Sampling strategy optimization to increase statistical power in landscape genomics: A simulation‐based approach

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. Implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistical constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic data sets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographical representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios. Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.     

Interactive effects of elevated temperature and CO2 levels on metabolism and oxidative stress in two common marine bivalves (Crassostrea virginica and Mercenaria mercenaria)

Marine bivalves such as the hard shell clams Mercenaria mercenaria and eastern oysters Crassostrea virginica are affected by multiple stressors, including fluctuations in temperature and CO₂ levels in estuaries, and these stresses are expected to be exacerbated by ongoing global climate change. Hypercapnia (elevated CO₂ levels) and temperature stress can affect survival, growth and development of marine bivalves, but the cellular mechanisms of these effects are not yet fully understood. In this study, we investigated whether oxidative stress is implicated in cellular responses to elevated temperature and CO₂ levels in marine bivalves. We measured the whole-organism standard metabolic rate (SMR), total antioxidant capacity (TAOC), and levels of oxidative stress biomarkers in the muscle tissues of clams and oysters exposed to different temperatures (22 and 27 °C) and CO₂ levels (the present day conditions of ~ 400 ppm CO₂ and 800 ppm CO₂ predicted by a consensus business-as-usual IPCC emission scenario for the year 2100). SMR was significantly higher and the antioxidant capacity was lower in oysters than in clams. Aerobic metabolism was largely temperature-independent in these two species in the studied temperature range (22–27 °C). However, the combined exposure to elevated temperature and hypercapnia led to elevated SMR in clams indicating elevated costs of basal maintenance. No persistent oxidative stress signal (measured by the levels of protein carbonyls, and protein conjugates with malondialdehyde and 4-hydroxynonenal) was observed during the long-term exposure to moderate warming (+ 5 °C) and hypercapnia (~ 800 ppm CO₂). This indicates that long-term exposure to moderately elevated CO₂ and temperature minimally affects the cellular redox status in these bivalve species and that the earlier observed negative physiological effects of elevated CO₂ and temperature must be explained by other cellular mechanisms.     

Influence of environmental factors on content and composition of essential oil from common juniper ripe berry cones (Juniperus communis L.)

Abstract

The present study evaluated the influence of some environmental factors on the quantity and composition of essential oil (EO) in ripe berry cones of Juniperus communis L. The berry cones were collected from juniper shrubs growing wild at five localities of north-east Slovakia during the years 2012–2014. The EO yield ranged from 0.4 to 1.9%, depending on the locality and year. In the EO, eight monoterpenes (α-pinene, β-pinene, β-myrcene, sabinene, limonene, terpinene-4-ol, borneol, bornylacetate) and one sesquiterpene (β-caryophyllene) were identified. The dominant component was the monoterpene α-pinene, ranging from 31.0 to 49.0%. The amount and composition of the EO was affected by soil composition (content of humus and pH) and topographic environmental factors, including air temperature and precipitation. According to the composition of the EO, the studied juniper shrubs belong to the α-pinene chemotype.     

rDNA analysis of the Red Sea seagrass,Halophila, reveals vicariant evolutionary diversification

The effects of opening the Suez Canal as a connection between the Red Sea and the Mediterranean Sea were reported for a number of marine species. However, the evolutionary origin of the seagrasses in the Red Sea and the linking population genetics of seagrasses between the Arabian Sea, the Gulf of Aden, the Red Sea and the Mediterranean Sea have not yet been investigated in detail. The invasion of Halophila stipulacea Asch. from the Red Sea into the Mediterranean Sea after the opening of the Suez Canal was already recorded. We hypothesize that Halophila ovalis populations in the Red Sea developed through long-term historical processes such as vicariant evolutionary diversification. Seagrass samples were collected along the Egyptian coastline of the Red Sea and analysed by the molecular marker ITS. The sequences were compared with published ITS sequences from seagrasses collected in the whole area of interest. In this study, we reveal the linking population genetics, phylogeography and phylogenetics of two dominant seagrass species, Halophila stipulacea and Halophila ovalis, among species collected in the Red Sea and worldwide. The results indicate that the Red Sea Halophila ovalis populations do not group to Halophila ovalis worldwide, and Halophila major, Halophila ovalis collected worldwide and Halophila ovalis collected at the Red Sea are sister clades. Hence, vicariant evolutionary diversification for Halophila ovalis may occur in the Red Sea.     

Preclinical Demonstration of Synergistic Active Nutrients/Drug (AND) Combination as a Potential Treatment for Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a poor prognosis disease lacking adequate therapy. We have previously shown that ascorbic acid administration is toxic to MPM cells. Here we evaluated a new combined therapy consisting of ascorbate/epigallocatechin-3-gallate/gemcitabine mixture (called AND, for Active Nutrients/Drug). In vitro effects of AND therapy on various MPM cell lines revealed a synergistic cytotoxic mechanism. In vivo experiments on a xenograft mouse model for MPM, obtained by REN cells injection in immunocompromised mice, showed that AND strongly reduced the size of primary tumor as well as the number and size of metastases, and prevented abdominal hemorrhage. Kaplan Meier curves and the log-rank test indicated a marked increase in the survival of AND-treated animals. Histochemical analysis of dissected tumors showed that AND induced a shift from cell proliferation to apoptosis in cancer cells. Lysates of tumors from AND-treated mice, analyzed with an antibody array, revealed decreased TIMP-1 and -2 expressions and no effects on angiogenesis regulating factors. Multiplex analysis for signaling protein phosphorylation exhibited inactivation of cell proliferation pathways. The complex of data showed that the AND treatment is synergistic in vitro on MPM cells, and blocks in vivo tumor progression and metastasization in REN-based xenografts. Hence, the AND combination is proposed as a new treatment for MPM.     

Multiparametric magnetic resonance imaging-guided salvage radiotherapy in prostate cancer

AimTo analyse the efficacy and toxicity of postprostatectomy SRT in patients with a BCR evaluated with mpMRI.BackgroundMultiparametric magnetic resonance imaging (mpMRI) has the ability to detect the site of pelvic recurrence in patients with biochemical recurrence (BCR) after radical prostatectomy (RP). However, we do not know the oncological outcomes of mpMRI-guided savage radiotherapy (SRT).ResultsLocal, lymph node, and pelvic bone recurrence was observed in 13, 4 and 2 patients, respectively. PSA levels were significantly lower in patients with negative mpMRI (0.4 ng/mL [0.4]) vs. positive mpMRI (2.2 ng/mL [4.1], p = 0.003). Median planning target volume doses in patients with visible vs. non-visible recurrences were 76 Gy vs. 70 Gy. Overall, mean follow-up was 41 months (6–81). Biochemical relapse-free survival (bRFS) at 3 years was 82.3% and 82.5%, respectively, for the negative and positive mpMRI groups (p = 0.800). Three-year rates of late grade ≥2 urinary and rectal toxicity were 14.8% and 1.9%, respectively; all but one patient recovered without sequelae.ConclusionSRT to the macroscopic recurrence identified by mpMRI is a feasible and well-tolerated option. In this study, there were no differences in bRFS between MRI-positive and MRI-negative patients, indicating effective targeting of MRI-positive lesions.     

Rapid identification and interpretation of gene–environment associations using the new R.SamBada landscape genomics pipeline

sam βada is a genome–environment association software, designed to search for signatures of local adaptation. However, pre‐ and postprocessing of data can be labour‐intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r ‐package providing a pipeline for landscape genomic analysis based on sam βada , spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).