Biology subjects

Hamilton, M. J.

Publications and source records attributed to Hamilton, M. J..

7 recordsLinked to original sources

bioRxiv2025

De novo heterozygous variants in EHMT2 genocopy Kleefstra syndrome via loss of G9a methyltransferase activity

EHMT1 and EHMT2 genes encode human euchromatin histone lysine methyltransferase 1 and 2 (EHMT1 alias GLP; EHMT2 alias G9a) that form heteromeric GLP/G9a complexes with essential roles in epigenetic regulation of gene expression. While EHMT1 haploinsufficiency has been established as the cause of Kleefstra syndrome 1, the pathogenesis of G9a dysfunction in human disease remains largely unknown. We identified seven de novo EHMT2 variants in patients with clinical presentation, episignatures, histone modifications and transcriptomic profiles similar to those of Kleefstra syndrome 1. In vitro studies revealed that these variants encode for structurally stable G9a proteins that are catalytically incompetent due to aberrant interactions either with histone H3 tail or with S-adenosylmethionine. Heterozygous mice carrying a patient-derived variant exhibited growth retardation, facial/skull dysmorphia and aberrant behavior. Here we report pathogenic EHMT2 variants that likely exert dominant-negative effect on GLP/G9a complexes and thus genocopy the EHMT1 haploinsufficiency via a distinct molecular mechanism, defining an autosomal dominant EHMT2-related Kleefstra syndrome.

genetics↗

bioRxiv2021

Reconstructing hunter-gatherer planet Earthusing machine-learning

Estimating the total human population size (i.e., abundance) of the preagricultural planet is important for setting the baseline expectations for human-environment interactions if all energy and material requirements to support growth, maintenance, and well-being were foraged from local environments. However, demographic parameters and biogeographic distributions do not preserve directly in the archaeological record. Rather than attempting to estimate human abundance at some specific time in the past, a principled approach to making inferences at this scale is to ask what the human demography and biogeography of a hypothetical planet Earth would look like if populated by ethnographic hunter-gatherer societies. Given ethnographic hunter-gatherer societies likely include the largest, densest, and most complex foraging societies to have existed, we suggest population inferences drawn from this sample provide an upper bound to demographic estimates in prehistory. Our goal in this paper is to produce principled estimates of hunter-gatherer abundance, diversity, and biogeography. To do this we trained an extreme gradient boosting algorithm (XGBoost) to learn ethnographic hunter-gatherer population densities from a large matrix of climatic, environmental, and geographic data. We used the predictions generated by this model to reconstruct the hunter-gatherer biogeography of the rest of the planet. We find the human abundance of this world to be 6.1{+/-}2 million with an ethnolinguistic diversity of 8,330{+/-}2,770 populations, most of whom would have lived near coasts and in the tropics. Significance StatementUnderstanding the abundance of humans on planet Earth prior to the development of agriculture and the industrialized world is essential to understanding human population growth. However, the problem is that these features of human populations in the past are unknown and so must be estimated from data. We developed a machine learning approach that uses ethnographic and environmental data to reconstruct the demography and biogeography of planet Earth if populated by hunter-gatherers. Such a world would house about 6 million people divided into about 8,330 populations with a particular concentration in the tropics and along coasts.

ecology↗

bioRxiv2021

Collective computation and the emergence ofhunter-gatherer small-worlds

Two defining features of human sociality are large brains with neurally-dense cerebral cortices and the propensity to form complex social networks with non-kin. Large brains and the social networks in which they are embedded facilitate flows of fitness-enhancing information at multiple scales, but are also energetically expensive. In this paper, we consider how flows of energy and information interact to shape the macroscopic features of hunter-gatherer socioecology. Collective computation is the processing of information by complex adaptive systems to generate inferences in order to solve adaptive problems. In hunter-gatherer societies the adaptive problem is how to maximize fitness by optimizing information processing given the energy constraints of complex environments. The solution is the emergent macroscopic structure of the socioecology. Here we show how computation is extended across social networks to form the decentralized knowledge systems characteristic of hunter-gatherer societies. Data show that hunter-gatherer bands of co-residing families constitute computationally powerful networks that are embedded within hierarchically modular social networks that form complex metapopulations bound by fission-fusion dynamics at multiple scales facilitating the flow of information far beyond local interactions. These dynamics lead to the emergence of hunter-gatherer small-worlds where highly clustered local interactions are embedded within much larger, but sparsely connected metapopulations. Hunter-gatherers optimize local energy budgets in small groups but maintain interactions with much larger social networks while avoiding many of the ecological costs.

ecology↗

bioRxiv2020

Diversity begets diversity in human cultures and mammal species

A key feature of the distribution of life on Earth is the positive correlation between environmental productivity and biodiversity. This correlation also characterizes the distribution of human cultural diversity, which is highest near the equator and decreases exponentially toward the poles. Moreover, it is now understood that the tropics house more biodiversity than would be expected from energy availability alone suggesting "diversity begets diversity". Here we show the same is also true for human cultural diversity. This convergence is particularly striking because while the dynamics of biological and cultural evolution may be similar in principle the mechanisms and time scales involved are very different. However, a common currency underlying all forms of diversity is ecological kinetics; the temperature-dependent fluxes of energy and biotic interactions that sustain life at all levels of biological and social organization. Using macroecological theory and the analysis of global databases we show both mammal diversity and cultural diversity scale superlinearly with environmental productivity at rates predicted by the ecological kinetics of environmental productivity. Diversity begets diversity in human cultures and mammal species because the kinetics of energy availability and biotic interactions result in superlinear scaling with environmental productivity.

ecology↗

bioRxiv2019

Unique allometry of group size and collective brain mass in humans and primates relative to other mammals

Group living is common in mammals, particularly in primates and humans. Across species, groups are social networks where co-residing members exchange information and balance trade-offs between competition and cooperation for space, resources, and reproductive opportunities. From a macroecological perspective, species-specific group sizes are ultimately constrained by body size, population density, and the environmental supply rate of home ranges. Here, we derive an allometric null model for group size in mammals based on individual energy demands and ecological constraints. Using Bayesian phylogenetic mixed models we show that primates exhibit unique allometries relative to other mammals. Moreover, as large-bodied primates, human hunter-gatherers have among the largest social groups of any mammal. We then explore the consequences of this unique social allometry by considering how mammalian brain size scales up in social groups that differ in size across mammals. We show similarly unique allometries in what we term the collective brain mass of social groups in primates relative to all other mammals. These results show that for a given body size primates have both larger brains and larger social networks than other mammals. Consequently, proportionally larger primate brains interact in proportionally larger social networks with important consequences for group cognition. We suggest that the size, scale, and complexity of human social networks in the 21st century have deep evolutionary roots in primate ecology and mammalian brain allometry.

ecology↗

bioRxiv2019

Localization of a feline autosomal dominant dwarfism locus: a novel model of chondrodysplasia

Despite the contribution of a few major genes for disproportionate dwarfism in humans, many dwarf patients are yet genetically undiagnosed. In domestic cats, disproportionate dwarfism has led to the development of a defined breed, the Munchkin or Minuet. This study examined the genetic aspects of feline dwarfism to consider cats as a new biomedical model. DNA from dwarf cats was genetically analyzed using parentage, linkage, and genome-wide association studies as well as whole genome sequencing. Each genetic approach localized the dwarfism phenotype to a region on cat chromosome B1. No coding variants suspected as causal for the feline dwarfism were identified but a critical region of [~]5.7 Mb from B1:170,278,183-175,975,857 was defined, which implicates a novel gene controlling disproportionate dwarfism. A yet unidentified but novel gene variant, likely structural or regulatory, produces disproportionate dwarfism in cats, which may define undiagnosed human patients.

genetics↗

bioRxiv2019

Nonlinear diversification rates of linguistic phylogenies over the Holocene

The expansion of the human species out of Africa in the Pleistocene, and the subsequent development of agriculture in the Holocene resulted in waves of linguistic diversification and replacement across the planet. Analogous to the growth of populations or the speciation of biological organisms, languages diversify over time to form phylogenies of language families. However, the dynamics of this diversification process are unclear. Bayesian methods applied to lexical and phonetic data have created dated linguistic phylogenies for 18 language families encompassing [~]3,000 of the worlds [~]7,000 extant languages. In this paper we use these phylogenies to quantify how fast languages expand and diversify through time both within and across language families. The overall diversification rate of languages in our sample is [~]0.001 yr-1 (or a doubling time of [~]700 yr) over the last 6,000 years with evidence for nonlinear dynamics in language diversification rates over time, where both within and across language families, diversity initially increases rapidly and then slows. The large-scale replacement of the worlds hunter-gatherer languages by agricultural languages over the Holocene was a non-constant process.

evolutionary biology↗