Determining sufficient sequencing depth in RNA-Seq differential expression studies, bioRxiv, 2019-05-13

AbstractRNA-Seq studies require a sufficient read depth to detect biologically important genes. Sequencing below this threshold will reduce statistical power while sequencing above will provide only marginal improvements in power and incur unnecessary sequencing costs. Although existing methodologies can help assess whether there is sufficient read depth, they are unable to guide how many additional reads should be sequenced to reach this threshold. We provide a new method called superSeq that models the relationship between statistical power and read depth. We apply the superSeq framework to 393 RNA-Seq experiments (1,021 total contrasts) in the Expression Atlas and find the model accurately predicts the increase in statistical power gained by increasing the read depth. Based on our analysis, we find that most published studies (> 70%) are undersequenced, i.e., their statistical power can be improved by increasing the sequencing read depth. In addition, the extent of saturation is highly dependent on statistical methodology only 9.5%, 29.5%, and 26.6% of contrasts are saturated when using DESeq2, edgeR, and limma, respectively. Finally, we also find that there is no clear minimum per-transcript read depth to guarantee saturation for an entire technology. Therefore, our framework not only delineates key differences among methods and their impact on determining saturation, but will also be needed even as technology improves and the read depth of experiments increases. Researchers can thus use superSeq to calculate the read depth to achieve required statistical power while avoiding unnecessary sequencing costs.

biorxiv genomics 100-200-users 2019

Stress-driven transposable element de-repression dynamics in a fungal pathogen, bioRxiv, 2019-05-10

AbstractTransposable elements (TEs) are drivers of genome evolution and affect the expression landscape of the host genome. Stress is a major factor inducing TE activity, however the regulatory mechanisms underlying de-repression are poorly understood. Key unresolved questions are whether different types of stress differentially induce TE activity and whether different TEs respond differently to the same stress. Plant pathogens are excellent models to dissect the impact of stress on TEs, because lifestyle transitions on and off the host impose exposure to a variety of stress conditions. We analyzed the TE expression landscape of four well-characterized strains of the major wheat pathogen Zymoseptoria tritici. We experimentally exposed strains to nutrient starvation and host infection stress. Contrary to expectations, we show that the two distinct conditions induce the expression of different sets of TEs. In particular, the most highly expressed TEs, including MITE and LTR-Gypsy elements, show highly distinct de-repression across stress conditions. Both the genomic context of TEs and the genetic background stress (i.e. different strains harboring the same TEs) were major predictors of de-repression dynamics under stress. Genomic defenses inducing point mutations in repetitive regions were largely ineffective to prevent TE de-repression. Consistent with TE de-repression being governed by epigenetic effects, we found that gene expression profiles under stress varied significantly depending on the proximity to the closest TEs. The unexpected complexity in TE responsiveness to stress across genetic backgrounds and genomic locations shows that species harbor substantial genetic variation to control TEs.

biorxiv genomics 0-100-users 2019

 

Created with the audiences framework by Jedidiah Carlson

Powered by Hugo