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  4. QTL×QTL×QTL Interaction Effects for Total Phenolic Content of Wheat Mapping Population of CSDH Lines under Drought Stress by Weighted Multiple Linear Regression
 
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QTL×QTL×QTL Interaction Effects for Total Phenolic Content of Wheat Mapping Population of CSDH Lines under Drought Stress by Weighted Multiple Linear Regression

Type
Journal article
Language
English
Date issued
2023
Author
Cyplik, Adrian
Czyczyło-Mysza, Ilona Mieczysława
Jankowicz-Cieslak, Joanna
Bocianowski, Jan 
Faculty
Wydział Rolnictwa, Ogrodnictwa i Biotechnologii
PBN discipline
agriculture and horticulture
Journal
Agriculture (Switzerland)
DOI
10.3390/agriculture13040850
Web address
https://www.mdpi.com/2077-0472/13/4/850
Volume
13
Number
4
Pages from-to
art. 850
Abstract (EN)
This paper proposes the use of weighted multiple linear regression to estimate the triple3interaction (additive×additive×additive) of quantitative trait loci (QTLs) effects. The use of unweighted regression yielded an improvement (in absolute value) in the QTL×QTL×QTL interaction effects compared to assessment based on phenotypes alone in three cases (severe drought in 2010, control in 2012 and severe drought in 2012). In contrast, weighted regression yielded an improvement (in absolute value) in the evaluation of the aaagw parameter compared to aaap in five cases, with the exception of severe drought in 2012. The results show that by using weighted regression on marker observations, the obtained estimates are closer to the ones obtained by the phenotypic method. The coefficients of determination for the weighted regression model were significantly higher than for the unweighted regression and ranged from 46.2% (control in 2010) to 95.0% (control in 2011). Considering this, it is clear that a three-way interaction had a significant effect on the expression of quantitative traits.
Keywords (EN)
  • three-way epistasis

  • weighted regression

  • doubled haploid lines

  • water deprivation stress

  • Triticum aestivum

License
cc-bycc-by CC-BY - Attribution
Open access date
April 11, 2023
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