A Comprehensive Image-based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa)
A Comprehensive Image-based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa)
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DOI：
10.3835/plantgenome2016.07.0064
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发表时间：
2017-07-01
期刊：
影响因子：
4.2
通讯作者：
Walia, Harkamal
中科院分区：
文献类型：
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作者：
Campbell, Malachy T.;Du, Qian;Walia, Harkamal
早活力是许多水稻生长环境的重要性状。然而，由于该性状的时间特性和x基因型强的环境效应，早期活力的遗传鉴定和改良受到阻碍。本研究采用功能建模和全基因组关联（GWAS）作图方法，在360个水稻品种的多样性面板上，探讨了分蘖早期和活跃分蘖阶段茎部生长动态的遗传结构。发现了多个对茎部生长轨迹影响较小的位点，表明其具有复杂的多基因结构。利用RNA测序和激素定量分析，对31种植物的芽部生长动态进行了自然变异评估。这些分析得到了一个赤霉素（GA）分解代谢基因OsGA2ox7，该基因可以影响GA水平，从而调节分蘖期早期的活力。考虑到茎部生长动力学的复杂遗传结构，利用基因组选择（GS）的36,901个单核苷酸多态性（snp）以及GWAS中最显著的几个snp亚群，探讨了基因组选择（GS）提高早期活力的潜力。利用来自GWAS的50个最显著snp（0.37 ~ 0.53）可以较好地预测茎部生长轨迹；然而，加入更多的标记物可以提高预测的准确性，这表明GS可能是改善营养生长期芽部生长动态的有效策略。该研究揭示了水稻幼苗早期生长动态的复杂遗传结构和分子机制，为改善这一复杂性状提供了基础。
Early vigor is an important trait for many rice (Oryza sativa L.)growing environments. However, genetic characterization and improvement for early vigor is hindered by the temporal nature of the trait and strong genotype x environment effects. We explored the genetic architecture of shoot growth dynamics during the early and active tillering stages by applying a functional modeling and genomewide association (GWAS) mapping approach on a diversity panel of similar to 360 rice accessions. Multiple loci with small effects on shoot growth trajectory were identified, indicating a complex polygenic architecture. Natural variation for shoot growth dynamics was assessed in a subset of 31 accessions using RNA sequencing and hormone quantification. These analyses yielded a gibberellic acid (GA) catabolic gene, OsGA2ox7, which could influence GA levels to regulate vigor in the early tillering stage. Given the complex genetic architecture of shoot growth dynamics, the potential of genomic selection (GS) for improving early vigor was explored using all 36,901 single-nucleotide polymorphisms (SNPs) as well as several subsets of the most significant SNPs from GWAS. Shoot growth trajectories could be predicted with reasonable accuracy using the 50 most significant SNPs from GWAS (0.37-0.53); however, the accuracy of prediction was improved by including more markers, which indicates that GS may be an effective strategy for improving shoot growth dynamics during the vegetative growth stage. This study provides insights into the complex genetic architecture and molecular mechanisms underlying early shoot growth dynamics and provides a foundation for improving this complex trait in rice.