Manjula, Prabuddha;Park, Hee-Bok;Seo, Dongwon;Choi, Nuri;Jin, Shil;Ahn, Sung Jin;Heo, Kang Nyeong;Kang, Bo Seok;Lee, Jun-Heon
Asian-Australasian Journal of Animal Sciences
/
v.31
no.1
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pp.26-31
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2018
Objective: This study estimated the genetic parameters for body weight gain and growth curve parameter traits in Korean native chicken (KNC). Methods: A total of 585 $F_1$ chickens were used along with 88 of their $F_0$ birds. Body weights were measured every 2 weeks from hatching to 20 weeks of age to measure weight gain at 2-week intervals. For each individual, a logistic growth curve model was fitted to the longitudinal growth dataset to obtain three growth curve parameters (${\alpha}$, asymptotic final body weight; ${\beta}$, inflection point; and ${\gamma}$, constant scale that was proportional to the overall growth rate). Genetic parameters were estimated based on the linear-mixed model using a restricted maximum likelihood method. Results: Heritability estimates of body weight gain traits were low to high (0.057 to 0.458). Heritability estimates for ${\alpha}$, ${\beta}$, and ${\gamma}$ were $0.211{\pm}0.08$, $0.249{\pm}0.09$, and $0.095{\pm}0.06$, respectively. Both genetic and phenotypic correlations between weight gain traits ranged from -0.527 to 0.993. Genetic and phenotypic correlation between the growth curve parameters and weight gain traits ranged from -0.968 to 0.987. Conclusion: Based on the results of this study population, we suggest that the KNC could be used for selective breeding between 6 and 8 weeks of age to enhance the overall genetic improvement of growth traits. After validation of these results in independent studies, these findings will be useful for further optimization of breeding programs for KNC.
The present study aimed to investigate the effects of maternal factors on body weight at hatching (day-old) and at six weeks of age in a commercial broiler line. A total of 6,765 records on body weight at day-old (BWTDO) and 115,421 records on body weight at six weeks of age (BWT6W), originated from a commercial broiler line during 14 generations, were used to estimate genetic parameters related to the effects of maternal traits on body weight of chicks immediately after hatch or six weeks thereafter. The data were analyzed using restricted maximum likelihood procedure (REML) and an animal model with DFREML software. Direct heritability ($h^{2}{_a}$), maternal heritability ($h^{2}{_m}$), and maternal environmental variance as the proportions of phenotypic variance ($c^{2}$) for body weight at day-old were estimated to be 0.050, 0.351, and 0.173, respectively. The respective estimated values for body weight at six weeks of age were 0.340, 0.022, and 0.030. The correlation coefficient between direct and maternal genetic effects for six-week-old body weight was found to be -0.335. Covariance components and genetic correlations were estimated using a bivariate analysis based on the best model determined by a univariate analysis. Between weights at hatching and at six week-old, the values of -0.07, 0.53 and 0.47 were found for the direct additive genetic variance, maternal additive genetic variance and permanent maternal environmental variance, respectively. The estimated correlation between direct additive genetic effect influencing weight at hatch and direct additive maternal effect affecting weight at six weeks of age was -0.21, whereas the correlation value of 0.15 was estimated between direct additive maternal effect influencing weight at hatch and direct additive genetic effect affecting weight at six-week-old. From the present findings, it can be concluded that the maternal additive genetic effect observed for weight at six weeks of age might be a factor transferred from genes influencing weight at hatch to weight at six-week-old.
Objective: The growth, carcass and retail cut yield records on 1,428 Hanwoo steers obtained through progeny testing were analyzed in this study, and their heritability and genetic relationships among the traits were estimated using animal models. Methods: Two different models were compared in this study. Each model was fitted for different fixed class effects, date of slaughter for carcass traits and batch of progeny test live measurement traits, and a choice of covariates (carcass weight in Model 1 or backfat thickness in Model 2) for carcass traits. Results: The differences in body composition among individuals were deemed being unaffected by their age at slaughter, except for carcass weight and backfat thickness. Heritability estimates of body size measurements were 0.21 to 0.36. Heritability estimates of retail cut percentage were high (0.56 from Model 1 and 0.47 from Model 2). And the heritability estimates for loin muscle percentage were 0.36 from Model 1 and 0.42 from Model 2, which were high enough to consider direct selection on carcass cutability traits as effective. The genetic correlations between body size measurements and retail cut ratio (RCR) were close to zero. But, some negative genetic correlations were found with chest girths measured at yearling (Model 1) or at 24 months of age or with chest widths. Loin muscle ratio (LMR) was genetically negatively correlated with body weights or body size measurements, in general in Model 1. These relationships were low close to zero but positive in Model 2. Phenotypic correlation between cutability traits (RCR, LMR) and live body size measurements were moderate and negative in Model 1 while those in Model 2 were all close to zero. Conclusion: Therefore, the body weights or linear body measurements at an earlier age may not be the most desirable selection traits for exploitation of correlated responses to improve loin muscle or lean meat yield.
This study was conducted to analyze the responses of some agronomic traits to the different cultural environments and relations among the agronomic traits for selecting sesame varieties with higher cultural stabilities. The indexes for stability parameters measured were coefficient of variability, heritabilities, genetic correlations and path coefficients of agronomic traits according to locations and years in Korea. The heritabilities of agronomic traits showed different by locations and years. Number of seeds per capsule and 1000 seeds weight showed higher heritabilities, but stem length and seed weight per plant showed relatively lower heritabilities. Average heritabilities of some agronomic traits in 1998 were comparatively higher than those of 1999. Of six areas, Jinju area showed biggest coefficient of yield variability in 1998-1999. Iksan and Taegu areas showed higher heritabilities in 1998, but Iksan and Jinju areas showed lower heritabilities in 1999. Genetic correlations were slightly higher than corresponding phenotypic correlations. Stem length showed positive genetic correlation with the number of capsules per plant, and seed weight per plant and the number of capsule per plant showed positive genetic correlation with seed weight per plant. On the analysis of path coefficients, stem length and number of capsules effected highly on grain yield. Great regional variations were observed on the effects of agronomic traits on grain yield. Higher direct effects of stem length on grain yield were observed at Suwon, Chungwon, Taegu, Jinju and Naju areas, but in Iksan area was observed higher direct effect of the number of capsules per plant on grain yield in 1998. In 1999, higher direct effect of stem length on grain yield was observed at Chungwon and Suwon areas. Iksan and Taegu areas were also observed higher direct effect of the number of capsule per plant on grain yield.
These studies were carried out to obtain useful information about the effective selection of vegetable perilla by estimating the genetic relationships between the heritabilities and the genetic correlations of quantitative traits among eight agronomic characters from 91 perilla varieties. The positive correlations were showed among characters such as between leaf weight and leaf size, leaf weight and leaf length, leaf weight and leaf width, leaf weight and plant height, leaf weight and stem diameter, leaf size and leaf length, leaf size and leaf width, leaf size and plant height, leaf size and stem diameter , leaf length and leaf width, leaf length and plant height, leaf length and stem diameter, leaf width and plant height, leaf width and stem diameter, plant height and stem diameter, plant height and the number of internodes per plant, and the number of internodes per plant and the number of leaves per plant. Heritabilities were high as from 0.7311 to 0.9112 among leaf weight, leaf size, leaf length, leaf width, plant height, stem diameter, and the number of internodes per plant.
Joon-Ki Hong;Yong-Min Kim;Eun-Seok Cho;Jae-Bong Lee;Young-Sin Kim;Hee-Bok Park
Animal Bioscience
/
v.37
no.4
/
pp.622-630
/
2024
Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.
The aim of this study was to isolate enterococci in Sucuk, a traditional Turkish dry-fermented sausage and to analyze isolates for their biodiversity, antibiotic resistance patterns and the presence of some antibiotic resistance genes. A total of 60 enterococci strains were isolated from 20 sucuk samples manufactured without using a starter culture and they were identified as E. faecium (73.3%), E. faecalis (11.7%), E. hirae (8.3%), E. durans (3.3%), E. mundtii (1.7%) and E. thailandicus (1.7%). Most of the strains were found resistant to rifampin (51.67%) followed by ciprofloxacin (38.33%), nitrofurantoin (33.33%) and erythromycin (21.67%). All strains were found susceptible to ampicillin. Only E. faecium FYE4 and FYE60 strains displayed susceptibility to all antibiotics. Other strains showed different resistance patterns to antibiotics. E. faecalis was found more resistant to antibiotics than other species. Most of the strains (61.7%) displayed resistance from between two and eight antibiotics. The ermB, ermC, gyrA, tetM, tetL and vanA genes were detected in some strains. A lack of correlation between genotypic and phenotypic analysis for some strains was detected. The results of this study indicated that Sucuk manufactured without using a starter culture is a reservoir of multiple antibiotic resistant enterococci. Consequently, Sucuk is a potential reservoir for the transmission of antibiotic resistance genes from animals to humans.
Natural killer (NK) cells have been reported to be dysfunctional in chronic hepatitis B (CHB) infection. However, the functional recovery of NK cells under antiviral therapeutic agents in CHB was not clearly understood. In this study, we investigated the phenotypic changes of NK(CD56+CD3-) cells in terms of their functional markers (CD16, NKG2A, NKG2D) during tenofovir therapy in CHB. The frequency of NK(CD56+CD3-) cells in CHB patients was significantly increased after 12 months of tenofovir therapy when compared with baseline. The expression levels of CD16+/CD56+CD3- and NKG2A+/CD56+CD3- cells were also affected by tenofovir treatment. In addition, there was a positive correlation between the proportion of NK(CD56+CD3-) cells and HBV DNA (log copies/ml) in CHB patients.
Lee, Suk-Ha;Park, Keum-Yong;Lee, Hong-Suk;H. Roger Boerma
KOREAN JOURNAL OF CROP SCIENCE
/
v.44
no.2
/
pp.166-170
/
1999
The identification of quantitative trait loci (QTL) has the potential to enhance the efficiency of im- proving food processing traits of soybean. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W$_1$ and T) were used to identify QTL associated with food processing traits of soybean for sprout in 83 F$_2$-derived lines from a cross of 'Pureun' x 'Jinpum 2'. The genetic map consisted of 76 loci which covered about 760 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected for hypocotyl length, abnormal seedling rate, and sprout yield seven days after seed germination at 2$0^{\circ}C$. Based on the single-factor analysis of variance, eight independent markers were associated with hypocotyl length. Four of seven markers associated with abnormal seedling rate were identified as independent. Seven loci were associated with sprout yield. For three different traits, much of genetic variation was explained by the identified QTL in this population. Several RFLP markers in linkage group (LG) Bl were detected as being associated with three traits, providing a genetic explanation for the biological correlation of sprout yield with hypocotyl length (r=OA07***) and with abnormal seedling rate (r=-406***).
The present study was carried out to obtain some basic informations of the breeding of tobacco varieties. Genetically divergent 8 varieties, 3 flue-cured, 2 burley and 3 sun-cured tobaccos, were used in half diallel cross. In order to analyze the heterosis, combining abilities, modes of inheritance and correlations for some agronomic and chemical characters, 8 parents and 28 $F_2$ were tested. The results obtained were summarized as follows: The percentages of heterosis for yield, stem diameter, internode length and total sugar content in $F_2$ hybrid were positive , where-as those for the other characters were negative. Yield had significant positive genotypic and phenotypic correlations with plant height, days to flower, leaves per plant, leaf length, leaf width and leaf shape index (Leaf length/leaf width). General (GCA) and specific combining abilities (SCA) for all characters of $F_2$ hybrid were significant. In the effect of GCA, yield was greater in combinations of Bulgaria and Xanthi, days to flower and leaves per plant were those of Burley 21 and Va 528, leaf length and width were those of Coker 139, respectively. In the effect of SCA, the major part of characters were greater than those of others in the combinations of Burley 21, Va 528, Hicks.
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