Transcriptome Mining to Identify Genes of Interest: From Local Databases to Phylogenetic Inference

Abstract

The advancement in next-generation sequencing technologies and the dropping of sequencing costs have seen an increase in the amount of transcriptome data generated each year. These data are of big potential for identifying genes and molecular pathways of interest across a plethora of organisms. However, navigating these resources requires some bioinformatics and evolutionary skills. Here, we describe a protocol of transcriptome data mining for genes of interest, from the creation of a protein database to the inference of phylogenetic trees, which was used for marine protists, but can be used as general pipeline across different taxa.

Keywords: Bioinformatics; Biosynthetic pathways; Genes of interest; Local databases; Marine protists; Phylogenies; Sequence alignment; Transcriptome mining.