Abstract: Space is an exciting frontier, but it presents unique environmental stressors like microgravity and space radiation. It is difficult to study the impact of spaceflight on terrestrial life due to the limited resources of the International Space Station (ISS). NASA created Genelab, a public Omics database for spaceflight relevant data, to give scientists access to data without needing a new experiment on the ISS. Transcription profiles are among the most common data type available on Genelab, and in the age of Next Generation Sequencing this commonly means RNA-Sequencing data. A developed pipeline that could find new information out of the public RNA-Seq data would be useful, especially in a case like this where the available data is extremely limited. This study aims to develop and use a pipeline analyzing Genelab’s RNA-Sequencing data from Arabidopsis thaliana for sequence variants. The hypothesis is that space’s environment will cause more variants to be called in the spaceflight A. thaliana samples than those in the ground control. RNA-Sequencing data is not the preferred method to call variants due an associated high false discovery rate, however recent studies show it can be done with appropriate precautions. The pipeline incorporates steps to combat factors leading to RNA Seq’s high false variant discovery rate including 2-pass mapping methods and stringent filters. Preliminary results show A. thaliana samples from space tend to have higher variant counts than those from the ground. The development of this pipeline would demonstrate RNA-Seq can be analyzed beyond gene expression to see the impact of abiotic stressors like microgravity and space radiation. Further, if the results continue trending towards spaceflight A. thaliana having a higher number of variants then this will show the damage spaceflight can have at the nucleotide level. This may lead to a better understanding of what future precautions may need to be taken for the better safety of those in space.