scholarly journals PSIII-8 Difference between two fecal egg count methods and estimation of genetic parameters for gastrointestinal parasite resistance traits in sheep

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 232-233
Author(s):  
Mohammed N Boareki ◽  
Olivia Willoughby ◽  
Delma Kennedy ◽  
Aroa Suarez-Vega ◽  
Larry Schaeffer ◽  
...  

Abstract Fecal egg count (FEC) is an indicative measurement for parasite infection in sheep. Different FEC methods may show inconsistent results. Not accounting for inconsistencies can be problematic when integrating measurements from different FEC methods for genetic evaluation. The objectives of this study were to: evaluate the difference between two FEC methods, the Modified McMaster (LMMR) and the Triple Chamber McMaster (LTCM); estimate the genetic and phenotypic correlations between records from two methods; and estimate genetic parameters for FEC and other gastrointestinal parasite resistance traits. A total of 1,676 fecal samples were collected from a commercial sheep farm between 2012 and 2019. Fecal egg counting was performed using the Modified McMaster (n = 998) and the Triple Chamber McMaster (n = 678) methods. Other parasite resistance trait records were collected from the same farm including eye score (FAMACHA©), body condition score (BCS), and body weight (WT). The mean and variance between the two FEC methods were significantly different (P < 0.0001), but phenotypic and genetic correlations between them were high (0.88 and 0.94, respectively). Therefore, pre-adjustment is required prior to integrating data from the different methods. For multiple trait analysis with other parasite resistance traits, data from the two fecal egg counting methods were integrated (LFEC) by using records for the LMMR when available and replacing missing records with standardized LTCM records for mean and variance of LMMR. Heritability estimates were 0.12, 0.07, 0.17, and 0.24, for LFEC, FAMACHA©, BCS, and the WT, respectively. Estimated genetic correlations between fecal egg count and the other parasite resistance traits were low with FAMACHA© (0.24), BCS (-0.03), and WT (0.22), suggesting little to no benefit of using such traits as indicators for LFEC.

Author(s):  
M N Boareki ◽  
F S Schenkel ◽  
O Willoughby ◽  
A Suarez-Vega ◽  
D Kennedy ◽  
...  

Abstract Fecal egg count (FEC) is an indicative measurement for parasite infection in sheep. Different FEC methods may show inconsistent results. Not accounting for inconsistencies can be problematic when integrating measurements from different FEC methods for genetic evaluation. The objectives of this study were to evaluate the difference in means and variances between two fecal egg counting methods used in sheep, the Modified McMaster (LMMR) and the Triple Chamber McMaster (LTCM); to estimate variance components for the two FEC methods, treating them as two different traits; and to integrate FEC data from the two different methods and estimate genetic parameters for FEC and other gastrointestinal parasite resistance traits. Fecal samples were collected from a commercial Rideau-Arcott sheep farm in Ontario. Fecal egg counting was performed using both Modified McMaster and the Triple Chamber McMaster methods. Other parasite resistance trait records were collected from the same farm including eye score (FAMACHA ©), body condition score (BCS), and body weight (WT). The two FEC methods were highly genetically (0.94) and phenotypically (0.88) correlated. However, the mean and variance between the two FEC methods were significantly different (P < 0.0001). Therefore, re-scaling is required prior to integrating data from the different methods. For the multiple trait analysis, data from the two fecal egg counting methods were integrated (LFEC) by using records for the LMMR when available and replacing missing records with re-standardized LTCM records converted to the same mean and variance of LMMR. Heritability estimates were 0.12 ± 0.04, 0.07 ± 0.05 , 0.17 ± 0.06, and 0.24 ± 0.07 for LFEC egg count, FAMACHA ©, BCS, and WT, respectively. The estimated genetic correlations between fecal egg count and the other parasite resistance traits were low and not significant (P>0.05) for FAMACHA © (r= 0.24 ± 0.32) and WT (r= 0.22 ± 0.19), and essentially zero for BCS (r= -0.03 ± 0.25), suggesting little to no benefit of using such traits as indicators for LFEC.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 242-242
Author(s):  
Zaira M Estrada-Reyes ◽  
Jorge A Hidalgo Moreno ◽  
Brittany N Diehl ◽  
Ibukun M Ogunade ◽  
Andres A Pech-Cervantes ◽  
...  

Abstract The Florida Native Sheep is one of the oldest sheep breeds in the United States. This heritage breed from Florida, naturally adapted to humid and hot climate conditions, is one of the most parasite resistant breeds from the Southern US. However, only approximately 1,000 individuals remain alive in the world. Therefore, conservation efforts and breeding programs are critical for survival of this breed. The objective of this research was to estimate genetic parameters for parasite resistance and body condition score in Florida Native sheep. The pedigree file contained 695 animals born between 2018 and 2020 and included 279 individuals with genotypes (38,429 SNP after quality control). The dataset contained 365 animals with phenotypic records at 38 days post-infection (natural Haemonchus contortus infection) for fecal egg count (FEC), blood packed count volume (PCV), FAMACHA score (FAM), and body condition score (BCS). Genetic parameters were estimated using a multi-trait model with a Bayesian implementation in the GIBBS3F90 program. Heritabilities were 0.38 0.07, 0.47 0.05, 0.27 0.04, and 0.52 0.07 for FEC, PCV, FAM, and BCS. Genetic correlations among parasite resistance traits were high and favorable: -0.82 0.06 (FEC-PCV), 0.83 0.07 (FEC-FAM), and -0.94 0.03 (PCV-FAM). Genetic correlations among parasite resistance traits and BCS were -0.42 0.11 (FEC-BCS), 0.75 0.09 (PCV-BCS), and -0.82 0.05 (FAM-BCS). Genetic progress for parasite resistance is possible in Florida Native sheep. The FAMACHA score is a phenotypic parameter easy to record in sheep; therefore, genetic selection for this trait can be effective to improve the remaining traits.


1996 ◽  
Vol 47 (8) ◽  
pp. 1251 ◽  
Author(s):  
DJ Johnston ◽  
H Chandler ◽  
HU Graser

Heritabilities and genetic correlations for cow weight and body condition score were estimated from field data for 3 beef breeds in Australia. In all, 8177 cows of mixed ages were weighed and scored for body condition at calf weaning time in seedstock herds as part of a large research project. The average weaning age was 212, 221, and 218 days for Angus, Hereford, and Poll Hereford, respectively. Cow weights and condition scores were analysed separately for each breed and estimates of genetic parameters were obtained by Restricted Maximum Likelihood (REML). Cow weight and condition score were moderately heritable: h2 = 0.43 and 0.21 for Angus, 0.39 and 0.14 for Hereford, and 0.48 and 0.17 for Poll Hereford. The genetic correlation between CW and CS was 0.49, 0.65, and 0.58 for Angus, Hereford, and Poll Hereford, respectively. There is potential for providing a genetic evaluation for cow weight using field data in Australian beef cattle. Its modelling for inclusion in a multiple trait genetic evaluation system such as BREEDPLAN is discussed.


2001 ◽  
Vol 72 (3) ◽  
pp. 449-456 ◽  
Author(s):  
A. Albera ◽  
R. Mantovani ◽  
G. Bittante ◽  
A. F. Groen ◽  
P. Carnier

AbstractEstimates of genetic parameters for beef production traits were obtained for Piemontese cattle. Data were from 988 young bulls station-tested from 1989 till 1998. Bulls entered the station at 6 to 8 weeks of age and, after an adaptation period of 3 months, were tested for growth, live fleshiness and bone thinness. Length of test was 196 days. Growth traits considered were gain at farm, gain during the adaptation period, gain on test and total gain at the station. Six different fleshiness traits and bone thinness were scored on live animals at the end of the test using a linear system. Live evaluations of fleshiness were adjusted for the weight at scoring in order to provide an assessment of conformation independent of body size. Genetic parameters were estimated using animal models. Heritability of live-weight gain ranged from 0·20 in the adaptation period to 0·60 for total gain at the station. Genetic correlations between gains at station in different periods were high (from 0·63 to 0·97). Residual correlation between gain during the adaptation period and gain during test was negative, probably due to the occurrence of compensatory growth of the animals.Live fleshiness traits and bone thinness were of moderate to high heritability (from 0·34 to 0·55) and highly correlated indicating that heavy muscled bulls also have thin bones. Accuracy of breeding values and therefore response to selection were improved by multiple trait analysis of the live fleshiness traits and bone thinness. Overall weight gain at the station had a moderate negative genetic correlation with all live fleshiness traits and bone thinness (from –0·11 to –0·39).


Animals ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 411
Author(s):  
Judith C. Miranda ◽  
José M. León ◽  
Camillo Pieramati ◽  
Mayra M. Gómez ◽  
Jesús Valdés ◽  
...  

This paper studies parameters of a lactation curve such as peak yield (PY) and persistency (P), which do not conform to the usual selection criteria in the Murciano-Granadina (MG) breed, but are considered to be an alternative to benefit animal welfare without reducing production. Using 315,663 production records (of 122,883 animals) over a period of 24 years (1990–2014), genetic parameters were estimated with uni-, bi- and multivariate analysis using multiple trait derivative free restricted maximum likelihood (MTDFREML). The heritability (h2)/repeatability (re) of PY, yield (Y) and P was estimated as 0.13/0.19, 0.16/0.25 and 0.08/0.09 with the uni-trait and h2 of bi- and multi-traits analysis ranging from 0.16 to 0.17 of Y, while that of PY and Y remained constant. Genetic correlations were high between PY–Y (0.94 ± 0.011) but low between PY–P (–0.16 ± 0.054 to –0.17 ± 0.054) and between Y–P (–0.06 ± 0.058 to –0.05 ± 0.058). Estimates of h2/re were low to intermediate. The selection for Y–PY or both can be implemented given the genetic correlation between these traits. PY–P and Y–P showed low to negligible correlation values indicating that if these traits are implemented in the early stages of evaluation, they would not be to the detriment of PY–Y. The combination of estimated breeding values (EBVs) for all traits would be a good criterion for selection.


2019 ◽  
Vol 32 (2) ◽  
pp. 100-106 ◽  
Author(s):  
Farzane Shokri-Sangari ◽  
Hadi Atashi ◽  
Mohammad Dadpasand ◽  
Fateme Saghanejad

Background: Lactation persistency influences cow health and reproduction and has an impact on the feed costs of dairy farms. Objective: To estimate (co)variance components and genetic parameters of 100- and 305-d milk yield, and lactation persistency in Holstein cows in Iran. Methods: Records collected from January 2000 to December 2012 by the Animal Breeding Center of Iran (Karaj, Iran) were used. The following four measures of lactation persistency were used: P21: Ratio of milk yield in the second 100-d in milk (DIM) divided by that of the first 100-d. P31: Ratios of milk yield in the third100-d divided by that of the first 100-d. PW: The persistency measure derived from the incomplete gamma function. PJ: The difference between milk yield in day 60th and 280th of lactation. Results: The estimated heritability of lactation persistency for the three first parities (first, second, and third lactation) ranged from 0.01 to 0.06, 0.02 to 0.10, and 0.01 to 0.12, respectively. Genetic correlations among lactation persistency measures for the three first parities ranged from 0.77 to 0.98, 0.65 to 0.98, and 0.58 to 0.98, respectively; while corresponding values for genetic correlations among lactation persistency with 305-d milk production ranged from 0.18 to 0.63, 0.32 to 0.75, and 0.41 to 0.71, respectively. The estimated repeatability for lactation persistency measures ranged from 0.06 to 0.20. Conclusion: The moderate positive genetic correlation between lactation persistency and 305-d milk yield indicates that selection for increasing milk yield can slightly improve lactation persistency.Key words: dairy cattle, heritability, lactation curve, milk yield, persistency, repeatability. ResumenAntecedentes: La persistencia de la lactancia tiene una gran influencia en la salud, la reproducción y los costos de alimentación de las granjas lecheras. Objetivo: Estimar los componentes de (co)varianza y los parámetros genéticos de la producción de leche a 100 y 305 d, asi como la persistencia de la lactancia en vacas Holstein en Irán. Métodos: Se utilizaron registros recopilados entre enero de 2000 y diciembre de 2012 por el Centro de cría de animales de Irán (Karaj, Irán). Se utilizaron las siguientes cuatro medidas de persistencia de la lactancia: P21: Proporción de producción de leche en los segundos 100-d en leche (DIM) dividida por la de los primeros 100-d. P31: Proporcion de producción de leche en los terceros 100-d dividido por el de los primeros 100-d. PW: medida de persistencia derivada de la función gamma incompleta. PJ: diferencia entre el rendimiento de leche en el 60 y el 280 día de lactancia. Resultados: La heredabilidad estimada de la persistencia de la lactancia para los tres primeros partos (primera, segunda y tercera lactancia) varió de 0,01 a 0,06; 0,02 a 0,10; y 0,01 a 0,12, respectivamente. Las correlaciones genéticas entre las medidas de persistencia de lactancia para los tres primeros partos variaron de 0,77 a 0,98; 0,65 a 0,98; y 0,58 a 0,98, respectivamente; mientras que los valores correspondientes para las correlaciones genéticas entre la persistencia de la lactancia con la producción de leche a 305 d variaron de 0,18 a 0,63; 0,32 a 0,75; y 0,41 a 0,71, respectivamente. La repetibilidad estimada para las medidas de persistencia de la lactancia varió de 0,06 a 0,20. Conclusión: La correlación genética positiva moderada entre la persistencia de la lactancia y la producción de leche a 305-d indica que la selección para aumentar la producción de leche puede mejorar ligeramente la persistencia de la lactancia.Palabras clave: curva de lactancia, ganado lechero, heredabilidad, persistencia, producción de leche, repetibilidad. ResumoAntecedentes: A persistência da lactação tem grande influência nos custos de saúde, reprodução e alimentação em fazendas leiteiras. Objetivo: Estimar os componentes da variância (co)variância e os parâmetros genéticos da produção de leite de 100 e 305 d e a persistência da lactação em vacas Holandesas no Irã. Métodos: Os dados utilizados foram registros coletados de janeiro de 2000 a dezembro de 2012 pelo Centro de Criação de Animais do Irã (Karaj, Irã). As seguintes quatro medidas de persistência de lactação foram utilizadas: P21: Razão da produção de leite no segundo 100-d em leite (DIM) dividido pelo primeiro 100-d. P31: Razões da produção de leite na terceira 100d dividida pela da primeira 100-d. PW: A medida de persistência derivada da função gama incompleta. PJ: A diferença entre a produção de leite no 60º e 280º dia de lactação. Resultados: A hereditariedade estimada da persistência da lactação para as três primeiras paridades (primeira, segunda e terceira lactação) variou de 0,01 a 0,06; 0,02 a 0,10; e 0,01 a 0,12, respectivamente. As correlações genéticas entre as medidas de persistência da lactação para as três primeiras paridades variaram de 0,77 a 0,98; 0,65 a 0,98; e 0,58 a 0,98, respectivamente; enquanto os valores correspondentes para correlações genéticas entre a persistência da lactação com produção de leite de 305d variaram de 0,18 a 0,63; 0,32 a 0,75; e 0,41 a 0,71, respectivamente. A repetibilidade estimada para medidas de persistência de lactação variou de 0,06 a 0,20. Conclusão: A correlação genética positiva moderada entre a persistência da lactação e a produção de leite de 305d indicou que a seleção para aumentar a produção de leite melhoraria ligeiramente a persistência da lactação.Palavras-chave: curva de lactação, gado de leite, hereditariedade, persistência, produção de leite, repetibilidade.


2004 ◽  
Vol 84 (3) ◽  
pp. 361-365 ◽  
Author(s):  
T. L. Fernandes ◽  
J. W. Wilton ◽  
J. J. Tosh

Data on ultrasound traits (loin depth, average backfat thickness, and loin width) were collected from lambs (n = 3483) across Ontario, born between 1997 and 1999. The data were analysed with a REML procedure in a multiple-trait mixed-animal model to obtain (co)variance component estimates. Analyses of all traits included the additive genetic effect of the lamb, sex of the lamb, contemporary group, and breed group effects. Weight or age was included as a covariate in two separate analyses. Estimates of direct additive heritabilities for loin depth, average backfat thickness, and loin width were 0.29, 0.29 and 0.26 respectively, with genetic correlations of -0.17 between loin depth and average backfat thickness, 0.43 between loin depth and loin width, and 0.23 between loin width and average backfat thickness for the weight constant analysis. When the data were analysed using age in the regression analysis, corresponding estimates of direct additive heritabilities were 0.38, 0.35 and 0.30, and genetic correlations between traits were all positive, 0.29 between loin depth and average backfat thickness, 0.61 between loin depth and loin width, and 0.44 between loin width and average backfat thickness. Results indicate that it is possible to make genetic improvement if selection is based on ultrasound information. Key words: Sheep, genetic parameters, heritability, ultrasound


PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247775
Author(s):  
Marco Antônio Peixoto ◽  
Jeniffer Santana Pinto Coelho Evangelista ◽  
Igor Ferreira Coelho ◽  
Rodrigo Silva Alves ◽  
Bruno Gâlveas Laviola ◽  
...  

Multiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low (ρg ≤ 0.33), moderate (0.34 ≤ ρg ≤ 0.66), and high magnitude (ρg ≥ 0.67) were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials.


2017 ◽  
Vol 52 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Adriane Molardi Bainy ◽  
Rodrigo Pelicioni Savegnago ◽  
Luara Afonso de Freitas ◽  
Beatriz do Nascimento Nunes ◽  
Jaqueline Oliveira Rosa ◽  
...  

Abstract: The objective of this work was to estimate genetic parameters for bird carcass and meat quality traits, as well as to explore the genetic patterns of the breeding values of this population using cluster analyses. Data from 1,846 birds were used to estimate the genetic parameters of production and quality traits using the multiple-trait animal model, and cluster analyses were performed. The heritability estimates ranged from 0.08± 0.03 for meat pH measured 24 hours after slaughter to 0.85± 0.09 for body weight. The genetic correlations between production traits were high and positive. The genetic correlations between meat quality traits were low and were not informative due to the high standard errors (same magnitudes as those of the genetic correlations). The genetic correlations between meat production and quality traits were negative, except between production traits and meat lightness intensity. Based on breeding values (EBVs), the evaluated population can be divided into four groups through cluster analyses, and one group is suitable for selection because the birds presented EBVs above and around the average of the population, respectively, for production and quality traits. Therefore, it is possible to obtain genetic gains for production-related traits without decreasing meat quality.


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