scholarly journals Comparison between methods for measuring fecal egg count and estimating genetic parameters for gastrointestinal parasite resistance traits in sheep

2021 ◽  
Author(s):  
M N Boareki ◽  
F S Schenkel ◽  
O Willoughby ◽  
A Suarez-Vega ◽  
D Kennedy ◽  
...  
Keyword(s):  
Genetic Parameters ◽  
Body Condition Score ◽  
Genetic Correlations ◽  
Gastrointestinal Parasite ◽  
Parasite Resistance ◽  
Multiple Trait ◽  
Fecal Egg Count ◽  
Counting Methods ◽  
Mean And Variance ◽  
Resistance Traits

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.

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 ◽  
...  
Keyword(s):  
Genetic Parameters ◽  
Body Condition Score ◽  
Genetic Correlations ◽  
Gastrointestinal Parasite ◽  
Parasite Resistance ◽  
Multiple Trait ◽  
Fecal Egg Count ◽  
Mean And Variance ◽  
The Difference ◽  
Resistance Traits

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.

PSVIII-8 Genetic parameters for parasite resistance in an endangered and heritage sheep breed from Florida

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 ◽  
...  
Keyword(s):  
Body Condition ◽  
Genetic Parameters ◽  
Body Condition Score ◽  
Genetic Correlations ◽  
The United States ◽  
Parasite Resistance ◽  
Southern Us ◽  
Condition Score ◽  
Native Sheep ◽  
Resistance Traits

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.

Genetic parameters for cow weight and condition score in Angus, Hereford, and Poll Hereford cattle

1996 ◽  
Vol 47 (8) ◽  
pp. 1251 ◽  
Author(s):  
DJ Johnston ◽  
H Chandler ◽  
HU Graser
Keyword(s):  
Body Condition ◽  
Evaluation System ◽  
Field Data ◽  
Genetic Parameters ◽  
Body Condition Score ◽  
Genetic Correlations ◽  
Genetic Evaluation ◽  
Multiple Trait ◽  
Hereford Cattle ◽  
Condition Score

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.

Genetic parameters for daily live-weight gain, live fleshiness and bone thinness in station-tested Piemontese young bulls

2001 ◽  
Vol 72 (3) ◽  
pp. 449-456 ◽  
Author(s):  
A. Albera ◽  
R. Mantovani ◽  
G. Bittante ◽  
A. F. Groen ◽  
P. Carnier
Keyword(s):  
Weight Gain ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Live Weight ◽  
Adaptation Period ◽  
Production Traits ◽  
Multiple Trait ◽  
Live Weight Gain ◽  
Total Gain

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).

scholarly journals Estimation of Genetic Parameters for Peak Yield, Yield and Persistency Traits in Murciano-Granadina Goats Using Multi-Traits Models

Animals ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 411
Author(s):  
Judith C. Miranda ◽  
José M. León ◽  
Camillo Pieramati ◽  
Mayra M. Gómez ◽  
Jesús Valdés ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Selection Criteria ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Multiple Trait ◽  
Lactation Curve ◽  
Derivative Free ◽  
Selection For ◽  
Estimated Breeding Values ◽  
Estimation Of Genetic Parameters

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.

Estimates of genetic parameters for ultrasound-measured carcass traits in sheep

2004 ◽  
Vol 84 (3) ◽  
pp. 361-365 ◽  
Author(s):  
T. L. Fernandes ◽  
J. W. Wilton ◽  
J. J. Tosh
Keyword(s):  
Genetic Improvement ◽  
Variance Component ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Backfat Thickness ◽  
Additive Genetic Effect ◽  
Multiple Trait ◽  
Breed Group ◽  
Variance Component Estimates

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

scholarly journals Multiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy

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 ◽  
...  
Keyword(s):  
Jatropha Curcas ◽  
Repeated Measures ◽  
Bayesian Model ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Monte Carlo Algorithm ◽  
Multiple Trait ◽  
Trait Model

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.

scholarly journals Estimates of genetic parameters and cluster analyses for carcass and meat quality traits in birds

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 ◽  
...  
Keyword(s):  
Meat Quality ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Meat Production ◽  
Quality Traits ◽  
Production Traits ◽  
Multiple Trait ◽  
Breeding Values ◽  
Cluster Analyses ◽  
Meat Quality Traits

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.

Estimation of genetic parameters of fertility traits in Chinese Holstein cattle

2014 ◽  
Vol 94 (2) ◽  
pp. 281-285 ◽  
Author(s):  
Gang Guo ◽  
Xiangyu Guo ◽  
Yachun Wang ◽  
Xu Zhang ◽  
Shengli Zhang ◽  
...  
Keyword(s):  
Genetic Parameters ◽  
Genetic Correlations ◽  
Holstein Cattle ◽  
Calving Interval ◽  
Strongly Correlated ◽  
Multiple Trait ◽  
Chinese Holstein ◽  
Chinese Holstein Cattle ◽  
Fertility Traits ◽  
Estimation Of Genetic Parameters

Guo, G., Guo, X., Wang, Y., Zhang, X., Zhang, S., Li, X., Liu, L., Shi, W., Usman, T., Wang, X., Du, L. and Zhang, Q. 2014. Estimation of genetic parameters of fertility traits in Chinese Holstein cattle. Can. J. Anim. Sci. 94: 281–285. The objective of this study was to estimate genetic parameters for fertility traits in Chinese Holstein heifers and cows. Data of 20169 animals with 42106 records over a period of 10 yr (2001–2010) were collected from Sanyuan Lvhe Dairy Cattle Center in Beijing, China. Traits included age at first service (AFS), number of services (NS), days from calving to first service (CTFS), days open (DO), and calving interval (CI). Genetic parameters were estimated with multiple-trait animal model using the DMU software. Heritability estimates for AFS, NS, CTFS, DO and CI were 0.100±0.012, 0.040±0.017, 0.034±0.011, 0.053±0.019 and 0.056±0.014, respectively. Genetic correlations between traits observed ranged from −0.13 to 0.99. Genetic correlations between AFS with NS, CTFS, DO and CI were −0.31, 0.15, −0.13 and −0.15, respectively. Calving interval was strongly correlated with NS, CTFS and DO (0.49–0.99), and DO showed strong correlation with NS and CTFS (0.49 and 0.58, respectively). The genetic correlation between CTFS and NS was negative moderate (−0.25). Results were in range with previous literature estimates and can be used in Chinese Holstein genetic evaluation for fertility traits.

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