Different kinds of genetic markers permit inference of Paleolithic and Neolithic expansions in humans

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.

Advances in genotyping microsatellite markers through sequencing and consequences of scoring methods for Ceratonia siliqua (Leguminosae)

PREMISE OF THE STUDY

Simple sequence repeat (SSR) or microsatellite markers have been used in a broad range of studies mostly scoring alleles on the basis of amplicon size as a proxy for the number of repeat units of an SSR motif. However, additional sources of variation within the SSR or in the flanking regions have largely remained undetected.

METHODS

In this study, we implemented a next-generation sequencing-based genotyping approach in a newly characterized set of 18 nuclear SSR markers for the carob tree, Ceratonia siliqua. Our aim was to evaluate the effect of three different methods of scoring molecular variation present within microsatellite markers on the genetic diversity and structure results.

RESULTS

The analysis of the sequences of 77 multilocus genotypes from four populations revealed SSR variation and additional sources of polymorphism in 87% of the loci analyzed (42 single-nucleotide polymorphisms and five insertion/deletion polymorphisms), as well as divergent paralog copies in two loci. Ignoring sequence variation under standard amplicon size genotyping resulted in incorrect identification of 69% of the alleles, with important effects on the genetic diversity and structure estimates.

DISCUSSION

Next-generation sequencing allows the detection and scoring of SSRs, single-nucleotide polymorphisms, and insertion/deletion polymorphisms to increase the resolution of population genetic studies.

Global demographic history of human populations inferred from whole mitochondrial genomes

The Neolithic transition has led to marked increases in census population sizes across the world, as recorded by a rich archaeological record. However, previous attempts to detect such changes using genetic markers, especially mitochondrial DNA (mtDNA), have mostly been unsuccessful. We use complete mtDNA genomes from over 1700 individuals, from the 1000 Genomes Project Phase 3, to explore changes in populations sizes in five populations for each of four major geographical regions, using a sophisticated coalescent-based Bayesian method (extended Bayesian skyline plots) and mutation rates calibrated with ancient DNA. Despite the power and sophistication of our analysis, we fail to find size changes that correspond to the Neolithic transitions of the study populations. However, we do detect a number of size changes, which tend to be replicated in most populations within each region. These changes are mostly much older than the Neolithic transition and could reflect either population expansion or changes in population structure. Given the amount of migration and population mixing that occurred after these ancient signals were generated, we caution that modern populations will often carry ghost signals of demographic events that occurred far away from their current location.

An earlier revolution: genetic and genomic analyses reveal pre-existing cultural differences leading to Neolithization

Archaeological evidence shows that, in the long run, Neolitization (the transition from foraging to food production) was associated with demographic growth. We used two methods (patterns of linkage disequilibrium from whole-genome SNPs and MSMC estimates on genomes) to reconstruct the demographic profiles for respectively 64 and 24 modern-day populations with contrasting lifestyles across the Old World (sub-Saharan Africa, south-eastern Asia, Siberia). Surprisingly, in all regions, food producers had larger effective population sizes (N_e) than foragers already 20 k years ago, well before the Neolithic revolution. As expected, this difference further increased ~12–10 k years ago, around or just before the onset of food production. Using paleoclimate reconstructions, we show that the early difference in N_e cannot be explained by food producers inhabiting more favorable regions. A number of mechanisms, including ancestral differences in census size, sedentism, exploitation of the natural resources, social stratification or connectivity between groups, might have led to the early differences in Ne detected in our analyses. Irrespective of the specific mechanisms involved, our results provide further evidence that long term cultural differences among populations of Palaeolithic hunter-gatherers are likely to have played an important role in the later Neolithization process.