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29 results for “phenotypic similarity”
Data from: Maximum mutational robustness in genotype-phenotype maps follows a self-similar blancmange-like curve
<div class="section abstract"> <p>Phenotype robustness, defined as the average mutational robustness of all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an evolving population. By applying results from coding theory, we prove that the maximum phenotype robustness occurs when genotypes are organised as bricklayer's graphs, so called because they resemble the way in which a bricklayer would fill in a Hamming graph. The value of the maximal robustness is given by a fractal continuous everywhere but differentiable nowhere sums-of-digits function from number theory. Interestingly, genotype-phenotype (GP) maps for RNA secondary structure and the HP model for protein folding can exhibit phenotype robustness that exactly attains this upper bound. By exploiting properties of the sums-of-digits function, we prove a lower bound on the deviation of the maximum robustness of phenotypes with multiple neutral components from the bricklayer's graph bound, and show that RNA secondary structure phenotypes obey this bound. Finally, we show how robustness changes when phenotypes are coarse-grained and derive a formula and associated bounds for the transition probabilities between such phenotypes.</p> </div>
Similarity network fusion to identify phenotypes of small for gestational age fetuses
<p>Fetal growth restriction (FGR) affects 5-10% of pregnancies, is the largest contributor to fetal death, and can have long-term consequences for the child. Implementation of a standard clinical classification system is hampered by the multiphenotypic spectrum of small fetuses with substantial differences in perinatal risks. Machine learning and multiomics data can potentially revolutionize clinical decision-making in FGR by identifying new phenotypes. Herein, we describe a cluster analysis of FGR based on an unbiased machine-learning method. Our results <em>confirm</em> the existence of two subtypes of human FGR with distinct molecular and clinical features based on multi-omic analysis. In addition, we demonstrated that clusters generated by machine learning significantly outperform single data subtype analysis and biologically support the current clinical classification in predicting adverse maternal and neonatal outcomes. Our approach can aid in the refinement of clinical classification systems for FGR supported by molecular and clinical signatures. </p>
Data from: Maximum mutational robustness in genotype-phenotype maps follows a self-similar blancmange-like curve
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Similar transcriptomic responses to early and late drought stresses produce divergent phenotypes in sunflower (Helianthus annuus L.)
<p>Cultivated sunflower (<em>Helianthus</em> <em>annuus</em> L.) exhibits numerous phenotypic and transcriptomic responses to drought. However, the ways in which these responses vary with differences in drought timing and severity are insufficiently understood. We used phenotypic and transcriptomic data to evaluate the response of sunflower to drought scenarios of different timing and severity in a common garden experiment. Using a semi-automated outdoor high-throughput phenotyping platform, we grew six oilseed sunflower lines under control and drought conditions. Our results reveal that similar transcriptomic responses can have disparate phenotypic effects when triggered at different developmental time points. Leaf transcriptomic responses, however, share similarities despite timing and severity differences (e.g., 523 differentially expressed genes (DEGs) were shared across all treatments), though increased severity elicits greater differences in expression, particularly during vegetative growth. Across treatments, DEGs were highly enriched for genes related to photosynthesis and plastid maintenance. A co-expression analysis identified a single module (M8) enriched in all drought stress treatments. Genes related to drought, temperature, proline biosynthesis, and other stress responses were overrepresented in this module. In contrast to transcriptomic responses, phenotypic responses were largely divergent between early and late drought. Early-stressed sunflowers responded to drought with reduced overall growth, but became highly water-acquisitive during recovery irrigation, resulting in overcompensation (higher aboveground biomass and leaf area) and a greater overall shift in phenotypic correlations, whereas late-stressed sunflowers were smaller and more water use-efficient. Taken together, these results suggest that drought stress at an earlier growth stage elicits a change in development that enables greater uptake and transpiration of water during recovery, resulting in higher growth rates despite similar initial transcriptomic responses.</p>
Similar transcriptomic responses to early and late drought stresses produce divergent phenotypes in sunflower (Helianthus annuus L.)
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Data from: Positive relationships between association strength and phenotypic similarity characterize the assembly of mixed-species bird flocks worldwide
Competition theory predicts that communities at small spatial scales should consist of species more dissimilar than expected by chance. We find a strikingly different pattern in a multi-continent dataset (55 presence-absence matrices from 24 locations) on the composition of mixed-species bird flocks, important subunits of local bird communities the world over. Using null models and randomization tests followed by meta-analysis, we find the association strength of species in flocks to be strongly related to similarity in body size and foraging behavior, and higher for congeneric compared with non-congeneric species pairs. Given the small spatial scale of our individual analyses, differences in habitat preferences of species are unlikely to have caused these association patterns; therefore, the patterns are most likely the outcome of species interactions. Extending group-living and social information use theory to a heterospecific context, we discuss potential behavioral mechanisms leading to positive interactions among similar species in flocks as well as ways in which competition costs are reduced. Our findings highlight the need to consider positive interactions along with competition when seeking to explain community assembly.
Fig. 4. A in Ontogenetic modifications produce similar phenotypes in distantly related click beetles (Coleoptera: Elateridae)
Fig. 4. A—Cebrio (Tibesia) igelmimen Rattu et François, 2021 from Morocco, female, general appearance. Cebriorhipis sp. from Bali. B—head, ventral view; C, D—pronotum, lateral and ventral view; F—elytron; G–I male genitalia, ventral, dorsal, and lateral view; J—abdomen, ventral view; K—terminal abdominal segments; L—mesoscutellum; M—metathoracic leg. Scales 1.0 mm. Figure 4A was published by Rattu and François (2021) and is here reprinted with permission of the authors who retain the copyright of this photo.
Fig. 1 in Ontogenetic modifications produce similar phenotypes in distantly related click beetles (Coleoptera: Elateridae)
Fig. 1. The mitogenomic relationships of soft-bodied and/or non-clicking genera Paulusiella, Cebrio, Scaptolenus, Analestesa, Plastocerus, Drilus, and their clicking relatives.The numbers at branches designate ultrafast bootstrap values and posterior probabilities. (A)The maximum likelihood analysis of the mt/nDNA dataset with single partition, non-focal clades are collapsed, Lissominae and Pityobiinae omitted. (B)The maximum likelihood analysis of thirteen protein-coding mitochondrial genes at the nucleotide level with coding masked by the degen software and partitioned by genes. (C)The Bayesian analysis using PhyloBayes at the nucleotide level.The trees with full-length branches and the results of additional analyses are shown in Supplementary Figs. S2–S14. Paulisiella, Cebrio, and Cebriorrhipis (red or grey colored)—the taxa earlier placed in Cebrionini; Plastocerus, Selasia, Drilus, and Malacogaster (magenta or grey colored)—non-clicking elaterids earlier placed in families Drilidae and Plastoceridae.
Fig. 3 in Ontogenetic modifications produce similar phenotypes in distantly related click beetles (Coleoptera: Elateridae)
Fig. 3. Analestesa arabica (Paulus, 1981) from Saudi Arabia (except for Fig. 3I). A—general appearance, dorsal view; B–D—frontal part of the body, dorsally (B, C) and ventrally); E—head in lateral view; F–H—pronotum, lateral, dorsolateral, and posterior view; I—antenna; J—elytron; K, M—male genitalia, ventrally, dorsally, laterally; l—Male genitalia of Dicronychus cinereus (Herbst, 1784); N—hind tarsus and apical part of tibia; O—abdomen, ventral view; P—terminal abdominal segments. Scales 0.5 mm.
Fig. 2 in Ontogenetic modifications produce similar phenotypes in distantly related click beetles (Coleoptera: Elateridae)
Fig. 2. Paulusiella sp. from Iran. A—general appearance, dorsal view; B, C—frontal part of the body, dorsally and ventrally; D—antenna; E—head and pronotum in lateral view; F, G—head, ventral and dorsal view; H—mesonotum; I—elytron; J–L—pronotum, dorsally, laterally, posterior view, M prosternal process, and mesosternal pit; N–P male genitalia, ventrally, dorsally, laterally; Q—terminal abdominal segments. Scales 0.5 mm.
Fig. 5 in Ontogenetic modifications produce similar phenotypes in distantly related click beetles (Coleoptera: Elateridae)
Fig. 5. Hemiops sp. from Laos. A–C general appearance, dorsal, ventral, and lateral aspects; D—pronotum; E—basal antennomeres; F—pronotum and head, ventrolateral view; G—head, dorsally; H—prosternal process and mesosternal pit; I, J—male genitalia; K—metathoracic leg; L—head ventrally; M—mesonotum; N, O º pronotum, dorsal, and posterior view; P—terminal abdominal segments. Scales 1.0 mm.
Data from: Genomic region associated with run-timing has similar haplotypes and phenotypic effects across three lineages of Chinook salmon
<p><span><span><span><span><span><span><span><span><span><span><span>Conserving life history variation is a stated goal of many management programs, but the most effective means by which to accomplish this are often far from clear. Early, premature migrating and late, mature migrating forms of Chinook salmon face unequal pressure from natural and anthropogenic forces. These forces may result in the diminishment of migration variation in some stocks because migration timing is known to be highly heritable. Genomic regions of chromosome 28 are known to be strongly associated with migration variation in adult Chinook salmon, but it remains unclear whether there is consistent association among the diverse populations of Chinook salmon. Therefore, application of this association for management may be premature. We examined the association of genetic variation in 28 markers on chromosome 28 surveyed with high-throughout genotyping (GT-seq) with individual run timing characteristics gleaned from passive integrated transponder recordings of over 5,000 Chinook salmon from the three phylogeographic lineages that inhabit the Columbia River Basin. Despite the strong genetic differences among them, the three lineages exhibited very similar genetic variants in the chromosome 28 region and moderate to strong association of these variants and run timing phenotypes. This is particularly notable for the interior stream-type lineage, which exhibits an earlier and more constrained migration of fish than the other lineages and which are exclusively premature when they enter freshwater. In both interior stream-type and interior-ocean type Chinook salmon, heterozygotes of the most strongly associated linkage groups are largely intermediate to homozygotes in migration timing, and while we make no robust conclusions about dominance, results indicate codominance or marginal partial dominance of the early migrating allele. Our results lend support to the cautious utilization of chromosome 28 variation in tracking and predicting run timing in these Chinook salmon.</span></span></span></span></span></span></span></span></span></span></span></p>
50 shades of greenbeard: Robust evolution of altruism based on similarity of complex phenotypes
<p>We study the evolution of altruistic behavior under a model where individuals choose to cooperate by comparing a set of continuous phenotype tags. Individuals play a donation game and only donate to other individuals that are sufficiently similar to themselves in a multidimensional phenotype space. We find the generic maintenance of robust altruism when phenotypes are multidimensional. Selection for altruism is driven by the coevolution of individual strategy and phenotype; altruism levels shape the distribution of individuals in phenotype space. Low donation rates induce a phenotype distribution that renders the population vulnerable to the invasion of altruists, whereas high donation rates prime a population for cheater invasion, resulting in cyclic dynamics that maintain substantial levels of altruism. Altruism is therefore robust to invasion by cheaters in the long term in this model. Furthermore, the shape of the phenotype distribution in high phenotype dimension allows altruists to better resist the invasion by cheaters, and as a result, the amount of donation increases with increasing phenotype dimension. We also generalize previous results in the regime of weak selection to two competing strategies in continuous phenotype space, and show that success under weak selection is crucial to success under strong selection in our model. Our results support the viability of a simple similarity-based mechanism for altruism in a well-mixed population.</p>
Data from: Genomic region associated with run-timing has similar haplotypes and phenotypic effects across three lineages of Chinook salmon
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50 shades of greenbeard: Robust evolution of altruism based on similarity of complex phenotypes
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Data from: Positive relationships between association strength and phenotypic similarity characterize the assembly of mixed-species bird flocks worldwide
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Data from: Color phenotypes are under similar genetic control in two distantly related species of Timema stick insect
Ecology and genetics are both of general interest to evolutionary biologists as they can influence the phenotypic and genetic response to selection. The stick insects Timema podura and T. cristinae exhibit a green/melanistic body color polymorphism that is subject to different ecologically-based selective regimes in the two species. Here we describe aspects of the genetics of this color polymorphism in T. podura, and compare this to previous results in T. cristinae. We first show that similar color phenotypes of the two species cluster in phenotypic space. We then use genome-wide association mapping to show that in both species, color is controlled by few loci, dominance relationships between color alleles are the same, and SNPs associated with color phenotypes co-localize to the same linkage group. Regions within this linkage group that harbor genetic variants associated with color exhibit elevated linkage disequilibrium relative to genome wide expectations, but more strongly so in T. cristinae. We use these results to discuss predictions regarding how the genetics of color could influence levels of phenotypic and genetic variation that segregate within and between populations of T. podura and T. cristinae, drawing parallels with other organisms.
Data from: Color phenotypes are under similar genetic control in two distantly related species of Timema stick insect
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Data from: Phylogenetic relatedness, phenotypic similarity, and plant-soil feedbacks
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Appropriately Differentiated ARPE-19 Cells Regain a Native Phenotype and Similar Gene Expression Profile
GEO Series GSE88848. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.