Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91190, Gif-sur-Yvette, France.
Université de Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), 91190, Gif-sur-Yvette, France.
Theor Appl Genet. 2023 Oct 19;136(11):228. doi: 10.1007/s00122-023-04458-z.
Multi-trial genome wide association study of plasticity indices allow to detect QTLs specifically involved in the genotype x water availability interaction. Concerns regarding high maize yield losses due to increasing occurrences of drought events are growing, and breeders are still looking for molecular markers for drought tolerance. However, the genetic determinism of traits in response to drought is highly complex and identification of causal regions is a tremendous task. Here, we exploit the phenotypic data obtained from four trials carried out on a phenotyping platform, where a diversity panel of 254 maize hybrids was grown under well-watered and water deficit conditions, to investigate the genetic bases of the drought response in maize. To dissociate drought effect from other environmental factors, we performed multi-trial genome-wide association study on well-watered and water deficit phenotypic means, and on phenotypic plasticity indices computed from measurements made for six ecophysiological traits. We identify 102 QTLs and 40 plasticity QTLs. Most of them were new compared to those obtained from a previous study on the same dataset. Our results show that plasticity QTLs cover genetic regions not identified by QTLs. Furthermore, for all ecophysiological traits, except one, plasticity QTLs are specifically involved in the genotype by water availability interaction, for which they explain between 60 and 100% of the variance. Altogether, QTLs and plasticity QTLs captured more than 75% of the genotype by water availability interaction variance, and allowed to find new genetic regions. Overall, our results demonstrate the importance of considering phenotypic plasticity to decipher the genetic architecture of trait response to stress.
多试验全基因组关联研究可塑性指标可以检测到专门参与基因型与水分可利用性互作的 QTL。由于干旱事件发生频率的增加导致玉米产量损失越来越大,人们对此表示担忧,育种者仍在寻找抗旱的分子标记。然而,响应干旱的性状的遗传决定因素非常复杂,确定因果区域是一项艰巨的任务。在这里,我们利用在表型平台上进行的四项试验获得的表型数据,该平台在充分供水和水分亏缺条件下种植了 254 个玉米杂交种的多样性群体,以研究玉米对干旱的遗传基础。为了将干旱效应与其他环境因素区分开来,我们对充分供水和水分亏缺的表型均值以及从六个生理生态性状的测量值计算得出的表型可塑性指数进行了多试验全基因组关联研究。我们确定了 102 个 QTL 和 40 个可塑性 QTL。与在同一数据集上进行的先前研究获得的 QTL 相比,其中大多数是新的。我们的结果表明,可塑性 QTL 覆盖了由 QTL 未识别的遗传区域。此外,除了一个性状外,对于所有生理生态性状,可塑性 QTL 都专门参与了基因型与水分可利用性互作,它们解释了 60%至 100%的方差。总体而言,QTL 和可塑性 QTL 捕获了超过 75%的基因型与水分可利用性互作方差,并找到了新的遗传区域。总的来说,我们的研究结果表明,考虑表型可塑性对于解析性状对胁迫的遗传结构非常重要。