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Neurogenomics of Behavioral Plasticity

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Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 781))

Abstract

Across animals, there is remarkable diversity in behavior. Modern genomic approaches have made it possible to identify the molecular underpinnings of varied behavioral phenotypes. By examining species with plastic phenotypes we have begun to understand the dynamic and flexible nature of neural transcriptomes and identified gene modules associated with variation in social and reproductive behaviors in diverse species. Importantly, it is becoming increasingly clear that some candidate genes and gene networks are involved in complex social behaviors across even divergent species, yet few comparative transcriptomics studies have been conducted that examine a specific behavior across species. We discuss the implications of a range of important and insightful studies that have increased our understanding of the neurogenomics of behavioral plasticity. Despite its successes, behavioral genomics has been criticized for its lack of hypotheses and causative insights. We propose here a novel avenue to overcome some of these short-comings by complementing “forward genomics” studies (i.e., from phenotype to behaviorally relevant gene modules) with a “reverse genomics” approach (i.e., manipulating novel gene modules to examine effects on behavior, hormones, and the genome itself) to examine the functional causes and consequences of differential gene expression patterns. We discuss how several established approaches (such as pharmacological manipulations of a novel candidate pathway, fine scale mapping of novel candidate gene expression in the brain, or identifying direct targets of a novel transcription factor of interest) can be used in combination with the analysis of the accompanying neurogenomic responses to reveal unexpected biological processes. The integration of forward and reverse genomics will move the field beyond statistical associations and yield great insights into the neural and molecular control of social behavior and its evolution.

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Acknowledgments

Research in our lab has been supported by NSF, NIH-NIGMS, and the Alfred P. Sloan Foundation. We want to thank the editors for giving us the opportunity to review the state of our field; Jeff Gross, Suzy Renn, and members of the Matz Lab and the Hofmann Lab for discussion; and Ryan Wong and two anonymous reviewers for helpful comments on earlier versions of this chapter.

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Correspondence to Hans A. Hofmann .

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Glossary

Bisulfite sequencing

The use of a bisulfite treatment of DNA followed by deep sequencing to determine the methylation pattern.

Chromatin immunoprecipitation sequencing (ChIP-seq)

The use of high-throughput sequencing technologies to sequence the regions of the genome that interact with a given protein of interest, often a transcription factor.

Deep sequencing

The process of obtaining both the sequence and frequency of RNA or DNA molecules in a given tissue at a given time through any number of next-generation sequencing technologies.

Dopaminergic reward processing

The role that dopamine plays in the integration of environmental and physiological cues and the encoding of the rewarding properties of a stimulus to generate an adaptive behavioral response.

Gene network

A statistical representation of correlated gene expression data for identifying sets of co-regulated genes or gene modules.

Gene module

A set of co-regulated genes.

Immediate early genes (IEGs)

Genes, usually encoding transcription factors, that are rapidly and transiently activated in response to a wide variety of cellular and extracellular stimuli.

Mating system

A classification of the time, place, and number of partners an individual has during reproduction.

Microarray

An array of thousands of RNA, cDNA, or DNA probes, usually printed on a glass slide with which the activity of thousands of genes can be assayed simultaneously.

Next-generation (NextGen) Sequencing (also referred to as high-throughput sequencing)

Any of a number of technologies that yield millions of sequences concurrently by parallelizing the sequencing process, thereby significantly lowering the cost of sequencing while increasing the amount of data.

Nucleus accumbens (NAcc)

A mesolimbic brain region that receives massive dopaminergic input from the VTA and is intimately involved in evaluating stimulus salience and reward processing.

Preoptic area (POA)

A region of the forebrain that is important for regulating many social behaviors in males and females as well as other basic physiological functions such as energy homeostasis and thermoregulation.

Quantitative PCR (qPCR)

A molecular technique used to amplify and simultaneously quantify a targeted DNA or RNA molecule.

Reproductive tactic

Behavioral strategy used by individuals to increase their reproductive success.

RNA sequencing (RNA-seq)

The use of high-throughput sequencing for quantitative analysis of short cDNA reads.

Small interfering RNA (siRNA)

A class of double stranded RNA molecules, usually 20–25 base pairs, that interferes with the expression of genes with complementary sequence.

Social dominance

High status or hierarchical rank in a social group.

Striato-pallidal Area X

A region of the songbird brain that has been linked to singing. It is part of the basal ganglia, a set of nuclei that have been widely implicated in motor control and learning.

Transcription factor binding site

Short stretches of DNA where other molecules, specifically transcription factors that regulate gene activity, can bind.

Transcriptome

The set of all the expressed RNA molecules (or a subset, e.g., mRNA) in a given tissue or cell.

Ventral tegmental area (VTA)

A region of the brain that is major source of dopamine in the brain. It plays an important role in evaluating the salience of environmental stimuli and signaling motivational events.

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Harris, R.M., Hofmann, H.A. (2014). Neurogenomics of Behavioral Plasticity. In: Landry, C., Aubin-Horth, N. (eds) Ecological Genomics. Advances in Experimental Medicine and Biology, vol 781. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7347-9_8

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