Single-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about tissue morphology and cellular interactions. Here, we combine single-cell and spatial transcriptomics with algorithms for data integration to study the development of the chicken heart from the early to late four-chambered heart stage. We create a census of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions in cardiac lineages defines transcriptional differences between epithelial and mesenchymal cells within the epicardial lineage. Using spatially resolved expression analysis, we identify anatomically restricted expression programs, including expression of genes implicated in congenital heart disease. Last, we discover a persistent enrichment of the small, secreted peptide, thymosin beta-4, throughout coronary vascular development. Overall, our study identifies an intricate interplay between cellular differentiation and morphogenesis.

The ability to manipulate small fluid droplets, colloidal particles and single cells with the precision and parallelization of modern-day computer hardware has profound applications for biochemical detection, gene sequencing, chemical synthesis and highly parallel analysis of single cells. Drawing inspiration from general circuit theory and magnetic bubble technology, here we demonstrate a class of integrated circuits for executing sequential and parallel, timed operations on an ensemble of single particles and cells. The integrated circuits are constructed from lithographically defined, overlaid patterns of magnetic film and current lines. The magnetic patterns passively control particles similar to electrical conductors, diodes and capacitors. The current lines actively switch particles between different tracks similar to gated electrical transistors. When combined into arrays and driven by a rotating magnetic field clock, these integrated circuits have general multiplexing properties and enable the precise control of magnetizable objects. O ne of the main goals of lab-on-a-chip research is to develop generic platforms for manipulating small fluid droplets, colloidal particles and single cells with the flexibility, scalability and automation of modern-day computer circuits. Single-cell arrays represent one high impact application of lab-on-a-chip tools, which are increasingly being adopted to evaluate rare biological responses in small-cell subsets that are overlooked by the ensemble averaging approaches of traditional biology. Improved understanding of these rare cellular responses can profoundly impact the development of vaccines and pharmaceuticals for curing infectious diseases and cancer 1,2 ; however there are few existing techniques with the scale and flexibility to unmask single-cell heterogeneity and pave the way for new medical breakthroughs 3-7 .In particular, there is an urgent need for tools to organize large arrays of single cells and single-cell pairs, evaluate the temporal responses of individual cell and cell-pair interactions over long durations, and retrieve specific cells from the array for follow-on analyses. The desired capabilities of single-cell arrays bear strong resemblance to random access memory (RAM) computer chips, including the ability to introduce and retrieve single cells from precise locations of the chip (writing data), and query the biological state of specified cells at future time points (reading data). Existing particle handling tools based on hydrodynamic 8-11 , optic 12-18 , electric [19][20][21][22] and magnetic [23][24][25][26][27][28][29][30][31][32][33][34][35][36] trapping forces can achieve parts of this desired functionality; however, no single technique to our knowledge encompasses the scalability, flexibility and automation that allows single-cell chips to perform with the level of integration of computer circuits.Our approach has significant similarities with magnetic bubble memory technology 37 , which was originally developed to store memory and implement lo...

Advances in electronics and life sciences have generated interest in "lab-on-a-chip" systems utilizing complementary metal oxide semiconductor (CMOS) circuitry for low-power, portable, and cost-effective biosensing platforms. Here, we present a simple and reliable approach for coating "high-κ" metal oxide dielectric materials with "non-fouling" (protein- and cell-resistant) poly(oligo(ethylene glycol) methyl ether methacrylate (POEGMA) polymer brushes as biointerfacial coatings to improve their relevance for biosensing applications utilizing advanced electronic components. By using a surface-initiated "grafting from" strategy, POEGMA films were reliably grown on each material, as confirmed by ellipsometric measurements and X-ray photoelectron spectroscopy (XPS) analysis. The electrical behavior of these POEGMA films was also studied to determine the potential impact on surrounding electronic devices, yielding information on relative permittivity and breakdown field for POEGMA in both dry and hydrated states. We show that the incorporation of POEGMA coatings significantly reduced levels of nonspecific protein adsorption compared to uncoated high-κ dielectric oxide surfaces as shown by protein resistance assays. These attributes, combined with the robust dielectric properties of POEGMA brushes on high-κ surfaces open the way to incorporate this protein and cell resistant polymer interface into CMOS devices for biomolecular detection in a complex liquid milieu.