Coronary arteries supply the heart with oxygen and nutrients, and coronary artery disease is the leading cause of death. Elucidating the program of coronary artery development could aid understanding of the disease and lead to new treatments, but many aspects of the process, including their developmental origin, remain obscure. Current models posit that coronary arteries form by de novo assembly of endothelial tubes from progenitor cells in the proepicardium, a tissue that spreads over and contributes to the developing heart. Here, we use histological and clonal analysis in mice, and cardiac organ culture, to show that coronary vessels arise instead from angiogenic sprouts of the sinus venosus, the major vein that returns circulating blood to the embryonic heart. Sprouting venous endothelial cells dedifferentiate as they migrate over and invade the myocardium. Invading cells differentiate into arteries and capillaries, whereas cells remaining on the surface redifferentiate into veins. These results show that some differentiated venous cells retain developmental plasticity, and suggest that position-specific cardiac signals trigger their dedifferentiation and conversion into coronary arteries, capillaries, and veins. Understanding this novel developmental reprogramming process and identifying the endogenous signals should suggest more natural ways of engineering coronary bypass grafts and revascularizing the heart.

Arteries and veins are specified by antagonistic transcriptional programs. However, during development and regeneration, new arteries can arise from pre-existing veins through a poorly understood process of cell fate conversion. Here, using single-cell RNA sequencing and mouse genetics, we show that vein cells of the developing heart undergo an early cell fate switch to create a pre-artery population that subsequently builds coronary arteries. Vein cells underwent a gradual and simultaneous switch from venous to arterial fate before a subset of cells crossed a transcriptional threshold into the pre-artery state. Before the onset of coronary blood flow, pre-artery cells appeared in the immature vessel plexus, expressed mature artery markers, and decreased cell cycling. The vein-specifying transcription factor COUP-TF2 (also known as NR2F2) prevented plexus cells from overcoming the pre-artery threshold by inducing cell cycle genes. Thus, vein-derived coronary arteries are built by pre-artery cells that can differentiate independently of blood flow upon the release of inhibition mediated by COUP-TF2 and cell cycle factors.

Highlights d Artery endothelial cells (ECs) of neonatal hearts have a unique response to injury d Injury stimulates artery cell migration and reassembly into collateral arteries d CXCL12-CXCR4 signaling guides artery reassembly, facilitating heart regeneration d Adult artery ECs can be induced to undergo artery reassembly with exogenous CXCL12

Coronary arteries bring blood flow to the heart muscle. Understanding the developmental program of the coronary arteries provides insights into the treatment of coronary artery diseases. Multiple sources have been described as contributing to coronary arteries including the proepicardium, sinus venosus (SV), and endocardium. However, the developmental origins of coronary vessels are still under intense study. We have produced a new genetic tool for studying coronary development, an AplnCreER mouse line, which expresses an inducible Cre recombinase specifically in developing coronary vessels. Quantitative analysis of coronary development and timed induction of AplnCreER fate tracing showed that the progenies of subepicardial endothelial cells (ECs) both invade the compact myocardium to form coronary arteries and remain on the surface to produce veins. We found that these subepicardial ECs are the major sources of intramyocardial coronary vessels in the developing heart. In vitro explant assays indicate that the majority of these subepicardial ECs arise from endocardium of the SV and atrium, but not from ventricular endocardium. Clonal analysis of Apln-positive cells indicates that a single subepicardial EC contributes equally to both coronary arteries and veins. Collectively, these data suggested that subepicardial ECs are the major source of intramyocardial coronary arteries in the ventricle wall, and that coronary arteries and veins have a common origin in the developing heart.

Illumina-based next generation sequencing (NGS) has accelerated biomedical discovery through its ability to generate thousands of gigabases of sequencing output per run at a fraction of the time and cost of conventional technologies. The process typically involves four basic steps: library preparation, cluster generation, sequencing, and data analysis. In 2015, a new chemistry of cluster generation was introduced in the newer Illumina machines (HiSeq 3000/4000/X Ten) called exclusion amplification (ExAmp), which was a fundamental shift from the earlier method of random cluster generation by bridge amplification on a non-patterned flow cell. The ExAmp chemistry, in conjunction with patterned flow cells containing nanowells at fixed locations, increases cluster density on the flow cell, thereby reducing the cost per run. It also increases sequence read quality, especially for longer read lengths (up to 150 base pairs). This advance has been widely adopted for genome sequencing because greater sequencing depth can be achieved for lower cost without compromising the quality of longer reads. We show that this promising chemistry is problematic, however, when multiplexing samples. We discovered that up to 5-10% of sequencing reads (or signals) are incorrectly assigned from a given sample to other samples in a multiplexed pool. We provide evidence that this "spreading-of-signals" arises from low levels of free index primers present in the pool. These index primers can prime pooled library fragments at random via complementary 3' ends, and get extended by DNA polymerase, creating a new library molecule with a new index before binding to the patterned flow cell to generate a cluster for sequencing. This causes the resulting read from that cluster to be assigned to a different sample, causing the spread of signals within multiplexed samples. We show that low levels of free index primers persist after the most common library purification procedure recommended by Illumina, and that the amount of signal spreading among samples is proportional to the level of free index primer present in the library pool. This artifact causes homogenization and misclassification of cells in single cell RNA-seq experiments. Therefore, all data generated in this way must now be carefully re-examined to ensure that "spreading-ofsignals" has not compromised data analysis and conclusions. Re-sequencing samples using an older technology that uses conventional bridge amplification for cluster generation, or improved library cleanup strategies to remove free index primers, can minimize or eliminate this signal spreading artifact.

In recent years, there has been increasing interest in the role of lymphatics in organ repair and regeneration, due to their importance in immune surveillance and fluid homeostasis. Experimental approaches aimed at boosting lymphangiogenesis following myocardial infarction in mice, were shown to promote healing of the heart. Yet, the mechanisms governing cardiac lymphatic growth remain unclear. Here, we identify two distinct lymphatic populations in the hearts of zebrafish and mouse, one that forms through sprouting lymphangiogenesis, and the other by coalescence of isolated lymphatic cells. By tracing the development of each subset, we reveal diverse cellular origins and differential response to signaling cues. Finally, we show that lymphatic vessels are required for cardiac regeneration in zebrafish as mutants lacking lymphatics display severely impaired regeneration capabilities. Overall, our results provide novel insight into the mechanisms underlying lymphatic formation during development and regeneration, opening new avenues for interventions targeting specific lymphatic populations.

Background: Endothelial cells (ECs) display considerable functional heterogeneity depending on the vessel and tissue in which they are located. While these functional differences are presumably imprinted in the transcriptome, the pathways and networks which sustain EC heterogeneity have not been fully delineated. Methods: To investigate the transcriptomic basis of EC specificity, we analyzed single-cell RNA-sequencing (scRNA-seq) data from tissue-specific mouse ECs generated by the Tabula Muris consortium. We employed a number of bioinformatics tools to uncover markers and sources of EC heterogeneity from scRNA-seq data. Results: We found a strong correlation between tissue-specific EC transcriptomic measurements generated by either scRNA-seq or bulk RNA-seq, thus validating the approach. Using a graph-based clustering algorithm, we found that certain tissue-specific ECs cluster strongly by tissue (e.g. liver, brain) whereas others (i.e. adipose, heart) have considerable transcriptomic overlap with ECs from other tissues. We identified novel markers of tissue-specific ECs and signaling pathways that may be involved in maintaining their identity. Sex was a considerable source of heterogeneity in the endothelial transcriptome and we discovered Lars2 to be a gene that is highly enriched in ECs from male mice. In addition, we found that markers of heart and lung ECs in mice were conserved in human fetal heart and lung ECs. Finally, we identified potential angiocrine interactions between tissue-specific ECs and other cell types by analyzing ligand and receptor expression patterns. Conclusions: In summary, we use scRNA-seq data generated by the Tabula Muris consortium to uncover transcriptional networks that maintain tissue-specific EC identity and to identify novel angiocrine and functional relationships between tissue-specific ECs.

Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type–specific RNA splicing was discovered and analyzed across tissues within an individual.