scholarly journals Genetic Analysis of Several Economically Important Disease Traits in German Holstein Cows

2006 ◽  
Vol 49 (3) ◽  
pp. 209-221
Author(s):  
D. Hinrichs ◽  
E. Stamer ◽  
W. Junge ◽  
E. Kalm
Keyword(s):  
Genetic Structure ◽  
Genetic Analysis ◽  
Genetic Correlation ◽  
Metabolic Diseases ◽  
Genetic Correlations ◽  
Holstein Cows ◽  
Data Recording ◽  
The Impact ◽  
All Diseases ◽  
Important Disease

Abstract. In the present study several disease categories were analysed. Data recording ends after 50, 100, or 300 days in milk. Furthermore, the impact of increasing numbers of daughters per sire (improved genetic structure of the data) was examined and genetic correlations between disease categories were estimated. Diseases were clustered into fertility diseases, udder diseases, metabolic diseases, and claw and leg diseases. In addition, all diseases were analysed simultaneously. Frequencies of the disease categories were moderately high and vary between 7% and 78%. The most frequent disease categories were fertility diseases and udder diseases. Heritabilities for all diseases varied between 0.03 and 0.05, and were 0.02 to 0.05 for fertility diseases, 0.06 to 0.08 for udder diseases, 0.08 to 0.16 for metabolic diseases, and 0.01 to 0.03 for claw and leg diseases, respectively. The genetic correlation between disease categories ranged from – 0.18 to 0.82.

scholarly journals Genetic analysis of tolerance to infections using random regressions: a simulation study

2011 ◽  
Vol 93 (4) ◽  
pp. 291-302 ◽  
Author(s):  
ANTTI KAUSE
Keyword(s):  
Genetic Analysis ◽  
Genetic Correlation ◽  
Simulation Study ◽  
Genetic Variance ◽  
Genetic Correlations ◽  
Experimental Conditions ◽  
Covariance Functions ◽  
Threshold Trait ◽  
Pathogen Burden ◽  
The Impact

SummaryTolerance to infections is the ability of a host to limit the impact of a given pathogen burden on host performance. This simulation study demonstrated the merit of using random regressions to estimate unbiased genetic variances for tolerance slope and its genetic correlations with other traits, which could not be obtained using the previously implemented statistical methods. Genetic variance in tolerance was estimated as genetic variance in regression slopes of host performance along an increasing pathogen burden level. Random regressions combined with covariance functions allowed genetic variance for host performance to be estimated at any point along the pathogen burden trajectory, providing a novel means to analyse infection-induced changes in genetic variation of host performance. Yet, the results implied that decreasing family size as well as a non-zero environmental or genetic correlation between initial host performance before infection and pathogen burden led to biased estimates for tolerance genetic variance. In both cases, genetic correlation between tolerance slope and host performance in a pathogen-free environment became artificially negative, implying a genetic trade-off when it did not exist. Moreover, recording a normally distributed pathogen burden as a threshold trait is not a realistic way of obtaining unbiased estimates for tolerance genetic variance. The results show that random regressions are suitable for the genetic analysis of tolerance, given suitable data structure collected either under field or experimental conditions.

scholarly journals The Impact on Estimations of Genetic Correlations of the Use, in Genome Wide Case-Control Studies, of Super-Normal, Unscreened and Family-History Screened Controls

2019 ◽  
Author(s):  
Kenneth S. Kendler ◽  
Chris Chatzinakos ◽  
Silviu-Alin Bacanu
Keyword(s):  
Genetic Correlation ◽  
Genetic Correlations ◽  
Case Control ◽  
Case Control Studies ◽  
Minimal Impact ◽  
Genome Wide ◽  
Unbiased Estimates ◽  
The Impact ◽  
Gwa Studies ◽  
Normal Controls

ABSTRACTTraditionally, in normal case-control studies of disorder A, individuals with disorder A are screened-out of controls. However, in genome wide association (GWA) studies, controls are sometimes unscreened or screened for disorder A and disorder B, producing super-normal controls. Using simulations, we examine how the observed genetic correlations between two disorders (A and B) are influenced by the use of unscreened, normal, and super-normal controls. Normal controls produce unbiased estimates of the genetic correlation. However, unscreened and super-normal controls both bias upward the genetic correlations. The strength of the bias increases with increasing population prevalences for the two disorders. With super-normal controls, the magnitude of bias is stronger when the true genetic correlation is low. The opposite is seen with the use of unscreened controls. Adding screening of first-degree relatives of controls substantially increases the bias in genetic correlations with super-normal controls but has minimal impact when normal controls are used.

A preliminary genetic analysis of breech and tail traits with the aim of improving the welfare of sheep

2007 ◽  
Vol 58 (2) ◽  
pp. 161 ◽  
Author(s):  
D. R. Scobie ◽  
D. O'Connell ◽  
C. A. Morris ◽  
S. M. Hickey
Keyword(s):  
New Zealand ◽  
Genetic Analysis ◽  
Genetic Correlation ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Linear Scale ◽  
Bare Area ◽  
Phenotypic Correlations ◽  
Tail Docking

The area of naturally bare skin around the perineum was scored at weaning in lambs (n = 2152) from a composite flock of New Zealand crossbred sheep. Breech bareness was scored on a range from 1, where wool was growing right to the edges of the anus, to 5, where a large bare area surrounded the perineum. Bareness on the under surface of the tail was measured on a linear scale at tail docking. Dag score (degree of breech soiling) was recorded at weaning, on a scale of 0–5, where an increasing score indicated more dags. Dag score was taken as a measure of the risk of flystrike in the breech. Female lambs tended to have slightly greater (P < 0.001) breech bareness score (mean score 2.7) than males (mean score 2.6), whereas mean dag score of females was lower than that of males (0.45 v. 0.53; P < 0.05). Breech bareness score had a heritability of 0.33 ± 0.06, and the length of bare skin under the tail had a heritability of 0.59 ± 0.06. The genetic correlation between breech bareness score at weaning and length of bare skin under the tail at docking was positive (0.35 ± 0.10). These 2 traits had phenotypic correlations with dag score of –0.17 ± 0.02 and –0.03 ± 0.03, respectively, and genetic correlations with dag score of –0.30 ± 0.13 and 0.03 ± 0.12, respectively; negative values indicated a favourable relationship. Tails were removed at docking, so the phenotypic correlation of about zero between tail data and dag score at weaning was of little utility. Our results suggest that selecting for these 2 bareness traits could reduce dag formation and the associated risk of breech strike.

Evaluation of repeatability and pre-structured repeatability models for genetic analyses of repeated records of fat and protein contents of milk in Iranian Holstein cows

2018 ◽  
Vol 58 (11) ◽  
pp. 1983
Author(s):  
M. Asadi Fozi
Keyword(s):  
Genetic Analysis ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Holstein Cows ◽  
Phenotypic Correlation ◽  
Genetic Covariance ◽  
Future Studies ◽  
Phenotypic Correlations ◽  
Variance Structure

Fat and protein content of milk measurements from first to fifth lactations of Iranian Holstein cows were analysed using repeatability and several pre-structured repeatability models that varied in additive genetic variance structure and fitted heterogeneous residual co (variance). For this research, a total of 257 197 fat and 218 688 protein records were used. The records were measured on 116 531 cows born between 2010 and 2014. The animals originated from 2355 sires and 91 212 dams. Pre-structured repeatability models with heterogeneous residual co (variance) and the respective genetic variance structure were the best models for genetic analysis of the fat and protein data. The results derived from these models showed that heritability of both fat and protein are decreased from first to fifth lactations. Heritability of fat measured at first, second, third, fourth and fifth locations were between 0.10 and 0.19 and those for protein were between 0.07 and 0.24. Moderate to high phenotypic correlations were estimated between the repeated records of the fat and protein. Values of 0.13 and 0.16 were estimated for heritability of fat and protein using repeatability model. Phenotypic correlations among the repeated records of fat and protein were estimated to be 0.30 and 0.33, respectively when this model was applied. The results showed the genetic variance, heritability and phenotypic correlation of the fat and protein are changed over the lactations but the genetic parameters derived from the repeatability model are homogenous whereas in both models unity genetic correlations are assumed among the repeated records. The results of this study show that the repeatability model is not an appropriate model for genetic analysis of the repeated records of fat and protein in the population investigated and can be improved when pre-structured repeatability model is used. In the present study homogenous genetic covariance was assumed among the fat and protein taken at the different lactations which can be modelled in future studies for more improving the models.

Genetic analysis of growth traits in Mecheri sheep

2015 ◽  
Author(s):  
V. Jeichitra ◽  
R. Rajendran ◽  
K. Karunanithi ◽  
P. S. Rahumathulla
Keyword(s):  
Genetic Analysis ◽  
Genetic Correlation ◽  
Genetic Control ◽  
South India ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Research Station ◽  
Body Weights ◽  
Weight Gains

Data on 1763 Mecheri sheep, maintained at the Mecheri Sheep Research Station, Pottaneri, Salem, south India, and recorded between 1991 and 2006, were analysed to study the growth related traits and their genetic control. The average weights at birth and at 12 months of age were 2.25 ± 0.01 and 17.48 ± 0.14 kg, respectively. The pre- and post-weaning (3-6, 3-9 and 3-12) average daily weight gains were 63.40 ± 0.58, 39.57 ± 0.57, 37.48 ± 0.44 and 34.31 ± 0.42 g respectively. The heritabilities of body weights and weight gains were in general moderate to high. The phenotypic and genetic correlations among body weights were positive and moderate to high. The phenotypic and genetic correlations among average daily gains were positive and low to high. The estimates of genetic correlation among average daily gains and body weights were positive and high with few exceptions.

scholarly journals Genetic Analysis of Several Disease Categories Using Test Day Threshold Models in German Holstein Cows

2006 ◽  
Vol 49 (1) ◽  
pp. 3-16
Author(s):  
D. Hinrichs ◽  
E. Stamer ◽  
W. Junge ◽  
E. Kalm
Keyword(s):  
Metabolic Disease ◽  
Variance Components ◽  
Metabolic Diseases ◽  
Threshold Model ◽  
Data Sets ◽  
Threshold Models ◽  
Lactation Length ◽  
Disease Information ◽  
The Impact ◽  
All Diseases

Abstract. In the present study trajectories for the disease categories udder diseases, metabolic diseases, all diseases, fertility diseases, and ovarian problems, are described. Variance components were estimated where the considered period of lactation varies between 50 and 300 days. Furthermore, the impact of the number of daughters per sire was analysed with disease information from the first 50 days of lactation. In total 18 data sets were analysed with a test day threshold model. The average disease frequencies were between 6.5% and 2.7% for udder diseases and they were between 1.7% and 0.4%, and 15.3% and 6.0% for metabolic diseases and 'all diseases', respectively. For udder diseases the estimated heritabilities vary between 0.12 and 0.25 depending on lactation length and the number of daughters per sire. For metabolic disease heritabilities were estimated within the interval of 0.12 to 0.24. Depending on the lactation length the heritabilities of all diseases were fairly constant (0.03 to 0.04). The heritabilities of all diseases increased if fertility diseases were excluded. Those estimates vary between 0.15 to 0.19.

Genetic and Environmental Influences on Executive Functions and Intelligence in the ABCD Study

2020 ◽  
Author(s):  
Samantha M Freis ◽  
Claire Morrison ◽  
Jeffrey M. Lessem ◽  
John K. Hewitt ◽  
Naomi P. Friedman
Keyword(s):  
Cognitive Development ◽  
Executive Functions ◽  
Genetic Correlation ◽  
Middle Childhood ◽  
Middle Age ◽  
Environmental Influences ◽  
Genetic Correlations ◽  
Twin Studies

Executive functions (EFs) and intelligence (IQ) are phenotypically correlated and heritable; however, they show variable genetic correlations in twin studies spanning childhood to middle age. We analyzed data from over 11,000 children (9-10-year-olds, including 749 twin pairs) in the Adolescent Brain Cognitive Development (ABCD) Study to examine the phenotypic and genetic relations between EFs and IQ in childhood. We identified two EF factors – Common EF and Updating-Specific, which were both related to IQ (rs = .64-.81). Common EF and IQ were heritable (53-67%), and their genetic correlation (rG = .86) was not significantly different than 1. These results suggest that EFs and IQ are phenotypically but not genetically separable in middle childhood.

Covid-19 In Man: A Very Dangerous Affair.

2021 ◽  
Vol 21 ◽  
Author(s):  
Giuseppe Lisco ◽  
Vito A. Giagulli ◽  
Giovanni De Pergola ◽  
Anna De Tullio ◽  
Edoardo Guastamacchia ◽  
...  
Keyword(s):  
Poor Prognosis ◽  
Metabolic Diseases ◽  
Systemic Disease ◽  
Public Health Issue ◽  
Immune System Dysfunction ◽  
Data Support ◽  
Systemic Spread ◽  
The Impact

Background: The novel pandemic of Coronavirus disease 2019 (COVID-19) has becoming a public health issue since March 2020 considering that more than 30 million people were found to be infected worldwide. Particularly, recent evidences suggested that men may be considered as at higher risk of poor prognosis or death once the infection occurred and concerns surfaced in regard of the risk of a possible testicular injury due to SARS-CoV-2 infection. Results: Several data support the existence of a bivalent role of testosterone (T) in driving poor prognosis in patients with COVID-19. On one hand, this is attributable to the fact that T may facilitate SARS-CoV-2 entry in human cells by means of an enhanced expression of transmembrane serine-protease 2 (TMPRSS2) and angiotensin-converting enzyme 2 (ACE2). At the same time, younger man with normal testicular function compared to women of similar age are prone to develop a blunted immune response against SARS-CoV-2, being exposed to less viral clearance and more viral shedding and systemic spread of the disease. Conversely, low levels of serum T observed in hypogonadal men predispose them to a greater background systemic inflammation, cardiovascular and metabolic diseases, and immune system dysfunction, hence driving harmful consequences once SARS-CoV-2 infection occurred. Finally, SARS-CoV-2, as a systemic disease, may also affect testicles with possible concerns for current and future testicular efficiency. Preliminary data suggested that SARS-CoV-2 genome is not normally found in gonads and gametes, therefore sex transmission could be excluded as a possible way to spread the COVID-19. Conclusion: Most data support a role of T as a bivalent risk factor for poor prognosis (high/normal in younger; lower in elderly) in COVID-19. However, the impact of medical treatment aimed to modify T homeostasis for improving the prognosis of affected patients is unknown in this clinical setting. In addition, testicular damage may be a harmful consequence of the infection even in case it occurred asymptomatically but no long-term evidences are currently available to confirm and quantify this phenomenon. Different authors excluded the presence of SARS-CoV-2 in sperm and oocytes, thus limiting worries about both a potential sexual and gamete-to-embryos transmission of COVID-19. Despite these evidence, long-term and well-designed studies are needed to clarify these issues.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

scholarly journals Impact of cyclones on hard coral and metapopulation structure, connectivity and genetic diversity of coral reef fish

Coral Reefs ◽  
2021 ◽  
Author(s):  
Gabriele Gerlach ◽  
Philipp Kraemer ◽  
Peggy Weist ◽  
Laura Eickelmann ◽  
Michael J. Kingsford
Keyword(s):  
Genetic Diversity ◽  
Coral Reef ◽  
Genetic Structure ◽  
Reef Fish ◽  
Coral Reef Fish ◽  
Population Genetic Study ◽  
Hard Coral ◽  
Great Loss ◽  
Metapopulation Structure ◽  
The Impact

AbstractCyclones have one of the greatest effects on the biodiversity of coral reefs and the associated species. But it is unknown how stochastic alterations in habitat structure influence metapopulation structure, connectivity and genetic diversity. From 1993 to 2018, the reefs of the Capricorn Bunker Reef group in the southern part of the Great Barrier Reef were impacted by three tropical cyclones including cyclone Hamish (2009, category 5). This resulted in substantial loss of live habitat-forming coral and coral reef fish communities. Within 6–8 years after cyclones had devastated, live hard corals recovered by 50–60%. We show the relationship between hard coral cover and the abundance of the neon damselfish (Pomacentrus coelestis), the first fish colonizing destroyed reefs. We present the first long-term (2008–2015 years corresponding to 16–24 generations of P. coelestis) population genetic study to understand the impact of cyclones on the meta-population structure, connectivity and genetic diversity of the neon damselfish. After the cyclone, we observed the largest change in the genetic structure at reef populations compared to other years. Simultaneously, allelic richness of genetic microsatellite markers dropped indicating a great loss of genetic diversity, which increased again in subsequent years. Over years, metapopulation dynamics were characterized by high connectivity among fish populations associated with the Capricorn Bunker reefs (2200 km2); however, despite high exchange, genetic patchiness was observed with annual strong genetic divergence between populations among reefs. Some broad similarities in the genetic structure in 2015 could be explained by dispersal from a source reef and the related expansion of local populations. This study has shown that alternating cyclone-driven changes and subsequent recovery phases of coral habitat can greatly influence patterns of reef fish connectivity. The frequency of disturbances determines abundance of fish and genetic diversity within species.

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