The great McGill scientist Donald Hebb, often considered the father of modern neuroscience, was asked his opinion whether “nature” (the genome) or “nurture” (the environment) contributed more to individual differences in human behaviour. He replied that this question was akin to asking what contributed more to the area of a rectangle – the length or the width! For Hebb, and many others in biology, variation in phenotype emerges as the constant interaction between environmental signals and genomic transcription. However, a fundamental issue is that of describing the nature of such gene ⨯ environment interactions: what biological processes define the “⨯”? This question is of particular importance for the study of development, where early experience commonly exerts lasting effects at the level of genomic transcription and complex phenotypes. Such effects can form stable individual differences in health and capacity over the lifespan.

The compelling challenge in the study of the gene ⨯ environment interactions that shape phenotypic variation is that of understanding the biological basis by which environmental signals produce an enduring effect on genomic structure and function, and thus on phenotype.This issue lies at the heart of the study of the effects of early experience and of developmental influences on phenotypic variation. It is this issue that forms the major focus for our research.

Our studies focus, in part, on rodent models that examine the effects of environmental conditions during postnatal development. In particular, we study the influence of naturally-occurring variations in maternal behaviour (see attached video link), with a focus on differences in pup licking/grooming behaviour. Our findings suggest that variations in the frequency of pup licking affect reproductive, metabolic, as well as cognitive-emotional development, with effects persisting into adulthood. These effects are in part or completely reversed by cross-fostering the offspring of high and low licking/grooming mothers. The findings suggest a direct effect of maternal care.

The results of studies from our lab and several others show that variations in the quality of mother – offspring interactions stably alter gene transcription, including regions that code for proteins implicated with brain development and function, reproduction and metabolism. We thus focused on the issue of how an environmental signal might stably affect transcription of the genome. We proposed an environmental epigenetics hypothesis, which suggests that biologically-relevant environmental signals alter the activity of intra-cellular signaling pathways, including signals that interact directly with chromatin and regulate chromatin structure. Alterations in chromatin structure and active transcription might then provide an opportunity for epigenetic modifications that would then be directly linked to the environmental signal. Epigenetics refers to chemical modifications of chromatin, including both the histone proteins and the DNA, which subsequently influence the probability of transcription factor binding and transcriptional activation.

The current studies in our lab focus on studies using a variety of approaches, each with the intent of establishing the relation between clinically-relevant environmental conditions (i.e., those that predict the quality of health and capacity) and the epigenome, as well as the functional importance of the resulting epigenetic variation for phenotype. Our current research projects, including those with both human and nonhuman models, are summarized under “Research”. We list current research protocols for a variety of studies under the heading “Protocols”. Readers are referred to the links for the Maternal Adversity, Vulnerability and Neurodevelopment website for a summary of the birth cohort study based at the Douglas as well as to the website for the Ludmer Centre for Neuroinformatics and Mental Health, which refers to a new initiative at McGill that will address the computational challenges associated with the integration of genome-wide genetic and epigenetic analyses, neuroimaging and phenotyping datasets in the service of understanding the origins of mental disorders.