Center for Research in Agricultural Genomics CSIC-IRTA-UAB, Barcelona 08034, Spain.
Curr Opin Biotechnol. 2011 Apr;22(2):260-70. doi: 10.1016/j.copbio.2010.11.010. Epub 2010 Dec 15.
Arabidopsis genomic and network analyses have facilitated crop research towards the understanding of many biological processes of fundamental importance for agriculture. Genes that were identified through genomic analyses in Arabidopsis have been used to manipulate crop traits such as pathogen resistance, yield, water-use efficiency, and drought tolerance, with the effects being tested in field conditions. The integration of diverse Arabidopsis genome-wide datasets in probabilistic functional networks has been demonstrated as a feasible strategy to associate novel genes with traits of interest, and novel genomic methods continue to be developed. The combination of genome-wide location studies, using ChIP-Seq, with gene expression profiling data is affording a genome-wide view of regulatory networks previously delineated through genetic and molecular analyses, leading to the identification of novel components and of new connections within these networks.
拟南芥基因组和网络分析促进了作物研究,有助于理解对农业具有重要基础意义的许多生物学过程。通过在拟南芥中的基因组分析鉴定的基因已被用于操纵作物特性,如抗病性、产量、水利用效率和耐旱性,其效果在田间条件下进行了测试。将不同的拟南芥全基因组数据集整合到概率功能网络中已被证明是一种可行的策略,可将新基因与感兴趣的性状相关联,并且新的基因组方法仍在不断发展。使用 ChIP-Seq 进行全基因组定位研究与基因表达谱数据的组合,提供了以前通过遗传和分子分析描绘的调控网络的全基因组视图,从而鉴定了这些网络中的新组件和新连接。