Assessing the impact of Swales on receiving water quality

Swales are one type of sustainable drainage system (SuDS) which contribute to the management of water quality in receiving waterbodies. Using a semi-quantitative approach, an impact assessment procedure is applied to the residual water quality that is carried forward to surface waters and groundwaters following treatment within a swale. Both volumetric and pollutant distributions are considered as stormwater passes through the swale system. The pollutant pathways followed by TSS, nitrate, chloride, metals (Cd, Cu, Pb, Zn) and polyaromatic hydrocarbons (PAHs) are determined for a swale receiving highway runoff. For TSS, metals and PAHs between 20% and 29% of the total mean influent pollutant load is predicted to be directed to infiltration through the underlying soils compared to between 4% and 16% of chloride and nitrate. Although surface water impacts are deemed possible, the discharges of swales to groundwaters are assessed to represent a negligible impact for effectively maintained systems

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism