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10 results for “genetic modularity”
Data from: Constraint and opportunity: the genetic basis and evolution of modularity in the cichlid mandible
Modular variation, whereby the relative degree of connectivity varies within a system, is sometimes thought to evolve through natural selection. In this way, modularity may facilitate evolution. Alternatively, conserved patterns of modularity may act to constrain evolution by preventing certain functions from evolving. A comprehensive understanding of the interplay between these phenomena will require knowledge of both the inheritance and genetic basis of modularity. Here we explore these ideas in the cichlid mandible by investigating modularity at the genus, species, and through a new approach, the individual level. Specifically, we assessed patterns of covariation in Lake Malawi cichlid species that employ alternate 'biting' and 'suction-feeding' modes of feeding, and in a hybrid cross between these two ecotypes. Across the suction-feeding genus, patterns of modularity were conserved and reflected function. In contrast, the 'biting' species displayed a pattern of modularity that closely matched developmental modules. The modularity pattern present in our F2 population was similar to the pattern exhibited by our biter, suggesting a role for dominance. We also demonstrated that our individual-level metrics of modularity (IMM) were a valid quantitative traits and used them to map modularity QTL. In all, our findings suggest that modularity is both a constraining and evolvable force in cichlid evolution, with distinct patterns between species and variation among individuals.
Data from: Genetic basis of continuous variation in the levels and modular inheritance of pigmentation in cichlid fishes
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Data from: Constraint and opportunity: the genetic basis and evolution of modularity in the cichlid mandible
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Data from: High-dimensional variance partitioning reveals the modular genetic basis of adaptive divergence in gene expression during reproductive character displacement
Although adaptive change is usually associated with complex changes in phenotype, few genetic investigations have been conducted of adaptations that involve sets of high dimensional traits. Microarrays have supplied high-dimensional descriptions of gene expression, and phenotypic change resulting from adaptation often results in large-scale changes in gene expression. We demonstrate how genetic analysis of large-scale changes in gene expression generated during adaptation can be accomplished by determining by high-dimensional variance partitioning within classical genetic experimental designs. A microarray experiment conducted on a panel of recombinant inbred lines (RILs) generated from two populations of Drosophila serrata that have diverged in response to natural selection, revealed genetic divergence in 10.6% of 3762 gene products examined. Over 97% of the genetic divergence in transcript abundance was explained by only 12 genetic modules. The two most important modules, explaining 50% of the genetic variance in transcript abundance, were genetically correlated with the morphological traits that are known to be under selection. The expression of three candidate genes from these two important genetic modules was assessed in an independent experiment using qRT-PCR on 430 individuals from the panel of RILs, and confirmed the genetic association between transcript abundance and morphological traits under selection.
Data from: Drosophila wing modularity revisited through a quantitative genetic approach
To predict the response of complex morphological structures to selection it is necessary to know how the covariation among its different parts is organized. Two key features of covariation are modularity and integration. The Drosophila wing is currently considered a fully integrated structure. Here, we study the patterns of integration of the Drosophila wing and test the hypothesis of the wing being divided into two modules along the proximo-distal axis, as suggested by developmental, biomechanical, and evolutionary evidence. To achieve these goals we perform a multilevel analysis of covariation combining the techniques of geometric morphometrics and quantitative genetics. Our results indicate that the Drosophila wing is indeed organized into two main modules, the wing base and the wing blade. The patterns of integration and modularity were highly concordant at the phenotypic, genetic, environmental, and developmental levels. Besides, we found that modularity at the developmental level was considerably higher than modularity at other levels, suggesting that in the Drosophila wing direct developmental interactions are major contributors to total phenotypic shape variation. We propose that the precise time at which covariance-generating developmental processes occur and/or the magnitude of variation that they produce favor proximo-distal, rather than anterior-posterior, modularity in the Drosophila wing.
Data from: Drosophila wing modularity revisited through a quantitative genetic approach
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Data from: High-dimensional variance partitioning reveals the modular genetic basis of adaptive divergence in gene expression during reproductive character displacement
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Bone Morphology is Regulated Modularly by Global and Regional Genetic Programs
GEO Series GSE129820. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice
GEO Series GSE294998. . 0 samples. Type: Expression profiling by high throughput sequencing.
Modular Design of T Cell Nanoengagers for Tumor Immunotherapy via Genetically Engineered Lipid-Tagged Antibody Fragments
GEO Series GSE293206. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.