Yan Wenliang, Liang Xitong, Li Yang, Jiang Xingtian, Liu Bing, Liu Leilei, Feng Jianying, Karikari Benjamin, Zhao Tuanjie, Jiang Haiyan, Zhu Yan
Sanya Institute of Nanjing Agricultural University, Nanjing Agricultural University, Sanya, 572025, People's Republic of China.
National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, People's Republic of China.
Theor Appl Genet. 2025 May 23;138(6):123. doi: 10.1007/s00122-025-04917-9.
Phenology plays an important role in determining the yield and environmental adaptation of soybean, but easily affected by quantitative trait nucleotides (QTN)-by-environment interactions (QEI) and QTN-by-QTN interactions (QQIs). Detailed understanding of the genetic basis and the interactions between genome and environments is critical for the development of cultivars with geographical-appropriate phenology.
A compressed variance component mixed model (3VmrMLM) was used to detect QTNs, QEIs and QQIs for four key phenological traits of 345 soybean accessions. These traits include days from emergence to first flower (R1), pod beginning (R3), seed formation (R5) and maturity initiation (R7). Meanwhile, QTNs, QEIs and QQIs were identified in at least ten environments and Best Linear Unbiased Prediction (BLUP) value.
(i) A total of 110-193 QTNs, 10-31 QEIs and 4-8 QQIs were identified for each trait. (ii) Sixty-six genes involved in regulation of flower to maturity were identified by functional annotations of GO. (iii) Further haplotype analysis assigned soybean phenology-associated genes into 34 haplotype blocks with 136 haplotypes. (iv) Fifty-nine genes contained within 31 haplotype blocks can be considered as candidate genes for regulating soybean phenology, because changes in these haplotypes led to significant variations in the corresponding phenological traits.
Extensive genetic analysis of the QEIs and QQIs was conducted on key phenological stages in soybean. The candidate genes predicted provide valuable information for functional validation to elucidate the molecular mechanism underlying the soybean phenology.
物候学在决定大豆产量和环境适应性方面发挥着重要作用，但易受数量性状核苷酸（QTN）与环境互作（QEI）以及QTN与QTN互作（QQI）的影响。深入了解遗传基础以及基因组与环境之间的相互作用对于培育具有适应当地物候特征品种至关重要。
采用压缩方差分量混合模型（3VmrMLM）检测345份大豆种质资源四个关键物候性状的QTN、QEI和QQI。这些性状包括出苗至始花天数（R1）、始荚期（R3）、结荚期（R5）和成熟始期（R7）。同时，在至少十个环境中鉴定QTN、QEI和QQI，并采用最佳线性无偏预测（BLUP）值。
（i）每个性状共鉴定出110 - 193个QTN、10 - 31个QEI和4 - 8个QQI。（ii）通过基因本体（GO）功能注释鉴定出66个参与花发育至成熟调控的基因。（iii）进一步的单倍型分析将大豆物候相关基因划分为34个单倍型块，包含136种单倍型。（iv）31个单倍型块中的59个基因可被视为调控大豆物候的候选基因，因为这些单倍型的变化导致相应物候性状出现显著差异。
对大豆关键物候期的QEI和QQI进行了广泛的遗传分析。预测的候选基因为功能验证提供了有价值的信息，以阐明大豆物候的分子机制。
