Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.

Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs in vivo. Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.

Microarray data and gene expression statistics for Saccharomyces cerevisiae exposed to simulated asbestos mine drainage.

Here we describe microarray expression data (raw and normalized), experimental metadata, and gene-level data with expression statistics from Saccharomyces cerevisiae exposed to simulated asbestos mine drainage from the Vermont Asbestos Group (VAG) Mine on Belvidere Mountain in northern Vermont, USA. For nearly 100 years (between the late 1890s and 1993), chrysotile asbestos fibers were extracted from serpentinized ultramafic rock at the VAG Mine for use in construction and manufacturing industries. Studies have shown that water courses and streambeds nearby have become contaminated with asbestos mine tailings runoff, including elevated levels of magnesium, nickel, chromium, and arsenic, elevated pH, and chrysotile asbestos-laden mine tailings, due to leaching and gradual erosion of massive piles of mine waste covering approximately 9 km2. We exposed yeast to simulated VAG Mine tailings leachate to help gain insight on how eukaryotic cells exposed to VAG Mine drainage may respond in the mine environment. Affymetrix GeneChip® Yeast Genome 2.0 Arrays were utilized to assess gene expression after 24-h exposure to simulated VAG Mine tailings runoff. The chemistry of mine-tailings leachate, mine-tailings leachate plus yeast extract peptone dextrose media, and control yeast extract peptone dextrose media is also reported. To our knowledge this is the first dataset to assess global gene expression patterns in a eukaryotic model system simulating asbestos mine tailings runoff exposure. Raw and normalized gene expression data are accessible through the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) Database Series GSE89875 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89875).

BRUTUS and its paralogs, BTS LIKE1 and BTS LIKE2, encode important negative regulators of the iron deficiency response in Arabidopsis thaliana.

Iron (Fe) is required for plant health, but it can also be toxic when present in excess. Therefore, Fe levels must be tightly controlled. The Arabidopsis thaliana E3 ligase BRUTUS (BTS) is involved in the negative regulation of the Fe deficiency response and we show here that the two A. thaliana BTS paralogs, BTS LIKE1 (BTSL1) and BTS LIKE2 (BTSL2) encode proteins that act redundantly as negative regulators of the Fe deficiency response. Loss of both of these E3 ligases enhances tolerance to Fe deficiency. We further generated a triple mutant with loss of both BTS paralogs and a partial loss of BTS expression that exhibits even greater tolerance to Fe-deficient conditions and increased Fe accumulation without any resulting Fe toxicity effects. Finally, we identified a mutant carrying a novel missense mutation of BTS that exhibits an Fe deficiency response in the root when grown under both Fe-deficient and Fe-sufficient conditions, leading to Fe toxicity when plants are grown under Fe-sufficient conditions.