Search

Abstract Objectives Development of sequencing technology has opened up vast opportunities for tree genomic research in the tropics. One of the aforesaid technologies named ONT (Oxford Nanopore Technology) has attracted researchers in undertaking testings and experiments due to its affordability and accessibility. To the best of our knowledge, there has been no published reports on the use of ONT for genomic analysis of Indonesian tree species. This progress is promising for further improvement in order to acquire more genomic data for research purposes. Therefore, the present study was carried out to determine the effectiveness of ONT in generating long-read DNA sequences using DNA isolated from leaves and wood cores of Macassar ebony (Diospyros celebica Bakh.). Data description Long-read sequences data of leaves and wood cores of Macassar ebony were generated by using the MinION device and MinKnow v3.6.5 (ONT). The obtained data, as the first long-read sequence dataset for Macassar ebony, is of great importance to conserve the genetic diversity, understanding the molecular mechanism, and sustainable use of plant genetic resources for downstream applications.

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.