This document summarizes a collection of research publications that were produced under the Marie Curie project HOPE. The primary focus of this project was to (i) investigate the phenotypic evolution of horses and its broader implications for human society, and (ii) identify and contrast horse traits preferred and selected by horse herders in Western Europe and the steppes. To facilitate accurate research on phenotypic evolution, two software tools were developed to manipulate ancient DNA data, which represent the main type of data generated and available during the course of the project: mapDATAge (Liu, 2022; Bioinformatics, Figure 1) and MethylationAge (Liu, 2023; iScience, Figure 2). These software represent significant advancements in the field of ancient DNA research as they enable the prediction and identification of various phenotypes using a combination of ancient and modern DNA data. These software tools were inspired by the notable identification of a causal mutation within the TBX3 enhancer, which drives height phenotypes in Asian horses (Liu, 2022; Current Biology, Figure 3). The project's research and impact transcended its initial intentions. In particular, it engaged in an exploration of sex-specific management practices across varying historical epochs in France, unearthing socio-cultural insights (Clavel, 2021; J. Archaeol. Sci. Rep.). Additionally, the contributed to an in-depth investigation into the early dispersal of domestic horses into the South American Great Plains, unveiling insights into the colonial expansion of European horses (Taylor, 2023; Science).
Problems Being Addressed:
1. How to effectively identify positively-selected candidate loci in ancient DNA datasets? mapDATAge provides a simple solution to this complex task by facilitating the interactive visualization of ancient DNA data, providing insights across spatial and temporal dimensions.
2. Age estimation stands as a classical yet pivotal indicator of animal management practices. However, the fragmented nature of the archaeological record have limited the capacity to obtain reliable age. To address this, we developed a new method to predict the age-at-death (and castration status) of ancient horses. Our method relies on the DNA methylation profiles at key CpG loci. It provides reliable age predictions within a one-year precision range.
3. How to explain the genetic variations contribute to phenotype? We first use these tools to make an prediction. Then validated through cellular and mice experiments, exemplified by the TBX3 study. This robust validation approach enhances our understanding of the genetic underpinnings driving phenotypic evolution in horses throughout their domestication history.
Importance for Society:
Our research spans multiple domains, exerting a profound influence that resonates with animal breeding, human history, and ancient DNA analysis. Advancements in Breeding: Our identification of key markers related to height and spinal development holds critical implications. These findings can guide modern horse breeding, particularly in providing new strategies for racehorse enhancement. Advancing ancient DNA Research: Our contributions introduce a new era in ancient DNA studies, with two pivotal software tools for phenotype and age prediction. Refining Historical Understanding: Our research sheds new light into the timeline of horse domestication and its societal roles, particularly and through uncovering sex-specific management practices and which phenotypes incentivized horse selective breeding in the course of history.
