Tolerance mechanisms to aluminum in popcorn inbred lines involving aluminum compartmentalization and ascorbate-glutathione redox pathway.

MAIN CONCLUSION: Inbred line 11-133 of popcorn showed the lowest apoplast Al and total Al concentrations and Al-lumogallion complex, associated with a more efficient antioxidant system, mainly due to glutathione metabolism. Popcorn (Zea mays L. var. everta) is largely intended for human consumption. About 40% of the world's arable soils are acidic. In soils acidic, aluminum (Al) ionizes producing the trivalent cation, which is highly toxic to plants. Hence, this work aimed to: (1) evaluate the Al toxicity sites and its effect on the structure of the root tips, (2) quantify Al concentrations in the apoplast and symplast of the roots, and (3) to elucidate the modulation on the activity of antioxidant enzymes and metabolites of the ascorbate-glutathione cycle in two popcorn inbred lines (ILs) 11-133 and 11-60, classified as tolerant and sensitive to this metal, respectively. Aluminum toxicity did not affect the shoot growth; however, there was a yellowing of the oldest leaf blade only in 11-60. The better performance of 11-133 is related to lower apoplastic and total Al concentrations and Al accumulation in the root associated with a lower fluorescence of Al-lumogallion complex at the root tip, indicating the presence of mechanisms of chelation with this metal. Consequently, this IL showed less change in root morphoanatomy and lower reactive oxygen species and malondialdehyde content, which are associated with a more efficient enzymatic and non-enzymatic system, mainly due to the higher content of the glutathione metabolite and the higher activities of superoxide dismutase, monodehydroascorbate reductase, dehydroascorbate reductase, γ-glutamylcysteine synthetase, and glutathione peroxidase enzymes. Thus, these findings illustrated above indicate how internal mechanisms of detoxification respond to Al in popcorn, which can be used as tolerance biomarkers.

Efficiency of mapping epistatic quantitative trait loci.

Most theoretical studies on epistatic QTL mapping have shown that this procedure is powerful, efficient to control the false positive rate (FPR), and precise to localize QTLs. The objective of this simulation-based study was to show that mapping epistatic QTLs is not an almost-perfect process. We simulated 50 samples of 400 F2 plants/recombinant inbred lines, genotyped for 975 SNPs distributed in 10 chromosomes of 100 cM. The plants were phenotyped for grain yield, assuming 10 epistatic QTLs and 90 minor genes. Adopting basic procedures of r/qtl package, we maximized the power of detection for QTLs (56-74%, on average) but associated with a very high FPR (65%) and a low detection power for the epistatic pairs (7%). Increasing the average detection power for epistatic pairs (14%) highly increased the related FPR. Adopting a procedure to find the best balance between power and FPR, there was a significant decrease in the power of QTL detection (17-31%, on average), associated with a low average detection power for epistatic pairs (8%) and an average FPR of 31% for QTLs and 16% for epistatic pairs. The main reasons for these negative results are a simplified specification of the coefficients of epistatic effects, as theoretically proved, and the effects of minor genes since 2/3 of the FPR for QTLs were due to them. We hope that this study, including the partial derivation of the coefficients of epistatic effects, motivates investigations on how to increase the power of detection for epistatic pairs, effectively controlling the FPR.

Significance of linkage disequilibrium and epistasis on genetic variances in noninbred and inbred populations.

BACKGROUND: The influence of linkage disequilibrium (LD), epistasis, and inbreeding on genotypic variance continues to be an important area of investigation in genetics and evolution. Although the current knowledge about biological pathways and gene networks indicates that epistasis is important in determining quantitative traits, the empirical evidence for a range of species and traits is that the genotypic variance is most additive. This has been confirmed by some recent theoretical studies. However, because these investigations assumed linkage equilibrium, considered only additive effects, or used simplified assumptions for two- and higher-order epistatic effects, the objective of this investigation was to provide additional information about the impact of LD and epistasis on genetic variances in noninbred and inbred populations, using a simulated dataset. RESULTS: In general, the most important component of the genotypic variance was additive variance. Because of positive LD values, after 10 generations of random crosses there was generally a decrease in all genetic variances and covariances, especially the nonepistatic variances. Thus, the epistatic variance/genotypic variance ratio is inversely proportional to the LD level. Increasing inbreeding increased the magnitude of the additive, additive x additive, additive x dominance, and dominance x additive variances, and decreased the dominance and dominance x dominance variances. Except for duplicate epistasis with 100% interacting genes, the epistatic variance/genotypic variance ratio was proportional to the inbreeding level. In general, the additive x additive variance was the most important component of the epistatic variance. Concerning the genetic covariances, in general, they showed lower magnitudes relative to the genetic variances and positive and negative signs. The epistatic variance/genotypic variance ratio was maximized under duplicate and dominant epistasis and minimized assuming recessive and complementary epistasis. Increasing the percentage of epistatic genes from 30 to 100% increased the epistatic variance/genotypic variance ratio by a rate of 1.3 to 12.6, especially in inbred populations. The epistatic variance/genotypic variance ratio was maximized in the noninbred and inbred populations with intermediate LD and an average allelic frequency of the dominant genes of 0.3 and in the noninbred and inbred populations with low LD and an average allelic frequency of 0.5. CONCLUSIONS: Additive variance is in general the most important component of genotypic variance. LD and inbreeding have a significant effect on the magnitude of the genetic variances and covariances. In general, the additive x additive variance is the most important component of epistatic variance. The maximization of the epistatic variance/genotypic variance ratio depends on the LD level, degree of inbreeding, epistasis type, percentage of interacting genes, and average allelic frequency.

Chronic Methylmercury Intoxication Induces Systemic Inflammation, Behavioral, and Hippocampal Amino Acid Changes in C57BL6J Adult Mice.

Methylmercury (MeHg) is highly toxic to the human brain. Although much is known about MeHg neurotoxic effects, less is known about how chronic MeHg affects hippocampal amino acids and other neurochemical markers in adult mice. In this study, we evaluated the MeHg effects on systemic lipids and inflammation, hippocampal oxidative stress, amino acid levels, neuroinflammation, and behavior in adult male mice. Challenged mice received MeHg in drinking water (2 mg/L) for 30 days. We assessed weight gain, total plasma cholesterol (TC), triglycerides (TG), endotoxin, and TNF levels. Hippocampal myeloperoxidase (MPO), malondialdehyde (MDA), acetylcholinesterase (AChE), amino acid levels, and cytokine transcripts were evaluated. Mice underwent open field, object recognition, Y, and Barnes maze tests. MeHg-intoxicated mice had higher weight gain and increased the TG and TC plasma levels. Elevated circulating TNF and LPS confirmed systemic inflammation. Higher levels of MPO and MDA and a reduction in IL-4 transcripts were found in the hippocampus. MeHg-intoxication led to increased GABA and glycine, reduced hippocampal taurine levels, delayed acquisition in the Barnes maze, and poor locomotor activity. No significant changes were found in AChE activity and object recognition. Altogether, our findings highlight chronic MeHg-induced effects that may have long-term mental health consequences in prolonged exposed human populations.

Deciphering the major metabolic pathways associated with aluminum tolerance in popcorn roots using label-free quantitative proteomics.

MAIN CONCLUSION: Al responsive proteins are associated with starch, sucrose, and other carbohydrate metabolic pathways. Sucrose synthase is a candidate to Al tolerance. Al responses are regulated at transcriptional and post-transcriptional levels. Aluminum toxicity is one of the important abiotic stresses that affects worldwide crop production. The soluble form of aluminum (Al3+) inhibits root growth by altering water and nutrient uptake, a process that also reduces plant growth and development. Under long-term Al3+ exposure, plants can activate several tolerance mechanisms. To date, no reports of large-scale proteomic data concerning maize responses to this ion have been published. To investigate the post-transcriptional regulation in response to Al toxicity, we performed label-free quantitative proteomics for comparative analysis of two Al-contrasting popcorn inbred lines and an Al-tolerant commercial hybrid during 72 h under Al-stress conditions. A total of 489 differentially accumulated proteins (DAPs) were identified in the Al-sensitive inbred line, 491 in the Al-tolerant inbred line, and 277 in the commercial hybrid. Among them, 120 DAPs were co-expressed in both Al tolerant genotypes. Bioinformatics analysis indicated that starch, sucrose, and other components of carbohydrate metabolism and glycolysis/gluconeogenesis are the biochemical processes regulated in response to Al toxicity. Sucrose synthase accumulation and an increase in sucrose content and starch degradation suggest that these components may enhance popcorn tolerance to Al stress. The accumulation of citrate synthase suggests a key role for this enzyme in the detoxification process in the Al-tolerant inbred line. The integration of transcriptomic and proteomic data indicates that the Al tolerance response presents a complex regulatory network into the transcription and translation dynamics of popcorn root development.

Genomic evaluation for novel stayability traits in Nellore cattle.

Cow stayability plays a major role on the overall profitability of the beef cattle industry, as it is directly related to reproductive efficiency and cow's longevity. Stayability (STAY63) is usually defined as the ability of the cow to calve at least three times until 76 months of age. This is a late-measured and lowly heritable trait, which consequently constrains genetic progress per time unit. Thus, the use of genomic information associated with novel stayability traits measured earlier in life will likely result in higher prediction accuracy and faster genetic progress for cow longevity. In this study, we aimed to compare pedigree-based and single-step GBLUP (ssGBLUP) methods as well as to estimate genetic correlations between the proposed stayability traits: STAY42, STAY53 and STAY64, which are measured at 52, 64 and 76 months of cow's age, considering at least 2, 3 and 4 calving, respectively. ssGBLUP yielded the highest prediction accuracy for all traits. The heritability estimates for STAY42, STAY53, STAY63 and STAY64 were 0.090, 0.151, 0.152 and 0.143, respectively. The genetic correlations between traits ranged from 0.899 (STAY42 and STAY53) to 0.985 (STAY53 and STAY63). The high genetic correlation between STAY42 and STAY53 suggests that besides being related to cow longevity, STAY53 is also associated with the early-stage reproductive efficiency. Thus, STAY53 is recommended as a suitable selection criterion for reproductive efficiency due to its higher heritability, favourable genetic correlation with other traits, and measured earlier in life, compared with the conventional stayability trait, that is STAY63.

Efficiency of genomic prediction of non-assessed single crosses.

An important application of genomic selection in plant breeding is predicting untested single crosses (SCs). Most investigations on the prediction efficiency were based on tested SCs using cross-validation. The main objective was to assess the prediction efficiency by correlating the predicted and true genotypic values of untested SCs (accuracy) and measuring the efficacy of identification of the best 300 untested SCs (coincidence) using simulated data. We assumed 10,000 SNPs, 400 QTLs, two groups of 70 selected DH lines, and 4900 SCs. The heritabilities for the assessed SCs were 30, 60, and 100%. The scenarios included three sampling processes of DH lines, two sampling processes of SCs for testing, two SNP densities, DH lines from distinct and the same populations, DH lines from populations with lower LD, two genetic models, three statistical models, and three statistical approaches. We derived a model for genomic prediction based on SNP average effects of substitution and dominance deviations. The prediction accuracy is not affected by the linkage phase. The prediction of untested SCs is very efficient. The accuracies and coincidences ranged from ~0.8 and 0.5 at low heritability to 0.9 and 0.7 at high heritability, respectively. We also highlight the relevance of the overall LD and demonstrate that efficient prediction of untested SCs can be achieved for crops that show no heterotic pattern, for reduced training set size (10%), for SNP density of 1 cM, and for distinct sampling processes of DH lines based on random choice of the SCs for testing.

Biophysical Effects of a Polymeric Biosurfactant in Candida krusei and Candida albicans Cells.

This study evaluated the effects of a polymeric biosurfactant produced by Trichosporon montevideense CLOA72 in the adhesion of Candida albicans and Candida krusei cells to human buccal epithelial cells and its interference in biofilm formation by these strains. The biofilm inhibition by biosurfactant (25 mg/mL) in C. krusei and C. albicans in polystyrene was reduced up to 79.5 and 85 %, respectively. In addition, the zeta potential and hydrodynamic diameter of the yeasts altered as a function of the biosurfactant concentration added to the cell suspension. The changes in the cell surface characteristics and the interface modification can contribute to the inhibition of the initial adherence of yeasts cells to the surface. In addition, the analyses of the biofilm matrix and planktonic cell surfaces demonstrated differences in carbohydrate and protein concentrations for the two studied strains, which may contribute to the modulation of cell adhesion or consolidation of biofilms, especially in C. krusei. This study suggests a possible application of the of CLOA72 biosurfactant in inhibiting the adhesion and formation of biofilms on biological surfaces by yeasts of the Candida genus.

Linkage disequilibrium, SNP frequency change due to selection, and association mapping in popcorn chromosome regions containing QTLs for quality traits.

The objectives of this study were to assess linkage disequilibrium (LD) and selection-induced changes in single nucleotide polymorphism (SNP) frequency, and to perform association mapping in popcorn chromosome regions containing quantitative trait loci (QTLs) for quality traits. Seven tropical and two temperate popcorn populations were genotyped for 96 SNPs chosen in chromosome regions containing QTLs for quality traits. The populations were phenotyped for expansion volume, 100-kernel weight, kernel sphericity, and kernel density. The LD statistics were the difference between the observed and expected haplotype frequencies (D), the proportion of D relative to the expected maximum value in the population, and the square of the correlation between the values of alleles at two loci. Association mapping was based on least squares and Bayesian approaches. In the tropical populations, D-values greater than 0.10 were observed for SNPs separated by 100-150 Mb, while most of the D-values in the temperate populations were less than 0.05. Selection for expansion volume indirectly led to increase in LD values, population differentiation, and significant changes in SNP frequency. Some associations were observed for expansion volume and the other quality traits. The candidate genes are involved with starch, storage protein, lipid, and cell wall polysaccharides synthesis.

Ridge, Lasso and Bayesian additive-dominance genomic models.

BACKGROUND: A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes). RESULTS: G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close. CONCLUSIONS: Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (-2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.

Assessing the spatiotemporal occurrence and ecological risk of antifouling biocides in a Brazilian estuary.

Diuron and Irgarol are common antifouling biocides used in paints to prevent the attachment and growth of fouling organisms on ship hulls and other submerged structures. Concerns about their toxicity to non-target aquatic organisms have led to various restrictions on their use in antifouling paints worldwide. Previous studies have shown the widespread presence of these substances in port areas along the Brazilian coast, with a concentration primarily in the southern part of the country. In this study, we conducted six sampling campaigns over the course of 1 year to assess the presence and associated risks of Diuron and Irgarol in water collected from areas under the influence of the Maranhão Port Complex in the Brazilian Northeast. Our results revealed the absence of Irgarol in the study area, irrespective of the sampling season and site. In contrast, the mean concentrations of Diuron varied between 2.0 ng L-1 and 34.1 ng L-1 and were detected at least once at each sampling site. We conducted a risk assessment of Diuron levels in this area using the risk quotient (RQ) method. Our findings indicated that Diuron levels at all sampling sites during at least one campaign yielded an RQ greater than 1, with a maximum of 22.7, classifying the risk as "high" based on the proposed risk classification. This study underscores the continued concern regarding the presence of antifouling biocides in significant ports and marinas in Brazilian ports, despite international bans.

Occurrence and Environmental Risk Assessment of Contaminants of Emerging Concern in Brazilian Surface Waters.

We investigated the occurrence and the environmental risk of eight contaminants of emerging concern (CECs; acetaminophen, naproxen, diclofenac, methylparaben, 17ß-estradiol, sulfathiazole, sulfadimethoxine, and sulfamethazine) in three Brazilian water bodies, namely, the Monjolinho River Basin (São Paulo State), the Mogi Guaçu River (São Paulo State), and the Itapecuru River (Maranhão State) in three sampling campaigns. The CECs were only quantified in surface water samples collected at the Monjolinho River Basin. Acetaminophen, naproxen, and methylparaben were detected in the range of <200 to 575.9 ng L-1, <200 to 224.7 ng L-1, and <200 to 303.6 ng L-1, respectively. The detection frequencies of the three measured compounds were between 33% and 67%. The highest concentrations of CECs were associated with intense urbanization and untreated sewage discharge. Furthermore, CEC concentrations were significantly correlated with total organic carbon, electrical conductivity, and dissolved oxygen levels, suggesting that domestic pollution from urban areas is an important source in the distribution of CECs in the Monjolinho River Basin. The environmental risk assessment indicated a high risk for acetaminophen (risk quotient [RQ] values between 2.1 and 5.8), a medium risk for naproxen (RQs between 0.6 and 0.7), and a low risk for methylparaben (RQs < 0.1) to the freshwater biota of the Monjolinho River Basin. Our findings show potential threats of CECs in Brazilian water bodies, especially in vulnerable areas, and reinforce the need for improvements in environmental regulations to include monitoring and control of these compounds in aquatic systems. Environ Toxicol Chem 2024;00:1-12. © 2024 SETAC.

Efficacy of population structure analysis with breeding populations and inbred lines.

The objective was to assess by simulation the efficacy of population structure analysis in plant breeding. Twelve populations and 300 inbred lines were simulated and genotyped using 100 microsatellite loci. The experimental material included populations with and without admixture, ancestry relationship and linkage disequilibrium, and with distinct levels of genetic differentiation and effective sizes. The analyses were performed using Structure software and employed all available models. For all the group number (K) tested, for both populations and inbred lines, the admixture model with correlated allelic frequencies provided the highest value for the logarithm of the marginal likelihood. Fitting appropriate model and using adequate sample size for individuals and markers, Structure was effective in identifying the correct population structure, migrants and individuals with genome from distinct populations. The linkage model did not result in an improvement in clustering relative to the admixture model with correlated allelic frequencies. The inclusion of prior information did not change the results; for some K values the analyses showed slight higher values of the marginal likelihood. The reduction in the number of individuals and markers negatively affected the results. There was a high variation in the most probable K value between the evaluated methods.

Bayesian inference of mixed models in quantitative genetics of crop species.

The objectives of this study were to implement a Bayesian framework for mixed models analysis in crop species breeding and to exploit alternatives for informative prior elicitation. Bayesian inference for genetic evaluation in annual crop breeding was illustrated with the first two half-sib selection cycles in a popcorn population. The Bayesian framework was based on the Just Another Gibbs Sampler software and the R2jags package. For the first cycle, a non-informative prior for the inverse of the variance components and an informative prior based on meta-analysis were used. For the second cycle, a non-informative prior and an informative prior defined as the posterior from the non-informative and informative analyses of the first cycle were used. Regarding the first cycle, the use of an informative prior from the meta-analysis provided clearly distinct results relative to the analysis with a non-informative prior only for the grain yield. Regarding the second cycle, the results for the expansion volume and grain yield showed differences among the three analyses. The differences between the non-informative and informative prior analyses were restricted to variance components and heritability. The correlations between the predicted breeding values from these analyses were almost perfect.

Relative efficiency of the genotypic value and combining ability effects on reciprocal recurrent selection.

Reciprocal recurrent selection (RRS) has been successfully applied to maize breeding for more than 60 years. Our objective was to assess the relative efficiency of the genotypic value and the effects of general and specific combining abilities (GCA and SCA) on selection. The GCA effect reflects the number of favorable genes in the parent. The SCA effect primarily reflects the differences in the gene frequencies between the parents. We simulated three traits, three classes of populations, and 10 cycles of half- and full-sib RRS. The RRS is a highly efficient process for intra- and interpopulation breeding, regardless of the trait or the level of divergence among the populations. The RRS increases the heterosis of the interpopulation cross when there is dominance, and it decreases the inbreeding depression in the populations and the genetic variability in the populations and in the hybrid. When there is not dominance and the populations are not divergent, the RRS also determines population differentiation. The half-sib RRS, which is equivalent to selection based on the GCA effect, is more efficient than the full-sib RRS based on the genotypic value, regardless of the trait or the level of improvement of the populations. The full-sib RRS based on the SCA effect is not efficient for intra- and interpopulation breeding.

Genomic growth curves of an outbred pig population.

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

The impact of epistasis in the heterosis and combining ability analyses.

The current theoretical knowledge concerning the influence of epistasis on heterosis is based on a simplified multiplicative model. The objective of this study was to assess how epistasis affects the heterosis and combining ability analyses, assuming additive model, hundreds of genes, linkage disequilibrium (LD), dominance, and seven types of digenic epistasis. We developed the quantitative genetics theory for supporting the simulation of the individual genotypic values in nine populations, the selfed populations, the 36 interpopulation crosses, 180 doubled haploids (DHs), and their 16,110 crosses, assuming 400 genes on 10 chromosomes of 200 cM. Epistasis only affects population heterosis if there is LD. Only additive × additive and dominance × dominance epistasis can affect the components of the heterosis and combining ability analyses of populations. Epistasis can have a negative impact on the heterosis and combining ability analysis of populations, leading to wrong inferences regarding the identification of superior and most divergent populations. However, this depends on the type of epistasis, percentage of epistatic genes, and magnitude of their effects. Except for duplicate genes with cumulative effects and non-epistatic genic interaction, there was a decrease in the average heterosis by increasing the percentage of epistatic genes and the magnitude of their effects. The same results are generally true for the combining ability analysis of DHs. The combining ability analyses of subsets of 20 DHs showed no significant average impact of epistasis on the identification of the most divergent ones, regardless of the number of epistatic genes and magnitude of their effects. However, a negative effect on the assessment of the superior DHs can occur assuming 100% of epistatic genes, but depending on the epistasis type and the epistatic effect magnitude.

A simulation-based assessment of the efficiency of QTL mapping under environment and genotype x environment interaction effects.

The objective of this simulation-based study was to assess how genes, environments, and genotype x environment (GxE) interaction affect the quantitative trait loci (QTL) mapping efficiency. The simulation software performed 50 samplings of 300 recombinant inbred lines (RILs) from a F2, which were assessed in six environments. The RILs were genotyped for 977 single nucleotide polymorphisms (SNP) and phenotyped for grain yield. The average SNP density was 2 cM. We defined six QTLs and 190 minor genes. The trait heritability ranged from 30 to 80%. We fitted the single QTL model and the multiple QTL model on multiple phenotypes. The environment and complex GxE interaction effects led to a low correlation between the QTL heritability and power. The single- and across-environment analyses allowed all QTLs be declared, with an average power of 28 to 100%. In the across-environment analysis, five QTLs showed average power in the range 46 to 82%. Both models provided a good control of the false positive rate (6%, on average) and a precise localization of the QTLs (bias of 2 cM, on average). The QTL power in each environment has a high positive correlation with the range between QTL genotypes for the sum of the additive, environment, and GxE interaction effects (0.76 to 0.96). The uncertainty about the magnitude and sign of the environment and GxE interaction effects makes QTL mapping in multi-environment trials unpredictable. Unfortunately, this uncertainty has no solution because the geneticist has no control over the magnitude and sign of the environment and GxE interaction effects. However, the single- and across-environment analyses are efficient even under a low correlation between QTL heritability and power.

Enhancement of upconversion photoluminescence in phosphor nanoparticle thin films using metallic nanoantennas fabricated by colloidal lithography.

Lanthanide-doped upconversion nanoparticles (UCNPs), as multifunctional light sources, are finding utility in diverse applications ranging from biotechnology to light harvesting. However, the main challenge in realizing their full potential lies in achieving bright and efficient photon upconversion (UC). In this study, we present a novel approach to fabricate an array of gold nanoantennas arranged in a hexagonal lattice using a simple and inexpensive colloidal lithography technique, and demonstrate a significant enhancement of UC photoluminescence (UCPL) by up to 35-fold through plasmon-enhanced photoexcitation and emission. To elucidate the underlying physical mechanisms responsible for the observed UCPL enhancement, we provide a comprehensive theoretical and experimental characterization, including a detailed photophysical description and numerical simulations of the spatial electric field distribution. Our results shed light on the fundamental principles governing the enhanced UCNPs and pave the way for their potential applications in photonic devices.

Establishment and Expansion Scenario of Drosophila suzukii (Diptera: Drosophilidae) in Central Brazil.

Drosophila suzukii Matsumura (Diptera: Drosophilidae), also known as spotted wing drosophila (SWD), is an important pest that damages various wild and cultivated soft fruits worldwide, especially in the Northern Hemisphere. In Brazil, it occurs mainly in the subtropical climates of the southern and southeastern regions. However, SWD has also been sporadically found in the central region of the country in the natural vegetation of the tropical Brazilian Savanna. In this study, we investigated the occurrence of SWD at the northern limit of its range in South America - the central region of Brazil - by monitoring an established drosophilid community in an orchard located in the Brazilian Federal District. We also investigated the current geographical distribution of this pest in Brazil and its potential geographical distribution using species distribution models under two different future shared socioeconomic pathways scenarios (2040 and 2060, optimist and pessimist). Twenty drosophilid species were detected among the 6,396 captured specimens, most of which are exotic in the Neotropical region. The fly community greatly fluctuated throughout the year, and the highest abundance of SWD (3.5% relative abundance and 1.38 flies/trap/day) was recorded in April during the rainy season. Potential distribution models indicate that suitable areas for SWD spread will decrease in the south and southeast but increase in the central region of Brazil. We recommend continuous SWD monitoring and improving bioclimatic forecast models for mitigating damage to local fruit production.