Patagonian Olive Mouse Transcriptomic and Phenotypic Data from Four Localities
by Facundo M. Giorello·Updated 6y ago
Available on 1 platform
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Description
Transcriptomic and phenotypic data from 95 Patagonian olive mouse specimens collected from four localities in steppe and forest biomes. The study identified nearly 3,000 differentially expressed genes between biomes, analyzing pathways for water regulation, immune function, and detoxification. Data supports investigation of genetic divergence and differential expression related to environmental adaptation.
Use Cases
Analyze differential expression of nearly 3,000 genes between steppe and forest biomes to study water regulation pathways.
Correlate phenotypic variables like kidney size and urine-to-plasma concentration ratios with annual rainfall data from sampled localities.
Investigate genetic divergence and allele frequency patterns for genes differentially expressed across contrasting habitats.
Study the expression of immune and detoxification function genes in response to different environmental conditions.
Strengths
Data from 95 individual mouse specimens provides a solid biological sample size.
Includes both transcriptomic data and phenotypic variables for integrative analysis.
Samples collected from four distinct localities representing contrasting steppe and forest biomes.
Study identified a specific set of nearly 3,000 differentially expressed genes for focused investigation.
Limitations
Specific column names, file formats, and data structure are not provided in the input.
Sample size of 95, while solid, may limit power for detecting subtle genetic or expression differences.
Geographic coverage is limited to four specific localities within Patagonia.
Provenance
Source
Dryad digital repository.
Collection Method
Specimens were sampled from four localities; phenotypic variables were measured and transcriptomic data was analyzed.
Freshness
Data was last updated in June 2020.
Geography
Localities in the arid Patagonian steppe and the Valdivian and Magellanic forests.
License is CC0 1.0 Public Domain Dedication. The specific variables (columns) and data file formats are not detailed in the provided input.