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性状捕获:植物表型组数据的基因组与环境建模

TraitCapture: genomic and environment modelling of plant phenomic data.

作者信息

Brown Tim B, Cheng Riyan, Sirault Xavier R R, Rungrat Tepsuda, Murray Kevin D, Trtilek Martin, Furbank Robert T, Badger Murray, Pogson Barry J, Borevitz Justin O

机构信息

Division of Plant Sciences, Research School of Biology, Australian National University, Australia.

High Resolution Plant Phenomics Centre, Plant Industry, CSIRO, Australia.

出版信息

Curr Opin Plant Biol. 2014 Apr;18:73-9. doi: 10.1016/j.pbi.2014.02.002. Epub 2014 Mar 16.

Abstract

Agriculture requires a second green revolution to provide increased food, fodder, fiber, fuel and soil fertility for a growing population while being more resilient to extreme weather on finite land, water, and nutrient resources. Advances in phenomics, genomics and environmental control/sensing can now be used to directly select yield and resilience traits from large collections of germplasm if software can integrate among the technologies. Traits could be Captured throughout development and across environments from multi-dimensional phenotypes, by applying Genome Wide Association Studies (GWAS) to identify causal genes and background variation and functional structural plant models (FSPMs) to predict plant growth and reproduction in target environments. TraitCapture should be applicable to both controlled and field environments and would allow breeders to simulate regional variety trials to pre-select for increased productivity under challenging environments.

摘要

农业需要第二次绿色革命,以便为不断增长的人口提供更多的食物、饲料、纤维、燃料,并提高土壤肥力,同时在有限的土地、水和养分资源条件下,增强对极端天气的抵御能力。如果软件能够整合这些技术,那么表型组学、基因组学以及环境控制/传感方面的进展现在就可以用于从大量种质资源中直接选择产量和抗逆性性状。通过应用全基因组关联研究(GWAS)来识别因果基因和背景变异,并利用功能性结构植物模型(FSPM)来预测目标环境中的植物生长和繁殖,可以从多维表型中在整个发育过程及不同环境中获取性状。性状捕获应适用于可控环境和田间环境,并将使育种者能够模拟区域品种试验,以便在具有挑战性的环境下预先选择提高生产力的品种。

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