20 research outputs found
Patterns of population structure and adaptive genetic variation in alpine populations of Picea abies (L.) Karst.
Get PDFForest trees dominate many alpine landscapes and are currently exposed to changing climate. Picea abies (L.) Karst (Norway spruce) is one of the most important conifer species of the Italian Alps due to its ecological and economical relevance. Natural populations of this species are found across steep environmental gradients with large differences in temperature and moisture availability. Steep environmental gradients represent interesting models to study the interaction between natural selection and gene flow, especially when aiming to understand adaptation processes under global change. The present work aims to understand adaptive responses to changing climate by determining and quantifying patterns of genetic diversity in natural population of P.abies. a wide array of potential candidate genes was tested, by means of Single Nucleotide Polymorphisms (SNPs), for correlation with climatic and environmental parameters at different spatial scales: i) a geographical scale corresponding to the natural distribution of P.abies across the Italian Alps and ii) at a regional scale on the Eastern Italian Alps. Weak population structure was revealed at the geographical scale with only one population clearly divergent from the unique major genetic cluster identified. At the regional scale, hierarchical analyses of molecular variance revealed that most of the genetic variability was found within populations (ca. 99%), and small but significant variation was also found due landscape features (ca. 0.38%). In order to detect potentially adaptive markers, classical FST outlier approaches were first applied and five outlier loci were revealed at broad scale, while contrasting results were obtained at the regional scale according to the model used. Subsequently, environmental association analysis were performed: at the geographical scale temperature and precipitation were found to influence allelic variation at seven polymorphic loci, while at the regional scale, the Alpine topography resulted a potential adaptive determinants at 19 polymorphic loci, thus considered of ecological relevance. The results obtained in this study may provide relevant information for forestry management and genetic conservation, to understand and quantify the effect of climate change on conifer species as well as their adaptive potential
Alpine forest genomics network (AForGeN): a report of the first annual meeting
No full textThe Alpine Forest Genomics Network was formed in 2011 and held its first annual meeting on June 24-26, 2012, in the Natural Park Adamello Brenta in Trentino Region, Italy. The meeting was attended by 30 researchers from the alpine region of Europe and had two primary goals: (1) for researchers to introduce each other to current and planned research activities in forest landscape genomics and (2) to develop a strategic vision for the network. A steering committee was elected and will develop a white paper over the next year. The next annual meeting will be held in Austria in June 201
Climate-related adaptive genetic variation and population structure in natural stands of Norway spruce in the South-Eastern Alps.
No full textForest trees dominate many Alpine landscapes that are currently exposed to changing climate. Norway spruce is one of the most important conifer species of the Italian Alps, and natural populations are found across steep environmental gradients with large differences in temperature and moisture availability. This study seeks to determine and quantify patterns of genetic diversity in natural populations toward understanding adaptive responses to changing climate. Across the Italian species range, 24 natural stands were sampled with a major focus on the Eastern Italian Alps. Sampled trees were genotyped for 384 selected single nucleotide polymorphisms (SNPs) from 285 genes. A wide array of potential candidate genes was tested for correlation with climatic parameters. To minimize false-positive association between genotype and climate, population structure was investigated. Pairwise F ST estimates between sampled populations ranged between 0.000 and 0.075, with the highest values involving the two disjoint populations, Valdieri, on the western Italian Alps, and Campolino, the most southern population on the Apennines. Despite considerable genetic admixture among populations, both Bayesian and multivariate approach identified four genetic clusters. Selection scans revealed five F ST outliers, and the environmental association analysis detected ten SNPs associated to one or more climatic variables. Overall, 13 potentially adaptive loci were identified, three of which have been reported in a previous study on the same species conducted on a broader geographical scale. In our study, precipitation, more than temperature, was often associated with genotype; therefore, it appears as the most important environmental variable associated with the high sensitivity of Norway spruce to soil water supply. These findings provide relevant information for understanding and quantifying climate change effects on this species and its ability to genetically adap
Genetic variation and adaptive potential to environment in five subalpine coniferous species
No full textForest ecosystems form a dominant landscape in many Alpine environments where natural populations of coniferous species are found across steep environmental gradients. Such populations are supposed to be tightly genetically adapted to these diverse environments; however the genetic basis of adaptation is still poorly understood. The present study investigated the genetic
pattern of five ecologically and economically important conifer species for the Italian Alps and Apennines: Abies alba Mill., Larix decidua Mill., Picea abies (L.) Karst, Pinus cembra L. and Pinus mugo Turra. Natural populations (from 24 to 36) of these species were sampled across the Italian species range, with a sampling core on the eastern Alps. Sampled trees were genotyped
for Single Nucleotide Polymorphisms (SNPs) markers. Genetic data were first used to investigate the pattern of population
structure within each species, using a Bayesian clustering analysis. The presence of 3 genetic clusters for A. alba and L.
decidua, and 4 for P. abies, P. cembra and P. mugo was revealed. The association between genetic variation and environmental
variables was then tested using a multivariate analysis and a Bayesian simulation, accounting for the inferred genetic structure. Genetic variation resulted significantly correlated with geographic position in all five species: latitude was highly significant for A. alba and longitude for the other species. As regarded to climatic variables, the Bayesian simulation identified a positive association between genetic variation (SNPs frequency) and winter precipitation and seasonal minimum temperature. Seasonal temperature and precipitations variables resulted as major ecological determinants for all species. Further analysis on a regional
scale are needed to deeply investigate the altitudinal gradient effec
Effects of climate on fine-scale spatial genetic structure in four alpine keystone species
Get PDFGenetic responses to environmental changes can take place at different spatial scales. While the effect of climate on the wide-range distribution of genetic diversity has been the focus of several recent studies, studies of genetic responses to climate at local scales are relatively scarce. Fine-scale spatial genetic structure (SGS) was investigated in four Alpine conifers (4 to 8 natural populations per species) in the Eastern Italian Alps. SNP assays were used to characterize SGS in Abies alba and Picea abies (384 SNPs), Larix decidua (528 SNPs) and Pinus cembra (768 SNPs). Significant SGS was found for 11 out of 25 populations tested, varying from Sp of 0.0018 in P. cembra to 0.0035 in Larix decidua. Several linear models were constructed to associate SGS with climate variables. Once corrected by confounding effects (e.g. differences of SGS across species due, for instance, to dispersal capability), the best model identified April minimum temperature and spring precipitation as the most relevant climatic variables associated with differences in SGS across populations. To study the potential effect of winter temperature in relation to plant physiology, two ecological indexes related to vegetation growth (chilling-degree-day, CDD, and freezing-degree-day, FDD) were also tested for association to SGS. A significant association was found between SGS and CDD across species. This study provides new insights on the expected genetic responses of four coniferous species to climate change at local scales, suggesting that climate change, through altering SGS, could also have relevant impacts in plant microevolutio
Adaptive variation in five conifer species across the Italian alpine ecosystems
No full textForest ecosystems form a dominant landscape in many alpine environments where natural populations of coniferous species are found across steep environmental gradients. Such populations are supposed to be tightly genetically adapted to these diverse environments; however the
genetic basis of these adaptations is poorly understood. A preliminary investigation was conducted on five ecologically and economically important conifer species for the Italian Alps and Apennines: Abies alba, Larix decidua, Picea abies, Pinus cembra and Pinus mugo. To understand genetic patterns of adaptive variation, natural populations of these species were sampled along an altitudinal gradient and genotyped for single nucleotide polymorphisms (SNPs) markers. Population structure was estimated using Bayesian clustering analyses and a multivariate method, revealing the presence of 3 genetic clusters for A. alba and L.decidua, and 4 for P.abies, P.cembra and P.mugo. Inferred genetic structure was tested for correlation with latitude, longitude and the altitudinal gradient using multivariate analysis. Genetic variation resulted significantly correlated with geographic location in all five species: latitude was highly significant for A. alba and longitude for the other species. Further analysis on a local scale are needed to deeply investigate the altitudinal gradient effect and possibly detect outlier loci associated to climatic and environmental parameter
Patterns of genetic variation across four forest species
No full textGenetic differentiation is related to the environmental heterogeneity and to the equilibrium between selection and gene flow. Both environmental variables and geography may affect genetic structure. Here, a single nucleotide polymorphism (SNP) genotyping was conduced on Abies alba Mill., Larix decidua L., Pinus cembra L. and Pinus mugo Turra, across their natural range in the Italian Alps and Apennines. Firstly, the presence of patterns of population structure was tested with Bayesian program, showing values of K between 3 and 5. Next, the genetic structure was correlated to a geographic factor, showing significant result only for P. cembra. To reduce dimensionality for the environmental variables a principal component analysis was used. Significant principal components (PC) were testing for association with SNPs through a Bayesian generalized linear mixed model. In all species, several SNPs were identified to be associated to PC1, corresponding to temperature and precipitation, in particular winter precipitation and seasonal minimum temperature. In A. alba, most SNPs were associated to PC2, corresponding to the seasonal minimum temperature
The geographical and environmental determinants of genetic diversity for four alpine conifers of the European Alps
Get PDFClimate is one of the most important drivers of local adaptation in forest tree species.
Standing levels of genetic diversity and structure within and among natural populations of forest trees are determined by the interplay between climatic heterogeneity and the balance between selection and gene flow. To investigate this interplay, single nucleotide polymorphisms (SNPs) were genotyped in 24 to 37 populations from four subalpine conifers, Abies alba Mill., Larix decidua Mill., Pinus cembra L. and Pinus mugo Turra, across their natural ranges in the Italian Alps and Apennines. Patterns of population structure were apparent using a Bayesian clustering program, STRUCTURE, which identified three to five genetic groups per species. Geographical correlates with these patterns, however, were only apparent for P. cembra. Multivariate environmental variables [i.e. principal components (PCs)] were subsequently tested for association with SNPs using a Bayesian generalized linear mixed model. The majority of the SNPs, ranging from six in L. decidua to 18 in P. mugo, were associated with PC1, corresponding to winter precipitation and seasonal minimum temperature. In A. alba, four SNPs were associated with PC2, corresponding to the seasonal minimum temperature. Functional annotation of those genes with the orthologs in Arabidopsis
revealed several genes involved in abiotic stress response. This study provides a
detailed assessment of population structure and its association with environment and
geography in four coniferous species in the Italian mountains
Expression of the new CXCL12 receptor, CXCR7, in gliomas
No full textGliomas are very invasive brain tumors with poor prognosis and therefore any attempt to limit tumor cell dissemination in the brain is expected to improve glioma treatment. The recent deorphanization of CXCR7 as additional receptor for CXCL12 and CXCL11 has raised key issues on its interaction with the CXCL12/CXCR4 axis as a mechanism to modulate glioma cell migration. In this work we investigated protein and mRNA expression of the two chemokines CXCL12 and CXCL11, together with their receptors CXCR4 and CXCR7 in human glioma specimens and cell lines by immunohistochemistry, flow cytometry and quantitative real-time PCR. The main purpose of this study was to find out whether and at what extent CXCR4 and CXCR7 are differentially expressed in glioma cells. In human glioma specimens the levels of CXCL11 and CXCR4 mRNA were significantly higher in glioblastomas compared to non-tumor controls or low grade gliomas, whilst no difference was found for CXCL12 and CXCR7 mRNA expression. In cell lines, flow cytometry and immunocytochemical experiments showed CXCR4 was mainly expressed irrespective of its membrane or intracellular localization. In contrast, a predominant intracellular localization together with a negligible membrane expression of CXCR7 was found in all cells examined. In in vitro experiments CXCR4 and CXCR7 antagonists and the silencing of CXCR4 showed complete inhibition of glioma proliferation. Our findings, in agreement with previous data, suggest that in human glioma cells the prevalent intracellular localization of CXCR7 might modulate the functionality of CXCL11/12 either acting as a scavenger for these chemokines or interfering with the signaling pathways activated by the stimulation of CXCR4
Micro- and macro-geographic scale effect on the molecular imprint of selection and adaptation in Norway spruce.
Get PDFForest tree species of temperate and boreal regions have undergone a long history of demographic changes and evolutionary adaptations. The main objective of this study was to detect signals of selection in Norway spruce (Picea abies [L.] Karst), at different sampling-scales and to investigate, accounting for population structure, the effect of environment on species genetic diversity. A total of 384 single nucleotide polymorphisms (SNPs) representing 290 genes were genotyped at two geographic scales: across 12 populations distributed along two altitudinal-transects in the Alps (micro-geographic scale), and across 27 populations belonging to the range of Norway spruce in central and south-east Europe (macro-geographic scale). At the macrogeographic scale, principal component analysis combined with Bayesian clustering revealed three major clusters, corresponding to the main areas of southern spruce occurrence, i.e. the Alps, Carpathians, and Hercynia. The populations along the altitudinal transects were not differentiated. To assess the role of selection in structuring genetic variation, we applied a Bayesian and coalescent-based F(ST)-outlier method and tested for correlations between allele frequencies and climatic variables using regression analyses. At the macro-geographic scale, the F(ST)-outlier methods detected together 11 F(ST)-outliers. Six outliers were detected when the same analyses were carried out taking into account the genetic structure. Regression analyses with population structure correction resulted in the identification of two (micro-geographic scale) and 38 SNPs (macro-geographic scale) significantly correlated with temperature and/or precipitation. Six of these loci overlapped with F(ST)-outliers, among them two loci encoding an enzyme involved in riboflavin biosynthesis and a sucrose synthase. The results of this study indicate a strong relationship between genetic and environmental variation at both geographic scales. It also suggests that an integrative approach combining different outlier detection methods and population sampling at different geographic scales is useful to identify loci potentially involved in adaptation
