The genomic origins of the world's first farmers.

The precise genetic origins of the first Neolithic farming populations in Europe and Southwest Asia, as well as the processes and the timing of their differentiation, remain largely unknown. Demogenomic modeling of high-quality ancient genomes reveals that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Southwest Asian population with a strongly bottlenecked western hunter-gatherer population after the last glacial maximum. Moreover, the ancestors of the first farmers of Europe and Anatolia went through a period of extreme genetic drift during their westward range expansion, contributing highly to their genetic distinctiveness. This modeling elucidates the demographic processes at the root of the Neolithic transition and leads to a spatial interpretation of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.

Inference of Locus-Specific Population Mixtures From Linked Genome-Wide Allele Frequencies.

Admixture between populations and species is common in nature. Since the influx of new genetic material might be either facilitated or hindered by selection, variation in mixture proportions along the genome is expected in organisms undergoing recombination. Various graph-based models have been developed to better understand these evolutionary dynamics of population splits and mixtures. However, current models assume a single mixture rate for the entire genome and do not explicitly account for linkage. Here, we introduce TreeSwirl, a novel method for inferring branch lengths and locus-specific mixture proportions by using genome-wide allele frequency data, assuming that the admixture graph is known or has been inferred. TreeSwirl builds upon TreeMix that uses Gaussian processes to estimate the presence of gene flow between diverged populations. However, in contrast to TreeMix, our model infers locus-specific mixture proportions employing a Hidden Markov Model that accounts for linkage. Through simulated data, we demonstrate that TreeSwirl can accurately estimate locus-specific mixture proportions and handle complex demographic scenarios. It also outperforms related D- and f-statistics in terms of accuracy and sensitivity to detect introgressed loci.

Human bony labyrinth is an indicator of population history and dispersal from Africa.

The dispersal of modern humans from Africa is now well documented with genetic data that track population history, as well as gene flow between populations. Phenetic skeletal data, such as cranial and pelvic morphologies, also exhibit a dispersal-from-Africa signal, which, however, tends to be blurred by the effects of local adaptation and in vivo phenotypic plasticity, and that is often deteriorated by postmortem damage to skeletal remains. These complexities raise the question of which skeletal structures most effectively track neutral population history. The cavity system of the inner ear (the so-called bony labyrinth) is a good candidate structure for such analyses. It is already fully formed by birth, which minimizes postnatal phenotypic plasticity, and it is generally well preserved in archaeological samples. Here we use morphometric data of the bony labyrinth to show that it is a surprisingly good marker of the global dispersal of modern humans from Africa. Labyrinthine morphology tracks genetic distances and geography in accordance with an isolation-by-distance model with dispersal from Africa. Our data further indicate that the neutral-like pattern of variation is compatible with stabilizing selection on labyrinth morphology. Given the increasingly important role of the petrous bone for ancient DNA recovery from archaeological specimens, we encourage researchers to acquire 3D morphological data of the inner ear structures before any invasive sampling. Such data will constitute an important archive of phenotypic variation in present and past populations, and will permit individual-based genotype-phenotype comparisons.

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution.

Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.

Low Prevalence of Lactase Persistence in Bronze Age Europe Indicates Ongoing Strong Selection over the Last 3,000 Years.

Lactase persistence (LP), the continued expression of lactase into adulthood, is the most strongly selected single gene trait over the last 10,000 years in multiple human populations. It has been posited that the primary allele causing LP among Eurasians, rs4988235-A [1], only rose to appreciable frequencies during the Bronze and Iron Ages [2, 3], long after humans started consuming milk from domesticated animals. This rapid rise has been attributed to an influx of people from the Pontic-Caspian steppe that began around 5,000 years ago [4, 5]. We investigate the spatiotemporal spread of LP through an analysis of 14 warriors from the Tollense Bronze Age battlefield in northern Germany (∼3,200 before present, BP), the oldest large-scale conflict site north of the Alps. Genetic data indicate that these individuals represent a single unstructured Central/Northern European population. We complemented these data with genotypes of 18 individuals from the Bronze Age site Mokrin in Serbia (∼4,100 to ∼3,700 BP) and 37 individuals from Eastern Europe and the Pontic-Caspian Steppe region, predating both Bronze Age sites (∼5,980 to ∼3,980 BP). We infer low LP in all three regions, i.e., in northern Germany and South-eastern and Eastern Europe, suggesting that the surge of rs4988235 in Central and Northern Europe was unlikely caused by Steppe expansions. We estimate a selection coefficient of 0.06 and conclude that the selection was ongoing in various parts of Europe over the last 3,000 years.

De novo assembly and transcriptome characterization of the freshwater prawn Palaemonetes argentinus: Implications for a detoxification response.

Palaemonetes argentinus, an abundant freshwater prawn species in the northern and central region of Argentina, has been used as a bioindicator of environmental pollutants as it displays a very high sensitivity to pollutants exposure. Despite their extraordinary ecological relevance, a lack of genomic information has hindered a more thorough understanding of the molecular mechanisms potentially involved in detoxification processes of this species. Thus, transcriptomic profiling studies represent a promising approach to overcome the limitations imposed by the lack of extensive genomic resources for P. argentinus, and may improve the understanding of its physiological and molecular response triggered by pollutants. This work represents the first comprehensive transcriptome-based characterization of the non-model species P. argentinus to generate functional genomic annotations and provides valuable resources for future genetic studies. Trinity de novo assembly consisted of 24,738 transcripts with high representation of detoxification (phase I and II), anti-oxidation, osmoregulation pathways and DNA replication and bioenergetics. This crustacean transcriptome provides valuable molecular information about detoxification and biochemical processes that could be applied as biomarkers in further ecotoxicology studies.