Recombining your way out of trouble: the genetic architecture of hybrid fitness under environmental stress

Hybridization between species is a fundamental evolutionary force that can both promote and delay adaptation. There is a deficit in our understanding of the genetic basis of hybrid fitness, especially in non-domesticated organisms. We also know little about how hybrid fitness changes as a function of environmental stress. Here, we made genetically variable F2 hybrid populations from two divergent Saccharomyces yeast species, exposed populations to ten toxins, and sequenced the most resilient hybrids on low coverage using ddRADseq. We expected to find strong negative epistasis and heterozygote advantage in the hybrid genomes. We investigated three aspects of hybridness: 1) hybridity, 2) interspecific heterozygosity, and 3) epistasis (positive or negative associations between non-homologous chromosomes). Linear mixed effect models revealed strong genotype-by-environment interactions with many chromosomes and chromosomal interactions showing species-biased content depending on the environment. Against our predictions, we found extensive selection against heterozygosity such that homozygous allelic combinations from the same species were strongly overrepresented in an otherwise hybrid genomic background. We also observed multiple cases of positive epistasis between chromosomes from opposite species, confirmed by epistasis- and selection-free simulations, which is surprising given the large divergence of the parental species (~15% genome-wide). Together, these results suggest that stress-resilient hybrid genomes can be assembled from the best features of both parents, without paying high costs of negative epistasis across large evolutionary distances. Our findings illustrate the importance of measuring genetic trait architecture in an environmental context when determining the evolutionary potential of hybrid populations

Editorial

Non peer reviewe

Intramolecular Phenotypic Capacitance in a Modular RNA Molecule

Phenotypic capacitance refers to the ability of a genome to accumulate mutations that are conditionally hidden and only reveal phenotype-altering effects after certain environmental or genetic changes. Capacitance has important implications for the evolution of novel forms and functions, but experimentally studied mechanisms behind capacitance are mostly limited to complex, multicomponent systems often involving several interacting protein molecules. Here we demonstrate phenotypic capacitance within a much simpler system, an individual RNA molecule with catalytic activity (ribozyme). This naturally occurring RNA molecule has a modular structure, where a scaffold module acts as an intramolecular chaperone that facilitates folding of a second catalytic module. Previous studies have shown that the scaffold module is not absolutely required for activity, but dramatically decreases the concentration of magnesium ions required for the formation of an active site. Here, we use an experimental perturbation of magnesium ion concentration that disrupts the folding of certain genetic variants of this ribozyme and use in vitro selection followed by deep sequencing to identify genotypes with altered phenotypes (catalytic activity). We identify multiple conditional mutations that alter the wild-type ribozyme phenotype under a stressful environmental condition of low magnesium ion concentration, but preserve the phenotype under more relaxed conditions. This conditional buffering is confined to the scaffold module, but controls the catalytic phenotype, demonstrating how modularity can enable phenotypic capacitance within a single macromolecule. RNA’s ancient role in life suggests that phenotypic capacitance may have influenced evolution since life’s origins

The Religious Identity of Young Muslim Women in Berlin

The Religious Identity of Young Muslim Women in Berlin offers an in-depth ethnographic account of Muslim youth’s religious identity formation and their engagement with Islam in everyday life. Focusing on Muslim women in the organisation MJD in Germany, it provides a deeper understanding of processes related to immigration, transnationalism, the transformation of identifications and the reconstruction of selfhood. The book deals with the collective content of religious identity formation and processes of differentiation, engaging with the changing role of religion in an urban European setting, restructuring of religious authority and the formation of gender identity through religion. Synnøve K.N. Bendixsen examines how the participants seek and debate what it means to be a good Muslim, and discusses the religious movement as individual engagement in a collective project

Empirical Investigations OF RNA Fitness Landscapes: Harnessing the Power of High-Throughput Sequencing and Evolutionary Simulations

Fitness landscapes or adaptive landscapes represent the mapping of genotype (sequence) to phenotype (function or fitness). Originally proposed as a metaphor to envision evolutionary processes and mutational interactions, the fitness landscape has recently transitioned from theoretical to empirical. This is due in part to advances in DNA synthesis and high-throughput sequencing. This allows for the construction and analysis of empirical fitness landscapes that encompass thousands of genotypes. These landscapes provide tractable insight into mutational pathways, the predictability of evolution or even the evolution of life. RNA enzymes (ribozymes) are an attractive model system for the construction of empirical fitness landscapes. Ribozymes function as both a genotype (primary RNA sequence) and a phenotype (catalytic function). To construct and characterize empirical RNA fitness landscapes, two high-throughput functional assays (self-cleavage and self-ligation), including a technique to improve data recovery from high-throughput sequencing using phased nucleotide inserts (Appendix A), were developed and implemented. Following fitness landscape construction, a stochastic evolutionary model was developed and employed based on the Wright-Fisher model. This model follows the principles of Darwinian evolution and allows a population to explore the fitness landscape by means of mutation and selection. These newly developed tools allowed for a novel approach to important evolutionary questions. Chapter 1 explored the evolution of innovation at the intersection of two ribozyme functions: self-cleavage and self-ligation. Evolutionary innovations are qualitatively novel traits that emerge through evolution. Theories have suggested that innovations can occur where two genotype networks are in close proximity. However, only isolated examples of intersections have been investigated. The fitness landscape between the two ribozyme functions was explored by determining the ability of numerous neighboring RNA sequences to catalyze two different chemical reactions. This revealed that there was extensive functional overlap, and over half the genotypes can catalyze both functions to some extent. Data-driven evolutionary simulations found that these numerous points of intersection facilitated the discovery of a new function, yet the rate of optimization depended upon the starting location in the genotype network. This study constructed a fitness landscape where genotype networks intersect and uncovered the implications for evolutionary innovations. Chapter 2 determined the effect of higher sequence space complexity and dimensionality on evolutionary adaptation in RNA fitness landscapes. The complexity and dimensionality of landscapes scale with the length of the RNA molecule. For this study, complexity was defined as the size of the genotype space and dimensionality as the number of edges connecting each genotype (node) to other genotypes that differ by a single mutation. Low-dimensional ‘direct’ landscapes consisting of only two possible nucleotides at various positions were compared to higher-dimensional ‘indirect’ landscapes that had all four nucleotides at the same positions. Indirect pathways contributed to the ruggedness and navigability of landscapes. Increased dimensionality in RNA fitness landscapes had the potential to circumvent fitness valleys, however indirect pathways also harbored stasis genotypes isolated by reciprocal sign epistasis. Chapter 3 applied ancestral sequence resurrection and fitness landscape construction to naturally evolved ribozymes. The CPEB3 ribozyme is highly conserved in mammals and has been linked to episodic memory. By predicting, ‘resurrecting’ and functionally characterizing ancient gene sequences, hypotheses about gene function or selection can be empirically tested in an evolutionary context. Using the extant ribozyme sequences found in a range of mammalian species as a basis for inference of ancestral sequences, a phylogenetic fitness landscape was experimentally resurrected and reconstructed. A single high-activity ancestral sequence was found to be highly conserved and purifying selection is expected to have reduced the accumulation of mutations through geologic time. Many of the extant mammalian ribozyme sequences had high ribozyme activity, however a few had relatively low activity. Yet, given the local fitness landscape, a selective pressure for functional ribozyme sequences was seen. A single nucleotide polymorphism (SNP) found in humans, reduced co-transcriptional ribozyme activity in vitro and might alter our understanding of the CPEB3 ribozyme’s biological function. Chapter 4 analyzed epistatic interactions in four published RNA fitness landscapes generated from high-throughput analyses. Two of the landscapes were assessed in vivo and two were assessed in vitro. Epistasis occurs when the effects of some mutations are dependent on the presence or absence of other mutations. The data allowed for an analysis of the distribution of fitness effects of individual mutations as well as combinations of two or more mutations. Two different approaches to measuring epistasis in the data both revealed a predominance of negative epistasis, such that higher combinations of two or more mutations are typically lower in fitness than expected from the effect of each individual mutation. This finding differed from studies using computationally predicted RNA but is similar to mutational experiments in protein enzymes. The work presented here represents a significant contribution to our ability to construct and empirically characterize RNA fitness landscapes. The development of two high-throughput ribozyme assays opens the door for further empirical landscape construction. The implementation of data-driven stochastic evolutionary modeling allows for a clearer evolutionary characterization of the landscape. Understanding the connection between genotype and phenotype in RNA systems is important for designing RNA functions, improving in vitro selections and understanding the origins and evolution of new RNA functions (innovations). Applying these advances yielded valuable information about evolutionary innovations, the effects of higher dimensionality, evolution of extant ribozymes and the prevalence of epistasis in RNA fitness landscapes. Construction and analysis of empirical RNA fitness landscapes provides tractable insight into evolutionary processes, mutational pathways and the predictability of evolution

The "Nordic Model" in the Middle East Oil Fields: How Shareholder Value Eclipses Corporate Responsibility.

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Editorial of Nordic Journal of Migration Research

Non peer reviewe