Please use this identifier to cite or link to this item: http://repository.afs.edu.gr/handle/6000/544
Title: Development and application of Single Primer Enrichment Technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce
Authors: Tripodi, Pasquale
Beretta, Massimiliano
Peltier, Damien
Kalfas, Ilias
Vasilikiotis, Christos
Laidet, Anthony
Briand, Gael
Aichholz, Charlotte
Zollinger, Tizian
van Treuren, Rob
Scaglione, Davide
Goritschnig, Sandra
Editors: Bazakos, Christos
Subjects LC: Genomics
Lettuce
Keywords: Lettuce
SPET
High-throughput genotyping
Genomic diversity
Phenotyping
GWAS
Candidate genes
Issue Date: 18-Aug-2023
Publisher: Frontiers Media S.A.
Abstract: Single primer enrichment technology (SPET) is a novel high-throughput genotyping method based on short-read sequencing of specific genomic regions harboring polymorphisms. SPET provides an efficient and reproducible method for genotyping target loci, overcoming the limits associated with other reduced representation library sequencing methods that are based on a random sampling of genomic loci. The possibility to sequence regions surrounding a target SNP allows the discovery of thousands of closely linked, novel SNPs. In this work, we report the design and application of the first SPET panel in lettuce, consisting of 41,547 probes spanning the whole genome and designed to target both coding (~96%) and intergenic (~4%) regions. A total of 81,531 SNPs were surveyed in 160 lettuce accessions originating from a total of 10 countries in Europe, America, and Asia and representing 10 horticultural types. Model ancestry population structure clearly separated the cultivated accessions (Lactuca sativa) from accessions of its presumed wild progenitor (L. serriola), revealing a total of six genetic subgroups that reflected a differentiation based on cultivar typology. Phylogenetic relationships and principal component analysis revealed a clustering of butterhead types and a general differentiation between germplasm originating from Western and Eastern Europe. To determine the potentiality of SPET for gene discovery, we performed genome-wide association analysis for main agricultural traits in L. sativa using six models (GLM naive, MLM, MLMM, CMLM, FarmCPU, and BLINK) to compare their strength and power for association detection. Robust associations were detected for seed color on chromosome 7 at 50 Mbp. Colocalization of association signals was found for outer leaf color and leaf anthocyanin content on chromosome 9 at 152 Mbp and on chromosome 5 at 86 Mbp. The association for bolting time was detected with the GLM, BLINK, and FarmCPU models on chromosome 7 at 164 Mbp. Associations were detected in chromosomal regions previously reported to harbor candidate genes for these traits, thus confirming the effectiveness of SPET for GWAS. Our findings illustrated the strength of SPET for discovering thousands of variable sites toward the dissection of the genomic diversity of germplasm collections, thus allowing a better characterization of lettuce collections.
Description: Article published as Open Access in the Frontiers in Plant Science journal, volume 14, 2023.
Length: 15 pages
Type: Journal Article
Relation (Part Of): Frontiers in Plant Science journal
Publication Status: Published
URI: https://doi.org/10.3389/fpls.2023.1252777
https://www.frontiersin.org/articles/10.3389/fpls.2023.1252777/full
https://www.researchgate.net/publication/373234390_Development_and_application_of_Single_Primer_Enrichment_Technology_SPET_SNP_assay_for_population_genomics_analysis_and_candidate_gene_discovery_in_lettuce
http://repository.afs.edu.gr/handle/6000/544
Citation: Tripodi, P, Beretta, M, Peltier, D, Kalfas, I, Vasilikiotis, C, Laidet, A, Briand, G, Aichholz, C, Zollinger, T, van Treuren, R, Scaglione, D, & Goritschnig, S 2023, 'Development and application of Single Primer Enrichment Technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce', Frontiers in Plant Science, vol. 14, pp. 1-15.
Restrictions: Open Access
Attribution 4.0 International
Language: en
Appears in Collections:Journal Articles

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