Subtractive hybridization-mediated analysis of genes and in silico prediction of associated microRNAs under waterlogged conditions in sugarcane (Saccharum spp.)
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AuthorsKhan, Mohammad Suhail
Gupta, Ram Sagar
Duttamajumder, Sanjoy Kumar
Online Publication Date2014-06-10
Print Publication Date2014-01-01
Permanent link to this recordhttp://hdl.handle.net/10754/334607
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AbstractSugarcane is an important tropical cash crop meeting 75% of world sugar demand and it is fast becoming an energy crop for the production of bio-fuel ethanol. A considerable area under sugarcane is prone to waterlogging which adversely affects both cane productivity and quality. In an effort to elucidate the genes underlying plant responses to waterlogging, a subtractive cDNA library was prepared from leaf tissue. cDNA clones were sequenced and annotated for their putative functions. Major groups of ESTs were related to stress (15%), catalytic activity (13%), cell growth (10%) and transport related proteins (6%). A few stress-related genes were identified, including senescence-associated protein, dehydration-responsive family protein, and heat shock cognate 70. kDa protein. A bioinformatics search was carried out to discover novel microRNAs (miRNAs) that can be regulated in sugarcane plants subjected to waterlogging stress. Taking advantage of the presence of miRNA precursors in the related sorghum genome, seven candidate mature miRNAs were identified in sugarcane. The application of subtraction technology allowed the identification of differentially expressed sequences and novel miRNAs in sugarcane under waterlogging stress. The comparative global transcript profiling in sugarcane plants undertaken in this study suggests that proteins associated with stress response, signal transduction, metabolic activity and ion transport play important role in conferring waterlogging tolerance in sugarcane. © 2014 The Authors.
CitationKhan MS, Khraiwesh B, Pugalenthi G, Gupta RS, Singh J, et al. (2014) Subtractive hybridization-mediated analysis of genes and in silico prediction of associated microRNAs under waterlogged conditions in sugarcane (Saccharum spp.). FEBS Open Bio 4: 533-541. doi:10.1016/j.fob.2014.05.007.
JournalFEBS Open Bio
PubMed Central IDPMC4087145
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Except where otherwise noted, this item's license is described as This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
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