Explore Plants Specific Responsive Genes To Different Heavy Metals In Silico

Heavy metal pollution is harmful for human health.Current physical and chemical methods used to test heavy metal pollution are not convenient and efficient.With the development of biological study with huge gene expression data including plants responding to different heavy metals provide the possibility to develop a way to detect heavy metals pollution with gene expression pattern.Through analysis of the large scale gene expression data from NCBI GEO database,we tried to isolate the different gene expression pattern response to different heavy metals respectively,so that the specific gene expression pattern can be used as markers for heavy metal pollution gene detection.After retrieved various heavy metal treated plant gene expression data,we did a series of normalizations,clustering,and further investigate the expression pattern including GO(Gene Ontology)enrichment and KEGG(Kyoto Encyclopedia of Genes and Genomes)pathway response to As,Zn,Fe,Cd with data from Arabidopsis.Factors which affect the accuracy of the detection were analyzed and discussed.Finally,we identified 221 candidate DEGs,which may involved in the progression of heavy metal.Among them,41 genes respond to iron,75 genes upregulated respond to arsenic and 105 downregulated respond to arsenic.