• Title/Summary/Keyword: Quantitative Trait Locus

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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.

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.

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.

Bootstrapping of Hanwoo Chromosome17 Based on BMS1167 Microsatellite Locus

  • Lee, Jea-Young;Lee, Yong-Won;Yeo, Jung-Sou
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.175-184
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    • 2007
  • LOD scores and a permutation test for detecting and locating quantitative trait loci (QTL) from the Hanwoo economic trait have been described and we selected a considerable major BMS1167 locus for further analysis. K-means clustering analysis, for the major DNA marker mining of BMS1167 microsatellite loci in Hanwoo chromosome17, has been tried and three cluster groups divide four traits. The three cluster groups are classified according to eight DNA marker bps. Finally, we employed the bootstrap test method to calculate confidence intervals using the resampling method to find major DNA markers. We conclude that the major marker of BMS1167 locus in Hanwoo chromosome17 is only DNA marker 100bp.

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Bootstrapping and DNA marker Mining of BMS941 microsatellite locus in Hanwoo chromosome 17

  • Lee, Jea-Young;Bae, Jung-Hwan;Yeo, Jung-Sou
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1103-1113
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    • 2007
  • LOD scores and a permutation test for detecting and locating Quantitative trait loci(QTL) from the Hanwoo economic trait have been described and we selected a considerable major BMS941 locus. K -means clustering analysis of eight markers in BMS941 and four traits resulted in three cluster groups. Finally, we applied the bootstrap test method to calculate confidence intervals for finding major DNA markers. We conclude that the major markers of BMS941 locus in Hanwoo chromosome 17 are markers 85bp and 105bp.

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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.

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.

Selective Allele Stacking of a Novel Quantitative Trait Locus Facilitates the Enhancement of Seed Epicatechin Contents in Soybean (Glycine max (L.) Merr.)

  • Sewon Park;Hakyung Kwon;Jae Ah Choi;Moon Young Kim;Suk-Ha Lee
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.27-27
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    • 2022
  • (-)-Epicatechin (EC), a primary form of flavan-3ol and a building block of proanthocyanidins, has health benefits as it is a potent antioxidant. So far, no quantitative trait loci (QTLs) associated with EC have yet been identified in soybean. In this study, QTLs for EC and hilum color were identified in recombinant inbred lines (RILs) derived from the varieties Jinpung and IT109098 using high-resolution single nucleotide polymorphism linkage mapping. This revealed two major QTLs for EC content, qEC06 and qEC08. qEC06 spanned the T Locus encoding flavonoid 3'-hydroxylase. qEC08, located near the I locus on Chr08, was also a major QTL for hilum color; however, allelic stacking of qEC08 and I revealed no relationship between I and EC content. RILs with IT 109098 alleles at both qEC06 and qEC08 had higher EC content than other lines. These results will enable the production of soybean varieties with high EC content via marker-assisted selection.

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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.

Molecular Identification and Fine Mapping of a Major Quantitative Trait Locus, OsGPq3 for Seed Low-Temperature Germinability in Rice

  • Nari Kim;Rahmatullah Jan;Jae-Ryoung Park;Saleem Asif;Kyung-Min Kim
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.283-283
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    • 2022
  • Abiotic stresses such as high/low temperature, drought, salinity, and submergence directly or indirectly influence the physiological status and molecular mechanisms of rice which badly affect yield. Especially, the low temperature causes harmful influences in the overall process of rice growth such as uneven germination and the establishment of seedlings, which has become one of the main limiting factors affecting rice production in the world. It is of great significance to find the candidate genes controlling low-temperature tolerance during seed germination and study their functions for breeding new rice cultivars with immense low-temperature tolerance during seed germination. In this study, 120 lines of Cheongcheong/Nagdong double haploid population were used for quantitative trait locus analysis of low-temperature germinability. The results showed significant difference in germination under low different temperature conditions. In total, 4 QTLs were detected on chromosome 3, 6, and 8. A total of 41 genes were identified from all the 4 QTLs, among them, 25 genes were selected by gene function annotation and further screened through quantitative real time polymerase chain reaction. Based on gene function annotation and level of expression under low-temperature, our study suggested OsGPq3 gene as a candidate gene controlling viviparous germination, ABA and GA signaling under low-temperature. This study will provide a theoretical basis for marker-assisted breeding.

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