Project description:Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven to be analytically challenging and prone to error. Here we report a novel method termed LEAP-RBP for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce new strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. The utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.
Project description:Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven analytically challenging and prone to error. Here we report a method termed LEAP-RBP (Liquid-Emulsion-Assisted-Purification of RNA-Bound Protein) for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. In this work, the utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.
Project description:To minimize the distortion of genetic signal by system noise, we have explored the latter in an archive of hybridizations in which no genetic signal is expected. This archive is obtained by comparative genomic hybridization (CGH) of a reference sample in one channel to the same sample in the other channel, which we have termed ‘self-self’ data. We show that these self-self hybridizations trap a variety of system noise inherent in sample-reference (test) data. Through singular value decomposition (SVD) of self-self data, we are able to determine the principal components of system noise. Assuming simple linear models of noise generation, we present evidence that the linear correction of test data with self-self data—which we call system normalization—reduces local and long-range correlations as well as improves signal-to-noise metrics, yet does not introduce detectable spurious signal.
Project description:The molecular mechanisms underlying the great differences in susceptibility to noise-induced hearing loss (NIHL) exhibited by both humans and laboratory animals are unknown. Using microarray technology, the present study demonstrates that the effects of noise overexposure on the expression of molecules likely to be important to the development of NIHL differ among inbred mice that have distinctive susceptibilities to NIHL including B6.CAST, 129X1/SvJ, and 129S1/SvImJ. The noise-exposure protocol produced, on average, a permanent loss of about 40 dB in sensitivity for auditory brainstem responses in susceptible B6.CAST mice, but no threshold elevations for the two resistant 129S1/SvImJ and 129X1/SvJ substrains. Measurements of noise-induced gene expression changes 6 h after the noise exposure revealed significant alterations in the expression levels of 48 genes in the resistant mice, while by these same criteria, there were seven differentially expressed genes in the susceptible B6.CAST mice. Differentially expressed genes in both groups of mice included subsets of transcription factors. However, only in the resistant mice was there a significant induction of proteins involved in cell-survival pathways such as HSP70, HSP40, p21, GADD45ï¢, Ier3, and Nfï«ï¢iïº. Moreover, increased expression of three of these factors after noise was confirmed at the protein level. Drastically enhanced HSP70, GADD45ï¢, and p21 immunostaining were detected 6 h after the noise exposure in subsets of cells of the lateral wall, spiral limbus, and organ of Corti as well as in cochlear nerve fibers. Upregulation of these proteins after noise exposure likely contributes to the prevalence of survival cellular pathways and thus to the resistance to NIHL that is characteristic of the 129X1/SvJ mice. Experiment Overall Design: Female 10-wk-old mice of the B6.CAST and 129X1/SvJ strains were divided randomly into non-noise control and noise-exposure groups. The non-noise mice served as controls in the gene-profiling experiments to control for the stress induced by experimenter handling and/or confinement of the mice in the noise-exposure chamber that was not directly related to the noise. This mice were in the noise chamber for a sham exposure. In contrast, the ânoiseâ groups were exposed to a 105-dB SPL, 10-kHz octave band of noise for 1 h and sacrificed 6 h after the exposure. Of each of these major groups, eight mice were used for each of three 129X1/SvJ control and three noise-exposed 129X1/SvJ arrays and two B6.CAST control and two noise-exposed B6.CAST arrays. Consequently within each subgroup the arrays are biological replicates.
Project description:Intrinsic biological fluctuation and/or measurement error can obscure the association of gene expression patterns between RNA and protein levels. Appropriate normalisation of reverse-transcription quantitative PCR (RT-qPCR) data can reduce technical noise in transcript measurement, thus uncovering such relationships. The accuracy of gene expression measurement is often challenged in the context of cancer due to its genetic instability and ‘splicing weakness’. Here we sequenced the poly(A) cancer transcriptome of canine osteosarcoma using mRNA-Seq. Expressed sequences were resolved at the level of two consecutive exons to enable the design of exon-border spanning RT-qPCR assays and ranked for stability based on the coefficient of variation (CV). Using the same template type for RT-qPCR validation, i.e. poly(A) RNA, avoided skewing of stability assessment by circular RNAs (circRNAs) and/or rRNA deregulation. The strength of the relationship between mRNA expression of the tumour marker S100A4 and its proportion score of quantitative immunochemistry (qIHC) was introduced as an experimental read-out to fine-tune the normalisation choice. Together with the essential logit transformation of qIHC scores, this approach reduced the noise of measurement as demonstrated by uncovering a highly significant, strong association between mRNA and protein expressions of S100A4 (Spearman's coefficient r = 0.72 (p = 0.006)).
Project description:Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data. We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.. Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with TPM > 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples. We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.
Project description:The molecular mechanisms underlying the great differences in susceptibility to noise-induced hearing loss (NIHL) exhibited by both humans and laboratory animals are unknown. Using microarray technology, the present study demonstrates that the effects of noise overexposure on the expression of molecules likely to be important to the development of NIHL differ among inbred mice that have distinctive susceptibilities to NIHL including B6.CAST, 129X1/SvJ, and 129S1/SvImJ. The noise-exposure protocol produced, on average, a permanent loss of about 40 dB in sensitivity for auditory brainstem responses in susceptible B6.CAST mice, but no threshold elevations for the two resistant 129S1/SvImJ and 129X1/SvJ substrains. Measurements of noise-induced gene expression changes 6 h after the noise exposure revealed significant alterations in the expression levels of 48 genes in the resistant mice, while by these same criteria, there were seven differentially expressed genes in the susceptible B6.CAST mice. Differentially expressed genes in both groups of mice included subsets of transcription factors. However, only in the resistant mice was there a significant induction of proteins involved in cell-survival pathways such as HSP70, HSP40, p21, GADD45beta, Ier3, and Nf-kappaB. Moreover, increased expression of three of these factors after noise was confirmed at the protein level. Drastically enhanced HSP70, GADD45beta, and p21 immunostaining were detected 6 h after the noise exposure in subsets of cells of the lateral wall, spiral limbus, and organ of Corti as well as in cochlear nerve fibers. Upregulation of these proteins after noise exposure likely contributes to the prevalence of survival cellular pathways and thus to the resistance to NIHL that is characteristic of the 129X1/SvJ mice. Keywords: effects of noise exposure in distinct inbred mice