93 research outputs found

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

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    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

    Study Content and Process, Competences Upon Graduation and Employment

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    Building the foundations for measuring learning gain in higher education: A conceptual framework and measurement instrument

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    In this paper we set out the first step towards the measurement of learning gain in higher education by putting forward a conceptual framework for understanding learning gain that is relevant across disciplines. We then introduce the operationalisation of this conceptual framework into a new set of measurement tools. With the use of data from a large-scale survey of eleven English universities and over 4,500 students, we test the reliability and validity of the measurement instrument empirically. We find support in the data for the reliability of most of the measurement scales we put forward, as well as for the validity of the conceptual framework. Based on these results, we reflect on the conceptual framework and associated measurement tools in the context of at-scale deployment and the potential implications for policy and practice in higher education.Higher Education Funding Council for England (HEFCE
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