The use of Raman spectroscopy to differentiate between different prostatic adenocarcinoma cell lines

Raman spectroscopy (RS) is an optical technique that provides an objective method of pathological diagnosis based on the molecular composition of tissue. Studies have shown that the technique can accurately identify and grade prostatic adenocarcinoma (CaP) in vitro. This study aimed to determine whether RS was able to differentiate between CaP cell lines of varying degrees of biological aggressiveness. Raman spectra were measured from two well-differentiated, androgen-sensitive cell lines (LNCaP and PCa 2b) and two poorly differentiated, androgen-insensitive cell lines (DU145 and PC 3). Principal component analysis was used to study the molecular differences that exist between cell lines and, in conjunction with linear discriminant analysis, was applied to 200 spectra to construct a diagnostic algorithm capable of differentiating between the different cell lines. The algorithm was able to identify the cell line of each individual cell with an overall sensitivity of 98% and a specificity of 99%. The results further demonstrate the ability of RS to differentiate between CaP samples of varying biological aggressiveness. RS shows promise for application in the diagnosis and grading of CaP in clinical practise as well as providing molecular information on CaP samples in a research setting

BRIE: transcriptome-wide splicing quantication in single cells

Abstract Single-cell RNA-seq (scRNA-seq) provides a comprehensive measurement of stochasticity in transcription, but the limitations of the technology have prevented its application to dissect variability in RNA processing events such as splicing. Here, we present BRIE (Bayesian regression for isoform estimation), a Bayesian hierarchical model that resolves these problems by learning an informative prior distribution from sequence features. We show that BRIE yields reproducible estimates of exon inclusion ratios in single cells and provides an effective tool for differential isoform quantification between scRNA-seq data sets. BRIE, therefore, expands the scope of scRNA-seq experiments to probe the stochasticity of RNA processing

Systematic identification of factors involved in post-transcriptional processes in wheat grain

The original publication can be found at www.springerlink.comPost-transcriptional processing of primary transcripts can significantly affect both the quantity and the structure of mature mRNAs and the corresponding protein products. It is an important mechanism of gene regulation in animals, yeast and plants. Here we have investigated the interactive networks of pre-mRNA processing factors in the developing grain of wheat (Triticum aestivum), one of the world’s major food staples. As a first step we isolated a homologue of the plant specific AtRSZ33 splicing factor, which has been shown to be involved in the early stages of embryo development in Arabidopsis. Real-time PCR showed that the wheat gene, designated TaRSZ38, is expressed mainly in young, developing organs (flowers, root, stem), and expression peaks in immature grain. In situ hybridization and immunodetection revealed preferential abundance of TaRSZ38 in mitotically active tissues of the major storage organ of the grain, the endosperm. The protein encoded by TaRSZ38 was subsequently used as a starting bait in a two-hybrid screen to identify additional factors in grain that are involved in pre-mRNA processing. Most of the identified proteins showed high homology to known splicing factors and splicing related proteins, supporting a role for TaRSZ38 in spliceosome formation and 5′ site selection. Several clones were selected as baits in further yeast two-hybrid screens. In total, cDNAs for 16 proteins were isolated. Among these proteins, TaRSZ22, TaSRp30, TaU1-70K, and the large and small subunits of TaU2AF, are wheat homologues of known plant splicing factors. Several, additional proteins are novel for plants and show homology to known pre-mRNA splicing, splicing related and mRNA export factors from yeast and mammals.Sergiy Lopato, Ljudmilla Borisjuk, Andrew S. Milligan, Neil Shirley, Natalia Bazanova and Peter Langridg