No abstract

International initiatives aimed at generating genomic resources, and particularly reference genomes, have flourished in recent years. Some focus on specific taxa, such as the Vertebrate Genomes Project, Bird Genome 10K Project, Bat1K Project, Global Invertebrate Genomics Alliance, 10 000 Plant Genomes Project, and 1000 Fungal Genomes project. Others focus on geographic regions, such as the California Conservation Genomics Project, Darwin Tree of Life for Britain and Ireland, Catalan Initiative for the Earth BioGenome Project in the Catalan territories, Endemixit in Italy, Norwegian Earth Biogenome Project, and SciLifeLab in Sweden, on applications such as the LOEWE Translational Biodiversity Genomics in Germany, or on ecological systems such as the Aquatic Symbiosis Genomics project. Collectively part of the Earth BioGenome Project (EBP), in Europe these initiatives are organized under the umbrella of the European Reference Genome Atlas (ERGA). A genome atlas of European biodiversityERGA is a pan-European scientific response to the current threats to biodiversity. Approximately one fifth of the ~200 000 eukaryotic species present in Europe can be inferred to be at risk of extinction according to the International Union for Conservation of Nature (IUCN) Red List classification (this estimate only considers the assessed species; https://www.iucn.org/regions/europe/our-work/biodiversity-conservation/european-red-list-threatened-species).ERGA aims to generate reference genomes of European eukaryotic species across the tree of life, including threatened, endemic, and keystone species, as well as pests and species important to agriculture, fisheries, and ecosystem function and stability. ERGA builds upon current genomic consortia in EU member states, EU Associated Countries, representatives of other countries within the European bioregion, and international collaborators. These reference genomes will address fundamental and applied questions in conservation, biology, and health. ERGA seeks to alert the EU about the potential of conservation genomics, and particularly the role of reference genomes, in biodiversity assessment, conservation strategies, and restoration efforts.

The need to better understand how plasticity and evolution affect organismal responses to environmental variability is paramount in the face of global climate change. The potential for using RNA sequencing (RNA-seq) to study complex responses by non-model organisms to the environment is evident in a rapidly growing body of literature. This is particularly true of fishes for which research has been motivated by their ecological importance, socioeconomic value, and increased use as model species for medical and genetic research. Here, we review studies that have used RNA-seq to study transcriptomic responses to continuous abiotic variables to which fishes have likely evolved a response and that are predicted to be affected by climate change (e.g., salinity, temperature, dissolved oxygen concentration, and pH). Field and laboratory experiments demonstrate the potential for individuals to respond plastically to short-and long-term environmental stress and reveal molecular mechanisms underlying developmental and transgenerational plasticity, as well as adaptation to different environmental regimes. We discuss experimental, analytical, and conceptual issues that have arisen from this work and suggest avenues for future study.

Characterization and population genetic analysis of multilocus genes, such as those found in the major histocompatibility complex (MHC) is challenging in nonmodel vertebrates. The traditional method of extensive cloning and Sanger sequencing is costly and time-intensive and indirect methods of assessment often underestimate total variation. Here, we explored the suitability of 454 pyrosequencing for characterizing multilocus genes for use in population genetic studies. We compared two sample tagging protocols and two bioinformatic procedures for 454 sequencing through characterization of a 185-bp fragment of MHC DRB exon 2 in wolverines (Gulo gulo) and further compared the results with those from cloning and Sanger sequencing. We found 10 putative DRB alleles in the 88 individuals screened with between two and four alleles per individual, suggesting amplification of a duplicated DRB gene. In addition to the putative alleles, all individuals possessed an easily identifiable pseudogene. In our system, sequence variants with a frequency below 6% in an individual sample were usually artefacts. However, we found that sample preparation and data processing procedures can greatly affect variant frequencies in addition to the complexity of the multilocus system. Therefore, we recommend determining a per-amplicon-variant frequency threshold for each unique system. The extremely deep coverage obtained in our study (approximately 5000×) coupled with the semi-quantitative nature of pyrosequencing enabled us to assign all putative alleles to the two DRB loci, which is generally not possible using traditional methods. Our method of obtaining locus-specific MHC genotypes will enhance population genetic analyses and studies on disease susceptibility in nonmodel wildlife species.

No abstract

The deep learning (DL) revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. New methods provide analysis of data from sensors, cameras, and acoustic recorders, even in real time, in ways that are reproducible and rapid. Off-the-shelf algorithms find, count, and classify species from digital images or video and detect cryptic patterns in noisy data. These endeavours require collaboration across ecological and data science disciplines, which can be challenging to initiate. To promote the use of DL towards ecosystem-based management of the sea, this paper aims to bridge the gap between marine ecologists and computer scientists. We provide insight into popular DL approaches for ecological data analysis, focusing on supervised learning techniques with deep neural networks, and illustrate challenges and opportunities through established and emerging applications of DL to marine ecology. We present case studies on plankton, fish, marine mammals, pollution, and nutrient cycling that involve object detection, classification, tracking, and segmentation of visualized data. We conclude with a broad outlook of the field’s opportunities and challenges, including potential technological advances and issues with managing complex data sets.

Abstract Genetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modelling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multi-locus model. Single-locus control of complex traits is thought to be uncommon, yet blocks of linked genes, such as those associated with some types of structural genomic variation, have emerged as taxonomically widespread phenomena. Inheritance of linked architectures resembles that of single loci, thus enabling single-locus-like modeling of polygenic adaptation. Yet, the number of loci, their effect sizes, and the degree of linkage among them all occur along a continuum. We review how linked architectures are often associated, directly or indirectly, with traits expected to be under selection from anthropogenic stressors and are likely to play a large role in adaptation to environmental disturbance. We suggest using single-locus models to explore evolutionary extremes and uncertainties when the trait architecture is unknown, refining parameters as genomic information becomes available, and explicitly incorporating linkage among loci when possible. By overestimating the complexity (e.g., number of independent loci) of the genomic architecture of traits under selection, we risk underestimating the complexity (e.g., nonlinearity) of their evolutionary dynamics.

The ability of populations to adapt to environmental change and the spatial scale at which this adaptation occurs are fundamentally important issues in evolutionary biology, and ones that may benefit greatly from the study of genetic variability in reaction norms, which represent the plasticity of phenotypic traits across an environmental gradient. Therefore variable reaction norms can reflect genetic differences in the ability of individuals, families, populations, and species to respond to natural and anthropogenic environmental change. Fishes are ideal organisms in which to study plasticity because of their remarkable intraspecific morphological, physiological, behavioural, and life history variation. Here, we review studies demonstrating genetic variability in reaction norms in fishes. Genetic variability in plasticity among full-and half-sib families suggests potential for some populations to develop an adaptive norm of reaction (recalling that plasticity need not be adaptive). Reaction norm variability among populations suggests that adaptive genetic divergence can occur rapidly when selection pressures are strong and that the spatial scale of adaptation is much smaller than previously believed for some species with high dispersal capabilities. These studies demonstrate the potential of using reaction norms to study the evolution of novel phenotypes and the influence of temporal environmental variability and gene flow on the evolution of phenotypic plasticity, which can then be used to predict how populations will respond to directional environmental change. To promote future research into genetic variability in reaction norms, we propose questions that would benefit from such an approach and discuss some important considerations for designing experiments to investigate questions related to genetic variation in plasticity and phenotypic evolution.Résumé : La capacité d'adaptation au changement environnemental et l'échelle spatiale à laquelle cette adaptation survient, constituent des défis d'importance fondamentale en biologie évolutive, un sujet qui pourrait bénéficier grandement de l'étude de la variabilité des normes de réaction. Les normes de réaction représentent la plasticité des traits phénotypiques le long d'un gradient environnemental. Conséquemment, des normes de réaction variables peuvent refléter des différences génétiques dans la capacité des individus, des familles, des populations et des espèces à réagir au changement environnemental naturel et anthropogène. Les poissons constituent des organismes idéaux pour l'étude de la plasticité compte tenu de la variation intraspécifique remarquable de leur morphologie, de leur physiologie, de leur comportement et de leur cycle de vie. Les auteurs passent en revue les études démontrant la variabilité génétique des normes de réaction chez les poissons. La variabilité de la plasticité parmi les familles biparentales ou mono parentales suggère la capacité de certaines populations à développer une norme de réaction adaptative (en se rappelant que la plastic...