Eco-evolutionary Dynamics of Individual-Based Food Webs

The past decade has seen the rise of high resolution datasets. One of the main surprises of analysing such data has been the discovery of a large genetic, phenotypic and behavioural variation and heterogeneous metabolic rates among individuals within natural populations. A parallel discovery from theory and experiments has shown a strong temporal convergence between evolutionary and ecological dynamics, but a general framework to analyse from individual-level processes the convergence between ecological and evolutionary dynamics and its implications for patterns of biodiversity in food webs has been particularly lacking. Here, as a first approximation to take into account intraspecific variability and the convergence between the ecological and evolutionary dynamics in large food webs, we develop a model from population genomics and microevolutionary processes that uses sexual reproduction, genetic-distance-based speciation and trophic interactions. We confront the model with the prey consumption per individual predator, species-level connectance and prey–predator diversity in several environmental situations using a large food web with approximately 25,000 sampled prey and predator individuals. We show higher than expected diversity of abundant species in heterogeneous environmental conditions and strong deviations from the observed distribution of individual prey consumption (i.e. individual connectivity per predator) in all the environmental conditions. The observed large variance in individual prey consumption regardless of the environmental variability collapsed species-level connectance after small increases in sampling effort. These results suggest (1) intraspecific variance in prey–predator interactions has a strong effect on the macroscopic properties of food webs and (2) intraspecific variance is a potential driver regulating the speed of the convergence between ecological and evolutionary dynamics in species-rich food webs. These results also suggest that genetic–ecological drift driven by sexual reproduction, equal feeding rate among predator individuals, mutations and genetic-distance-based speciation can be used as a neutral food web dynamics test to detect the ecological and microevolutionary processes underlying the observed patterns of individual and species-based food webs at local and macroecological scales.

Genomics of Divergence along a Continuum of Parapatric Population Differentiation

The patterns of genomic divergence during ecological speciation are shaped by a combination of evolutionary forces. Processes such as genetic drift, local reduction of gene flow around genes causing reproductive isolation, hitchhiking around selected variants, variation in recombination and mutation rates are all factors that can contribute to the heterogeneity of genomic divergence. On the basis of 60 fully sequenced three-spined stickleback genomes, we explore these different mechanisms explaining the heterogeneity of genomic divergence across five parapatric lake and river population pairs varying in their degree of genetic differentiation. We find that divergent regions of the genome are mostly specific for each population pair, while their size and abundance are not correlated with the extent of genome-wide population differentiation. In each pair-wise comparison, an analysis of allele frequency spectra reveals that 25–55% of the divergent regions are consistent with a local restriction of gene flow. Another large proportion of divergent regions (38–75%) appears to be mainly shaped by hitchhiking effects around positively selected variants. We provide empirical evidence that alternative mechanisms determining the evolution of genomic patterns of divergence are not mutually exclusive, but rather act in concert to shape the genome during population differentiation, a first necessary step towards ecological speciation.

Hox cluster genomics in the horn shark, Heterodontus francisci

Reconstructing the evolutionary history of Hox cluster origins will lead to insights into the developmental and evolutionary significance of Hox gene clusters in vertebrate phylogeny and to their role in the origins of various vertebrate body plans. We have isolated two Hox clusters from the horn shark, Heterodontus francisci. These have been sequenced and compared with one another and with other chordate Hox clusters. The results show that one of the horn shark clusters (HoxM) is orthologous to the mammalian HoxA cluster and shows a structural similarity to the amphioxus cluster, whereas the other shark cluster (HoxN) is orthologous to the mammalian HoxD cluster based on cluster organization and a comparison with noncoding and Hox gene-coding sequences. The persistence of an identifiable HoxA cluster over an 800-million-year divergence time demonstrates that the Hox gene clusters are highly integrated and structured genetic entities. The data presented herein identify many noncoding sequence motifs conserved over 800 million years that may function as genetic control motifs essential to the developmental process.

Targeted sequencing for high-resolution evolutionary analyses following genome duplication in salmonid fish : Proof of concept for key components of the insulin-like growth factor axis

Acknowledgements This study was funded by a Natural Environment Research Council grant (NERC, project code: NBAF704). FML is funded by a NERC Doctoral Training Grant (Project Reference: NE/L50175X/1). RLS was an undergraduate student at the University of Aberdeen and benefitted from financial support from the School of Biological Sciences. DJM is indebted to Dr. Steven Weiss (University of Graz, Austria), Dr. Takashi Yada (National Research Institute of Fisheries Science, Japan), Dr. Robert Devlin (Fisheries and Oceans Canada, Canada), Prof. Samuel Martin (University of Aberdeen, UK), Mr. Neil Lincoln (Environment Agency, UK) and Prof. Colin Adams/Mr. Stuart Wilson (University of Glasgow, UK) for providing salmonid material or assisting with its sampling. We are grateful to staff at the Centre for Genomics Research (University of Liverpool, UK) (i.e. NERC Biomolecular Analysis Facility – Liverpool; NBAF-Liverpool) for performing sequence capture/Illumina sequencing and providing us with details on associated methods that were incorporated into the manuscript. Finally, we are grateful to the organizers of the Society of Experimental Biology Satellite meeting 'Genome-powered perspectives in integrative physiology and evolutionary biology' (held in Prague, July 2015) for inviting us to contribute to this special edition of Marine Genomics and hosting a really stimulating meeting.

Behavior Genetics and Post Genomics

The science of genetics is undergoing a paradigm shift. Recent discoveries, including the activity of retrotransposons, the extent of copy number variations, somatic and chromosomal mosaicism, and the nature of the epigenome as a regulator of DNA expressivity, are challenging a series of dogmas concerning the nature of the genome and the relationship between genotype and phenotype. DNA, once held to be the unchanging template of heredity, now appears subject to a good deal of environmental change; considered to be identical in all cells and tissues of the body, there is growing evidence that somatic mosaicism is the normal human condition; and treated as the sole biological agent of heritability, we now know that the epigenome, which regulates gene expressivity, can be inherited via the germline. These developments are particularly significant for behavior genetics for at least three reasons: First, these phenomena appear to be particularly prevalent in the human brain, and likely are involved in much of human behavior; second, they have important implications for the validity of heritability and gene association studies, the methodologies that largely define the discipline of behavior genetics; and third, they appear to play a critical role in development during the perinatal period, and in enabling phenotypic plasticity in offspring in particular. I examine one of the central claims to emerge from the use of heritability studies in the behavioral sciences, the principle of “minimal shared maternal effects,” in light of the growing awareness that the maternal perinatal environment is a critical venue for the exercise of adaptive phenotypic plasticity. This consideration has important implications for both developmental and evolutionary biology

An updated evolutionary classification of CRISPR–Cas systems

The evolution of CRISPR–cas loci, which encode adaptive immune systems in archaea and bacteria, involves rapid changes, in particular numerous rearrangements of the locus architecture and horizontal transfer of complete loci or individual modules. These dynamics complicate straightforward phylogenetic classification, but here we present an approach combining the analysis of signature protein families and features of the architecture of cas loci that unambiguously partitions most CRISPR–cas loci into distinct classes, types and subtypes. The new classification retains the overall structure of the previous version but is expanded to now encompass two classes, five types and 16 subtypes. The relative stability of the classification suggests that the most prevalent variants of CRISPR–Cas systems are already known. However, the existence of rare, currently unclassifiable variants implies that additional types and subtypes remain to be characterized.

A generative design system based on evolutionary and mathematical functions

Previous work by Professor John Frazer on Evolutionary Architecture provides a basis for the development of a system evolving architectural envelopes in a generic and abstract manner. Recent research by the authors has focused on the implementation of a virtual environment for the automatic generation and exploration of complex forms and architectural envelopes based on solid modelling techniques and the integration of evolutionary algorithms, enhanced computational and mathematical models. Abstract data types are introduced for genotypes in a genetic algorithm order to develop complex models using generative and evolutionary computing techniques. Multi-objective optimisation techniques are employed for defining the fitness function in the evaluation process.