Diversity-generating retroelements: natural variation, classification and evolution inferred from a large-scale genomic survey.

Diversity-generating retroelements (DGRs) are novel genetic elements that use reverse transcription to generate vast numbers of sequence variants in specific target genes. Here, we present a detailed comparative bioinformatic analysis that depicts the landscape of DGR sequences in nature as represented by data in GenBank. Over 350 unique DGRs are identified, which together form a curated reference set of putatively functional DGRs. We classify target genes, variable repeats and DGR cassette architectures, and identify two new accessory genes. The great variability of target genes implies roles of DGRs in many undiscovered biological processes. There is much evidence for horizontal transfers of DGRs, and we identify lineages of DGRs that appear to have specialized properties. Because GenBank contains data from only 10% of described species, the compilation may not be wholly representative of DGRs present in nature. Indeed, many DGR subtypes are present only once in the set and DGRs of the candidate phylum radiation bacteria, and Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaea archaea, are exceptionally diverse in sequence, with little information available about functions of their target genes. Nonetheless, this study provides a detailed framework for classifying and studying DGRs as they are uncovered and studied in the future.

Teasing apart the impacts of curriculum and professional development on teaching assistants' teaching practices.

Teaching assistants (TAs) often lead courses using curricula they did not design. Therefore, examining how curriculum and professional development (PD) interact to influence TAs' teaching practices is critical. This study describes the effects of a curriculum and PD intervention in two contexts: when TAs are teaching curriculum that is explicitly linked to PD, and when teaching curriculum that is not linked to PD. The Intervention curriculum featured structured opportunities for reform-oriented teaching practices. The Intervention PD was situated in the context of these specific curriculum activities and modelled the desired teaching practices. TAs that participated in the intervention implemented more student-centered teaching practices than TAs that did not participate in the intervention, even when teaching curriculum that was not designed to be student-centered and was not linked to PD. A linear model of TAs' teaching practices that included PD type, task cognitive demand and curriculum type indicates that cognitive demand has the largest relationship with teaching practices, followed by PD type. These results have implications for policy. They suggest that investment in curriculum-linked TA PD can be effective even when teaching curricula that is not linked to PD. Additionally, investment in development of higher-cognitive-demand tasks may be an effective strategy to support implementation of student-centered practices.

Paired Multiple-Choice Questions Reveal Students' Incomplete Statistical Thinking about Variation during Data Analysis.

Biologists consider variability during biological investigations. A robust quantitative understanding of variability is particularly important during data analysis, where statistics are used to quantify variation and draw conclusions about phenomena while accounting for variation. Many students struggle to correctly apply a quantitative understanding of variation to statistically analyze data. We present quantitative and qualitative analyses of introductory biology students' responses on two pairs of multiple-choice questions querying two concepts related to the quantitative analysis of variation. More students correctly identify a mathematical expression of variation than correctly interpret it. Many students correctly interpret a nonsignificant p-value in the context of a very small sample size, but fewer students do so in the context of a large sample size. These results imply that many students have an incomplete quantitative understanding of variation. These findings suggest that instruction focusing on conceptual understanding, not procedural problem solving, may elevate students' quantitative understanding of variation.

A pipeline of programs for collecting and analyzing group II intron retroelement sequences from GenBank.

BACKGROUND: Accurate and complete identification of mobile elements is a challenging task in the current era of sequencing, given their large numbers and frequent truncations. Group II intron retroelements, which consist of a ribozyme and an intron-encoded protein (IEP), are usually identified in bacterial genomes through their IEP; however, the RNA component that defines the intron boundaries is often difficult to identify because of a lack of strong sequence conservation corresponding to the RNA structure. Compounding the problem of boundary definition is the fact that a majority of group II intron copies in bacteria are truncated. RESULTS: Here we present a pipeline of 11 programs that collect and analyze group II intron sequences from GenBank. The pipeline begins with a BLAST search of GenBank using a set of representative group II IEPs as queries. Subsequent steps download the corresponding genomic sequences and flanks, filter out non-group II introns, assign introns to phylogenetic subclasses, filter out incomplete and/or non-functional introns, and assign IEP sequences and RNA boundaries to the full-length introns. In the final step, the redundancy in the data set is reduced by grouping introns into sets of ≥95% identity, with one example sequence chosen to be the representative. CONCLUSIONS: These programs should be useful for comprehensive identification of group II introns in sequence databases as data continue to rapidly accumulate.