Modeling adaptive and non-adaptive responses to environmental change

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient

Functional expression of PHO1 to the Golgi and trans-Golgi network and its role in export of inorganic phosphate.

Arabidopsis thaliana PHO1 is primarily expressed in the root vascular cylinder and is involved in the transfer of inorganic phosphate (Pi) from roots to shoots. To analyze the role of PHO1 in transport of Pi, we have generated transgenic plants expressing PHO1 in ectopic A. thaliana tissues using an estradiol-inducible promoter. Leaves treated with estradiol showed strong PHO1 expression, leading to detectable accumulation of PHO1 protein. Estradiol-mediated induction of PHO1 in leaves from soil-grown plants, in leaves and roots of plants grown in liquid culture, or in leaf mesophyll protoplasts, was all accompanied by the specific release of Pi to the extracellular medium as early as 2-3 h after addition of estradiol. Net Pi export triggered by PHO1 induction was enhanced by high extracellular Pi and weakly inhibited by the proton-ionophore carbonyl cyanide m-chlorophenylhydrazone. Expression of a PHO1-GFP construct complementing the pho1 mutant revealed GFP expression in punctate structures in the pericycle cells but no fluorescence at the plasma membrane. When expressed in onion epidermal cells or in tobacco mesophyll cells, PHO1-GFP was associated with similar punctate structures that co-localized with the Golgi/trans-Golgi network and uncharacterized vesicles. However, PHO1-GFP could be partially relocated to the plasma membrane in leaves infiltrated with a high-phosphate solution. Together, these results show that PHO1 can trigger Pi export in ectopic plant cells, strongly indicating that PHO1 is itself a Pi exporter. Interestingly, PHO1-mediated Pi export was associated with its localization to the Golgi and trans-Golgi networks, revealing a role for these organelles in Pi transport

Effect of time series length and resolution on abundance‐ and trait‐based early warning signals of population declines

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics

Regulatory feedback response mechanisms to phosphate starvation in rice

Phosphorus is a growth-limiting nutrient for plants. The growing scarcity of phosphate stocks threatens global food security. Phosphate-uptake regulation is so complex and incompletely known that attempts to improve phosphorus use efficiency have had extremely limited success. This study improves our understanding of the molecular mechanisms underlying phosphate uptake by investigating the transcriptional dynamics of two regulators: the Ubiquitin ligase PHO2 and the long non-coding RNA IPS1. Temporal measurements of RNA levels have been integrated into mechanistic mathematical models using advanced statistical techniques. Models based solely on current knowledge could not adequately explain the temporal expression profiles. Further modeling and bioinformatics analysis have led to the prediction of three regulatory features: the PHO2 protein mediates the degradation of its own transcriptional activator to maintain constant PHO2 mRNA levels; the binding affinity of the transcriptional activator of PHO2 is impaired by a phosphate-sensitive transcriptional repressor/inhibitor; and the extremely high levels of IPS1 and its rapid disappearance upon Pi re-supply are best explained by Pi-sensitive RNA protection. This work offers both new opportunities for plant phosphate research that will be essential for informing the development of phosphate efficient crop varieties, and a foundation for the development of models integrating phosphate with other stress responses

Diurnal control of iron responsive element containing mRNAs through iron regulatory proteins IRP1 and IRP2 is mediated by feeding rhythms.

Cellular iron homeostasis is regulated by iron regulatory proteins (IRP1 and IRP2) that sense iron levels (and other metabolic cues) and modulate mRNA translation or stability via interaction with iron regulatory elements (IREs). IRP2 is viewed as the primary regulator in the liver, yet our previous datasets showing diurnal rhythms for certain IRE-containing mRNAs suggest a nuanced temporal control mechanism. The purpose of this study is to gain insights into the daily regulatory dynamics across IRE-bearing mRNAs, specific IRP involvement, and underlying systemic and cellular rhythmicity cues in mouse liver. We uncover high-amplitude diurnal oscillations in the regulation of key IRE-containing transcripts in the liver, compatible with maximal IRP activity at the onset of the dark phase. Although IRP2 protein levels also exhibit some diurnal variations and peak at the light-dark transition, ribosome profiling in IRP2-deficient mice reveals that maximal repression of target mRNAs at this timepoint still occurs. We further find that diurnal regulation of IRE-containing mRNAs can continue in the absence of a functional circadian clock as long as feeding is rhythmic. Our findings suggest temporally controlled redundancy in IRP activities, with IRP2 mediating regulation of IRE-containing transcripts in the light phase and redundancy, conceivably with IRP1, at dark onset. Moreover, we highlight the significance of feeding-associated signals in driving rhythmicity. Our work highlights the dynamic nature and regulatory complexity in a metabolic pathway that had previously been considered well-understood

Detecting context dependence in the expression of life history trade‐offs

Life history trade‐offs are one of the central tenets of evolutionary demography. Trade‐offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero‐sum game between somatic and reproductive functions. While theory predicts that trade‐offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. One way to improve the detection of trade‐offs is by accounting for the environmental context, as trade‐off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. Here, we present a hierarchical multivariate ‘covariance reaction norm’ model, adapted from Martin (2023), to help detect context dependence in the expression of life‐history trade‐offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade‐offs. We then apply it to empirical datasets of yellow‐bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof‐of‐concept showing that new insights can be gained by applying our methodology, such as detecting trade‐offs only in specific environments. We discuss its potential for application to many of the existing long‐term demographic datasets and how it could improve our understanding of trade‐off expression in particular, and life history theory in general

Detecting context dependence in the expression of life history trade-offs

1. Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. 2. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. 3. Here, we present a hierarchical multivariate 'covariance reaction norm' model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. 4. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. 5. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general

Transcriptome-wide sites of collided ribosomes reveal principles of translational pausing.

Translation initiation is the major regulatory step defining the rate of protein production from an mRNA. Meanwhile, the impact of nonuniform ribosomal elongation rates is largely unknown. Using a modified ribosome profiling protocol based on footprints from two closely packed ribosomes (disomes), we have mapped ribosomal collisions transcriptome-wide in mouse liver. We uncover that the stacking of an elongating onto a paused ribosome occurs frequently and scales with translation rate, trapping ∼10% of translating ribosomes in the disome state. A distinct class of pause sites is indicative of deterministic pausing signals. Pause site association with specific amino acids, peptide motifs, and nascent polypeptide structure is suggestive of programmed pausing as a widespread mechanism associated with protein folding. Evolutionary conservation at disome sites indicates functional relevance of translational pausing. Collectively, our disome profiling approach allows unique insights into gene regulation occurring at the step of translation elongation

Higher temperature extremes exacerbate negative disease effects in a social mammal

DATA AVAILABILITY: All data to construct and project the individual-based model have been deposited on Zenodo: https://doi.org/10.5281/zenodo.5784649.CODE AVAILABILITY: All R scripts to construct and project the individual-based model have been deposited on Zenodo: https://doi.org/10.5281/zenodo.5784649.One important but understudied way in which climate change may impact the fitness of individuals and populations is by altering the prevalence of infectious disease outbreaks. This is especially true in social species where endemic diseases are widespread. Here we use 22 years of demographic data from wild meerkats (Suricata suricatta) in the Kalahari, where temperatures have risen steadily, to project group persistence under interactions between weather extremes and fatal tuberculosis outbreaks caused by infection with Mycobacterium suricattae. We show that higher temperature extremes increase the risk of outbreaks within groups by increasing physiological stress as well as the dispersal of males, which are important carriers of tuberculosis. Explicitly accounting for negative effects of tuberculosis outbreaks on survival and reproduction in groups more than doubles group extinction risk in 12 years under projected temperature increases. Synergistic climate–disease effects on demographic rates may therefore rapidly intensify climate-change impacts in natural populations.https://www.nature.com/nclimatehj2023Mammal Research Institut

Comprehensive Functional Analyses of Expressed Sequence Tags in Common Wheat (Triticum aestivum)

About 1 million expressed sequence tag (EST) sequences comprising 125.3 Mb nucleotides were accreted from 51 cDNA libraries constructed from a variety of tissues and organs under a range of conditions, including abiotic stresses and pathogen challenges in common wheat (Triticum aestivum). Expressed sequence tags were assembled with stringent parameters after processing with inbuild scripts, resulting in 37 138 contigs and 215 199 singlets. In the assembled sequences, 10.6% presented no matches with existing sequences in public databases. Functional characterization of wheat unigenes by gene ontology annotation, mining transcription factors, full-length cDNA, and miRNA targeting sites were carried out. A bioinformatics strategy was developed to discover single-nucleotide polymorphisms (SNPs) within our large EST resource and reported the SNPs between and within (homoeologous) cultivars. Digital gene expression was performed to find the tissue-specific gene expression, and correspondence analysis was executed to identify common and specific gene expression by selecting four biotic stress-related libraries. The assembly and associated information cater a framework for future investigation in functional genomics