A multiscale approach to detect selection in nonmodel tree species: Widespread adaptation despite population decline in Taxus baccata L

Microbial glycosylation of antitubercular agent chlorflavonin

Flavonoids have shown health-benefiting properties, such as antioxidative and anti-inflammatory activities, and are commonly used as nutraceuticals and pharmaceuticals. Although flavonoids are predominantly identified from plants, several filamentous fungal species have also been reported to produce bioactive flavonoids, including chlorflavonin from Aspergillus candidus, a novel halogenated flavonoid with potent antifungal and antitubercular (anti-TB) activities. Unfortunately, the low water-solubility of this molecule may hinder its bioavailability. Glycosylation is an effective method to enhance the polarity of natural products and alter their physicochemical properties. This work focuses on the development of novel water-soluble chlorflavonin derivatives to combat the threat of drug-resistant tuberculosis. In this study, we first increased the production titer of chlorflavonin in A. candidus NRRL 5214 by optimizing the fermentation and purification processes. Next, chlorflavonin-5-O-β-d-glucuronopyranoside (1) and chlorflavonin-7-O-4″-O-methyl-β-d-glucopyranoside (2) were produced from chlorflavonin using Streptomyces chromofuscus ATCC 49982 and Beauveria bassiana ATCC 7159, respectively. Compared to chlorflavonin (4.38 ± 0.54 mg/L in water), the water solubility of the two new glycosides was determined to be 117.86 ± 4.81 mg/L (1) and 124.34 ± 9.13 mg/L (2), respectively. This study provides a promising method to create water-soluble glycosides of chlorflavonin for the development of novel anti-TB drugs.

Genomic insights into genetic diversity and local adaptation of a dominant desert steppe feather grass, Stipa breviflora Griseb

Investigating the genetic mechanisms of local adaptation is critical to understanding how species adapt to heterogeneous environments. In the present study, we analyzed restriction site-associated DNA sequencing (RADseq) data in order to explore genetic diversity, genetic structure, genetic differentiation, and local adaptation of Stipa breviflora. In total, 135 individual plants were sequenced and 25,786 polymorphic loci were obtained. We found low genetic diversity (He = 0.1284) within populations of S. breviflora. Four genetic clusters were identified along its distribution range. The Mantel test, partial Mantel test, and multiple matrix regression with randomization (MMRR) indicate that population differentiation was caused by both geographic distance and environmental factors. Through the F_ST outlier test and environmental association analysis (EAA), 113 candidate loci were identified as putatively adaptive loci. RPK2 and CPRF1, which are associated with meristem maintenance and light responsiveness, respectively, were annotated. To explore the effects of climatic factors on genetic differentiation and local adaptation of S. breviflora, gradient forest (GF) analysis was applied to 25,786 single nucleotide polymorphisms (SNPs) and 113 candidate loci, respectively. The results showed that both temperature and precipitation affected the genetic differentiation of S. breviflora, and precipitation was strongly related to local adaptation. Our study provides a theoretical basis for understanding the local adaptation of S. breviflora.

Adaptive divergence for a drought resistance related trait among invasive Saltcedar (Tamarix L.) populations in southwestern US: Inferences from QCT - FCT

Biological invasion poses several biotic and abiotic challenges due to abrupt distribution shifts. Invasive species may benefit from local adaptation responding to environmental stresses during colonization. Saltcedar (Tamarix), a notorious invasive shrub in the western US introduced from Eurasia may have adapted to low rainfall as the species widely occupies the arid land throughout the southwestern US. We investigated variation of quantitative traits in saltcedar between two regions exhibiting opposing average annual precipitations under experimentally manipulated water treatments to test local adaptation. We measured eight quantitative traits, proxies for fitness and genotyped 64 individual samples using genotype by sequencing technique. To test local adaptation, we applied Q_CT - F_CT test based on null distribution of F_CT estimated from 2,697 genome-wide SNPs and Q_CT estimated for the eight phenotypic traits measured. Saltcedar in the southwestern US exhibited a significant interaction between the degree of leaf loss (biomass loss by senesced leaves to total biomass) under simulated drought conditions and the origins from which the genotypes were collected, either relatively high or low rainfall regimes. The divergence found in leaf loss was significantly greater among regions than the expected given the genetic divergence on neutral loci suggesting signature of local adaptation responding to drought. The results demonstrate adaptive potential of saltcedar populations to extreme drought. As extreme aridity is often predicted in climate models across the southwestern US, the western saltcedar genotypes locally adapted to drought may further expand their ranges in this region.

Polygenic adaptation and negative selection across traits, years and environments in a long-lived plant species (Pinus pinaster Ait., Pinaceae)

A decade of genetic association studies in multiple organisms suggests that most complex traits are polygenic, i.e., they have a genetic architecture determined by numerous loci each with small effect-size. Thus, determining the degree of polygenicity and its variation across traits, environments and time is crucial to understand the genetic basis of phenotypic variation. We applied multilocus approaches to estimate the degree of polygenicity of fitness-related traits in a long-lived plant (Pinus pinaster Ait., maritime pine) and to analyze this variation across environments and years. We evaluated five categories of fitness-related traits (survival, height, phenology, functional, and biotic-stress response traits) in a clonal common-garden network, planted in contrasted environments (over 12,500 trees). Most of the analyzed traits showed evidence of local adaptation based on Q_st -F_st comparisons. We further observed a remarkably stable degree of polygenicity, averaging 6% (range of 0-27%), across traits, environments and years. We detected evidence of negative selection, which could explain, at least partially, the high degree of polygenicity. Because polygenic adaptation can occur rapidly, our results suggest that current predictions on the capacity of natural forest tree populations to adapt to new environments should be revised, especially in the current context of climate change.

Signatures of natural selection in a foundation tree along Mediterranean climatic gradients

Temperature and precipitation regimes are rapidly changing, resulting in forest dieback and extinction events, particularly in Mediterranean‐type climates (MTC). Forest management that enhance forests’ resilience is urgently required, however adaptation to climates in heterogeneous landscapes with multiple selection pressures is complex. For widespread trees in MTC we hypothesized that: patterns of local adaptation are associated with climate; precipitation is a stronger factor of adaptation than temperature; functionally related genes show similar signatures of adaptation; and adaptive variants are independently sorting across the landscape. We sampled 28 populations across the geographic distribution of Eucalyptus marginata (jarrah), in South‐west Western Australia, and obtained 13,534 independent single nucleotide polymorphic (SNP) markers across the genome. Three genotype‐association analyses that employ different ways of correcting population structure were used to identify putatively adapted SNPs associated with independent climate variables. While overall levels of population differentiation were low (F_ST = 0.04), environmental association analyses found a total of 2336 unique SNPs associated with temperature and precipitation variables, with 1440 SNPs annotated to genic regions. Considerable allelic turnover was identified for SNPs associated with temperature seasonality and mean precipitation of the warmest quarter, suggesting that both temperature and precipitation are important factors in adaptation. SNPs with similar gene functions had analogous allelic turnover along climate gradients, while SNPs among temperature and precipitation variables had uncorrelated patterns of adaptation. These contrasting patterns provide evidence that there may be standing genomic variation adapted to current climate gradients, providing the basis for adaptive management strategies to bolster forest resilience in the future.

pH-responsive delivery vehicle based on RGD-modified polydopamine-paclitaxel-loaded poly (3-hydroxybutyrate-co-3-hydroxyvalerate) nanoparticles for targeted therapy in hepatocellular carcinoma

A limitation of current anticancer nanocarriers is the contradiction between multiple functions and favorable biocompatibility. Thus, we aimed to develop a compatible drug delivery system loaded with paclitaxel (PTX) for hepatocellular carcinoma (HCC) therapy. A basic backbone, PTX-loaded poly (3-hydroxybutyrate-co-3-hydroxyvalerate) PHBV nanoparticle (PHBV-PTX-NPs), was prepared by emulsion solvent evaporation. As a gatekeeper, the pH-sensitive coating was formed by self-polymerization of dopamine (PDA). The HCC-targeted arginine-glycine-aspartic acid (RGD)-peptide and PDA-coated nanoparticles (NPs) were combined through the Michael addition. Subsequently, the physicochemical properties of RGD-PDA-PHBV-PTX-NPs were characterized by dynamic light scattering-autosizer, transmission electron microscope, fourier transform infrared spectroscopy, differential scanning calorimetry, thermogravimetry and X-ray spectroscopy. As expected, the RGD-PDA-PHBV-PTX-NPs showed robust anticancer efficacy in a xenograft mouse model. More importantly, they exhibited lower toxicity than PTX to normal hepatocytes and mouse in vitro and in vivo, respectively. Taken together, these results indicate that the RGD-PDA-PHBV-PTX-NPs are potentially beneficial for easing conflict between multifunction and biocompatible characters of nanocarriers.

Temperature, rainfall and wind variables underlie environmental adaptation in natural populations of Drosophila melanogaster

While several studies in a diverse set of species have shed light on the genes underlying adaptation, our knowledge on the selective pressures that explain the observed patterns lags behind. Drosophila melanogaster is a valuable organism to study environmental adaptation because this species originated in Southern Africa and has recently expanded worldwide, and also because it has a functionally well-annotated genome. In this study, we aimed to decipher which environmental variables are relevant for adaptation of D. melanogaster natural populations in Europe and North America. We analysed 36 whole-genome pool-seq samples of D. melanogaster natural populations collected in 20 European and 11 North American locations. We used the BayPass software to identify single nucleotide polymorphisms (SNPs) and transposable elements (TEs) showing signature of adaptive differentiation across populations, as well as significant associations with 59 environmental variables related to temperature, rainfall, evaporation, solar radiation, wind, daylight hours, and soil type. We found that in addition to temperature and rainfall, wind related variables are also relevant for D. melanogaster environmental adaptation. Interestingly, 23%-51% of the genes that showed significant associations with environmental variables were not found overly differentiated across populations. In addition to SNPs, we also identified 10 reference transposable element insertions associated with environmental variables. Our results showed that genome-environment association analysis can identify adaptive genetic variants that are undetected by population differentiation analysis while also allowing the identification of candidate environmental drivers of adaptation.

Identification of determinants of pollen donor fecundity using the hierarchical neighborhood model

Individual differences in male reproductive success drive genetic drift and natural selection, altering genetic variation and phenotypic trait distributions in future generations. Therefore, identifying the determinants of reproductive success is important for understanding the ecology and evolution of plants. Here, based on the spatially explicit mating model (the neighborhood model), we develop a hierarchical probability model that links co-dominant genotypes of offspring and candidate parents with phenotypic determinants of male reproductive success. The model accounts for pollen dispersal, genotyping errors as well as individual variation in selfing, pollen immigration, and differentiation of immigrant pollen pools. Unlike the classic neighborhood model approach, our approach is specially designed to account for excessive variation (overdispersion) in male fecundity. We implemented a Bayesian estimation method (the Windows computer program available at: https://www.ukw.edu.pl/pracownicy/plik/igor_chybicki/1806/) that, among others, allows for selecting phenotypic variables important for male fecundity and assessing the fraction of variance in fecundity (R² ) explained by selected variables. Simulations showed that our method outperforms both the classic neighborhood model and the two-step approach, where fecundities and the effects of phenotypic variables are estimated separately. The analysis of two data examples showed that in wind-pollinated trees, male fecundity depends on both the amount of produced pollen and the ability to pollen spread. However, despite that the tree size was positively correlated with male fecundity, it explained only a fraction of the total variance in fecundity, indicating the presence of additional factors. Finally, case studies highlighted the importance of accounting for pollen dispersal in the estimation of fecundity determinants.

Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate

Studying the genetics of adaptation to new environments in ecologically and industrially important tree species is currently a major research line in the fields of plant science and genetic improvement for tolerance to abiotic stress. Specifically, exploring the genomic basis of local adaptation is imperative for assessing the conditions under which trees will successfully adapt in situ to global climate change. However, this knowledge has scarcely been used in conservation and forest tree improvement because woody perennials face major research limitations such as their outcrossing reproductive systems, long juvenile phase, and huge genome sizes. Therefore, in this review we discuss predictive genomic approaches that promise increasing adaptive selection accuracy and shortening generation intervals. They may also assist the detection of novel allelic variants from tree germplasm, and disclose the genomic potential of adaptation to different environments. For instance, natural populations of tree species invite using tools from the population genomics field to study the signatures of local adaptation. Conventional genetic markers and whole genome sequencing both help identifying genes and markers that diverge between local populations more than expected under neutrality, and that exhibit unique signatures of diversity indicative of "selective sweeps." Ultimately, these efforts inform the conservation and breeding status capable of pivoting forest health, ecosystem services, and sustainable production. Key long-term perspectives include understanding how trees' phylogeographic history may affect the adaptive relevant genetic variation available for adaptation to environmental change. Encouraging "big data" approaches (machine learning-ML) capable of comprehensively merging heterogeneous genomic and ecological datasets is becoming imperative, too.

Adaptation to drought is coupled with slow growth, but independent from phenology in marginal silver fir (Abies alba Mill.) populations

Drought is one of the most important selection pressures for forest trees in the context of climate change. Yet, the different evolutionary mechanisms, and their environmental drivers, by which certain populations become more drought tolerant than others is still little understood. We studied adaptation to drought in 16 silver fir (Abies alba Mill.) populations from the French Mediterranean Alps by combining observations on seedlings from a greenhouse experiment (N = 8,199) and on adult tress in situ (N = 315). In the greenhouse, we followed half-sib families for four growing seasons for growth and phenology traits, and tested their water stress response in a "drought until death" experiment. Adult trees in the field were assessed for δ 13C, a proxy for water use efficiency, and genotyped at 357 SNP loci. SNP data was used to generate a null expectation for seedling trait divergence between populations in order to detect the signature of selection, and 31 environmental variables were used to identify the selective environment. We found that seedlings originating from populations with low soil water capacity grew more slowly, attained a smaller stature, and resisted water stress for a longer period of time in the greenhouse. Additionally, adult trees of these populations exhibited a higher water use efficiency as evidenced by their δ 13C. These results suggest a correlated evolution of the growth-drought tolerance trait complex. Population divergence in bud break phenology was adaptive only in the second growing season, and evolved independently from the growth-drought tolerance trait complex. Adaptive divergence in bud break phenology was principally driven by the inter- and intra-annual variation in temperature at the geographic origin of the population. Our results illustrate the different evolutionary strategies used by populations to cope with drought stress at the range limits across a highly heterogeneous landscape, and can be used to inform assisted migration programs.

Genomic insights into adaptation to heterogeneous environments for the ancient relictual Circaeaster agrestis (Circaeasteraceae, Ranunculales)

Investigating the interaction between environmental heterogeneity and local adaptation is critical for understanding the evolutionary history of a species, providing the premise for studying the response of organisms to rapid climate change. However, for most species how exactly the spatial heterogeneity promotes population divergence and how genomic variations contribute to adaptive evolution remain poorly understood. We examine the contributions of geographical and environmental variables to population divergence of the relictual, alpine herb Circaeaster agrestis, as well as the genetic basis of local adaptation using RAD-seq and plastome data. We detected significant genetic structure with an extraordinary disequilibrium of genetic diversity among regions, and signals of isolation-by-distance along with isolation-by-resistance. The populations were estimated to begin diverging in the late Miocene, along with a possible ancestral distribution of the Hengduan Mountains and adjacent regions. Both environmental gradient and redundancy analyses revealed significant association between genetic variation and temperature variables. Genome-environment association analyses identified 16 putatively adaptive loci related mainly to biotic and abiotic stress resistance. Our genome-wide data provide new insights into the important role of environmental heterogeneity in shaping genetic structure, and access the footprints of local adaptation in an ancient relictual species, informing future conservation efforts.

Forest genomics: Advancing climate adaptation, forest health, productivity, and conservation

Forest ecosystems provide important ecological services and resources, from habitat for biodiversity to the production of environmentally friendly products, and play a key role in the global carbon cycle. Humanity is counting on forests to sequester and store a substantial portion of the anthropogenic carbon dioxide produced globally. However, the unprecedented rate of climate change, deforestation, and accidental importation of invasive insects and diseases are threatening the health and productivity of forests, and their capacity to provide these services. Knowledge of genetic diversity, local adaptation, and genetic control of key traits is required to predict the adaptive capacity of tree populations, inform forest management and conservation decisions, and improve breeding for productive trees that will withstand the challenges of the 21st century. Genomic approaches have well accelerated the generation of knowledge of the genetic and evolutionary underpinnings of nonmodel tree species, and advanced their applications to address these challenges. This special issue of Evolutionary Applications features 14 papers that demonstrate the value of a wide range of genomic approaches that can be used to better understand the biology of forest trees, including species that are widespread and managed for timber production, and others that are threatened or endangered, or serve important ecological roles. We highlight some of the major advances, ranging from understanding the evolution of genomes since the period when gymnosperms separated from angiosperms 300 million years ago to using genomic selection to accelerate breeding for tree health and productivity. We also discuss some of the challenges and future directions for applying genomic tools to address long-standing questions about forest trees.