Transcriptomics

Dataset Information

0

Heterogeneity in Somatic Cell Nuclear Transfer Embryo Reprogramming Across Mammalian Species


ABSTRACT: Somatic cell nuclear transfer (SCNT) enables the reprogramming of terminally differentiated somatic cells into a totipotent state, yet whether this process is governed by conserved mechanisms across mammalian species remains poorly understood. Here, we employed low input transcriptomics to profile global transcriptional dynamics during zygotic genome activation in SCNT embryos from five species: mouse, pig, cattle, goat, and sheep. Our analysis revealed distinct genome-wide expression patterns among these species, with 70.17% of differentially expressed genes (DEGs) being species-specific, while only 9.17% were shared DEGs. Functional annotation of the shared DEGs highlighted their enrichment in processes such as mRNA transcription, translation, and carbohydrate metabolism. Notably, we observed widespread pathway overactivation in SCNT embryos from cattle, mouse, and pig, whereas goat and sheep SCNT embryos exhibited broad suppression. Furthermore, weighted gene co-expression network analysis (WGCNA) demonstrated that species-specific effects exerted a far greater influence on reprogramming outcomes than the method of embryo generation (Fertilization or SCNT). Through systematic identification of key transcription factors, signaling pathways, epigenetic markers, and alternative splicing events, we uncovered species-specific regulatory patterns underlying reprogramming. Additionally, genome browser analysis revealed regional chromosomal expression anomalies in GDF9 and BMP15 during reprogramming across species. Collectively, our findings provide critical insights into the divergent mechanisms of reprogramming in mammalian species and establish a robust theoretical foundation for future studies in this field.

ORGANISM(S): Ovis aries

PROVIDER: GSE293654 | GEO | 2025/04/03

REPOSITORIES: GEO

Shared Molecules

Only show the datasets with similarity scores above: 0.5
     

Similar Datasets

2017-09-06 | GSE77020 | GEO
2010-11-16 | GSE25122 | GEO
2010-11-16 | E-GEOD-25122 | biostudies-arrayexpress
2021-09-21 | GSE161526 | GEO
2021-09-21 | GSE161525 | GEO
2021-09-21 | GSE161527 | GEO
2021-09-21 | GSE179527 | GEO
2017-09-06 | GSE93855 | GEO
2023-11-16 | GSE161563 | GEO
2022-11-09 | GSE217092 | GEO