piRNA-mediated regulation of transposon alternative splicing in the soma and germ line

Transposable elements can drive genome evolution, but their enhanced activity is detrimental to the host and therefore must be tightly regulated1. The Piwi-interacting small RNA (piRNA) pathway is vital for the regulation of transposable elements, by inducing transcriptional silencing or post-transcriptional decay of mRNAs2. Here we show that piRNAs and piRNA biogenesis components regulate precursor mRNA splicing of P-transposable element transcripts in vivo, leading to the production of the non-transposase-encoding mature mRNA isoform in Drosophila germ cells. Unexpectedly, we show that the piRNA pathway components do not act to reduce transcript levels of the P-element transposon during P–M hybrid dysgenesis, a syndrome that affects germline development in Drosophila3,4. Instead, splicing regulation is mechanistically achieved together with piRNA-mediated changes to repressive chromatin states, and relies on the function of the Piwi–piRNA complex proteins Asterix (also known as Gtsf1)5,6,7 and Panoramix (Silencio)8,9, as well as Heterochromatin protein 1a (HP1a; encoded by Su(var)205). Furthermore, we show that this machinery, together with the piRNA Flamenco cluster10, not only controls the accumulation of Gypsy retrotransposon transcripts11 but also regulates the splicing of Gypsy mRNAs in cultured ovarian somatic cells, a process required for the production of infectious particles that can lead to heritable transposition events12,13. Our findings identify splicing regulation as a new role and essential function for the Piwi pathway in protecting the genome against transposon mobility, and provide a model system for studying the role of chromatin structure in modulating alternative splicing during development

SPNS2 enables T cell egress from lymph nodes during an immune response

T cell expression of sphingosine 1-phosphate receptor 1 (S1PR1) enables T cell exit from lymph nodes (LN) into lymph, while endothelial S1PR1 expression regulates vascular permeability. Drugs targeting S1PR1 treat autoimmune disease by trapping pathogenic T cells within LN, but have adverse cardiovascular side-effects. In homeostasis, the transporter SPNS2 supplies lymph S1P and enables T cell exit, while the transporter MFSD2B supplies most blood S1P and supports vascular function. It is unknown whether SPNS2 remains necessary to supply lymph S1P during an immune response, or whether in inflammation other compensatory transporters are up- regulated. Here, using a model of dermal inflammation, we demonstrate that SPNS2 supplies the S1P that guides T cells out of LN with an ongoing immune response. Furthermore, deletion of Spns2 is protective in a mouse model of multiple sclerosis.These results support the therapeutic potential of SPNS2 inhibitors to achieve spatially specific modulation of S1P signaling

Methodology for Diagnosing the Causes of Die-Casting Defects, Based on Advanced Big Data Modelling

The purpose of this paper was to develop a methodology for diagnosing the causes of die-casting defects based on advanced modelling, to correctly diagnose and identify process parameters that have a significant impact on product defect generation, optimize the process parameters and rise the products’ quality, thereby improving the manufacturing process efficiency. The industrial data used for modelling came from foundry being a leading manufacturer of the high-pressure die-casting production process of aluminum cylinder blocks for the world's leading automotive brands. The paper presents some aspects related to data analytics in the era of Industry 4.0. and Smart Factory concepts. The methodology includes computation tools for advanced data analysis and modelling, such as ANOVA (analysis of variance), ANN (artificial neural networks) both applied on the Statistica platform, then gradient and evolutionary optimization methods applied in MS Excel program’s Solver add-in. The main features of the presented methodology are explained and presented in tables and illustrated with appropriate graphs. All opportunities and risks of implementing data-driven modelling systems in high-pressure die-casting processes have been considered