Evaluating mechanisms of genetic adaptation to rapid environmental changes: agriculture and the human model – AGRHUM

To achieve our goals, we will generate genome-wide data, using whole-exome sequencing, from a large panel of individuals originating from different rainforest hunter-gatherer and farmer populations. We will use this dataset to examine the demographic history of these populations, by inferring best-fitting demographic models, and to evaluate how demography and lifestyle have (differently) affected the efficiency of purifying selection (i.e., the purging of weakly deleterious alleles). In parallel, we will develop new methods to investigate the occurrence of rapid adaptation through various evolutionary mechanisms, including positive selection following the classic sweep model as well as other modes of adaptive evolution, such as selection on standing variation, polygenic adaptation and adaptive introgression.

In this initial phase of the project, we have focused on data generation and evaluation of how changes in demographic history can affect the efficiency of purifying selection, as well as on the development (or improvement) of statistical methods to detect selection from next-generation sequencing data. Some preliminary results are worth discussing. We have defined the demographic model that explains the best the genetic variability of populations of rainforest hunter-gatherers and farmers from Central Africa. The model shows strong differences in the demographic success of these populations, with important changes in their effective population sizes over time. Despite such strong demographic differences, our analyses show that both groups of populations have kept the same potential to purge deleterious mutations and therefore, the same efficiency of purifying selection. We have also developed a method to detect positive selection, “pcadapt”, which is based on principal component analyses. Furthermore, we have compared the relative efficiency of different methods to detect positive selection and developed a simulation programme aiming to detect polygenic adaptation.

Over the next period, we will study and quantify the relative contribution of the various evolutionary mechanisms involved in rapid adaptation to environmental changes, including positive selection following the classic sweep model as well as other modes of adaptive evolution, such as selection on standing variation, polygenic adaptation and adaptive introgression. The integration of all these data, together with the estimation of the times at which deleterious and adaptive variants have arisen in these populations, will allow us to evaluate the impact of rapid changes in the environment on genetic fitness and efficiency of selection. The main novelty of our study lies in the fact that it will be the first to characterise the impact of the emergence of agriculture on the demographic, selective and adaptive history of human populations, by combining cutting-edge deep sequencing techniques with computational analyses and the development of new statistical approaches to detect genetic adaptation.

Duforet-Frebourg N, Luu K, Laval G, Bazin E, Blum MG. Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data. Mol Biol Evol. 2016 Apr;33(4):1082-93. doi: 10.1093/molbev/msv334.

The study of genetic adaptation in specific epochs can inform about specific adaptive processes in critical periods of innovation. The transition from food collection (hunter-gathering) to food production (farming/herding) has probably been the most important innovation in human history. The shift to agriculture led humans to adopt sedentary lifestyles, resulting in increased population densities, and modified the chemical, nutritional and pathogenic environments of early farmers, leading to novel selective pressures. However, the extent and rapidity of the genetic adaptation to such novel environments remain largely unknown. Furthermore, although some general insights are beginning to emerge, such as the moderate occurrence of classic selective sweeps and the roles that alternative selection models have likely played in recent adaptation, the contributions of each of these forces is unclear and the path to a more comprehensive understanding of selection and adaptation remains arduous. The AGRHUM project aims to increase knowledge of how species can genetically adapt, through diverse evolutionary mechanisms, to rapid changes in their environment, and to provide methodological tools to tackle this question in a wide variety of species. To do so, we will use humans as a model by evaluating the impact of the emergence of agriculture on selection and adaptation. We will focus on Central Africa, a region that presents one of the highest levels of biodiversity, as this region hosts the world’s largest group of hunter-gatherer populations, the rainforest hunter-gatherers, living in close proximity with groups that have adopted a farming lifestyle over the past 5,000 years. We will generate genome-wide data, using whole-exome sequencing, from a large panel of individuals originating from different rainforest hunter-gatherer and farmer populations. We will use this dataset to examine the demographic history of these populations, by inferring best-fitting demographic models, and to evaluate how demography and lifestyle have (differently) affected the efficiency of purifying selection (i.e., the purging of weakly deleterious alleles). In parallel, we will apply existing and newly developed methods to investigate the occurrence of rapid adaptation through various evolutionary mechanisms, including positive selection following the classic sweep model as well as other modes of adaptive evolution, such as selection on standing variation, polygenic adaptation and adaptive introgression. The integration of all these data, together with the estimation of the times at which deleterious and adaptive variants have arisen in these populations, will allow us to evaluate the impact of rapid changes in the environment on genetic fitness and efficiency of selection. The main novelty of our study lies in the fact that it will be the first to characterise the impact of the emergence of agriculture on the demographic, selective and adaptive history of human populations, by combining cutting-edge deep sequencing techniques with computational analyses and the development of new statistical approaches to detect genetic adaptation. Using the human paradigm, AGRHUM should help us to better understand, and possibly predict, how species can rapidly adapt (or maladapt) to abrupt changes in environmental pressures. Likewise, this project will have a direct scientific benefit for other projects and disciplines, as the knowledge and tools we will develop, especially with regard to methods to detect different types of genetic adaptation, will be useful for a wide range of biologists interested in the impact of environmental changes on non-human species. We believe that our proposed partnership in this endeavor based on a long-standing collaboration between the Quintana-Murci, Blum and Austerlitz laboratories, which have different but complementary expertise, will ensure a synergistic use of local resources and knowledge in advancing the project’s aims.