Genes, behavior and next‐generation RNA sequencing

Hitzemann, R.; Bottomly, D.; Darakjian, P.; Walter, N.; Iancu, O.; Searles, R.; Wilmot, B.; McWeeney, S.

doi:10.1111/gbb.12007

Cited by 88Genomics and Phylogenetic StudiesSingle-cell and spatial transcriptomicsGene expression and cancer classification

Genes, behavior and next‐generation RNA sequencing

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Hitzemann, R., Bottomly, D., Darakjian, P., Walter, N., Iancu, O., Searles, R., Wilmot, B., McWeeney, S.·2013·Genes, Brain and Behavior

DOI 10.1111/gbb.12007PMC PMC6050050

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Abstract

Advances in next‐generation sequencing suggest that RNA‐Seq is poised to supplant microarray‐based approaches for transcriptome analysis. This article briefly reviews the use of microarrays in the brain‐behavior context and then illustrates why RNA‐Seq is a superior strategy. Compared with microarrays, RNA‐Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, detects allele specific expression and can be used to extract genotype information, e.g. nonsynonymous coding single nucleotide polymorphisms. Examples of where RNA‐Seq has been used to assess brain gene expression are provided. Despite the advantages of RNA‐Seq, some disadvantages remain. These include the high cost of RNA‐Seq and the computational complexities associated with data analysis. RNA‐Seq embraces the complexity of the transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain‐behavior relationship is substantial.

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RNA-seq carries technical and biological biases, such as dependence on library preparation, sequencing depth, gene length, GC content, transcript length, and laboratory-specific practices.
“These include dependencies on library preparation, sequencing depth, gene lengths, GC content and transcript lengths, as well as other laboratory-specific practices (Hitzemann et al., 2013).”
From Guidance for RNA-seq co-expression network construction and analysis: safety in numbers (2015) · cites this paper as Hitzemann et al., 2013

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Authors: Hitzemann, R., Bottomly, D., Darakjian, P., Walter, N., Iancu, O., Searles, R., Wilmot, B., & McWeeney, S.
Affiliations: Oregon Health & Science University (US)
Corresponding author: Hitzemann, R.
ORCID: Bottomly, D.
Walter, N.
Searles, R.
Wilmot, B.
McWeeney, S.
Venue: Genes, Brain and Behavior
Publisher: Wiley
Published: 2012-12-28
Volume: 12
Issue: 1
Pages: 1-12
ISSN: 1601-183X (ISSN-L)
1601-1848
DOI: 10.1111/gbb.12007
PMC: PMC6050050
OpenAlex: W1777871578
Cited by: 88
References: 125
Citations by year: 2025: 3 · 2024: 1 · 2023: 4 · 2022: 3 · 2021: 14 · 2020: 6 · 2019: 7 · 2018: 6 · 2017: 3 · 2016: 8 · 2015: 11 · 2014: 15 · 2013: 7
FWCI: 0.96
Type: journal article
Language: en
Open access: green
europepmc.org
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Genes Brain & Behavior (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health (UL1TR000128)
National Institute on Alcohol Abuse and Alcoholism (R01AA011034, AA 13484, AA 10760, U01AA013484, P50AA010760, AA11034)
National Institute of Mental Health (MH 51372, R01MH051372)
National Center for Advancing Translational Sciences
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords: RNA-seq, microarray, gene expression profiling, brain gene expression, gene expression regulation, alternative splicing, non-coding RNA, allele-specific expression, single nucleotide polymorphisms, gene networks, brain-behavior relationship
MeSH terms: Animals, Brain, Genes, Humans, Sequence Analysis, RNA, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, High-Throughput Nucleotide Sequencing

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