• Asian-Australasian Journal of Animal Sciences
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• v.27 no.6
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• pp.778-783
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• 2014

The polymorphism of microphthalmia-associated transcription factor (MITF) and tyrosinase (TYR) genes have been proposed to play a vital role in coat colour genesis in mammals, but their role remains ambiguous in geese at best. Here, we cloned and sequenced 1,397 bp coding region of MITF gene and a 588 bp fragment of TYR exon 1 for polymorphism analysis among 157 domestic geese showing three types of plumage colour. We detected a total of three SNPs (c.280T>C, c.345G>A, and c.369G>A) in TYR and six haplotypes (H1-H6). Among them, haplotypes H1, H2, H3, and H5 were significantly associated with white plumage trait of Zhedong White Geese. However, only diplotype H1H1 and H3H5 were significantly associated with white plumage trait of Zhedong White Geese (p<0.01). We only detected one SNP (c.1109C>T) for MITF gene and found that genotype CT and TT were significantly associated with white plumage trait of Zhedong White Geese. Briefly, our study suggested an association between polymorphisms of TYR and MITF genes and the plumage colour trait in domestic geese.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1400-1410
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• 2020

Objective: Genome-wide association study and two meta-analysis based on GWAS performed to explore the genetic mechanism underlying variation in pig number born alive (NBA) and total number born (TNB). Methods: Single trait GWAS and two meta-analysis (single-trait meta analysis and multi-trait meta analysis) were used in our study for NBA and TNB on 3,121 Yorkshires from 4 populations, including three different American Yorkshire populations (n = 2,247) and one British Yorkshire populations (n = 874). Results: The result of single trait GWAS showed that no significant associated single nucleotide polymorphisms (SNPs) were identified. Using single-trait meta analysis and multi-trait meta analysis within populations, 11 significant loci were identified associated with target traits. Spindlin 1, vascular endothelial growth factor A, forkhead box Q1, msh homeobox 1, and LHFPL tetraspan submily member 3 are five functionally plausible candidate genes for NBA and TNB. Compared to the single population GWAS, single-trait Meta analysis can improve the detection power to identify SNPs by integrating information of multiple populations. The multiple-trait analysis reduced the power to detect trait-specific loci but enhanced the power to identify the common loci across traits. Conclusion: In total, our findings identified novel genes to be validated as candidates for NBA and TNB in pigs. Also, it enabled us to enlarge population size by including multiple populations with different genetic backgrounds and increase the power of GWAS by using meta analysis.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.3
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• pp.320-324
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• 2003

The objective of this study was to localize QTL affecting meat quality in a pig family of three generations. All animals were genotyped for twenty-four microsatellites on SSC3 (Sus scrofa chromosome 3), SSC4 and SSC7. One hundred and forty $F_2$ offsprings were scored for eleven meat quality traits. Least square regression interval mapping revealed quantitative trait loci (QTL) effect for meat pH (m. Semipinalis Capitis, SC) on SSC4 and SSC7; for moisture (m. Longissimus Dorsi, LD) on SSC3. Furthermore, there was suggestive evidence for a QTL on SSC4 affecting intramuscular fat (IMF) content that nearly approached the chromosomewise (p=0.05) significance threshold.

• Animal Bioscience
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• v.34 no.2
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• pp.185-191
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• 2021

Objective: The objective of this study was to estimate the genetic parameters for worm resistance (WR) and associated characteristics, using the linear-threshold animal model via Bayesian inference in single- and multiple-trait analyses. Methods: Data were collected from a herd of Santa Inês breed sheep. All information was collected with animals submitted to natural contamination conditions. All data (number of eggs per gram of feces [FEC], Famacha score [FS], body condition score [BCS], and hematocrit [HCT]) were collected on the same day. The animals were weighed individually on the day after collection (after 12-h fasting). The WR trait was defined by the multivariate cluster analysis, using the FEC, HCT, BCS, and FS of material collected from naturally infected sheep of the Santa Inês breed. The variance components and genetic parameters for the WR, FEC, HCT, BCS, and FS traits were estimated using the Bayesian inference under the linear and threshold animal model. Results: A low magnitude was obtained for repeatability of worm-related traits. The mean values estimated for heritability were of low-to-high (0.05 to 0.88) magnitude. The FEC, HCT, BCS, FS, and body weight traits showed higher heritability (although low magnitude) in the multiple-trait model due to increased information about traits. All WR characters showed a significant genetic correlation, and heritability estimates ranged from low (0.44; single-trait model) to high (0.88; multiple-trait model). Conclusion: Therefore, we suggest that FS be included as a criterion of ovine genetic selection for endoparasite resistance using the trait defined by multivariate cluster analysis, as it will provide greater genetic gains when compared to any single trait. In addition, its measurement is easy and inexpensive, exhibiting greater heritability and repeatability and a high genetic correlation with the trait of resistance to worms.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.3
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• pp.341-349
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• 2019

Objective: Internal organs indirectly affect economic performance and well-being of animals. Study of internal organs during later layer period will allow full utilization of layer hens. Hence, we conducted a genome-wide association study (GWAS) to identify potential quantitative trait loci or genes that potentially contribute to internal organ weight. Methods: A total of 1,512 chickens originating from White Leghorn and Dongxiang Blue-Shelled chickens were genotyped using high-density Affymetrix 600 K single nucleotide polymorphism (SNP) array. We conducted a GWAS, linkage disequilibrium analysis, and heritability estimated based on SNP information by using GEMMA, Haploview and GCTA software. Results: Our results displayed that internal organ weights show moderate to high (0.283 to 0.640) heritability. Variance partitioned across chromosomes and chromosome lengths had a linear relationship for liver weight and gizzard weight ($R^2=0.493$, 0.753). A total of 23 highly significant SNPs that associated with all internal organ weights were mainly located on Gallus gallus autosome (GGA) 1 and GGA4. Six SNPs on GGA2 affected heart weight. After the final analysis, five top SNPs were in or near genes 5-Hydroxytryptamine receptor 2A, general transcription factor IIF polypeptide 2, WD repeat and FYVE domain containing 2, non-SMC condensin I complex subunit G, and sonic hedgehog, which were considered as candidate genes having a pervasive role in internal organ weights. Conclusion: Our findings provide an understanding of the underlying genetic architecture of internal organs and are beneficial in the selection of chickens.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.12
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• pp.1669-1674
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• 2005

Maximum likelihood methodology was applied to analyze the efficiency and statistical power of interval mapping by using a threshold model. The factors that affect QTL detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the size of segregating population is 500. The results showed that the threshold model has a great advantage in parameters estimation and power of QTL mapping, and has nice efficiency and accuracy for discrete traits. In addition, the accuracy and power of QTL mapping depended on the effect of putative quantitative trait loci, the value of heritability and incidence directly. With the increase of QTL effect, heritability and incidence of categories, the accuracy and power of QTL mapping improved correspondingly.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.1
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• pp.70-73
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• 1999

This study was conducted to ascertain the chromosomal locations and effect of quantitative trait loci (QTL) associated with the physical traits of rice (Oryza sativa L.) eating quality. One hundred sixty four recombinant inbred lines (MGRILs) of F$_{11}$ were derived from the cross between Milyang 23 (Tongil type) and Gihobyeo (japonica type). They were evaluated for six physical traits of cooked rice. Transgressive segregation was observed for all examined traits. Significant QTL were detected (LOD$\geq$2.0) in three traits, including single QTL for adhesiveness, gumminess, and chewiness of cooked rice, respectively. Phenotypic variation explained by each QTL ranged from 6.3% to 14.6%. However, no significant QTL was detected for hardness, cohesiveness, and elasticity of cooked rice. Pleiotropic effects of single QTL on different traits are observed.d.

• Korean Journal of Breeding Science
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• v.40 no.1
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• pp.39-47
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• 2008

The 1,874 rice lines were selected from 3,000 Ds insertional mutant pool by Basta herbicide treatment and were surveyed for trait variation and molecular characteristics of genes knocked out by Ds insertion. Compared with "Donjin", an original japonica cultivar used for transformation, Ds insertion mutant pool showed large variation in major agronomic traits including tiller, panicle, and heading etc. Southern blot analysis demonstrated that these lines on the average had two Ds copies in Donjin genome, resulting in 38.4% of one copy, 32.5% of two copies, 16.7% of three copies, and 11.3% of over four copies. GUS analysis showed that 3.9% of lines (73/1,860) had tissue-specific expression in leaves, nodal parts, floral organs such as stigma and pollen, and roots. Data set obtained from agricultural trait variation and molecular characteristics for individual Ds insertional lines would provide researchers with more information for understanding the function of unknown rice genes controlling economically important traits.

• Animal Bioscience
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• v.35 no.11
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• pp.1649-1655
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• 2022

Objective: The primary objective of this study was to determine the genetic parameters for reproductive traits among Large White pigs, including the following traits: total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), gestation length (GL), age at first service (AFS) and age at first farrowing (AFF). Methods: The dataset consisted of 19,036 reproductive records from 4,986 sows, and a multi-trait animal model was used to estimate genetic variance components of seven reproductive traits. Results: The heritability estimates for these reproductive traits ranged from 0.09 to 0.26, with the highest heritability for GL and AFF, and the lowest heritability for NBA. The repeatabilities for TNB, NBA, LWB, ABW, and GL were ranged from 0.16 to 0.34. Genetic and phenotypic correlations ranged from -0.41 to 0.99, and -0.34 to 0.98, respectively. In particular, the correlations between TNB, NBA and LBW, between AFS and AFF, exhibited a strong positive correlation. Furthermore, for TNB, NBA, LBW, ABW, and GL, genetic correlations of the same trait between different parities were moderately to strongly correlated (0.32 to 0.97), and the correlations of adjacent parities were higher than those of nonadjacent parities. Conclusion: All the results in the present study can be used as a basis for the genetic assessment of the target population. In the formulation of dam line selection index, AFS or AFF can be considered to combine with TNB in a multiple trait swine breeding value estimation system. Moreover, breeders are encouraged to increase the proportion of sows at parity 3-5 and reinforce the management of sows at parity 1 and parity ≥8.

• Journal of Crop Science and Biotechnology
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• v.11 no.1
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• pp.7-12
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• 2008

Quantitative trait loci, a genetic concept for explaining the inheritance of non-Mendelian traits in 1940s, have been realized as particular fragments of chromosome even unique genes in most crops in 21st century. However, only very a small portion of QTL has been screened out by geneticists comparing to a great number of genes underneath the quantitative traits. These identified QTL even have been seldom used into breeding program because crop breeders may not find the QTL in their breeding populations in their field station. Several key points will be proposed to meet the challenges of QTL analysis today: a fine mapping population and the related reference genetic map, QTL evaluation in multiple environments, recognizing real QTL with small genetic effect, map integration.