• Journal of Microbiology and Biotechnology
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• v.24 no.9
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• pp.1162-1169
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• 2014

Glyphosate is the active component of the top-selling herbicide, the phytotoxicity of which is due to its inhibition of the shikimic acid pathway. 5-Enolpyruvylshikimate-3-phosphate synthase (EPSPS) is a key enzyme in the shikimic acid pathway. Glyphosate tolerance in plants can be achieved by the expression of a glyphosate-insensitive aroA gene (EPSPS). In this study, we used a PCR-based two-step DNA synthesis method to synthesize a new aroA gene ($aroA_{R.\;leguminosarum}$) from Rhizobium leguminosarum. In vitro glyphosate sensitivity assays showed that $aroA_{R.\;leguminosarum}$ is glyphosate tolerant. The new gene was then expressed in E. coli and key kinetic values of the purified enzyme were determined. Furthermore, we transformed the aroA gene into Arabidopsis thaliana by the floral dip method. Transgenic Arabidopsis with the $aroA_{R.\;leguminosarum}$ gene was obtained to prove its potential use in developing glyphosate-resistant crops.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.5
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• pp.597-602
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• 2001

This study was conducted to examine the relationships between the methods used to determine the number of transferable embryos collected per flush and the estimated cumulative genetic improvements in the Japanese Holstein MOET breeding population. Cumulative genetic improvements were predicted by Monte Carlo simulation using three different determination methods (MODEL 1, MODEL 2, and MODEL 3), for calculating the number of embryos collected per flush. Moreover EBVs were estimated including or ignoring coefficients of inbreeding in MME. Inbreeding coefficients were also predicted. The number of transferable embryos was determined using normal, gamma, and Poisson distributions in MODEL 1, gamma and Poisson distributions in MODEL 2, and only the Poisson distribution in MODEL 3. The fitness of MODEL 2 in relation to field data from Hokkaido Japan was the best, and the results for MODEL3 indicated that this model is unsuitable for determining the number of transferable embryos. The largest cumulative genetic improvement (3.11) in the 10th generation was predicted by MODEL 3 and the smallest (2.83) by MODEL 2. Mean coefficients of correlation between the true and estimated breeding values were 0.738, 0.729, and 0.773 in MODELS 1, 2, and 3, respectively. It is suggested that the smallest genetic improvement in MODEL 2 resulted from the smallest correlation coefficient between the true and estimated breeding values. The differences in milk, fat, and protein yields between MODELS 2 and 3 were 182.0, 7.0, and 5.6 kg, respectively, in real units when each trait was independently selected. The inbreeding coefficient was the highest (0.374) in MODEL 2 and the lowest (0.357) in MODEL 3. The effects of different methods for determining the number of transferable embryos per flush on genetic improvements and inbreeding coefficients of the simulated populations were remarkable. The effects of including coefficients of inbreeding in MME, however, were unclear.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1217-1224
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• 2006

The registration data of 15 populations from nine major swine breeding farms were investigated to check levels of inbreeding and the current status of pedigree structures of breeding stocks. The average rate of inbreeding per generation was 0.208%, 0.209%, 0.098%, 0.307% and 0.071% for farms D, S, K, H, and Y in Duroc, 0.071%, 0.188%, 0.685%, 0.336%, and 0.449% for farms S, H, C, J, and W in Landrace, and 0.243%, 0.123%, 0.103%, 0.165%, and 0.286% for farms D, S, G, H, and J in Yorkshire, respectively. The average inbreeding rate was highest for Landrace, intermediate for Yorkshire, and lowest for Duroc farms. In Landrace and Yorkshire populations there were few immigrant animals per generation. In Duroc, however, there were quite large numbers of immigrant animals per generation compared to other breeds. The effective population sizes calculated from the average rate of inbreeding were distributed between 73.0 and 708.7. Specific values were 204.8, 239.7, 508.8, 163.0 and 708.2 for farms D, S, K, H, and Y in Duroc, 708.7, 266.5, 73.0, 148.9, and 111.3 for farms S, H, C, J, and W in Landrace, and 205.5, 406.0, 486.9, 302.6 and 175.0 for farms D, S, G, H, and J in Yorkshire, respectively. The values were acceptable for natural selection for fitness and inbreeding depression. The results showed that there was no cause for concern over the current inbreeding level of major swine breeding farm populations and the inbreeding level was within an acceptable range.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.5
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• pp.628-635
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• 2018

Objective: To determine the effects of genomic breeding values (GBV) and single nucleotide polymorphisms (SNP) on the total number of piglets born (TNB) in 3 pig breeds (Berkshire, Landrace, and Yorkshire). Methods: After collecting genomic information (Porcine SNP BeadChip) and phenotypic TNB records for each breed, the effects of GBV and SNP were estimated by using single step best linear unbiased prediction (ssBLUP) method. Results: The heritability estimates for TNB in Berkshire, Landrace, and Yorkshire breeds were 0.078, 0.107, and 0.121, respectively. The breeding value estimates for TNB in Berkshire, Landrace, and Yorkshire breeds were in the range of -1.34 to 1.47 heads, -1.79 to 1.87 heads, and -2.60 to 2.94 heads, respectively. Of sows having records for TNB, the reliability of breeding value for individuals with SNP information was higher than that for individuals without SNP information. Distributions of the SNP effects on TNB did not follow gamma distribution. Most SNP effects were near zero. Only a few SNPs had large effects. The numbers of SNPs with absolute value of more than 4 standard deviations in Berkshire, Landrace, and Yorkshire breeds were 11, 8, and 19, respectively. There was no SNP with absolute value of more than 5 standard deviations in Berkshire or Landrace. However, in Yorkshire, four SNPs (ASGA 0089457, ASGA0103374, ALGA0111816, and ALGA0098882) had absolute values of more than 5 standard deviations. Conclusion: There was no common SNP with large effect among breeds. This might be due to the large genetic composition differences and the small size of reference population. For the precise evaluation of genetic performance of individuals using a genomic selection method, it may be necessary to establish the appropriate size of reference population.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.5
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• pp.635-638
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• 2003

Japanese Black cattle (Wagyu) are fed for a long period to produce high quality beef, however, extended feeding often causes inefficiency and greater environmental load mainly derived from their manure. The objectives of this study were to analyze changes in feeding length by listing breeding values (BVs) at calf markets and the relationships between BVs and carcass characteristics of 4,052 Japanese Black cattle, and to examine the feasibility of optimizing feeding length by referring to listed BVs. BV classes A, B, and C were defined based on BVs of cows in Shimane Prefecture as follows: an upper quarter of BVs was classified as A, a second quarter as B, and under the average as C. For cattle sold at calf markets in the first term of 1996, just before the start of BV listing, the feeding length of cattle with class B BVs for the beef marbling standard (BMS) was longer (p>0.05) than that of class A cattle. However, in the second term of 1996, just after the start of BV listing, the feeding length of class B cattle became shorter (p<0.001) than that of class A cattle. Then, the feeding lengths of both classes showed no significant differences. Feeding lengths of both class A and B BVs for carcass weight (CW) changed similarly to the corresponding BV classes for BMS. The analysis of the relationships among the listed BV classes and the actual carcass characteristics showed that class A cattle had a higher (p<0.001) BMS than class B cattle, and that the higher-class cattle had a heavier CW (p<0.05). On the basis of previous reports, the cattle, particularly those with lower genetic marbling ability, seem to only increase marbling at markedly low efficiency for a few months before slaughter. Therefore, the finding that carcass characteristics corresponded to their class of BVs suggests that an optimum feeding length based on listed BVs not only increases the efficiency of beef production, but also reduces the environmental load.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.9
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• pp.1244-1251
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• 2015

A herd of Berkshire pigs was established in 2003 and subjected to selection without introduction of any genetic resources until 2007. The complete pedigree, including 410 boars and 916 sows, as well as the records from 5,845 pigs and 822 litters were used to investigate the results obtained from the selections. The index of selection for breeding values included days to 90 kg (D90kg), backfat thickness (BF) and number of piglets born alive (NBA). The average inbreeding coefficients of pigs were found to be 0.023, 0.008, 0.013, 0.025, 0.026, and 0.005 from 2003 to 2007, respectively. The genetic gains per year were 12.1 g, -0.04 mm, -3.13 days, and 0.181 head for average daily gain (ADG), BF, D90kg, and NBA, respectively. Breeding values of ADG, BF and D90kg were not significantly correlated with inbreeding coefficients of individuals, except for NBA (-0.21). The response per additional 1% of inbreeding was 0.0278 head reduction in NBA. The annual increase of inbreeding was 0.23% and the annual decrease in NBA due to inbreeding was 0.0064 head. This magnitude could be disregarded when compared with the annual gain in NBA (0.181 head). These results suggest that inbreeding and inbreeding depression on ordinary farms can be controlled with a proper breeding scheme and that breeding programs are economical and safe relative to the risks associated with importation of pigs.

• Journal of Veterinary Clinics
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• v.16 no.2
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• pp.332-338
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• 1999

This study was carried out to investigate weight gain and prevention of diarrhea in suckling calves which were injected with recombinant bovine somatopropin (rBST). A total of 101 breeding cows were assigned to the six groups according to the administered dosage and injected time, respectively. Groups T-1, T-3, T-4 and T-6 were injected starting 1 week before calving and groups T-2 and T-5 were injected on the calving day. The six groups were injected five times at two week intervals. Groups T-1 and T-2 were injected with 250mg composite rBST, Group T-3 was injected with 375 mg composite rBST. Groups T-4 and T-5 were injected with 500mg composite rBST, And group T-6 was injected with 500mg rBST-S. The control group was not injected with BST. The groups injected with 500 mg BrST had a lower rate of morbidity from diarrhea than the control group or the groups injected with 250 mg rBST (T-1 and T-2). Weight gain was higher in group T-4 than in the control group or groups T-1 and T-2. In Korean Native Cattle, the total weight gain was greater in group T-4 than in the control group (p<0.05). In crossbred cows, total weight gain was the highest in group T-4, and the total weight gain rate was greater than in group T-4 and the control group (p<0.05). The results of the hematological values showed that injections of rBST did not affect the level of the RBC, TP and BUN in the breeding cows at 9 weeks after postpartum or the neonatal calves. The results of this study indicate that injecting breeding cows with 500 mg rBST before calving would be effective in the preventing of diarrhea and in increasing weight gain of calves from birth to weaning.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.3
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• pp.299-303
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• 2012

Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ($\bar{r_j}$) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, $EBV^*=EBV_j(1-k\bar{{r}_j})$ Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.6
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• pp.772-779
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• 2013

Linkage disequilibrium (LD) plays an important role in genomic selection and mapping quantitative trait loci (QTL). In this study, the pattern of LD and effective population size ($N_e$) were investigated in Chinese beef Simmental cattle. A total of 640 bulls were genotyped with IlluminaBovinSNP50BeadChip and IlluminaBovinHDBeadChip. We estimated LD for each autosomal chromosome at the distance between two random SNPs of <0 to 25 kb, 25 to 50 kb, 50 to 100 kb, 100 to 500 kb, 0.5 to 1 Mb, 1 to 5 Mb and 5 to 10 Mb. The mean values of $r^2$ were 0.30, 0.16 and 0.08, when the separation between SNPs ranged from 0 to 25 kb to 50 to 100 kb and then to 0.5 to 1 Mb, respectively. The LD estimates decreased as the distance increased in SNP pairs, and increased with the increase of minor allelic frequency (MAF) and with the decrease of sample sizes. Estimates of effective population size for Chinese beef Simmental cattle decreased in the past generations and $N_e$ was 73 at five generations ago.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.11
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• pp.1540-1547
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• 2014

The accuracy of genomic estimated breeding values (GEBV) was evaluated for sixteen meat quality traits in a Berkshire population (n = 1,191) that was collected from Dasan breeding farm, Namwon, Korea. The animals were genotyped with the Illumina porcine 62 K single nucleotide polymorphism (SNP) bead chips, in which a set of 36,605 SNPs were available after quality control tests. Two methods were applied to evaluate GEBV accuracies, i.e. genome based linear unbiased prediction method (GBLUP) and Bayes B, using ASREML 3.0 and Gensel 4.0 software, respectively. The traits composed different sets of training (both genotypes and phenotypes) and testing (genotypes only) data. Under the GBLUP model, the GEBV accuracies for the training data ranged from $0.42{\pm}0.08$ for collagen to $0.75{\pm}0.02$ for water holding capacity with an average of $0.65{\pm}0.04$ across all the traits. Under the Bayes B model, the GEBV accuracy ranged from $0.10{\pm}0.14$ for National Pork Producers Council (NPCC) marbling score to $0.76{\pm}0.04$ for drip loss, with an average of $0.49{\pm}0.10$. For the testing samples, the GEBV accuracy had an average of $0.46{\pm}0.10$ under the GBLUP model, ranging from $0.20{\pm}0.18$ for protein to $0.65{\pm}0.06$ for drip loss. Under the Bayes B model, the GEBV accuracy ranged from $0.04{\pm}0.09$ for NPCC marbling score to $0.72{\pm}0.05$ for drip loss with an average of $0.38{\pm}0.13$. The GEBV accuracy increased with the size of the training data and heritability. In general, the GEBV accuracies under the Bayes B model were lower than under the GBLUP model, especially when the training sample size was small. Our results suggest that a much greater training sample size is needed to get better GEBV accuracies for the testing samples.