Elsevier

Hormones and Behavior

Volume 127, January 2021, 104882
Hormones and Behavior

Specificity in sociogenomics: Identifying causal relationships between genes and behavior

https://doi.org/10.1016/j.yhbeh.2020.104882Get rights and content

Highlights

  • Increased specificity is important for characterizing heterogeneous sub-cortical brain regions that regulate innate behaviors

  • Capturing active neuronal populations can improve transcriptomic specificity

  • Single-cell approaches can reveal cell types that differ across species

Abstract

There has been rapid growth in the use of transcriptomic analyses to study the interplay between gene expression and behavior. Experience can modify gene expression in the brain, leading to changes in internal state and behavioral displays, while gene expression variation between species is thought to specify many innate behavior differences. However, providing a causal association between a gene and a given behavior remains challenging as it is difficult to determine when and where a gene contributes to the function of a behaviorally-relevant neuronal population. Moreover, given that there are fewer genetic tools available for non-traditional model organisms, transcriptomic approaches have been largely limited to profiling of bulk tissue, which can obscure the contributions of subcortical brain regions implicated in multiple behaviors. Here, we discuss how emerging single cell technologies combined with methods offering additional spatial and connectivity information can give us insight about the genetic profile of specific cells involved in the neural circuit of target social behaviors. We also emphasize how these techniques are broadly adaptable to non-traditional model organisms. We propose that, ultimately, a combination of these approaches applied throughout development will be key to discerning how genes shape the formation of social behavior circuits.

Introduction

As described by Robinson, Fernald, and Clayton, two principal lines of investigation in the field of sociogenomics are 1) understanding how social experiences modify gene expression to produce lasting effects on brain function and 2) understanding how information encoded in the genome leads to a unique repertoire of social behaviors (Robinson et al., 2008). A central challenge in addressing these questions is identifying neuronal populations in which expression of a given candidate gene shows some kind of causality for or effect from the behavior of interest. Moreover, most genetic gain- or loss-of function experiments, have implicated brain regions in behavior rather than genetically-defined cell types, leading to studies focusing on gene expression in bulk tissue dissections. This has been the case for quantitative trait locus (QTL) analyses, which have revealed many loci that associate with a behavioral trait, but cannot address how specific neural substrates mediate such traits. Given that brain regions are highly heterogeneous, it is likely that only a subset of cells in a given region are uniquely contributing to the behavior of interest, and the differential gene expression signal from these cells may be lost in the noise from their neighbors, making it difficult to identify genes involved in specific behaviors.

An example of this idea was shown in the mouse arcuate–median eminence complex, where fasting behavior was shown to significantly affect gene expression in subsets of pro-opiomelanocortin (POMC)-expressing neurons and Agouti-related protein (AGRP)-expressing neurons, contrary to previous bulk tissue analyses that had not reported these changes as significant (Campbell et al., 2017). Indeed, characterizing specific cell types involved in target behaviors within heterogeneous brain regions would be the first step to identifying gene candidates associated with the organization and display of social behaviors.

In this review, we will discuss recent technical advances that can be applied to study neuronal populations associated with specific neural pathways or behaviors, schematized in Fig. 1. These include methods to capture active neuronal populations and gene expression programs that are active during or as a consequence of specific behaviors, as well as approaches that can help characterize the development of specific cell types and their connectivity patterns. Notably, many of these approaches do not require germline genetic modification, making them suitable for a variety of interesting species with diverse behavioral repertoires. We describe isolation of RNA from acutely activated neurons, projection-specific RNA-seq, and single-cell methodologies that provide cellular and spatial resolution. We conclude by suggesting that the field consider a developmental approach to understanding species differences in behavior, based on the hypothesis that the neural pathways that drive such differences are specified in early life. That is to say, in order to fully understand how social behavior neural circuits function, gene programs dictating the organization and activation of such neural pathways must be equally considered, as articulated by Tinbergen's questions about ontogeny and mechanism for understanding animal behavior (Tinbergen, 2010; Bateson and Laland, 2013).

Section snippets

Logical insights from flies and worms

Associating genes with behavior necessitates identification of the anatomic location and developmental time in which a gene product acts in the brain to facilitate said behavior. Previous studies using chemo- and opto-genetic approaches have shown necessity and sufficiency of genetically-defined cell populations in the display of behaviors. Testing the requirement for an individual gene in a distinct population of neurons has only recently become possible with the advent of a CRISPR activation

Capturing active neuronal populations

One way to identify neuronal populations potentially associated with behaviors is to look for cells that become active during a sensory experience or behavioral display. Researchers have long used neural activity regulated immediate early genes (IEG) such as FBJ osteosarcoma oncogene (Fos), activity regulated cytoskeletal-associated protein (Arc), and early growth response 1 (Egr1) to identify brain regions that are active during specific behaviors. Cellular resolution can be obtained by

Projection-specific transcriptomics

Another way to isolate cells participating in an individual behavior is by considering their connectivity patterns. That is to say, when the brain regions and neuronal populations active during a behavior are known, they can then go on to be profiled based on their projection targets. Species and sex differences in behavior may result from cells receiving different inputs by having formed different neuronal connections throughout development. In Drosophila, differences in weighting of

Comparing gene expression across species

One approach that has been employed to study how candidate genes affect social behaviors in non-traditional model species, is to compare gene sequence variation amongst members of the same species, to assess how these differences contribute to varying degrees of behavioral display. For example, sequence variation in potential regulatory regions for OT and AVP receptors resulting in varying degrees of gene expression in specific brain regions, were linked to differences in social attachment and

Single-cell methodologies

As mentioned previously, subcortical brain regions such as the POA and ventromedial hypothalamus (VMH) are highly heterogeneous; one region contains multiple sub-nuclei, which could be participating in different behavioral circuits. Several parameters can be used collectively to characterize different neuronal types, which include spatial context, morphology, connectivity, gene expression patterns, and evolutionary history (Arendt et al., 2016; Mukamel and Ngai, 2019). Gene products are

Genetic labeling to enhance scRNA-seq

Various studies have sought to determine which genes are the best classifiers of cell type and have found that transcription factors (TFs) are the most robust discriminators of neuronal types and their progenitors throughout embryonic development (Shimogori et al., 2010; Arber, 2012; Hobert, 2016; Li et al., 2017; Paul et al., 2017; Huisman et al., 2019). Neuromodulator receptors, although weakly expressed in comparison to TFs, can also be used to define cell types, and can give clues as to

Development and circuit specification

Differential gene expression signatures likely reflect differences in internal state, neuronal activity patterns, or in the case of species comparisons, composition of cell types. While the approaches described above may be used to pinpoint functional populations that are modified by experience, in our view identification of gene programs responsible for the organization of specific behavioral circuits requires a neurodevelopmental approach. As previously stated, an integrative understanding of

Funding information

This work was supported by the NIH (R01 MH113628 to JT and T-32 2T32GM065094 to J R-O) the Pershing Square Foundation, and the Stanley Foundation.

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