Alterations in DNA Methylation and Hydroxymethylation Due to Parental Care in Rhesus Macaques

Early life is one of the most important and sensitive periods during the development of an individual. During this stage, the body and especially the brain are known to be greatly responsive to environmental cues, such as the early social environment. As a consequence, early life adverse social experiences in humans are associated with a wide range of health problems in adulthood. The broad range of phenotypes associated with early life stress (ELS) suggests a system-wide response of the organism, which is yet to be determined. In the last decade, increasing evidence suggests that epigenetic mechanisms underlie the effects of ELS on adult human health. However, there are critical challenges in delineating the direct effects of ELS on epigenetic profiles and phenotypes in human studies. It is impossible to randomize ELS and rare are the studies where complete information about past environmental insults is available, which would allow us to conclude on causality. Nonhuman primates offer several advantages in addressing these challenges. This chapter focuses on parental deprivation models in rhesus macaques which have been shown to produce an array of behavioral, physiological, and neurobiological deficits that parallel those identified in humans subjected to ELS. It describes the evidence for epigenetic alterations induced by differential rearing in this model and points out the differences between tissue-specific versus multi-tissue changes and outlines possible mechanisms for these to occur. In addition, it highlights the need for multi-omics longitudinal studies to better understand the epigenetic trajectories induced by ELS exposure and their impact on adult health

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity