Dataset Information

Metatranscriptomic analysis of small RNAs present in soybean deep sequencing libraries.

ABSTRACT: A large number of small RNAs unrelated to the soybean genome were identified after deep sequencing of soybean small RNA libraries. A metatranscriptomic analysis was carried out to identify the origin of these sequences. Comparative analyses of small interference RNAs (siRNAs) present in samples collected in open areas corresponding to soybean field plantations and samples from soybean cultivated in greenhouses under a controlled environment were made. Different pathogenic, symbiotic and free-living organisms were identified from samples of both growth systems. They included viruses, bacteria and different groups of fungi. This approach can be useful not only to identify potentially unknown pathogens and pests, but also to understand the relations that soybean plants establish with microorganisms that may affect, directly or indirectly, plant health and crop production.

SUBMITTER: Molina LG

PROVIDER: S-EPMC3392881 | biostudies-other | 2012 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Metatranscriptomic analysis of small RNAs present in soybean deep sequencing libraries.

Molina Lorrayne Gomes LG da Fonseca Guilherme Cordenonsi GC de Morais Guilherme Loss GL de Oliveira Luiz Felipe Valter LF de Carvalho Joseane Biso JB Kulcheski Franceli Rodrigues FR Margis Rogerio R

Genetics and molecular biology 20120601 1 (suppl)

A large number of small RNAs unrelated to the soybean genome were identified after deep sequencing of soybean small RNA libraries. A metatranscriptomic analysis was carried out to identify the origin of these sequences. Comparative analyses of small interference RNAs (siRNAs) present in samples collected in open areas corresponding to soybean field plantations and samples from soybean cultivated in greenhouses under a controlled environment were made. Different pathogenic, symbiotic and free-liv ...[more]

PMID: 22802714

Similar Datasets

Project description:BACKGROUND: MicroRNAs are a class of small non-coding RNAs that regulate mRNA expression at the post - transcriptional level and thereby many fundamental biological processes. A number of methods, such as multiplex polymerase chain reaction, microarrays have been developed for profiling levels of known miRNAs. These methods lack the ability to identify novel miRNAs and accurately determine expression at a range of concentrations. Deep or massively parallel sequencing methods are providing suitable platforms for genome wide transcriptome analysis and have the ability to identify novel transcripts. RESULTS: The results of analysis of small RNA sequences obtained by Solexa technology of normal peripheral blood mononuclear cells, tumor cell lines K562 and HL60 are presented. In general K562 cells displayed overall low level of miRNA population and also low levels of DICER. Some of the highly expressed miRNAs in the leukocytes include several members of the let-7 family, miR-21, 103, 185, 191 and 320a. Comparison of the miRNA profiles of normal versus K562 or HL60 cells revealed a specific set of differentially expressed molecules. Correlation of the miRNA with that of mRNA expression profiles, obtained by microarray, revealed a set of target genes showing inverse correlation with miRNA levels. Relative expression levels of individual miRNAs belonging to a cluster were found to be highly variable. Our computational pipeline also predicted a number of novel miRNAs. Some of the predictions were validated by Real-time RT-PCR and or RNase protection assay. Organization of some of the novel miRNAs in human genome suggests that these may also be part of existing clusters or form new clusters. CONCLUSIONS: We conclude that about 904 miRNAs are expressed in human leukocytes. Out of these 370 are novel miRNAs. We have identified miRNAs that are differentially regulated in normal PBMC with respect to cancer cells, K562 and HL60. Our results suggest that post - transcriptional processes may play a significant role in regulating levels of miRNAs in tumor cells. The study also provides a customized automated computation pipeline for miRNA profiling and identification of novel miRNAs; even those that are missed out by other existing pipelines. The Computational Pipeline is available at the website: http://mirna.jnu.ac.in/deep_sequencing/deep_sequencing.html.

Dataset Information

Metatranscriptomic analysis of small RNAs present in soybean deep sequencing libraries.

Publications

Metatranscriptomic analysis of small RNAs present in soybean deep sequencing libraries.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets