scholarly journals Quantitative Trait Loci Controlling the Number of Spikelets and Component Traits in Rice: Their Main Effects and Interaction with Years

2004 ◽  
Vol 54 (2) ◽  
pp. 125-132 ◽  
Author(s):  
Tsuneo Kato
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Trait Loci ◽  
Component Traits ◽  
Main Effects

Identification of quantitative trait loci underlying seed shape in soybean across multiple environments

2017 ◽  
Vol 156 (1) ◽  
pp. 3-12 ◽  
Author(s):  
W. L. Teng ◽  
M. N. Sui ◽  
W. Li ◽  
D. P. Wu ◽  
X. Zhao ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Average Distance ◽  
Recombinant Inbred Lines ◽  
Soybean Seeds ◽  
Seed Shape ◽  
Phenotypic Data ◽  
Trait Loci ◽  
Component Traits ◽  
Seed Width

AbstractSeed shape (SS) affects the yield and appearance of soybean seeds significantly. However, little detailed information has been reported about the quantitative trait loci (QTL) affecting SS, especially SS components such as seed length (SL), seed width (SW) and seed thickness (ST), and their mutual ratios of length-to-weight (SLW), length-to-thickness (SLT) and weight-to-thickness (SWT). The aim of the present study was to identify QTL underlying SS components using 129 recombinant inbred lines derived from a cross between Dongnong46 and L-100. Phenotypic data were collected from this population after it was grown across nine environments. A total of 213 simple sequence repeat markers were used to construct the genetic linkage map, which covered approximately 3623·39 cM, with an average distance of 17·01 cM between markers. Five QTL were identified as being associated with SL, five with SW, three with ST, four with SLW, two with SLT and three with SWT. These QTL could explain 1·46–22·16% of the phenotypic variation in SS component traits. Three QTL were identified in more than six tested environments three for SL, two for SW, one for ST, two for SLW and one for SLT. These QTL have great potential value for marker-assistant selection of SS in soybean seeds.

scholarly journals Candidate Gene Test for Quantitative Trait Loci Conferring Hypercholesterolemia on Mouse Chromosome 1

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 942-942
Author(s):  
Jung Han Kim ◽  
Jacaline Parkman ◽  
Kristiana Sklioutovskaya-Lopez
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Significant Interaction ◽  
Plasma Cholesterol ◽  
Complementation Test ◽  
Total Plasma Cholesterol ◽  
Total Plasma ◽  
Cholesterol Levels ◽  
Trait Loci ◽  
Main Effects

Abstract Objectives The TALLYHO (TH) mouse is a polygenic model for obesity, type 2 diabetes and hyperlipidemia. We previously established a subcongenic mouse with TH donor segment, ∼25 Mb, on chromosome (Chr) 1 in a C57BL/6J (B6) background that harbors quantitative trait loci (QTL) conferring hypercholesterolemia, named Tchol1 (Tallyho Associated Cholesterol 1). The subcongenic mouse developed hypercholesterolemia compared to B6 mice demonstrating that distal segment of Chr 1 from TH genome is necessary to cause the hypercholesterolemia. In this study, we tested the candidacy of the apolipoprotein A2 (Apoa2) gene for Tachol1 by the quantitative complementation test. Apoa2, known regulator of cholesterol metabolism, maps to the Tchol1 locus. Methods To carry out the quantitative complementation test, both TH-homozygous Tachol1 subcongenic and B6-homozygous (B6) mice were mated to the Apoa2 knockout heterozygous [wild-type (wt)/null] mice to produce four types of animals; TH/wt, TH/null, B6/wt, and B6/null. Both male and female mice were weaned onto standard rodent chow and maintained. Blood was collected when animals were euthanized at 16 weeks of age. Total plasma cholesterol levels were determined using colorimetric assays. A two-way ANOVA was used to evaluate Apoa2 (null vs. wt) and Tachol1 (TH vs. B6) interaction effects for dependent variables, followed by the multiple comparison post test with Tukey correction using GraphPad Prism 8. Results Total plasma cholesterol levels were: 137 ± 5 (TH/wt), 119 ± 8 (TH/null), 103 ± 8 (B6/wt), and 80 ± 4 (B6/null) for males, and 149 ± 8 (TH/wt), 130 ± 9 (TH/null), 98 ± 3 (B6/wt), and 103 ± 6 (B6/null) for females [mean ± s.e.m; mg/dl]. Two-way ANOVA revealed no significant interaction between Tchol1 and Apoa2 knockout alleles for total plasma cholesterol levels in both males and females. However, there were significant main effects of Tchol1 and Apoa2 knockout alleles on total plasma cholesterol levels in males, while significant main effects of Tchol1 on them in females. Conclusions No significant interaction effect between knockout and QTL alleles is interpreted as evidence that the knockout locus is not equal to the QTL. Our results suggest that the Apoa2 gene is not identical to the Tchol1 QTL. Funding Sources AHA 18AIREA33960437, NIH 1 R15 DK113604-01A1, the WV-INBRE grant (P20GM103434), and the COBRE ACCORD grant (1P20GM121299).

scholarly journals Overdominance and Epistasis Are Important for the Genetic Basis of Heterosis in Brassica rapa

HortScience ◽  
2007 ◽  
Vol 42 (5) ◽  
pp. 1207-1211 ◽  
Author(s):  
De-Kun Dong ◽  
Jia-Shu Cao ◽  
Kai Shi ◽  
Le-Cheng Liu
Keyword(s):  
Quantitative Trait Loci ◽  
Brassica Rapa ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Phenotypic Variance ◽  
Epistasis Analysis ◽  
Main Effect ◽  
Trait Loci ◽  
Component Traits ◽  
The Cross

To investigate the genetic basis of heterosis in Brassica rapa, an F2 population was produced from the cross of B. rapa L. subsp. chinensis (L.) Hanelt and B. rapa L. subsp. rapifera Metzg. Trait performances of the F1 hybrid showed evident mid parent heterosis, which varied from 18.55% to 101.62% for the 11 traits investigated. A total of 23 main effect quantitative trait loci (QTLs) were detected for biomass and its component traits, which could explain 4.38% to 47.80% of the phenotypic variance, respectively. Sixty-five percent of these QTLs showed obvious overdominance. Epistasis analysis detected 444 two-locus interactions for the 11 traits at the threshold of P < 0.005. Some of them remained significant when more stringent threshold were set. These results suggested that overdominance and epistasis might play an important role as the genetic basis of heterosis in B. rapa.

Quantitative Trait Loci and Epistasis for Oat Winter-Hardiness Component Traits

Crop Science ◽  
2009 ◽  
Vol 49 (6) ◽  
pp. 1989-1998 ◽  
Author(s):  
D. R. Wooten ◽  
D. P. Livingston ◽  
H. J. Lyerly ◽  
J. B. Holland ◽  
E. N. Jellen ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Winter Hardiness ◽  
Trait Loci ◽  
Component Traits
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