National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Agricultural Bioinformatics Key Laboratory of Hubei Province, College of Informatics, and College of Engineering, Huazhong Agricultural University, Wuhan, China.
Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, and Key Laboratory of Ministry of Education for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan, China.
J Exp Bot. 2019 Jan 7;70(2):545-561. doi: 10.1093/jxb/ery373.
Manual phenotyping of rice tillers is time consuming and labor intensive, and lags behind the rapid development of rice functional genomics. Thus, automated, non-destructive methods of phenotyping rice tiller traits at a high spatial resolution and high throughput for large-scale assessment of rice accessions are urgently needed. In this study, we developed a high-throughput micro-CT-RGB imaging system to non-destructively extract 739 traits from 234 rice accessions at nine time points. We could explain 30% of the grain yield variance from two tiller traits assessed in the early growth stages. A total of 402 significantly associated loci were identified by genome-wide association study, and dynamic and static genetic components were found across the nine time points. A major locus associated with tiller angle was detected at time point 9, which contained a major gene, TAC1. Significant variants associated with tiller angle were enriched in the 3'-untranslated region of TAC1. Three haplotypes for the gene were found, and rice accessions containing haplotype H3 displayed much smaller tiller angles. Further, we found two loci containing associations with both vigor-related traits identified by high-throughput micro-CT-RGB imaging and yield. The superior alleles would be beneficial for breeding for high yield and dense planting.
手动表型分析水稻分蘖是一项耗时耗力的工作,并且跟不上水稻功能基因组学的快速发展。因此,迫切需要一种自动化、非破坏性的方法,以高空间分辨率和高通量对大量水稻品系进行水稻分蘖特性的表型分析。在本研究中,我们开发了一种高通量微 CT-RGB 成像系统,可在 9 个时间点非破坏性地从 234 个水稻品系中提取 739 个特征。我们可以从早期生长阶段评估的两个分蘖特征中解释 30%的籽粒产量变异。通过全基因组关联研究鉴定了 402 个与分蘖相关的显著关联位点,并在 9 个时间点发现了动态和静态遗传成分。在第 9 个时间点检测到一个与分蘖角度相关的主要位点,其中包含一个主基因 TAC1。与分蘖角度相关的显著变体在 TAC1 的 3'非翻译区富集。发现了该基因的三个单倍型,含有单倍型 H3 的水稻品系表现出更小的分蘖角度。此外,我们发现了两个包含与高通量微 CT-RGB 成像和产量鉴定的活力相关特征的关联的位点。这些优异的等位基因将有利于高产和密植的选育。