Amborella trichopoda
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA224129 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Amborella trichopoda Genome sequencing and assembly
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Project description:Amborella trichopoda Transcriptome or Gene expression
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Project description:Amborella trichopoda Transcriptome or Gene expression
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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 Amborella trichopoda leaves. The high depth of the resulting datasets enabled us to examine in detail critical small RNA features such 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 maize genome under study.
2011-04-30 | GSE28749 | GEO
Project description:Characterization of small RNAs and their targets in Amborella trichopoda
| PRJNA178223 | ENA
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 Amborella trichopoda leaves. The high depth of the resulting datasets enabled us to examine in detail critical small RNA features such 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 maize genome under study. A small RNA library was derived from leaves of Amborella trichopoda. The tissue represented a mixture of developmental stages, with a bias towards those from early, actively differentiating cells. Total RNA was isolated using the TriReagent (Molecular Research Center) 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 library was 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 Doug Soltis and André Chanderbali for providing the plant material, as well as Kan Nobuta and Gayathri Mahalingam for assistance with the computational methods.
2011-04-29 | E-GEOD-28749 | biostudies-arrayexpress
Project description:The small RNAs and their targets were characterized in Amborella genome by deep sequencing the small RNA populations of leaf tissue and opened-female flower tissue. The small RNA targets were also validated from degradome populations of leaf tissue and opened-female flower tissue.
2013-07-01 | GSE41811 | GEO
Project description:Amborella trichopoda isolate:Mont Aoupinie Raw sequence reads
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