1. Transcriptome dataset of omental and subcutaneous adipose tissues from gestational diabetes patients
- Author
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David Salcedo-Tacuma, Leonardo Bonilla, Maria Cristina Geney Montes, Jorge Ernesto Niño Gonzalez, Sandra Milena Sanchez Gutierrez, Miguel Chirivi, and G. Andres Contreras
- Subjects
Statistics and Probability ,Pregnancy Outcome ,Library and Information Sciences ,Computer Science Applications ,Education ,Diabetes, Gestational ,Adipose Tissue ,Pregnancy ,Humans ,RNA ,Female ,Statistics, Probability and Uncertainty ,Transcriptome ,Information Systems - Abstract
Gestational diabetes (GD) is one of the most prevalent metabolic diseases in pregnant women worldwide. GD is a risk factor for adverse pregnancy outcomes, including macrosomia and preeclampsia. Given the multifactorial etiology and the complexity of its pathogenesis, GD requires advanced omics analyses to expand our understanding of the disease. Next generation RNA sequencing (RNA-seq) was used to evaluate the transcriptomic profile of subcutaneous and omental adipose tissues (AT) collected from patients with gestational diabetes and matched controls. Samples were harvested during cesarean delivery. Results show differences based on anatomical location and provide whole-transcriptome data for further exploration of gene expression patterns unique to GD patients.
- Published
- 2022
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