Characterization of differentially expressed genes to Cu stress in Brassica nigra by Arabidopsis genome arrays


Cevher-Keskin B., Yildizhan Y., Yuksel B., Dalyan E. , Memon A. R.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, cilt.26, ss.299-311, 2019 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 26 Konu: 1
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1007/s11356-018-3577-7
  • Dergi Adı: ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • Sayfa Sayıları: ss.299-311

Özet

Phytoremediation is an efficient and promising cleanup technology to extract or inactivate heavy metals and several organic and inorganic pollutants from soil and water. In this study, different Brassica nigra L. ecotypes, including Diyarbakr, collected from mining areas were exposed to different concentrations of copper and harvested after 72h of Cu stress for the assessment of phytoremediation capacity. The Diyarbakr ecotype was called as metallophyte because of surviving at 500M Cu. To better understand Cu stress mechanism, ArabidopsisATH1 genome array was used to compare the gene expression in root and shoot tissues of B. nigra under 25M Cu. The response to Cu was much stronger in roots (88 genes showing increased or decreased mRNA levels) than in leaf tissues (24 responding genes). These genes were classified into the metal transport and accumulation-related genes, signal transduction and metabolism-related genes, and transport facilitation genes. Glutathione pathway-related genes (-ECS, PC, etc.) mRNAs were identified as differentially expressed in root and shoot tissues. QRT-PCR validation experiments showed that -ECS and PC expression was upregulated in the shoot and leaf tissues of the 100M Cu-subjected B. nigra-tolerant ecotype. This is the first study showing global expression profiles in response to Cu stress in B. nigra by Arabidopsis genome array. This work presented herein provides a well-illustrated insight into the global gene expression to Cu stress response in plants, and identified genes from microarray data will serve as molecular tools for the phytoremediation applications in the future.