Single-cell lineage tracing reveals hierarchy and mechanism of adipocyte precursor maturation.

White adipose tissue is crucial in various physiological processes. In response to high caloric intake, adipose tissue may expand by generating new adipocytes. Adipocyte precursor cells (progenitors and preadipocytes) are essential for generating mature adipocytes, and single-cell RNA sequencing provides new means to identify these populations. Here, we characterized adipocyte precursor populations in the skin, an adipose depot with rapid and robust generation of mature adipocytes. We identified a new population of immature preadipocytes, revealed a biased differentiation potential of progenitor cells, and identified Sox9 as a critical factor in driving progenitors toward adipose commitment, the first known mechanism of progenitor differentiation. These findings shed light on the specific dynamics and molecular mechanisms underlying rapid adipogenesis in the skin.

CellTagging: combinatorial indexing to simultaneously map lineage and identity at single-cell resolution.

Single-cell technologies are offering unparalleled insight into complex biology, revealing the behavior of rare cell populations that are masked in bulk population analyses. One current limitation of single-cell approaches is that lineage relationships are typically lost as a result of cell processing. We recently established a method, CellTagging, permitting the parallel capture of lineage information and cell identity via a combinatorial cell indexing approach. CellTagging integrates with high-throughput single-cell RNA sequencing, where sequential rounds of cell labeling enable the construction of multi-level lineage trees. Here, we provide a detailed protocol to (i) generate complex plasmid and lentivirus CellTag libraries for labeling of cells; (ii) sequentially CellTag cells over the course of a biological process; (iii) profile single-cell transcriptomes via high-throughput droplet-based platforms; and (iv) generate a CellTag expression matrix, followed by clone calling and lineage reconstruction. This lentiviral-labeling approach can be deployed in any organism or in vitro culture system that is amenable to viral transduction to simultaneously profile lineage and identity at single-cell resolution.

Population structure leads to male-biased population sex ratios under environmental sex determination.

Spatial structure has been shown to favor female-biased sex allocation, but current theory fails to explain male biases seen in many taxa, particularly those with environmental sex determination (ESD). We present a theory and accompanying individual-based simulation model that demonstrates how population structure leads to male-biased population sex ratios under ESD. Our simulations agree with earlier work showing that the high productivity of female-producing habitats creates a net influx of sex-determining alleles into male-producing habitats, causing larger sex ratio biases, and lower productivity in male-producing environments (Harts et al. 2014). In contrast to previous findings, we show that male-biasing habitats disproportionately impact the global sex ratio, resulting in stable male-biased population sex ratios under ESD. The failure to detect a male bias in earlier work can be attributed to small subpopulation sizes leading to local mate competition, a condition unlikely to be met in most ESD systems. Simulations revealed that consistent male biases are expected over a wide range of population structures, environmental conditions, and genetic architectures of sex determination, with male excesses as large as 30 percent under some conditions. Given the ubiquity of genetic structure in natural populations, we predict that modest, enduring male biased allocation should be common in ESD species, a pattern consistent with reviews of ESD sex ratios.