Graphical abstract A proposed model illustrating the therapeutic effect of QCT on AKI. QCT inhibits the expression of ATF3. While ATF3 blocks the system Xc-, and then suppresses GPX4, inducing ferroptosis. In another side, ferroptotic cells secrete chemokines like CCL2, CCL7, induce the recruitment of macrophages, and then cause the inflammation in AKI. In summary, QCT ameliorates AKI through the inhibition on ferroptosis and the following inflammation.

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SummaryHere we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses.

BackgroundRNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression analysis. In addition, false discovery rate (FDR), instead of family-wise type I error rate, is controlled for the multiple testing error in RNA-seq data analysis. So far, there are very few proposals on sample size calculation for RNA-seq experiments.ResultsIn this paper, we propose a procedure for sample size calculation while controlling FDR for RNA-seq experimental design. Our procedure is based on the weighted linear model analysis facilitated by the voom method which has been shown to have competitive performance in terms of power and FDR control for RNA-seq differential expression analysis. We derive a method that approximates the average power across the differentially expressed genes, and then calculate the sample size to achieve a desired average power while controlling FDR. Simulation results demonstrate that the actual power of several popularly applied tests for differential expression is achieved and is close to the desired power for RNA-seq data with sample size calculated based on our method.ConclusionsOur proposed method provides an efficient algorithm to calculate sample size while controlling FDR for RNA-seq experimental design. We also provide an R package ssizeRNA that implements our proposed method and can be downloaded from the Comprehensive R Archive Network (http://cran.r-project.org).Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0994-9) contains supplementary material, which is available to authorized users.

The unfolded protein response (UPR) is a highly conserved response that protects plants from adverse environmental conditions. The UPR is elicited by endoplasmic reticulum (ER) stress, in which unfolded and misfolded proteins accumulate within the ER. Here, we induced the UPR in maize () seedlings to characterize the molecular events that occur over time during persistent ER stress. We found that a multiphasic program of gene expression was interwoven among other cellular events, including the induction of autophagy. One of the earliest phases involved the degradation by regulated IRE1-dependent RNA degradation (RIDD) of RNA transcripts derived from a family of peroxidase genes. RIDD resulted from the activation of the promiscuous ribonuclease activity of ZmIRE1 that attacks the mRNAs of secreted proteins. This was followed by an upsurge in expression of the canonical UPR genes indirectly driven by ZmIRE1 due to its splicing of mRNA to make an active transcription factor that directly upregulates many of the UPR genes. At the peak of UPR gene expression, a global wave of RNA processing led to the production of many aberrant UPR gene transcripts, likely tempering the ER stress response. During later stages of ER stress, ZmIRE1's activity declined, as did the expression of survival modulating genes, and , amid a rising tide of cell death. Thus, in response to persistent ER stress, maize seedlings embark on a course of gene expression and cellular events progressing from adaptive responses to cell death.

Leprosy is a chronic infectious and neurological disease that is caused by infection of Mycobacterium leprae (M. leprae). A recent genome-wide association study indicated a suggestive association of LRRK2 genetic variant rs1873613 with leprosy in Chinese population. To validate this association and further identify potential causal variants of LRRK2 with leprosy, we genotyped 13 LRRK2 variants in 548 leprosy patients and 1078 healthy individuals from Yunnan Province and (re-)analyzed 3225 Han Chinese across China. Variants rs1427267, rs3761863, rs1873613, rs732374 and rs7298930 were significantly associated with leprosy per se and/or paucibacillary leprosy (PB). Haplotype A-G-A-C-A was significantly associated with leprosy per se (P=0.018) and PB (P=0.020). Overexpression of the protective allele (Thr2397) of rs3761863 in HEK293 cells led to a significantly increased nuclear factor of activated T-cells' activity compared with allele Met2397 after lipopolysaccharides stimulation. Allele Thr2397 could attenuate 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine-induced autophagic activity in U251 cells. These data suggest that the protective effect of LRRK2 variant p.M2397T on leprosy might be mediated by increasing immune response and decreasing neurotoxicity after M. leprae loading. Our findings confirm that LRRK2 is a susceptible gene to leprosy in Han Chinese population.

Retinal ganglion cells can be classified into more than 40 distinct subtypes, whether by functional classification or transcriptomics. The examination of these subtypes in relation to their physiology, projection patterns, and circuitry would be greatly facilitated through the identification of specific molecular identifiers for the generation of transgenic mice. Advances in single cell transcriptomic profiling have enabled the identification of molecular signatures for cellular subtypes that are only rarely found. Therefore, we used single cell profiling combined with hierarchical clustering and correlate analyses to identify genes expressed in distinct populations of Parvalbumin-expressing cells and functionally classified RGCs. RGCs were manually isolated based either upon fluorescence or physiological distinction through cell-attached recordings. Microarray hybridization and RNA-Sequencing were employed for the characterization of transcriptomes and in situ hybridization was utilized to further characterize gene candidate expression. Gene candidates were identified based upon cluster correlation, as well as expression specificity within physiologically distinct classes of RGCs. Further, we identified Prph, Ctxn3, and Prkcq as potential candidates for ipRGC classification in the murine retina. The use of these genes, or one of the other newly identified subset markers, for the generation of a transgenic mouse would enable future studies of RGC-subtype specific function, wiring, and projection.