Single-cell RNA sequencing (scRNA-seq) enables molecular characterization of complex biological tissues at high resolution. The requirement of single-cell extraction, however, makes it challenging for profiling tissues such as adipose tissue, for which collection of intact single adipocytes is complicated by their fragile nature. For such tissues, single-nucleus extraction is often much more efficient and therefore single-nucleus RNA sequencing (snRNA-seq) presents an alternative to scRNA-seq. However, nuclear transcripts represent only a fraction of the transcriptome in a single cell, with snRNA-seq marked with inherent transcript enrichment and detection biases. Therefore, snRNA-seq may be inadequate for mapping important transcriptional signatures in adipose tissue. In this study, we compare the transcriptomic landscape of single nuclei isolated from preadipocytes and mature adipocytes across human white and brown adipocyte lineages, with whole-cell transcriptome. We show that snRNA-seq is capable of identifying the broad cell types present in scRNA-seq at all states of adipogenesis. However, we also explore how and why the nuclear transcriptome is biased and limited, as well as how it can be advantageous. We robustly characterize the enrichment of nuclear-localized transcripts and adipogenic regulatory lncRNAs in snRNA-seq, while also providing a detailed understanding for the preferential detection of long genes upon using this technique. To remove such technical detection biases, we propose a normalization strategy for a more accurate comparison of nuclear and cellular data. Finally, we show successful integration of scRNA-seq and snRNA-seq data sets with existing bioinformatic tools. Overall, our results illustrate the applicability of snRNA-seq for the characterization of cellular diversity in the adipose tissue.

Noradrenaline (NA) regulates cold-stimulated adipocyte thermogenesis¹. Aside from cAMP signalling downstream of β-adrenergic receptor activation, how NA promotes thermogenic output is still not fully understood. Here, we show that coordinated α₁-adrenergic receptor (AR) and β₃-AR signalling induces the expression of thermogenic genes of the futile creatine cycle^2,3, and that early B cell factors, oestrogen-related receptors and PGC1α are required for this response in vivo. NA triggers physical and functional coupling between the α₁-AR subtype (ADRA1A) and Gα_q to promote adipocyte thermogenesis in a manner that is dependent on the effector proteins of the futile creatine cycle, creatine kinase B and tissue-non-specific alkaline phosphatase. Combined Gα_q and Gα_s signalling selectively in adipocytes promotes a continual rise in whole-body energy expenditure, and creatine kinase B is required for this effect. Thus, the ADRA1A-Gα_q-futile creatine cycle axis is a key regulator of facultative and adaptive thermogenesis.

Brown adipose tissue (BAT) regulates metabolic physiology. However, nearly all mechanistic studies of BAT protein function occur in a single inbred mouse strain, which has limited the understanding of generalizable mechanisms of BAT regulation over physiology. Here, we perform deep quantitative proteomics of BAT across a cohort of 163 genetically defined diversity outbred mice, a model that parallels the genetic and phenotypic variation found in humans. We leverage this diversity to define the functional architecture of the outbred BAT proteome, comprising 10,479 proteins. We assign co-operative functions to 2,578 proteins, enabling systematic discovery of regulators of BAT. We also identify 638 proteins that correlate with protection from, or sensitivity to, at least one parameter of metabolic disease. We use these findings to uncover SFXN5, LETMD1, and ATP1A2 as modulators of BAT thermogenesis or adiposity, and provide OPABAT as a resource for understanding the conserved mechanisms of BAT regulation over metabolic physiology.