• Title/Summary/Keyword: Phenotypic and Genetic Correlation

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Agronomic Characters and Their Correlation Coefficient on Black Seeded Soybeans Collected in Chonnam Province

  • Kwon, Byung-Sun;Choi, Seong-kyu;Shin, Jeong-Sik;Shin, Dong-Youn;Kyu Hwan
    • Plant Resources
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    • v.5 no.2
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    • pp.118-123
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    • 2002
  • In order to obtain the genetic information on the quantitative characters of black seeded soybeans, which would be needed to improve selection efficiency for breeding high yielding genotype, 45 varieties of black seeded soybeans collected in Chonnam, Korea were grown and variations of several important characters were observed. Heritability of each observed character, phenotypic and genotypic correlations among the characters and contribution of each yield component on grain yield through path coefficient analysis were estimated. Both number of pods per plant and 100-seed weight showed not only high heritability but also highly significant phenotypic and genotypic correlation with seed yield, and hence it was desirable to select plants with more number of pods per plant and higher 100-seed weight than raise seed yield of black seeded soybeans collected in Chonnam. In addition, number of pods per and 100-seed weight were proved to be the most influential variables on the viability of seed yield by path coefficient analysis. Since these showed the high heritability of number of pods per plant, selection of plants with higher 100-seed weight would be more efficient for breeding high yielding genotype.

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Utilization of Elite Korean Japonica Rice Varieties for Association Mapping of Heading Time, Culm Length, and Amylose and Protein Content

  • Mo, Youngjun;Jeong, Jong-Min;Kim, Bo-Kyeong;Kwon, Soon-Wook;Jeung, Ji-Ung
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.65 no.1
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    • pp.1-21
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    • 2020
  • Association mapping is widely used in rice and other crops to identify genes underlying important agronomic traits. Most association mapping studies use diversity panels comprising accessions with various geographical origins to exploit their wide genetic variation. While locally adapted breeding lines are rarely used in association mapping owing to limited genetic diversity, genes/alleles identified from elite germplasm are practically valuable as they can be directly utilized in breeding programs. In this study, we analyzed genetic diversity of 179 rice varieties (161 japonica and 18 Tongil-type) released in Korea from 1970 to 2006 using 192 microsatellite markers evenly distributed across the genome. The 161 japonica rice varieties were genetically very close to each other with limited diversity as they were developed mainly through elite-by-elite crosses to meet the specific local demands for high quality japonica rice in Korea. Despite the narrow genetic background, abundant phenotypic variation was observed in heading time, culm length, and amylose and protein content in the 161 japonica rice varieties. Using these varieties in association mapping, we identified six, seven, ten, and four loci significantly associated with heading time, culm length, and amylose and protein content, respectively. The sums of allelic effects of these loci showed highly significant positive correlation with the observed phenotypic values for each trait, indicating that the allelic variation at these loci can be useful when designing cross combinations and predicting progeny performance in local breeding programs.

Estimation of heritability and genetic correlation of body weight gain and growth curve parameters in Korean native chicken

  • 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
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    • 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.

Genetic parameters and correlations of related feed efficiency, growth, and carcass traits in Hanwoo beef cattle

  • Mehrban, Hossein;Naserkheil, Masoumeh;Lee, Deuk Hwan;Ibanez-Escriche, Noelia
    • Animal Bioscience
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    • v.34 no.5
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    • pp.824-832
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    • 2021
  • Objective: This study aimed to estimate the genetic parameters and genetic correlations for related feed efficiency, growth, and carcass traits in Hanwoo cattle. Methods: Phenotypic data from 15,279 animals born between 1989 and 2015 were considered. The related feed efficiency traits considered were Kleiber ratio (KR) and relative growth rate (RGR). Carcass traits analyzed were backfat thickness (BT), carcass weight, eye muscle area, and marbling score. Growth traits were assessed by the average daily gain (ADG), metabolic body weight (MBW) at mid-test age from 6 to 24 months, and yearling weight (YW). Variance and covariance components were estimated using restricted maximum likelihood using nine multi-trait animal models. Results: The heritability estimates for related feed efficiency (0.28±0.04 for KR and RGR) and growth traits (0.26±0.02 to 0.33±0.04) were moderate, but the carcass traits tended to be higher (0.38±0.04 to 0.61±0.06). The related feed efficiency traits were positively genetically correlated with all the carcass traits (0.37±0.09 to 0.47±0.07 for KR, and 0.14±0.09 to 0.37±0.09 for RGR), except for BT, which showed null to weak correlation. Conversely, the genetic correlations of RGR with MBW (-0.36±0.08) and YW (-0.30±0.08) were negative, and those of KR with MBW and YW were close to zero, whereas the genetic correlations of ADG with RGR (0.40±0.08) and KR (0.70±0.05) were positive and relatively moderate to high. The genetic (0.92±0.02) correlations between KR and RGR were very high. Conclusion: Sufficient genetic variability and heritability were observed for traits of interest. Moreover, the inclusion of KR and/or RGR in Hanwoo cattle breeding programs could improve the feed efficiency without producing any unfavorable effects on the carcass traits.

Genetic correlation between live body measurements and beef cutability traits in Hanwoo steers

  • Choy, Yun Ho;Lee, Jae Goo;Mahboob, Alam;Choi, Tae Jeong;Rho, Seung Hee
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.8
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    • pp.1074-1080
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    • 2017
  • 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.

Estimation of Heritabilities and Genetic Correlations on Major Economic Traits in Korean Native Chicken (한국재래계의 주요경제형질에 대한 유전력 및 유전상관 추정)

  • 한성욱;이준현;상병찬
    • Korean Journal of Poultry Science
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    • v.22 no.2
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    • pp.67-75
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    • 1995
  • The present study was conducted to estimate production performances, heritabilities, and genetic and phenotypic correlations on several economic traits in Korean native chicken. Data analyzed were the records of 1,096 pullets produced from 180 dams and 26 sires of Korean native chicken from April 19,1994 to February 26, 1995. Results obtained are surnmarized as follows: 1. The body weights(X${\pm}$SD) at 2, 8, 14 and 20 weeks of age were 114${\pm}$13, 690${\pm}$114, 1,163${\pm}$238, and 1,687${\pm}$349g, respectively. The age at first egg was 165.95${\pm}$14.54 days, and the number of eggs produced by 300 days of age were 70.78i23.47. The egg weights of the first egg and at 300 days of age were 37.88${\pm}$3.73 and 50.97${\pm}$3.69 g, respectively. 2. The heritability estimates of body weight based on the variance of sires, dams and combined components were 0.149, 0.298, and 0.224 at 8 weeks of age: 0.162, 0.220, and 0.192 at 20 weeks of age, respectively. 3. The heritability estimates of egg production traits based on the variance of sires, dams, and combined components were 0.232, 0.504, and 0.368 for age at first egg; 0.113, 0.172, and 0.143 for number of egg production by 300 days of age: 0.174, 0.352, and 0.236 for egg weight at 300 days of age, respectively. 4. The genetic correlation coefficients of some economic traits were as follows: between body weight and age at first egg, -0.354~-0.048; between body weight and number of egg production, -0.279~ -0.002; between body weight and egg weight, 0.338~0.977; between age at first egg and number of egg production, -0.791; between age at first egg and egg weight, 0.009~0.178; between number of egg production and egg weight, -0.572~ -0.256, respectively. 5. The phenotypic correlation coefficients of some economic traits were as follows: between body weight and age at first egg, -0.179~-0.006 between body weight and number of egg production, -0.045~0.074: between body weight and egg weight, 0.229~0.404: between age at first egg and number of egg production, -0.588: between age at first egg and egg weight, -0.029~0.597: between number of egg production and egg weight, -0.376~0. 019, respectively.

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Genetic and Phenotypic Parameter Estimates of Body Weight at Different Ages and Yearling Fleece Weight in Markhoz Goats

  • Rashidi, A.;Sheikahmadi, M.;Rostamzadeh, J.;Shrestha, J.N.B.
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.10
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    • pp.1395-1403
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    • 2008
  • The objective of the present study was to estimate genetic parameters for economic traits in Markhoz goats. Data collected from 1993 to 2006 by the Markhoz goat Performance Testing Station in Sanandaj, Iran, were analyzed. The traits recorded as body weight performance at birth (BW), weaning (WW), six month (6MW), nine month (9MW), yearling (YW) and yearling fleece weight (YFW) were investigated. Least square analyses were used for estimation of environmental effects. Genetic parameters were estimated with single and multi trait analysis using restricted maximum likelihood (REML) procedures, under animal models. By ignoring or including maternal additive genetic effects and maternal permanent environmental effects, five different models were fitted for each trait. The effects of sex, type of birth, age of dam and year of birth on the all body weights were significant (p<0.01), but had no effects on YFW except year of birth. Age of kids had significant influences on WW and 6MW (p<0.01). A log likelihood ratio test was carried out for choosing the most suitable model for each trait. Total heritability estimates for YFW and growth traits varied from 0.16 for YFW and WW to 0.41 for YW. For all traits, maternal heritability was lower than direct heritability, ranging from 0.06 for BW to 0.01 for 6MW and 9MW. The magnitude of $c^2$ was more substantial for BW than the others, and relative importance was reduced from 0.12 for BW to 0.04 for 9MW. The direct additive genetic correlations estimates were positive and varied from 0.21 between BW-YW to 0.96 between WW-6MW. Direct additive genetic correlations between YFW and body weight traits were positive and ranged from 0.14 between BW-YFW to 0.67 between 6MW-YFW. For all traits, the corresponding estimates for phenotypic correlation were positive and lower than genetic correlations. The maternal additive genetic correlations between various traits were varied and ranged from -0.19 between 9MW-YFW to 0.96 between 6MW-9MW. The estimates of the maternal permanent environmental correlations between various traits were positive and ranged from 0.33 between WW-YFW to 0.93 between WW-6MW. Also, the environmental correlations between various traits ranged from 0.01 between BW-YFW and WW-YFW to 0.70 between 9MW-YW. Estimates of genetic parameters for various traits in this study confirm that selection should be applied on WW for genetic improvement in Markhoz goats.

Effects of season and age at first calving on genetic and phenotypic characteristics of lactation curve parameters in Holstein cows

  • Torshizi, Mahdi Elahi
    • Journal of Animal Science and Technology
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    • v.58 no.2
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    • pp.8.1-8.14
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    • 2016
  • In this research data representing 72,946 primiparous cows from 724 herds with 638,063 total test day records calved between 2001 and 2011. These data were analysed to determine the effect of age at first and season of calving on parameters of the Wood lactation curve. Also, genetic trend of the lactation curve parameters in different calving years were evaluated. The results indicate that the highest rate of atypical lactation curve was related to cows that calved in summer (28.05 %). The maximum phenotypic relationship between initial milk yield and total 305-d milk yield was observed in cows calved in spring (0.40). The role of peak yield is more than peak time on 305-d total milk yield in primiparous Holstein. One month increase in age at first calving from 18 to 26 month raised 305-d milk yield by around 138 kg and from 27 to 32 month decreased by 61 kg. The persistency of lactation between 101 and 200 days is higher than that of 201-305 days. Our results indicate that the shape of lactation curve is largely dependent on the season of calving (higher level of milk production in cows which calved in autumn and winter). The heritabilities of parameters of lactation curve and persistency measures were low. The genetic trends for peak time, peak yield and 305-d milk yields were positive and estimated to be 0.019, 0.021 and 8.13 kg/year respectively. So the range from 24 to 26.5 month of calving is the optimum calving time in primiparous Holstein for maximizing 305-d milk yield.

Application of deep learning with bivariate models for genomic prediction of sow lifetime productivity-related traits

  • Joon-Ki Hong;Yong-Min Kim;Eun-Seok Cho;Jae-Bong Lee;Young-Sin Kim;Hee-Bok Park
    • Animal Bioscience
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    • v.37 no.4
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    • pp.622-630
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    • 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.

Genetic Relationship of Productive Life, Production and Type Traits of Korean Holsteins at Early Lactations

  • Wasana, Nidarshani;Cho, GwangHyun;Park, SuBong;Kim, SiDong;Choi, JaeGwan;Park, ByungHo;Park, ChanHyuk;Do, ChangHee
    • Asian-Australasian Journal of Animal Sciences
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    • v.28 no.9
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    • pp.1259-1265
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    • 2015
  • The present study was performed to study the genetic relationship of productive life with production and type traits of Korean Holsteins at first three lactations. The data for the analysis from 56,054, 28,997, and 11,816 animals of first, second and third parity cows which were born from 2006 to 2011 were collected by Dairy Cattle Improvement Center, National Agricultural Co-operative Federation. Milk, protein and fat yields adjusted for 305 days and average somatic cell score considered as production traits and analyzed type traits were stature, strength, body depth, dairy form, rump angle, rump width, rear leg side view, foot angle, front attachment placement, rear attachment height, rear attachment width, udder cleft, udder depth, front teat placement and front teat length. A multi trait genetic analysis was performed using Wombat program with restricted maximum likelihood animal model composed of fixed effect of birth year, farm and the random effect of animal and random residual effect according to the traits. Heritability estimates of productive life were between 0.06 and 0.13. Genetic and phenotypic correlations between production and productive life traits ranged from 0.35 to 0.04 for milk, 0.16 to 0.05 for protein and 0.18 to 0.02 f 15-0034 (2nd) 150520 or fat. Somatic cells score showed a negative genetic and phenotypic correlation with productive life and also udder type traits, indicating that the selection for higher udder traits will likely to improve resistance to mastitis and persistence in the herd. Among all dairy form type traits, udder characters such as udder cleft showed a significant relationship with productive life. However, a specific change of heritabilities or correlations were not observed with the change of parity. Moreover, further studies are needed to further confirm the significance of the above traits and the effect of parity on above relationships in order to minimize both voluntary and involuntary culling rates while improving herd health and maintaining high yielding dairy cows.