E-MTAB-4400
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ABSTRACT:
PROVIDER: E-MTAB-4400 | ExpressionAtlas | 2016-10-17
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:This study utilized next generation sequencing technology (RNA-Seq and BS-Seq) to examine the transcriptome and methylome of various tissues within sorghum plants with the ultimate goal of improving the Sorghum bicolor annotation We examined the mRNA of various Sorghum bicolor (BTx623) tissues (flowers, vegitative and floral meristems, embryos, roots and shoots) and bisulfite treated DNA from two root samples
2014-08-29 | E-GEOD-50464 | biostudies-arrayexpress
Project description:This study utilized next generation sequencing technology (RNA-Seq and BS-Seq) to examine the transcriptome and methylome of various tissues within sorghum plants with the ultimate goal of improving the Sorghum bicolor annotation
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Project description:This study used with RNA-Seq to examine the tissue specific expression data within sorghum plants for improving the Sorghum bicolor gene annotation. We examined the RNA from tissues (spikelet, seed and stem) in Sorghum bicolor (BTx623).Total RNAs form each tissues were extracted using SDS/phenol method followed by LiCl purification
2015-03-11 | E-MTAB-4273 | biostudies-arrayexpress
Project description:We developed a commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) and generated this dataset to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (corn and sugarcane) were also included in our array design. 78 samples were analyzed from four different tissue types (shoot, seedling, leaves and stem), two dissected stem tissues (pith and rind) and six diverse genotypes (PI455230, Atlas, PI152611, AR2400, R159, and Fremont)
2013-12-31 | E-GEOD-49879 | biostudies-arrayexpress
Project description:The present study is expected to reveal regulatory network of small RNAs under drought in Sorghum (Sorghum bicolor (L.) Moench). Sorghum genotype drought tolerant (DT) and drought susceptible (DS) were grown at 28-32 degrees C day/night temperature with 12/12 h light/dark period in the phytotron glass house. The fully opened uppermost leaves from control and drought stressed seedlings were sampled and stored at -80 degrees C, and used for generation of a small RNA library. Total RNA was isolated from the leaves using the TRIzol reagent (Invitrogen, USA). Small RNA sequencing libraries were prepared using Illumina Truseq small RNA Library preparation kit following manufacturer's protocol and these libraries were sequenced on GAIIx platform (Illumina Inc., USA). Small RNA reads contaminated with poor-quality and adaptor sequences were trimmed by using the UEA sRNA workbench 2.4- Plant version sequence file pre-processing (http://srna-tools.cmp.uea.ac.uk/). Then, all unique reads were submitted to the UEA sRNA toolkit-Plant version miRCat pipeline (http://srna-tools.cmp.uea.ac.uk/) to predict novel miRNAs from high-throughput small RNA sequencing data.
2014-04-15 | E-MTAB-1630 | biostudies-arrayexpress
Project description:Sorghum (Sorghum bicolor) is the fifth most important cereal crop in the world. It is an annual C4 crop having a high biomass, used widely, and has a strong resistance to stress. Obviously, there are many benefits of planting sorghum on marginal soils such as saline-alkali land.
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Project description:This experiment contains the subset of data corresponding to sorghum RNA-Seq data from experiment E-GEOD-50464 (http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-50464/), which goal is to examine the transcriptome of various Sorghum bicolor (BTx623) tissues: flowers, vegetative and floral meristems, embryos, roots and shoots. Thus, we expanded the existing transcriptome atlas for sorghum by conducting RNA-Seq analysis on meristematic tissues, florets, and embryos, and these data sets have been used to improve on the existing community structural annotations.
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2020-05-19 | GSE150798 | GEO
Project description:Small RNAs (21-24 nt) are pivotal regulators of gene expression that guide both transcriptional and post-transcriptional silencing mechanisms in diverse eukaryotes, including most if not all plants. MicroRNAs (miRNAs) and short interfering RNAs (siRNAs) are the two major types, both of which have a demonstrated and important role in plant development, stress responses and pathogen resistance. In this work, we used a deep sequencing approach (Sequencing-By-Synthesis, or SBS) to develop sequence resources of small RNAs from Sorghum bicolor tissues (including leaves, flowers and panicle). The high depth of the resulting datasets enabled us to examine in detail critical small RNA features as size distribution, tissue-specific regulation and sequence conservation between different organs in this species. We also developed database resources and a dedicated website (http://smallrna.udel.edu/) with computational tools for allowing other users to identify new miRNAs or siRNAs involved in specific regulatory pathways, verify the degree of conservation of these sequences in other plant species and map small RNAs on genes or larger regions of the genome under study. Small RNA libraries were derived from leaves, flowers and panicle of Sorghum bicolor. Total RNA was isolated using the Plant RNA Purification Reagent (Invitrogen), and submitted to Illumina (Hayward, CA, http://www.illumina.com) for small RNA library construction using approaches described in (Lu et al., 2007) with minor modifications. The small RNA libraries were sequenced with the Sequencing-By-Synthesis (SBS) technology by Illumina. PERL scripts were designed to remove the adapter sequences and determine the abundance of each distinct small RNA. We thank Patricia Klein for providing the plant material as well as Kan Nobuta and Gayathri Mahalingam for assistance with the computational methods.
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