Runx1 promotes scar deposition and inhibits myocardial proliferation and survival during zebrafish heart regeneration.

Runx1 is a transcription factor that plays a key role in determining the proliferative and differential state of multiple cell types, during both development and adulthood. Here, we report how Runx1 is specifically upregulated at the injury site during zebrafish heart regeneration, and that absence of runx1 results in increased myocardial survival and proliferation, and overall heart regeneration, accompanied by decreased fibrosis. Using single cell sequencing, we found that the wild-type injury site consists of Runx1-positive endocardial cells and thrombocytes that induce expression of smooth muscle and collagen genes. Both these populations cannot be identified in runx1 mutant wounds that contain less collagen and fibrin. The reduction in fibrin in the mutant is further explained by reduced myofibroblast formation and upregulation of components of the fibrin degradation pathway, including plasminogen receptor annexin 2A as well as downregulation of plasminogen activator inhibitor serpine1 in myocardium and endocardium, resulting in increased levels of plasminogen. Our findings suggest that Runx1 controls the regenerative response of multiple cardiac cell types and that targeting Runx1 is a novel therapeutic strategy for inducing endogenous heart repair.BHF, Wellcome, MR

Unlocking the secrets of the regenerating fish heart: comparing regenerative models to shed light on successful regeneration

The adult human heart cannot repair itself after injury and, instead, forms a permanent fibrotic scar that impairs cardiac function and can lead to incurable heart failure. The zebrafish, amongst other organisms, has been extensively studied for its innate capacity to repair its heart after injury. Understanding the signals that govern successful regeneration in models such as the zebrafish will lead to the development of effective therapies that can stimulate endogenous repair in humans. To date, many studies have investigated cardiac regeneration using a reverse genetics candidate gene approach. However, this approach is limited in its ability to unbiasedly identify novel genes and signalling pathways that are essential to successful regeneration. In contrast, drawing comparisons between different models of regeneration enables unbiased screens to be performed, identifying signals that have not previously been linked to regeneration. Here, we will review in detail what has been learnt from the comparative approach, highlighting the techniques used and how these studies have influenced the field. We will also discuss what further comparisons would enhance our knowledge of successful regeneration and scarring. Finally, we focus on the Astyanax mexicanus, an intraspecies comparative fish model that holds great promise for revealing the secrets of the regenerating heart

Discordant genome assemblies drastically alter the interpretation of single-cell RNA sequencing data which can be mitigated by a novel integration method

Advances in sequencing and assembly technology have led to the creation of genome assemblies for a wide variety of non-model organisms. The rapid production and proliferation of updated, novel assembly versions can create vexing problems for researchers when multiple-genome assembly versions are available at once, requiring researchers to work with more than one reference genome. Multiple-genome assemblies are especially problematic for researchers studying the genetic makeup of individual cells, as single-cell RNA sequencing (scRNAseq) requires sequenced reads to be mapped and aligned to a single reference genome. Using the Astyanax mexicanus, this study highlights how the interpretation of a single-cell dataset from the same sample changes when aligned to its two different available genome assemblies. We found that the number of cells and expressed genes detected were drastically different when aligning to the different assemblies. When the genome assemblies were used in isolation with their respective annotations, cell-type identification was confounded, as some classic cell-type markers were assembly-specific, whilst other genes showed differential patterns of expression between the two assemblies. To overcome the problems posed by multiple-genome assemblies, we propose that researchers align to each available assembly and then integrate the resultant datasets to produce a final dataset in which all genome alignments can be used simultaneously. We found that this approach increased the accuracy of cell-type identification and maximised the amount of data that could be extracted from our single-cell sample by capturing all possible cells and transcripts. As scRNAseq becomes more widely available, it is imperative that the single-cell community is aware of how genome assembly alignment can alter single-cell data and their interpretation, especially when reviewing studies on non-model organisms