Differential sRNA regulation in leaves and roots of sugarcane under water depletion.

Plants have developed multiple regulatory mechanisms to respond and adapt to stress. Drought stress is one of the major constraints to agricultural productivity worldwide and recent reports have highlighted the importance of plant sRNA in the response and adaptation to water availability. In order to increase our understanding of the roles of sRNA in response to water depletion, cultivars of sugarcane were submitted to treatment of ceasing drip irrigation for 24 hours. Deep sequencing analysis was carried out to identify the sRNA regulated in leaves and roots of sugarcane cultivars with different drought sensitivities. The pool of sRNA selected allowed the analysis of different sRNA classes (miRNA and siRNA). Twenty-eight and 36 families of conserved miRNA were identified in leaf and root libraries, respectively. Dynamic regulation of miRNA was observed and the expression profiles of eight miRNA were verified in leaf samples from three biological replicates by stem-loop qRT-PCR assay using the cultivars: SP90-1638--sensitive cultivar--and SP83-2847 and SP83-5073--tolerant cultivars. Altered miRNA regulation was correlated with changes in mRNA levels of specific targets. Two leaf libraries from individual sugarcane cultivars with contrasting drought-tolerance properties were also analyzed. An enrichment of 22-nt sRNA species was observed in leaf libraries. 22-nt miRNA triggered siRNA production by cleavage of their targets in response to water depletion. A number of genes of the sRNA biogenesis pathway were down-regulated in tolerant genotypes and up-regulated in sensitive in response to water depletion treatment. Our analysis contributes to increase the knowledge on the roles of sRNA in sugarcane submitted to water depletion.

High-throughput sequencing of small RNA transcriptome reveals salt stress regulated microRNAs in sugarcane.

Salt stress is a primary cause of crop losses worldwide, and it has been the subject of intense investigation to unravel the complex mechanisms responsible for salinity tolerance. MicroRNA is implicated in many developmental processes and in responses to various abiotic stresses, playing pivotal roles in plant adaptation. Deep sequencing technology was chosen to determine the small RNA transcriptome of Saccharum sp cultivars grown on saline conditions. We constructed four small RNAs libraries prepared from plants grown on hydroponic culture submitted to 170 mM NaCl and harvested after 1 h, 6 hs and 24 hs. Each library was sequenced individually and together generated more than 50 million short reads. Ninety-eight conserved miRNAs and 33 miRNAs* were identified by bioinformatics. Several of the microRNA showed considerable differences of expression in the four libraries. To confirm the results of the bioinformatics-based analysis, we studied the expression of the 10 most abundant miRNAs and 1 miRNA* in plants treated with 170 mM NaCl and in plants with a severe treatment of 340 mM NaCl. The results showed that 11 selected miRNAs had higher expression in samples treated with severe salt treatment compared to the mild one. We also investigated the regulation of the same miRNAs in shoots of four cultivars grown on soil treated with 170 mM NaCl. Cultivars could be grouped according to miRNAs expression in response to salt stress. Furthermore, the majority of the predicted target genes had an inverse regulation with their correspondent microRNAs. The targets encode a wide range of proteins, including transcription factors, metabolic enzymes and genes involved in hormone signaling, probably assisting the plants to develop tolerance to salinity. Our work provides insights into the regulatory functions of miRNAs, thereby expanding our knowledge on potential salt-stressed regulated genes.

Computational identification and analysis of novel sugarcane microRNAs.

BACKGROUND: MicroRNA-regulation of gene expression plays a key role in the development and response to biotic and abiotic stresses. Deep sequencing analyses accelerate the process of small RNA discovery in many plants and expand our understanding of miRNA-regulated processes. We therefore undertook small RNA sequencing of sugarcane miRNAs in order to understand their complexity and to explore their role in sugarcane biology. RESULTS: A bioinformatics search was carried out to discover novel miRNAs that can be regulated in sugarcane plants submitted to drought and salt stresses, and under pathogen infection. By means of the presence of miRNA precursors in the related sorghum genome, we identified 623 candidates of new mature miRNAs in sugarcane. Of these, 44 were classified as high confidence miRNAs. The biological function of the new miRNAs candidates was assessed by analyzing their putative targets. The set of bona fide sugarcane miRNA includes those likely targeting serine/threonine kinases, Myb and zinc finger proteins. Additionally, a MADS-box transcription factor and an RPP2B protein, which act in development and disease resistant processes, could be regulated by cleavage (21-nt-species) and DNA methylation (24-nt-species), respectively. CONCLUSIONS: A large scale investigation of sRNA in sugarcane using a computational approach has identified a substantial number of new miRNAs and provides detailed genotype-tissue-culture miRNA expression profiles. Comparative analysis between monocots was valuable to clarify aspects about conservation of miRNA and their targets in a plant whose genome has not yet been sequenced. Our findings contribute to knowledge of miRNA roles in regulatory pathways in the complex, polyploidy sugarcane genome.

Patterns of genetic diversity in southern and southeastern Araucaria angustifolia (Bert.) O. Kuntze relict populations.

Habitat fragmentation and a decrease in population size may lead to a loss in population genetic diversity. For the first time, the reduction in genetic diversity in the northernmost limit of natural occurence (southeastern Brazil) of Araucaria angustifolia in comparison with populations in the main area of the species continuous natural distribution (southern Brazil), was tested. The 673 AFLPs markers revealed a high level of genetic diversity for the species (Ht = 0.27), despite anthropogenic influence throughout the last century, and a decrease of H in isolated populations of southeastern Brazil (H = 0.16), thereby indicating the tendency for higher genetic diversity in remnant populations of continuous forests in southern Brazil, when compared to natural isolated populations in the southeastern region. A strong differentiation among southern and southeastern populations was detected (AMOVA variance ranged from 10%-15%). From Bayesian analysis, it is suggested that the nine populations tested form five "genetic clusters" (K = 5). Five of these populations, located in the northernmost limit of distribution of the species, represent three "genetic clusters". These results are in agreement with the pattern of geographic distribution of the studied populations.

Patterns of genetic diversity in southern and southeastern Araucaria angustifolia (Bert.) O. Kuntze relict populations

Habitat fragmentation and a decrease in population size may lead to a loss in population genetic diversity. For the first time, the reduction in genetic diversity in the northernmost limit of natural occurence (southeastern Brazil) of Araucaria angustifolia in comparison with populations in the main area of the species continuous natural distribution (southern Brazil), was tested. The 673 AFLPs markers revealed a high level of genetic diversity for the species (Ht = 0.27), despite anthropogenic influence throughout the last century, and a decrease of H in isolated populations of southeastern Brazil (H = 0.16), thereby indicating the tendency for higher genetic diversity in remnant populations of continuous forests in southern Brazil, when compared to natural isolated populations in the southeastern region. A strong differentiation among southern and southeastern populations was detected (AMOVA variance ranged from 10 percent-15 percent). From Bayesian analysis, it is suggested that the nine populations tested form five "genetic clusters" (K = 5). Five of these populations, located in the northernmost limit of distribution of the species, represent three "genetic clusters". These results are in agreement with the pattern of geographic distribution of the studied populations.