|GAO, YAHUI - University Of Maryland|
|FANG, LINGZHAO - University Of Edinburgh|
|Baldwin, Ransom - Randy|
|CONNOR, ERIN - University Of Delaware|
|Van Tassell, Curtis - Curt|
|MA, LI - University Of Maryland|
|Li, Congjun - Cj|
|Liu, Ge - George|
Submitted to: Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/27/2021
Publication Date: 4/29/2021
Citation: Gao, Y., Fang, L., Baldwin, R.L., Connor, E.E., Cole, J.B., Van Tassell, C.P., Ma, L., Li, C., Liu, G. 2021. Single-cell transcriptomic analyses of cattle ruminal epithelial cells before and after weaning. Genomics. 113(4):2045-2055. https://doi.org/10.1016/j.ygeno.2021.04.039.
Interpretive Summary: Comprehensive analyses of tissues at single-cell level will benefit our understanding of genetic bases for complex traits. We provided the first cell type profiles for cattle rumen epithelial cells before and after weaning at a single-cell resolution. These results fill our knowledge gaps and provide the foundation for incorporating new transcriptome insights into the future animal breeding program. Farmers, scientist, and policy planners who need improve animal health and production based on genome-enabled animal selection will benefit from this study.
Technical Abstract: Background: Comprehensive analyses of tissues at single-cell level will benefit our understanding of genetic bases for complex traits. Although single cell RNA sequencing (scRNA-seq) has been widely explored in humans and other model species, its applications in livestock like cattle are still largely unreported. Here we present an initial effort of single-cell transcriptomic analyses of cattle ruminal epithelial cells before and after weaning. Results: Using the 10X Genomics Chromium Controller, we obtained 5064 and 1372 cells from Holstein ruminal epithelial cells before and after weaning, respectively. We detected 6 distinct cell clusters and designated their cell types using Human Cell Atlas/Blueprint reference cell datasets. We also found thousands of differential expressed genes (DEG), among cell clusters and between the feed schemes. We then performed cell cycle, pseudotime trajectory, regulatory network, as well as weighted gene co-expression network and gene ontology analyses. We proposed to assign Clusters C1 as active dividing epithelial stem cells, C0 as resting poised epithelial cells, C4 as keratinized epithelial cells during their terminal differentiation, C5 as muscle-like vascular cells, C2 and C3 as their intermediate populations for these differentiated extremes. We also reported a distinct sets of cell markers for these cell types, for example, BCRA1, HMMR, MKI67, and EZH2 for C1 and the TGFbeta pathway and the keratin gene family for C4. By integrating these DEG with Holstein GWAS signals, we found out all clusters, especially C5 and C0, were enriched for animal production and body type traits. Additionally, we confirmed their cell identifies by comparing them with the human and mouse stomach epithelial cells. Conclusions: This study provides a comprehensive resource for bovine rumen research and enables new discoveries about tissue/cell type roles in complex traits at single-cell resolution.