• The Plant Pathology Journal
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• v.32 no.2
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• pp.95-101
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• 2016

Inheritance of resistance to Fusarium wilt (FW) disease caused by Fusarium udum was investigated in pigeonpea using four different long duration FW resistant genotypes viz., BDN-2004-1, BDN-2001-9, BWR-133 and IPA-234. Based on the $F_2$ segregation pattern, FW resistance has been reported to be governed by one dominant gene in BDN-2004-1 and BDN-2001-9, two duplicate dominant genes in BWR-133 and two dominant complimentary genes in resistance source IPA-234. Further, the efficacy of six simple sequence repeat (SSR) markers namely, ASSR-1, ASSR-23, ASSR-148, ASSR-229, ASSR-363 and ASSR-366 reported to be associated with FW resistance were also tested and concluded that markers ASSR-1, ASSR-23, ASSR-148 will be used for screening of parental genotypes in pigeonpea FW resistance breeding programs. The information on genetics of FW resistance generated from this study would be used, to introgress FW resistance into susceptible but highly adopted cultivars through marker-assisted backcross breeding and in conventional breeding programs.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2005.04a
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• pp.90-90
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• 2005

• Molecules and Cells
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• v.40 no.11
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• pp.814-822
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• 2017

Meiotic homologous recombination generates new combinations of preexisting genetic variation and is a crucial process in plant breeding. Within the last decade, our understanding of plant meiotic recombination and genome diversity has advanced considerably. Innovation in DNA sequencing technology has led to the exploration of high-resolution genetic and epigenetic information in plant genomes, which has helped to accelerate plant breeding practices via high-throughput genotyping, and linkage and association mapping. In addition, great advances toward understanding the genetic and epigenetic control mechanisms of meiotic recombination have enabled the expansion of breeding programs and the unlocking of genetic diversity that can be used for crop improvement. This review highlights the recent literature on plant meiotic recombination and discusses the translation of this knowledge to the manipulation of meiotic recombination frequency and location with regards to crop plant breeding.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.4
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• pp.441-444
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• 2004

The genetic diversities and relationships of 10 Chinese indigenous pig breeds and three exotic pig breeds have been evaluated using 26 microsatellites recommended by the Food and Agriculture Organization & the International Society of Animal Genetics (FAO-ISAG). The allele frequencies, genetic heterozygosity (H) and polymorphism information content (PIC) have been calculated. The results showed that genetic diversity of Chinese indigenous pig breeds is higher than that of the introduced pig breeds. The clustering of 10 breeds is generally consistent with their geographical distribution.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.720-734
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• 2023

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (M_e) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between M_e and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between M_e and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the M_e, the higher the accuracy of EBV.

• Food Science of Animal Resources
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• v.42 no.1
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• pp.1-17
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• 2022

Lipids are one of the major macronutrients essential for adequate growth and maintenance of human health. Their structure is not only complex but also diverse, which makes systematic and holistic analyses challenging; consequently, little is known regarding the relationship between phenotype and mechanism of action. In recent years, rapid advancements have been made in the fields of lipidomics and bioinformatics. In comparison with traditional approaches, mass spectrometry-based lipidomics can rapidly identify as well as quantify >1,000 lipid species at the same time, facilitating comprehensive, robust analyses of lipids in tissues, cells, and body fluids. Accordingly, lipidomics is now being widely applied in various fields, particularly food and nutrition science. In this review, we discuss lipid classification, extraction techniques, and detection and analysis using lipidomics. We also cover how lipidomics is being used to assess food obtained from livestock and poultry. The information included herein should serve as a reference to determine how to characterize lipids in animal food samples, enhancing our understanding of the application of lipidomics in the field in animal husbandry.

• Korean Journal of Breeding Science
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• v.42 no.1
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• pp.11-22
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• 2010

The population structure of a domesticated species is influenced by the natural history of the populations of its pre-domesticated ancestors, as well as by the breeding system and complexity of breeding practices implemented by humans. In the genetic and population structure analysis of 122 South Asia collections using 29 simple sequence repeat (SSR) markers, 362 alleles were detected, with an average of 12.5 per locus. The average expected heterozygosity and polymorphism information content (PIC) for each SSR locus were 0.74 and 0.72,respectively. The model-based structure analysis revealed the presence of three clusters with the 91.8% (shared > 75%) membership, with 8.2% showing admixture. The genetic distances of Clusters 1-3 were 0.55, 0.56, and 0.68, respectively. Polymorphic information content followed the same trend (Cluster 3 had the highest value and Cluster 1 had smallest value), with genetic distances for each cluster of 0.52, 0.52, and 0.65, respectively. This result could be used for supporting rice breeding programs in South Asia countries.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.233-233
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• 2022

As the world's population grows and food needs diversify, the demand for horticultural crops for beneficial traits is increasing. In order to meet this demand, it is necessary to develop suitable cultivars and breeding methods accordingly. Breeding methods have changed over time. With the recent development of sequencing technology, the concept of genomic selection (GS) has emerged as large-scale genome information can be used. GS shows good predictive ability even for quantitative traits by using various markers, breaking away from the limitations of Marker Assisted Selection (MAS). Moreover, GS using machine learning (ML) and deep learning (DL) has been studied recently. In this study, we aim to build a system that selects phenotype-related markers using the genomic information of the pepper population and trains a genomic selection model to select individuals from the validation population. We plan to establish an optimal genome wide association analysis model by comparing and analyzing five models. Validation of molecular markers by applying linkage markers discovered through genome wide association analysis to breeding populations. Finally, we plan to establish an optimal genome selection model by comparing and analyzing 12 genome selection models. Then We will use the genome selection model of the learning group in the breeding group to verify the prediction accuracy and discover a prediction model.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.11
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• pp.1529-1534
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• 2005

Individual-breed assignments were implemented in six swine populations using twenty six microsatellites recommended by the Food and Agriculture Organization and the International Society for Animal Genetics (FAO-ISAG). Most microsatellites exhibited high polymorphisms as shown by the number of alleles and the polymorphism information content. The assignment accuracy per locus obtained by using the Bayesian method ranged from 33.33% (CGA) to 68.47% (S0068), and the accumulated assignment accuracy of the top ten loci combination added up to 96.40%. The assignment power of microsatellites based on the Bayesian method had positive correlations with the number of alleles and the gene differential coefficient ($G_{st}$) per locus, while it has no relationship to genetic heterozygosity, polymorphism information content per locus and the exclusion probabilities under case II and case III. The percentage of corrected assignment was highest for the Bayesian method, followed by the gene frequency and distancebased methods. The assignment efficiency of microsatellites rose with increase in the number of loci used, and it can reach 98% when using a ten-locus combination. This indicated that such a set of ten microsatellites is sufficient for breed verification purposes.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.4
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• pp.478-483
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• 2008

Records of a Northeastern Thai indigenous cattle line population were used to estimate genetic parameters and annual trends for calf weights. The data set comprised records of 1,922 and 1,489 animals for birth and weaning weight, respectively born from 1993 to 2004. A bivariate analysis was carried out for variance and covariance components estimations using average information restricted maximum likelihood procedure. Average estimated breeding value and maternal breeding value of the animals born in 1993 were set to zero as a base group. Genetic trends of each trait were calculated by regressing average estimated breeding values and maternal breeding values on birth year of calves. Phenotypic trends for each trait were calculated by regressing the yearly adjusted weight on birth year of calves. The results revealed that the estimate of direct heritability, maternal heritability and maternal permanent environmental variance as a proportion of phenotypic variance for birth and weaning weight was 0.40, 0.14 and 0.04; 0.27, 0.05 and 0.23, respectively. Direct heritability was moderately heritable and genetic improvement through selection can be achieved. The estimate of phenotypic, direct genetic, maternal genetic and maternal permanent environmental correlation between birth and weaning weight was 0.48, 0.65, 0.98 and 0.73, respectively. The phenotypic trend, genetic trends of estimated breeding value and maternal breeding value for birth weight was 0.18, 0.04 and 0.01 kg/year, respectively. The phenotypic trend, genetic trends of estimated breeding value and maternal breeding value for weaning weight was -1.36, 0.32 and 0.03 kg/year, respectively. As maternal genetic effect was considerably less important than direct genetic effect, selection for improved weaning weight of this Northeastern Thai indigenous cattle line can place more emphasis on the direct genetic effect.