Image-based QTL mapping of grain size for establishment of predictive breeding in rice

Abstract

Rice is a staple food and a major source of calories for much of the global population. With the global population continuing to rise, breeding high-yielding rice cultivars is critical for future food security. Grain size is a key trait directly related to rice yield. In this study, QTL mapping was conducted using both phenotypic data collected with Vernier calipers and image-based phenotyping. All QTLs identified through caliper measurements were also detected using image data, which allowed for more precise localization with higher LOD scores. Grain size-related QTLs were identified on chromosomes 3, 5, 6, and 7, including major genes such as GS3, qSW5, and GW7. A novel QTL region between markers RM586 and RM1163 on chromosome 6 was identified, which has not been previously reported. Introgression of this region positively affected grain length, and an additive effect was observed when combined with qGL3. Within the RM586-RM1163 region, 16 open reading frames (ORFs) were annotated, and Gene Ontology (GO) analysis suggested their roles in regulating cellular structures and organelle functions during grain development. Among these, OsGSq6 showed a significant increase in expression from the panicle formation stage to the heading stage. Fifteen SNPs were identified within the gene, resulting in 11 distinct haplotypes, several of which were predominantly found in indica rice. OsGSq6 encodes a phosphotyrosyl phosphatase activator, suggesting its role in grain development. Image-based phenotyping also enabled the detection of varietal admixtures, contributing to improved genetic purity. This approach offers a promising strategy for enhancing rice breeding precision.

Plant phenotyping relevance

画像ベース表現型解析を用いてイネ粒サイズを定量し、ノギス測定との比較でQTL検出精度を評価しており、表現型取得法の実質的な適用が研究上重要です。

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