Front Cover

Brain Transcriptome

Copyright

Contents

Contributors

Chapter One: Introduction to Sequencing the Brain Transcriptome

1. Introduction

2. From Microarrays to RNA-Seq

3. NGS Platforms

4. RNA-Seq Overview

5. RNA-Seq and Data Analysis

6. Sequencing the Brain Transcriptome

7. Conclusions

Acknowledgments

References

Chapter Two: Analysis Considerations for Utilizing RNA-Seq to Characterize the Brain Transcriptome

1. Introduction

2. Defining and Quantifying Transcript/Gene Expression

2.1. Step 1: Alignment of RNA-Seq reads to a reference sequence

2.1.1. Splice-aware aligners

2.1.2. Sequence variations between the short read and reference sequence

2.1.3. Uniquely mapping or multimapping reads

2.2. Step 2: Transcriptome reconstruction

2.2.1. Genome guided

2.2.2. Genome independent

2.3. Step 3: Quantification of expression levels

3. Detecting Differential Expression

3.1. The need for normalization

3.2. Inferring putative DE

3.3. Outliers, subgroups, and individual expression

3.4. Isoform-specific DE

4. Frameworks for Interpretation

4.1. RNA-Seq library construction

4.2. Gene-model databases

4.3. Functional annotation databases

5. Summary

References

Further Reading

Chapter Three: Data Integration and Reproducibility for High-Throughput Transcriptomics

1. Opportunities for Secondary Use of Data and Meta-Anlaysis in Transcriptomics

1.1. Transcriptomics platforms

2. Selecting the Unit of Comparison

3. Metrics for Agreement

4. Studies on Reproducibility and Validation

5. Guidelines for Cross-Platform Studies

6. Other Data Integration Considerations

6.1. Multi-omic data integration

6.2. Cross-species comparisons

7. Summary

References

Chapter Four: Coexpression and Cosplicing Network Approaches for the Study of Mammalian Brain Transcriptomes

1. Introduction

2. Construction of Coexpression and Cosplicing Networks

3. Cosplicing Network Construction

4. Biological Annotation of Coexpression and Cosplicing Networks

5. Effects of Genetic Selection on Gene Networks

6. Module Preservation Across Subpopulations and Species

7. Module Disruption Related to Behavioral Changes

8. Summary and Future Directions

References

Chapter Five: Splicing in the Human Brain

1. Pre-mRNA Splicing in Human Cells

2. Alternative Pre-mRNA Splicing

3. Tissue-Specific Alternative Splicing

4. Alternative Splicing in the Brain

5. Brain-Specific Splicing Regulation

6. Transcription-Coupled Regulation of Alternative Splicing

7. Cotranscriptional and Posttranscriptional Splicing

8. Global Analysis of Pre-mRNA Splicing

9. The Influence of RNA Extraction Methods on Transcriptome Analysis

10. Computational Methods to Study Splicing Dynamics

References

Chapter Six: Understanding Complex Transcriptome Dynamics in Schizophrenia and Other Neurological Diseases Using RNA Seque ...

1. Introduction

2. RNA-Seq Studies on Neurological Disorders

2.1. Study design

2.2. Sequencing platforms and strategies

2.3. Data analysis

3. Quantifying Transcriptome Dynamics in Neurological Disorders

3.1. Gene/transcript expression

3.1.1. Synaptic plasticity and neurotransmission

3.1.2. Inflammatory/immune pathways

3.2. Alternative splicing

3.3. Allele-specific expression

3.4. RNA editing

3.5. Integrative analysis

3.6. Noncoding RNA alterations in neurological disorders

4. Discussion and Perspectives

References

Chapter Seven: The Central Role of Noncoding RNA in the Brain

1. Introduction

2. The Long and Short of Noncoding RNAs

2.1. Short noncoding RNAs

2.2. Long noncoding RNAs

3. Types and Function of lncRNAs

3.1. Current lncRNA classification according to origin and function

4. RNA Structure

5. Splicing

6. NcRNA Editing

7. Epigenetic Modifications

8. ncRNAs Are Involved in Neuronal Development, Maintenance, and Plasticity

8.1. Stimuli depend on expression, specificity, and memory

9. Evolutionary Role of ncRNAs and Primate Specificity

10. The Role of (Retro)transposons and Pseudogenes in ncRNA Evolution

11. ncRNAs and Disease

11.1. Alzheimer´s disease

11.2. Schizophrenia

11.3. Autism spectrum disorder

11.4. Parkinson´s disease

11.5. Angelman syndrome

11.6. Huntington´s disease

11.7. ncRNA as biomarkers

12. Perspectives and Outlook

Acknowledgments

References

Chapter Eight: Genetics of Gene Expression in CNS

1. Introduction

1.1. The history

1.2. How much variation is there in gene expression in brain?

1.3. Brain gene expression studies-A summary

1.4. Missing pieces

1.5. Genetic architecture of expression traits

1.6. RNA-seq to the rescue?

1.7. RNA-seq data generation

2. Genetic Resources for eQTL Analysis in Mice

2.1. Intercross progeny

2.2. RI strains

2.3. The BXD family

2.4. Heterogeneous stock

2.5. The Collaborative Cross

3. Genetic Mapping Methods

3.1. Single marker test

3.2. Interval mapping

3.3. Composite interval mapping

3.4. Evaluation of mapping precision

4. RNA-seq eQTL Studies

5. Pros and Cons of Arrays and RNA-seq for eQTL Studies

5.1. Advantages of arrays

5.2. Advantages of RNA-seq

6. RNA-seq Read Alignment and Normalization

6.1. Allelic bias in read mapping

6.2. Correct normalization of RNA-seq counts

7. eQTL Mapping of Alternative Splicing and Polyadenylation

8. RNA-seq for Allele-Specific Expression

8.1. Key factors in design of genomewide ASE

8.2. Advantages and disadvantages of ASE

9. Conclusions

Acknowledgments

References

Chapter Nine: Transcriptomic Changes in Brain Development

1. Introduction

2. Gene Expression

3. DNA Sequence Variation and Epigenetic Modification in Brain Development

4. Alternative Splicing

5. RNA Editing

6. Noncoding RNA

7. Summary

References

Chapter Ten: Gene Expression in the Addicted Brain

1. Introduction

2. Molecular Adaptations Accompanying Early Response and Long-Term Adaptations in the Addicted Brain

3. Substance-Specific and Shared Gene Expression Changes in Addicted Brain

4. Region-Specific Gene Expression Changes in Addicted Brain

5. Perturbation of the Glutamatergic System in Addicted Brain

6. Epigenetic Regulation of Gene Expression in Addicted Brain

7. Conclusion

References

Chapter Eleven: RNA-Seq Reveals Novel Transcriptional Reorganization in Human Alcoholic Brain

1. Overview

2. RNA-Seq of Postmortem Brain Tissue

3. Detection of Technical Biases in RNA-Seq Data

4. Normalization of RNA-Seq Data

5. Alternative Splicing and Differential Expression

6. Long Noncoding RNA

7. Novel Three Prime Untranslated Regions

8. Genetic Variation and Alcohol Dependence

9. Biological Coexpression Networks

10. Future Directions

References

Index

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