Seeding Multi-omic Improvement of Apple

Seeding Multi-omic Improvement of Apple

Bibliographic Details
Main Author: Bilbrey, Emma A.
Language:English
Published: The Ohio State University / OhioLINK 2020
Subjects:
Horticulture
Genetics
Biochemistry
Untargeted Metabolomics
Genomics
Apple
GWAS
QTL
Tree Crop
LC-MS
NMR
Pedigree-based analysis
Chlorogenic acid
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=osu1594907111820227
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-osu15949071118202272021-08-03T07:15:42Z Seeding Multi-omic Improvement of Apple Bilbrey, Emma A. Horticulture Genetics Biochemistry Untargeted Metabolomics Genomics Apple GWAS QTL Tree Crop LC-MS NMR Pedigree-based analysis Chlorogenic acid Apples are one of the most commonly consumed fruits in America, and “an apple a day keeps the doctor away” is a well-known adage. The commercial and nutritional importance of apples has prompted interest in varietal improvement. However, progress is limited by a long juvenile period, which delays fruit evaluation for quality traits, such as phytochemical composition. To minimize this drawback, apple breeders have begun using marker-assisted selection (MAS) for some traits, but breeding strategies for fruit phytochemicals have yet to be developed.In response, we have developed an integrated genomic-metabolomic platform to better understand gene-phytochemical associations in breeding-relevant apple germplasm. Phytochemicals that are potentially health beneficial, contribute disease resistance, or improve fruit quality can be characterized using metabolomics, providing a foundation to study apple’s breeding potential. The platform is based on high-throughput genomic and metabolomic assessment of 173 unique apples, including members of three pedigree-connected families alongside diverse and wild selections. Single nucleotide polymorphism (SNP) data was obtained from the 20K SNP array for apple and integrated with metabolomic datasets from high-resolution mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy analyses of polar/semi-polar apple fruit extracts. Metabolite genome-wide association studies (mGWAS) were conducted with 11,165 SNPs for two LC-MS data sets of 4,000+ features each and an NMR data set of 756 bins. Novel schemes for prioritizing results from mGWAS indicated 519 (LC-MS (+)), 726 (LC-MS (-)), and 177 (NMR) significant marker-trait associations across the apple genome (LC-MS: p < .00001, NMR: p < .0001). These results were then sifted to select features to analyze with a more powerful pedigree-based analysis (PBA) in FlexQTL™ with 6,034 SNPs to identify metabolite quantitative trait loci (mQTL), genomic areas exerting genetic control over phytochemical production. An mQTL for chlorogenic acid was identified on the bottom of chromosome 17 across all three metabolomic data sets and was used as a proof-of-concept example to demonstrate the applicability of the platform. Determining gene-phytochemical relationships in apple will inform breeding and facilitate future MAS for improved nutrition along with attributes related to flavor and disease resistance etiology. 2020 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1594907111820227 http://rave.ohiolink.edu/etdc/view?acc_num=osu1594907111820227 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Horticulture
Genetics
Biochemistry
Untargeted Metabolomics
Genomics
Apple
GWAS
QTL
Tree Crop
LC-MS
NMR
Pedigree-based analysis
Chlorogenic acid
spellingShingle Horticulture
Genetics
Biochemistry
Untargeted Metabolomics
Genomics
Apple
GWAS
QTL
Tree Crop
LC-MS
NMR
Pedigree-based analysis
Chlorogenic acid
Bilbrey, Emma A.
Seeding Multi-omic Improvement of Apple
author Bilbrey, Emma A.
author_facet Bilbrey, Emma A.
author_sort Bilbrey, Emma A.
title Seeding Multi-omic Improvement of Apple
title_short Seeding Multi-omic Improvement of Apple
title_full Seeding Multi-omic Improvement of Apple
title_fullStr Seeding Multi-omic Improvement of Apple
title_full_unstemmed Seeding Multi-omic Improvement of Apple
title_sort seeding multi-omic improvement of apple
publisher The Ohio State University / OhioLINK
publishDate 2020
url http://rave.ohiolink.edu/etdc/view?acc_num=osu1594907111820227
work_keys_str_mv AT bilbreyemmaa seedingmultiomicimprovementofapple
_version_ 1719457584223617024

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