Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation

Grain and flour quality traits affect marketing potential and milling and baking properties. Trait means varied in fourteen wheat grain and flour quality traits for a population of 188 diverse soft winter wheat varieties harvested from 2020 to 2023 at the same location. Significant weather differenc...

Full description

Saved in:
Bibliographic Details
Main Author: Bryan W. Penning
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Agriculture
Subjects:
Online Access:https://www.mdpi.com/2077-0472/14/12/2317
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846106413614497792
author Bryan W. Penning
author_facet Bryan W. Penning
author_sort Bryan W. Penning
collection DOAJ
description Grain and flour quality traits affect marketing potential and milling and baking properties. Trait means varied in fourteen wheat grain and flour quality traits for a population of 188 diverse soft winter wheat varieties harvested from 2020 to 2023 at the same location. Significant weather differences occurred yearly. This created a challenge for the detection of chromosome locations affecting these traits through genome-wide association studies (GWAS). Mean normalization using standard deviation to transform raw data to Z scores has been used successfully in other statistical analyses of biological systems with mean differences. Mean normalization was applied to a GWAS, improving detection power for thirteen grain and flour quality traits with high broad-sense heritability. It did not improve the lone trait with low heritability. Improvement was measured as the reduction in the <i>p</i>-value of mean normalized data compared with raw data for the same significant marker using the same GWAS model in the same trait. Improvement varied by trait and marker, but the average <i>p</i>-value of 135 common significant marker/GWAS model combinations was reduced 27 times with mean normalization over raw averaged data. Mean normalization reduced <i>p</i>-values ~1800 times when compared with a GWAS using best linear unbiased predictors. However, the best linear unbiased predictors led to only 15 common marker/GWAS model combinations with mean normalization, limiting the ability for direct marker comparison. Test weight, kernel protein, kernel weight, sodium carbonate solvent retention capacity, and sucrose solvent retention capacity showed the greatest increased detection power.
format Article
id doaj-art-60e3cbdafed5498aaf8cfc094c6adba2
institution Kabale University
issn 2077-0472
language English
publishDate 2024-12-01
publisher MDPI AG
record_format Article
series Agriculture
spelling doaj-art-60e3cbdafed5498aaf8cfc094c6adba22024-12-27T14:03:21ZengMDPI AGAgriculture2077-04722024-12-011412231710.3390/agriculture14122317Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year VariationBryan W. Penning0United States Department of Agriculture, Agricultural Research Services, Wooster, OH 44691, USAGrain and flour quality traits affect marketing potential and milling and baking properties. Trait means varied in fourteen wheat grain and flour quality traits for a population of 188 diverse soft winter wheat varieties harvested from 2020 to 2023 at the same location. Significant weather differences occurred yearly. This created a challenge for the detection of chromosome locations affecting these traits through genome-wide association studies (GWAS). Mean normalization using standard deviation to transform raw data to Z scores has been used successfully in other statistical analyses of biological systems with mean differences. Mean normalization was applied to a GWAS, improving detection power for thirteen grain and flour quality traits with high broad-sense heritability. It did not improve the lone trait with low heritability. Improvement was measured as the reduction in the <i>p</i>-value of mean normalized data compared with raw data for the same significant marker using the same GWAS model in the same trait. Improvement varied by trait and marker, but the average <i>p</i>-value of 135 common significant marker/GWAS model combinations was reduced 27 times with mean normalization over raw averaged data. Mean normalization reduced <i>p</i>-values ~1800 times when compared with a GWAS using best linear unbiased predictors. However, the best linear unbiased predictors led to only 15 common marker/GWAS model combinations with mean normalization, limiting the ability for direct marker comparison. Test weight, kernel protein, kernel weight, sodium carbonate solvent retention capacity, and sucrose solvent retention capacity showed the greatest increased detection power.https://www.mdpi.com/2077-0472/14/12/2317wheatflour qualitygrain qualitygenome-wide association studymean normalization
spellingShingle Bryan W. Penning
Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation
Agriculture
wheat
flour quality
grain quality
genome-wide association study
mean normalization
title Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation
title_full Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation
title_fullStr Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation
title_full_unstemmed Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation
title_short Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (<i>Triticum aestivum</i>) Grain and Flour Quality Traits with Year-to-Year Variation
title_sort mean normalization improved genome wide association detection power of wheat i triticum aestivum i grain and flour quality traits with year to year variation
topic wheat
flour quality
grain quality
genome-wide association study
mean normalization
url https://www.mdpi.com/2077-0472/14/12/2317
work_keys_str_mv AT bryanwpenning meannormalizationimprovedgenomewideassociationdetectionpowerofwheatitriticumaestivumigrainandflourqualitytraitswithyeartoyearvariation