De novo assembly of transcriptome dataset from leaves of Dryobalanops aromatica (Syn. Dryobalanops sumatrensis) seedlings grown in two contrasting potting media

Abstract

Objectives: Efforts to restore tropical peat swamp forests in Indonesia face huge challenges of potential failures due to socio-economic factors and ecological dynamics attributed to lack of knowledge on the adaptive mechanisms of potential tree species such as Kapur (Dryobalanops aromatica C.F.Gaertn Syn. Dryobalanops sumatrensis J.F. Gmelin A.J.G.H Kostermans). This species is a multi-purpose tree that, commonly grows in mineral soils, but also in peat swamp as previously reported, which raised a fundamental question regarding the molecular mechanism of this adaptation. Therefore, a dataset was created aiming to detect candidates of adaptive genes in D. aromatica seedlings, cultivated in two contrasting potting media, namely mineral soil and peat media, based on RNA Sequencing Transcriptome Analysis. Data description: The RNA transcriptome data of D. aromatica's seedlings derived from young leaves of three one-year-old seedlings, raised in each dry mineral soil media and peat media, were generated by using Illumina HiSeq 4000 platform in NovogenAIT, Singapore. The acquired data, as the first transcriptome dataset for D. aromatica, is of a great importance in understanding molecular mechanism and responses of the involved genes of D. aromatica to the contrasting, growing potting media conditions that could also be useful to generate molecular markers.