增量     

Comparison of selection methods at the same level of inbreeding.

Animal geneticists predict higher genetic responses to selection by increasing the accuracy of selection using BLUP with information on relatives. Comparison of different selection methods is usually made with the same total number tested and with the same number of parents and mating structure so as to give some acceptable (low) level of inbreeding. Use of family information by BLUP results in the individuals selected being more closely related, and the levels of inbreeding are increased, thereby breaking the original restriction on inbreeding. An alternative is to compare methods at the same level of inbreeding. This would allow more intense selection (fewer males selected) with the less accurate methods. Stochastic simulation shows that, at the same level of inbreeding, differences between the methods are much smaller than if inbreeding is unrestricted. If low to moderate inbreeding levels are targeted, as in a closed line of limited size, then selection on phenotype can yield higher genetic responses than selection on BLUP. Extra responses by BLUP are at the expense of extra inbreeding. The results derived here show that selection on BLUP of breeding values may not be optimal in all cases. Thus, current theory and teaching on selection methods are queried. Revision of the methodology and a reappraisal of the optimization results of selection theory are required.     

近交与贴现对优化群体规模的影响

小群体的闭锁选育不可避免产生近交及遗传方差下降，导致近期与远期选择效果的矛盾。本文通过考察猪核心群育种方案中群体规模及公母比例对近交增量（％）及累积育种产出（元）的作用，分析遗传方差下降以及育种产出的贴现等因素对选择方案评估效果的影响。群体有效规模主要受每世代选择公猪头数的影响，为了控制群体近交增量必须维持一定的公猪头数。在所模拟的１６种方案中，１５代的贴现累积选择进展以每代选择８头公猪为最高；而母猪规模越大，累积选择进展越高。不考虑近交引起遗传方差的下降，或不进行选择进展的贴现，都造成过高估计选择方案的效果，且导致选择不适当的方案；对各世代选择进展进行贴现时，需要考虑较大的世代数，否则也会影响各选择方案的比较结果。     

Inbreeding in genome-wide selection

Traditional selection methods, such as sib and best linear unbiased prediction (BLUP) selection, which increased genetic gain by increasing accuracy of evaluation have also led to an increased rate of inbreeding per generation (DeltaFG). This is not necessarily the case with genome-wide selection, which also increases genetic gain by increasing accuracy. This paper explains why genome-wide selection reduces DeltaFG when compared with sib and BLUP selection. Genome-wide selection achieves high accuracies of estimated breeding values through better prediction of the Mendelian sampling term component of breeding values. This increases differentiation between sibs and reduces coselection of sibs and DeltaFG. The high accuracy of genome-wide selection is expected to reduce the between family variance and reweigh the emphasis of estimated breeding values of individuals towards the Mendelian sampling term. Moreover, estimation induced intraclass correlations of sibs are expected to be lower in genome-wide selection leading to a further decrease of coselection of sibs when compared with BLUP. Genome-wide prediction of breeding values, therefore, enables increased genetic gain while at the same time reducing DeltaFG when compared with sib and BLUP selection.     

Causes of culling and death in sows.

Over a 4-year period, the annual number of culled sows in 9 Danish herds averaged 54.8 per cent of the year-sows and the number of culled sows in per cent of total number of farrowings averaged 25.8 (Table I). -- The culling rate varied considerably from herd to herd within the same year and from year to year (Tables I and II); however, the average annual culling rate for all the herds only presented small variations (Table II). The average number of litters reared per sow before culling was 3.6. The culling rate was higher in pedigree herds than in commercial herds, and it was highest in the small pedigree herds (Table III). The hygiene level in the herds and the introduction of new female breeding stock did not influence the culling rate (Table IV). A proportionally lower percentage of the sows was culled in herds where the dry and pregnant sows were housed in stalls and/or were tethered, as compared to herds where these sows were housed in pens (Table V). -- The culling rate in the age groups of sows with less than 8 farrowings remained at approximately the same level (Table VI). The main reason for culling was infertility problems, which were recorded in 41.4 per cent of the culled sows, while 16.7 per cent of the sows were culled because their litters were poor and/or small (Table VII). The mortality rate among the culled sows was 11.9 (Table VII), and the main causes of death were chronic pyogenic infections, which occurred in 25.5 per cent of the fatal cases (Table VIII). Certain aspects concerning the recording and calculation of culling rates in the different herds are discussed and it is emphasized that the culling rate per se may not have any direct relationship to the productivity in the herd.     

动物模型BLUP选择效果的计算机模拟研究

在采用动物模型最佳线性无偏预测(BLUP) 方法对个体育种值进行估计的基础上, 模拟了在一个闭锁群体内连续对单个性状选择10个世代的情形, 并系统地比较了群体规模、公母比例和性状遗传力对选择所获得的遗传进展和群体近交系数变化的影响。结果表明, 扩大育种群规模不仅可以获得更大的持续进展, 同时还可有效缓解近交系数的过快上升; 育种群中公畜比例过低时, 不仅会降低遗传进展, 群体近交系数的上升速度也会加快, 实际中应保证育种群具有一定的规模和适宜的公母比例。对高遗传力性状进行选择时, 可望获得更大的遗传进展, 同时近交系数的上升速度也会快一些。     

Efficiency of selection strategies for halothane-negative gene

Use of a method to estimate the frequency of the halothane-negative allele in boars is illustrated for different sampling schemes for boar testing programs and for testing within closed breeding populations. This method uses information not only on the individual, but also on all mates and relatives including parents, siblings and offspring. Accuracy of the estimates of the allelic frequency in boars was measured through use of Monte Carlo simulation. The selection differential in real frequency of the halothane-negative allele when boars were selected on estimated allelic frequency was used as the criterion for accuracy. In the progeny testing situation, phenotypes of base boars and one generation of offspring were available. The average selection differentials with 90% selection (i.e., culling 10% of boars on estimated allelic frequency) when 2 and 10 litters of two boars each were tested were .017 and .044 in base boars and .013 and .025 in the offspring. The value of the boar's own phenotype was small. Higher selection differentials were found in the closed herd situation, where data on two generations were available. The selection differential in base boars when 10 litters were tested increased from .046 to .066 when the proportion of boars selected decreased from 90% to 50%. No improvement in selection differential with proportion selected was found in the progeny testing situation. Intense selection is most effective when the number of litters per boar is large and data over several generations are used. The estimation procedure for allelic frequencies in boars should improve current screening and selection programs to reduce halothane sensitivity in pigs.     

The use of mathematical programming to control inbreeding in selection schemes

Selection on the best estimate of the breeding value of individuals should, in large populations, provide the maximal response in breeding value. However, many breeders deal with the selection of small numbers of animals from relatively small populations and therefore there is a trend for inbreeding to rise because of genetic drift. Moreover, as the evaluation of candidates is traditionally based on methodologies including information from relatives [selection indices, best linear unbiased predictor (BLUP)] more individuals are selected from the best families and so closely related individuals will generate most of the offspring. This effect is more important for traits with low heritability as phenotype gives little information on the breeding value of the individuals and more weight is given to relatives’ data. The need for controlling inbreeding refers not only to a better use of the genetic variability available and to a reduced inbreeding depression in the selected trait, but also to a reduced depression of fitness-related traits, which may be the most serious drawback at present due to the increase in inbreeding in domestic populations (M euwissen and W oolliams 1994). In recent years considerable work has been carried out on the design of strategies to maintain genetic diversity in selection programmes. These strategies are aimed at simultaneously optimizing genetic gain and inbreeding, either by reducing the rate of inbreeding (or variance of response) while keeping genetic gains at a predetermined level, or by increasing selection response under a restriction on inbreeding (or on variance of response). Following T oro and P& eacute ; rez -E nciso (1990) the different strategies can be classified according to the factor on which they act: (i) the selection criterion used; (ii) the mating system imposed; (iii) the number of selected individuals and their contribution to the next generation. The first group of strategies proposes the use of a suboptimal selection criterion that reduces the weight given to family information or the use of an upward-biased heritability in BLUP evaluation (T oro and P& eacute ; rez -E nciso 1990; see G rundy et al. 1998a for the latest development of this idea). The second group of strategies proposes action on the mating system including factorial mating designs, minimum co-ancestry mating (using linear programming) or compensatory mating (see review by C aballero et al. 1996). The third group of strategies includes the ones considered in the present work. The first possibility is to modify the contribution of the selected individuals of generation t to the selected individuals of generation t + 1, by practising some form of within-family selection with respect to BLUP values. Two strategies of this type were considered: modified within-family selection (MWFS) and restricted co-ancestry selection (RCS). The second possibility is to modify the contribution of the selected individuals of generation t to the evaluated individuals of generation t + 1 (instead of to the selected individuals) by a strategy called weighted selection (T oro and N ieto 1984). Three strategies were considered in this case: weighted selection (WS), restricted co-ancestry weighted selection (RCWS) and pair weighted selection (PWS). More specifically, the aim of the present paper is to show how these five strategies can be implemented using mathematical programming techniques. A small example comparing all of these strategies with standard truncation selection (TS) is also given for illustration.     

The effect of sire selection on cow mortality and early lactation culling in adverse and favorable cow survival environments

The objective of this study was to determine the extent that genetic selection can help reduce dairy cow mortality and early lactation culling in adverse cow survival environments. Two datasets were constructed. The first contained 100,911 mortality records and 171,178 sixty-day culling records from 1467 herds. Cows that left the herd (culled or died) from 21 days prior to a due date through 60 days in milk were considered a 60-day cull. Cows were classified as belonging to herds with adverse cow survival environments (≥ 4.4% mortality rate and ≥ 7.1% 60-day cull rate) or favorable cow survival environments (<4.4% mortality rate and <7.1% 60-day cull rate). The second dataset included 20,438 mortality records and 34,942 sixty-day culling records from 314 herds with a known herd management system. Cows from both datasets were stratified into quartiles based on their sire's predicted transmitting ability (PTA) for productive life and other traits. Cows in the first dataset were also stratified into high (>50th percentile) and low (≤ 50th percentile) groups based on their sire's PTA for daughter calving ease and daughter stillbirth rates. Mortality and 60-day culling in the first dataset were evaluated with logistic regression models with the independent effects of sire PTA quartile, cow survival environment (adverse or favorable), the interaction of sire PTA quartile with cow survival environment, lactation number, age within lactation number, and herd-calving-cluster. The second dataset was analyzed in the same manner, but with cow survival environment replaced by herd management system. The estimated proportion of lactations that ended in death declined from 9.0% to 6.8% and 60-day culling incidence from 7.6% to 4.9% as sire productive life PTA went from the lowest to highest quartile in adverse cow survival environments. The corresponding reduction in mortality (0.7%) and 60-day culling (0.9%) were also significant in favorable cow survival environments. Mortality and 60-day culling both declined by 2.0% from low to high sire productive life PTA quartile in complete confinement free-stalls, which was the most unfavorable herd management system for cow survival. Daughters of bulls with high somatic cell score PTA and low daughter pregnancy rate PTA had higher incidences of mortality and 60-day culling, and 60-day culling was higher for daughters of sires with high milk and protein yield PTA. Selection to reduce stillbirth risk was associated with less mortality and 60-day culling, whereas mortality risk was reduced in favorable cow survival environments with selection to lower the incidence of stillbirths and calving difficulty. In conclusion, this study provides evidence that sire selection can play an important role in reducing the incidence of mortality and early lactation culling, particularly in herds with adverse cow survival environments.     

Implementation of genetic evaluation and mating designs for the endangered local pig breed ‘Bunte Bentheimer’

A pedigree including 1538 individuals of the endangered pig breed ‘Bunte Bentheimer’ and 3008 records of the fertility traits ‘number of piglets born alive’ (NBA) and ‘number of piglets weaned’ (NW) were used to i) characterize the population structure, ii) to estimate genetic (co)variance components and estimated breeding values (EBVs) and iii) to use EBVs for the application of the concept of optimal genetic contributions. The average coefficient of inbreeding increased from F = 0.103 to F = 0.121 within the two recent cohorts. Average rate of inbreeding amounted to 1.66%, which resulted in an effective population size of N_e = 30 animals in the recent cohort. Average generation interval was 3.07 years considering the whole pedigree, and in total, only 612 sows and boars generated offspring. Estimated heritabilities for both traits NBA and NW were 0.12, and the estimated genetic correlation between both traits was 0.96. The variance component due to the service sire was higher than in commercial pig breeds, presumably due to the widespread use of natural service boars. The EBVs for NBA from 333 selection candidates (63 boars and 270 sows) were used to determine optimal genetic contributions. Based on selected animals and their optimal genetic contributions, specific mating designs were evaluated to minimize inbreeding in the next generation. Best results were achieved when using a simulated annealing algorithm and allowing artificial insemination.     

Impacts of genotyping strategies on long‐term genetic response in genomic selection

The present study investigated the effects of the choices of animals of reference populations on long‐term responses to genomic selection. Simulated populations comprised 300 individuals and 10 generations of selection practiced for a trait with heritability of 0.1, 0.3 or 0.5. Thirty individuals were randomly selected in the first five generations and selected by estimated breeding values from best linear unbiased prediction (BLUP) and genomic BLUP in the subsequent five generations. The reference populations comprise all animals for all generations (scenario 1), all animals for 6‐10 generations (scenario 2) and 2‐6 generations (scenario 3), and half of the animals for all generations (scenario 4). For all heritability levels, the genetic gains in generation 10 were similar in scenarios 1 and 2. Among scenarios 2 to 4, the highest genetic gains were obtained in scenario 2, with heritabilities of 0.1 and 0.3 as well as scenario 4 with heritability of 0.5. The inbreeding coefficients in scenarios 1, 2 and 4 were lower than those in BLUP, especially within cases with low heritability. These results indicate an appropriate choice of reference population can improve genetic gain and restrict inbreeding even when the reference population size is limited.     

Reducing the effect of parent averages from animal solutions in mixed model equations

Selection of animals based on their BLUP evaluations from an animal model results in animals that are closely related which leads to increased rates of inbreeding. The tendency for higher inbreeding rates is greater at low heritability values. Several attempts have been made to reduce the impact of parent average breeding values from animals evaluations in order to reduce inbreeding while not sacrificing genetic response. A method that modifies the rules for forming the inverse of the additive genetic relationship matrix for use in best linear unbiased estimation of breeding values via an animal model was developed. This method and several others were compared analytically and empirically, from the perspective of partitioning the animal solutions into contributions from the data, from progeny, and from the parent average. The ratio of genetic progress to average level of inbreeding showed that the modified relationship matrix method was superior to the other methods. Similar results could be obtained by using artificially high heritability in a usual BLUP analysis.