Data from 178 Jersey calves born at Livestock Experiment Station were analyzed to obtain estimates of heritability, genetic and phenotypic correlations of some growth traits. Sex-specific variance and covariance components were estimated for birth weight (BWT), 180-d weight (WWT), 365-d weight (YWT), birth to weaning daily gain (BWG), weaning to yearling daily gain (WYG) and brith to yearling gain (BYG). Heritabilities, genetic and phenotypic correlations were generally higher in males than females. Heritabilities estimated for males and females respectively were 0.98 and 0.49 for BWT; 0.70 and 0.76 for WWT; 0.71 and 0.26 for YWT. Genetic correlations were higher than phenotypic correlations in all the treats studied.
Improved meat quality and greater muscle yield are highly sought after in high-quality chicken breeding programs. Past studies indicated that polymorphisms of the Perilipin gene (PLIN1) are highly associated with adiposity in mammals and are potential molecular markers for improving meat quality and carcass traits in chickens. In the present study, we screened single nucleotide polymorphisms (SNPs) in all exons of the PLIN1 gene with a direct sequencing method in six populations with different genetic backgrounds (total 240 individuals). We evaluated the association between the polymorphisms and carcass and meat quality traits. We identified three SNPs, located on the 5' flanking region and exon 1 of PLIN1 on chromosome 10 (rs315831750, rs313726543, and rs80724063, respectively). Eight main haplotypes were constructed based on these SNPs. We calculated the allelic and genotypic frequencies, and genetic diversity parameters of the three SNPs. The polymorphism information content (PIC) ranged from 0.2768 to 0.3750, which reflected an intermediate genetic diversity for all chickens. The CC, CT, and TT genotypes influenced the percentage of breast muscle (PBM), percentage of leg muscle (PLM) and percentage of abdominal fat at rs315831750 (p<0.05). Diplotypes (haplotype pairs) affected the percentage of eviscerated weight (PEW) and PBM (p<0.05). Compared with chickens carrying other diplotypes, H3H7 had the greatest PEW and H2H2 had the greatest PBM, and those with diplotype H7H7 had the smallest PEW and PBM. We conclude that PLIN1 gene polymorphisms may affect broiler carcass and breast muscle yields, and diplotypes H3H7 and H2H2 could be positive molecular markers to enhance PEW and PBM in chickens.
Objective: This study was conducted to estimate the genetic parameters and breeding values of breast meat related traits of Pekin ducks. Selection response was also determined by using ultrasound breast muscle thickness (BMT) measurements in combination with bosom breadth (BB) and keel length (KL) values. Methods: The traits analyzed were breast meat weight (BMW), body weight (BW), breast meat percentage (BMP) and the three parameters of breast meat (BB, KL, and BMT). These measurements were derived from studying 15,781 Pekin ducks selected from 10 generations based on breast meat weight. Genetic parameters and breeding value were estimated for the analysis of the breeding process. Results: Estimated heritability of BMW and BMP were moderate (0.23 and 0.16, respectively), and heritability of BW was high (0.48). Other traits such as BB, KL, and BMT indicated moderate heritability ranging between 0.11 and 0.28. Significant phenotypic correlations of BMW with BW and BMP were discovered (p<0.05), and genetic correlations of BMW with BW and BMP were positive and high (0.83 and 0.66, respectively). It was noted that BMW had positive correlations with all the other traits. Generational average estimated breeding values of all traits increased substantially over the course of selection, which demonstrated that the ducks responded efficiently to increased breast meat yield after 10 generations of breeding. Conclusion: The results indicated that duck BMW had the potential to be increased through genetic selection with positive effects on BW and BMP. The ultrasound BMT, in combination with the measurement of BB and KL, is shown to be essential and effective in the process of high breast meat yield duck breeding.
Carcass characteristics of 241 crossbred pigs (Korean wild boars ${\times}$ Landrace sows) were analyzed to examine variations in fasted body weight (FASTWT), carcass weight (CARCWT), dressing percentage (DP), back fat thickness (BFT) and longissimus muscle weight (LMW), and to estimate genetic and phenotypic parameters using three different slaughter-end points. Covariates in the least squares full sib model were slaughter age, fasted body weight and back fat thickness of the carcass. Coefficient of variation was highest for BFT followed by LMW, CARCWT, FASTWT and DP in magnitude. Regressions of three covariates on traits were all linear. However, slaughter age was not significant as a linear covariate for five traits while FASTWT was significant for CARCWT and LMW and BFT was significant for all remaining traits. Genetic and phenotypic variation was considerably reduced by regressing FASTWT or BFT in the model. Heritability estimates of FASTWT, CARCWT, DP and BFT were 0.68, 0.61, 0.11 and 0.49, respectively, using slaughter age as covariate (model 1). Those of CARCWT, DP, BFT and LMW were 0.15, 0.15, 0.30 and 0.11, respectively, using FASTWT as covariate (model 2). Heritability estimates of the traits using LMW as covariate (model 3) were similar to the estimates from Model 1 except that the estimate of CARCWT was reduced to 0.39. Genetic or phenotypic correlations among FASTWT, CARCWT and BFT were all positive and moderate to high. Those between BFT and LMW were also positive and low to moderate. However, genetic and phenotypic correlations between DP and CARCWT were positive while those between DP and FASTWT were negative. It was suggested from this study that differences in carcass yield traits be determined using slaughter age or back fat thickness as slaughter-end point and carcass quality traits using fasted body weight as slaughter-end point.
Background: Despite the importance of relationships between somatic cell score (SCS) and currently selected traits (milk, fat and protein yield) of Holstein cows, there was a lack of comprehensive literature for it in Iran. Therefore we tried to examine heritabilities and relationships between these traits using a fixed-regression animal model and Bayesian inference. The data set consisted of 1,078,966 test-day observations from 146,765 primiparous daughters of 1930 sires, with calvings from 2002 to 2013. Results: Marginal posterior means of heritability estimates for SCS ($0.03{\pm}0.002$) were distinctly lower than those for milk ($0.204{\pm}0.006$), fat ($0.096{\pm}0.004$) and protein ($0.147{\pm}0.005$) yields. In the case of phenotypic correlations, the relationships between production and SCS were near zero at the beginning of lactation but become increasingly negative as days in milk increased. Although all environmental correlations between production and SCS were negative ($-0.177{\pm}0.007$, $-0.165{\pm}0.008$ and $-0.152{\pm}0.007$ between SCS and milk, fat, and protein yield, respectively), slightly antagonistic genetic correlations were found; with posterior mean of relationships ranging from $0.01{\pm}0.039$ to $0.11{\pm}0.036$. This genetic opposition was distinctly higher for protein than for fat. Conclusion: Although small, the positive genetic correlations suggest some genetic antagonism between desired increased milk production and reduced SCS (i.e., single-trait selection for increased milk production will also increase SCS).
Choudhary, V.;Kothekar, M.D.;Raheja, K.L.;Kasturiwale, N.N.;Khire, D.W.;Kumar, P.
Asian-Australasian Journal of Animal Sciences
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v.16
no.5
/
pp.639-643
/
2003
The data on 283 Sahiwal cows, sired by 16 bulls, maintained at Cattle Breeding Farm of Nagpur Veterinary College and Dairy Farm of Agricultural College, Nagpur, were considered for the estimation of genetic parameters. Variance and covariance estimates of first lactation traits were obtained using restricted maximum likelihood technique (REML). When first lactation milk yield (FLMY), first lactation length (FLL) and average daily yield (ADY) traits were considered for REML analysis, the heritabilities were $0.184{\pm}0.146$, $0.132{\pm}0.131$ and $0.141{\pm}0.133$, respectively. While, genetic and phenotypic correlations between them were medium to high except phenotypic correlations between FLL and ADY (-0.025). REML procedure considering FLMY, age at first calving (AFC) and first service period (FSP) combination exhibits heritabilities as $0.274{\pm}0.173$, $0.506{\pm}0.233$ and $0.274{\pm}0.172$, respectively. Genetic correlations were $-0.120{\pm}0.376$, $0.225{\pm}0.423$ and $0.365{\pm}0.331$ between FLMY and AFC, FLMY and FSP, AFC and FSP, respectively. Phenotypic correlations were 0.057, 0.289 and 0.123, respectively. Considering all five traits REML combination heritabilities estimated were $0.238{\pm}0.162$, $0.160{\pm}0.139$, $0.136{\pm}0.132$, $0.409{\pm}0.209$ and $0.259{\pm}0.168$ for FLMY, FLL, ADY, AFC and FSP, respectively. The genetic correlations were positive except FLMY and AFC. The phenotypic correlations were also positive except FLL and ADY, ADY and FSP. Almost all estimates were associated with high standard error.
Genetic variants of Hanwoo mtDNA in the region of cytochrome oxidase subunit I, II and III complex were detected using restriction enzymes. PCR primers were designed based on the bovine mtDNA sequence, and 6 primer sets (Mt4, Mt5, Mt6, Mt7, Mt8 and Mt9) were used. A total of 20 restriction enzymes were used, and 6 restriction enzymes, which were Hinf I, Pvu II, Rsa I, Eco RI, Bgl II, and Msp I, showed genetic polymorphisms. Significant associations between genetic variants and weight traits were observed at WT15 (p<0.05) and WT18 (p<0.01) with Pvu II for Mt9, Bgl II for Mt6 and Rsa I for Mt8 segments in the region of cytochrome oxidase subunit complex. Significant associations were also observed at Mt9-Pvu II and Mt6-Bgl II segments for WT9 (p=0.01), WT12 (p=0.02), respectively. These results suggest that genetic variants of mtDNA in the region of cytochrome oxidase subunit complex may be candidate segments for improvement of animal growth as weight traits.
Kim, Sung-Mi;Reddy, Inja Naga Bheema Lingeswar;Yoon, In Sun;Kim, Beom-Gi;Kwon, Taek-Ryoun
Proceedings of the Korean Society of Crop Science Conference
/
2017.06a
/
pp.189-189
/
2017
Salinity is one of the major abiotic stresses that severely affect crop production throughout the world; especially rice plant which is generally categorized as a typical glycophyte as it cannot grow in the presence of salinity. Phenotypic resistance of salinity is expressed as the ability to survive and grow in a salinity condition. Salinity resistance has, at least implicitly, been treated as a single trait. Physiological studies of rice suggest that a range of characteristics (such as low shoot sodium concentration, compartmentation of salt in older rather than younger leaves, high potassium concentration, high $K^+/Na^+$ ratio, high biomass and plant vigour) would increase the ability of the plant to cope with salinity. Criteria for evaluating and screening salinity tolerance in crop plants vary depending on the level and duration of salt stress and the plant developmental stage. Plant growth responses to salinity vary with plant life cycle; critical stages sensitive to salinity are germination, seedling establishment and flowering. We have established a standard protocol to evaluate large rice germplasms for overall performance based on specific physiological traits for salt tolerance at seedling stage. This protocol will help in identifying germplasms which can perform better in the presence of different salinity treatments based on single trait and also combination of different physiological traits. The salt tolerant germplasm can be taken forward into developing better varieties by conventional breeding and exploring genes for salt tolerance.
Carcass characteristics data of Hanwoo (N = 1,084) were collected from two stations of the National Livestock Institute of Animal Science (NIAS), Korea and records from thirteen individual cow-calf operators were analyzed to estimate variance and covariance components and the effect of different slaughter endpoints. Carcass traits analyzed were cold carcass weight (CWT, kg), REA (rib eye area, cm2), back fat thickness (mm) and marbling score (1-7). Four different models were examined. All models included sex and contemporary group as fixed effects and the animal's direct genetic potential and environment as random effects. The first model fitted a linear covariate of age at slaughter. The second model fitted both linear and quadratic covariates of age at slaughter. The third model fitted a linear covariate of body weight at slaughter. The fourth model fitted both linear covariates of age at slaughter and body weight at slaughter. Variance components were estimated using the REML procedure with Gibb's sampler. Heritability estimate of CWT was in the range of 0.08-0.11 depending on the model applied. Heritability estimates of BF, REA and MS were in the ranges of 0.23-0.28, 0.19-0.26, and 0.44-0.45, respectively. Genetic correlations between CWT and BF, between CWT and REA, and between CWT and MS were in the ranges of -0.33 - -0.14, 0.73-0.84, and -0.01- 0.11, respectively. Genetic correlations between REA and BF, between MS and BF and between REA and MS were in the ranges of -0.82 ~ -0.72, 0.04~0.28 and -0.08 ~ -0.02, respectively. Variance and covariance components estimated varied by model with different slaughter endpoints. Body weight endpoint was more effective for direct selection in favor of yield traits and body weight endpoints affected more of the correlated response to selection for the traits of yield and quality of edible portion of beef.
Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.
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