Evaluating kin and group selection as tools for quantitative analysis of microbial data.
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ABSTRACT:
SUBMITTER: Smith J
PROVIDER: S-EPMC8131122 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In a recent paper, Traulsen and Nowak use a multilevel selection model to show that cooperation can be favored by group selection in finite populations [Traulsen A, Nowak M (2006) Proc Natl Acad Sci USA 103:10952-10955]. The authors challenge the view that kin selection may be an appropriate interpretation of their results and state that group selection is a distinctive process "that permeates evolutionary processes from the emergence of the first cells to eusociality and the economics of nations." In this paper, we start by addressing Traulsen and Nowak's challenge and demonstrate that all their results can be obtained by an application of kin selection theory. We then extend Traulsen and Nowak's model to life history conditions that have been previously studied. This allows us to highlight the differences and similarities between Traulsen and Nowak's model and typical kin selection models and also to broaden the scope of their results. Our retrospective analyses of Traulsen and Nowak's model illustrate that it is possible to convert group selection models to kin selection models without disturbing the mathematics describing the net effect of selection on cooperation.
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Project description:Kin selection theory has been the central model for understanding the evolution of cooperative breeding, where non-breeders help bear the cost of rearing young. Recently, the dominance of this idea has been questioned; particularly in obligate cooperative breeders where breeding without help is uncommon and seldom successful. In such systems, the direct benefits gained through augmenting current group size have been hypothesized to provide a tractable alternative (or addition) to kin selection. However, clear empirical tests of the opposing predictions are lacking. Here, we provide convincing evidence to suggest that kin selection and not group augmentation accounts for decisions of whether, where and how often to help in an obligate cooperative breeder, the chestnut-crowned babbler (Pomatostomus ruficeps). We found no evidence that group members base helping decisions on the size of breeding units available in their social group, despite both correlational and experimental data showing substantial variation in the degree to which helpers affect productivity in units of different size. By contrast, 98 per cent of group members with kin present helped, 100 per cent directed their care towards the most related brood in the social group, and those rearing half/full-sibs helped approximately three times harder than those rearing less/non-related broods. We conclude that kin selection plays a central role in the maintenance of cooperative breeding in this species, despite the apparent importance of living in large groups.
| S-EPMC3415917 | biostudies-literature
Project description:Various steps in the RNA world required cooperation. Why did life's first inhabitants, from polymerases to synthetases, cooperate? We develop kin selection models of the RNA world to answer these questions. We develop a very simple model of RNA cooperation and then elaborate it to model three relevant issues in RNA biology: (1) whether cooperative RNAs receive the benefits of cooperation; (2) the scale of competition in RNA populations; and (3) explicit replicator diffusion and survival. We show: (1) that RNAs are likely to express partial cooperation; (2) that RNAs will need mechanisms for overcoming local competition; and (3) in a specific example of RNA cooperation, persistence after replication and offspring diffusion allow for cooperation to overcome competition. More generally, we show how kin selection can unify previously disparate answers to the question of RNA world cooperation.
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Project description:Comparative sequence analysis permits unraveling the molecular processes underlying gene evolution. Many statistical methods generate candidate positions within genes, such as fast or slowly evolving sites, coevolving groups of residues, sites undergoing positive selection, or changes in evolutionary rates. Understanding the functional causes of these evolutionary patterns requires combining the results of these analyses and mapping them onto molecular structures, a complex task involving distinct coordinate referential systems. To ease this task, we introduce the site/group extended data format, a simple text format to store (groups of) site annotations. We developed a toolset, the SgedTools, which permits site/group extended data file manipulation, creating them from various software outputs and translating coordinates between individual sequences, alignments, and three-dimensional structures. The package also includes a Monte-Carlo procedure to generate random site samples, possibly conditioning on site-specific features. This eases the statistical testing of evolutionary hypotheses, accounting for the structural properties of the encoded molecules.
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Project description:A computerized paradigm was created to allow for testing in the laboratory whether increasing systematicity helps the recruiter make better selection decisions. Participants were introduced to the job and the applicants on the computer screen and asked to select who they thought should be considered for the job and who should not. Level of systematicity, i.e. the extent to which the recruitment is methodical and uses prepared tools, was manipulated between subjects. Depending on experimental condition participants were helped by means of a tool for extracting judgment criteria (job analysis) and a tool for making judgments related to selected criteria (including calculation of a final score). The general prediction that increased systematicity leads to the selection of more qualified candidates was supported by the results, particularly when the motivation to put time and effort into the task was higher. The results support the claim from Industrial/Organizational psychologists that systematicity is a desirable characteristic in selection processes. The fact that increasing systematicity led to better selection decisions in a controlled laboratory experiment, along with process-related measures, suggests that this kind of paradigm could be useful when evaluating new tools for improving selection decisions, before they are tested in large (and costly) field studies of actual personnel selection.
| S-EPMC5440047 | biostudies-literature
Project description:PurposeTo use multimodal retinal images (including quantitative fundus autofluorescence [QAF]) for spectral-domain optical coherence tomography (SD-OCT)-based image registration and alignment. For each age decade of healthy adults, normative fine-grained QAF retinal maps are generated and advanced methods for QAF image analysis are applied.MethodsMultimodal retinal images were obtained from 103 healthy subjects (age 19-77 years; unremarkable retina/macula, age-appropriate clear optic media). Custom written FIJI plugins enabled: (1) determination of the fovea in SD-OCT and the edge of the optic disc in infrared (IR) images; (2) alignment and superimposition of multimodal retinal images based on foveal and optic disc position; (3) plotting of normative QAF retinal maps for each decade; and (4) comparison of individual retinas with normative retinas of different decades using newly introduced analysis patterns (QAF97, freehand tool).ResultsSD-OCT based image registration enables easy image registration, alignment, and analysis of different modalities (QAF, IR, and SD-OCT here reported). In QAF, intensities significantly increase with age with two major inclines between the third/fourth and seventh/eighth decades. With aging, the parafoveal area of maximum QAF intensity slightly shifts from temporal-superior to temporal. Compared with standard QAF analysis, refined QAF analysis patterns reveal a more detailed analysis of QAF, especially in the diseased retina.ConclusionsAge-related QAF normative retinal maps can be used to directly compare and classify individual's QAF intensities. Advanced QAF analysis tools will further help to interpret autofluorescence changes in normal aging and in the diseased retina in a multimodal imaging setting.Translational relevanceAdvanced methods for QAF analysis link basic findings with clinical observations in normal aging and in the diseased macula.
| S-EPMC7422829 | biostudies-literature
Project description:Variable selection in the presence of grouped variables is troublesome for competing risks data: while some recent methods deal with group selection only, simultaneous selection of both groups and within-group variables remains largely unexplored. In this context, we propose an adaptive group bridge method, enabling simultaneous selection both within and between groups, for competing risks data. The adaptive group bridge is applicable to independent and clustered data. It also allows the number of variables to diverge as the sample size increases. We show that our new method possesses excellent asymptotic properties, including variable selection consistency at group and within-group levels. We also show superior performance in simulated and real data sets over several competing approaches, including group bridge, adaptive group lasso, and AIC / BIC-based methods.
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Project description:BackgroundConventional wisdom in evolutionary theory considers aging as a non-selected byproduct of natural selection. Based on this, conviction aging was regarded as an inevitable phenomenon. It was also thought that in the wild organisms tend to die from diseases, predation and other accidents before they could reach the time when senescence takes its course. Evidence has accumulated, however, that aging is not inevitable and there are organisms that show negative aging even. Furthermore, old age does play a role in the deaths of many different organisms in the wild also. The hypothesis of programmed aging posits that a limited lifespan can evolve as an adaptation (i.e., positively selected for) in its own right, partly because it can enhance evolvability by eliminating "outdated" genotypes. A major shortcoming of this idea is that non-aging sexual individuals that fail to pay the demographic cost of aging would be able to steal good genes by recombination from aging ones.ResultsHere, we show by a spatially explicit, individual-based simulation model that aging can positively be selected for if a sufficient degree of kin selection complements directional selection. Under such conditions, senescence enhances evolvability because the rate of aging and the rate of recombination play complementary roles. The selected aging rate is highest at zero recombination (clonal reproduction). In our model, increasing extrinsic mortality favors evolved aging by making up free space, thereby decreasing competition and increasing drift, even when selection is stabilizing and the level of aging is set by mutation-selection balance. Importantly, higher extrinsic mortality is not a substitute for evolved aging under directional selection either. Reduction of relatedness decreases the evolved level of aging; chance relatedness favors non-aging genotypes. The applicability of our results depends on empirical values of directional and kin selection in the wild.ConclusionsWe found that aging can positively be selected for in a spatially explicit population model when sufficiently strong directional and kin selection prevail, even if reproduction is sexual. The view that there is a conceptual link between giving up clonal reproduction and evolving an aging genotype is supported by computational results.
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Project description:Valid variant calling results are crucial for the use of next-generation sequencing in clinical routine. However, there are numerous variant calling tools that usually differ in algorithms, filtering strategies, recommendations and thus, also in the output. We evaluated eight open-source tools regarding their ability to call single nucleotide variants and short indels with allelic frequencies as low as 1% in non-matched next-generation sequencing data: GATK HaplotypeCaller, Platypus, VarScan, LoFreq, FreeBayes, SNVer, SAMtools and VarDict. We analysed two real datasets from patients with myelodysplastic syndrome, covering 54 Illumina HiSeq samples and 111 Illumina NextSeq samples. Mutations were validated by re-sequencing on the same platform, on a different platform and expert based review. In addition we considered two simulated datasets with varying coverage and error profiles, covering 50 samples each. In all cases an identical target region consisting of 19 genes (42,322 bp) was analysed. Altogether, no tool succeeded in calling all mutations. High sensitivity was always accompanied by low precision. Influence of varying coverages- and background noise on variant calling was generally low. Taking everything into account, VarDict performed best. However, our results indicate that there is a need to improve reproducibility of the results in the context of multithreading.
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Project description:Group testing, as a cost-effective strategy, has been widely used to perform large-scale screening for rare infections. Recently, the use of multiplex assays has transformed the goal of group testing from detecting a single disease to diagnosing multiple infections simultaneously. Existing research on multiple-infection group testing data either exclude individual covariate information or ignore possible retests on suspicious individuals. To incorporate both, we propose a new regression model. This new model allows us to perform a regression analysis for each infection using multiple-infection group testing data. Furthermore, we introduce an efficient variable selection method to reveal truly relevant risk factors for each disease. Our methodology also allows for the estimation of the assay sensitivity and specificity when they are unknown. We examine the finite sample performance of our method through extensive simulation studies and apply it to a chlamydia and gonorrhea screening data set to illustrate its practical usefulness.
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