Advances in single-cell transcriptomics in animal research.
Yunan YanSenlin ZhuMinghui JiaXinyi ChenWenlingli QiFengfei GuTeresa G ValencakJian-Xin LiuHui-Zeng SunPublished in: Journal of animal science and biotechnology (2024)
Understanding biological mechanisms is fundamental for improving animal production and health to meet the growing demand for high-quality protein. As an emerging biotechnology, single-cell transcriptomics has been gradually applied in diverse aspects of animal research, offering an effective method to study the gene expression of high-throughput single cells of different tissues/organs in animals. In an unprecedented manner, researchers have identified cell types/subtypes and their marker genes, inferred cellular fate trajectories, and revealed cell‒cell interactions in animals using single-cell transcriptomics. In this paper, we introduce the development of single-cell technology and review the processes, advancements, and applications of single-cell transcriptomics in animal research. We summarize recent efforts using single-cell transcriptomics to obtain a more profound understanding of animal nutrition and health, reproductive performance, genetics, and disease models in different livestock species. Moreover, the practical experience accumulated based on a large number of cases is highlighted to provide a reference for determining key factors (e.g., sample size, cell clustering, and cell type annotation) in single-cell transcriptomics analysis. We also discuss the limitations and outlook of single-cell transcriptomics in the current stage. This paper describes the comprehensive progress of single-cell transcriptomics in animal research, offering novel insights and sustainable advancements in agricultural productivity and animal health.
Keyphrases
- single cell
- rna seq
- high throughput
- gene expression
- healthcare
- public health
- mental health
- dna methylation
- climate change
- health information
- depressive symptoms
- quality improvement
- intellectual disability
- induced apoptosis
- cell death
- autism spectrum disorder
- heavy metals
- amino acid
- oxidative stress
- endoplasmic reticulum stress
- transcription factor
- pi k akt
- bioinformatics analysis