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Cannabis sativa L., also known as hemp, cannabis, and marijuana, has been cultivated for over 10,000 years all over the world. It is one of the most versatile crops, serving as raw material for fabrics, paper, building materials, medicines, and food production. However, cannabis is historically surrounded by taboos and prejudice. This plant is considered a drug in most parts of the world due to the hallucinogenic properties of some of its secondary metabolites, (e.g. tetrahydrocannabinol, or THC). Nevertheless, only recently the scientific initiatives to study this species have started to accelerate, following a wave of legalization of cannabis cultivation in several countries, specially for medicinal uses. Following the sequencing of several cannabis genomes, we have witnessed the publication of several transcriptomic studies. Here, we performed an extensive literature mining process to gather as many as possible cannabis RNA-Seq datasets. Preliminary analyses were conducted with the R packages bears, dplyr, ggplot2, and stringr. In total, 582 raw read sequencing files were downloaded from the NCBI SRA database, being 91.75% paired-end and 8.25% single-end sequencing. This represents 35 BioProjects comprising 15 different tissue categories. Approximately 5.84% (34 of 582) of the samples lacked cultivar/genotype information. Among the other 548 samples, we found 44 different cannabis cultivar names. The cultivar Santhica 27, which a great potential as source of textile fiber and seed, represented approximately 35% (204 of 582) of the total samples, and the medicinal cultivar Cannbio-2, which a balanced CBD:THC cannabinoid ratio production, represented approximately 11% (64 of 582) of the samples. Hypocotyl was the most abundant tissue, representing approximately 24.7% (144 of 582) of the samples. Other two most abundant tissues are trichome (21.5% of the samples) and flower (15.6% of the samples), these tissues are the most important at cannabinoid production studies. The gathered data and associated information will be used for integrative studies in our lab, which hopefully will bring insights for future genetic and biotechnological applications.

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1	Kevelin Xavier(kevellynbarbosaxavier@gmail.com)
2	Thiago Venâncio(tmvenancio@uenf.br)

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1	Almeida-Silva, F. and Venancio, T. (2021). bears: Building Expression Atlas from RNA-Seq data. R package version 0.99.0., https://github.com/almeidasilvaf/bears, July. Gao, S., Wang, B., Xie, S., Xu, X., Zhang, J., Pei, L., ... & Zhang, Y. (2020). A high-quality reference genome of wild Cannabis sativa. Horticulture research, 7. Wickham, H., François, R., Henry, L. and Müller, K. (2022). dplyr: A Grammar of Data Manipulation. R package version 1.0.9., https://CRAN.R-project.org/package=dplyr, Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. https://ggplot2.tidyverse.org, July. Wickham, H. (2019). stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.4.0., https://CRAN.R-project.org/package=stringr, July. Hussain, T., Jeena, G., Pitakbut, T., Vasilev, N., & Kayser, O. (2021). Cannabis sativa research trends, challenges, and new-age perspectives. Iscience, 24(12), 103391.

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