Campbell Malachy T, Knecht Avi C, Berger Bettina, Brien Chris J, Wang Dong, Walia Harkamal
Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.).
Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
Plant Physiol. 2015 Aug;168(4):1476-89. doi: 10.1104/pp.15.00450. Epub 2015 Jun 25.
Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides one-third of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 d of 90 mm NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on chromosome 3 was strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer term ionic stress and the early growth rate decline during salinity stress. We present, to our knowledge, a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model.
盐度影响着很大一部分耕地,对灌溉农业尤其有害,而灌溉农业提供了全球三分之一的粮食供应。水稻(Oryza sativa)是最重要的粮食作物,对盐敏感。水稻种质中存在耐盐的遗传资源,但由于难以捕捉对盐胁迫生理反应的动态特性,这些资源未得到充分利用。预计这些生理反应的遗传基础是多基因的。为应对这一挑战,我们在90毫米氯化钠胁迫下,对378种不同水稻基因型进行了为期14天的时间成像数据采集,并开发了一个统计模型,以评估水稻种质中动态盐度诱导生长反应的遗传结构。3号染色体上的一个基因组区域与早期生长反应密切相关,可通过可见光成像捕捉到。荧光成像确定了四个与盐度诱导荧光反应相关的基因组区域。1号染色体上的一个区域既调节指示长期离子胁迫的荧光变化,也调节盐胁迫期间早期生长速率的下降。据我们所知,我们提出了一种新方法,通过纵向全基因组关联模型来捕捉植物对其环境的动态反应,并阐明这些反应的遗传基础。