Dataset of natural antisense transcripts in P. vivax clinical isolates derived using custom designed strand-specific microarray
| Autor: | Parmendra Sirohi, Deepak Pakalapati, Raja C. Mugasimangalam, Mohammed Aiyaz, Ashis Das, Sanjay K. Kochar, Dhanpat K. Kochar, P.A. Boopathi, Amit Kumar Subudhi, Bipin Chand, Jyoti Acharya, Shilpi Garg, Vishal Saxena, Sheetal Middha |
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| Rok vydání: | 2014 |
| Předmět: |
Genetics
Natural antisense transcripts lcsh:QH426-470 biology Microarray Microarray analysis techniques Plasmodium vivax Uncomplicated malaria Complicated malaria Plasmodium falciparum biology.organism_classification Strand specific microarray Biochemistry Genome Gene expression profiling lcsh:Genetics Data in Brief parasitic diseases Gene expression Sense (molecular biology) Molecular Medicine Biotechnology |
| Zdroj: | Genomics Data Genomics Data, Vol 2, Iss C, Pp 199-201 (2014) |
| ISSN: | 2213-5960 |
| DOI: | 10.1016/j.gdata.2014.06.024 |
| Popis: | Natural antisense transcripts (NATs) have been detected in many organisms and shown to regulate gene expression. Similarly, NATs have also been observed in malaria parasites with most studies focused on Plasmodium falciparum. There were no reports on the presence of NATs in Plasmodium vivax, which has also been shown to cause severe malaria like P. falciparum, until a recent study published by us. To identify in vivo prevalence of antisense transcripts in P. vivax clinical isolates, we performed whole genome expression profiling using a custom designed strand-specific microarray that contains probes for both sense and antisense strands. Here we describe the experimental methods and analysis of the microarray data available in Gene Expression Omnibus (GEO) under GSE45165. Our data provides a resource for exploring the presence of antisense transcripts in P. vivax isolated from patients showing varying clinical symptoms. Related information about the description and interpretation of the data can be found in a recent publication by Boopathi and colleagues in Infection, Genetics and Evolution 2013. |
| Databáze: | OpenAIRE |
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