Wong, W. S. | Search bioRxiv

bioRxiv2026

Cardiac-immune microniches programme macrophage states in the regenerating heart

Adult zebrafish regenerate their hearts after injury, a process that requires macrophages, yet how local tissue microenvironments instruct macrophage states and function remains unclear. Here we combine single cell RNA sequencing with Visium and high-resolution MERFISH spatial transcriptomics to map the cardio-immune landscape of homeostatic and regenerating zebrafish hearts. We identify a mpeg1.1+ compartment comprising macrophages, dendritic, B and NK-like cells, and show that injury establishes a macrophage-centred immune environment with transcriptional programmes spanning resident surveillance, damage sensing, inflammation, antigen presentation, resolution and metabolic support. Communication-aware spatial modelling reveals that these states are not randomly distributed but organised into discrete structural-immune microniches across the injury region, each defined by stereotyped cellular compositions and ligand-receptor circuits. Within a fibroblast-macrophage microniche, we uncover an il34-csf1ra-egr1 axis in which col12a1a+ il34+ fibroblasts promote an egr1 pro-regenerative macrophage state that couples fibrosis, vascular integrity and epicardial signalling. We show that disruption of this axis by csf1ra loss of function reduces macrophage-, endothelial- and epicardial-rich microniches, amplifying fibroblast-driven domains that shift macrophages towards stress and long-sustained inflammatory programmes, thereby biasing early injury response towards a pro-fibrotic state. Our work establishes spatially defined cardio-immune microniches as key organisers of macrophage function and regenerative outcome, providing a mechanistic framework and actionable targets for reprogramming cardiac repair.

developmental biology↗

bioRxiv2017

Mendelian inheritance errors in whole genome sequenced trios are enriched in repeats and cluster within copy number losses

Trio-based whole genome sequencing (WGS) data can contribute significantly towards the development of quality control methods that can be applied to non-family WGS. Mendelian inheritance errors (MIEs) in parent-offspring trios are commonly attributed to erroneous sequencing calls, as the rate of true de novo mutations is extremely low compared to the incidence of MIEs. Here, we analyzed WGS data from 1,314 trios across diverse human populations with the goal of studying the characteristics of MIEs. We applied filters based on genotype call quality and observed that filtering has a greater impact on frequent MIEs. Our results indicate that MIEs are enriched in repeats and MIE density correlates with short interspersed nuclear elements (SINEs) density. We also observed clustered MIEs in regions overlapping large deletions. We created population-specific MIE profiles and discovered regions that represent different MIE distributions across populations. Finally, we have provided population-specific MIE tracks that can be loaded in UCSC Genome Browser. These profiles can be used for flagging calls in proximity of clustered MIEs before allele frequency and admixture calculations, annotating candidate de novo mutations, discovering population-specific putative deletions, and for distinguishing between regions that have errors due to sequence quality vs. chromosomal anomalies.

genomics↗