Challenges of Translating Gene Regulatory Information into Agronomic Improvements

First author: Nathan Springer; Affiliations: University of Minnesota (明尼苏达大学): St Paul, USA

Corresponding author: Nathan Springer

Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.

农艺物种的遗传改良已经利用了很多复杂数量性状的遗传变异。很多这种功能变异具有调控能力，要么是顺式调控元件，要么是反式作用因子，能够最终作用于基因的差异表达。然而，鉴定有助于增加植物产量或适应性的基因调控网络组份富有挑战性，然而对用于改良目的性状的基因组工程增加可预测能力非常重要。本文中，作者讨论了利用基因共表达、转录因子结合以及全基因组关联作图等方法预测的调控互作应用于作物遗传改良的机遇与限制。显然，利用这些不同的数据类型组合对于有效鉴定和利用复杂农艺性状背后潜在遗传调控网络是必要的。

通讯：Nathan Springer  (https://cbs.umn.edu/contacts/nathan-m-springer)

个人简介：1997年，东南密苏里州立大学，学士；2000年，明尼苏达大学，博士；2000-2004年，威斯康星大学麦迪逊分校，博士后 。

研究方向：玉米的分子变异与遗传。

doi: https://doi.org/10.1016/j.tplants.2019.07.004

Journal: Trends in Plant Science

Available online: July 31, 2019