Transcriptome Profiling
Progress and Prospects
- 1st Edition - October 7, 2022
- Imprint: Academic Press
- Editors: Mohammad Ajmal Ali, Joongku Lee
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 1 8 1 0 - 7
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 7 2 3 1 - 4
Transcriptome Profiling: Progress and Prospects assists readers in assessing and interpreting a large number of genes, up to and including an entire genome. It provides key insig… Read more
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Request a sales quoteTranscriptome Profiling: Progress and Prospects assists readers in assessing and interpreting a large number of genes, up to and including an entire genome. It provides key insights into the latest tools and techniques used in transcriptomics and its relevant topics which can reveal a global snapshot of the complete RNA component of a cell at a given time. This snapshot, in turn, enables the distinction between different cell types, different disease states, and different time points during development.
Transcriptome analysis has been a key area of biological inquiry for decades. The next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution. Transcriptome analysis has evolved from the detection of single RNA molecules to large-scale gene expression profiling and genome annotation initiatives.
Written by a team of global experts, key topics in Transcriptome Profiling include transcriptome characterization, expression analysis of transcripts, transcriptome and gene regulation, transcriptome profiling and human health, medicinal plants transcriptomics, transcriptomics and genetic engineering, transcriptomics in agriculture, and phylotranscriptomics.
- Presents recent development in the tools and techniques in transcriptomic characterization
- Integrates expression analysis of transcripts and gene regulation
- Includes the application of transcriptomics in human health, genetic engineering and agriculture
Graduates and Professionals; Academics in Biological Sciences, Molecular biologist, Bioinformatician
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Preface
- Chapter 1. Transcriptomic analysis of genes: expression and regulation
- Abstract
- Outline
- 1.1 Techniques for transcription analysis and RNA-seq profiling
- 1.2 Sequencing platforms and gene analysis workflow for genome and transcriptome assembly
- 1.3 Expression and differential expression analysis: methods and programs
- 1.4 Data integration techniques for coexpression network construction
- 1.5 Gene regulation studies on bacteria and fungi
- 1.6 Application of transcriptomics to the study of small RNAs, transcription factors, heat shock factors, kinases (MAPK), PCR, and metabolite production
- 1.7 Transcriptomic studies of genetic engineering approaches
- 1.8 Application of transcriptomics in the context of diseases and clinical studies
- References
- Chapter 2. Transcriptomics and genetic engineering
- Abstract
- Outline
- 2.1 Introduction
- 2.2 History
- 2.3 Transcriptomics
- 2.4 Gene ontology
- 2.5 Genetic engineering approaches to target the transcriptome
- 2.6 Model organisms for transcriptome research
- 2.7 Challenges and conclusion
- Authors contributions
- Financial support
- Competing interests
- Acknowledgements
- References
- Further reading
- Chapter 3. Single-cell transcriptomics
- Abstract
- Outline
- 3.1 Introduction
- 3.2 Measurement techniques in single-cell transcriptomics
- 3.3 Noise in single-cell sequencing
- 3.4 Preprocessing of 10X scRNAseq data
- 3.5 Analysis of 10X scRNAseq data
- References
- Chapter 4. Time course gene expression experiments
- Abstract
- Outline
- 4.1 Introduction
- 4.2 Designing time course experiments
- 4.3 A holistic method to analyze time course gene expression experiments
- 4.4 Conclusions and perspectives
- 4.5 Appendix: standardized expression profile estimation
- References
- Chapter 5. Measurement and meaning in gene expression evolution
- Abstract
- Outline
- 5.1 Introduction
- 5.2 What is gene expression?
- 5.3 Gene expression evolution
- 5.4 Measuring gene expression
- 5.5 Measuring gene expression evolution
- Acknowledgments
- References
- Chapter 6. G-quadruplexes as key motifs in transcriptomics
- Abstract
- Outline
- Abbreviations
- 6.1 Introduction
- 6.2 G-quadruplexes
- 6.3 Approaches to identify G4s
- 6.4 Functions of G4s
- 6.5 Genome instability associated to G4s
- 6.6 G4-binding proteins
- 6.7 G4s’ involvement in disease
- 6.8 G4 Ligands
- 6.9 Future perspectives
- References
- Chapter 7. Spatial transcriptomics
- Abstract
- Outline
- 7.1 An introduction to spatial transcriptomics
- 7.2 Origin of spatial transcriptomics
- 7.3 Implementation of a spatial transcriptomics study: tools and techniques
- 7.4 Applications and impact of spatial transcriptomics
- 7.5 Perspectives
- References
- Chapter 8. Desert plant transcriptomics and adaptation to abiotic stress
- Abstract
- Outline
- 8.1 Introduction
- 8.2 Potential of desert plant research
- 8.3 Strategies for gene discovery in desert plants
- 8.4 Current state of desert plant transcriptomics
- 8.5 Drought stress
- 8.6 Salinity stress
- 8.7 Heat and cold stress
- 8.8 Oxidative stress
- 8.9 Identification of lncRNA as key regulators in adaptation to abiotic stress
- 8.10 Conclusions and perspectives
- References
- Chapter 9. Transcriptomics in agricultural sciences: capturing changes in gene regulation during abiotic or biotic stress
- Abstract
- Outline
- 9.1 Application of transcriptomics in breeding
- 9.2 Transcriptomics and plant interactions: from genes to the field
- 9.3 Transcriptomics and breeding of orphan crops
- 9.4 Transcriptomic technology for gene identification: expression regulation for biotic stress resistance, quality traits, signal transduction reactions, and defense responses
- 9.5 Advances in transcriptomic analysis of multiple abiotic stresses
- 9.6 RNA-seq coupled with other genomic tools in agricultural sciences: multiomics technologies to study metabolism during multiple stress responses
- References
- Chapter 10. Transcriptomics in response of biotic stress in plants
- Abstract
- Outline
- 10.1 Introduction
- 10.2 Methodology of RNA-seq analysis
- 10.3 Transcriptome analysis of biotic stress response in crop plants
- 10.4 Conclusion
- References
- Chapter 11. Functional genomics to understand the tolerance mechanism against biotic and abiotic stresses in Capsicum species
- Abstract
- Outline
- 11.1 Introduction
- 11.2 Economic and medicinal importance of Capsicum
- 11.3 Impact of stresses on Capsicum
- 11.4 Application of omics tools towards understanding the plant responses against various stresses and their tolerance mechanisms
- 11.5 Functional genomics of biotic and abiotic stress responses in Capsicum
- 11.6 Developing stress-tolerant Capsicum cultivars
- 11.7 Concluding remarks
- References
- Further reading
- Chapter 12. Transcriptomic and epigenomic network analysis reveals chicken physiological reactions against heat stress
- Abstract
- Outline
- 12.1 Introduction
- 12.2 The importance of knowing nonadapted and adaptation-specific biological reaction mechanisms
- 12.3 Strategy
- 12.4 Comparison of two chicken heart and muscle transcriptome datasets
- 12.5 Comparison of transcriptome and epigenome datasets
- 12.6 General reactions of adapted and not-adapted chicken types to heat stress
- 12.7 Conclusions
- Perspectives
- Acknowledgment
- References
- Chapter 13. Transcriptome-wide identification of immune-related genes after bacterial infection in fish
- Abstract
- Outline
- 13.1 Introduction
- 13.2 Importance of transcriptome in aquaculture
- 13.3 Concept of transcriptome workflow in fish
- 13.4 Fish immune response post bacterial infection
- 13.5 Conclusion
- References
- Chapter 14. Human transcriptome profiling: applications in health and disease
- Abstract
- Outline
- 14.1 Introduction
- 14.2 A brief history of transcriptomics
- 14.3 Microarrays
- 14.4 RNA-seq
- 14.5 Single-cell transcriptomics
- 14.6 Conclusion and future perspectives
- References
- Chapter 15. Transcriptomics to devise human health and disease
- Abstract
- Outline
- 15.1 Introduction
- 15.2 Transcriptomics
- 15.3 Transcriptomics of noncoding RNAs
- 15.4 Application of transcriptomics
- 15.5 System biology: integration of omics
- 15.6 Conclusions
- References
- Chapter 16. Single-cell/nucleus transcriptomic and muscle pathologies
- Abstract
- Outline
- 16.1 Methods and technologies for single-cell/nucleus RNA sequencing
- 16.2 Advantages and disadvantages of using single-cell/nucleus analysis
- 16.3 Different muscles and different functions
- 16.4 Single-cell/nucleus analysis in skeletal muscle. What does the dimension of the cells (myofibers) allow or not allow to do?
- 16.5 Single-cell/nucleus analysis in heart
- 16.6 Single-cell analysis in smooth muscles
- 16.7 Single-cell/nucleus RNA-seq bioinformatics analysis
- 16.8 Discussion and conclusions
- References
- Chapter 17. Transcriptomics of intracranial aneurysms
- Abstract
- Outline
- 17.1 Introduction
- 17.2 Intracranial aneurysms
- 17.3 Transcriptomics of intracranial aneurysms
- 17.4 Transcriptomics of unruptured and ruptured intracranial aneurysms
- 17.5 Blood transcriptomic fingerprints of intracranial aneurysms
- 17.6 Immune cell transcriptomic fingerprints of intracranial aneurysms
- 17.7 Concluding remarks
- References
- Chapter 18. Recent advances in transcriptomic biomarker detection for cancer
- Abstract
- Outline
- 18.1 Introduction
- 18.2 The evolution of transcriptomic methods
- 18.3 Cancer biomarkers currently in clinical use
- 18.4 Steps of clinical biomarker development in cancer
- 18.5 Cancer data availability in the form of database
- 18.6 Application of machine learning in biomarker identification
- 18.7 Conclusion
- References
- Chapter 19. Future prospects of transcriptomics
- Abstract
- Outline
- 19.1 Transcriptome: regulatory mechanisms
- 19.2 Current perspectives in the field of transcriptomics and health
- 19.3 Translational transcriptomics of cancer
- 19.4 Translational transcriptomics of obesity
- 19.5 Epitranscriptomics
- 19.6 Types of significant RNA modifications
- 19.7 Final considerations
- References
- Index
- Edition: 1
- Published: October 7, 2022
- Imprint: Academic Press
- No. of pages: 528
- Language: English
- Paperback ISBN: 9780323918107
- eBook ISBN: 9780323972314
MA
Mohammad Ajmal Ali
Mohammad Ajmal Ali is an Associate Professor in the Department of Botany and Microbiology at King Saud University in Riyadh, Saudi Arabia, where he has taught molecular biology and bionanotechnology since 2010. He received his M.S. (1999) and Ph.D. (2006) degrees in Botany from TM Bhagalpur University in Bihar, India, and pursued postdoctoral research at Korea Research Institute of Biosciences and Biotechnology in Daejeon, South Korea. Ali's research program encompasses next-generation sequencing, computational chemistry, bioprospecting and bionanotechnology. He has authored/co-authored eight books and over 200 research articles in more than 52 journals of international repute.
Affiliations and expertise
Associate Professor, Department of Botany and Microbiology, King Saud University, Riyadh, Saudi ArabiaJL
Joongku Lee
Joongku Lee is a Professor in the Department of Environment and Forest Resources at Chungnam National University in Daejeon, South Korea. He received Ph.D. (1998) from the Department of Biology at SungKyunKwan University, South Korea. He conducted postdoctoral work at Jepson Herbarium and Department of Integrative Biology at the University of California, Berkeley, USA. Lee’s present research program encompasses next-generation sequencing, bioprospecting, and plant phylogeny. He has authored/co-authored 17 books and 171 publications.
Affiliations and expertise
Professor, Department of Environment and Forest Resources, Chungnam National University, Daejeon, South KoreaRead Transcriptome Profiling on ScienceDirect