Repeated chip analysis for reducing the effect of genotyping errors on gene mapping for two recombinant inbred line populations in wheat (Triticum aestivum L.)

Genotypic data has been applied in multiple research fields, such as molecular biology, genetics, and breeding. However, due to various reasons, genotyping data inevitably contains a certain percentage of errors, which affects the reliability of gene localization. This study conducted quantitative t...

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Vydáno v:BMC plant biology Ročník 25; číslo 1; s. 1117 - 12
Hlavní autoři: Zhang, Hengyi, Wang, Jiankang, Cao, Shuanghe, Hao, Yuanfeng, Xia, Xianchun, Xu, Xiaowan, Li, Lingli, Zhang, Luyan
Médium: Journal Article
Jazyk:angličtina
Vydáno: London BioMed Central 22.08.2025
BioMed Central Ltd
Springer Nature B.V
BMC
Témata:
Accuracy
Agricultural research
Agriculture
Biomedical and Life Sciences
Chromosome mapping
Chromosome Mapping - methods
Error correction
Error correction & detection
Gene mapping
Genetic aspects
Genetic linkage
Genetic markers
Genetics
Genotype
Genotype & phenotype
Genotypes
Genotyping
Genotyping error
Genotyping Techniques - methods
Inbreeding
Life Sciences
Localization
Mapping
Methods
Molecular biology
Plant genetic engineering
Plant Sciences
Populations
QTL mapping
Quantitative trait loci
Quantitative Trait Loci - genetics
Repeated genotyping data
Simulation
Software packages
Tree Biology
Triticum - genetics
Wheat
China
Beijing China
Genotyping error
Error correction
Repeated genotyping data
QTL mapping
ISSN:1471-2229, 1471-2229
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Shrnutí:Genotypic data has been applied in multiple research fields, such as molecular biology, genetics, and breeding. However, due to various reasons, genotyping data inevitably contains a certain percentage of errors, which affects the reliability of gene localization. This study conducted quantitative trait locus (QTL) mapping for some yield related and disease resistant traits, using repeated genotyping data of two wheat RIL populations derived from Yangxiaomai × Zhongyou 9507 and Jingshuang 16 × Bainong 64, and non-erroneous data consisting of consistent genotypes between the two replications. Mapping results were compared with reported QTL for the corresponding traits. Then error correction methods implemented in software packages QTL IciMapping (EC), Genotype-Corrector (GC) and R/qtl were applied to these datasets, followed by QTL mapping. Simulation study was performed by randomly adding five levels of genotyping errors to investigate the effect of genotyping errors on QTL mapping and the efficiency of error correction methods. The results indicated that the impact of genotyping errors on QTL mapping was mainly reflected in the decrease in QTL detection power and accuracy of estimation for QTL positions and effects. The impact was increased with the increasing of errors. EC, GC, and R/qtl improved the mapping accuracy, but all of them cannot eliminate the negative effect of errors completely. Considering detection power, false discovery rate, estimation of QTL position and effect, correction accuracy, and running time, EC was better than the other two methods.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1471-2229
1471-2229
DOI:10.1186/s12870-025-07184-4