Dataset Information

Integrating genomics and multi‐platform metabolomics enables metabolite QTL detection in breeding‐relevant apple germplasm

ABSTRACT: Apple (Malus × domestica) has commercial and nutritional value, but breeding constraints of tree crops limit varietal improvement. Marker-assisted selection minimizes these drawbacks, but breeders lack applications for targeting fruit phytochemicals. To understand genotype-phytochemical associations in apples, we have developed a high-throughput integration strategy for genomic and multi-platform metabolomics data. 124 apple genotypes, including members of three pedigree-connected breeding families alongside diverse cultivars and wild selections, were genotyped and phenotyped. Metabolite genome-wide association studies (mGWAS) were conducted with ~10,000 single nucleotide polymorphisms and phenotypic data acquired via LC-MS and ¹ H NMR untargeted metabolomics. Putative metabolite quantitative trait loci (mQTL) were then validated via pedigree-based analyses (PBA). Using our developed method, 519, 726, and 177 putative mQTL were detected in LC-MS positive and negative ionization modes and NMR, respectively. mQTL were indicated on each chromosome, with hotspots on linkage groups 16 and 17. A chlorogenic acid mQTL was discovered on chromosome 17 via mGWAS and validated with a two-step PBA, enabling discovery of novel candidate gene-metabolite relationships. Complementary data from three metabolomics approaches and dual genomics analyses increased confidence in validity of compound annotation and mQTL detection. Our platform demonstrates the utility of multi-omic integration to advance data-driven, phytochemical-based plant breeding.

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Nuclear Magnetic Resonance (NMR) -, Liquid Chromatography MS - positive - reverse phase

SUBMITTER: Jessica Cooperstone

PROVIDER: MTBLS2327 | MetaboLights | 2021-09-21

REPOSITORIES: MetaboLights

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Integrating genomics and multiplatform metabolomics enables metabolite quantitative trait loci detection in breeding-relevant apple germplasm.

Bilbrey Emma A EA Williamson Kathryn K Hatzakis Emmanuel E Miller Diane Doud DD Fresnedo-Ramírez Jonathan J Cooperstone Jessica L JL

The New phytologist 20211004 5

Apple (Malus × domestica) has commercial and nutritional value, but breeding constraints of tree crops limit varietal improvement. Marker-assisted selection minimises these drawbacks, but breeders lack applications for targeting fruit phytochemicals. To understand genotype-phytochemical associations in apples, we have developed a high-throughput integration strategy for genomic and multiplatform metabolomics data. Here, 124 apple genotypes, including members of three pedigree-connected breeding ...[more]

PMID: 34472097

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Project description:Molecular events regulating apple fruit ripening and sensory quality are largely unknown. Such knowledge is essential for genomic-assisted apple breeding and postharvest quality management. In this study, a parallel transcriptome profile analysis, scanning electron microscopic (SEM) examination and systematic physiological characterization were performed on two apple cultivars, Honeycrisp (HC) and Cripps Pink (CP), which have distinct ripening features and texture attributes. Systematic physiological characterization of fruit ripening based on weekly maturity data indicated substantial differences in fruit crispness and firmness at comparable ripening stages. SEM images of fruit cortex tissues prepared from fruits with equivalent maturity suggested that the cell wall thickness may contribute to the observed phenotypes of fruit firmness and crispness. A high-density long-oligo apple microarray consisting of duplex 190,135 cross-hybridization-free 50-70-mer isothermal probes, and representing 23,997 UniGene clusters, was manufactured on a Nimblegen array platform. Transcriptome profiling identified a total of 1793 and 1209 UniGene clusters differentially expressed during ripening from cortex tissues of HC and CP, respectively. UniGenes implicated in hormone metabolism and response, cell wall biosynthesis and modification and those encoding transcription factors were among the prominent functional groups. Between the two cultivars, most of the identified UniGenes were similarly regulated during fruit ripening; however, a short list of gene families or specific family members exhibited distinct expression patterns between the two cultivars, which may represent candidate genes regulating cultivar-specific apple fruit ripening patterns and quality attributes. Using a single color labeling system, a total of 24 microarray slides were utilized, one for each cortex tissue sample, for transcriptome profiling analysis. 2 cultivars x 3 developmental stages x 4 biological replicates.

Dataset Information

Integrating genomics and multi‐platform metabolomics enables metabolite QTL detection in breeding‐relevant apple germplasm

Publications

Integrating genomics and multiplatform metabolomics enables metabolite quantitative trait loci detection in breeding-relevant apple germplasm.

Similar Datasets

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