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Understanding the genotype-by-environment interaction (GEI) and considering it in the selection process is a sine qua non condition for the expansion of Brazilian eucalyptus silviculture. This study's objective is to select high-performance and stable eucalyptus clones based on a novel selection index that considers the Factor Analytic Selection Tools (FAST) and the clone's reliability. The investigation explores the nuances interplay of GEI and extends its insights by scrutinizing the relationship between latent factors and real environmental features. The analysis, conducted across seven trials in five Brazilian states involving 78 clones, employs FAST. The clonal selection was performed using an extended FAST index weighted by the clone's reliability. Further insights about GEI emerge from the integration of factor loadings with 25 environmental features through a principal component analysis. Ten clones, distinguished by high performance, stability, and reliability, have been selected across the target population of environments. The environmental features most closely associated with factor loadings, encompassing air temperature, radiation, and soil characteristics, emerge as pivotal drivers of GEI within this dataset. This study contributes insights to eucalyptus breeders, equipping them to enhance decision-making by harnessing a holistic understanding-from the genotypes under evaluation to the diverse environments anticipated in commercial plantations.

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Early or late pubertal onset can lead to disease in adulthood, including cancer, obesity, type 2 diabetes, metabolic disorders, bone fractures, and psychopathologies. Thus, knowing the age at which puberty is attained is crucial as it can serve as a risk factor for future diseases. Pubertal development is divided into five stages of sexual maturation in boys and girls according to the standardized Tanner scale. We performed genome-wide association studies (GWAS) on the "Growth and Obesity Chilean Cohort Study" cohort composed of admixed children with mainly European and Native American ancestry. Using joint models that integrate time-to-event data with longitudinal trajectories of body mass index (BMI), we identified genetic variants associated with phenotypic transitions between pairs of Tanner stages. We identified $42$ novel significant associations, most of them in boys. The GWAS on Tanner $3\rightarrow 4$ transition in boys captured an association peak around the growth-related genes LARS2 and LIMD1 genes, the former of which causes ovarian dysfunction when mutated. The associated variants are expression and splicing Quantitative Trait Loci regulating gene expression and alternative splicing in multiple tissues. Further, higher individual Native American genetic ancestry proportions predicted a significantly earlier puberty onset in boys but not in girls. Finally, the joint models identified a longitudinal BMI parameter significantly associated with several Tanner stages' transitions, confirming the association of BMI with pubertal timing.

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This paper presents a general framework for simulating plot data in multi-environment field trials with one or more traits. The framework is embedded within the R package FieldSimR, whose core function generates plot errors that capture global field trend, local plot variation, and extraneous variation at a user-defined ratio. FieldSimR's capacity to simulate realistic plot data makes it a flexible and powerful tool for a wide range of improvement processes in plant breeding, such as the optimisation of experimental designs and statistical analyses of multi-environment field trials. FieldSimR provides crucial functionality that is currently missing in other software for simulating plant breeding programmes and is available on CRAN. The paper includes an example simulation of field trials that evaluate 100 maize hybrids for two traits in three environments. To demonstrate FieldSimR's value as an optimisation tool, the simulated data set is then used to compare several popular spatial models for their ability to accurately predict the hybrids' genetic values and reliably estimate the variance parameters of interest. FieldSimR has broader applications to simulating data in other agricultural trials, such as glasshouse experiments.

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This research evaluated the agronomic performance through mixed models, and determined the genetic divergence between black oat genotypes. The experiment was carried out at Federal University of Santa Maria, Frederico Westphalen/RS. Fourteen black oat genotypes were evaluated, being 11 lines developed by Breeding Program of University, and three commercial cultivars (IAPAR 61, UPFA 21 - Moreninha and, IPR Cabocla). We evaluated quantitative traits associated to plant height, cycle, dry mass yield and seeds yield; and 19 qualitative traits, being these morphological descriptors. The results showed that lines UFSMFW 2-05 and UFSMFW 2-07 stand out with characteristics such as early cycle, higher dry mass and grain yield. Divergence analysis revealed the formation of three distinct groups, indicating the presence of variability. These results suggested the potential for the development of new cultivars of black oat, presenting early cycle and good grain yield.

O objetivo deste trabalho foi avaliar o desempenho agronômico por meio de modelos mistos e determinar a divergência genética entre genótipos de aveia preta. O experimento foi conduzido na Universidade Federal de Santa Maria, campus de Frederico Westphalen/RS. Catorze genótipos de aveia preta foram avaliados, sendo 11 linhagens desenvolvidas pelo Programa de Melhoramento da Universidade e três cultivares comercias (IAPAR 61, UPFA 21 - Moreninha e IPR Cabocla). Foram avaliadas características agronômicas quantitativas relacionadas ao porte, ciclo e produtividade de massa seca e de sementes; e 19 características qualitativas, sendo estes descritores morfológicos. Os resultados mostraram que as linhagens UFSMFW 2-05 e UFSMFW 2-07 se destacam com características como ciclo precoce, elevada produtividade de massa seca e de sementes. A análise de divergência revelou a formação de três grupos distintos, indicando presença de variabilidade. Os resultados demonstram o potencial de desenvolvimento de novas cultivares de aveia preta, apresentando precocidade e boa produtividade de sementes.

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In this work, we propose an extension of a semiparametric nonlinear mixed-effects model for longitudinal data that incorporates more flexibility with penalized splines (P-splines) as smooth terms. The novelty of the proposed approach consists of the formulation of the model within the stochastic approximation version of the EM algorithm for maximum likelihood, the so-called SAEM algorithm. The proposed approach takes advantage of the formulation of a P-spline as a mixed-effects model and the use of the computational advantages of the existing software for the SAEM algorithm for the estimation of the random effects and the variance components. Additionally, we developed a supervised classification method for these non-linear mixed models using an adaptive importance sampling scheme. To illustrate our proposal, we consider two studies on pregnant women where two biomarkers are used as indicators of changes during pregnancy. In both studies, information about the women's pregnancy outcomes is known. Our proposal provides a unified framework for the classification of longitudinal profiles that may have important implications for the early detection and monitoring of pregnancy-related changes and contribute to improved maternal and fetal health outcomes. We show that the proposed models improve the analysis of this type of data compared to previous studies. These improvements are reflected both in the fit of the models and in the classification of the groups.

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Climate changes have become undisputed, as have their consequences for global ecosystems and mankind. The coastal areas are among the most affected areas on the planet due to their geographical location. The effects suffered by coastal areas can render the residing populations homeless, as well as compromise the continuity of the history and culture of these environments. The Marine Extractive Reserve of the city of Soure (coastal area of eastern Amazonia) stands out for housing populations that have developed an intimate relationship with nature and have knowledge that can explain people's perception of climate changes. In this context, this study investigated how local residents perceive climate change and its consequences considering different temporal and spatial scales. To this end, questionnaires were developed and applied using a 5-point Likert scale. Our results indicate that perception is shaped by socioeconomic and demographic factors, and that they are perceived on different time scales and geographic space. These findings reflect the awareness-raising efforts of the management body of this Conservation Unit and the local knowledge, derived from the relationship of the residents with the natural environment, which, together, provided the population with assertive information that favor a better understanding of this phenomenon.

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The resilience of forests to drought events has become a major natural resource sustainability concern, especially in response to climate change. Yet, little is known about the legacy effects of repeated droughts, and tree species ability to respond across environmental gradients. In this study, we used a tree-ring database (121 sites) to evaluate the overall resilience of tree species to drought events in the last century. We investigated how climate and geography affected the response at the species level. We evaluated temporal trends of resilience using a predictive mixed linear modeling approach. We found that pointer years (e.g., tree growth reduction) occurred during 11.3% of the 20th century, with an average decrease in tree growth of 66% compared to the previous period. The occurrence of pointer years was associated with negative values of the Standardized Precipitation Index (SPI, 81.6%) and Palmer Drought Severity Index (PDSI, 77.3%). Tree species differed in their resilience capacity, however, species inhabiting xeric conditions were less resistant but with higher recovery rates (e.g., Abies concolor, Pinus lambertiana, and Pinus jeffreyi). On average, tree species needed 2.7 years to recover from drought events, with extreme cases requiring more than a decade to reach pre-drought tree growth rates. The main abiotic factor related to resilience was precipitation, confirming that some tree species are better adapted to resist the effects of droughts. We found a temporal variation for all tree resilience indices (scaled to 100), with a decreasing resistance (-0.56 by decade) and resilience (-0.22 by decade), but with a higher recovery (+1.72 by decade) and relative resilience rate (+0.33 by decade). Our results emphasize the importance of time series of forest resilience, particularly by distinguishing the species-level response in the context of legacy of droughts, which are likely to become more frequent and intense under a changing climate.

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Suboptimal adherence to antiretroviral therapy (ART) in people with HIV, even during sustained viral suppression, is associated with persistent inflammation, immune activation, and coagulopathy. Persistently low CD4-CD8 Ratio has been also associated with residual inflammation, is a good predictor of increased risk of death and more widely available than inflammatory biomarkers. We tested the hypothesis that the CD4-CD8 Ratio is associated with ART adherence during periods of complete viral suppression. We used the Medication Possession Ratio based in pharmacy registries as measure of adherence and time-varying, routine care CD4 and CD8 measurements as outcome. We used a linear mixed model for longitudinal data, including fixed effects for sex, age, education, date of ART initiation, AIDS-related conditions, and baseline CD4 to model the outcome. In 988 adults with a median follow-up of 4.13 years, higher ART adherence was independently associated with a modest increase in CD4-CD8. For each increasing percentage point in adherence, the CD4-CD8 Ratio increased 0.000857 (95% confidence interval [CI] -0.000494 to 0.002209, p = .213731) in the first year after achieving viral suppression; 0.001057 (95% CI 0.000262-0.001853, p = .009160) in years 1 to 3; 0.000323 (95% CI -0.000448 to 0.001095, p = .411441) in years 3 to 5; and 0.000850 (95% CI 0.000272-0.001429, p = .003946) 5-10 years after achieving viral suppression. The magnitude of the effect of adherence over CD4-CD8 Ratios varied over time and by baseline CD4 count, with increasing adherence having a larger effect early after ART initiation in people with higher baseline CD4 (>500 cells/µL) and in later years in people with lower baseline CD4 count (≥200 cells/µL). Our findings expand on previous evidence suggesting that the benefits of optimal adherence to modern ART regimens goes beyond maintaining viral suppression. These results highlight the importance of including objective measurements of adherence as part of routine care, even in patients with complete HIV suppression over long-term follow-up.

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ABSTRACT: This research studied the genetic control of the traits related to melon fruit quality. The F1, F2, BC1, BC2 generations from the OL x A-16 and OL x PV crossings were evaluated in two separate trials conducted in randomized blocks with three replications. The evaluated traits were: average fruit weight, shape index, pulp thickness, pulp firmness, soluble solids content and cracking rate. The analyses were accomplished through a classic study of generations involving mixed models. The parameters on heritability and number of loci controlling the traits were evaluated in a broad and narrow sense. The inheritance of the evaluated traits is complex, presenting one gene of greater effect and polygenes with additive and dominant effects.

RESUMO: Objetivou-se com este trabalho estudar o controle genético de caracteres relacionados à qualidade do fruto do melão. Foram avaliadas as gerações F1, F2, RC1, RC2 dos cruzamentos OL x A-16 e OL x PV em dois ensaios separados conduzidos em blocos casualizados com três repetições. Os caracteres avaliados foram: peso médio do fruto, índice de formato, espessura da polpa, firmeza da polpa, sólidos solúveis e porcentagem de rachadura. As análises foram feitas por meio de estudo clássico de gerações envolvendo modelos mistos. Foram estimados os parâmetros de herdabilidades nos sentidos amplo e restrito e número de loci que controlam o caráter. A herança dos caracteres estudados é complexa com a presença de gene de efeito maior e poligenes com efeitos aditivos e de dominância.

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In neuroscience research, longitudinal data are often analysed using analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA) for repeated measures (rmANOVA/rmMANOVA). However, these analyses have special requirements: The variances of the differences between all possible pairs of within-subject conditions (i.e., levels of the independent variable) must be equal. They are also limited to fixed repeated time intervals and are sensitive to missing data. In contrast, other models, such as the generalized estimating equations (GEE) and the generalized linear mixed models (GLMM), suggest another way to think about the data and the studied phenomenon. Instead of forcing the data into the ANOVAs assumptions, it is possible to design a flexible/personalized model according to the nature of the dependent variable. We discuss some advantages of GEE and GLMM as alternatives to rmANOVA and rmMANOVA in neuroscience research, including the possibility of using different distributions for the parameters of the dependent variable, a better approach for different time length points, and better adjustment to missing data. We illustrate these advantages by showing a comparison between rmANOVA and GEE in a real example and providing the data and a tutorial code to reproduce these analyses in R. We conclude that GEE and GLMM may provide more reliable results when compared to rmANOVA and rmMANOVA in neuroscience research, especially in small sample sizes with unbalanced longitudinal designs with or without missing data.

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Our objectives were to evaluate the variability among animals regarding to the degradation rate of the potentially degradable fraction of dry matter, crude protein, and neutral detergent fiber, as well as to establish the minimum number of animals and provide a standardized design of sampling times for in situ ruminal degradation assays of tropical feeds with cattle. Seven feeds were evaluated, four concentrates and three forages. The incubations were performed using five rumen-cannulated Nellore heifers (328 ± 9.8 kg of body weight). The complete sets of incubation sampling times encompassed 16 time points for forage samples (0-240 h) and 13 time points for concentrate samples (0-144 h). The profiles were adjusted using both fixed and mixed model approaches. When the variation among animals on the degradation rate was considered using the mixed model approach, the precision of the adjusted degradation profiles was increased. Moreover, the utilization of a low number of animals increases the probability to obtain biased estimates of degradation rate and increased random variances. A minimum of three animals is recommended for in situ trials with cattle. Minimum designs of sampling times regarding number and position of incubation times were proposed, discussed, and recommended to assess the dynamics of tropical feed degradation.

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BACKGROUND: Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engelm) trees from four open-pollinated progeny trials were genotyped with 25,099 SNPs, and phenotyped for 15 growth, wood quality, pest resistance, drought tolerance, and defense chemical (monoterpenes) traits. The main objectives of this study were to: (1) identify genetic markers associated with these traits and determine their genetic architecture, and to compare the marker detected by single- (ST) and multiple-trait (MT) GWA models; (2) evaluate and compare the accuracy and control of bias of the genomic predictions for these traits underlying different ST and MT parametric and non-parametric GP methods. GWA, ST and MT analyses were compared using a linear transformation of genomic breeding values from the respective genomic best linear unbiased prediction (GBLUP) model. GP, ST and MT parametric and non-parametric (Reproducing Kernel Hilbert Spaces, RKHS) models were compared in terms of prediction accuracy (PA) and control of bias. RESULTS: MT-GWA analyses identified more significant associations than ST. Some SNPs showed potential pleiotropic effects. Averaging across traits, PA from the studied ST-GP models did not differ significantly from each other, with generally a slight superiority of the RKHS method. MT-GP models showed significantly higher PA (and lower bias) than the ST models, being generally the PA (bias) of the RKHS approach significantly higher (lower) than the GBLUP. CONCLUSIONS: The power of GWA and the accuracy of GP were improved when MT models were used in this lodgepole pine population. Given the number of GP and GWA models fitted and the traits assessed across four progeny trials, this work has produced the most comprehensive empirical genomic study across any lodgepole pine population to date.

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The study aimed to analyze the agronomic performance of 11 safflower genotypes using adaptability and stability methods, while identifying safflower genotypes with stable behavior and a high grain yield in different environments of the Brazilian Cerrado. Ten lines and a cultivar of safflower were evaluated in four environments in the Brazilian conditions. Our results revealed the genotypes P30, P35, P9, P11, and P31 to be superior for grain yield and P43, P7, P11, and P31 to be superior for oil content. The lowest Wricke index, an indication of genotype stability, was observed for P9 (0.41%), which is considered the most stable genotype, followed by P35 (1.29%) and P31 (1.98%). For the predictability of the behavior of genotypes in the environments, P7 (80.85%), P35 (86.10%), P31 (85.90%), and P9 (97.42%) were considered predictable genotypes. The genotypes P11 (1045.6 kg ha-1 and 19.7%) and P21 (952.7 kg ha-1 and 20.6%) are recommended for cultivation in this region, considering both their grain yield and oil content. Safflower is viable to use out of season in the Brazilian Cerrado. The crop can generate profits for farmers and be used for oil production in periods of uncertain corn production.

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Aedes (Stegomyia) aegypti (L.) (Diptera: Culicidae) is the vector of multiple arboviruses. To evaluate the association between environmental factors and the oviposition activity of Ae. aegypti in Argentina, data on the presence and abundance of eggs were collected using ovitraps, between September of 2018 and May of 2019, in the cities of Villa María, Río Cuarto and Salsipuedes (Córdoba province, Argentina). We analysed the relationships between oviposition and five environmental factors: Temperature, precipitation, vegetation cover, human population density and distance to sites with a potential high density of larval habitats, like cemeteries and trash dumps. Environmental factors' data were collected using satellite image products. The oviposition activity was randomly distributed in three cities. Using generalized linear mixed models, we show that the house where each ovitrap was placed was a source of variability in oviposition, suggesting the relevance of microsite factors and the importance of domestic control actions. Ae. aegypti oviposition was positively correlated with night-time temperature of the previous 3 weeks, and in a context-dependent manner, it was positively correlated with human population density, vegetation cover and precipitation. The consistency and magnitude of these relationships varied between cities, indicating that oviposition is related to a complex system of environmental variables.

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We examined associations of individual-, neighborhood- and city-level education -as proxies of SES at different levels-, with diabetes, hypertension, obesity, smoking and binge drinking (non-communicable disease risk factors -NCD/RF) among Argentinian adults. We estimated mixed models based on 21,415 individuals from the 2013 National Survey of Risk Factors, living in 2,698 neighborhoods and 33 cities. Gradients by individual-level education differed by gender and NCD/RF, and some were modified by city education. In addition, we identified contextual effects of neighborhood and city education on some NCD/RF. Urban efforts to tackle NCD/RF in Argentina should be context- and gender-sensitive, and mainly focused on socially disadvantaged groups.

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Genetics plays a role in age-related macular degeneration (AMD), a common cause of blindness in the elderly. There is a need for powerful methods for carrying out region-based association tests between a dichotomous trait like AMD and genetic variants on family data. Here, we apply our new generalized functional linear mixed models (GFLMM) developed to test for gene-based association in a set of AMD families. Using common and rare variants, we observe significant association with two known AMD genes: CFH and ARMS2. Using rare variants, we find suggestive signals in four genes: ASAH1, CLEC6A, TMEM63C, and SGSM1. Intriguingly, ASAH1 is down-regulated in AMD aqueous humor, and ASAH1 deficiency leads to retinal inflammation and increased vulnerability to oxidative stress. These findings were made possible by our GFLMM which model the effect of a major gene as a fixed mean, the polygenic contributions as a random variation, and the correlation of pedigree members by kinship coefficients. Simulations indicate that the GFLMM likelihood ratio tests (LRTs) accurately control the Type I error rates. The LRTs have similar or higher power than existing retrospective kernel and burden statistics. Our GFLMM-based statistics provide a new tool for conducting family-based genetic studies of complex diseases. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

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We introduce a numerically tractable formulation of Bayesian joint models for longitudinal and survival data. The longitudinal process is modeled using generalized linear mixed models, while the survival process is modeled using a parametric general hazard structure. The two processes are linked by sharing fixed and random effects, separating the effects that play a role at the time scale from those that affect the hazard scale. This strategy allows for the inclusion of nonlinear and time-dependent effects while avoiding the need for numerical integration, which facilitates the implementation of the proposed joint model. We explore the use of flexible parametric distributions for modeling the baseline hazard function which can capture the basic shapes of interest in practice. We discuss prior elicitation based on the interpretation of the parameters. We present an extensive simulation study, where we analyze the inferential properties of the proposed models, and illustrate the trade-off between flexibility, sample size, and censoring. We also apply our proposal to two real data applications in order to demonstrate the adaptability of our formulation both in univariate time-to-event data and in a competing risks framework. The methodology is implemented in rstan.

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BACKGROUND: Quinoa (Chenopodium quinoa Willd.) is an ancient grain crop that is tolerant to abiotic stress and has favorable nutritional properties. Downy mildew is the main disease of quinoa and is caused by infections of the biotrophic oomycete Peronospora variabilis Gaüm. Since the disease causes major yield losses, identifying sources of downy mildew tolerance in genetic resources and understanding its genetic basis are important goals in quinoa breeding. RESULTS: We infected 132 South American genotypes, three Danish cultivars and the weedy relative C. album with a single isolate of P. variabilis under greenhouse conditions and observed a large variation in disease traits like severity of infection, which ranged from 5 to 83%. Linear mixed models revealed a significant effect of genotypes on disease traits with high heritabilities (0.72 to 0.81). Factors like altitude at site of origin or seed saponin content did not correlate with mildew tolerance, but stomatal width was weakly correlated with severity of infection. Despite the strong genotypic effects on mildew tolerance, genome-wide association mapping with 88 genotypes failed to identify significant marker-trait associations indicating a polygenic architecture of mildew tolerance. CONCLUSIONS: The strong genetic effects on mildew tolerance allow to identify genetic resources, which are valuable sources of resistance in future quinoa breeding.

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In longitudinal studies, repeated measures are collected over time and hence they tend to be serially correlated. These studies are commonly analyzed using linear mixed models (LMMs), and in this article we consider an extension of the skew-normal/independent LMM, where the error term has a dependence structure, such as damped exponential correlation or autoregressive correlation of order p. The proposed model provides flexibility in capturing the effects of skewness and heavy tails simultaneously when continuous repeated measures are serially correlated. For this robust model, we present an efficient EM-type algorithm for parameters estimation via maximum likelihood and the observed information matrix is derived analytically to account for standard errors. The methodology is illustrated through an application to schizophrenia data and some simulation studies. The proposed algorithm and methods are implemented in the new R package skewlmm.

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This cross-sectional study explores the different conditions related to the infestation of ticks in households and the potential risks for rickettsial transmission in Urabá, Colombia. The main outcome of interest was villagers' perception of tick infestation. The data were analyzed using a clog-log mixed regression model. Ticks were collected from infested humans to diagnose infection by spotted fever group rickettsiae (SFGR). In addition, a thematic analysis of qualitative data from key informants concerning knowledge about ticks was conducted. The prevalence of infestation of ticks in households was estimated at 60.99% (95% CI: 51.58-93.51). The multivariate model suggested that households with palm leaf roofs (PR = 1.95; 95% CI: 1.19-2.95), canines (PR = 1.76; 95% CI: 1.21-2.46), rats (PR = 2.19; 95% CI: 1.45-3.08), and with the presence of opossums in areas surrounding the households (PR = 1.51; 95% CI: 1.05-2.10) had a higher prevalence of tick infestation. Two samples of the tick species Amblyomma patinoi were found infected with Rickettsia amblyommatis and Candidatus Rickettsia colombianensi. A thematic analysis provided the names that local community members give to ticks, areas where ticks are common, and the individuals at risk of infestation. The presence of domestic, synanthropic, and wild animals suggests a high risk of the dissemination of ticks inside dwellings and close to them in these rural areas.

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