High-resolution genetic map and QTL analysis of growth-related traits of Hevea brasiliensis cultivated under suboptimal temperature and humidity conditions

Rubber tree (Hevea brasiliensis) cultivation is the main source of natural rubber worldwide and has been extended to areas with suboptimal climates and lengthy drought periods; this transition affects growth and latex production. High-density genetic maps with reliable markers support precise mapping of quantitative trait loci (QTL), which can help reveal the complex genome of the species, provide tools to enhance molecular breeding, and shorten the breeding cycle. In this study, QTL mapping of the stem diameter, tree height, and number of whorls was performed for a full-sibling population derived from a GT1 and RRIM701 cross. A total of 225 simple sequence repeats (SSRs) and 186 single-nucleotide polymorphism (SNP) markers were used to construct a base map with 18 linkage groups and to anchor 671 SNPs from genotyping by sequencing (GBS) to produce a very dense linkage map with small intervals between loci. The final map was composed of 1,079 markers, spanned 3,779.7 cM with an average marker density of 3.5 cM, and showed collinearity between markers from previous studies. Significant variation in phenotypic characteristics was found over a 59-month evaluation period with a total of 38 QTLs being identified through a composite interval mapping method. Linkage group 4 showed the greatest number of QTLs (7), with phenotypic explained values varying from 7.67 to 14.07%. Additionally, we estimated segregation patterns, dominance, and additive effects for each QTL. A total of 53 significant effects for stem diameter were observed, and these effects were mostly related to additivity in the GT1 clone. Associating accurate genome assemblies and genetic maps represents a promising strategy for identifying the genetic basis of phenotypic traits in rubber trees. Then, further research can benefit from the QTLs identified herein, providing a better understanding of the key determinant genes associated with growth of Hevea brasiliensis under limiting water conditions

Linkage disequilibrium and population structure in wild and cultivated populations of rubber tree (Hevea brasiliensis).

Abstract: Among rubber tree species, which belong to the Hevea genus of the Euphorbiaceae family, Hevea brasiliensis (Willd. ex Adr.de Juss.) Muell. Arg. is the main commercial source of natural rubber production worldwide. Knowledge of the population structure and linkage disequilibrium (LD) of this species is essential for the efficient organization and exploitation of genetic resources. Here, we obtained single-nucleotide polymorphisms (SNPs) using a genotyping-by-sequencing (GBS) approach and then employed the SNPs for the following objectives: (i) to identify the positions of SNPs on a genetic map of a segregating mapping population, (ii) to evaluate the population structure of a germplasm collection, and (iii) to detect patterns of LD decay among chromosomes for future genetic association studies in rubber tree. A total of 626 genotypes, including both germplasm accessions (368) and individuals from a genetic mapping population (254), were genotyped. A total of 77,660 and 21,283 SNPs were detected by GBS in the germplasm and mapping populations, respectively. The mapping population, which was previously mapped, was constructed with 1,062 markers, among which only 576 SNPs came from GBS, reducing the average interval between two adjacent markers to 4.4 cM. SNPs from GBS genotyping were used for the analysis of genetic structure and LD estimation in the germplasm accessions. Two groups, which largely corresponded to the cultivated and wild populations, were detected using STRUCTURE and via principal coordinate analysis. LD analysis, also using the mapped SNPs, revealed that non-random associations varied along chromosomes, with regions of high LD interspersed with regions of low LD. Considering the length of the genetic map (4,693 cM) and the mean LD (0.49 for cultivated and 0.02 for wild populations), a large number of evenly spaced SNPs would be needed to perform genome-wide association studies in rubber tree, and the wilder the genotypes used, the more difficult the mapping saturation

Emotional, hyperactivity and inattention problems in adolescents with immunocompromising chronic diseases during the COVID-19 pandemic

Objective: To assess factors associated with emotional changes and Hyperactivity/Inattention (HI) motivated by COVID-19 quarantine in adolescents with immunocompromising diseases. Methods: A cross-sectional study included 343 adolescents with immunocompromising diseases and 108 healthy adolescents. Online questionnaires were answered including socio-demographic data and self-rated healthcare routine during COVID-19 quarantine and validated surveys: Strengths and Difficulties Questionnaire (SDQ), Pittsburgh Sleep Quality Index (PSQI), Pediatric Quality of Life Inventory 4.0 (PedsQL4.0). Results: The frequencies of abnormal emotional SDQ scores from adolescents with chronic diseases were similar to those of healthy subjects (110/343 [32%] vs. 38/108 [35%], p = 0.548), as well as abnormal hyperactivity/inattention SDQ scores (79/343 [23%] vs. 29/108 [27%], p = 0.417). Logistic regression analysis of independent variables associated with abnormal emotional scores from adolescents with chronic diseases showed: female sex (Odds Ratio [OR = 3.76]; 95% Confidence Interval (95% CI) 2.00‒7.05; p < 0.001), poor sleep quality (OR = 2.05; 95% CI 1.08‒3.88; p = 0.028) and intrafamilial violence during pandemic (OR = 2.17; 95% CI 1.12‒4.19; p = 0.021) as independently associated with abnormal emotional scores, whereas total PedsQL score was inversely associated with abnormal emotional scores (OR = 0.95; 95% CI 0.93‒0.96; p < 0.0001). Logistic regression analysis associated with abnormal HI scores from patients evidenced that total PedsQL score (OR = 0.97; 95% CI 0.95‒0.99; p = 0.010], changes in medical appointments during the pandemic (OR = 0.39; 95% CI 0.19-0.79; p = 0.021), and reliable COVID-19 information (OR = 0.35; 95% CI 0.16‒0.77; p = 0.026) remained inversely associated with abnormal HI scores. Conclusion: The present study showed emotional and HI disturbances in adolescents with chronic immunosuppressive diseases during the COVID-19 pandemic. It reinforces the need to promptly implement a longitudinal program to protect the mental health of adolescents with and without chronic illnesses during future pandemics

The discovery space of ELT-ANDES. Stars and stellar populations

The ArmazoNes high Dispersion Echelle Spectrograph (ANDES) is the optical and near-infrared high-resolution echelle spectrograph envisioned for the European Extremely Large Telescope (ELT). We present a selection of science cases, supported by new calculations and simulations, where ANDES could enable major advances in the fields of stars and stellar populations. We focus on three key areas, including the physics of stellar atmospheres, structure, and evolution; stars of the Milky Way, Local Group, and beyond; and the star-planet connection. The key features of ANDES are its wide wavelength coverage at high spectral resolution and its access to the large collecting area of the ELT. These features position ANDES to address the most compelling and potentially transformative science questions in stellar astrophysics of the decades ahead, including questions which cannot be anticipated today.Comment: 46 pages, 8 figures; submitted to Experimental Astronomy on behalf of the ANDES Science Tea

Contribution of the carbohydrate-binding ability of Vatairea guianensis lectin to induce edematogenic activity

Vatairea guianensis lectin (VGL), Dalbergiae tribe, is a N-acetyl-galactosamine (GalNAc)/Galactose (Gal) lectin previously purified and characterized. In this work, we report its structural features, obtained from bioinformatics tools, and its inflammatory effect, obtained from a rat paw edema model. The VGL model was obtained by homology with the lectin of Vatairea macrocarpa (VML) as template, and we used it to demonstrate the common characteristics of legume lectins, such as the jellyroll motif and presence of a metal-binding site in the vicinity of the carbohydrate-recognition domain (CRD). Protein-ligand docking revealed favorable interactions with N-acetyl-D-galactosamine, D-galactose and related sugars as well as several biologically relevant N- and O-glycans. In vivo testing of paw edema revealed that VGL induces edematogenic effect involving prostaglandins, interleukins and VGL CRD. Taken together, these data corroborate with previous reports showing that VGL interacts with N- and/or O-glycans of molecular targets, particularly in those presenting galactosides in their structure, contributing to the lectin inflammatory effect. © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM

Nootropic effects of LSD: Behavioral, molecular and computational evidence

The therapeutic use of classical psychedelic substances such as d-lysergic acid diethylamide (LSD) surged in recent years. Studies in rodents suggest that these effects are produced by increased neural plasticity, including stimulation of the mTOR pathway, a key regulator of metabolism, plasticity, and aging. Could psychedelic-induced neural plasticity be harnessed to enhance cognition? Here we show that LSD treatment enhanced performance in a novel object recognition task in rats, and in a visuo-spatial memory task in humans. A proteomic analysis of human brain organoids showed that LSD affected metabolic pathways associated with neural plasticity, including mTOR. To gain insight into the relation of neural plasticity, aging and LSD-induced cognitive gains, we emulated the experiments in rats and humans with a neural network model of a cortico-hippocampal circuit. Using the baseline strength of plasticity as a proxy for age and assuming an increase in plasticity strength related to LSD dose, the simulations provided a good fit for the experimental data. Altogether, the results suggest that LSD has nootropic effects.This project was supported by the Beckley Foundation; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Finance Code 001, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grants 308775/2015-5 and 408145/2016-1), São Paulo Research Foundation grants (2013/07699-0, 2014/10068-4, 2017/25588-1 and 2019/00098-7), intramural grants from D'Or Institute and Federal University of Rio Grande do Norte, and a Juan de la Cierva-Incorporación Scholarship (IJCI-2016-27864) from the Spanish Ministry of Science, Innovation and Universities, and a Newton International Fellowship from the Royal Society.Peer reviewe

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio