scholarly journals Categorical Visual Score Traits of a Nellore Beef Cattle Population

2017 ◽  
Vol 9 (8) ◽  
pp. 63
Author(s):  
Jairo Azevedo Junior ◽  
Juliana Petrini ◽  
Gerson Barreto Mourão ◽  
José Bento Sterman Ferraz
Keyword(s):  
Variance Components ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Genetic Correlations ◽  
Estimation Method ◽  
Analysis Data ◽  
Suitable Model ◽  
Linear Distribution ◽  
Tropical Regions ◽  
Trait Analysis

Variance components and genetic parameters of economically relevant traits in livestock, whether continuous or categorical, can be estimated by methods computationally available providing support for the selection and mating of animals in breeding programs. The objectives of this paper were to obtain and compare the variance components estimates for visual traits under continuous or categorical distribution in single-trait analysis and their correlations with continuous productive traits in two-trait analysis. Data of conformation (CONF), precocity of fat deposition (PREC) and muscling (MUSC) visual scores evaluated at 18 months of age as well as the weight at 18 months of age (YW) were collected from animals born from 2000 to 2012, in Nellore cattle herds raised in Southeastern and Central Western tropical regions of Brazil. Methods III of Henderson, Restricted Maximum Likelihood (REML), Bayesian Inference and generalized linear mixed model (GLMM) were tested. Variance components obtained from single-trait analysis were similar to those obtained from two-trait analysis. The estimates of heritability (h2) for the visual scores ranged from 0.1081 to 0.2190. Heritability estimates for traits evaluated by visual scores have moderate to high magnitude justifying the inclusion of visual scores as selection criteria in animal breeding and the selection of animals with higher scores for mating. High genetic correlations between yearling weight and morphological traits were verified. For visual scores of conformation, precocity and muscling, the most suitable model based on one-trait or two-trait analyses considered an animal model, a linear distribution of the data and the estimation method of the components of (co)variance based on Bayesian methodology.

scholarly journals Analysis of Genetic Parameters for Reproductive Traits in Crossbred Dairy Cattle Maintained at Holetta Agricultural Research Center.

2020 ◽  
Vol 39 (01) ◽  
Author(s):  
Kefale Getahun ◽  
Million Tadesse ◽  
Direba Hundie
Keyword(s):  
Dairy Cattle ◽  
Genetic Parameters ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Agricultural Research ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Breeding Value ◽  
Research Center ◽  
Phenotypic Correlation

This study was aimed to generate information on variance components and the resulting genetic parameters (heritability, repeatability, genetic and phenotypic correlations and genetic trends) of some economic traits of Borena and its crosses with Holstein Friesian dairy cattle maintained at Holetta agricultural research center dairy farm. Traits studied were age at first service (AFS), age at first calving (AFC), calving interval (CI), days open (DO) and number of service per conception (NSC). Overall, 11331 dairy cattle reproductive performance records were used for the study. WOMBAT, which is a software package for quantitative genetic analysis of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters were employed and obtained. Heritability values of reproductive traits were from very low (0.071, 0.082 and 0.012) for CI, DO and NSC to moderate (0.3 and 0.22) for AFC and AFS traits. Repeatability estimate for CI, DO and NSC were low (0.17, 0.17 and 0.129). Strong and positive genetic correlation (0.98) was appeared between AFS and AFC traits. Negative genetic correlations were observed between AFS and DO (-0.001), AFC and DO (-0.05), AFS and NSC (-0.022), AFC and NSC (-0.29) and CI and NSC (-0.31). AFS were negative phenotypic correlation with CI, DO and NSC. Similarly, AFC was negative phenotypic correlation with CI and DO. Low phenotypic correlation was observed between AFC and NSC, CI and DO, CI and NSC and, DO and NSC. Strong and positive phenotypic correlation was appeared between AFS and AFC. The regression coefficient of mean breeding value for NSC, CI, DO, AFC and AFS on year of birth were -0.0066x+13.25 times/year, -1.19x+2387.4 days/year, -1.23x+2445.6 days/year, 0.2x-410 months/year and 0.48x-980 months/year, respectively.

How standard are standardized drought indices? Uncertainty contributions for the SPI & SPEI case

2020 ◽  
Author(s):  
Johannes Laimighofer ◽  
Gregor Laaha
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Estimation Method ◽  
Drought Indices ◽  
Drought Severity ◽  
Main Question ◽  
Data Set ◽  
Total Uncertainty ◽  
Sources Of Uncertainty ◽  
Shed Light

<p><span lang="en-US">Standardized drought indices such as SPI are frequently used around the world to assess drought severity across a continent or a larger region covering different meteorological regimes. But how standard are the standardized indices? In this paper we quantify the uncertainty of SPI and SPEI based on an Austrian data set to shed light on what are the main sources of uncertainty in the study area. Here we analyze the uncertainty contributions by a linear mixed model that employs a restrictive maximum likelihood estimator in order to produce unbiased variance and covariance components. Five factors that either defy the control of the analyst (record length, observation period), or need to be subjectively decided during the steps of the calculation (choice of the distribution, parameter estimation method, and GOF-test of the fitted distribution) are considered. The results show that, overall, the choice of the distribution and the observational window are the most important sources of uncertainty. We quantify the relative uncertainty contributions in greater detail in order to give guidance how to make estimates most accurate for a given data set. We finally analyze the total uncertainty of SPI and SPEI to shed light on our main question whether the indices are skillful enough to provide a quantification of atmospheric drought that is standardized enough to allow the intended comparisons across various data situations and meteorological regimes. </span></p>

scholarly journals Genetic parameters for some growth traits of Nigerian local chickens

2017 ◽  
Vol 33 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Ifeanyichukwu Udeh
Keyword(s):  
Unbiased Estimator ◽  
Variance Components ◽  
Genetic Parameters ◽  
Mixed Model ◽  
Wing Length ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Mass Selection ◽  
Minimum Norm ◽  
Local Chickens

Genetic parameters were estimated for bodyweight (BWT), shank length (SHL), and wing length (WL) of Nigerian local chicken (NLC) from 4 to 20 weeks of age by fitting dyadic mixed model (dmm) equations which yield estimates of variance components equivalent to minimum norm quadratic unbiased estimator (MINQUE). Data obtained from 600 chicks, progenies of 300 hens and 30 cocks were used for the analysis. The heritability estimates range from 0.08 to 0.80 for BWT, 0.03 to 0.69 for SHL and 0.22 to 0.47 for WL. The genetic correlations among BWT, SHL and WL at different ages were high and positive and range from 0.18 to 0.96 with the exemption of SHL and WL at 16 weeks (- 0.06). The phenotypic correlations were positive and range from 0.10 to 0.91. The results imply that NLC could be improved on any of the studied traits through mass selection and that improvement in one trait will result to correlated improvement in the others.

scholarly journals Quantitative genetic basis of floral design in a natural plant population

2020 ◽  
Author(s):  
Juannan Zhou ◽  
Charles B. Fenste ◽  
Richard J. Reynolds
Keyword(s):  
Genetic Variation ◽  
Genetic Parameters ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Genetic Correlations ◽  
Natural Populations ◽  
Plant Evolution ◽  
Floral Traits ◽  
Floral Trait ◽  
Evolutionary Trajectory

AbstractThe amount of genetic variation of floral traits and the degree to which they are genetically correlated are important parameters for the study of plant evolution. Estimates of these parameters can reveal the effect of historical selection relative to neutral processes such as mutation and drift, and allow us to predict the short-term evolutionary trajectory of a population under various selective regimes. Here, we assess the heritability and genetic correlation of the floral design of a native N. American tetraploid plant, Silene stellata (Caryophyllaceae), in a natural population. Specifically, we use a linear mixed model to estimate the genetic parameters based on a genealogy reconstructed from highly variable molecular markers. Overall, we found significant heritabilities in five out of nine studied traits. The level of heritability was intermediate (0.027 – 0.441). Interestingly, the floral trait showing the highest level of genetic variation was previously shown to be under strong sexually conflicting selection, which may serve as a mechanism for maintaining the observed genetic variation. Additionally, we also found prevalent positive genetic correlations between floral traits. Our results suggest that S. stellata is capable of responding to phenotypic selection on its floral design, while the abundant positive genetic correlations could also constrain the evolutionary trajectories to certain directions. Furthermore, this study demonstrates the utility and feasibility of marker-based approaches for estimating genetic parameters in natural populations.

scholarly journals LMM-22: An Enhanced Linear Mixed Model (LMM) Approach for Genome-Wide Association Studies (GWAS) for the Prediction of Diseases and Traits among Humans from Genomics Data

2020 ◽  
Author(s):  
Siddharth Sharma
Keyword(s):  
Data Analysis ◽  
Graphics Processing Units ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Association Studies ◽  
Analysis Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Quality Of Data ◽  
Genome Wide

Increasingly, genomics is being used for the prediction of specific traits and diseases (phenotypes) among humans. Wider availability of genomics data through multiple research projects (such as International HapMap Project1 and 1000 Genomes2) has been a catalyst in that direction. With the recent advances in machine learning and big data analysis, data computation resources and data models needed for genomics data analysis are readily available. However, the prediction of traits and diseases has its own challenges in terms of computational requirements and computational analysis, statistical analysis (example: confounding variables), and limited quality of data collection. Linear Mixed Models (LMM, a type of linear regression) is a common approach for Genome-wide Association Studies (GWAS) for the prediction of common traits among humans using genomics. This paper researches the existing LMM-based approaches for Genome-wide Association Studies (GWAS), describes the experiment performed on FaST-LMM approach from Microsoft Research, and then proposes an enhanced approach (called LMM-22) on how to address computational and statistical issues. LMM-22 focuses on the parallelization of LMM computations and execution of LMM-22 on General Purpose Graphics Processing Units (GPU) as against CPUs to accelerate the LMM approach for GWAS studies.

scholarly journals Short communication: Genetic analysis of lactation curves in buffaloes, using Wood’s model

2020 ◽  
Vol 18 (3) ◽  
pp. e04SC01
Author(s):  
Ludmilla A. Marques de Carvalho ◽  
Guilherme F. de Moura ◽  
Dheynne A. Vieira ◽  
Naudin A. Hurtado-Lugo ◽  
Rusbel R. Aspilcueta-Borquis ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Short Communication ◽  
Genetic Correlations ◽  
Peak Time ◽  
Breeding Programs ◽  
High Magnitude ◽  
Lactation Curve ◽  
Heritability Estimates ◽  
The Individual

Aim of study: To estimate the heritability and genetic correlations for lactation curve traits in buffaloes.Area of study: The buffalo cows were raised on properties located in the states of São Paulo, Ceará and Rio Grande do Norte, Brazil.Material and methods: The individual parameters of Wood’s model ( , , and ) were obtained using a non-linear mixed model. Peak yield (PY), peak time (PT) and lactation persistency (LP) were also calculated. These individual parameters were employed in multi-trait analysis with the milk yield (MY) using Bayesian inference.Main results: The heritability estimates were of low to moderate magnitudes, with values ranging from 0.156 ( ) to 0.299 (PY). The estimates for genetic correlation between the Wood’s parameters and MY were of low to high magnitude and ranged from -0.533 (  and MY) to 0.983 (PY and MY).Research highlights: The heritability estimates obtained indicate that the traits studied can be used in animal breeding programs.

scholarly journals A Small Area Estimation Method for Investigating the Relationship between Public Perception of Drug Problems with Neighborhood Prognostics: Trends in London between 2012 and 2019

2021 ◽  
Vol 18 (17) ◽  
pp. 9016
Author(s):  
Arun Sondhi ◽  
Alessandro Leidi ◽  
Emily Gilbert
Keyword(s):  
Public Perception ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Statistical Significance ◽  
Local Population ◽  
Random Effect ◽  
Gaussian Quadrature ◽  
Estimation Method ◽  
Likelihood Method ◽  
Drug Problems

The correlation of the public’s perception of drug problems with neighborhood characteristics has rarely been studied. The aim of this study was to investigate factors that correlate with public perceptions in London boroughs using the Mayor’s Office for Policing and Crime (MOPAC) Public Attitude Survey between 2012 and 2019. A subject-specific random effect deploying a Generalized Linear Mixed Model (GLMM) using an Adaptive Gaussian Quadrature method with 10 integration points was applied. To obtain time trends across inner and outer London areas, the GLMM was fitted using a Restricted Marginal Pseudo Likelihood method. The perception of drug problems increased with statistical significance in 17 out of 32 London boroughs between 2012 and 2019. These boroughs were geographically clustered across the north of London. Levels of deprivation, as measured by the English Index of Multiple Deprivation, as well as the percentage of local population who were non-UK-born and recorded vehicle crime rates were shown to be positively associated with the public’s perception of drug problems. Conversely, recorded burglary rate was negatively associated with the public’s perception of drug problems in their area. The public are influenced in their perception of drug problems by neighborhood factors including deprivation and visible manifestations of antisocial behavior.

Multisite genetic parameter estimates from a Callitropsis nootkatensis diallel study with clonally replicated progeny

2015 ◽  
Vol 45 (6) ◽  
pp. 689-697 ◽  
Author(s):  
John H. Russell ◽  
João Costa e Silva ◽  
Brian S. Baltunis
Keyword(s):  
Genetic Variance ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Additive Genetic Variance ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Parameter Estimates ◽  
Narrow Sense ◽  
Spatially Correlated ◽  
Crown Form

Clonally replicated Callitropsis nootkatensis (D. Don) D.P. Little progeny from partial diallels were established in nine trials on coastal British Columbia, Canada. The trials were assessed for height, diameter, and crown form at age 12 years. An individual-genotype, linear mixed model with spatially correlated residuals was used to estimate the variance components and related genetic parameters. The majority of the estimated genetic variance for all traits was additive, and nonadditive genetic variance was predominantly due to dominance effects. Narrow-sense heritabilities for height and diameter at individual sites varied from 0.07 to 0.39, whereas for crown form, they were all less than 0.1. Dominance and epistasis ratios were, for the most part, lower than narrow-sense heritabilities. Common across-site additive and nonadditive genetic correlations were strongly positive and not significantly different from 1.0 for the majority of traits across sites within a series. Significant levels of additive genetic variance, coupled with insignificant to low nonadditive genetic variance for growth and crown form, would seem to be contrary to developing a clonal testing and deployment program. However, the lack of viable orchard seed and the faster delivery of genetic gain to reforestation, as well as more accurate forward selections based on additive genetic effects, makes this strategy viable for C. nootkatensis.

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