A 2026 study by T. Cody Brown integrates transcriptomic and proteomic data from peripheral white blood cells of 12 beef heifers (6 fertile, 6 subfertile). The dataset includes 230 differentially expressed genes and 70 differentially abundant proteins identified between groups, linked to pathways like cell cycle, metabolism, and immune signaling. Data integration and network analysis reveal regulatory patterns and potential biomarkers for fertility.
Use Cases
- Identify potential fertility biomarkers based on differentially expressed genes and proteins.
- Analyze regulatory networks and connectivity patterns between fertile and subfertile groups.
- Investigate the interplay between hormone signaling and chromatin regulation based on rewired epigenetic transcription factors.
- Validate candidate genes like NPL for their role in early pregnancy establishment.
Strengths
- Integrates two omics layers (transcriptomics and proteomics) from the same biological sample.
- Includes 230 differentially expressed genes and 70 differentially abundant proteins with statistical thresholds (P ≤ 0.05).
- Data is licensed under CC-BY-4.0, permitting open reuse with attribution.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The dataset is very small (13.7 KB), indicating a limited scope focused on summary results rather than raw sequencing data.
Provenance
- Source
- figshare, author T. Cody Brown.
- Collection Method
- RNA-Sequencing and untargeted proteomics performed on peripheral white blood cells collected before artificial insemination.
- Time Range
- The study was published in 2026; specific collection dates are not provided.
- Freshness
- Last updated 2026-04 19 22:01:30; freshness should be verified.
- Geography
- null