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The Bee the CURE is a novel course-based undergraduate research experience (CURE) that engages introductory biology students in DNA barcoding (DNA extraction, amplification, and bioinformatics) in partnership with the Tucson Bee Collaborative and the University of Arizona. The first iteration of this CURE taught at Pima Community College (PCC) occurred during the Fall 2020 semester in which the course was taught online and students focused on bioinformatics. Due to the online format, students were unable to participate directly in the wet-lab components (extraction and amplification) of the course. These were approximated with videos of the instructor performing the tasks. A qualitative case study of this semester built from student interviews found that students were able to form positive relationships with instructors and peer mentors but that the online format of the class posed some challenges to relationship formation. Students reported developing self-efficacy in bioinformatics skills while online lab participation disrupted student’s gaining “hands-on experiences” and seldom led to development of science self-efficacy in wet lab skills. Our findings from a study of a synchronous online CURE allowed us to characterize a context in which online learning posed a challenge and perhaps even a threat to research self-efficacy, especially regarding skill development and self-efficacy in “hands-on” areas, such as wet-bench research skills. Yet optimistically, our study highlights the potential of online community college learning environments to provide mastery experiences in online science contexts (e.g., bioinformatics) and opportunities for relationship building.

 

Abstract Dissecting the relationship between gene function and substitution rates is key to understanding genome-wide patterns of molecular evolution. Biochemical pathways provide powerful systems for investigating this relationship because the functional role of each gene is often well characterized. Here, we investigate the evolution of the flavonoid pigment pathway in the colorful Petunieae clade of the tomato family (Solanaceae). This pathway is broadly conserved in plants, both in terms of its structural elements and its MYB, basic helix–loop–helix, and WD40 transcriptional regulators, and its function has been extensively studied, particularly in model species of petunia. We built a phylotranscriptomic data set for 69 species of Petunieae to infer patterns of molecular evolution across pathway genes and across lineages. We found that transcription factors exhibit faster rates of molecular evolution (dN/dS) than their targets, with the highly specialized MYB genes evolving fastest. Using the largest comparative data set to date, we recovered little support for the hypothesis that upstream enzymes evolve slower than those occupying more downstream positions, although expression levels do predict molecular evolutionary rates. Although shifts in floral pigmentation were only weakly related to changes affecting coding regions, we found a strong relationship with the presence/absence patterns of MYB transcripts. Intensely pigmented species express all three main MYB anthocyanin activators in petals, whereas pale or white species express few or none. Our findings reinforce the notion that pathway regulators have a dynamic history, involving higher rates of molecular evolution than structural components, along with frequent changes in expression during color transitions. 

Syndromes, wherein multiple traits evolve convergently in response to a shared selective driver, form a central concept in ecology and evolution. Recent work has questioned the existence of some classic syndromes, such as pollination and seed dispersal syndromes. Here, we discuss some of the major issues that have afflicted research into syndromes in macroevolution and ecology. First, correlated evolution of traits and hypothesized selective drivers is often relied on as the only evidence for adaptation of those traits to those hypothesized drivers, without supporting evidence. Second, the selective driver is often inferred from a combination of traits without explicit testing. Third, researchers often measure traits that are easy for humans to observe rather than measuring traits that are suited to testing the hypothesis of adaptation. Finally, species are often chosen for study because of their striking phenotypes, which leads to the illusion of syndromes and divergence. We argue that these issues can be avoided by combining studies of trait variation across entire clades or communities with explicit tests of adaptive hypotheses and that taking this approach will lead to a better understanding of syndrome‐like evolution and its drivers.