Bar, H. | Search bioRxiv

bioRxiv2021

ABA homeostasis and long-distance translocation is redundantly regulated by ABCG ABA importers

The effects of abscisic acid (ABA) on plant growth, development and response to the environment depend on local ABA concentrations. Here, we exploited a genome-scale amiRNA screen, targeting the Arabidopsis transportome, to show that ABA homeostasis is regulated by two previously unknown ABA transporters. ABCG17 and ABCG18 are localized to the plasma membranes of leaf mesophyll and stem cortex cells to redundantly promote ABA import, leading to conjugated inactive ABA sinks, thus restricting stomatal closure. ABCG17 and ABCG18 double knockdown revealed that the transporters encoded by these genes not only limit stomatal aperture size, conductance and transpiration while increasing water-use efficiency but also control ABA translocation from the shoot to the root to regulate lateral root emergence. The proposed ABCG17- and ABCG18-dependent ABA glucosyl ester shoot sink mechanism is restrained under abiotic stress conditions to further activate the ABA responses.

plant biology↗

bioRxiv2018

Differential variation and expression analysis

We propose an empirical Bayes approach using a three-component mixture model, the L2N model, that may be applied to detect both differential expression (mean) and variation. It consists of two log-normal components (L2) for the differentially expressed (dispersed) features (one component for under-expressed [dispersed] and the other for over-expressed [dispersed] features), and a single normal component (N) for the null features (i.e., non-differentially expressed [dispersed] features). Simulation results show that L2N can capture asymmetries in the numbers of over-and under-expressed (dispersed) features (e.g., genes) when they exist, can provide a better fit to data in which the distributions of the null and non-null features are not well-separated, but can also perform well under symmetry and separation. Thus the L2N model is particularly appealing when no a priori biological knowledge about the mixture density is available. The L2N model is implemented in an R package called DVX, for Differential Variation and eXpression analysis. The package also includes an implementation of differential expression analysis via the limma package, and a differential variation and expression analysis using a three-way normal mixture model. DVX is a user-friendly, graphical interface implemented via the Shiny package [6], so that a user is not required to have R programming knowledge. It offers a set of diagnostics plots, data transformation tools, and report generation in Microsoft Excel- and Word-compatible formats. The package is available on the web, at https://haim-bar.uconn.edu/software/DVX/.

bioinformatics↗