Undergraduate Performance in Solving Ill-Defined Biochemistry Problems.

With growing interest in promoting skills related to the scientific process, we studied performance in solving ill-defined problems demonstrated by graduating biochemistry majors at a public, minority-serving university. As adoption of techniques for facilitating the attainment of higher-order learning objectives broadens, so too does the need to appropriately measure and understand student performance. We extended previous validation of the Individual Problem Solving Assessment (IPSA) and administered multiple versions of the IPSA across two semesters of biochemistry courses. A final version was taken by majors just before program exit, and student responses on that version were analyzed both quantitatively and qualitatively. This mixed-methods study quantifies student performance in scientific problem solving, while probing the qualitative nature of unsatisfactory solutions. Of the five domains measured by the IPSA, we found that average graduates were only successful in two areas: evaluating given experimental data to state results and reflecting on performance after the solution to the problem was provided. The primary difficulties in each domain were quite different. The most widespread challenge for students was to design an investigation that rationally aligned with a given hypothesis. We also extend the findings into pedagogical recommendations.

Optimized approach for Ion Proton RNA sequencing reveals details of RNA splicing and editing features of the transcriptome.

RNA-sequencing (RNA-seq) has become the standard method for unbiased analysis of gene expression but also provides access to more complex transcriptome features, including alternative RNA splicing, RNA editing, and even detection of fusion transcripts formed through chromosomal translocations. However, differences in library methods can adversely affect the ability to recover these different types of transcriptome data. For example, some methods have bias for one end of transcripts or rely on low-efficiency steps that limit the complexity of the resulting library, making detection of rare transcripts less likely. We tested several commonly used methods of RNA-seq library preparation and found vast differences in the detection of advanced transcriptome features, such as alternatively spliced isoforms and RNA editing sites. By comparing several different protocols available for the Ion Proton sequencer and by utilizing detailed bioinformatics analysis tools, we were able to develop an optimized random primer based RNA-seq technique that is reliable at uncovering rare transcript isoforms and RNA editing features, as well as fusion reads from oncogenic chromosome rearrangements. The combination of optimized libraries and rapid Ion Proton sequencing provides a powerful platform for the transcriptome analysis of research and clinical samples.