Harnessing the power of multi-omics data for predicting climate change response

Exploring and exploiting the rice phytobiome to tackle climate change challenges

The future of agriculture is uncertain under the current climate change scenario. Climate change directly and indirectly affects the biotic and abiotic elements that control agroecosystems, jeopardizing the safety of the world's food supply. A new area that focuses on characterizing the phytobiome is emerging. The phytobiome comprises plants and their immediate surroundings, involving numerous interdependent microscopic and macroscopic organisms that affect the health and productivity of plants. Phytobiome studies primarily focus on the microbial communities associated with plants, which are referred to as the plant microbiome. The development of high-throughput sequencing technologies over the past 10 years has dramatically advanced our understanding of the structure, functionality, and dynamics of the phytobiome; however, comprehensive methods for using this knowledge are lacking, particularly for major crops such as rice. Considering the impact of rice production on world food security, gaining fresh perspectives on the interdependent and interrelated components of the rice phytobiome could enhance rice production and crop health, sustain rice ecosystem function, and combat the effects of climate change. Our review re-conceptualizes the complex dynamics of the microscopic and macroscopic components in the rice phytobiome as influenced by human interventions and changing environmental conditions driven by climate change. We also discuss interdisciplinary and systematic approaches to decipher and reprogram the sophisticated interactions in the rice phytobiome using novel strategies and cutting-edge technology. Merging the gigantic datasets and complex information on the rice phytobiome and their application in the context of regenerative agriculture could lead to sustainable rice farming practices that are resilient to the impacts of climate change.

Multi-Omics Inform Invasion Risks Under Global Climate Change

Global climate change is exacerbating biological invasions; however, the roles of genomic and epigenomic variations and their interactions in future climate adaptation remain underexplored. Using the model invasive ascidian Botryllus schlosseri across the Northern Hemisphere, we investigated genomic and epigenomic responses to future climates and developed a framework to assess future invasion risks. We employed generalized dissimilarity modeling and gradient forest analyses to assess genomic and epigenomic offsets under climate change. Our results showed that populations with genomic maladaptation did not geographically overlap with those experiencing epigenomic maladaptation, suggesting that genomic and epigenomic variations play complementary roles in adaptation to future climate conditions. By integrating genomic and epigenomic offsets into the genome-epigenomic index, we predicted that populations with lower index values were less maladapted, indicating a higher risk of future invasions. Native populations exhibited lower offsets than invasive populations, suggesting greater adaptive potentials and higher invasion risks under future climate change scenarios. These results highlight the importance of incorporating multi-omics data into predictive models to study future climate (mal)adaptation and assess invasion risks under global climate change.

Does climate change increase the risk of marine toxins? Insights from changing seawater conditions

Marine toxins produced by marine organisms threaten human health and impose a heavy public health burden on coastal countries. Lately, there has been an emergence of marine toxins in regions that were previously unaffected, and it is believed that climate change may be a significant factor. This paper systematically summarizes the impact of climate change on the risk of marine toxins in terms of changes in seawater conditions. From our findings, climate change can cause ocean warming, acidification, stratification, and sea-level rise. These climatic events can alter the surface temperature, salinity, pH, and nutrient conditions of seawater, which may promote the growth of various algae and bacteria, facilitating the production of marine toxins. On the other hand, climate change may expand the living ranges of marine organisms (such as algae, bacteria, and fish), thereby exacerbating the production and spread of marine toxins. In addition, the sources, distribution, and toxicity of ciguatoxin, tetrodotoxin, cyclic imines, and microcystin were described to improve public awareness of these emerging marine toxins. Looking ahead, developing interdisciplinary cooperation, strengthening monitoring of emerging marine toxins, and exploring more novel approaches are essential to better address the risks of marine toxins posed by climate change. Altogether, the interrelationships between climate, marine ecology, and marine toxins were analyzed in this study, providing a theoretical basis for preventing and managing future health risks from marine toxins.

Experimental Evolution in a Warming World: The Omics Era

A comprehensive understanding of the genetic mechanisms that shape species responses to thermal variation is essential for more accurate predictions of the impacts of climate change on biodiversity. Experimental evolution with high-throughput resequencing approaches (evolve and resequence) is a highly effective tool that has been increasingly employed to elucidate the genetic basis of adaptation. The number of thermal evolve and resequence studies is rising, yet there is a dearth of efforts to integrate this new wealth of knowledge. Here, we review this literature showing how these studies have contributed to increase our understanding on the genetic basis of thermal adaptation. We identify two major trends: highly polygenic basis of thermal adaptation and general lack of consistency in candidate targets of selection between studies. These findings indicate that the adaptive responses to specific environments are rather independent. A review of the literature reveals several gaps in the existing research. Firstly, there is a paucity of studies done with organisms of diverse taxa. Secondly, there is a need to apply more dynamic and ecologically relevant thermal environments. Thirdly, there is a lack of studies that integrate genomic changes with changes in life history and behavioral traits. Addressing these issues would allow a more in-depth understanding of the relationship between genotype and phenotype. We highlight key methodological aspects that can address some of the limitations and omissions identified. These include the need for greater standardization of methodologies and the utilization of new technologies focusing on the integration of genomic and phenotypic variation in the context of thermal adaptation.

Putative climate adaptation in American pikas (Ochotona princeps) is associated with copy number variation across environmental gradients

Improved understanding of the genetic basis of adaptation to climate change is necessary for maintaining global biodiversity moving forward. Studies to date have largely focused on sequence variation, yet there is growing evidence that suggests that changes in genome structure may be an even more significant source of adaptive potential. The American pika (Ochotona princeps) is an alpine specialist that shows some evidence of adaptation to climate along elevational gradients, but previous work has been limited to single nucleotide polymorphism based analyses within a fraction of the species range. Here, we investigated the role of copy number variation underlying patterns of local adaptation in the American pika using genome-wide data previously collected across the entire species range. We identified 37-193 putative copy number variants (CNVs) associated with environmental variation (temperature, precipitation, solar radiation) within each of the six major American pika lineages, with patterns of divergence largely following elevational and latitudinal gradients. Genes associated (n = 158) with independent annotations across lineages, variables, and/or CNVs had functions related to mitochondrial structure/function, immune response, hypoxia, olfaction, and DNA repair. Some of these genes have been previously linked to putative high elevation and/or climate adaptation in other species, suggesting they may serve as important targets in future studies.

Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont

Since their radiation in the Middle Triassic period ∼240 million years ago, stony corals have survived past climate fluctuations and five mass extinctions. Their long-term survival underscores the inherent resilience of corals, particularly when considering the nutrient-poor marine environments in which they have thrived. However, coral bleaching has emerged as a global threat to coral survival, requiring rapid advancements in coral research to understand holobiont stress responses and allow for interventions before extensive bleaching occurs. This review encompasses the potential, as well as the limits, of multiomics data applications when applied to the coral holobiont. Synopses for how different omics tools have been applied to date and their current restrictions are discussed, in addition to ways these restrictions may be overcome, such as recruiting new technology to studies, utilizing novel bioinformatics approaches, and generally integrating omics data. Lastly, this review presents considerations for the design of holobiont multiomics studies to support lab-to-field advancements of coral stress marker monitoring systems. Although much of the bleaching mechanism has eluded investigation to date, multiomic studies have already produced key findings regarding the holobiont's stress response, and have the potential to advance the field further.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Predicting the future of our oceans-Evaluating genomic forecasting approaches in marine species

Climate change is restructuring biodiversity on multiple scales and there is a pressing need to understand the downstream ecological and genomic consequences of this change. Recent advancements in the field of eco-evolutionary genomics have sought to include evolutionary processes in forecasting species' responses to climate change (e.g., genomic offset), but to date, much of this work has focused on terrestrial species. Coastal and offshore species, and the fisheries they support, may be even more vulnerable to climate change than their terrestrial counterparts, warranting a critical appraisal of these approaches in marine systems. First, we synthesize knowledge about the genomic basis of adaptation in marine species, and then we discuss the few examples where genomic forecasting has been applied in marine systems. Next, we identify the key challenges in validating genomic offset estimates in marine species, and we advocate for the inclusion of historical sampling data and hindcasting in the validation phase. Lastly, we describe a workflow to guide marine managers in incorporating these predictions into the decision-making process.

Combination of RNAseq and RADseq to Identify Physiological and Adaptive Responses to Acidification in the Eastern Oyster (Crassostrea virginica)

Ocean acidification (OA) is a major stressor threatening marine calcifiers, including the eastern oyster (Crassostrea virginica). In this paper, we provide insight into the molecular mechanisms associated with resilience to OA, with the dual intentions of probing both acclimation and adaptation potential in this species. C. virginica were spawned, and larvae were reared in control or acidified conditions immediately after fertilization. RNA samples were collected from larvae and juveniles, and DNA samples were collected from juveniles after undergoing OA-induced mortality and used to contrast gene expression (RNAseq) and SNP (ddRADseq) profiles from animals reared under both conditions. Results showed convergence of evidence from both approaches, particularly in genes involved in biomineralization that displayed significant changes in variant frequencies and gene expression levels among juveniles that survived acidification as compared to controls. Downregulated genes were related to immune processes, supporting previous studies demonstrating a reduction in immunity from exposure to OA. Acclimation to OA via regulation of gene expression might confer short-term resilience to immediate threats; however, the costs may not be sustainable, underscoring the importance of selection of resilient genotypes. Here, we identified SNPs associated with survival under OA conditions, suggesting that this commercially and ecologically important species might have the genetic variation needed for adaptation to future acidification. The identification of genetic features associated with OA resilience is a highly-needed step for the development of marker-assisted selection of oyster stocks for aquaculture and restoration activities.

Evolutionary genomics: Insights from the invasive European starlings

Two fundamental questions for evolutionary studies are the speed at which evolution occurs, and the way that this evolution may present itself within an organism's genome. Evolutionary studies on invasive populations are poised to tackle some of these pressing questions, including understanding the mechanisms behind rapid adaptation, and how it facilitates population persistence within a novel environment. Investigation of these questions are assisted through recent developments in experimental, sequencing, and analytical protocols; in particular, the growing accessibility of next generation sequencing has enabled a broader range of taxa to be characterised. In this perspective, we discuss recent genetic findings within the invasive European starlings in Australia, and outline some critical next steps within this research system. Further, we use discoveries within this study system to guide discussion of pressing future research directions more generally within the fields of population and evolutionary genetics, including the use of historic specimens, phenotypic data, non-SNP genetic variants (e.g., structural variants), and pan-genomes. In particular, we emphasise the need for exploratory genomics studies across a range of invasive taxa so we can begin understanding broad mechanisms that underpin rapid adaptation in these systems. Understanding how genetic diversity arises and is maintained in a population, and how this contributes to adaptability, requires a deep understanding of how evolution functions at the molecular level, and is of fundamental importance for the future studies and preservation of biodiversity across the globe.

Genome-wide DNA methylation patterns harbour signatures of hatchling sex and past incubation temperature in a species with environmental sex determination

Conservation of thermally sensitive species depends on monitoring organismal and population-level responses to environmental change in real time. Epigenetic processes are increasingly recognized as key integrators of environmental conditions into developmentally plastic responses, and attendant epigenomic data sets hold potential for revealing cryptic phenotypes relevant to conservation efforts. Here, we demonstrate the utility of genome-wide DNA methylation (DNAm) patterns in the face of climate change for a group of especially vulnerable species, those with temperature-dependent sex determination (TSD). Due to their reliance on thermal cues during development to determine sexual fate, contemporary shifts in temperature are predicted to skew offspring sex ratios and ultimately destabilize sensitive populations. Using reduced-representation bisulphite sequencing, we profiled the DNA methylome in blood cells of hatchling American alligators (Alligator mississippiensis), a TSD species lacking reliable markers of sexual dimorphism in early life stages. We identified 120 sex-associated differentially methylated cytosines (DMCs; FDR < 0.1) in hatchlings incubated under a range of temperatures, as well as 707 unique temperature-associated DMCs. We further developed DNAm-based models capable of predicting hatchling sex with 100% accuracy (in 20 training samples and four test samples) and past incubation temperature with a mean absolute error of 1.2°C (in four test samples) based on the methylation status of 20 and 24 loci, respectively. Though largely independent of epigenomic patterning occurring in the embryonic gonad during TSD, DNAm patterns in blood cells may serve as nonlethal markers of hatchling sex and past incubation conditions in conservation applications. These findings also raise intriguing questions regarding tissue-specific epigenomic patterning in the context of developmental plasticity.

Application of Omics Tools in Designing and Monitoring Marine Protected Areas For a Sustainable Blue Economy

A key component of the global blue economy strategy is the sustainable extraction of marine resources and conservation of marine environments through networks of marine protected areas (MPAs). Connectivity and representativity are essential factors that underlie successful implementation of MPA networks, which can safeguard biological diversity and ecosystem function, and ultimately support the blue economy strategy by balancing ocean use with conservation. New “big data” omics approaches, including genomics and transcriptomics, are becoming essential tools for the development and maintenance of MPA networks. Current molecular omics techniques, including population-scale genome sequencing, have direct applications for assessing population connectivity and for evaluating how genetic variation is represented within and among MPAs. Effective baseline characterization and long-term, scalable, and comprehensive monitoring are essential for successful MPA management, and omics approaches hold great promise to characterize the full range of marine life, spanning the microbiome to megafauna across a range of environmental conditions (shallow sea to the deep ocean). Omics tools, such as eDNA metabarcoding can provide a cost-effective basis for biodiversity monitoring in large and remote conservation areas. Here we provide an overview of current omics applications for conservation planning and monitoring, with a focus on metabarcoding, metagenomics, and population genomics. Emerging approaches, including whole-genome sequencing, characterization of genomic architecture, epigenomics, and genomic vulnerability to climate change are also reviewed. We demonstrate that the operationalization of omics tools can enhance the design, monitoring, and management of MPAs and thus will play an important role in a modern and comprehensive blue economy strategy.

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges

Microbial communities are ubiquitous and carry an exceptionally broad metabolic capability. Upon environmental perturbation, microbes are also amongst the first natural responsive elements with perturbation-specific cues and markers. These communities are thereby uniquely positioned to inform on the status of environmental conditions. The advent of microbial omics has led to an unprecedented volume of complex microbiological data sets. Importantly, these data sets are rich in biological information with potential for predictive environmental classification and forecasting. However, the patterns in this information are often hidden amongst the inherent complexity of the data. There has been a continued rise in the development and adoption of machine learning (ML) and deep learning architectures for solving research challenges of this sort. Indeed, the interface between molecular microbial ecology and artificial intelligence (AI) appears to show considerable potential for significantly advancing environmental monitoring and management practices through their application. Here, we provide a primer for ML, highlight the notion of retaining biological sample information for supervised ML, discuss workflow considerations, and review the state of the art of the exciting, yet nascent, interdisciplinary field of ML-driven microbial ecology. Current limitations in this sphere of research are also addressed to frame a forward-looking perspective toward the realization of what we anticipate will become a pivotal toolkit for addressing environmental monitoring and management challenges in the years ahead.