scholarly journals A framework for studying behavioral evolution by reconstructing ancestral repertoires

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Damián G Hernández ◽  
Catalina Rivera ◽  
Jessica Cande ◽  
Baohua Zhou ◽  
David Stern ◽  
...  

Although different animal species often exhibit extensive variation in many behaviors, typically scientists examine one or a small number of behaviors in any single study. Here, we propose a new framework to simultaneously study the evolution of many behaviors. We measured the behavioral repertoire of individuals from six species of fruit flies using unsupervised techniques and identified all stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the intra- and inter-species behavioral covariances, and, by using the known phylogenetic relationships among species, we estimated the (unobserved) behaviors exhibited by ancestral species. We found that much of intra-specific behavioral variation has a similar covariance structure to previously described long-time scale variation in an individual’s behavior, suggesting that much of the measured variation between individuals of a single species in our assay reflects differences in the status of neural networks, rather than genetic or developmental differences between individuals. We then propose a method to identify groups of behaviors that appear to have evolved in a correlated manner, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the mechanistic basis of behavioral evolution.

2020 ◽  
Author(s):  
Damián G. Hernández ◽  
Catalina Rivera ◽  
Jessica Cande ◽  
Baohua Zhou ◽  
David L. Stern ◽  
...  

Although extensive behavioral changes often exist between closely related animal species, our understanding of the genetic basis underlying the evolution of behavior has remained limited. Here, we propose a new framework to study behavioral evolution by computational estimation of ancestral behavioral repertoires. We measured the behaviors of individuals from six species of fruit flies using unsupervised techniques and identified suites of stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the suites of behaviors exhibited by ancestral species, as well as the intra- and inter-species behavioral covariances. We found that much of intraspecific behavioral variation is explained by differences between individuals in the status of their behavioral hidden states, what might be called their “mood.” Lastly, we propose a method to identify groups of behaviors that appear to have evolved together, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the genetic basis of behavioral evolution.


2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Alireza Mirshahi ◽  
Peter Raak ◽  
Katharina Ponto ◽  
Bernhard Stoffelns ◽  
Katrin Lorenz ◽  
...  

Purpose. To report one-year results of phacoemulsification combined with deep sclerectomy and goniosynechiolysis ab interno for chronic glaucoma associated with peripheral anterior synechiae (PAS).Methods. We retrospectively analyzed medical charts of 16 patients (20 eyes) treated by one-site combined phacoemulsification and deep sclerectomy with goniosynechiolysis ab interno. PAS were transected by a spatula introduced into the anterior chamber through a paracentesis. To account for the correlation of right and left eyes a linear mixed model with unstructured covariance structure was calculated.Results. The mean preoperative intraocular pressure (IOP) was20.3±5.2 mmHg with2.4±1.0medications. One year postoperatively, the mean IOP was15.3±3.3 mmHg (P=0.004, pairedt-test) with0.6±1.0medications. A postoperative IOP of ≤21 mmHg without medication was achieved in 17 of 19 eyes (89.5%) and in 12/19 eyes (63.2%) at 3 and 12 months after surgery, respectively. In the remaining eyes (10.5% at 3 months and 36.8% at 12 months), additional medication led to an IOP ≤21 mmHg or the target pressure. No case required further glaucoma surgery. In one eye, conversion of the surgery to trabeculectomy was necessary due to Descemet’s window rupture.Conclusions. With goniosynechiolysis ab interno, effective and safe nonpenetrating glaucoma surgery is possible in presence of PAS.


2021 ◽  
Author(s):  
Hans-Peter Piepho ◽  
Martin Boer ◽  
Emlyn R. Williams

Large agricultural field trials may display irregular spatial trends that cannot be fully captured by a purely randomization-based analysis. For this reason, paralleling the development of analysis-of-variance procedures for randomized field trials, there is a long history of spatial modelling for field trials, starting with the early work of Papadakis on nearest neighbour analysis, which can be cast in terms of first or second differences among neighbouring plot values. This kind of spatial modelling is amenable to a natural extension using P-splines, as has been demonstrated in recent publications in the field. Here, we consider the P-spline framework, focussing on model options that are easy to implement in linear mixed model packages. Two examples serve to illustrate and evaluate the methods. A key conclusion is that first differences are rather competitive with second differences. A further key observation is that second differences require special attention regarding the representation of the null space of the smooth terms for spatial interaction, and that an unstructured variance-covariance structure is required to ensure invariance to translation and rotation of eigenvectors associated with that null space. We develop a strategy that permits fitting this model with ease, but the approach is more demanding than that needed for fitting models using first differences. Hence, even though in other areas second differences are very commonly used in the application of P-splines, our main conclusion is that with field trials first differences have advantages for routine use.


2019 ◽  
Author(s):  
Simone Lederer ◽  
Tom Heskes ◽  
Simon J. van Heeringen ◽  
Cornelis A. Albers

AbstractMotivationCellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different, yet similar, experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities.ResultsWe extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we in-vestigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using two representative real data sets we show that at most ∼ 40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure.Availability & ImplementationThe project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2980-2980
Author(s):  
Fabio Efficace ◽  
Valeria Santini ◽  
Giorgio La Nasa ◽  
Francesco Cottone ◽  
Carlo Finelli ◽  
...  

Abstract Background Anemia is a common symptom in patients with Myelodysplastic Syndromes (MDS) and although erythropoietic agents are often active, it is frequently treated with red blood cell (RBC) transfusions. A substantial proportion of patients might also eventually become transfusion-dependent and, Iron-chelating therapies might be important to minimize complications of iron overload. Objectives To investigate the impact of deferasirox therapy on health-related quality of life (HRQOL) of lower risk transfusion-dependent MDS patients over a one year period. Secondary objectives were to investigate relationships between HRQOL and ferritin levels and to explore the prognostic value of baseline HRQOL on the probability of achieving transfusion independence. Patients and Methods This was a prospective study whose clinical findings (i.e., primary endpoint was safety and tolerability) were previously reported. HRQOL was a secondary endpoint of the study and we herein report, for the first time, HRQOL prospective findings. Eligible patients included: MDS patients 18 years or older, International Prognostic Scoring System (IPSS) low or intermediate-1 risk and diagnosed with transfusional siderosis following a minimum of 20 blood transfusions. Patients received daily oral deferasirox at a dose between 10 and 30 mg/kg of body weight for a period of 1 year. HRQOL was assessed with the EORTC QLQ-C30. HRQOL at baseline and at 3, 6, 9 and 12 months after treatment start. The EORTC QLQ-C30 consists of 30 items and includes five functional scales (physical, role, emotional, social, and cognitive), three symptom (fatigue, nausea and vomiting and pain) and a global health status/QOL scale and six single items (dyspnea, insomnia, appetite loss, constipation, diarrhea and financial difficulties). The mean trend of HRQOL over time was estimated via a linear mixed model with a one-step autoregressive covariance structure. Such covariance structure provided the best model fit among those investigated. Results Overall, 159 patients were screened at 37 centers. The median duration of disease at enrollment was 32 months and median number of units of packed RBC received was 37. Seven patients did not start treatment at all and thus there were 152 expected HRQOL forms at baseline assessment. Out of these, 146 patients returned the questionnaire yielding a baseline compliance of 96%. No statistically significant differences over time were found for any scale of the EORTC QLQ-C30. Figure 1 depicts mean scores over time for selected scales of: fatigue, physical functioning, pain and global HRQOL. No HRQOL differences were found between patients with serum ferritin levels lower or higher than 2000 μg/L (pretreatment median value) at baseline. Also, the possible impact of ferritin level on HRQoL over time was estimated via a linear mixed model with a one-step autoregressive covariance structure. Coefficients and p values are reported in table 1. The prognostic impact of baseline HRQOL on the probability of achieving transfusion independence (i.e., defined as freedom from transfusion for 3 consecutive months) was investigated. Higher severity of pain (P=0.007) was associated with a greater likelihood of achieving transfusion independence. Multivariate analysis, controlling for age, IPSS risk score, time from diagnosis, number of previous blood transfusions and baseline ferritin level confirmed the independent value of pain (P=0.003). Conclusion Current findings suggest that Deferasirox therapy does not decrease HRQOL in lower risk transfusion-dependent MDS patients. Patients with higher baseline pain severity seems more likely to achieve transfusion independence and further analysis is needed to understand underlying reasons. Disclosures: No relevant conflicts of interest to declare.


2015 ◽  
Author(s):  
Sang Hong Lee ◽  
Julius van der Werf

We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method could be more than 1000 times faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multi-trait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss advantages and limitations.


2021 ◽  
Author(s):  
Mohammed Sultan ◽  
Ritbano Ahmed

Abstract The linear mixed model is one of the common models used to analyze the longitudinal data;it may comprise of separate (Univariate), joint Bivariate, and joint Multivariate linear mixed model, which is predicted on the number of response variables incorporated in the analysis. Adjusting for correlation matrix and covariance matrix between and within subjects is one reason why modern longitudinal data analysis techniques are deemed more appropriate than some of the previous methods of analysis. Some studies assume that the correlation between observation is zero. However, it is unlikely that repeated measurements on the same individual Will actually be independent. To that end, comparing the different linear mixed models identifying the appropriate model demonstrates that the evolution of patients with congestive heart failure is necessary.In this study the separate, bivariate, and multivariate linear mixed models were compared with different covariance and correlation structures. Finally, a multivariate linear mixed model with autoregressive order one correlation structure and unstructured covariance structure for random effects, to consider within and between patient's variations, was considered as a best model to depict the evolution of patients with congestive heart failure.


2021 ◽  
Vol 11 (1) ◽  
pp. 232
Author(s):  
Bartosz Dawidowski ◽  
Grzegorz Grelecki ◽  
Adam Biłgorajski ◽  
Piotr Podwalski ◽  
Błażej Misiak ◽  
...  

Background: Studies have shown that there are deviations in the results of peripheral blood counts, which lead to increased values of the neutrophils-to-lymphocytes ratio (NLR) in schizophrenia. Antipsychotic drugs have proven to lower the levels of pro-inflammatory cytokines and a growing number of studies indicate a similar effect on NLR values. Methods: We identified inpatients with schizophrenia and collected data of NLR at the beginning (NLR1) and end (NLR2) of hospitalization, the status of antipsychotic medication on admission and potential confounding factors. In the statistical analysis, we applied a linear mixed model. Results: After the inclusion and exclusion process the records of 40 patients (np = 40) and 71 hospitalizations (nh = 71) were analyzed. We found that in the group of antipsychotics-naive patients, the NLR1 were significantly higher than the NLR2 values. Such a difference did not occur in the case of non-antipsychotics-naïve patients. Age and the diagnosis of hypothyroidism influenced the value of change in NLR from the beginning to the end of hospitalization in a given patient (ΔNLR). Conclusions: The study confirmed the lowering effect of antipsychotics on NLR values in psychosis. The NLR may potentially be a tool for assessing response to treatment with antipsychotics.


2016 ◽  
Vol 10 (01) ◽  
pp. 1750007
Author(s):  
Yazhou Wu ◽  
Ling Zhang ◽  
Liang Zhou ◽  
Xiaoyu Liu ◽  
Ling Liu ◽  
...  

In repeated measurement data, the variables are not independent, and a certain auto-correlation typically exists between different levels of repeated measurement factors. The random error is composed of at least two parts, i.e. the individual random effect and the intra-individual multi-repeated measurement effect. Traditional statistical analysis methods (such as the [Formula: see text]-test and the one-way analysis of variance) are not applicable. The linear mixed model has been widely applied for the analysis and design of repeated measurement data. This paper focuses on medical examples and describes the selection of a covariance structure for the linear mixed model of repeated measurement in the modeling of different variance–covariance structures. By selecting different covariance structures, we can perform the parameter estimation and statistical test for the fixed effect of repeated measurement data, the parameters of random effects, and the covariance matrix. The results are analyzed and compared to provide a reference for applying the linear mixed model of repeated measurement to medical research.


2021 ◽  
Vol 16 (1) ◽  
pp. 13-18
Author(s):  
Victoria L. Goosey-Tolfrey ◽  
Julia O. Totosy de Zepetnek ◽  
Mhairi Keil ◽  
Katherine Brooke-Wavell ◽  
Alan M. Batterham

Purpose: To evaluate the tracking of within-athlete changes in criterion measures of whole-body fat percentage (BF%; dual-energy X-ray absorptiometry) with skinfold thickness (Σ 4, 6, or 8) in wheelchair basketball players. Methods: Dual-energy X-ray absorptiometry-derived whole BF% and Σ 4, 6, or 8 skinfolds were obtained at 5 time points over 15 months (N = 16). A linear mixed model with restricted maximum likelihood (random intercept, with identity covariance structure) to derive the within-athlete prediction error for predicting criterion BF% from Σ skinfolds was used. This prediction error allowed us to evaluate how well a simple measure of the Σ skinfolds could track criterion changes in BF %; that is, the authors derived the change in Σ skinfolds that would have to be observed in an individual athlete to conclude that a substantial change in criterion BF% had occurred. Data were log-transformed prior to analysis. Results: The Σ 8 skinfolds was the most precise practical measure for tracking changes in BF%. For the monitoring of an individual player, a change in Σ 8 skinfolds by a factor of greater than 1.28 (multiply or divide by 1.28) is associated with a practically meaningful change in BF% (≥1 percentage point). Conclusions: The Σ 8 skinfolds can track changes in BF% within individuals with reasonable precision, providing a useful field monitoring tool in the absence of often impractical criterion measures.


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