Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA.
Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA.
Plant J. 2024 Jul;119(2):844-860. doi: 10.1111/tpj.16801. Epub 2024 May 29.
Transcriptome-wide association studies (TWAS) can provide single gene resolution for candidate genes in plants, complementing genome-wide association studies (GWAS) but efforts in plants have been met with, at best, mixed success. We generated expression data from 693 maize genotypes, measured in a common field experiment, sampled over a 2-h period to minimize diurnal and environmental effects, using full-length RNA-seq to maximize the accurate estimation of transcript abundance. TWAS could identify roughly 10 times as many genes likely to play a role in flowering time regulation as GWAS conducted data from the same experiment. TWAS using mature leaf tissue identified known true-positive flowering time genes known to act in the shoot apical meristem, and trait data from a new environment enabled the identification of additional flowering time genes without the need for new expression data. eQTL analysis of TWAS-tagged genes identified at least one additional known maize flowering time gene through trans-eQTL interactions. Collectively these results suggest the gene expression resource described here can link genes to functions across different plant phenotypes expressed in a range of tissues and scored in different experiments.
转录组关联研究（TWAS）可以为植物中的候选基因提供单基因分辨率，补充全基因组关联研究（GWAS），但在植物中的努力充其量只是喜忧参半。我们使用全长 RNA-seq 生成了 693 个玉米基因型的表达数据，这些数据是在一个常见的田间实验中测量的，在 2 小时的时间内进行采样，以最大程度地减少昼夜和环境影响，从而最大限度地准确估计转录丰度。TWAS 可以识别出大约 10 倍数量的基因，这些基因可能在开花时间调控中发挥作用，而 GWAS 则使用来自同一实验的数据进行分析。使用成熟叶片组织进行的 TWAS 可以识别出已知的在茎尖分生组织中起作用的真正的开花时间基因，并且来自新环境的性状数据使我们无需新的表达数据就可以识别出其他开花时间基因。TWAS 标记基因的 eQTL 分析通过跨 eQTL 相互作用鉴定出至少一个已知的玉米开花时间基因。总的来说，这些结果表明，这里描述的基因表达资源可以将基因与不同组织中表达的不同植物表型以及在不同实验中评分的功能联系起来。
