Transposing from the laboratory to the classroom to generate authentic research experiences for undergraduates.

Large lecture classes and standardized laboratory exercises are characteristic of introductory biology courses. Previous research has found that these courses do not adequately convey the process of scientific research and the excitement of discovery. Here we propose a model that provides beginning biology students with an inquiry-based, active learning laboratory experience. The Dynamic Genome course replicates a modern research laboratory focused on eukaryotic transposable elements where beginning undergraduates learn key genetics concepts, experimental design, and molecular biological skills. Here we report on two key features of the course, a didactic module and the capstone original research project. The module is a modified version of a published experiment where students experience how virtual transposable elements from rice (Oryza sativa) are assayed for function in transgenic Arabidopsis thaliana. As part of the module, students analyze the phenotypes and genotypes of transgenic plants to determine the requirements for transposition. After mastering the skills and concepts, students participate in an authentic research project where they use computational analysis and PCR to detect transposable element insertion site polymorphism in a panel of diverse maize strains. As a consequence of their engagement in this course, students report large gains in their ability to understand the nature of research and demonstrate that they can apply that knowledge to independent research projects

Varieties of Exploratory Experimentation in Nanotoxicology

There has been relatively little effort to provide a systematic overview of different forms of exploratory experimentation (EE). The present paper examines the growing subdiscipline of nanotoxicology and suggests that it illustrates at least four ways that researchers can engage in EE: searching for regularities; developing new techniques, simulation models, and instrumentation; collecting and analyzing large swaths of data using new experimental strategies (e.g., computer-based simulation and “high-throughput” instrumentation); and structuring an entire disciplinary field around exploratory research agendas. In order to distinguish these and other activities more effectively, the paper proposes a taxonomy that includes three dimensions along which types of EE vary: (1) the aim of the experimental activity, (2) the role of theory in the activity, and (3) the methods or strategies employed for varying experimental parameters

Long-Distance Wind-Dispersal of Spores in a Fungal Plant Pathogen: Estimation of Anisotropic Dispersal Kernels from an Extensive Field Experiment

Given its biological significance, determining the dispersal kernel (i.e., the distribution of dispersal distances) of spore-producing pathogens is essential. Here, we report two field experiments designed to measure disease gradients caused by sexually- and asexually-produced spores of the wind-dispersed banana plant fungus Mycosphaerella fijiensis. Gradients were measured during a single generation and over 272 traps installed up to 1000 m along eight directions radiating from a traceable source of inoculum composed of fungicide-resistant strains. We adjusted several kernels differing in the shape of their tail and tested for two types of anisotropy. Contrasting dispersal kernels were observed between the two types of spores. For sexual spores (ascospores), we characterized both a steep gradient in the first few metres in all directions and rare long-distance dispersal (LDD) events up to 1000 m from the source in two directions. A heavy-tailed kernel best fitted the disease gradient. Although ascospores distributed evenly in all directions, average dispersal distance was greater in two different directions without obvious correlation with wind patterns. For asexual spores (conidia), few dispersal events occurred outside of the source plot. A gradient up to 12.5 m from the source was observed in one direction only. Accordingly, a thin-tailed kernel best fitted the disease gradient, and anisotropy in both density and distance was correlated with averaged daily wind gust. We discuss the validity of our results as well as their implications in terms of disease diffusion and management strategy

An Inquiry-Infused Introductory Biology Laboratory That Integrates Mendel\u27s Pea Phenotypes With Molecular Mechanisms

We developed a multi-week laboratory in which college-level introductory biology students investigate Mendel\u27s stem length phenotype in peas. Students collect, analyze and interpret convergent evidence from molecular and physiological techniques. In weeks 1 and 2, students treat control and experimental plants with Gibberellic Acid (GA) to determine whether uncharacterized short mutant lines are GA responsive. These data allow students to place the mutation in the GA signal transduction pathway. During weeks 2 and 3, plants are genotyped for Mendel\u27s le mutation using a derived cleaved polymorphic sequences (dCAPS) PCR assay. This laboratory allows students to make a direct connection between modern molecular genetics and the easily scored phenotypes Mendel used as the basis of his fundamental discoveries. We administered surveys to assess student gains in accord with four learning goals: understanding the lab, basic science literacy, scientific practices, and working collaboratively. Student confidence increased significantly in the first three, but not in working collaboratively, although students reported greater confidence working in groups than alone

The Evolution of Student Engagement: Writing Improves Teaching in Introductory Biology

In response to calls for pedagogical reforms in undergraduate biology courses to decrease student attrition rates and increase active learning, this article describes one faculty member’s conversion from traditional teaching methods to more engaging forms of practice. Partially told as a narrative, this article illustrates a.) the way many faculty initially learn to teach by modeling the pedagogy from their own undergraduate programs; b.) the kind of support biology faculty may need to break out of traditional molds; c.) how writing can promote active learning; and d.) the impact of reformed pedagogy on student levels of engagement. The latter will be demonstrated through assessment results gathered from student surveys, reflective writing, and focus group interview. Ultimately, the study challenges misunderstandings some faculty might have regarding the value of writing in science classes and offers inspiration, urging critical reflection and persistence

Multi-locus analysis of genomic time series data from experimental evolution.

Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the genome and across sampled time points, in an approximate but principled manner. We first use simulated data to demonstrate the power of our method to correctly detect, locate and estimate the fitness of a selected allele from among several linked sites. We study how this power changes for different values of selection strength, initial haplotypic diversity, population size, sampling frequency, experimental duration, number of replicates, and sequencing coverage depth. In addition to providing quantitative estimates of selection parameters from experimental evolution data, our model can be used by practitioners to design E&R experiments with requisite power. We also explore how our likelihood-based approach can be used to infer other model parameters, including effective population size and recombination rate. Then, we apply our method to analyze genome-wide data from a real E&R experiment designed to study the adaptation of D. melanogaster to a new laboratory environment with alternating cold and hot temperatures

Genetic regulation of mouse liver metabolite levels.

We profiled and analyzed 283 metabolites representing eight major classes of molecules including Lipids, Carbohydrates, Amino Acids, Peptides, Xenobiotics, Vitamins and Cofactors, Energy Metabolism, and Nucleotides in mouse liver of 104 inbred and recombinant inbred strains. We find that metabolites exhibit a wide range of variation, as has been previously observed with metabolites in blood serum. Using genome-wide association analysis, we mapped 40% of the quantified metabolites to at least one locus in the genome and for 75% of the loci mapped we identified at least one candidate gene by local expression QTL analysis of the transcripts. Moreover, we validated 2 of 3 of the significant loci examined by adenoviral overexpression of the genes in mice. In our GWAS results, we find that at significant loci the peak markers explained on average between 20 and 40% of variation in the metabolites. Moreover, 39% of loci found to be regulating liver metabolites in mice were also found in human GWAS results for serum metabolites, providing support for similarity in genetic regulation of metabolites between mice and human. We also integrated the metabolomic data with transcriptomic and clinical phenotypic data to evaluate the extent of co-variation across various biological scales

Plant Metabolomics Applications in the Brassicaceae: Added Value for Science and Industry

Crops from the family Brassicaceae represent a diverse and very interesting group of plants. In addition, their close relationship with the model plant, Arabidopsis thaliana, makes combined research on these species both scientifically valuable and of considerable commercial importance. In the post-genomics era, much effort is being placed on expanding our capacity to use advanced technologies such as proteomics and metabolomics, to broaden our knowledge of the molecular organization of plants and how genetic differences are translated into phenotypic ones. Metabolomics in particular is gaining much attention mainly due both to the comprehensiveness of the technology and also the potentially close relationship between biochemical composition (including human health-related phytochemicals) and phenotype. In this short review, a brief introduction to the main metabolomics technologies is given taking examples from research on the Brassicaceae for illustratio

Experimental harvesting of fish populations drives genetically based shifts in body size and maturation

Size-selective harvesting in commercial fisheries can induce rapid changes in biological traits. While experimental and wild harvested populations often exhibit clear shifts in body size and maturation associated with fishing pressure, the relative contributions of genetic and environmental factors to these shifts remain uncertain and have been much debated. To date, observations of so-called fisheries-induced evolution (FIE) have been based solely on phenotypic measures, such as size data. Genetic data are hitherto lacking. Here, we quantify genetic versus environmental change in response to size-selective harvesting for small and large body size in guppies (Poecilia reticulata) across three generations of selection. We document for the first time significant changes at individual genetic loci, some of which have previously been associated with body size. In contrast, variation at neutral microsatellite markers was unaffected by selection, providing direct genetic evidence for rapid evolution induced by size-selective harvesting. These findings demonstrate FIE in an experimental system, with major implications for the sustainability of harvested populations, as well as impacts on size-structured communities and ecosystem processes. These findings highlight the need for scientists and managers to reconsider the capacity of harvested stocks to adapt to, and recover from, harvesting and predation. © 2013 The Ecological Society of America