Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA.
Department of Computer Science and Engineering, and Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA.
Plant Sci. 2022 Aug;321:111318. doi: 10.1016/j.plantsci.2022.111318. Epub 2022 May 13.
Stagnated crop improvement has raised questions of whether and how current crop cultivars can be further improved. Genes are the core determinants of performance of all cultivars. Here, we report the molecular basis of plant breeding and address these questions by analyzing 226 GFL genes controlling and accurately predicting fiber length, an important breeding objective trait, in cotton (Gossypium sp.). We first identified the favorable allele and the number of favorable alleles (NFAs) of each GFL gene, calculated the total NFAs of the 226 GFL genes accumulated in 198 advanced breeding lines, and analyzed them against fiber lengths. Fiber lengths of the breeding lines were strongly correlated with the total NFAs of the GFL genes (r = 0.85, P < 0.0001), suggesting that accumulation of the favorable alleles of the genes controlling objective traits is the molecular basis of cotton breeding. Surprisingly, a breeding line with a fiber length of present cultivars having the longest fibers contained only about 51% of the total NFAs of the 226 GFL genes. The genetic potentials of current cultivars were then predicted using linear and non-linear models, respectively, revealing that a breeding line or cultivar with a fiber length of 33.8 mm could be further improved in fiber length by up to 118%. Finally, we showed that the genetic potential of such a breeding line can be realized through gene-based breeding. Therefore, these findings shed light on continued crop improvement in general and provide 740 genic biomarkers desirable for enhanced cotton fiber breeding.
作物改良停滞不前，引发了人们对于当前作物品种是否以及如何进一步改良的质疑。基因是所有品种表现的核心决定因素。在这里，我们通过分析控制和准确预测棉花纤维长度（重要的育种目标性状）的 226 个 GFL 基因，报告了植物育种的分子基础，并通过分析 226 个 GFL 基因来解决这些问题，这些基因控制和准确预测棉花纤维长度（重要的育种目标性状）。我们首先鉴定了每个 GFL 基因的有利等位基因和有利等位基因数量（NFA），计算了 198 个先进育种系中累积的 226 个 GFL 基因的总 NFA，并分析了它们与纤维长度的关系。育种系的纤维长度与 GFL 基因的总 NFA 呈强烈相关性（r=0.85，P<0.0001），这表明控制目标性状的基因有利等位基因的积累是棉花育种的分子基础。令人惊讶的是，纤维长度与现有最长纤维品种的育种系仅包含约 226 个 GFL 基因总 NFA 的 51%。然后，我们分别使用线性和非线性模型预测了当前品种的遗传潜力，结果表明，纤维长度为 33.8mm 的育种系或品种，纤维长度可进一步提高 118%。最后，我们表明，这种育种系的遗传潜力可以通过基于基因的育种来实现。因此，这些发现为一般作物改良提供了新的思路，并为增强棉花纤维育种提供了 740 个理想的基因生物标志物。
