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Genetic improvement of feed intake and methane emissions of cattle
Manzanilla Pech, Coralia I.V. - \ 2017
University. Promotor(en): Roel Veerkamp, co-promotor(en): Yvette de Haas. - Wageningen : Wageningen University - ISBN 9789463430692 - 199
cattle - feed intake - methane production - genetic improvement - genetic parameters - conformation - breeding value - animal genetics - rundvee - voeropname - methaanproductie - genetische verbetering - genetische parameters - bouw (dier) - fokwaarde - diergenetica
Feed costs represent half of the total costs of dairy production. One way to increase profitability of dairy production is to reduce feed costs by improving feed efficiency. As DMI is a trait that varies significantly during and across lactations, it is imperative to understand the underlying genetic architecture of DMI across lactation. Moreover, phenotypes of DMI are scarce, due to the difficulty of recording them (expensive and labor-intensive). Some predictor traits have been suggested to predict DMI. Examples of these predictor traits are those related to production (milk yield (MY) or milk content) or to the maintenance of the cow (body weight (BW) or conformation traits). The ability to determine when predictor traits ideally should be measured in order to achieve an accurate prediction of DMI throughout the whole lactation period is thus important. Recently, with the use of information of single nucleotide polymorphism (SNP) markers, together with phenotypic data and pedigree, genomically estimated breeding values (GEBV) of scarcely recorded traits, such as DMI, have become easier to accurately predict. This approach, combined with predictor traits, could contribute to an increased accuracy of predictions of GEBV of DMI. Methane (CH4) is the second important greenhouse gas, and enteric CH4 is the largest source of anthropogenic CH4, representing 17% of global CH4 emissions. Furthermore, methane emissions represent 2-12% of feed energy losses. Selecting for lower CH4 emitting animals and more feed-efficient animals would aid in mitigating global CH4 emissions. To identify the impact on CH4 emissions of selecting for lower DMI animals, it is important to determine the correlations between DMI and CH4 and to identify whether the same genes that control DMI affect CH4. Therefore, the general objectives of this thesis were to (1) explore the genetic architecture of DMI during lactation, (2) study the relationship of DMI to conformation, production and other related traits, (3) investigate the correlations between DMI and methane traits, and determine the SNP in common between DMI and CH4 through a genome-wide association study (GWAS), and (4) investigate the accuracy of predictions of DMI using predictor traits combined with genomic data.
Genetic improvement of longevity in dairy cows
Pelt, Mathijs van - \ 2017
University. Promotor(en): Roel Veerkamp, co-promotor(en): T.H.E. Meuwissen. - Wageningen : Wageningen University - ISBN 9789463430821 - 188
dairy cows - longevity - genetic improvement - breeding value - genetic analysis - survival - animal models - animal genetics - melkkoeien - gebruiksduur - genetische verbetering - fokwaarde - genetische analyse - overleving - diermodellen - diergenetica
Improving longevity helps to increase the profit of the farmer, and it is seen as an important measure of improved animal welfare and sustainability of the sector. Breeding values for longevity have been published since in 1999 in the Netherlands. For AI-companies and farmers it is necessary that breeding values are accurately estimated and will remain stable for the rest of life. However, current breeding values for longevity of bulls seem to fluctuate more than expected. The main aim of this thesis was to revisit the genetics of longevity and develop a genetic evaluation model for longevity, where breeding values reflect the true breeding value quicker during early life and therefore breeding values become more stable. Genetic parameters were estimated for survival up to 72 months after first calving with a random regression model (RRM). Survival rates were higher in early life than later in life (99 vs. 95%). Survival was genetically not the same trait across the entire lifespan, because genetic correlations differ from unity between different time intervals, especially when intervals were further apart. Survival in the first year after first calving was investigated more in depth. Survival of heifers has improved considerably in the past 25 years, initially due to the focus on a high milk production. More recently, the importance of a high milk production for survival has been reduced. Therefore functional survival was defined as survival adjusted for within-herd production level. For survival the optimum age at first calving was around 24 months, whereas for functional survival calving before 24 months resulted in a higher survival. Over years, genetic correlations between survival in different 5-yr intervals were below unity, whereas for functional survival genetic correlations did not indicate that survival changed over years. This suggested that a genetic evaluation using historical data should analyze functional survival rather than survival. A new genetic evaluation system for longevity was developed based on a RRM analyzing functional survival. Based on the correlation between the first breeding value of a bull and his later breeding values, the ranking of bulls was shown to be more stable for RRM than the current genetic evaluation. Bias in breeding value was observed, mainly for bulls with a large proportion of living daughters. Adjusting for within-herd production level reduced this bias in the breeding values greatly. Before implementing this new model for genetic evaluation, the cause of this bias needs to be further investigated.
Antibodies and longevity of dairy cattle : genetic analysis
Klerk, B. de - \ 2016
University. Promotor(en): Johan van Arendonk, co-promotor(en): Jan van der Poel; Bart Ducro. - Wageningen : Wageningen University - ISBN 9789462577589 - 134 p.
dairy cattle - dairy cows - antibodies - longevity - genetic analysis - breeding value - genomes - genetic improvement - animal genetics - melkvee - melkkoeien - antilichamen - gebruiksduur - genetische analyse - fokwaarde - genomen - genetische verbetering - diergenetica
The dairy sector has a big impact on food production for the growing world population and contributes substantially to the world economy. In order to produce food in a sustainable way, dairy cows need to be able to produce milk without problems and as long as possible. Therefore, breeding programs focuses on improvement of important traits for dairy cows. In order to improve desirable traits and obtain genetic gain there is a constant need for optimization of breeding programs and search for useful parameters to include within breeding programs. Over the last several decades, breeding in dairy cattle mainly focused on production and fertility traits, with less emphasis on health traits. Health problems, however, can cause substantial economic losses to the dairy industry. The economic losses, together with the rising awareness of animal welfare, increased herd size, and less attention for individual animals, have led to an increased need to focus more on health traits. Longevity is strongly related to disease resistance, since a more healthy cow will live a longer productive life (longevity). The identification of biomarkers and the detection of genes controlling health and longevity, would not only greatly enhance the understanding of such traits but also offer the opportunity to improve breeding schemes. The objectives of this thesis therefore were 1) to find an easy measurable disease resistance related biomarker in dairy cows, 2) identify the relation between antibodies and longevity, 3) identify genomic regions that are involved with antibody production/expression. In this thesis antibodies are investigated as parameter for longevity. Antibodies might be a novel parameter that enables selection of cows with an improved ability to stay healthy and to remain productive over a longer period of time. In this thesis antibodies bindiging the naive antigen keyhole limpet hemocyanin (KLH) were assumed to be natural antibodies. Antibodies binding bacteria-derived antigens lipoteichoic acid (LTA), lipopolysaccharide (LPS) and peptidoglycan (PGN) were assumed to be specific antibodies. In chapter 2 it was shown that levels of antibodies are heritable (up to h2 = 0.23). Additionally, antibody levels measured in milk and blood are genetically highly correlated (± 0.80) for the two studied isotypes (IgG and IgM). On the other hand, phenotypically, natural antibodies (from both IgG and IgM isotype) measured in milk cannot be interpreted as the same trait (phenotypic correlation = ± 0.40). In chapter 3 and 4 it was shown that levels of antibodies (both natural-and specific antibodies) showed a negative relation with longevity: first lactation cows with low IgM or IgG levels were found to have a longer productive life. When using estimated breeding values for longevity, only a significant relation was found between natural antibody level (IgM binding KLH) and longevity. Lastly chapter 5 reports on a genome-wide-association study (GWAS), to detect genes contributing to genetic variation in natural antibody level. For natural antibody isotype IgG, genomic regions with a significant association were found on chromosome 21 (BTA). These regions included genes have impact on in isotype class switching (from IgM to IgG). The gained knowledge on relations between antibodies and longevity and the gained insight on genes responsible for natural antibodies level make antibodies potential interesting biomarkers for longevity.
Estimating host genetic effects on susceptibility and infectivity to infectious diseases and their contribution to response to selection
Anche, M.T. - \ 2016
University. Promotor(en): Mart de Jong, co-promotor(en): Piter Bijma. - Wageningen : Wageningen University - ISBN 9789462577442 - 185 p.
livestock - hosts - genetic effects - susceptibility - infectivity - infectious diseases - breeding value - heritability - epidemics - vee - gastheren (dieren, mensen, planten) - genetische effecten - vatbaarheid - infectiviteit - infectieziekten - fokwaarde - epidemieën
Mahlet Teka Anche. (2016). Estimating host genetic effects on susceptibility and infectivity to infectious diseases and their contribution to response to selection. PhD thesis, Wageningen University, the Netherlands
Genetic approaches aiming to reduce the prevalence of an infection in a population usually focus on improving host susceptibility to an infection. The prevalence of an infection, however, is also affected by the infectivity of individuals. Studies reported that there exists among host (genetic/phenotypic) variation in susceptibility and infectivity to infectious diseases. The effect of host genetic variation in susceptibility and infectivity on the prevalence and risk of an infection is usually measured by the value of the basic reproduction ratio, R0. R0 is an important epidemiological parameter that determines the risk and prevalence of an infection. It has a threshold value of 1, where major disease outbreak can occur when R0 > 1 and the disease will die out when R0 < 1. Due to this threshold property, genetic improvements aiming to reduce the prevalence of an infection should focus on reducing R0 to a value below 1. The overall aim of this thesis was to develop methodologies that allow us to investigate the genetic effects of host susceptibility and infectivity on the prevalence of an infection, which is measured by the value of R0. Moreover, we also aim to investigating the effect of relatedness among groupmates on the utilization of among host genetic variation in susceptibility and infectivity so as to reduce the prevalence of infectious diseases. The theory of direct-indirect genetic effects and epidemiological concepts were combined to develop methodologies. In addition, a simulation study was performed to validate the methodologies developed and examine the effect of relatedness on the utilization of genetic variation in susceptibility and infectivity. It was shown that an individual’s genetic effect on its susceptibility and infectivity affect the prevalence of an infection and that an individual’s breeding value for R0 can be defined as a function of its own allele frequencies for susceptibility and infectivity and of population average susceptibility and infectivity. Moreover, simulation results show that, not only an individual’s infectivity but also an individual’s susceptibility represents an indirect genetic effect on the disease status of individuals and on the prevalence of an infection in a population. It was shown that having related groupmates allows breeders to utilize the genetic variation in susceptibility and infectivity, so as to reduce the prevalence of an infection.
Fokwaarde voeropname op volle kracht : vanaf komende Interbull-draai is de fokwaarde voeropname voor elke stier beschikbaar in Nederland en Vlaanderen
Haas, Yvette de; Veerkamp, Roel - \ 2016
cattle husbandry - bulls - milk production - dairy cows - feed intake - farm results - intensive livestock farming - breeding value - flanders - netherlands - australia
Genomic selection in egg-laying chickens
Heidaritabar, M. - \ 2016
University. Promotor(en): Martien Groenen, co-promotor(en): John Bastiaansen. - Wageningen : Wageningen University - ISBN 9789462576704 - 220 p.
hens - genomics - genetic variation - selective breeding - quantitative traits - breeding value - animal genetics - animal breeding - hennen - genomica - genetische variatie - selectief fokken - kwantitatieve kenmerken - fokwaarde - diergenetica - dierveredeling
Heidaritabar, M. (2016). Genomic selection in egg-laying chickens. PhD thesis, Wageningen University, the Netherlands
In recent years, prediction of genetic values with DNA markers, or genomic selection (GS), has become a very intense field of research. Many initial studies on GS have focused on the accuracy of predicting the genetic values with different genomic prediction methods. In this thesis, I assessed several aspects of GS. I started with evaluating results of GS against results of traditional pedigree-based selection (BLUP) in data from a selection experiment that applied both methods side by side. The impact of traditional selection and GS on the overall genome variation as well as the overlap between regions selected by GS and the genomic regions predicted to affect the traits were assessed. The impact of selection on genome variation was assessed by measuring changes in allele frequencies that allowed the identification of regions in the genome where changes must be due to selection. These frequency changes were shown to be larger than what could be expected from random fluctuations, indicating that selection is really affecting the allele frequencies and that this effect is stronger in GS compared with BLUP. Next, concordance was tested between the selected regions and regions that affect the traits, as detected by a genome-wide association study. Results showed a low concordance overall between the associated regions and the selected regions. However, markers in associated regions did show larger changes in allele frequencies compared with the average changes across the genome. The selection experiment was performed using a medium density of DNA markers (60K). I subsequently explored the potential benefits of whole-genome sequence data for GS by comparing prediction accuracy from imputed sequence data with the accuracy obtained from the 60K genotypes. Before sequencing, the selection of key animals that should be sequenced to maximize imputation accuracy was assessed with the original 60K genotypes. The accuracy of genotype imputation from lower density panels using a small number of selected key animals as reference was compared with a scenario where random animals were used as the reference population. Even with a very small number of animals as reference, reasonable imputation accuracy could be obtained. Moreover, selecting key animals as reference considerably improved imputation accuracy of rare alleles compared with a set of random reference animals. While imputation from a small reference set was successful, imputation to whole-genome sequence data hardly improved genomic prediction accuracy compared with the predictions based on 60K genotypes. Using only those markers from the whole-genome sequence that are more likely to affect the phenotype was expected to remove noise from the data, but resulted in slightly lower prediction accuracy compared with the complete genome sequence. Finally, I evaluated the inclusion of dominance effects besides additive effects in GS models. The proportion of variance due to additive and dominance effects were estimated for egg production and egg quality traits of a purebred line of layers. The proportion of dominance variance to the total phenotypic variance ranged from 0 to 0.05 across traits. Also, the impact of fitting dominance besides additive effects on prediction accuracy was investigated, but was not found to improve accuracy of genomic prediction of breeding values.
Breeding against infectious diseases in animals
Rashidi, H. - \ 2016
University. Promotor(en): Johan van Arendonk, co-promotor(en): Herman Mulder; P.K. Mathur. - Wageningen University - ISBN 9789462576452 - 179 p.
livestock - infectious diseases - animal breeding - selective breeding - disease resistance - tolerance - genetic variation - breeding value - genetic correlation - traits - genomics - animal genetics - vee - infectieziekten - dierveredeling - selectief fokken - ziekteresistentie - tolerantie - genetische variatie - fokwaarde - genetische correlatie - kenmerken - genomica - diergenetica
Infectious diseases in farm animals are of major concern because of animal welfare, production costs, and public health. Farms undergo huge economic losses due to infectious disease. The costs of infections in farm animals are mainly due to production losses, treatment of infected animals, and disease control strategies. Control strategies, however, are not always successful. Selective breeding for the animals that can mount a defence against infection could therefore be a promising approach. Defensive ability of an animal has two main mechanisms: resistance (ability to control the pathogen burden) and tolerance (ability to maintain performance when pathogen burden increases). When it is difficult to distinguish between resistance and tolerance, defensive ability is measured as resilience that is the ability to maintain performance during a disease outbreak regardless of pathogen burden. Studies have focused on the genetics of resistance and resilience with little known about the genetics of tolerance and its relationship with resistance and resilience. The objectives of this thesis were to: 1) estimate the genetic variation in resistance, tolerance, and resilience to infection in order to assess the amenability of these traits for selective breeding in farm animals, 2) estimate the genetic correlation between resistance, tolerance and resilience and 3) detect genomic regions associated with resistance, tolerance, and resilience.
In chapter 2, we studied the variation among sows in response to porcine reproductive and respiratory syndrome (PRRS). First a statistical method was developed to detect PRRS outbreaks based on reproduction records of sows. The method showed a high sensitivity (78%) for disease phases. Then the variation of sows in response to PRRS was quantified using 2 models on the traits number of piglets born alive (NBA) and number of piglets born dead (LOSS): 1) bivariate model considering the trait in healthy and disease phases as different traits, and 2) reaction norm model modelling the response of sows as a linear regression of the trait on herd-year-week estimates of NBA. Trait correlations between healthy and disease phases deviated from unity (0.57±0.13 – 0.87±0.18). The repeatabilities ranged from 0.07±0.027 to 0.16±0.005. The reaction norm model had higher predictive ability in disease phase compared to the bivariate model.
In chapter 3 we studied 1) the genetic variation in resistance and tolerance of sheep to gastrointestinal nematode infection and 2) the genetic correlation between resistance and tolerance. Sire models on faecal nematode egg count (FEC), IgA, and pepsinogen were used to study the genetic variation in resistance. Heritability for resistance traits ranged from 0.19±0.10 to 0.59±0.20. A random regression model was used to study the reaction norm of sheep body weight on FEC as an estimate of tolerance to nematode infection. We observed a significant genetic variance in tolerance (P<0.05). Finally a bivariate model was used to study the genetic correlation between resistance and tolerance. We observed a negative genetic correlation (-0.63±0.25) between resistance and tolerance.
In chapter 4, we studied the response to selection in resistance and tolerance when using estimated breeding values for resilience. We used Monte Carlo simulation to generate 100 half-sib families with known breeding values for resistance (pathogen burden) and tolerance. We used selection index theory to predict response to selection for resistance and tolerance: 1) when pathogen burden is known and selection is based on true breeding values for resistance and tolerance and 2) when pathogen burden is unknown and selection is based on estimated breeding values for resilience. Using EBV for resilience in absence of records for pathogen burden resulted in favourable responses in resistance and tolerance to infections, with more emphasis on tolerance than on resistance. However, more genetic gain in resistance and tolerance could be achieved when pathogen burden was known.
In chapter 5 we studied genomics regions associated with resistance, resilience, and tolerance to PRRS. Resistance was modelled as sire effect on area under the PRRS viremia curve up to 14 days post infection (AUC14). Resilience was modelled as sire effects on daily growth of pigs up to 28 days post infection (ADG28). Tolerance was modelled as the sire effect on the regression of ADG28 on AUC14. We identified a major genomics region on chromosome 4 associated with resistance and resilience to PRRS. We also identified genomics regions on chromosome 1 associated with tolerance to PRRS.
In the general discussion (chapter 6) I discussed: 1) response to infection as a special case of genotype by environment interaction, 2) random regression model as a statistical tool for studying response to disease, 3) advantages and requirements of random regression models, and 4) selective breeding of farm animals for resistance, tolerance, and resilience to infections. I concluded that random regression is a powerful approach to estimate response to infection in animals. If the adequate amount of data is available random regression model could estimate breeding values of animals more accurately compared to other models. I also concluded that before including resistance and tolerance into breeding programs, breeders should make sure about the added values of including these traits on genetic progress. Selective breeding for resilience could be a pragmatic approach to simultaneously improve resistance and tolerance.
Multi-population genomic prediction
Wientjes, Y.C.J. - \ 2016
University. Promotor(en): Roel Veerkamp; Mario Calus. - Wageningen : Wageningen University - ISBN 9789462576193 - 267 p.
cum laude - dairy cattle - genomics - prediction - quantitative trait loci - genetic improvement - breeding value - selective breeding - animal breeding - animal genetics - melkvee - genomica - voorspelling - loci voor kwantitatief kenmerk - genetische verbetering - fokwaarde - selectief fokken - dierveredeling - diergenetica
Cum laude graduation
Exploiting genomic information on purebred and crossbred pigs
Hidalgo, A.M. - \ 2015
University. Promotor(en): Martien Groenen, co-promotor(en): D.J. de Koning; John Bastiaansen. - Wageningen : Wageningen University - ISBN 9789462576018 - 202
varkens - genomica - kruising - inteeltlijnen - genetische verbetering - fokwaarde - drachtigheidsperiode - androstenon - prestatieniveau - varkensfokkerij - diergenetica - pigs - genomics - crossbreds - inbred lines - genetic improvement - breeding value - gestation period - androstenone - performance - pig breeding - animal genetics
Natuurlijke antilichamen als voorspeller zieke koe
Knaap, J. van der; Poel, J.J. van der - \ 2015
Veeteelt 32 (2015)15. - ISSN 0168-7565 - p. 10 - 12.
melkveehouderij - dierveredeling - natuurlijke antilichamen - diergezondheid - fokwaarde - dairy farming - animal breeding - natural antibodies - animal health - breeding value
De aanwezigheid van natuurlijke antilichamen, de zogenaamde NAbs, kan sterk verschillen per koe. Door de erfelijkheidsgraad van NAbs is het mogelijk om erop te fokken, zo blijkt uit het project Weerbaar Vee. De uitkomsten bieden perspectief om de gezondheid te verbeteren, maar de uitvoering lijkt nog niet prakijkrijp.
Linkage disequilibrium and genomic selection in pigs
Veroneze, R. - \ 2015
University. Promotor(en): Johan van Arendonk; S.E.F. Guimarães, co-promotor(en): John Bastiaansen. - Wageningen : Wageningen University - ISBN 9789462574151 - 142
varkens - verstoord koppelingsevenwicht - loci voor kwantitatief kenmerk - genomica - populaties - kruising - inteeltlijnen - fokwaarde - selectief fokken - genetica - pigs - linkage disequilibrium - quantitative trait loci - genomics - populations - crossbreds - inbred lines - breeding value - selective breeding - genetics
Securing a sufficiently large set of genotypes and phenotypes can be a limiting factor when implementing genomic selection. This limitation may be overcome by combining data from multiple populations or by using information of crossbred animals. The research described in this thesis characterized linkage disequilibrium (LD) patterns in different pig populations and evaluated whether the consistency of LD between populations allows us to make predictions about the performance of genomic selection when multiple populations are included in the prediction and/or validation datasets.
In chapter 2 I evaluated the persistence of LD and patterns of LD decay of pure and crossbred pig populations using real data that was representative of the crossbreeding structure of pig production. The persistence of phase between the crosses and their parental populations was high, indicating that similar marker effects might be expected across these populations. Across the purebred populations the persistence of phase was low therefore higher density panels should be used to have the same marker-QTL associations across these populations.
In chapter 3, the well-known nonlinear model developed by Sved (1971) was compared against a an alternative, loess regression, to describe LD decay. The loess regression model was found to be less influenced by the lack of residual normality, independence and homogeneity of variance than the nonlinear regression model. The loess regression model resulted in more reliable LD predictions and can be used to formally compare the LD decay curves between populations.
Chapter 4 showed the utility of different reference sets (across- and multi-population) for the prediction of genomic breeding values, as well as the potential of using crossbred performance in genomic prediction. None of the accuracies obtained using across-population, or multi-population genomic prediction, nor the accuracies obtained using crossbred data, followed the expectations based on LD that was described in chapter 2. I showed that across-population prediction accuracy was negligible even when the populations had common breeds in their genetic background. The variable accuracies of multi-population prediction and moderate accuracy of prediction of crossbred performance appeared to be a result of the differences in genetic architecture between pure populations and between purebred and crossbred animals.
In chapter 5, a methodology that uses information from genome wide association analyses in the genomic predictions was developed and evaluated. The aim in chapter 5 was to let the genomic prediction model use information from the genetic architecture in single- and multi-population genomic prediction. I showed that using weights based on GWAS results from a combined population did result in higher accuracies of GBLUP in single- as well as in multi-population predictions.
In chapter 6 I placed my results in a broader context. I discussed about the theoretical and practical aspects of linkage disequilibrium in breeding and in the estimation of effective population size. I also discussed the application of genomic selection in a small population and in practical pig breeding, including the prospects of using whole genome sequence for genomic prediction.
GReIS en Elda als registratiesystemen voor geitenrassen
Oldenbroek, J.K. ; Eijndhoven, M.H.T. - \ 2015
Zeldzaam huisdier 40 (2015)2. - ISSN 0929-905X - p. 16 - 17.
dierveredeling - rassen (dieren) - zeldzame rassen - geitenrassen - registratie - melkcontrole - computer software - stamboeken - bedrijfsinformatiesystemen - toggenburgergeit - fokwaarde - animal breeding - breeds - rare breeds - goat breeds - registration - milk recording - herdbooks - management information systems - toggenburg - breeding value
In een serie artikelen worden de mogelijkheden van registratiesystemen voor zeldzame rassen toegelicht. In dit tweede artikel komt eerst GReIS (GeitenRegistratie- en InformatieSysteem) aan de orde en daarna het Elda-systeem.
Fokwaarde voeropname : introductie van fokwaarde voor voeropname in Nederland
Haas, Y. de; Veerkamp, R.F. - \ 2015
Wageningen : Wageningen UR Livestock Research (Livestock Research rapport 837) - 17
fokwaarde - melkveehouderij - melkproductie - voeropname - dierveredeling - rundveehouderij - rundveevoeding - breeding value - dairy farming - milk production - feed intake - animal breeding - cattle husbandry - cattle feeding
Feed costs represent above 50% of the total costs of dairy production, so reducing costs by improving dairy cow feed efficiency is a way to increase profitability. Therefore it is important to improve efficiency of that dairy cattle population. This project has shown that it is possible to breed for more efficient animals, resulting in permanent and cumulative changes in the genetic merit of dairy cows. The breeding value for feed intake is currently integrated in the Better Life Efficiency index for all sires of CRV, and it is under discussing if it will be included in the national index (published by GES) for all bulls in the Netherlands and Flanders.
Het hoe en waarom van een fokprogramma
Eijndhoven, M.H.T. ; Oldenbroek, J.K. - \ 2015
Zeldzaam huisdier 40 (2015)1. - ISSN 0929-905X - p. 10 - 11.
kenmerken - dierveredeling - rassen (dieren) - fokwaarde - fokdoelen - selectiecriteria - traits - animal breeding - breeds - breeding value - breeding aims - selection criteria
Voor velen van u zal het herkenbaar zijn: verknocht zijn aan een dier om zijn of haar uiterlijk en gedrag. Juist deze kenmerken die horen bij een bepaald ras, wilt u behouden en optimaliseren wanneer u gaat fokken. Verstandig fokken binnen een ras vraagt naast enige kennis van erfelijkheidsleer om het systematisch nalopen van een aantal foktechnische stappen. Deze stappen, die samen het fokprogramma bepalen, komen vanaf dit nummer van Zeldzaam Huisdier in 2015 aan bod.
Effect van fokwaarde voor berengeur op het gedrag en berengeur van beren : Effect of genetic background for boar taint on the behaviour and boar taint of boars
Peet-Schwering, C.M.C. van der; Troquet, L.M.P. ; Binnendijk, G.P. ; Vermeer, H.M. ; Riel, J.W. van; Fels, J.B. van der; Vogelzang, R.H. ; Knol, E.F. ; Heres, L. - \ 2014
Wageningen : Wageningen UR Livestock Research (Rapport / Wageningen UR Livestock Research 808) - 37
varkenshouderij - beren (varkens) - berengeur - diergedrag - dierenwelzijn - fokwaarde - selectie - varkens - dierlijke productie - pig farming - boars - boar taint - animal behaviour - animal welfare - breeding value - selection - pigs - animal production
In opdracht van het ministerie van Economische Zaken en het Productschap Vee en Vlees is op Varkens Innovatie Centrum (VIC) Sterksel en een praktijkbedrijf onderzocht of er een relatie is tussen ongewenst gedrag van beren en berengeur. Mocht deze relatie er zijn, dan wordt bij selectie op minder berengeur mogelijk ook geselecteerd op minder ongewenst gedrag van beren. Daarnaast is op 9 praktijkbedrijven nagegaan wat het effect is op berengeur bij de inzet van eindberen met een lage fokwaarde voor berengeur.
(Em)pathetic pigs? : the impact of social interactions on welfare, health and productivity
Reimert, I. - \ 2014
University. Promotor(en): Bas Kemp, co-promotor(en): Liesbeth Bolhuis; Bas Rodenburg. - Wageningen : Wageningen University - ISBN 9789461739964 - 264
varkens - sociaal gedrag - sociaal milieu - emoties - diergedrag - dierenwelzijn - diergezondheid - fokwaarde - dierlijke productie - varkenshouderij - pigs - social behaviour - social environment - emotions - animal behaviour - animal welfare - animal health - breeding value - animal production - pig farming
The welfare, health and productivity of intensively raised pigs may be affected by routine management procedures and the physical environment they are housed in, but also by their social environment, i.e. by social interactions between pen mates. In this thesis, the effect of social interactions on pig welfare, health and productivity has been investigated in several ways. On the one hand, a new breeding method based on interactions, i.e. on heritable effects on the performance of pen mates, was investigated. The effect of divergent selection for a relatively positive or negative indirect genetic effect on growth of pen mates on pig behavior and physiology was studied. On the other hand, it was investigated whether pigs can be affected by (the emotional state of) their pen mates on the basis of two social processes, emotional contagion and social support. Pigs selected for a relatively positive indirect genetic effect on the growth of their pen mates seemed less fearful and less stressed in several novelty tests and they had lower leukocyte, lymphocyte and haptoglobin concentrations compared to pigs selected for a relatively negative indirect genetic effect on the growth of their pen mates. Moreover, it was found that pigs can indeed be affected by the emotional state of their pen mates either in a positive or negative way, which points to emotional contagion, a simple form of empathy, in pigs. Furthermore, evidence for social support has also been found. To conclude, this breeding method may be a strategy to improve the social environment of intensively raised pigs as pigs with relatively positive indirect genetic effects for growth may create a less stressful social environment for themselves. In addition, the welfare, health and productivity of pigs may not only depend on their own emotional state, but also on the emotional state of their pen mates.
Kaf van het koren scheiden
Calus, Mario - \ 2014
dairy farming - ai bulls - dairy bulls - animal breeding - breeding value - selective breeding - genome analysis - genomes
Het Nederlands Groot-Yorkshire varken
Slaghuis, H. ; Oldenbroek, J.K. - \ 2014
Zeldzaam huisdier 39 (2014)2. - ISSN 0929-905X - p. 20 - 21.
varkensfokkerij - varkensrassen - zeldzame rassen - veredelingsprogramma's - fokwaarde - rassen (dieren) - pig breeding - pig breeds - rare breeds - breeding programmes - breeding value - breeds
De Bonte Bentheimer en het Nederlands landvarken hebben al de volle aandacht van de SZH. Maar verdient het Groot-Yorkshirevarken die aandacht ook niet? In de Nederlandse varkensfokkerij is dit ras indertijd gefokt voor de productie van slagersvarkens. In dit artikel wordt de geschiedenis van het Nederlands Groot-Yorkshirevarken op een rij gezet en aangegeven hoe het er nu voorstaat.
‘Speciale technieken alleen voor topfokkerij': Gary Hennip voorspelt het einde van KI als geavanceerde technieken worden gecombineerd
Hogenkamp, W. ; Veerkamp, R.F. - \ 2014
Boerderij 99 (2014)27. - ISSN 0006-5617 - p. 38 - 38.
veehouderij - dierveredeling - fokwaarde - kunstmatige inseminatie - genetica - genomen - technieken - nieuwe combinatie - toekomst - livestock farming - animal breeding - breeding value - artificial insemination - genetics - genomes - techniques - new combination - future
Gary Hennip, onderzoeker bij Penn State University (VS), denkt dat ki overbodig is bij slim combineren van technieken als ovum pick-up, ivf, genomics en sperma seksen op het bedrijf. Boerderij legt de stelling voor aan professor generieke genetcia Roel Veerkamp.
Optimizing genomic selection for scarcely recorded traits
Pszczola, M.J. - \ 2013
University. Promotor(en): Johan van Arendonk, co-promotor(en): Mario Calus; T. Strabel. - Wageningen : Wageningen UR - ISBN 9789461737663 - 158
melkvee - genomen - selectief fokken - genetische verbetering - fokwaarde - fenotypen - genotypen - kenmerken - voeropname - dierveredeling - dairy cattle - genomes - selective breeding - genetic improvement - breeding value - phenotypes - genotypes - traits - feed intake - animal breeding
Animal breeding aims to genetically improve animal populations by selecting the best individuals as parents of the next generation. New traits are being introduced to breeding goals to satisfy new demands faced by livestock production. Selecting for novel traits is especially challenging when recording is laborious and expensive and large scale recording is not possible. Genetic improvement of novel traits may be thus limited due to the small number of observations. New breeding tools, such as genomic selection, are therefore needed to enable the genetic improvement of novel traits. Using the limited available data optimally may, however, require alternative approaches and methodologies than currently used for conventional breeding goal traits. The overall objective of this thesis was to investigate different options for optimizing genomic selection for scarcely recorded novel traits. The investigated options were: (1) genotype imputation for ungenotyped but phenotyped animals to be used to enlarge the reference population; (2) optimization of the design of the reference population with respect to the relationships among the animals included in it; (3) prioritizing genotyping of the reference population or the selection candidates; and (4) using easily recordable predictor traits to improve the accuracy of breeding values for scarcely recorded traits. Results showed that: (1) including ungenotyped animals to the reference population can lead to a limited increase in the breeding values accuracy; (2) the reference population is designed optimally when the relationship within the reference are minimized and between reference population and potential selection candidates maximized; (3) the main gain in accuracy when moving from traditional to genomic selection is due to genotyping the selection candidates, but preferably both reference population and selection candidates should be genotyped; and (4) including the predictor traits in the analysis when it is recorded on both reference population and selection candidates can lead to a significant increase in the selection accuracy. The key factors for successful implementation of selection for a novel trait in a breeding scheme are: (1) maximizing accuracy of genotype prediction for ungenotyped animals to be used for updating the reference population; (2) optimizing the design of the reference population; (3) determining easy to record indicator traits that are also available on the selection candidates (4) developing large scale phenotyping techniques; and (5) establishing strategies and policies for increasing the engagement of farmers in the recording of novel traits.