BACKGROUND Have a gene involved in neurological disease, its function unclear Knockout is lethal, so… Designed a conditional knockout (cKO) mouse where.

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Presentation transcript:

BACKGROUND Have a gene involved in neurological disease, its function unclear Knockout is lethal, so… Designed a conditional knockout (cKO) mouse where gene is deleted from non-neuronal cell type in the brain Behavioral phenotype: obsessive-compulsive disorder We know the gene product regulates transcription Hypothesis: Changes in gene expression are responsible for phenotype

MODULE RESEARCH GOALS 1.Sample preparation Extract total RNA from optic nerves of test (cKO) and control (+/Cre;+/+ and +/+;flox/flox) animals and send for sequencing. 2.Computation Get list of differentially expressed genes. 3.Lead generation Pare list to manageable number of candidate genes (top 20) for follow-up by qRT-PCR.

STUDENT LEARNING GOALS 1.Experimental design Students will become familiar with the major anatomical features of the brain (cortex, cerebellum, hippocampus, striatum, thalamus, hypothalamus, prefrontal cortex) Students will be able to explain how a conditional knockout is designed and made. Students will be able to explain the current deep sequencing technologies (specifically, Illumina)

STUDENT LEARNING GOALS 2.Working with large datasets Students will become comfortable managing large datasets Students will become familiar with the Galaxy platform for managing datasets Students will have the option of learning script code Students will understand the principles of filtering data and be able to justify their choices for the filtering of data

STUDENT LEARNING GOALS 3.Application Students will identify the genes whose transcription has changed Students will be able to use gene ontology software to identify pathways whose constituent genes have substantial changes Students will take one of the genes from the putative target list and identify its key features including tissue expression, function, family members, isoforms, domain structure, etc.

STUDENT LEARNING GOALS 4.Communication Students will be able to assemble a coherent oral description of the Galaxy workflow Students will be able to clearly communicate the design of the experiment, including the design of the conditional knockout animal Students will have a final written report on one of the putative genes (see Student Learning Goals #3)

CORE COMPETENCIES 1.Apply the Process of Science Phenotype  Transcriptional Changes  RNA-Seq  Genes 2.Use Quantitative Reasoning Statistics Managing large data sets 3.Use Modeling and Simulation Modeling disease state through pathways

CORE COMPETENCIES 4.Tap Into the Interdisciplinary Nature of Science Molecular Biology  Behavior  Disease/Medicine  Statistics  Computation 5.Ability to Communicate and Collaborate with Other Disciplines Crowd sourcing Gene report/Final project Liberal Arts Symposium potential

CORE COMPETENCIES 6.Understand the Relationship Between Science and Society Genetic component of neurological behavior Using mouse models for human disease

GCAT-SEEK SEQUENCING REQUIREMENTS Any compatible RNA-seq platform Illumina used here 454, SOLiD also possibilities

ASSESSMENT Experimental design Weekly quizzes 3-4 page report RNAseq workflow Compare next-gen and microarrays Summary of RNAseq paper Working with large datasets/application Examine the effect of changing parameters Oral presentation: report back to group 10-page gene report

TIME LINE OF MODULE (1 SEMESTER) WeekMondayWednesdayFriday 1Biology backgroundNext-gen technologiesExperimental design 2 Student presentations on an RNAseq paper 3RNA and transcriptionRNA extractionBioanalyzer Library construction* 4Tuxedo workflow, Galaxy Processing sequences, examine output Changing parameters, submit history 5Lecture: de novo txtome sequencing Begin de novo assemblySubmit de novo assembly 6Lecture: mapping readsMap against reference transcriptome 7Compare de novo assembly with reference txtomeLearn/run Cuffmerge 8Learn/run CuffdiffLecture: StatsLecture: GO 9Learn/run GOGene lists, analysis of hits, database tools

REFERENCES Note: The module described uses a conditional knockout (cKO) mouse which has not yet been published. Therefore, we have intentionally left the details vague enough to protect our research interests, yet providing enough detail for an interested researcher to substitute our cKO mouse with his/her organism of choice for RNA-seq. When our paper on the cKO mouse has been accepted, we will update this file to reflect the citation and all relevant background material.