Genetic Relationships under Different Management Systems and their Consequences for Dairy Cattle Breeding
04 Sep 2013-Vol. 78, Iss: 3, pp 183-186
TL;DR: Advances in breeding and management resulted in a considerable increase of production traits in Austrian dairy cattle and genetic antagonisms between milk yield and functional traits were stronger in intensive systems, however, standard errors were large.
Abstract: Summary Advances in breeding and management resulted in a considerable increase of production traits in Austrian dairy cattle. Besides, low input systems were also established. Possible genotype by environment interactions (G x E) and genetic antagonisms dependent on production level might indicate the need for separate breeding programmes for dairy farms diff ering in management intensity. Th us, G x E and genetic correlations (ra) between milk yield and selected fi tness traits were estimated for Upper Austrian Fleckvieh cattle under high and low production levels. Data of the current herdbook cow population and their dams were extracted. Two data sets were selected based on the herd average of milk; extensive (≤6,000 kg herd average) and intensive (≥9,000 kg herd average) farms. Yield deviations were used for the analysis of yield traits, functional longevity, reproduction traits and milking speed; raw data were used for somatic cell count (SCC). For yield deviations, a model including the eff ects year of birth (fi xed) and animal (genetic, random) was applied, while a model close to the routine evaluation was run for SCC. Th e lowest ra between extensive and intensive farms was found for protein yield (ra = 0.89) while ra values close to unity were found for all functional traits. Genetic antagonisms between milk yield and functional traits were stronger in intensive systems, however, standard errors were large. Currently, separate breeding programmes for diff erent management intensities do not seem to be necessary.
Citations
More filters
Journal Article•
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
9,847 citations
TL;DR: The results suggest that some opportunity may exist for genetic improvements in fat and milk yield in Iranian Holstein cattle and the relationship between longevity and production traits.
Abstract: We used data collected on 48,739 cows from 1982 to 2013 from Foka farm in the Isfahan province of Iran to assess the reasons for culling in Iranian Holstein dairy cattle in the context of breeding values of economic traits, and also to study the relationship between longevity and production traits. Estimation of (co)variance components and genetic parameters for studied traits including MY, FY, herd life (HL) and length of production life (LPL) was by AI-REML algorithm in WOMBAT software. The results showed that 27.11% of cows were culled voluntarily under the farmers’ command. The number and reasons for culling animals varied considerably over the years. Also, the results showed that involuntarily culled animals were valuable with significantly higher breeding values for MY and FY (P < .0001) than those of voluntarily culled individuals. The estimates of heritability for longevity traits (HL and LPL) were low (0.11 and 0.09), but their genetic correlation with production traits were high and posi...
18 citations
Cites background from "Genetic Relationships under Differe..."
...On the other hand, Fuerst-Waltl et al. (2013) reported unfavourable correlations between milk yield and LPL in both extensive (−0.159) and intensive (−0.192) management systems in Austrian Fleckvieh (dual-purpose Simmental)....
[...]
TL;DR: The need for a correction method for the heterogeneous variance in the small cattle breed used as a case study is suggested, particularly in the selection of best cows that are more susceptible to biases in EBVs.
7 citations
01 Jan 2018
TL;DR: Different regions were associated with 305-d milk yield while considering the three production scenarios as observed in chromosomes 11 and 21 that were more strongly associated with milk yield in the low input data set than in the other two.
Abstract: With the objective of exploring genotype by environment interaction in the Brazilian National Dairy Gir Breeding Program, a total of 97,476 lactation records were separated into three data sets, according to the average milk yield within each management group. They were designated as low input, medium input, or high input management groups. Breeding values were predicted for 305-d milk yield using records from those three data sets as three different traits: Low input 305-d milk yield; Medium input 305-d milk yield; and High input 305-d milk yield. Genetic correlations ranged from 0.75, between the low input and high input traits, to 0.97, between the medium input and high input traits. Reordering of ranking of sires has been observed, especially in the comparison between the low input and high input EBVs. SNP genotypes were obtained for a sample of 2,681 animals, including animals with lactation records (own or from their progeny) within the three data sets. The EBVs of the genotyped animals were later deregressed and used in three Genome Wide Association Studies (GWAS). Different regions were associated with 305-d milk yield while considering the three production scenarios as observed in chromosomes 11 and 21 that were more strongly associated with milk yield in the low input data set than in the other two.
1 citations
Cites background from "Genetic Relationships under Differe..."
...On the contrary, Fuerst-Waltl et al. (2013) found that genetic correlations between production and functional traits of dairy cattle in Austria, measured in low or high productivity systems, were mostly close to unity, suggesting no need of distinct breeding programs according to the management…...
[...]
01 Jan 2018
TL;DR: This study confirms the importance to detect GxE in local breeds reared in various environments and explains a certain quote of phenotypic variance, even greater than G in milk, protein yield and SCS.
Abstract: Genotype by environment interactions (GxE) may occur when individuals show different adaptation to local environment. Due to their typically great adeptness to environment local breeds may be reared in a variety of geographical areas and farming conditions, suggesting to investigate the occurrence of GxE for genetic improvement. Considering the local cattle breed Rendena, this study aimed to investigate GxE for traits of interest in a number of environmental conditions including the geographical area (plain, hill or mountain), the type of housing (tie-stall or loose housing), the feeding system (traditional or total mixed ration) and the occurrence of summer pasture. Following the reaction norm model approach, milk yield, fat and protein yield and percentage, and SCS were analysed via Bayesian inference. The solutions for the herd-test day (HTD) effect firstly obtained via animal model as estimates of environmental effect, were then used in a random regression model as environmental covariate for sire effect to obtain the intercept and the slope for target traits across different HTD levels. As result, GxE interactions explained a certain quote of phenotypic variance (about the 20% on average), even greater than G in milk, protein yield and SCS. Some differences in genetic variances were observed between estimates for HTD ascribable to different environmental conditions. A greater genetic component was observed for milk, fat and protein yield in plain farms, without summer pasture, under loose housing, and with a total mixed ration as feed. This may be explained by the fact that better conditions for individuals or for production could enhance the expression of individual performance. This study confirms the importance to detect GxE in local breeds reared in various environments.
1 citations
Cites background from "Genetic Relationships under Differe..."
...Genetic improvement of local breeds should account for GxE, as suggested by the heterogeneous variances estimated in different environments (e.g., Fuerst-Waltl et al., 2013)....
[...]
References
More filters
Book•
01 Jan 1981
TL;DR: The genetic constitution of a population: Hardy-Weinberg equilibrium and changes in gene frequency: migration mutation, changes of variance, and heritability are studied.
Abstract: Part 1 Genetic constitution of a population: Hardy-Weinberg equilibrium. Part 2 Changes in gene frequency: migration mutation. Part 3 Small populations - changes in gene frequency under simplified conditions. Part 4 Small populations - less simplified conditions. Part 5 Small populations - pedigreed populations and close inbreeding. Part 6 Continuous variation. Part 7 Values and means. Part 8 Variance. Part 9 Resemblance between relatives. Part 10 Heritability. Part 11 Selection - the response and its prediction. Part 12 Selection - the results of experiments. Part 13 Selection - information from relatives. Part 14 Inbreeding and crossbreeding - changes of mean value. Part 15 Inbreeding and crossbreeding - changes of variance. Part 16 Inbreeding and crossbreeding - applications. Part 17 Scale. Part 18 Threshold characters. Part 19 Correlated characters. Part 20 Metric characters under natural selection.
20,288 citations
Journal Article•
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
9,847 citations
TL;DR: A working hypothesis is proposed in which any activity or condition that limits the availability of oxidizable fuels can inhibit both gonadotropin-releasing hormone (GnRH)/luteinizing hormone secretion and female copulatory behaviors, and disruption of these signaling processes allows normal reproduction to proceed in the face of energetic deficits.
Abstract: Natural selection has linked the physiological controls of energy balance and fertility such that reproduction is deferred during lean times, particularly in female mammals. In this way, an energetically costly process is confined to periods when sufficient food is available to support pregnancy and lactation. Even in the face of abundance, nutritional infertility ensues if energy intake fails to keep pace with expenditure. A working hypothesis is proposed in which any activity or condition that limits the availability of oxidizable fuels (e.g., undereating, excessive energy expenditure, diabetes mellitus) can inhibit both gonadotropin-releasing hormone (GnRH)/luteinizing hormone secretion and female copulatory behaviors. Decreases in metabolic fuel availability appear to be detected by cells in the caudal hindbrain. Hindbrain neurons producing neuropeptide Y (NPY) and catecholamines (CA) then project to the forebrain where they contact GnRH neurons both directly and also indirectly via corticotropin-releasing hormone (CRH) neurons to inhibit GnRH secretion. In the case of estrous behavior, the best available evidence suggests that the inhibitory NPY/CA system acts primarily via CRH or urocortin projections to various forebrain loci that control sexual receptivity. Disruption of these signaling processes allows normal reproduction to proceed in the face of energetic deficits, indicating that the circuitry responds to energy deficits and that no signal is necessary to indicate that there is an adequate energy supply. While there is a large body of evidence to support this hypothesis, the data do not exclude nutritional inhibition of reproduction by other pathways and processes, and the full story will undoubtedly be more complex than this.
281 citations
TL;DR: This bridge between genetics and other parts of biology shows that the various theories apparently causing concern for the modern synthetic theory of evolution are entirely compatible with it.
Abstract: ummary
We have provided a bridge between geneticists, who tend to concentrate on genes and their frequencies, and other biologists, who are much more aware of how severely the environment constrains and limits life. This bridge is the recognition that
a. fitness is a product of important component traits,
b. these and most other traits consume environmental resources and these resources are additively related and can sum to no more than the total resources an animal can obtain from the environment,
c. allele frequencies can alter only to the degree that the phenotypes that carry the alleles reproduce themselves successfully, i. e. are fit,
d. fitness must rise, because it is never free from natural selection upwards, to the point where it can rise no further, because all environmental resources available to an animal are being used most efficiently,
e. in this state of adaptation, fitness is completely limited by the environment and all other traits important to the animal are constrained to a greater or lesser degree at intermediate, “optimal” values, and
f. traits or molecules unimportant to animals, so that they are completely neutral with respect to fitness, are free to drift genetically and hence gene substitutions can occur at rates related to their mutation rates.
This bridge between genetics and other parts of biology shows that the various theories apparently causing concern for the modern synthetic theory of evolution are entirely compatible with it. Bursts of rapid evolutionary change between long periods of evolutionary stasis are the necessary consequences of strong natural selection acting on fitness, in ecosystems that are stable until external forces cause them to change. Neutral (random) evolution describes the fate of genetic material that is unimportant for organisms, i. e. material that is truly neutral with respect to fitness.
Zusammenfassung
Quantitative Genetik und Evolution. Genugt unser genetisches Verstandnis um Evolution zu erklaren?
Wir bauten eine Brucke zwischen Genetikern, die mit Genen und ihren Frequenzen arbeiten, und anderen Biologen, die wissen wie stark die Umwelt Lebewesen hemmend beeinflust. Diese Brucke besteht aus den folgenden Erkenntnissen:
a. Fitness ist ein Produkt der wichtigsten Komponenten.
b. Diese und die meisten anderen Merkmale verbrauchen Nahrung. Die Nahrung, die ein Lebewesen nur aus der Umwelt erhalten kann, enthalt die maximale Summe der metabolischen Ressourcen, die das Wesen dann in additiver Weise in einzelne Merkmale investiert.
c. Allelfrequenzen konnen sich nur erhohen, wenn der Phanotyp, der die Allele tragt, sich erfolgreich fortpflanzt.
d. Weil Fitness immer unter naturlicher Selektion nach oben steht, mus der Fitnesswert steigen bis alle Umweltressourcen so effizient wie moglich genutzt werden.
e. In solchem Stadium der volligen Anpassung an die Umwelt, ist Fitness ganz durch die Umwelt limitiert und alle anderen wichtigen Merkmale in groserem oder kleinerem Mase in Optimalwerte gezwangt.
f. Unwichtige Merkmale oder genetische Molekule, die keine Wirkung im Lebewesen haben, so das sie wirklich neutral sind gegenuber Fitness, durfen ungehemmt driften und zeigen deshalb Substitutionsraten, die ihren Mutationsraten entsprechen.
Diese Brucke zwischen Genetik und der ubrigen Biologie zeigt, das die Evolutionstheorien, die angeblich die moderne Evolutionssynthese storen, vollkommen mit ihr im Einklang sind. Sprungartige Evolution zwischen langen, stabilen Zeitraumen sind die Zwangsfolgen starker naturlicher Selektion auf Fitness in Okosystemen, die sich nicht andern bis ein Druck auserhalb des Systems das bewirkt. Neutrale Evolution beschreibt, was mit dem Material passiert, das unwichtig fur Lebewesen ist.
178 citations
01 Jan 2010
171 citations
"Genetic Relationships under Differe..." refers background or methods in this paper
...By means of REML and the soft ware package VCE6 (Groeneveld et al., 2010), bivariate models, treating the respective traits as separate traits in both environments, were used to estimate heritabilities and genetic correlations....
[...]
...In such analyses, when observations of an animal may only be found in either of the two environments, the residual covariance is omitted by VCE6 (Groeneveld et al., 2010)....
[...]