Population Genomics Reveals the Underlying Structure of the Small Pelagic European Sardine and Suggests Low Connectivity within Macaronesia.

The European sardine (Sardina pilchardus, Walbaum 1792) is indisputably a commercially important species. Previous studies using uneven sampling or a limited number of makers have presented sometimes conflicting evidence of the genetic structure of S. pilchardus populations. Here, we show that whole genome data from 108 individuals from 16 sampling areas across 5000 km of the species' distribution range (from the Eastern Mediterranean to the archipelago of Azores) support at least three genetic clusters. One includes individuals from Azores and Madeira, with evidence of substructure separating these two archipelagos in the Atlantic. Another cluster broadly corresponds to the center of the distribution, including the sampling sites around Iberia, separated by the Almeria-Oran front from the third cluster that includes all of the Mediterranean samples, except those from the Alboran Sea. Individuals from the Canary Islands appear to belong to the Mediterranean cluster. This suggests at least two important geographical barriers to gene flow, even though these do not seem complete, with many individuals from around Iberia and the Mediterranean showing some patterns compatible with admixture with other genetic clusters. Genomic regions corresponding to the top outliers of genetic differentiation are located in areas of low recombination indicative that genetic architecture also has a role in shaping population structure. These regions include genes related to otolith formation, a calcium carbonate structure in the inner ear previously used to distinguish S. pilchardus populations. Our results provide a baseline for further characterization of physical and genetic barriers that divide European sardine populations, and information for transnational stock management of this highly exploited species towards sustainable fisheries.

Inferring the mode and strength of ongoing selection.

Genome sequence data are no longer scarce. The UK Biobank alone comprises 200,000 individual genomes, with more on the way, leading the field of human genetics toward sequencing entire populations. Within the next decades, other model organisms will follow suit, especially domesticated species such as crops and livestock. Having sequences from most individuals in a population will present new challenges for using these data to improve health and agriculture in the pursuit of a sustainable future. Existing population genetic methods are designed to model hundreds of randomly sampled sequences but are not optimized for extracting the information contained in the larger and richer data sets that are beginning to emerge, with thousands of closely related individuals. Here we develop a new method called trio-based inference of dominance and selection (TIDES) that uses data from tens of thousands of family trios to make inferences about natural selection acting in a single generation. TIDES further improves on the state of the art by making no assumptions regarding demography, linkage, or dominance. We discuss how our method paves the way for studying natural selection from new angles.

Population Genomics of the Maize Pathogen Ustilago maydis: Demographic History and Role of Virulence Clusters in Adaptation.

The tight interaction between pathogens and their hosts results in reciprocal selective forces that impact the genetic diversity of the interacting species. The footprints of this selection differ between pathosystems because of distinct life-history traits, demographic histories, or genome architectures. Here, we studied the genome-wide patterns of genetic diversity of 22 isolates of the causative agent of the corn smut disease, Ustilago maydis, originating from five locations in Mexico, the presumed center of origin of this species. In this species, many genes encoding secreted effector proteins reside in so-called virulence clusters in the genome, an arrangement that is so far not found in other filamentous plant pathogens. Using a combination of population genomic statistical analyses, we assessed the geographical, historical, and genome-wide variation of genetic diversity in this fungal pathogen. We report evidence of two partially admixed subpopulations that are only loosely associated with geographic origin. Using the multiple sequentially Markov coalescent model, we inferred the demographic history of the two pathogen subpopulations over the last 0.5 Myr. We show that both populations experienced a recent strong bottleneck starting around 10,000 years ago, coinciding with the assumed time of maize domestication. Although the genome average genetic diversity is low compared with other fungal pathogens, we estimated that the rate of nonsynonymous adaptive substitutions is three times higher in genes located within virulence clusters compared with nonclustered genes, including nonclustered effector genes. These results highlight the role that these singular genomic regions play in the evolution of this pathogen.

A Population Genomics Lexicon.

Population genomics is a growing field stemming from soon a 100 years of developments in population genetics. Here, we summarize the main concepts and terminology underlying both theoretical and empirical statistical population genomics studies. We provide the reader with pointers toward the original literature as well as methodological and historical reviews.

On the limits of complexity in living forms.

In a recent book chapter, Morris, S.C., 2013. Life: the final frontier for complexity? In: Lineweaver, C.H., Davies, P.C.W., Ruse, M. (Eds.), Complexity and the Arrow of Time. pp. 135-161. argues that there are limits to the complexity of life forms and that with the exception of human beings these limits have already been reached. We recommend seeing human use of technology as a natural, evolutionary process. We then proceed to claim that biological engineering other species to increase their complexity can be an efficient way to delay the heat death locally. Whenever, wherever in the universe living things become intelligent enough to perform these kinds of operations, they will be able to increase complexity around them as long as a gradient of energy is available. This conclusion has deep impact on both science and philosophy.