The IICR (inverse instantaneous coalescence rate) as a summary of genomic diversity: insights into demographic inference and model choice

An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions

Species generally undergo a complex demographic history consisting, in particular, of multiple changes in population size. Genome-wide sequencing data are potentially highly informative for reconstructing this demographic history. A crucial point is to extract the relevant information from these very large data sets. Here, we design an approach for inferring past demographic events from a moderate number of fully sequenced genomes. Our new approach uses Approximate Bayesian Computation, a simulation-based statistical framework that allows 1) identifying the best demographic scenario among several competing scenarios and 2) estimating the best-fitting parameters under the chosen scenario. Approximate Bayesian Computation relies on the computation of summary statistics. Using a cross-validation approach, we show that statistics such as the lengths of haplotypes shared between individuals, or the decay of linkage disequilibrium with distance, can be combined with classical statistics (e.g., heterozygosity and Tajima's D) to accurately infer complex demographic scenarios including bottlenecks and expansion periods. We also demonstrate the importance of simultaneously estimating the genotyping error rate. Applying our method on genome-wide human-sequence databases, we finally show that a model consisting in a bottleneck followed by a Paleolithic and a Neolithic expansion is the most relevant for Eurasian populations.

A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data

A common goal of population genomics and molecular ecology is to reconstruct the demographic history of a species of interest. A pair of powerful tools based on the sequentially Markovian coalescent have been developed to infer past population sizes using genome sequences. These methods are most useful when sequences are available for only a limited number of genomes and when the aim is to study ancient demographic events. The results of these analyses can be difficult to interpret accurately, because doing so requires some understanding of their theoretical basis and of their sensitivity to confounding factors. In this practical review, we explain some of the key concepts underpinning the pairwise and multiple sequentially Markovian coalescent methods (PSMC and MSMC, respectively). We relate these concepts to the use and interpretation of these methods, and we explain how the choice of different parameter values by the user can affect the accuracy and precision of the inferences. Based on our survey of 100 PSMC studies and 30 MSMC studies, we describe how the two methods are used in practice. Readers of this article will become familiar with the principles, practice, and interpretation of the sequentially Markovian coalescent for inferring demographic history.

Aquatic Adaptation and Depleted Diversity: A Deep Dive into the Genomes of the Sea Otter and Giant Otter

Despite its recent invasion into the marine realm, the sea otter (Enhydra lutris) has evolved a suite of adaptations for life in cold coastal waters, including limb modifications and dense insulating fur. This uniquely dense coat led to the near-extinction of sea otters during the 18th-20th century fur trade and an extreme population bottleneck. We used the de novo genome of the southern sea otter (E. l. nereis) to reconstruct its evolutionary history, identify genes influencing aquatic adaptation, and detect signals of population bottlenecks. We compared the genome of the southern sea otter with the tropical freshwater-living giant otter (Pteronura brasiliensis) to assess common and divergent genomic trends between otter species, and with the closely related northern sea otter (E. l. kenyoni) to uncover population-level trends. We found signals of positive selection in genes related to aquatic adaptations, particularly limb development and polygenic selection on genes related to hair follicle development. We found extensive pseudogenization of olfactory receptor genes in both the sea otter and giant otter lineages, consistent with patterns of sensory gene loss in other aquatic mammals. At the population level, the southern sea otter and the northern sea otter showed extremely low genomic diversity, signals of recent inbreeding, and demographic histories marked by population declines. These declines may predate the fur trade and appear to have resulted in an increase in putatively deleterious variants that could impact the future recovery of the sea otter.

Plant population dynamics on oceanic islands during the Late Quaternary climate changes: genetic evidence from a tree species (Coffea mauritiana) in Reunion Island

Past climatic fluctuations have played a major role in shaping the current plant biodiversity. Although harbouring an exceptional biota, oceanic islands have received little attention in studies on species demographic history and past vegetation patterns. We investigated the impact of past climatic changes on the effective population size of a tree (Coffea mauritiana) that is endemic to Reunion Island, located in the south-western Indian Ocean (SWIO). Demographic changes were inferred using summary statistics calculated from genomic data. Using ecological niche modelling and the current distribution of genetic diversity, the paleodistribution of the species was also assessed. A reduction in the effective population size of C. mauritiana during the last glaciation maximum was inferred. The distribution of the species was reduced on the western side of the island, due to low rainfall. It appeared that a major reduction in rainfall and a slight temperature decrease prevailed in the SWIO. Our findings indicated that analyses on the current patterns of intraspecific genetic variations can efficiently contribute to past climatic changes characterisation in remote islands. Identifying area with higher resilience in oceanic islands could provide guidance in forest management and conservation faced to the global climate change.

Ice-Age Climate Adaptations Trap the Alpine Marmot in a State of Low Genetic Diversity

Some species responded successfully to prehistoric changes in climate [1, 2], while others failed to adapt and became extinct [3]. The factors that determine successful climate adaptation remain poorly understood. We constructed a reference genome and studied physiological adaptations in the Alpine marmot (Marmota marmota), a large ground-dwelling squirrel exquisitely adapted to the "ice-age" climate of the Pleistocene steppe [4, 5]. Since the disappearance of this habitat, the rodent persists in large numbers in the high-altitude Alpine meadow [6, 7]. Genome and metabolome showed evidence of adaptation consistent with cold climate, affecting white adipose tissue. Conversely, however, we found that the Alpine marmot has levels of genetic variation that are among the lowest for mammals, such that deleterious mutations are less effectively purged. Our data rule out typical explanations for low diversity, such as high levels of consanguineous mating, or a very recent bottleneck. Instead, ancient demographic reconstruction revealed that genetic diversity was lost during the climate shifts of the Pleistocene and has not recovered, despite the current high population size. We attribute this slow recovery to the marmot's adaptive life history. The case of the Alpine marmot reveals a complicated relationship between climatic changes, genetic diversity, and conservation status. It shows that species of extremely low genetic diversity can be very successful and persist over thousands of years, but also that climate-adapted life history can trap a species in a persistent state of low genetic diversity.

On the unfounded enthusiasm for soft selective sweeps II: Examining recent evidence from humans, flies, and viruses

Since the initial description of the genomic patterns expected under models of positive selection acting on standing genetic variation and on multiple beneficial mutations—so-called soft selective sweeps—researchers have sought to identify these patterns in natural population data. Indeed, over the past two years, large-scale data analyses have argued that soft sweeps are pervasive across organisms of very different effective population size and mutation rate—humans, Drosophila, and HIV. Yet, others have evaluated the relevance of these models to natural populations, as well as the identifiability of the models relative to other known population-level processes, arguing that soft sweeps are likely to be rare. Here, we look to reconcile these opposing results by carefully evaluating three recent studies and their underlying methodologies. Using population genetic theory, as well as extensive simulation, we find that all three examples are prone to extremely high false-positive rates, incorrectly identifying soft sweeps under both hard sweep and neutral models. Furthermore, we demonstrate that well-fit demographic histories combined with rare hard sweeps serve as the more parsimonious explanation. These findings represent a necessary response to the growing tendency of invoking parameter-heavy, assumption-laden models of pervasive positive selection, and neglecting best practices regarding the construction of proper demographic null models.

A long-standing debate in evolutionary biology revolves around the role of selective vs. stochastic processes in driving molecular evolution and shaping genetic variation. With the advent of genomics, genome-wide polymorphism data have been utilized to characterize these processes, with a major interest in describing the fraction of genomic variation shaped by positive selection. These genomic scans were initially focused around a hard sweep model, in which selection acts upon rare, newly arising beneficial mutations. Recent years have seen the description of sweeps occurring from both standing and rapidly recurring beneficial mutations, collectively known as soft sweeps. However, common to both hard and soft sweeps is the difficulty in distinguishing these effects from neutral demographic patterns, and disentangling these processes has remained an important field of study within population genetics. Despite this, there is a recent and troubling tendency to neglect these demographic considerations, and to naively fit sweep models to genomic data. Recent realizations of such efforts have resulted in the claim that soft sweeps play a dominant role in shaping genomic variation and in driving adaptation across diverse branches of the tree of life. Here, we reanalyze these findings and demonstrate that a more careful consideration of neutral processes results in highly differing conclusions.

Demographic inferences after a range expansion can be biased: the test case of the blacktip reef shark (Carcharhinus melanopterus)

The evolutionary history of species is a dynamic process as they modify, expand, and contract their spatial distributions over time. Range expansions (REs) occur through a series of founder events that are followed by migration among neighboring demes. The process usually results in structured metapopulations and leaves a distinct signature in the genetic variability of species. Explicitly modeling the consequences of complex demographic events such as REs is computationally very intensive. Here we propose an an alternative approach that requires less computational effort than a comprehensive RE model, but that can recover the demography of species undergoing a RE, by combining spatially explicit modelling with simplified but realistic metapopulation models. We examine the demographic and colonization history of Carcharhinus melanopterus, an abundant reef-associated shark, as a test case. We first used a population genomics approach to statistically confirm the occurrence of a RE in C. melanopterus, and identify its origin in the Indo-Australian Archipelago. Spatial genetic modelling identified two waves of stepping-stone colonization: an eastward wave moving through the Pacific and a westward one moving through the Indian Ocean. We show that metapopulation models best describe the demographic history of this species and that not accounting for this may lead to incorrectly interpreting the observed genetic variation as signals of widespread population bottlenecks. Our study highlights insights that can be gained about demography by coupling metapopulation models with spatial modeling and underscores the need for cautious interpretation of population genetic data when advancing conservation priorities.

Using Genomic Data to Infer Historic Population Dynamics of Nonmodel Organisms

Genome sequence data are now being routinely obtained from many nonmodel organisms. These data contain a wealth of information about the demographic history of the populations from which they originate. Many sophisticated statistical inference procedures have been developed to infer the demographic history of populations from this type of genomic data. In this review, we discuss the different statistical methods available for inference of demography, providing an overview of the underlying theory and logic behind each approach. We also discuss the types of data required and the pros and cons of each method. We then discuss how these methods have been applied to a variety of nonmodel organisms. We conclude by presenting some recommendations for researchers looking to use genomic data to infer demographic history.

Emerging and Enduring Issues in Primate Conservation Genetics

Conservation genetics is a branch of conservation biology that uses molecular data to assist in the conservation and management of imperiled populations, subspecies, and species. In this review, I examine conservation action plans (CAPs)—instrumental documents designed to influence conservation policy—for selected primate species. I use the information contained in CAPs as a means to guide this review. The primary genetics-based topics that are mentioned in CAPs are genetic connectivity, inbreeding, and subspecies/species delimitation. I discuss these topics as well as historical demographic inference and hybridization using examples from wild primate species to illustrate the myriad ways in which genetics can assist in conservation efforts. I also discuss some recent technological advances such as genomic capture techniques and the potential to do molecular work in remote locations.

The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure

In the last years, a wide range of methods allowing to reconstruct past population size changes from genome-wide data have been developed. At the same time, there has been an increasing recognition that population structure can generate genetic data similar to those produced under models of population size change. Recently, Mazet et al. (Heredity 116:362-371, 2016) showed that, for any model of population structure, it is always possible to find a panmictic model with a particular function of population size changes, having exactly the same distribution of T₂ (the coalescence time for a sample of size two) as that of the structured model. They called this function IICR (Inverse Instantaneous Coalescence Rate) and showed that it does not necessarily correspond to population size changes under non-panmictic models. Besides, most of the methods used to analyse data under models of population structure tend to arbitrarily fix that structure and to minimise or neglect population size changes. Here, we extend the seminal work of Herbots (PhD thesis, University of London, 1994) on the structured coalescent and propose a new framework, the Non-Stationary Structured Coalescent (NSSC) that incorporates demographic events (changes in gene flow and/or deme sizes) to models of nearly any complexity. We show how to compute the IICR under a wide family of stationary and non-stationary models. As an example we address the question of human and Neanderthal evolution and discuss how the NSSC framework allows to interpret genomic data under this new perspective.

Did Our Species Evolve in Subdivided Populations across Africa, and Why Does It Matter?

We challenge the view that our species, Homo sapiens, evolved within a single population and/or region of Africa. The chronology and physical diversity of Pleistocene human fossils suggest that morphologically varied populations pertaining to the H. sapiens clade lived throughout Africa. Similarly, the African archaeological record demonstrates the polycentric origin and persistence of regionally distinct Pleistocene material culture in a variety of paleoecological settings. Genetic studies also indicate that present-day population structure within Africa extends to deep times, paralleling a paleoenvironmental record of shifting and fractured habitable zones. We argue that these fields support an emerging view of a highly structured African prehistory that should be considered in human evolutionary inferences, prompting new interpretations, questions, and interdisciplinary research directions.

The view that Homo sapiens evolved from a single region/population within Africa has been given primacy in studies of human evolution.

However, developments across multiple fields show that relevant data are no longer consistent with this view.

We argue instead that Homo sapiens evolved within a set of interlinked groups living across Africa, whose connectivity changed through time.

Genetic models therefore need to incorporate a more complex view of ancient migration and divergence in Africa.

We summarize this new framework emphasizing population structure, outline how this changes our understanding of human evolution, and identify new research directions.

History of the fragmentation of the African rain forest in the Dahomey Gap: insight from the demographic history of Terminalia superba

Paleo-environmental reconstructions show that the distribution of tropical African rain forests was affected by Quaternary climate changes. They suggest that the Dahomey Gap (DG)-the savanna corridor that currently separates Upper Guinean (UG, West Africa) and Lower Guinean (LG, western Central Africa) rain forest blocks-was forested during the African Humid Holocene period (from at least 9 ka till 4.5 ka), and possibly during other interglacial periods, while an open vegetation developed in the DG under drier conditions, notably during glacial maxima. Nowadays, relics of semi-deciduous forests containing UG and LG forest species are still present within the DG. We used one of these species, the pioneer tree Terminalia superba (Combretaceae), to study past forest fragmentation in the DG and its impact on infraspecific biodiversity. A Bayesian clustering analysis of 299 individuals genotyped at 14 nuclear microsatellites revealed five parapatric genetic clusters (UG, DG, and three in LG) with low to moderate genetic differentiation (Fst from 0.02 to 0.24). Approximate Bayesian Computation analyses inferred a demographic bottleneck around the penultimate glacial period in all populations. They also supported an origin of the DG population by admixture of UG and LG populations around 54,000 (27,600-161,000) years BP, thus before the Last Glacial Maximum. These results contrast with those obtained on Distemonanthus benthamianus where the DG population seems to originate from the Humid Holocene period. We discuss these differences in light of the ecology of each species. Our results challenge the simplistic view linking population fragmentation/expansion with glacial/interglacial periods in African forest species.