Full
Outline
Bulk RNA sequencing （bulk RNA-seq） is extensively used in livestock research to characterize transcriptomic variation at the tissue level. However， as it captures only the average gene expression across mixed cell populations， it fails to resolve cellular heterogeneity， thereby limiting the dissection of complex trait regulation at the cellular scale. In contrast， single-cell RNA sequencing （scRNA-seq）， with its high resolution and sensitivity， enables detailed profiling of cellular composition and uncovers regulatory mechanisms underlying cell-to-cell variability. Despite its advantages， large-scale adoption of scRNA-seq in livestock is hindered by high costs， complex biological systems， and technical barriers. Against this background， single-cell deconvolution algorithms have emerged. Depending on data characteristics， these methods leverage strategies such as reference expression profile construction， marker gene selection， or unsupervised learning to infer cellular composition proportions from bulk RNA-seq data， thereby overcoming its inherent limitation in resolving cellular heterogeneity. Moreover， advanced algorithms can further predict cell-type-specific expression patterns， enabling functional interpretation at single-cell resolution from population-level transcriptomes. In recent years， these methods have been applied in key domestic species such as pigs， cattle， and chickens， supporting studies in traits related to growth， reproduction， and immune function. This review systematically summarizes the principles， mainstream algorithms， and current applications of single-cell deconvolution in livestock， with a particular focus on challenges in reference matrix construction， cross-platform data integration， and model adaptation. Furthermore， we discuss the expanding potential of deconvolution in multi-omics integration and functional cellular analysis， aiming to provide a conceptual and methodological framework for advancing its use in livestock research.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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