Microglia have long been considered a homogenous cell population that uniformly responds to extrinsic factors. Here, we describe how the recent development of single-cell technologies has revealed the heterogeneity of both human and mouse microglia and identified distinct microglial states linked to specific developmental, aging, and disease stages. We discuss progress and future developments in data analysis, essential tools for the comprehension of big data derived from single-cell omics, and the necessity of integrating such data with functional studies to correlate genetic cues with the relevant biological functions of microglia. Defining the functional correlates of distinct microglia states is fundamental to dissecting the 'microglial etiology' of aging and complex neurological diseases and identifying novel therapeutic and diagnostic targets.
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