@article {8888, title = {Genome-wide changes in microRNA expression during short and prolonged heat stress and recovery in contrasting rice cultivars [Next Gen Genomics Facility]}, journal = {J Exp Bot}, volume = {68}, year = {2017}, month = {2017 Apr 01}, pages = {2399-2412}, abstract = {

MicroRNAs (miRNAs) are known to regulate expression of genes under stress. We report here the deep sequencing of small RNAs expressed during control, short and prolonged heat stress and recovery. Genome-wide identification of miRNAs in tolerant (Nagina 22) and susceptible (Vandana) rice cultivars was performed in 16 samples representing root and shoot of 13-day-old seedlings. The expression profile of miRNAs was analysed in 36 pairwise combinations to identify the genotype-, treatment- and tissue-dependent expression of miRNAs. Small-RNA sequencing of 16 libraries yielded ~271 million high-quality raw sequences; 162 miRNA families were identified. The highly expressed miRNAs in rice tissues were miR166, miR168, miR1425, miR529, mR162, miR1876, and miR1862. Expression of osa-miR1436, osa-miR5076, osa-miR5161, and osa-miR6253 was observed only in stressed tissue of both genotypes indicating their general role in heat stress response. Expression of osa-miR1439, osa-miR1848, osa-miR2096, osa-miR2106, osa-miR2875, osa-miR3981, osa-miR5079, osa-miR5151, osa-miR5484, osa-miR5792, and osa-miR5812 was observed only in Nagina 22 during high temperature, suggesting a specific role of these miRNAs in heat stress tolerance. This study provides details of the repertoire of miRNAs expressed in root and shoot of heat susceptible and tolerant rice genotypes under heat stress and recovery.

}, keywords = {Gene Expression Regulation, Plant, Genome, Plant, High-Throughput Nucleotide Sequencing, Hot Temperature, MicroRNAs, Oryza, RNA, Plant, Seedlings, Sequence Analysis, RNA, Time Factors}, issn = {1460-2431}, doi = {10.1093/jxb/erx111}, author = {Mangrauthia, Satendra K and Bhogireddy, Sailaja and Agarwal, Surekha and Prasanth, Vishnu V and Voleti, S R and Neelamraju, Sarla and Subrahmanyam, Desiraju} } @article {518, title = {Vertebrate Hedgehog is secreted on two types of extracellular vesicles with different signaling properties. (Mass spectrometry - Proteomics)}, journal = {Sci Rep}, volume = {4}, year = {2014}, month = {2014 Dec 08}, pages = {7357}, abstract = {

Hedgehog (Hh) is a secreted morphogen that elicits differentiation and patterning in developing tissues. Multiple proposed mechanisms to regulate Hh dispersion includes lipoprotein particles and exosomes. Here we report that vertebrate Sonic Hedgehog (Shh) is secreted on two types of extracellular-vesicles/exosomes, from human cell lines and primary chick notochord cells. Although largely overlapping in size as estimated from electron micrographs, the two exosomal fractions exhibited distinct protein and RNA composition. We have probed the functional properties of these vesicles using cell-based assays of Hh-elicited gene expression. Our results suggest that while both Shh-containing exo-vesicular fractions can activate an ectopic Gli-luciferase construct, only exosomes co-expressing Integrins can activate endogenous Shh target genes HNF3β and Olig2 during the differentiation of mouse ES cells to ventral neuronal progenitors. Taken together, our results demonstrate that primary vertebrate cells secrete Shh in distinct vesicular forms, and support a model where packaging of Shh along with other signaling proteins such as Integrins on exosomes modulates target gene activation. The existence of distinct classes of Shh-containing exosomes also suggests a previously unappreciated complexity for fine-tuning of Shh-mediated gradients and pattern formation.

}, keywords = {Animals, Chick Embryo, Exosomes, Extracellular Space, Hedgehog Proteins, HEK293 Cells, Humans, MicroRNAs, Models, Biological, Protein Transport, Signal Transduction, Vertebrates}, issn = {2045-2322}, doi = {10.1038/srep07357}, author = {Vyas, Neha and Walvekar, Ankita and Tate, Dhananjay and Lakshmanan, Vairavan and Bansal, Dhiru and Lo Cicero, Alessandra and Raposo, Graca and Palakodeti, Dasaradhi and Dhawan, Jyotsna} } @article {493, title = {Deep sequencing reveals unique small RNA repertoire that is regulated during head regeneration in Hydra magnipapillata. [Next Generation Genomics facility]}, journal = {Nucleic Acids Res}, volume = {41}, year = {2013}, month = {2013 Jan 07}, pages = {599-616}, abstract = {

Small non-coding RNAs such as miRNAs, piRNAs and endo-siRNAs fine-tune gene expression through post-transcriptional regulation, modulating important processes in development, differentiation, homeostasis and regeneration. Using deep sequencing, we have profiled small non-coding RNAs in Hydra magnipapillata and investigated changes in small RNA expression pattern during head regeneration. Our results reveal a unique repertoire of small RNAs in hydra. We have identified 126 miRNA loci; 123 of these miRNAs are unique to hydra. Less than 50\% are conserved across two different strains of Hydra vulgaris tested in this study, indicating a highly diverse nature of hydra miRNAs in contrast to bilaterian miRNAs. We also identified siRNAs derived from precursors with perfect stem-loop structure and that arise from inverted repeats. piRNAs were the most abundant small RNAs in hydra, mapping to transposable elements, the annotated transcriptome and unique non-coding regions on the genome. piRNAs that map to transposable elements and the annotated transcriptome display a ping-pong signature. Further, we have identified several miRNAs and piRNAs whose expression is regulated during hydra head regeneration. Our study defines different classes of small RNAs in this cnidarian model system, which may play a role in orchestrating gene expression essential for hydra regeneration.

}, keywords = {Animals, Gene Expression Regulation, Head, High-Throughput Nucleotide Sequencing, Hydra, MicroRNAs, Regeneration, RNA, Small Interfering, RNA, Small Untranslated, Sequence Analysis, RNA, Transcriptome}, issn = {1362-4962}, doi = {10.1093/nar/gks1020}, author = {Krishna, Srikar and Nair, Aparna and Cheedipudi, Sirisha and Poduval, Deepak and Dhawan, Jyotsna and Palakodeti, Dasaradhi and Ghanekar, Yashoda} }