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Tackling "Big Data" with Biology Undergrads: A Simple RNA-seq Data Analysis Tutorial Using GalaxyLearning Objectives
- Students will locate and download high-throughput sequence data and genome annotation files from publically available data repositories.
- Students will use Galaxy to create an automated computational workflow that performs sequence quality assessment, trimming, and mapping of RNA-seq data.
- Students will analyze and interpret the outputs of RNA-seq analysis programs.
- Students will identify a group of genes that is differentially expressed between treatment and control samples, and interpret the biological significance of this list of differentially expressed genes.
An undergraduate bioinformatics curriculum that teaches eukaryotic gene structureLearning ObjectivesModule 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.
- 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.
- 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:
- 5' capping
- 3' polyadenylation
- 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.
- 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.
- 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.
Building Trees: Introducing evolutionary concepts by exploring Crassulaceae phylogeny and biogeographyLearning ObjectivesStudents will be able to:
- Estimate phylogenetic trees using diverse data types and phylogenetic models.
- Correctly make inferences about evolutionary history and relatedness from the tree diagrams obtained.
- Use selected computer programs for phylogenetic analysis.
- Use bootstrapping to assess the statistical support for a phylogeny.
- Use phylogenetic data to construct, compare, and evaluate the role of geologic processes in shaping the historical and current geographic distributions of a group of organisms.
The Leaky Neuron: Understanding synaptic integration using an analogy involving leaky cupsLearning ObjectivesStudents 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
Investigating Cell Signaling with Gene Expression DatasetsLearning ObjectivesStudents will be able to:
- Explain the hierarchical organization of signal transduction pathways.
- Explain the role of enzymes in signal propagation and amplification.
- Recognize the centrality of signaling pathways in cellular processes, such as metabolism, cell division, or cell motility.
- Rationalize the etiologic basis of disease in terms of deranged signaling pathways.
- Use software to analyze and interpret gene expression data.
- Use an appropriate statistical method for hypotheses testing.
- Produce reports that are written in scientific style.