Genotype by environment interaction in Nelore cattle from five Brazilian states

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10%) during selection.     

Comparison of breeding value prediction for two traits in a Nellore-Angus crossbred population using different Bayesian modeling methodologies

The objectives of this study were to 1) compare four models for breeding value prediction using genomic or pedigree information and 2) evaluate the impact of fixed effects that account for family structure. Comparisons were made in a Nellore-Angus population comprising F₂, F₃ and half-siblings to embryo transfer F₂ calves with records for overall temperament at weaning (TEMP; n = 769) and Warner-Bratzler shear force (WBSF; n = 387). After quality control, there were 34,913 whole genome SNP markers remaining. Bayesian methods employed were BayesB ($\tilde{\pi }$ = 0.995 or 0.997 for WBSF or TEMP, respectively) and BayesC (π = 0 and $\tilde{\pi }$), where $\tilde{\pi }$ is the ideal proportion of markers not included. Direct genomic values (DGV) from single trait Bayesian analyses were compared to conventional pedigree-based animal model breeding values. Numerically, BayesC procedures (using $\tilde{\pi }$) had the highest accuracy of all models for WBSF and TEMP ($\widehat{\rho }$_gĝ = 0.843 and 0.923, respectively), but BayesB had the least bias (regression of performance on prediction closest to 1, $\widehat{\beta }$_y,x = 2.886 and 1.755, respectively). Accounting for family structure decreased accuracy and increased bias in prediction of DGV indicating a detrimental impact when used in these prediction methods that simultaneously fit many markers.     

Exploration of lagged relationships between mastitis and milk yield in dairycows using a Bayesian structural equation Gaussian-threshold model

A Gaussian-threshold model is described under the general framework of structural equation models for inferring simultaneous and recursive relationships between binary and Gaussian characters, and estimating genetic parameters. Relationships between clinical mastitis (CM) and test-day milk yield (MY) in first-lactation Norwegian Red cows were examined using a recursive Gaussian-threshold model. For comparison, the data were also analyzed using a standard Gaussian-threshold, a multivariate linear model, and a recursive multivariate linear model. The first 180 days of lactation were arbitrarily divided into three periods of equal length, in order to investigate how these relationships evolve in the course of lactation. The recursive model showed negative within-period effects from (liability to) CM to test-day MY in all three lactation periods, and positive between-period effects from test-day MY to (liability to) CM in the following period. Estimates of recursive effects and of genetic parameters were time-dependent. The results suggested unfavorable effects of production on liability to mastitis, and dynamic relationships between mastitis and test-dayMYin the course of lactation. Fitting recursive effects had little influence on the estimation of genetic parameters. However, some differences were found in the estimates of heritability, genetic, and residual correlations, using different types of models (Gaussian-threshold vs. multivariate linear).     

Markov chain Monte Carlo fitting of single-channel data from inositol trisphosphate receptors

In many cell types, the inositol trisphosphate receptor (IPR) is one of the important components that control intracellular calcium dynamics, and an understanding of this receptor (which is also a calcium channel) is necessary for an understanding of calcium oscillations and waves. Recent advances in experimental techniques now allow for the measurement of single-channel activity of the IPR in conditions similar to its native environment, and these data can be used to determine the rate constants in Markov models of the IPR. We illustrate a parameter estimation method based on Markov chain Monte Carlo, which can be used to fit directly to single-channel data, and determining, as an intrinsic part of the fit, the times at which the IPR is opening and closing. We show, using simulated data, the most complex Markov model that can be unambiguously determined from steady-state data and show that non-steady-state data is required to determine more complex models.     

使用多因素易患性阈值模型评估双相情感障碍的遗传度缺失

为了评估双向情感障碍的遗传度缺失,文章通过查询美国国家人类基因组研究所(National Human Genome Research Institute,NHGRI)的gwascatalog目录,检索出所有已发现的双相情感障碍易感变异,使用多因素易患性阈值模型计算每个易感变异对双相情感障碍遗传度的解释度。将所有易感变异遗传度解释度求和得到双相情感障碍已知易感变异对遗传度的总解释度,使用此总解释度评估双相情感障碍的遗传度缺失。结果显示,已知双相情感障碍易感变异对双相情感障碍遗传度的合计解释度为38.34%,尚有61.66%的遗传度无法被已有易感变异解释,属于遗传度缺失。双相情感障碍38.34%的遗传度解释度较早前国外同类研究大幅度提高,表明随着新的双相情感障碍易感变异被不断发现,双相情感障碍遗传度缺失得到大幅度减小。但双相情感障碍遗传度缺失依然存在且数目较大的事实也表明双相情感障碍尚存在许多未知的分子遗传学机制有待进一步阐明。     

Genomics of isolation in hybrids

Hybrid zones are common in nature and can offer critical insights into the dynamics and components of reproductive isolation. Hybrids between diverged lineages are particularly informative about the genetic architecture of reproductive isolation, because introgression in an admixed population is a direct measure of isolation. In this paper, we combine simulations and a new statistical model to determine the extent to which different genetic architectures of isolation leave different signatures on genome-level patterns of introgression. We found that reproductive isolation caused by one or several loci of large effect caused greater heterogeneity in patterns of introgression than architectures involving many loci with small fitness effects, particularly when isolating factors were closely linked. The same conditions that led to heterogeneous introgression often resulted in a reasonable correspondence between outlier loci and the genetic loci that contributed to isolation. However, demographic conditions affected both of these results, highlighting potential limitations to the study of the speciation genomics. Further progress in understanding the genomics of speciation will require large-scale empirical studies of introgression in hybrid zones and model-based analyses, as well as more comprehensive modelling of the expected levels of isolation with different demographies and genetic architectures of isolation.     

Spread of Q fever within dairy cattle herds: key parameters inferred using a Bayesian approach

Q fever is a worldwide zoonosis caused by Coxiella burnetii. Although ruminants are recognized as the most important source of human infection, no previous studies have focused on assessing the characteristics of the bacterial spread within a cattle herd and no epidemic model has been proposed in this context. We assess the key epidemiological parameters from field data in a Bayesian framework that takes into account the available knowledge, missing data and the uncertainty of the observation process owing to the imperfection of diagnostic tests. We propose an original individual-based Markovian model in discrete time describing the evolution of the infection for each animal. Markov chain Monte Carlo methodology is used to estimate parameters of interest from data consisting of individual health states of 217 cows of five chronically infected dairy herds sampled every week for a four-week period. Outputs are the posterior distributions of the probabilities of transition between health states and of the environmental bacterial load. Our findings show that some herds are characterized by a very low infection risk while others have a mild infection risk and a non-negligible intermittent shedding probability. Moreover, the antibody status seems to be a key point in the bacterial spread (shedders with antibodies shed for a longer period of time than shedders without antibodies). In addition to the biological insights, these estimates also provide information for calibrating simulation models to assess control strategies for C. burnetii infection.     

Heritability of short-scale natal dispersal in a large-scale foraging bird, the wandering albatross

Natal dispersal is a key life history trait for the evolution and adaptation of wild populations. Although its evolution has repeatedly been related to the social and environmental context faced by individuals, parent-offspring regressions have also highlighted a possible heritable component. In this study, we explore heritability of natal dispersal, at the scale of the sub-Antarctic Possession Island, for a large-scale foraging seabird, the Wandering albatross Diomedea exulans, exploiting a pedigree spanning over four decades and a maximum of four generations. The comparison of three different methods shows that heritability on the liability scale can vary drastically depending on the type of model (heritability from 6% to 86%), with a notable underestimation by restricted maximum likelihood animal models (6%) compared to Bayesian animal models (36%). In all cases, however, our results point to significant additive genetic variance in the individual propensity to disperse, after controlling for substantial effects of sex and natal colony. These results reveal promising evolutionary potential for short-scale natal dispersal, which could play a critical role for the long-term persistence of this species on the long run.