976 resultados para Genetic parameters


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We described the patterns and extent of microsatellite DNA variation in historical and present-day Atlantic salmon (Salmo salar L.) stocks in the Baltic Sea and neighbouring areas, and in European whitefish (Coregonus lavaretus) ecotypes, populations and run-timing types in Finland. Moreover, the amount and pattern of genetic diversity in historical salmon populations before human impact were described, and the proportion of diversity maintained in the present hatchery stocks evaluated. Salmon populations in the Baltic Sea were, on average, significantly less variable than eastern Atlantic populations, and the diversity of landlocked populations (Lakes Vänern, Saimaa, Onega and Ladoga) was in turn significantly lower than that of anadromous salmon populations in the Baltic Sea populations. Within the Baltic Sea, the anadromous populations of Atlantic salmon formed three clear groups, corresponding to the northern (Gulf of Bothnia), eastern (Gulf of Finland and eastern Baltic Main Basin) and southern (western Baltic Main Basin) regions. Based on microsatellite data, three salmon population groups in the Baltic Sea were considered potentially different colonization lineages. In short- and long-term breeding programmes of Atlantic salmon, the average observed rate of loss of alleles was 4.9% and 2.0% per generation and the average rate of loss of heterozygosity was 1.4% and 1% per generation, respectively. When comparing the genetic parameters of stocks before and after hatchery breeding of several successive generations (Rivers Iijoki and Oulujoki), statistically significant changes in allele frequencies were common, while large wild stock in the Teno River has remained temporally very stable over 56 years. Despite the observed losses of genetic diversity in broodstock breeding, a large proportion of the genetic resources of the extirpated stocks are still conserved in the broodstocks. Genetic differentiation among European whitefish ecotypes was generally low, thus giving support to the hypothesis of one native European whitefish species in Fennoscandia. Among the ecotypes, the northern, large sparsely rakered, bottom-dwelling whitefish was the most unique. The known genetic differences in quantitative traits have thus either developed independently of potential phylogenetic lineages, or the lineages have mixed and the quantitative traits of the ecotypes, like gill-raker number, have later changed according to environment and selection pressures. Overall, genetic distances between the anadromous whitefish populations along the Finnish coast, especially in the Bothnian Bay area, were small. Wild whitefish populations studied had slightly higher allelic diversity than hatchery-reared populations in corresponding rivers.

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Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.

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The main objective of this thesis was to determine the potential impact of heat stress (HS) on physiological traits of lactating cows and semen quality of bulls kept in a temperate climate. The thesis is comprised of three studies. An innovative statistical modeling aspect common to all three studies was the application of random regression methodology (RRM) to study the phenotypic and genetic trajectory of traits in dependency of a continuous temperature humidity index (THI). In the first study, semen quality and quantity traits of 562 Holstein sires kept on an AI station in northwestern Germany were analyzed in the course of THI calculated from data obtained from the nearest weather station. Heat stress was identified based on a decline in semen quality and quantity parameters. The identified general HS threshold (THI = 60) and the thermoneutal zone (THI in the range from 50 to 60) for semen production were lower than detected in studies conducted in tropical and subtropical climates. Even though adult bulls were characterized by higher semen productivity compared to younger bulls, they responded with a stronger semen production loss during harsh environments. Heritabilities (low to moderate range) and additive genetic variances of semen characteristics varied with different levels of THI. Also, based on genetic correlations genotype, by environment interactions were detected. Taken together, these findings suggest the application of specific selection strategies for specific climate conditions. In the second study, the effect of the continuous environmental descriptor THI as measured inside the barns on rectal temperatures (RT), skin temperatures (ST), vaginal temperatures (VT), respiration rates (RR), and pulse rate (PR) of lactating Holstein Friesian (HF) and dual-purpose German black pied cattle (DSN) was analyzed. Increasing HS from THI 65 (threshold) to THI 86 (maximal THI) resulted in an increase of RT by 0.6 °C (DSN) and 1 °C (HF), ST by 3.5 °C (HF) and 8 °C (DSN), VT by 0.3 °C (DSN), and RR by 47 breaths / minute (DSN), and decreased PR by 7 beats / minute (DSN). The undesired effects of rising THI on physiological traits were most pronounced for cows with high levels of milk yield and milk constituents, cows in early days in milk and later parities, and during summer seasons in the year 2014. In the third study of this dissertation, the genetic components of the cow’s physiological responses to HS were investigated. Heat stress was deduced from indoor THI measurements, and physiological traits were recorded on native DSN cows and their genetically upgraded crosses with Holstein Friesian sires in two experimental herds from pasture-based production systems reflecting a harsh environment of the northern part of Germany. Although heritabilities were in a low range (from 0.018 to 0.072), alterations of heritabilities, repeatabilities, and genetic components in the course of THI justify the implementation of genetic evaluations including heat stress components. However, low repeatabilities indicate the necessity of using repeated records for measuring physiological traits in German cattle. Moderate EBV correlations between different trait combinations indicate the potential of selection for one trait to simultaneously improve the other physiological attributes. In conclusion, bulls of AI centers and lactating cows suffer from HS during more extreme weather conditions also in the temperate climate of Northern Germany. Monitoring physiological traits during warm and humid conditions could provide precious information for detection of appropriate times for implementation of cooling systems and changes in feeding and management strategies. Subsequently, the inclusion of these physiological traits with THI specific breeding values into overall breeding goals could contribute to improving cattle adaptability by selecting the optimal animal for extreme hot and humid conditions. Furthermore, the recording of meteorological data in close distance to the cow and visualizing the surface body temperature by infrared thermography techniques might be helpful for recognizing heat tolerance and adaptability in cattle.

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Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

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It is well established in genetic epidemiology that family history is an important indicator of familial aggregation of disease in a family. A strong genetic risk factor or an environmental risk factor with high familial correlation can result in a strong family history. In this paper, family history refers to the number of first-degree relatives affected with the disease. Cui and Hopper (Journal of Epidemiology and Biostatistics 2001; 6: 331-342) proposed an analytical relationship between family history and relevant genetic parameters. In this paper we expand the relationship to both genetic and environmental risk factors. We established a closed-form formula for family history as a function of genetic and environmental parameters which include genetic and environmental relative risks, genotype frequency, prevalence and familial correlation of the environmental risk factor. The relationship is illustrated by an example of female breast cancer in Australia. For genetic and environmental relative risks less than 10, most of the female breast cancer cases occur between the age of 40 and 60 years. A higher genetic or environmental relative risk will move the peak of the distribution to a younger age. A more common disease allele or more prevalent environmental risk factor will move the peak to an older age. For a proband with breast cancer, it is most likely (with probability ge80%) that none of her first-degree relatives is affected with the disease. To enable the probability of having a positive family history to reach 50%, the environmental relative risks must be extremely as high as 100, the familial correlation as high as 0.8 and the prevalence as low as 0.1. For genetic risk alone, even the relative risk is as high as 100, the probability of having a positive family history can only reach about 30%. This suggests that the environmental risk factor seems to play a more important role in determining a strong family history than the genetic risk factor.

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The effect of competition is an important source of variation in breeding experiments. This study aimed to compare the selection of plants of open-pollinated families of Eucalyptus with and without the use of competition covariables. Genetic values were determined for each family and tree and for the traits height, diameter at breast height and timber volume in a randomized block design, resulting in the variance components, genetic parameters, selection gains, effective size and selection coincidence, with and without the use of covariables. Intergenotypic competition is an important factor of environmental variation. The use of competition covariables generally reduces the estimates of variance components and influences genetic gains in the studied traits. Intergenotypic competition biases the selection of open-pollinated eucalypt progenies, and can result in an erroneous choice of superior genotypes; the inclusion of covariables in the model reduces this influence.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Records of Nellore animals born from 1990 to 2006 were used to estimate genetic correlations of visual scores at yearling (conformation, C; finishing precocity, P; and muscling, M) with primiparous subsequent rebreeding (SR) and days to first calving (DC), because the magnitude of these associations is still unknown. Genetic parameters were estimated by multiple-traits Bayesian analysis, using a nonlinear (threshold) animal models for visual scores and SR and a linear animal models for weaning weight (WW) and DC. WW was included in the analysis to account for the effects of sequential selection. The posterior means of heritabilities estimated for C, P, M, SR and DC were 0.24 +/- 0.01, 0.31 +/- 0.01, 0.30 +/- 0.01, 0.18 +/- 0.02 and 0.06 +/- 0.02, respectively. The posterior means of genetic correlations estimated between SR and visual scores were low and positive, with values of 0.09 +/- 0.02 (C), 0.19 +/- 0.03 (P) and 0.18 +/- 0.05 (M). on the other hand, negative genetic correlations were found between DC and C (-0.11 +/- 0.09), P (-0.19 +/- 0.09) and M (-0.16 +/- 0.09). The primiparous rebreeding trait has genetic variability in Nellore cattle. The genetic correlations between visual scores, and SR and DC were low and favourable. The genetic changes in C, P and M were 0.02, 0.03 and 0.03/year, respectively. For SR and DC, genetic trends were 0.01/year and -0.01 days/year, respectively, indicating that the increase in genetic merit for reproductive traits was small over time. Direct selection for visual scores together with female reproductive traits is recommended to increase the fertility of beef cows.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)