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  • A A student assists Colorado Parks & Wildlife employees spawning greenback cutthroat trout at the Leadville National Fish Hatchery; B greenback cutthroat trout adults in a hatchery raceway; C tissue samples collected by students to be used for genetic analysis (images taken by S. Love Stowell)

    Cutthroat trout in Colorado: A case study connecting evolution and conservation

    Learning Objectives
    Students will be able to:
    • interpret figures such as maps, phylogenies, STRUCTURE plots, and networks for species delimitation
    • identify sources of uncertainty and disagreement in real data sets
    • propose research to address or remedy uncertainty
    • construct an evidence-based argument for the management of a rare taxon
  • Plant ecology students surveying vegetation at Red Hills, CA, spring 2012.  From left to right are G.L, F.D, A.M., and R.P.  Photo used with permission from all students.

    Out of Your Seat and on Your Feet! An adaptable course-based research project in plant ecology for advanced students

    Learning Objectives
    Students will:
    • Articulate testable hypotheses. (Lab 8, final presentation/paper, in-class exercises)
    • Analyze data to determine the level of support for articulated hypotheses. (Labs 4-7, final presentation/paper)
    • Identify multiple species of plants in the field quickly and accurately. (Labs 2-3, field trip)
    • Measure environmental variables and sample vegetation in the field. (Labs 2-3, field trip)
    • Analyze soil samples using a variety of low-tech lab techniques. (Open labs after field trip)
    • Use multiple statistical techniques to analyze data for patterns. (Labs 4-8, final presentation/paper)
    • Interpret statistical analyses to distinguish between strong and weak interactions in a biological system. (Labs 4-7, final presentation/paper)
    • Develop and present a conference-style presentation in a public forum. (Lab 8, final presentation/paper)
    • Write a publication-ready research paper communicating findings and displaying data. (Lab 8, final presentation/paper)
  • Experimental design schematic
  • Image from a clicker-based case study on muscular dystrophy and the effect of mutations on the processes in the central dogma.

    A clicker-based case study that untangles student thinking about the processes in the central dogma

    Learning Objectives
    Students will be able to:
    • explain the differences between silent (no change in the resulting amino acid sequence), missense (a change in the amino acid sequence), and nonsense (a change resulting in a premature stop codon) mutations.
    • differentiate between how information is encoded during DNA replication, transcription, and translation.
    • evaluate how different types of mutations (silent, missense, and nonsense) and the location of those mutations (intron, exon, and promoter) differentially affect the processes in the central dogma.
    • predict the molecular (DNA size, mRNA length, mRNA abundance, and protein length) and/or phenotypic consequences of mutations.
  • Students using the Understanding Eukaryotic Genes curriculum to construct a gene model. Students are working as a pair to complete each Module using classroom computers.

    An undergraduate bioinformatics curriculum that teaches eukaryotic gene structure

    Learning Objectives
    Module 1
    • Demonstrate basic skills in using the UCSC Genome Browser to navigate to a genomic region and to control the display settings for different evidence tracks.
    • Explain the relationships among DNA, pre-mRNA, mRNA, and protein.
    Module 2
    • Describe how a primary transcript (pre-mRNA) can be synthesized using a DNA molecule as the template.
    • Explain the importance of the 5' and 3' regions of the gene for initiation and termination of transcription by RNA polymerase II.
    • Identify the beginning and the end of a transcript using the capabilities of the genome browser.
    Module 3
    • Explain how the primary transcript generated by RNA polymerase II is processed to become a mature mRNA, using the sequence signals identified in Module 2.
    • Use the genome browser to analyze the relationships among:
    • pre-mRNA
    • 5' capping
    • 3' polyadenylation
    • splicing
    • mRNA
    Module 4
    • Identify splice donor and acceptor sites that are best supported by RNA-Seq data and TopHat splice junction predictions.
    • Utilize the canonical splice donor and splice acceptor sequences to identify intron-exon boundaries.
    Module 5
    • Determine the codons for specific amino acids and identify reading frames by examining the Base Position track in the genome browser.
    • Assemble exons to maintain the open reading frame (ORF) for a given gene.
    • Define the phases of the splice donor and acceptor sites and describe how they impact the maintenance of the ORF.
    • Identify the start and stop codons of an assembled ORF.
    Module 6
    • Demonstrate how alternative splicing of a gene can lead to different mRNAs.
    • Show how alternative splicing can lead to the production of different polypeptides and result in drastic changes in phenotype.
  • “The outcome of the Central Dogma is not always intuitive” Variation in gene size does not necessarily correlate with variation in protein size. Here, two related genes differ in length due to a deletion mutation that removes four nucleotides. Many students do not predict that the smaller gene, after transcription and translation, would produce a larger protein.

    Predicting and classifying effects of insertion and deletion mutations on protein coding regions

    Learning Objectives
    Students will be able to:
    • accurately predict effects of frameshift mutations in protein coding regions
    • conduct statistical analysis to compare expected and observed values
    • become familiar with accessing and using DNA sequence databases and analysis tools
  • The MAP Kinase signal transduction pathway

    Cell Signaling Pathways - a Case Study Approach

    Learning Objectives
    • Use knowledge of positive and negative regulation of signaling pathways to predict the outcome of genetic modifications or pharmaceutical manipulation.
    • From phenotypic data, predict whether a mutation is in a coding or a regulatory region of a gene involved in signaling.
    • Use data, combined with knowledge of pathways, to make reasonable predictions about the genetic basis of altered signaling pathways.
    • Interpret and use pathway diagrams.
    • Synthesize information by applying prior knowledge on gene expression when considering congenital syndromes.
  • Arabidopsis Seedling

    Linking Genotype to Phenotype: The Effect of a Mutation in Gibberellic Acid Production on Plant Germination

    Learning Objectives
    Students will be able to:
    • identify when germination occurs.
    • score germination in the presence and absence of GA to construct graphs of collated class data of wild-type and mutant specimens.
    • identify the genotype of an unknown sample based on the analysis of their graphical data.
    • organize data and perform quantitative data analysis.
    • explain the importance of GA for plant germination.
    • connect the inheritance of a mutation with the observed phenotype.
  • Students preforming the leaky neuron activity.

    The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cups

    Learning Objectives
    Students will able to:
    • compare and contrast spatial and temporal summation in terms of the number of presynaptic events and the timing of these events
    • predict the relative contribution to reaching threshold and firing an action potential as a function of distance from the axon hillock
    • predict how the frequency of incoming presynaptic action potentials effects the success of temporal summation of resultant postsynaptic potentials
  • Structure of protein ABCB6

    Investigating the Function of a Transport Protein: Where is ABCB6 Located in Human Cells?

    Learning Objectives
    At the end of this activity students will be able to:
    • describe the use of two common research techniques for studying proteins: SDS-PAGE and immunoblot analysis.
    • determine a protein’s subcellular location based on results from: 1) immunoblotting after differential centrifugation, and 2) immunofluorescence microscopy.
    • analyze protein localization data based on the limitations of differential centrifugation and immunofluorescence microscopy.