scholarly journals Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model

Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1432
Author(s):  
Mohammed Boareki ◽  
Flavio Schenkel ◽  
Delma Kennedy ◽  
Angela Cánovas
Keyword(s):  
Animal Model ◽  
Prediction Accuracy ◽  
Genetic Resistance ◽  
Genetic Effect ◽  
Risk Groups ◽  
Selection Response ◽  
Additive Genetic Effect ◽  
Breeding Programs ◽  
Estimated Breeding Values ◽  
Available Information

Selection based on scrapie genotypes could improve the genetic resistance for scrapie in sheep. However, in practice, few animals are genotyped. The objectives were to define numerical values of scrapie resistance genotypes and adjust for their non-additive genetic effect; evaluate prediction accuracy of ungenotyped animals using linear animal model; and predict and assess selection response based on estimated breeding values (EBV) of ungenotyped animals. The scrapie resistance (SR) was defined by ranking scrapie genotypes from low (0) to high (4) resistance based on genotype risk groups and was also adjusted for non-additive genetic effect of the haplotypes. Genotypes were simulated for 1,671,890 animals from pedigree. The simulated alleles were assigned to scrapie haplotypes in two scenarios of high (SRh) and low (SRl) resistance populations. A sample of 20,000 genotyped animals were used to predict ungenotyped using animal model. Prediction accuracies for ungenotyped animals for SRh and SRl were 0.60 and 0.54, and for allele content were from 0.41 to 0.71, respectively. Response to selection on SRh and SRl increased SR by 0.52 and 0.28, and on allele content from 0.13 to 0.50, respectively. In addition, the selected animals had large proportion of homozygous for the favorable haplotypes. Thus, pre-selection prior to genotyping could reduce genotyping costs for breeding programs. Using a linear animal model to predict SR makes better use of available information for the breeding programs.

Evaluation genetic parameters for weight at different ages in Baluchi breed of sheep

2003 ◽  
Vol 2003 ◽  
pp. 145-145
Author(s):  
M. Hosseinpour Mashhadi ◽  
F. Eftekhari Shahroudi ◽  
R. Valizadeh
Keyword(s):  
Birth Weight ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Maternal Environment ◽  
Breeding Programs ◽  
Breeding Values ◽  
Genetic Potential ◽  
Different Ages ◽  
Maternal Genetic Effect

Improving breeding values and breeding programs should be done based on genetic potential. The range of additive direct heritability and maternal environment heritability for birth weight is about 0.07 to 0.22 and 0.1 to 0.33 respectively the range of these values for the following weights are 0.09- 0.58 and 0.01- 0.17. the objective of this study was to predict the direct additive genetic effect, maternal genetic effect and heritabilities of lamb weight traits in baluchi breed of sheep.

scholarly journals Genetic analysis of clinical mastitis data for Holstein cattle in the Czech Republic

2015 ◽  
Vol 58 (1) ◽  
pp. 199-204 ◽  
Author(s):  
L. Zavadilová ◽  
M. Štípková ◽  
N. Šebková ◽  
A. Svitáková
Keyword(s):  
Czech Republic ◽  
Animal Models ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Clinical Mastitis ◽  
Additive Genetic Effect ◽  
Herd Effect ◽  
Breeding Programs ◽  
The Czech Republic ◽  
Calving Season

Abstract. Cases of mastitis were recorded from 22 812 lactations of 10 294 cows on seven farms in the Czech Republic from 2000 to 2012. The per cow number of clinical mastitis (CM) cases per lactation (CM1), number of days of CM per lactation (CM2), and CM considered as an all-or-none trait (CM3) with values of 0 (no CM case) or 1 (at least 1 CM case) were analyzed with linear animal models. Bivariate linear animal models were used for estimation of genetic correlations between CM traits and average lactation somatic cell score (SCS305), average 305-day milk (MY305), fat (FY305) and protein (PY305) yield, and interval between calving and first insemination (INT) and days open (DO). Factors included in the model of choice were parity, herd effect, year of calving, calving season, permanent environmental effect of the cow, and additive genetic effect of the cow. Estimated heritabilities for CM traits were in the range of 0.09 to 0.10. Genetic correlations of SCS305 with CM traits 1, 2, and 3 were 0.22 ± 0.062, 0.23 ± 0.064, and 0.29 ± 0.086, respectively; those of MY305 with the three CM traits were 0.80 ± 0.037, 0.79 ± 0.040, and 0.83 ± 0.038, respectively; those of INT with the three CM traits were 0.19 ± 0.087, 0.17 ± 0.089, and 0.26 ± 0.091, respectively; and those of DO with the three CM traits were 0.28 ± 0.089, 0.22 ± 0.091, and 0.27 ± 0.091, respectively. Knowledge of genetic parameters of mastitis incidence and assessment of the economic importance of the disease is necessary to design breeding programs to improve udder health.

scholarly journals Use of individual race results in the estimation of genetic parameters of trotting performance for Finnhorse and Standardbred trotters

1999 ◽  
Vol 8 (4-5) ◽  
pp. 353-363 ◽  
Author(s):  
T. THUNEBERG-SELONEN ◽  
J. PÖSÖ ◽  
E. MÄNTYSAARI
Keyword(s):  
Animal Model ◽  
Maximum Likelihood ◽  
Variance Components ◽  
Fixed Effects ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Performance Traits ◽  
Estimation Of Genetic Parameters

The heritability and repeatability for trotting performance traits were estimated from individual race results. Data comprised of records from 1991 to 1995 for 4808 Finnhorses and from 1993 to 1995 for 5869 Standardbred trotters. The statistical model included the additive genetic effect of an animal and two permanent environmental effects, and the fixed effects of sex, age, starting method*starting lane combination, driver and race. The first permanent environmental effect described repeatability over a horse’s career while the second one characterized repeatability within a racing year. Variance components for three trotting performance traits were estimated by the animal model and the method of restricted maximum likelihood (REML). Heritability and repeatability estimates were moderately high for time at finish (h 2 =0.23–0.28 and r=0.50–0.57), moderate for ranking within a race (h 2 =0.12 and r=0.25) and low for earnings (h 2 =0.05–0.09 and r=0.15–0.18). Time at finish seemed to be the most usable measure of trotting performance because of its wide information substance. However, time at finish does not take into account records of disqualified horses or of those which did not finish, but use of earnings, either from individual race results or preferably from annual records, is one possible way to consider records of such horses.;

Personal Goals of Older Female Twins

2009 ◽  
Vol 14 (2) ◽  
pp. 160-167 ◽  
Author(s):  
Katariina Salmela-Aro ◽  
Sanna Read ◽  
Jari-Erik Nurmi ◽  
Markku Koskenvuo ◽  
Jaakko Kaprio ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Independent Living ◽  
Environmental Effect ◽  
Close Relationships ◽  
Environmental Influence ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Personal Goals ◽  
Cultural Activities ◽  
The Individual

This study examined genetic and environmental influences on older women’s personal goals by using data from the Finnish Twin Study on Aging. The interview for the personal goals was completed by 67 monozygotic (MZ) pairs and 75 dizygotic (DZ) pairs. The tetrachoric correlations for personal goals related to health and functioning, close relationships, and independent living were higher in MZ than DZ twins, indicating possible genetic influence. The pattern of tetrachoric correlations for personal goals related to cultural activities, care of others, and physical exercise indicated environmental influence. For goals concerning health and functioning, independent living, and close relationships, additive genetic effect accounted for about half of the individual variation. The rest was the result of a unique environmental effect. Goals concerning physical exercise and care of others showed moderate common environmental effect, while the rest of the variance was the result of a unique environmental effect. Personal goals concerning cultural activities showed unique environmental effects only.

ESTIMASI NILAI HERITABILITAS BOBOT IKAN MAS VARIETAS PUNTEN DALAM PROGRAM SELEKSI INDIVIDU

2016 ◽  
Vol 11 (3) ◽  
pp. 217
Author(s):  
Estu Nugroho ◽  
Budi Setyono ◽  
Mochammad Su’eb ◽  
Tri Heru Prihadi
Keyword(s):  
Body Weight ◽  
Selection Response ◽  
Base Population ◽  
Breeding Programs ◽  
Male And Female ◽  
Body Weight Trait ◽  
Population Selection ◽  
Selection For ◽  
Weight Trait ◽  
Selection Of

Program pemuliaan ikan mas varietas Punten dilakukan dengan seleksi individu terhadap karakter bobot ikan. Pembentukan populasi dasar untuk kegiatan seleksi dilakukan dengan memijahkan secara massal induk ikan mas yang terdiri atas 20 induk betina dan 21 induk jantan yang dikoleksi dari daerah Punten, Kepanjen (delapan betina dan enam jantan), Kediri (tujuh betina dan 12 jantan), Sragen (27 betina dan 10 jantan), dan Blitar (15 betina dan 11 jantan). Larva umur 10 hari dipelihara selama empat bulan. Selanjutnya dilakukan penjarangan sebesar 50% dan benih dipelihara selama 14 bulan untuk dilakukan seleksi dengan panduan hasil sampling 250 ekor individu setiap populasi. Seleksi terhadap calon induk dilakukan saat umur 18 bulan pada populasi jantan dan betina secara terpisah dengan memilih berdasarkan 10% bobot ikan yang terbaik. Calon induk yang terseleksi kemudian dipelihara hingga matang gonad, kemudian dipilih sebanyak 150 pasang dan dipijahkan secara massal. Didapatkan respons positif dari hasil seleksi berdasarkan bobot ikan, yaitu 49,89 g atau 3,66% (populasi ikan jantan) dan 168,47 g atau 11,43% (populasi ikan betina). Nilai heritabilitas untuk bobot ikan adalah 0,238 (jantan) dan 0,505 (betina).Punten carp breeding programs were carried out by individual selection for body weight trait. The base population for selection activities were conducted by mass breeding of parent consisted of 20 female and 21 male collected from area Punten, eight female and six male (Kepanjen), seven female and 12 male (Kediri), 27 female and 10 male (Sragen), 15 female and 11 male (Blitar). Larvae 10 days old reared for four moths. Then after spacing out 50% of total harvest, the offspring reared for 14 months for selection activity based on the sampling of 250 individual each population. Selection of broodstock candidates performed since 18 months age on male and female populations separately by selecting based on 10% of fish with best body weight. Candidates selected broodstocks were then maintained until mature. In oder to produce the next generation 150 pairs were sets and held for mass spawning. The results revealed that selection response were positive, 49.89 g (3.66%) for male and 168.47 (11.43%) for female. Heritability for body weight is 0.238 (male) and 0.505 (female).

scholarly journals A review of deep learning applications for genomic selection

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Osval Antonio Montesinos-López ◽  
Abelardo Montesinos-López ◽  
Paulino Pérez-Rodríguez ◽  
José Alberto Barrón-López ◽  
Johannes W. R. Martini ◽  
...  
Keyword(s):  
Deep Learning ◽  
Plant Breeding ◽  
Genomic Selection ◽  
Genomic Prediction ◽  
Mixed Model ◽  
Prediction Models ◽  
Genetic Effect ◽  
Training Data ◽  
Additive Genetic Effect ◽  
Main Body

Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction methods have been proposed including the standard additive genetic effect model for which the variance components are estimated with mixed model equations. In recent years, deep learning (DL) methods have been considered in the context of genomic prediction. The DL methods are nonparametric models providing flexibility to adapt to complicated associations between data and output with the ability to adapt to very complex patterns. Main body We review the applications of deep learning (DL) methods in genomic selection (GS) to obtain a meta-picture of GS performance and highlight how these tools can help solve challenging plant breeding problems. We also provide general guidance for the effective use of DL methods including the fundamentals of DL and the requirements for its appropriate use. We discuss the pros and cons of this technique compared to traditional genomic prediction approaches as well as the current trends in DL applications. Conclusions The main requirement for using DL is the quality and sufficiently large training data. Although, based on current literature GS in plant and animal breeding we did not find clear superiority of DL in terms of prediction power compared to conventional genome based prediction models. Nevertheless, there are clear evidences that DL algorithms capture nonlinear patterns more efficiently than conventional genome based. Deep learning algorithms are able to integrate data from different sources as is usually needed in GS assisted breeding and it shows the ability for improving prediction accuracy for large plant breeding data. It is important to apply DL to large training-testing data sets.

scholarly journals Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

2019 ◽  
Vol 67 (5) ◽  
pp. 1245-1251
Author(s):  
Ludmila Zavadilová ◽  
Eva Kašná ◽  
Zuzana Krupová
Keyword(s):  
Infectious Diseases ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Holstein Cows ◽  
Additive Genetic Effect ◽  
Genomic Information ◽  
White Line ◽  
Genomic Breeding ◽  
Breeding Values

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

scholarly journals Genetic-Quantitative Uni- and Bi-Trait Analysis for Growth Traits in the Colombian Creole Breed Blanco Orejinegro (BON)

2021 ◽  
Author(s):  
Marisol Londoño-Gil ◽  
Juan Carlos Rincón Flórez ◽  
Albeiro López-Herrera ◽  
Luis Gabriel Gonzalez-Herrera
Keyword(s):  
Growth Traits ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Cattle Breed ◽  
Live Weight ◽  
Daily Weight Gain ◽  
Additive Genetic Effect ◽  
Selection Processes ◽  
Heritability Estimates ◽  
Maternal Heritability

Abstract The Blanco Orejinegro (BON) is a Colombian creole cattle breed that is not genetically well characterized for growth traits. The aim of this work was to estimate genetic parameters for birth weight (BW), weaning weight (WW), yearling weight (YW), daily weight gain between birth and weaning (DWG), time to reach 120 kg of live weight (T120), and time to reach 60% of adult weight (T60%), and establish the selection criteria for growth traits in the BON population of Colombia. Genealogical and phenotypic information for BW, WW, YW, DWG, T120, and T60% traits of BON animals from 14 Colombian herds were used. These traits were analyzed with the AIREML method in a uni- and bi-trait animal model including the maternal effect for BW, WW, DWG, and T120. The direct heritability estimates values were 0.22 ± 0.059 (BW), 0.20 ± 0.057 (WW), 0.20 ± 0.153 (YW), 0.17 ± 0.07 (DWG), 0.26 (T120), and 0.44 ± 0.03 (T60%). The maternal heritability estimates values were 0.14 ± 0.040 (BW), 0.15 ± 0.039 (WW), 0.25 ± 0.06 (DWG), and 0.16 (T120). The direct genetic correlations were high (>|0.60|) among all the traits, except between T60% with BW, WW, YW, and DWG (ranged from -0.02 to -0.51), all in a favorable direction. The results showed that there is genetic variation in the growth traits associated with the additive genetic effect and they might respond to selection processes. Furthermore, genetic gains would improve through selection, especially for YW and T60% when WW is used as criterion.

A note on heritability estimates for growth traits in male and female Romanov sheep

1993 ◽  
Vol 57 (2) ◽  
pp. 326-328 ◽  
Author(s):  
G. A. María ◽  
K. G. Boldman ◽  
L. D. van Vleck
Keyword(s):  
Animal Model ◽  
Birth Weight ◽  
Maximum Likelihood ◽  
Random Effects ◽  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Effect ◽  
Male And Female ◽  
Males And Females ◽  
Direct Genetic Effect

A total of 1855 records were analysed using restricted maximum likelihood (REML) techniques to estimate heritabilities separately for males and females lambs on birth weight (BW), weaning weight (WW), 90-day weight (W90) and average daily gains birth to weaning (Cl) and weaning to 90 days (C2). An animal model including fixed effects of year × season, parity, litter size and rearing type; and random effects of direct genetic effect (h2D) and residual was applied. Estimates ofh2Dfor BWwere 048 (males) and 0·50 (females); for WW 0·35 (males) and 0·22 (females); for W90 0·21 (males) and 0·31 (females); for Cl 0·20 (males) and 0·25 (females); and for C2 0·18 (males) and 0·29 (females).

Efecto de dos estrategias de agrupación de padres fantasmas en la evaluación genética de rasgos de crecimiento en el ganado Braunvieh mexicano

2021 ◽  
Vol 12 (3) ◽  
pp. 878-892
Author(s):  
Luis Antonio Saavedra-Jiménez ◽  
Rodolfo Ramírez-Valverde ◽  
Rafael Núñez-Domínguez ◽  
Agustín Ruíz-Flores ◽  
José Guadalupe García-Muñiz ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Genetic Trend ◽  
Phenotypic Data ◽  
Genetic Groups ◽  
Grouping Strategies ◽  
Parent Groups ◽  
Different Sources

The study aimed to compare two grouping strategies for unknown parents or phantom parent groups (PPG) on the genetic evaluation of growth traits for Mexican Braunvieh cattle. Phenotypic data included birth (BW), weaning (WW) and yearling (YW) weights. Pedigree included 57,341 animals. The first strategy involved 12 PPG (G12) based on the birth year of the unknown parent’s progeny and the sex of the unknown parent, while the second involved 24 PPG (G24) based on the birth year of the unknown parent’s progeny and 4-selection pathways. The animal models included fixed effects and the random direct additive genetic effect; WW also included random maternal genetic and maternal permanent environmental effects. Product-moment correlations between EBV from G0 (no PPG) and G12 were 0.96, 0.77 and 0.69 for BW, WW and YW, respectively, and between EBV from G0 and G24 were 0.91, 0.54, and 0.53, respectively. Corresponding rank correlations between G0 and G12 were 0.94, 0.77, and 0.72, and between G0 and G24 were 0.89, 0.61, and 0.60. Genetic trends showed a base deviation from the genetic trend of G0, except for BW of G12. The results did not support the use of the two grouping strategies on the studied population and traits, and further research is required. Introducing PPG to the model, enough phenotype contribution from descendants to PPG, and avoiding collinearity between PPG and fixed effects are important. Genetic groups should reflect changes in the genetic structure of the population to the unknown parents, including different sources of genetic materials, and changes made by selection over time.

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