• Title/Summary/Keyword: Quantitative Trait Locus

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Power of Variance Component Linkage Analysis to Identify Quantitative Trait Locus in Chickens

  • Park, Hee-Bok;Heo, Kang-Nyeong;Kang, Bo-Seok;Jo, Cheorun;Lee, Jun Heon
    • Journal of Animal Science and Technology
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    • v.55 no.2
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    • pp.103-107
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    • 2013
  • A crucial first step in the planning of any scientific experiment is to evaluate an appropriate sample size to permit sufficient statistical power to detect the desired effect. In this study, we investigated the optimal sample size of quantitative trait locus (QTL) linkage analysis for simple random sibship samples in pedigreed chicken populations, under the variance component framework implemented in the genetic power calculator program. Using the program, we could compute the statistical power required to achieve given sample sizes in variance component linkage analysis in random sibship data. For simplicity, an additive model was taken into account. Power calculations were performed to relate sample size to heritability attributable to a QTL. Under the various assumptions, comparative power curves indicated that the power to detect QTL with the variance component method is highly affected by a function of the effect size of QTL. Hence, more power can be achievable for QTL with a larger effect. In addition, a marked improvement in power could be obtained by increasing the sibship size. Thus, the use of chickens is advantageous regarding the sampling unit issue, since desirable sibship size can be easily obtained compared with other domestic species.

Variance Component Quantitative Trait Locus Analysis for Body Weight Traits in Purebred Korean Native Chicken

  • Cahyadi, Muhammad;Park, Hee-Bok;Seo, Dong-Won;Jin, Shil;Choi, Nuri;Heo, Kang-Nyeong;Kang, Bo-Seok;Jo, Cheorun;Lee, Jun-Heon
    • Asian-Australasian Journal of Animal Sciences
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    • v.29 no.1
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    • pp.43-50
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    • 2016
  • Quantitative trait locus (QTL) is a particular region of the genome containing one or more genes associated with economically important quantitative traits. This study was conducted to identify QTL regions for body weight and growth traits in purebred Korean native chicken (KNC). F1 samples (n = 595) were genotyped using 127 microsatellite markers and 8 single nucleotide polymorphisms that covered 2,616.1 centi Morgan (cM) of map length for 26 autosomal linkage groups. Body weight traits were measured every 2 weeks from hatch to 20 weeks of age. Weight of half carcass was also collected together with growth rate. A multipoint variance component linkage approach was used to identify QTLs for the body weight traits. Two significant QTLs for growth were identified on chicken chromosome 3 (GGA3) for growth 16 to18 weeks (logarithm of the odds [LOD] = 3.24, Nominal p value = 0.0001) and GGA4 for growth 6 to 8 weeks (LOD = 2.88, Nominal p value = 0.0003). Additionally, one significant QTL and three suggestive QTLs were detected for body weight traits in KNC; significant QTL for body weight at 4 weeks (LOD = 2.52, nominal p value = 0.0007) and suggestive QTL for 8 weeks (LOD = 1.96, Nominal p value = 0.0027) were detected on GGA4; QTLs were also detected for two different body weight traits: body weight at 16 weeks on GGA3 and body weight at 18 weeks on GGA19. Additionally, two suggestive QTLs for carcass weight were detected at 0 and 70 cM on GGA19. In conclusion, the current study identified several significant and suggestive QTLs that affect growth related traits in a unique resource pedigree in purebred KNC. This information will contribute to improving the body weight traits in native chicken breeds, especially for the Asian native chicken breeds.

What Holds the Future of Quantitative Genetics? - A Review

  • Lee, Chaeyoung
    • Asian-Australasian Journal of Animal Sciences
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    • v.15 no.2
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    • pp.303-308
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    • 2002
  • Genetic markers engendered by genome projects drew enormous interest in quantitative genetics, but knowledge on genetic architecture of complex traits is limited. Complexities in genetics will not allow us to easily clarify relationship between genotypes and phenotypes for quantitative traits. Quantitative genetics guides an important way in facing such challenges. It is our exciting task to find genes that affect complex traits. In this paper, landmark research and future prospects are discussed on genetic parameter estimation and quantitative trait locus (QTL) mapping as major subjects of interest.

Identification of quantitative trait loci for the fatty acid composition in Korean native chicken

  • Jin, Shil;Park, Hee Bok;Seo, Dongwon;Choi, Nu Ri;Manjula, Prabuddha;Cahyadi, Muhammad;Jung, Samooel;Jo, Cheorun;Lee, Jun Heon
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.8
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    • pp.1134-1140
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    • 2018
  • Objective: Fatty acid composition is one of the most important meat quality traits because it can contribute to functional, sensorial, and nutritional factors. In this study, quantitative trait locus (QTL) analyses for fatty acid composition traits were investigated in thigh and breast meat of Korean native chicken (KNC). Methods: In total, 18 fatty acid composition traits were investigated from each meat sample using 83 parents, and 595 $F_1$ chicks of 20 week old. Genotype assessment was performed using 171 informative DNA markers on 26 autosomes. The KNC linkage map was constructed by CRI-MAP software, which calculated genetic distances, with map orders between markers. The half-sib and full-sib QTL analyses were performed using GridQTL and SOLAR programs, respectively. Results: In total, 30 QTLs (12 in the thigh and 18 in the breast meat) were detected by the half-sib analysis and 7 QTLs (3 in the thigh and 4 in the breast meat) were identified by the full-sib analysis. Conclusion: With further verification of the QTL regions using additional markers and positional candidate gene studies, these results can provide valuable information for determining causative mutations affecting the fatty acid composition of KNC meat. Moreover, these findings may aid in the selection of birds with favorable fatty acid composition traits.

Current Research Status for Economically Important Candidate Genes and Microarray Studies in Cattle (소의 경제형질 관련 후보 유전자 및 Microarray 연구현황)

  • 유성란;이준헌
    • Journal of Animal Science and Technology
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    • v.48 no.2
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    • pp.169-190
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    • 2006
  • Researches in livestock are currently actively progressing to improve economically important traits using DNA markers. In cattle, the candidate genes have been selected based on their known functions in the target QTL (quantitative trait locus) region in order to identify QTN (quantitative trait nucleotide) for improving productivities. In this review, molecular genetic studies for the meat related traits, one of the major determinant of market prices, have been fully described. Also recent emerging microarray technique for identifying candidate genes in cattle has been discussed. In case of microarray, cDNA microarrays have been replaced to oligoarrays in order to minimize the experimental errors in cattle. Since the first draft of bovine genome sequences was appeared in the public domain, more markers in relation to the quantitative traits will be discovered in a short period of time and genes affecting difficult-to-measure traits, such as disease resistance, can also be selected for marker assisted selection in near future.

Quantitative Trait Loci Affecting Rous Sarcoma Virus Induced Tumor Regression Trait in F2 Intercross Chickens

  • Uemoto, Y.;Saburi, J.;Sato, S.;Odawara, S.;Ohtake, T.;Yamamoto, R.;Miyata, T.;Suzuki, K.;Yamashita, H.;Irina, C.;Plastow, G.;Mitsuhashi, T.;Kobayashi, E.
    • Asian-Australasian Journal of Animal Sciences
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    • v.22 no.10
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    • pp.1359-1365
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    • 2009
  • We performed a genome-wide linkage and quantitative trait locus (QTL) analysis to confirm the existence of QTL affecting Rous Sarcoma Virus (RSV) induced tumor regression, and to estimate their effects on phenotypic variance in an F2 resource population. The F2 population comprised 158 chickens obtained by crossing tumor regressive White Leghorn (WL) and tumor progressive Rhode Island Red (RIR) lines was measured for tumor formation after RSV inoculation. Forty-three tumor progressive and 28 tumor regressive chickens were then used for genome-wide linkage and QTL analysis using a total of 186 microsatellite markers. Microsatellite markers were mapped on 20 autosomal chromosomes. A significant QTL was detected with marker LEI0258 located within the MHC B region on chromosome 16. This QTL had the highest F ratio (9.8) and accounted for 20.1% of the phenotypic variation. Suggestive QTL were also detected on chromosomes 4, 7 and 10. The QTL on chromosome 4 were detected at the 1% chromosome-wide level explaining 17.5% of the phenotypic variation, and the QTLs on chromosome 7 and 10 were detected at the 5% chromosome-wide level and explained 11.1% and 10.5% of the phenotypic variation, respectively. These results indicate that the QTLs in the non-MHC regions play a significant role in RSV-induced tumor regression. The present study constitutes one of the first preliminary reports in domestic chickens for QTLs affecting RSV-induced tumor regression outside the MHC region.

Quantitative Trait Loci and Candidate Genes Affecting Fatty Acid Composition in Cattle and Pig

  • Maharani, Dyah;Jo, Cheo-Run;Jeon, Jin-Tae;Lee, Jun-Heon
    • Food Science of Animal Resources
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    • v.31 no.3
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    • pp.325-338
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    • 2011
  • Investigations into fatty acid composition in meats are becoming more important due to consumer demand for high quality healthy food. Marker-assisted selection has been applied to livestock to improve meat quality by directly selecting animals for favorable alleles that affect economic traits. Quantitative trait loci affecting fatty acid composition in cattle and pigs were investigated, and five candidate genes (ACACA, FASN, SCD, FABPs, and SREBP-1) were significantly associated with fatty acid composition. The information presented here should provide valuable guidelines to detect causative mutations affecting fatty acid composition in cattle and pigs.

Investigation of Splicing Quantitative Trait Loci in Arabidopsis thaliana

  • Yoo, Wonseok;Kyung, Sungkyu;Han, Seonggyun;Kim, Sangsoo
    • Genomics & Informatics
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    • v.14 no.4
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    • pp.211-215
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    • 2016
  • The alteration of alternative splicing patterns has an effect on the quantification of functional proteins, leading to phenotype variation. The splicing quantitative trait locus (sQTL) is one of the main genetic elements affecting splicing patterns. Here, we report the results of genome-wide sQTLs across 141 strains of Arabidopsis thaliana with publicly available next generation sequencing datasets. As a result, we found 1,694 candidate sQTLs in Arabidopsis thaliana at a false discovery rate of 0.01. Furthermore, among the candidate sQTLs, we found 25 sQTLs that overlapped with the list of previously examined trait-associated single nucleotide polymorphisms (SNPs). In summary, this sQTL analysis provides new insight into genetic elements affecting alternative splicing patterns in Arabidopsis thaliana and the mechanism of previously reported trait-associated SNPs.

Current Status of Quantitative Trait Locus Mapping in Livestock Species - Review -

  • Kim, Jong-Joo;Park, Young I.
    • Asian-Australasian Journal of Animal Sciences
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    • v.14 no.4
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    • pp.587-596
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    • 2001
  • In the last decade, rapid developments in molecular biotechnology and of genomic tools have enabled the creation of dense linkage maps across whole genomes of human, plant and animals. Successful development and implementation of interval mapping methodologies have allowed detection of the quantitative trait loci (QTL) responsible for economically important traits in experimental and commercial livestock populations. The candidate gene approach can be used in any general population with the availability of a large resource of candidate genes from the human or rodent genomes using comparative maps, and the validated candidate genes can be directly applied to commercial breeds. For the QTL detected from primary genome scans, two incipient fine mapping approaches are applied by generating new recombinants over several generations or utilizing historical recombinants with identity-by-descent (IBD) and linkage disequilibrium (LD) mapping. The high resolution definition of QTL position from fine mapping will allow the more efficient implementation of breeding programs such as marker-assisted selection (MAS) or marker-assisted introgression (MAI), and will provide a route toward cloning the QTL.

Quantitative Trait Locus and Association Studies affecting Meat Colors in Chicken : Review (닭의 육질 개량을 위한 육색 관련 양적형질좌위 및 연관마커에 관한 고찰: 총설)

  • Seo, Dongwon;Lee, Jun Heon
    • Korean Journal of Poultry Science
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    • v.42 no.4
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    • pp.315-325
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    • 2015
  • Recently, livestock breeding is more focused on the meat quality rather than meat quantity, mainly due to the improvement of consumers' income. Among the meat quality traits, meat color is one of very important traits because meat color is the first selection criterion from the consumers in the market. Most of the economically important traits have continuous variations and these are called quantitative traits. the genomic locations affecting these traits are called quantitative trait locus (QTL), which is mostly controlled by many genes having small effects. In this study, the recent QTL and candidate gene studies were reviewed in order to meet the consumers' demand for the future market. In the chicken QTL database, three traits are related with meat colors, namely breast color (Bco), meat color (Mco), drip loss (DL) and pH. The identified number of QTLs is 33 from 13 chromosomal regions. In these QTL regions, 14 candidate genes were identified; Eight for meat color (APP, BCMO1, COL1A2, FTO, KPNA2, PSMD12, G0S2, FTSJ3), two for drip loss (AGRP, FTO) and four for pH (GALNT1, PCDH19, DIAPH1, SPP2). These QTLs and candidate genes need to be confirmed and fine mapping is ultimately needed for identification of causative variations. The recently developed chicken resource population using Korean native chicken can be used for the improvement of meat quality traits, which increase the value that needed in the chicken industry.