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Bioinformatics
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A CURE-based approach to teaching genomics using mitochondrial genomes
Learning Objectives- Install the appropriate programs such as Putty and WinSCP.
- Navigate NCBI's website including their different BLAST programs (e.g., blastn, tblastx, blastp and blastx)
- Use command-line BLAST to identify mitochondrial contigs within a whole genome assembly
- Filter the desired sequence (using grep) and move the assembled mitochondrial genome onto your own computer (using FTP or SCP)
- Error-correct contigs (bwa mem, samtools tview), connect and circularize organellar contigs (extending from filtered reads)
- Transform assembled sequences into annotated genomes
- Orient to canonical start locations in the mitochondrial genome (cox1)
- Identify the boundaries of all coding components of the mitochondrial genome using BLAST, including: Protein coding genes (BLASTx and tBLASTX), tRNAs (proprietary programs such as tRNAscan), rRNAs (BLASTn, Chlorobox), ORFs (NCBI's ORFFinder)
- Deposit annotation onto genome repository (NCBI)
- Update CV/resume to reflect bioinformatics skills learned in this lesson
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Sequence Similarity: An inquiry based and "under the hood" approach for incorporating molecular sequence...
Learning ObjectivesAt the end of this lesson, students will be able to:- Define similarity in a non-biological and biological sense when provided with two strings of letters.
- Quantify the similarity between two gene/protein sequences.
- Explain how a substitution matrix is used to quantify similarity.
- Calculate amino acid similarity scores using a scoring matrix.
- Demonstrate how to access genomic data (e.g., from NCBI nucleotide and protein databases).
- Demonstrate how to use bioinformatics tools to analyze genomic data (e.g., BLASTP), explain a simplified BLAST search algorithm including how similarity is used to perform a BLAST search, and how to evaluate the results of a BLAST search.
- Create a nearest-neighbor distance matrix.
- Create a multiple sequence alignment using a nearest-neighbor distance matrix and a phylogram based on similarity of amino acid sequences.
- Use appropriate bioinformatics sequence alignment tools to investigate a biological question.
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Training future faculty in 30 minutes a week: A modular framework to provide just-in-time professional development to...
Learning ObjectivesTAs will be able to:- design small classroom activities
- design fair quiz and exam questions
- use rubrics to grade assignments fairly and in a timely manner
- offer constructive, actionable feedback on student written work
- compare and contrast context-specific strategies for dealing with student problems
- compare and contrast context-specific time management strategies
- discuss the importance of diversity, evaluate their own implicit biases, and discuss how these could impact their teaching
- compare and contrast different methods of summarizing teaching experience on job application materials
- evaluate their teaching in a reflective manner to develop future teaching goals
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Using Undergraduate Molecular Biology Labs to Discover Targets of miRNAs in Humans
Learning Objectives- Use biological databases to generate and compare lists of predicted miR targets, and obtain the mRNA sequence of their selected candidate gene
- Use bioinformatics tools to design and optimize primer sets for qPCR
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Tackling "Big Data" with Biology Undergrads: A Simple RNA-seq Data Analysis Tutorial Using Galaxy
Learning 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.
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Predicting and classifying effects of insertion and deletion mutations on protein coding regions
Learning ObjectivesStudents 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
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CURE-all: Large Scale Implementation of Authentic DNA Barcoding Research into First-Year Biology Curriculum
Learning ObjectivesStudents will be able to: Week 1-4: Fundamentals of Science and Biology- List the major processes involved in scientific discovery
- List the different types of scientific studies and which types can establish causation
- Design experiments with appropriate controls
- Create and evaluate phylogenetic trees
- Define taxonomy and phylogeny and explain their relationship to each other
- Explain DNA sequence divergence and how it applies to evolutionary relationships and DNA barcoding
- Define and measure biodiversity and explain its importance
- Catalog organisms using the morphospecies concept
- Geographically map organisms using smartphones and an online mapping program
- Calculate metrics of species diversity using spreadsheet software
- Use spreadsheet software to quantify and graph biodiversity at forest edges vs. interiors
- Write a formal lab report
- Extract, amplify, visualize and sequence DNA using standard molecular techniques (PCR, gel electrophoresis, Sanger sequencing)
- Explain how DNA extraction, PCR, gel electrophoresis, and Sanger sequencing work at the molecular level
- Trim and assemble raw DNA sequence data
- Taxonomically identify DNA sequences isolated from unknown organisms using BLAST
- Visualize sequence data relationships using sequence alignments and gene-based phylogenetic trees
- Map and report data in a publicly available online database
- Share data in a formal scientific poster
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Homologous chromosomes? Exploring human sex chromosomes, sex determination and sex reversal using bioinformatics...
Learning ObjectivesStudents successfully completing this lesson will:- Practice navigating an online bioinformatics resource and identify evidence relevant to solving investigation questions
- Contrast the array of genes expected on homologous autosomal chromosomes pairs with the array of genes expected on sex chromosome pairs
- Use bioinformatics evidence to defend the definition of homologous chromosomes
- Define chromosomal sex and defend the definition using experimental data
- Investigate the genetic basis of human chromosomal sex determination
- Identify at least two genetic mutations can lead to sex reversal
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An undergraduate bioinformatics curriculum that teaches eukaryotic gene structure
Learning 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:
- pre-mRNA
- 5' capping
- 3' polyadenylation
- splicing
- mRNA
- 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.
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Exploration of the Human Genome by Investigation of Personalized SNPs
Learning ObjectivesStudents successfully completing this lesson will be able to:- Effectively use the bioinformatics databases (SNPedia, the UCSC Genome Browser, and NCBI) to explore SNPs of interest within the human genome.
- Identify three health-related SNPs of personal interest and use the UCSC Genome Browser to define their precise chromosomal locations and determine whether they lie within a gene or are intergenic.
- Establish a list of all genome-wide association studies correlated with a particular health-related SNP.
- Predict which model organism would be most appropriate for conducting further research on a human disease.
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Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active Teaching
Learning Objectives- From raw RNAseq data, run a basic analysis culminating in a list of differentially expressed genes.
- Explain and evaluate statistical tests in RNAseq data. Specifically, given the output of a particular test, students should be able to interpret and explain the result.
- Use the Linux command line to complete specified objectives in an RNAseq workflow.
- Generate meaningful visualizations of results from new data in R.
- (In addition, each chapter of this lesson plan contains more specific learning objectives, such as “Students will demonstrate their ability to map reads to a reference.”)
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Using computational molecular modeling software to demonstrate how DNA mutations cause phenotypes
Learning ObjectivesStudents successfully completing this lesson will:- Practice basic molecular biology laboratory skills such as DNA isolation, PCR, and gel electrophoresis.
- Gather and analyze quantitative and qualitative scientific data and present it in figures.
- Use bioinformatics to analyze DNA sequences and obtain protein sequences for molecular modeling.
- Make and analyze three-dimensional (3-D) protein models using molecular modeling software.
- Write a laboratory report using the collected data to explain how mutations in the DNA cause changes in protein structure/function which lead to mutant phenotypes.
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CRISPR/Cas9 in yeast: a multi-week laboratory exercise for undergraduate students
Learning ObjectivesWeek 1: CRISPR design- Locate the coding sequence, flanking sequence, protein product, and characteristics of a given gene from the Saccharomyces Genome Database (https://www.yeastgenome.org/).
- Design and defend the design of guide RNA and single stranded template for DNA repair in CRISPR/Cas9 gene editing studies to generate Saccharomyces cerevisiae auxotrophic mutants.
- Describe the qualities of the vector, pML104, that allow replication and selection in bacteria and yeast as well as allow expression of necessary factors in CRISPR/Cas9 genome editing, including Cas9 and sgRNA.
- Describe the rationale of and perform procedures necessary for cloning a small cassette (i.e., sgRNA gene) into a vector (i.e., pML104) including; restriction digest, annealing of DNA strands, removal of 5’ phosphates, ligation, and transformation.
- Recognize and design appropriate controls for cloning procedures such as ligation and transformation.
- Describe the method of polymerase chain reaction (PCR), including the rationale for essential components of a reaction mixture and thermal-cycling conditions.
- Locate the binding sites of and design primers for PCR, then report the expected size of the amplification product.
- Describe and perform isolation of plasmid DNA from E. coli.
- Describe the rationale for and perform procedures to transform yeast, including the essential components of a transformation mixture and conditions necessary for transformation.
- Describe the basic conditions required for cultivating yeast.
- Describe the rationale for and perform agarose gel electrophoresis of a given size of DNA.
- Analyze DNA separated by agarose gel electrophoresis, including size estimation.
- Recognize and describe the qualities of a template for DNA repair that allows efficient DNA repair.
- Design an experiment to determine auxotrophic phenotypes.
- Predict the outcome of multi-step experiments.
- Recognize and describe conditions necessary for growth of E. coli and S. cerevisiae.
- Qualitatively and quantitatively analyze scientific data from scientific experiments, including bacterial and yeast transformation, agarose gel electrophoresis, extraction of plasmid DNA from bacteria, PCR, and auxotroph phenotypic analysis.
- Communicate science to peers through maintenance of a laboratory notebook, verbal communication with group members, and writing of a formal laboratory report written in a format acceptable for journal publication.
- Troubleshoot scientific protocols by identifying procedures that are prone to error, comparing recommended protocols to actual procedure, and using positive and negative controls to narrow the location of a potential error.
- Communicate specific potential or actual uses of CRISPR/Cas9 in science and/or medicine.
- Use various bioinformatics approaches to analyze macromolecular primary sequence and structure.
- Illustrate how DNA is replicated and genes are transmitted from one generation to the next in multiple types of organisms including bacteria, eukaryotes, viruses, and retroviruses.
- Define what a genome consists of and how the information in various genes and other sequence classes within each genome are used to store and express genetic information.
- Explain the meaning of ploidy (haploid, diploid, aneuploid etc.) and how it relates to the number of homologues of each chromosome.
- Predict the effects of mutations on the activity, structure, or stability of a protein and design appropriate experiments to assess the effects of mutations.
- Predict the growth behavior of microbes based on their growth conditions, e.g., temperature, available nutrient, aeration level, etc.
- Discuss the benefits of specific tools of modern biotechnology that are derived from naturally occurring microbes (e.g. cloning vectors, restriction enzymes, Taq polymerase, etc.)
- Accurately prepare and use reagents and perform experiments.
- When presented with an observation, develop a testable and falsifiable hypothesis.
- When provided with a hypothesis, identify the appropriate experimental observations and controllable variables.
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Using QIIME to Interpret Environmental Microbial Communities in an Upper Level Metagenomics Course
Learning ObjectivesStudents will be able to:- list and perform the steps of sequence processing and taxonomic inference.
- interpret microbial community diversity from metagenomic sequence datasets.
- compare microbial diversity within and between samples or treatments.
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An Introduction to Eukaryotic Genome Analysis in Non-model Species for Undergraduates: A tutorial from the Genome...
Learning ObjectivesAt the end of the activity, students will be able to:- Explain the steps involved in genome assembly, annotation, and variant detection to other students and instructors.
- Create meaningful visualizations of their data using the integrated genome viewer.
- Use the Linux command line and web-based tools to answer research questions.
- Produce annotated genomes and call variants from raw sequencing reads in non-model species.
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Infectious Chocolate Joy with a Side of Poissonian Statistics: An activity connecting life science students with subtle...
Learning Objectives- Students will define a Poisson distribution.
- Students will generate a data set on the probability of a T cell being infected with a virus(es).
- Students will predict the likelihood of one observing the mean value of viruses occurring.
- Students will evaluate the outcomes of a random process.
- Students will hypothesize whether a process is Poissonian and design a test for that hypothesis.
- Students will collect data and create a histogram from their data.