Sugarcane is an important international commodity as a valuable agricultural crop especially in developing countries. Sequencing was carried out to generate >35,000 expressed sequence tags (ESTs) from healthy as well as red-rot-infected tissue of Indian subtropical variety of sugarcane. Subsequent clustering with existing sugarcane ESTs in public databases identified 4,087 clusters, including 85 clusters that preferentially express upon Colletotrichum falcatum (red-rot) infection, which were previously unreported. Real-time reverse transcription-PCR profiling of selected EST clusters identified several sugarcane clusters that show differential expression in response to biotic and abiotic stress conditions. Twenty-five stress-related clusters showed >2-fold relative expression during water-deficit stress in sugarcane. Similarly, EST clusters could be identified, which exhibit association with red-rot disease when assessed in red-rot-susceptible and red-rot-resistant varieties of sugarcane. Such EST clusters are good candidates for in-depth analysis to elucidate stress-responsive pathways in sugarcane and facilitate genetic manipulation to tailor this crop for tolerance to various stresses.

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Therapeutic factors operative in in-patient and out-patient therapy groups were compared. These settings differ greatly, both in terms of the patient population they serve and the overall systems within which they operate. The study revealed significant differences between the therapeutic factors operative in these two settings, and suggested that clinicians should modify their techniques for running psychotherapy groups across settings, to take account of these findings.

HighlightsWaterlogging adversely affects sugarcane productivity and quality.A subtractive cDNA library was prepared from sugarcane leaf tissue and sequenced to generate ESTs.EST sequences were used to identify transcripts induced by waterlogging.The sequenced clones were classified by predicted functions and stress-related genes formed the largest class.EST sequences were also used to identify putative novel microRNAs and their targets.

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