ReviewGenes, brain, and behavior2013
Genes, behavior and next-generation RNA sequencing.
Review in Genes, brain, and behavior, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
46 citing papers in PubMed.
- Your Blood is Out for Delivery: Considerations of Shipping Time and Temperature on Degradation of RNA from Stabilized Whole Blood.Analytical chemistry · 2025Article
- Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models.Current topics in behavioral neurosciences · 2025Review
- Your Blood is Out for Delivery: Considerations of Shipping Time and Temperature on Degradation of RNA from Stabilized Whole Blood.bioRxiv : the preprint server for biology · 2024Article
- Particulate matter impairs immune system function by up-regulating inflammatory pathways and decreasing pathogen response gene expression.Scientific reports · 2023Article
- Optimization of RNA extraction for bacterial whole transcriptome studies of low-biomass samples.iScience · 2022Article
- Article
- SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data.Journal of statistical software · 2021Article
- Differential regulation of alcohol consumption and reward by the transcriptional cofactor LMO4.Molecular psychiatry · 2021Article
- Repeated morphine exposure activates synaptogenesis and other neuroplasticity-related gene networks in the dorsomedial prefrontal cortex of male and female rats.Drug and alcohol dependence · 2021Article
- High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis.Human genomics · 2021Article
- On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption.Frontiers in psychiatry · 2021Review
- Expression Profiles of Circular RNAs in Human Papillary Thyroid Carcinoma Based on RNA Deep Sequencing.OncoTargets and therapy · 2021Article
- Experimental Strategies to Explore Drug Action and Resistance in Kinetoplastid Parasites.Microorganisms · 2020Review
- Non-coding RNAs in neuropathic pain.Neuronal signaling · 2020Review
- RNA-Seq Analysis of Genetic and Transcriptome Network Effects of Dual-Trait Selection for Ethanol Preference and Withdrawal Using SOT and NOT Genetic Models.Alcoholism, clinical and experimental research · 2020Article
- Function of fibroblast growth factor 2 in gastric cancer occurrence and prognosis.Molecular medicine reports · 2020Article
- Transcriptomic Analysis of Testicular Gene Expression in Normal and Cryptorchid Horses.Animals : an open access journal from MDPI · 2020Article
- Expression profiles of circular RNAs in human colorectal cancer based on RNA deep sequencing.Journal of clinical laboratory analysis · 2019Article
- Regional Analysis of the Brain Transcriptome in Mice Bred for High and Low Methamphetamine Consumption.Brain sciences · 2019Article
- Studying alcohol use disorder using Drosophila melanogaster in the era of 'Big Data'.Behavioral and brain functions : BBF · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.