Development of a Flex-Seq SNP panel for raspberry (Rubus idaeus L.) and validation through linkage map construction and identification of QTL for several traits of agronomic importance to raspberry breeding

High-throughput and reproducible genotyping platforms are critical for advancing genetic research and breeding in horticultural crops. Here, the development and validation of a custom single nucleotide polymorphism (SNP) panel using the Flex-Seq genotyping platform for red raspberry (Rubus idaeus L.) is described. SNPs were derived from existing linkage maps and RNA-seq data, resulting in a panel of 5,639 high-confidence, bi-allelic markers distributed across the seven chromosomes of the R. idaeus 'Malling Jewel' reference genome. The panel was used to genotype 457 red raspberry accessions including 161 individuals from a bi-parental mapping population (Paris×486), enabling the construction of high-density linkage maps and the identification of quantitative trait loci (QTL) for fruit size, leaf colour, plant vigour, and thorn density. Genome-wide association studies (GWAS) identified a major QTL for thornlessness on chromosome 4, co-locating with a candidate HOX3 gene, and multiple QTLs associated with anthocyanin biosynthesis genes for leaf colour. The SNP panel demonstrated utility for linkage mapping and trait association analyses, offering a powerful resource for marker-assisted selection and genetic improvement in red raspberry.

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Publication Details

Journal
PLoS ONE
Published
2026-02-17
DOI
https://doi.org/10.1371/journal.pone.0328606
Primary Topic
Berry genetics and cultivation research
Type
article
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article

Development of a Flex-Seq SNP panel for raspberry (Rubus idaeus L.) and validation through linkage map construction and identification of QTL for several traits of agronomic importance to raspberry breeding

Jahn Davik, Matteo Buti, Linda Milne, Julie Graham et al.
PLoS ONE
Berry genetics and cultivation research
article

Development of a Flex-Seq SNP panel for raspberry (Rubus idaeus L.) and validation through linkage map construction and identification of QTL for several traits of agronomic importance to raspberry breeding

Jahn Davik, Matteo Buti, Linda Milne, Julie Graham, Paolo Zucchi, Daniel James Sargent
article en

Abstract

High-throughput and reproducible genotyping platforms are critical for advancing genetic research and breeding in horticultural crops. Here, the development and validation of a custom single nucleotide polymorphism (SNP) panel using the Flex-Seq genotyping platform for red raspberry (Rubus idaeus L.) is described. SNPs were derived from existing linkage maps and RNA-seq data, resulting in a panel of 5,639 high-confidence, bi-allelic markers distributed across the seven chromosomes of the R. idaeus 'Malling Jewel' reference genome. The panel was used to genotype 457 red raspberry accessions including 161 individuals from a bi-parental mapping population (Paris×486), enabling the construction of high-density linkage maps and the identification of quantitative trait loci (QTL) for fruit size, leaf colour, plant vigour, and thorn density. Genome-wide association studies (GWAS) identified a major QTL for thornlessness on chromosome 4, co-locating with a candidate HOX3 gene, and multiple QTLs associated with anthocyanin biosynthesis genes for leaf colour. The SNP panel demonstrated utility for linkage mapping and trait association analyses, offering a powerful resource for marker-assisted selection and genetic improvement in red raspberry.

PLoS ONEVol. 21(2)
National Institute of Agricultural Botany (GB), James Hutton Institute (GB), IRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola (IT), Norwegian Institute of Bioeconomy Research (NO), University of Florence (IT)
Openalex Percentile: Top 52%
Berry genetics and cultivation research
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Development of a Flex-Seq SNP panel for raspberry (Rubus idaeus L.) and validation through linkage map construction and identification of QTL for several traits of agronomic importance to raspberry breeding — Jahn Davik, Matteo Buti, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS