Transcriptome-wide comparison of stress granules and P-bodies reveals that translation plays a major role in RNA partitioning

The eukaryotic cytosol contains multiple RNP granules including P-bodies and stress granules. Three different methods have been used to describe the transcriptome of stress granules or P-bodies, but how these methods compare, and how RNA partitioning occurs between P-bodies and stress granules has not been addressed. Herein, we compare the analysis of the stress granule transcriptome based on differential centrifugation, with and without subsequent stress granule immunopurification. We find that while differential centrifugation alone gives a first approximation of the stress granule transcriptome, this methodology contains non-specific transcripts that play a confounding role in the interpretation of results. We also immunopurify and compare the RNAs in stress granules and P-bodies under arsenite stress and compare those results to the P-body transcriptome described under non-stress conditions. We find that the P-body transcriptome is dominated by poorly translated mRNAs under non-stress conditions, but during arsenite stress, when translation is globally repressed, the P-body transcriptome is very similar to the stress granule transcriptome. This suggests that translation is a dominant factor in targeting mRNAs into both P-bodies and stress granules, and during stress, when most mRNAs are untranslated, the composition of P- bodies reflects this broader translation repression. Overall design: Pellet and cyotplasmic RNA were obtained from U-2 OS cells during arsenite stress and unsetressed conditions. Biological triplicates were obtained for each sample. Paired-end libraries were prepared for these samples. We also sequenced the RNAs from P-bodies during arsenite stress conditions in both WT and G3BP ko U-2 OS cells. This was achieved by adapting a previously reported stress granule purification protocol, using an anti-EDC3 antibody(Khong et al. 2017). Biological triplicates were obtained for each sample. Single-end libraries were prepared for these samples.