Software to generate BLUPs, QTL, and meta-QTL are available at https://github.com/bliptrip/CNJ0x-Trait-Mapping .
Open resource ↗GitHub · bliptrip/CNJ0x-Trait-Mapping · lines:1105-1155Unverified paper record
Of buds and bits: a meta-QTL study identifies stable QTL for berry quality and yield traits in cranberry mapping populations ( Vaccinium macrocarpon Ait.).
Frontiers in Plant Science · 17 Sept 2024 · 10.3389/fpls.2024.1294570
Abstract
Introduction For nearly two centuries, cranberry (Vaccinium macrocarpon Ait.) breeders have improved fruit quality and yield by selecting traits on fruiting stems, termed “reproductive uprights.” Crop improvement is accelerating rapidly in contemporary breeding programs due to modern genetic tools and high-throughput phenotyping methods, improving selection efficiency and accuracy. Methods We conducted genotypic evaluation on 29 primary traits encompassing fruit quality, yield, and chemical composition in two full-sib cranberry breeding populations—CNJ02 (n = 168) and CNJ04 (n = 67)—over 3 years. Genetic characterization was further performed on 11 secondary traits derived from these primary traits. Results For CNJ02, 170 major quantitative trait loci (QTL; R2≥ 0.10) were found with interval mapping, 150 major QTL were found with model mapping, and 9 QTL were found to be stable across multiple years. In CNJ04, 69 major QTL were found with interval mapping, 81 major QTL were found with model mapping, and 4 QTL were found to be stable across multiple years. Meta-QTL represent stable genomic regions consistent across multiple years, populations, studies, or traits. Seven multi-trait meta-QTL were found in CNJ02, one in CNJ04, and one in the combined analysis of both populations. A total of 22 meta-QTL were identified in cross-study, cross-population analysis using digital traits for berry shape and size (8 meta-QTL), digital images for berry color (2 meta-QTL), and three-study cross-analysis (12 meta-QTL). Discussion Together, these meta-QTL anchor high-throughput fruit quality phenotyping techniques to traditional phenotyping methods, validating state-of-the-art methods in cranberry phenotyping that will improve breeding accuracy, efficiency, and genetic gain in this globally significant fruit crop.
Plant phenotyping relevance
ベリー形状・サイズ・色のデジタル形質および画像を用いた果実フェノタイピングをQTL解析で検証し、従来法との対応付けを行っており、手法の妥当性評価が研究の主要な成果に含まれる。
abstractdigital traits for berry shape and size (8 meta-QTL), digital images for berry color (2 meta-QTL)
abstractTogether, these meta-QTL anchor high-throughput fruit quality phenotyping techniques to traditional phenotyping methods, validating state-of-the-art methods in cranberry phenotyping
Code and data availability
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