INVITED REVIEW: Phenotyping strategies and genetic background of dairy cattle behavior in intensive production systems - from trait definition to genomic selection.

Understanding and assessing dairy cattle behavior is critical for developing sustainable breeding programs and management practices. The behavior of individual animals can provide valuable information on their health and welfare status, improve reproductive management, and predict efficiency traits such as feed efficiency and milking efficiency. Routine genetic evaluations of animal behavior traits can contribute to optimizing breeding and management strategies for dairy cattle but require the identification of traits that capture the most important biological processes involved in behavioral responses. These traits should be heritable, repeatable, and measured in non-invasive and cost-effective ways in many individuals from the breeding populations or related reference populations. While behavior traits are heritable in dairy cattle populations, they are highly polygenic, with no known major genes influencing their phenotypic expression. Genetically selecting dairy cattle based on their behavior can be advantageous because of their relationship with other key traits such as animal health, welfare, and productive efficiency, as well as animal and handlers' safety. Trait definition and longitudinal data collection are still key challenges for breeding for behavioral responses in dairy cattle. However, the more recent developments and adoption of precision technologies in dairy farms provide avenues for more objective phenotyping and genetic selection of behavior traits. Furthermore, there is still a need to standardize phenotyping protocols for existing traits and develop guidelines for recording novel behavioral traits and integrating multiple data sources. This review gives an overview of the most common indicators of dairy cattle behavior, summarizes the main methods used for analyzing animal behavior in commercial settings, describes the genetic and genomic background of previously defined behavioral traits, and discusses strategies for breeding and improving behavior traits coupled with future opportunities for genetic selection for improved behavioral responses.

Sequential social experiences interact to modulate aggression but not brain gene expression in the honey bee (Apis mellifera).

BACKGROUND: In highly structured societies, individuals behave flexibly and cooperatively in order to achieve a particular group-level outcome. However, even in social species, environmental inputs can have long lasting effects on individual behavior, and variable experiences can even result in consistent individual differences and constrained behavioral flexibility. Despite the fact that such constraints on behavior could have implications for behavioral optimization at the social group level, few studies have explored how social experiences accumulate over time, and the mechanistic basis of these effects. In the current study, I evaluate how sequential social experiences affect individual and group level aggressive phenotypes, and individual brain gene expression, in the highly social honey bee (Apis mellifera). To do this, I combine a whole colony chronic predator disturbance treatment with a lab-based manipulation of social group composition. RESULTS: Compared to the undisturbed control, chronically disturbed individuals show lower aggression levels overall, but also enhanced behavioral flexibility in the second, lab-based social context. Disturbed bees display aggression levels that decline with increasing numbers of more aggressive, undisturbed group members. However, group level aggressive phenotypes are similar regardless of the behavioral tendencies of the individuals that make up the group, suggesting a combination of underlying behavioral tendency and negative social feedback influences the aggressive behaviors displayed, particularly in the case of disturbed individuals. An analysis of brain gene expression showed that aggression related biomarker genes reflect an individual's disturbance history, but not subsequent social group experience or behavioral outcomes. CONCLUSIONS: In highly social animals with collective behavioral phenotypes, social context may mask underlying variation in individual behavioral tendencies. Moreover, gene expression patterns may reflect behavioral tendency, while behavioral outcomes are further regulated by social cues perceived in real-time.

Socially responsive effects of brain oxidative metabolism on aggression.

Despite ongoing high energetic demands, brains do not always use glucose and oxygen in a ratio that produces maximal ATP through oxidative phosphorylation. In some cases glucose consumption exceeds oxygen use despite adequate oxygen availability, a phenomenon known as aerobic glycolysis. Although metabolic plasticity seems essential for normal cognition, studying its functional significance has been challenging because few experimental systems link brain metabolic patterns to distinct behavioral states. Our recent transcriptomic analysis established a correlation between aggression and decreased whole-brain oxidative phosphorylation activity in the honey bee (Apis mellifera), suggesting that brain metabolic plasticity may modulate this naturally occurring behavior. Here we demonstrate that the relationship between brain metabolism and aggression is causal, conserved over evolutionary time, cell type-specific, and modulated by the social environment. Pharmacologically treating honey bees to inhibit complexes I or V in the oxidative phosphorylation pathway resulted in increased aggression. In addition, transgenic RNAi lines and genetic manipulation to knock down gene expression in complex I in fruit fly (Drosophila melanogaster) neurons resulted in increased aggression, but knockdown in glia had no effect. Finally, honey bee colony-level social manipulations that decrease individual aggression attenuated the effects of oxidative phosphorylation inhibition on aggression, demonstrating a specific effect of the social environment on brain function. Because decreased neuronal oxidative phosphorylation is usually associated with brain disease, these findings provide a powerful context for understanding brain metabolic plasticity and naturally occurring behavioral plasticity.

Comparative genomics and the roots of human behavior.

Advances in genomics provide tools to test whether similar behaviors in distinct species have statistically similar brain transcriptomic signatures. Here, we (a genomicist and a cognitive neuroscientist) suggest that these techniques can help cognitive scientists tackle some of the most pressing questions about the roots of human behavior.

Probing the genomic landscape of human sexuality: a critical systematic review of the literature.

Whether human sexuality is the result of nature or nurture (or their complex interplay) represents a hot, often ideologically driven, and highly polarized debate with political and social ramifications, and with varying, conflicting findings reported in the literature. A number of heritability and behavioral genetics studies, including pedigree-based investigations, have hypothesized inheritance patterns of human sexual behaviors. On the other hand, in most twin, adoption, and nuclear family studies, it was not possible to disentangle between underlying genetic and shared environmental sources. Furthermore, these studies were not able to estimate the precise extent of genetic loading and to shed light both on the number and nature of the putative inherited factors, which remained largely unknown. Molecular genetic studies offer an unprecedented opportunity to overcome these drawbacks, by dissecting the molecular basis of human sexuality and allowing a better understanding of its biological roots if any. However, there exists no systematic review of the molecular genetics of human sexuality. Therefore, we undertook this critical systematic review and appraisal of the literature, with the ambitious aims of filling in these gaps of knowledge, especially from the methodological standpoint, and providing guidance to future studies. Sixteen studies were finally retained and overviewed in the present systematic review study. Seven studies were linkage studies, four studies utilized the candidate gene approach, and five studies were GWAS investigations. Limitations of these studies and implications for further research are discussed.

Wrestling with Public Input on an Ethical Analysis of Scientific Research.

Bioethicists frequently call for empirical researchers to engage participants and community members in their research, but don't themselves typically engage community members in their normative research. In this article, we describe an effort to include members of the public in normative discussions about the risks, potential benefits, and ethical responsibilities of social and behavioral genomics (SBG) research. We reflect on what might-and might not- be gained from engaging the public in normative scholarship and on lessons learned about public perspectives on the risks and potential benefits of SBG research and the responsible conduct and communication of such research. We also provide procedural lessons for others in bioethics who are interested in engaging members of the public in their research.

Addressing diversity and inclusion challenges in global neuro-psychiatric and behavioral genomics research.

Advancements in neuro-psychiatric and behavioral genomics offer significant opportunities for better understanding the human brain, behavior and associated disorders. Such advancements may help us prevent, manage and/or cure complex conditions. The serious challenge confronted by these disciplines however is diversity. Both fields lack diversity in terms of genomic reference datasets needed for discovery research, engagement of diverse communities in translational research and in terms of diverse and multidisciplinary scientific teams. This is a challenge because diversity is needed on all levels in order to increase representation and inclusion of all populations across the globe as we move research activities forward. The lack of diversity can translate to an inability to use scientific innovations from these fields for the benefit of all people everywhere and signifies a missed opportunity to address pervasive global health inequities. In this commentary we identify three persistent barriers to reaching diversity targets while focusing on discovery and translational science. Additionally, we propose four suggestions on how to advance efforts and rapidly move towards achieving diversity and inclusion in neuro-psychiatric and behavioral genomics. Without systematically addressing the diversity gap within these fields, the benefits of the science may not be relevant and accessible to all people.

Social Equality in an Alternate World.

Genes have long been used to validate social inequality. The Genetic Lottery: Why DNA Matters for Social Equality, by Kathryn Paige Harden, attempts not only to reclaim genetic research on human behavior from its eugenic past but also to argue that genetic research can be used to understand and enhance social equality. This review essay illustrates why embracing a political agenda in which genetics matter for social equality will not in practice advance efforts to reduce social inequality. It argues that the points raised in The Genetic Lottery would be important in an alternate world in which structural inequalities have ceased to exist, but not in the world we live in today.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding.

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Behavioral Genetic Toolkits: Toward the Evolutionary Origins of Complex Phenotypes.

The discovery of toolkit genes, which are highly conserved genes that consistently regulate the development of similar morphological phenotypes across diverse species, is one of the most well-known observations in the field of evolutionary developmental biology. Surprisingly, this phenomenon is also relevant for a wide array of behavioral phenotypes, despite the fact that these phenotypes are highly complex and regulated by many genes operating in diverse tissues. In this chapter, we review the use of the toolkit concept in the context of behavior, noting the challenges of comparing behaviors and genes across diverse species, but emphasizing the successes in identifying genetic toolkits for behavior; these successes are largely attributable to the creative research approaches fueled by advances in behavioral genomics. We have two general goals: (1) to acknowledge the groundbreaking progress in this field, which offers new approaches to the difficult but exciting challenge of understanding the evolutionary genetic basis of behaviors, some of the most complex phenotypes known, and (2) to provide a theoretical framework that encompasses the scope of behavioral genetic toolkit studies in order to clearly articulate the research questions relevant to the toolkit concept. We emphasize areas for growth and highlight the emerging approaches that are being used to drive the field forward. Behavioral genetic toolkit research has elevated the use of integrative and comparative approaches in the study of behavior, with potentially broad implications for evolutionary biologists and behavioral ecologists alike.

Cross-Species Integrative Functional Genomics in GeneWeaver Reveals a Role for Pafah1b1 in Altered Response to Alcohol.

Identifying the biological substrates of complex neurobehavioral traits such as alcohol dependency pose a tremendous challenge given the diverse model systems and phenotypic assessments used. To address this problem we have developed a platform for integrated analysis of high-throughput or genome-wide functional genomics studies. A wealth of such data exists, but it is often found in disparate, non-computable forms. Our interactive web-based software system, Gene Weaver (http://www.geneweaver.org), couples curated results from genomic studies to graph-theoretical tools for combinatorial analysis. Using this system we identified a gene underlying multiple alcohol-related phenotypes in four species. A search of over 60,000 gene sets in GeneWeaver's database revealed alcohol-related experimental results including genes identified in mouse genetic mapping studies, alcohol selected Drosophila lines, Rattus differential expression, and human alcoholic brains. We identified highly connected genes and compared these to genes currently annotated to alcohol-related behaviors and processes. The most highly connected gene not annotated to alcohol was Pafah1b1. Experimental validation using a Pafah1b1 conditional knock-out mouse confirmed that this gene is associated with an increased preference for alcohol and an altered thermoregulatory response to alcohol. Although this gene has not been previously implicated in alcohol-related behaviors, its function in various neural mechanisms makes a role in alcohol-related phenomena plausible. By making diverse cross-species functional genomics data readily computable, we were able to identify and confirm a novel alcohol-related gene that may have implications for alcohol use disorders and other effects of alcohol.