Dynamics of the transcriptional profile of two sugarcane cultivars contrasting the dry and submitted to the prolonged water deficit

Abstract

Extended periods of drought have become more frequent in some regions of Brazil. The expansion of sugarcane production on regions with chronic water scarcity makes sugarcane production limited in these areas. The best way around this problem is to use stress-tolerant cultivars. Therefore, the aim of this study was to investigate the physiological and molecular behavior (RNA-Seq/Illumina) of two drought-resistant sugarcane cultivars (SP81-3250/tolerant and RB855453/sensitive), submitted to three different soil water potentials (control (without water stress), moderate water scarcity and severe water scarcity) starting 60 days after sowing. These plants were evaluated molecularly and physiologically at three distinct times: 30, 60 and 90 days after the application of the treatments, this is one of the few studies so far on the response of sugarcane plants under chronic water scarcity, stress that was carried out in the period known as the sugar cane formation phase, comprehending the most critical period of water demand. The physiological parameters evaluated and the overall analysis of gene expression showed significant changes in response to the water scarcity between the two cultivars. At an initial work, reassembly of these transcripts, performed using the Trinity program, generated transcript sequences for the cultivars. In order to understand the dynamics of the gene profiles during the three stress periods evaluated and within each soil stress in the two sugarcane cultivars, the aim of the study was to deepen the analysis of the generated transcriptomes and, consequently, to unravel which biological processes are involved in the tolerance and/or sensitivity character of sugar cane subjected to chronic water scarcity. For the validation of the results obtained in the RNA-Seq experiment, the real-time quantitative PCR (qRT-PCR) technique will be used, which is very precise to quantify expression levels of a given gene, as well as offer fast and reproducible data (STOLF, 2007). (AU)