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The human U1A protein‐U1A pre‐mRNA complex and the relationship between its structure and function in inhibition of polyadenylation in vitro were investigated. Two molecules of U1A protein were shown to bind to a conserved region in the 3′ untranslated region of U1A pre‐mRNA. The secondary structure of this region was determined by a combination of theoretical prediction, phylogenetic sequence alignment, enzymatic structure probing and molecular genetics. The U1A binding sites form (part of) a complex secondary structure which is significantly different from the binding site of U1A protein on U1 snRNA. Studies with mutant pre‐mRNAs showed that the integrity of much of this structure is required for both high affinity binding to U1A protein and specific inhibition of polyadenylation in vitro. In particular, binding of a single molecule of U1A protein to U1A pre‐mRNA is not sufficient to produce efficient inhibition of polyadenylation.

The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.

The secondary structures of human hY1 and hY5 RNAs were determined using both chemical modification techniques and enzymatic structure probing. The results indicate that both for hY1 and for hY5 RNA the secondary structure largely corresponds to the structure predicted by sequence alignment and computerized energy-minimization. However, some important deviations were observed. In the case of hY1 RNA, two regions forming a predicted helix appeared to be single-stranded. Furthermore, the pyrimidine-rich region of hY1 RNA appeared to be very resistant to reagents under native conditions, although it was accessible to chemical reagents under semi-denaturing conditions. This may point to yet unidentified tertiary interactions for this region of hY1 RNA. In the case of hY5 RNA, two neighbouring internal loops in the predicted structure appeared to form one large internal loop.