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Assumpcao, P. P.

Publications and source records attributed to Assumpcao, P. P..

2 recordsLinked to original sources

Characterization and analysis of the transcriptome in Arapaima gigas using multi-tissue RNA-sequencing

Arapaima gigas is a giant bony tongue air-breathing fish, and a promising species for aquaculture due to its particular features. However, there is still a lack of information on its biology and few transcriptome studies are available. Our aim was to characterize the transcriptome of arapaima in order to shed light on molecular networks contributing to its unique traits. Through RNA-sequencing, we generated a transcriptome from eight tissues (brain, pituitary, heart, muscle, kidney, lung, ovary, and testis) collected from arapaima adults specimens. Using a genome-guided strategy associated with homologous protein evidence, 57,706 transcripts were assembled, which aligned to 23,353 high confidence protein-coding genes. The analysis revealed a global view of expression patterns, as well as it allowed us to identify tissue-specific gene clusters, transcription factors within the clusters, and to compare expression patterns between male and female. These analyses has generated tissue-specific and sex-biased transcriptome profiles, which will be helpful to understand its molecular biology, evolution, and also guide future functional studies of the arapaima.

genomics

A small interfering RNA (siRNA) database for SARS-CoV-2

Coronavirus disease 2019 (COVID-19) rapidly transformed into a global pandemic, for which a demand for developing antivirals capable of targeting the SARS-CoV-2 RNA genome and blocking the activity of its genes has emerged. In this work, we propose a database of SARS-CoV-2 targets for siRNA approaches, aiming to speed the design process by providing a broad set of possible targets and siRNA sequences. Beyond target sequences, it also displays more than 170 features, including thermodynamic information, base context, target genes and alignment information of sequences against the human genome, and diverse SARS-CoV-2 strains, to assess whether siRNAs targets bind or not off-target sequences. This dataset is available as a set of four tables in a single spreadsheet file, each table corresponding to sequences of 18, 19, 20, and 21 nucleotides length, respectively, aiming to meet the diversity of technology and expertise among labs around the world concerning siRNAs design of varied sizes, more specifically between 18 and 21nt length. We hope that this database helps to speed the development of new target antivirals for SARS-CoV-2, contributing to more rapid and effective responses to the COVID-19 pandemic.

bioinformatics