L. Samsa, M. Eslinger, Adam J. Kleinschmit, Amanda C Solem, Carlos C. Goller
{"title":"单细胞洞察癌症转录组:一个由五部分组成的单细胞RNAseq案例研究课程","authors":"L. Samsa, M. Eslinger, Adam J. Kleinschmit, Amanda C Solem, Carlos C. Goller","doi":"10.24918/cs.2021.26","DOIUrl":null,"url":null,"abstract":"There is a growing need for integration of “Big Data” into undergraduate biology curricula. Transcriptomics is one venue to examine biology from an informatics perspective. RNA sequencing has largely replaced the use of microarrays for whole genome gene expression studies. Recently, single cell RNA sequencing (scRNAseq) has unmasked population heterogeneity, offering unprecedented views into the inner workings of individual cells. scRNAseq is transforming our understanding of development, cellular identity, cell function, and disease. As a ‘Big Data,’ scRNAseq can be intimidating for students to conceptualize and analyze, yet it plays an increasingly important role in modern biology. To address these challenges, we created an engaging case study that guides students through an exploration of scRNAseq technologies. Students work in groups to explore external resources, manipulate authentic data and experience how single cell RNA transcriptomics can be used for personalized cancer treatment. This five-part case study is intended for upper-level life science majors and graduate students in genetics, bioinformatics, molecular biology, cell biology, biochemistry, biology, and medical genomics courses. The case modules can be completed sequentially, or individual parts can be separately adapted. The first module can also be used as a stand-alone exercise in an introductory biology course. Students need an intermediate mastery of Microsoft Excel but do not need programming skills. Assessment includes both students’ self-assessment of their learning as answers to previous questions are used to progress through the case study and instructor assessment of final answers. This case provides a practical exercise in the use of high-throughput data analysis to explore the molecular basis of cancer at the level of single cells. Citation: Samsa LA, Eslinger M, Kleinschmit A, Solem A, Goller CC. 2021. Single cell insights into cancer transcriptomes: A five-part single-cell RNAseq case study lesson. CourseSource. https:// doi.org/10.24918/cs.2021.26 Editor: William Morgan, College of Wooster Received: 10/6/2020; Accepted: 3/25/2021; Published: 9/24/2021 Copyright: © 2021 Samsa, Eslinger, Kleinschmit, Solem, and Goller. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. Conflict of Interest and Funding Statement: This case study is part of other cases created as part of the NSF HITS RCN network (NSF award: 1730317). Our goal is to raise awareness of the use of high-throughput approaches and datasets using case study pedagogies. Carlos C. Goller is also supported by an NIH Innovative Program to Enhance Research Training (IPERT) grant “Molecular Biotechnology Laboratory Education Modules (MBLEMs)” 1R25GM130528-01A1. None of the authors has a financial, personal, or professional conflict of interest related to this work. Supporting Materials: Supporting Files S1. scRNAseq – scRNAseq Case Study Parts 1-5 Student version; S2. scRNAseq – scRNAseq Case Study Parts 1-5 Answer key; S3. scRNAseq – Part 1 The patient and diagnosis Student version; S4. scRNAseq – Part 2 The technician and the samples Student version; S5. scRNAseq – Part 3 Data processing Student version; S6. scRNAseq – Part 4 Data visualization Student version; S7. scRNAseq – Part 5 Treatment Student version; S8. scRNAseq – Part 1 The patient and diagnosis Answer key; S9. scRNAseq – Part 2 The technician and the samples Answer key; S10. scRNAseq – Part 3 Data processing Answer key; S11. scRNAseq – Part 4 Data visualization Answer key; S12. scRNAseq – Part 5 Treatment Answer key; S13. scRNAseq – File for Part 2 Sequencing Metadata Student version; S14. scRNAseq – File for Part 2 Sequencing Metadata Instructor version; S15. scRNAseq – File for Part 2 Processing Datasheet Student version; S16. scRNAseq – File for Part 2 Processing Datasheet Instructor version; S17. scRNAseq – File for Part 3 Expression Student version; S18. scRNAseq – File for Part 3 Expression Instructor version; S19. scRNAseq – File for Part 3 Metadata Student version; S20. scRNAseq – File for Part 3 Metadata Instructor version; S21. scRNAseq – File for Part 3 Processing Notes Student version; S22. scRNAseq – File for Part 3 Processing Notes Instructor version; S23. scRNAseq – File from Part 4 Normalized Expression Instructor version; S24. scRNAseq – File from Part 4 Metadata with Clusters Instructor version; S25. scRNAseq – File from Part 4 DE PDX meta vs PDX primaryInstructor Version; and S26. scRNAseq – File for Part 5 Normalized Expression annotated for instructor. *Correspondence to co-corresponding authors: Leigh Ann Samsa: 123 W. Franklin St, Ste 600 B, Chapel Hill, NC 27516. Carlos Goller: Campus Box 7512, 6104 Jordan Hall, 2800 Faucette Drive Raleigh, NC 27695-7512. ccgoller@ncsu.edu CourseSource | www.coursesource.org 2021 | Volume 08 1 Lesson","PeriodicalId":72713,"journal":{"name":"CourseSource","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Single Cell Insights Into Cancer Transcriptomes: A Five-Part Single-Cell RNAseq Case Study Lesson\",\"authors\":\"L. Samsa, M. Eslinger, Adam J. Kleinschmit, Amanda C Solem, Carlos C. Goller\",\"doi\":\"10.24918/cs.2021.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is a growing need for integration of “Big Data” into undergraduate biology curricula. Transcriptomics is one venue to examine biology from an informatics perspective. 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引用次数: 0
Single Cell Insights Into Cancer Transcriptomes: A Five-Part Single-Cell RNAseq Case Study Lesson
There is a growing need for integration of “Big Data” into undergraduate biology curricula. Transcriptomics is one venue to examine biology from an informatics perspective. RNA sequencing has largely replaced the use of microarrays for whole genome gene expression studies. Recently, single cell RNA sequencing (scRNAseq) has unmasked population heterogeneity, offering unprecedented views into the inner workings of individual cells. scRNAseq is transforming our understanding of development, cellular identity, cell function, and disease. As a ‘Big Data,’ scRNAseq can be intimidating for students to conceptualize and analyze, yet it plays an increasingly important role in modern biology. To address these challenges, we created an engaging case study that guides students through an exploration of scRNAseq technologies. Students work in groups to explore external resources, manipulate authentic data and experience how single cell RNA transcriptomics can be used for personalized cancer treatment. This five-part case study is intended for upper-level life science majors and graduate students in genetics, bioinformatics, molecular biology, cell biology, biochemistry, biology, and medical genomics courses. The case modules can be completed sequentially, or individual parts can be separately adapted. The first module can also be used as a stand-alone exercise in an introductory biology course. Students need an intermediate mastery of Microsoft Excel but do not need programming skills. Assessment includes both students’ self-assessment of their learning as answers to previous questions are used to progress through the case study and instructor assessment of final answers. This case provides a practical exercise in the use of high-throughput data analysis to explore the molecular basis of cancer at the level of single cells. Citation: Samsa LA, Eslinger M, Kleinschmit A, Solem A, Goller CC. 2021. Single cell insights into cancer transcriptomes: A five-part single-cell RNAseq case study lesson. CourseSource. https:// doi.org/10.24918/cs.2021.26 Editor: William Morgan, College of Wooster Received: 10/6/2020; Accepted: 3/25/2021; Published: 9/24/2021 Copyright: © 2021 Samsa, Eslinger, Kleinschmit, Solem, and Goller. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. Conflict of Interest and Funding Statement: This case study is part of other cases created as part of the NSF HITS RCN network (NSF award: 1730317). Our goal is to raise awareness of the use of high-throughput approaches and datasets using case study pedagogies. Carlos C. Goller is also supported by an NIH Innovative Program to Enhance Research Training (IPERT) grant “Molecular Biotechnology Laboratory Education Modules (MBLEMs)” 1R25GM130528-01A1. None of the authors has a financial, personal, or professional conflict of interest related to this work. Supporting Materials: Supporting Files S1. scRNAseq – scRNAseq Case Study Parts 1-5 Student version; S2. scRNAseq – scRNAseq Case Study Parts 1-5 Answer key; S3. scRNAseq – Part 1 The patient and diagnosis Student version; S4. scRNAseq – Part 2 The technician and the samples Student version; S5. scRNAseq – Part 3 Data processing Student version; S6. scRNAseq – Part 4 Data visualization Student version; S7. scRNAseq – Part 5 Treatment Student version; S8. scRNAseq – Part 1 The patient and diagnosis Answer key; S9. scRNAseq – Part 2 The technician and the samples Answer key; S10. scRNAseq – Part 3 Data processing Answer key; S11. scRNAseq – Part 4 Data visualization Answer key; S12. scRNAseq – Part 5 Treatment Answer key; S13. scRNAseq – File for Part 2 Sequencing Metadata Student version; S14. scRNAseq – File for Part 2 Sequencing Metadata Instructor version; S15. scRNAseq – File for Part 2 Processing Datasheet Student version; S16. scRNAseq – File for Part 2 Processing Datasheet Instructor version; S17. scRNAseq – File for Part 3 Expression Student version; S18. scRNAseq – File for Part 3 Expression Instructor version; S19. scRNAseq – File for Part 3 Metadata Student version; S20. scRNAseq – File for Part 3 Metadata Instructor version; S21. scRNAseq – File for Part 3 Processing Notes Student version; S22. scRNAseq – File for Part 3 Processing Notes Instructor version; S23. scRNAseq – File from Part 4 Normalized Expression Instructor version; S24. scRNAseq – File from Part 4 Metadata with Clusters Instructor version; S25. scRNAseq – File from Part 4 DE PDX meta vs PDX primaryInstructor Version; and S26. scRNAseq – File for Part 5 Normalized Expression annotated for instructor. *Correspondence to co-corresponding authors: Leigh Ann Samsa: 123 W. Franklin St, Ste 600 B, Chapel Hill, NC 27516. Carlos Goller: Campus Box 7512, 6104 Jordan Hall, 2800 Faucette Drive Raleigh, NC 27695-7512. ccgoller@ncsu.edu CourseSource | www.coursesource.org 2021 | Volume 08 1 Lesson