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Motivation Single-cell RNA sequencing (scRNA-seq) continues to expand our knowledge by facilitating the study of transcriptional heterogeneity at the level of single cells. Despite this technology's utility and success in biomedical research, technical artifacts are present in scRNA-seq data. Doublets/multiplets are a type of artifact that occurs when two or more cells are tagged by the same barcode, and therefore they appear as a single cell. Because this introduces non-existent transcriptional profiles, doublets can bias and mislead downstream analysis. To address this limitation, computational methods to annotate and remove doublets form scRNA-seq datasets are needed. Results We introduce vaeda (Variational Auto-Encoder for Doublet Annotation), a new approach for computational annotation of doublets in scRNA-seq data. Vaeda integrates a variational auto-encoder and Positive-Unlabeled learning to produce doublet scores and binary doublet calls. We apply vaeda, along with seven existing doublet annotation methods, to 16 benchmark datasets and find that vaeda performs competitively in terms of doublet scores and doublet calls. Notably, vaeda outperforms other python-based methods for doublet annotation. Altogether, vaeda is a robust and competitive method for scRNA-seq doublet annotation and may be of particular interest in the context of python-based workflows. Availability and implementation Vaeda is available at https://github.com/kostkalab/vaeda , and the version used for the results we present here is archived at zenodo (https://doi.org/10.5281/zenodo.7199783). Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Recent technological advances in single-cell RNA sequencing (scRNA-Seq) have enabled scientists to answer novel questions in biology with unparalleled precision. Indeed, in the field of ocular development and regeneration, scRNA-Seq studies have resulted in a number of exciting discoveries that have begun to revolutionize the way we think about these processes. Despite the widespread success of scRNA-Seq, many scientists are wary to perform scRNA-Seq experiments due to the uncertainty of obtaining high-quality viable cell populations that are necessary for the generation of usable data that enable rigorous computational analyses. Here, we describe methodology to reproducibility generate high-quality single-cell suspensions from embryonic zebrafish eyes. These single-cell suspensions served as inputs to the 10× Genomics v3.1 system and yielded high-quality scRNA-Seq data in proof-of-principle studies. In describing methodology to quantitatively assess cell yields, cell viability, and other critical quality control parameters, this protocol can serve as a useful starting point for others in designing their scRNA-Seq experiments in the zebrafish eye and in other developing or regenerating tissues in zebrafish or other model systems., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Tet enzymes are epigenetic modifiers that impact gene expression via 5mC to 5hmC oxidation. Previous work demonstrated the requirement for Tet and 5hmC during zebrafish retinogenesis. tet2 -/- ;tet3 -/- mutants possessed defects in the formation of differentiated retinal neurons, but the mechanisms underlying these defects are unknown. Here, we leveraged scRNAseq technologies to better understand cell type-specific deficits and molecular signatures underlying the tet2 -/- ;tet3 -/- retinal phenotype. Our results identified defects in the tet2 -/- ;tet3 -/- retinae that included delayed specification of several retinal cell types, reduced maturity across late-stage cones, expansions of immature subpopulations of horizontal and bipolar cells, and altered biases of bipolar cell subtype fates at late differentiation stages. Together, these data highlight the critical role that tet2 and tet3 play as regulators of cell fate specification and terminal differentiation events during retinal development.

Laterality defects are defined by perturbations in the usual left-right asymmetry of organs. Due to low known genetic etiology of congenital heart disease (CHD) cases (less than 40%), we used a digenic model approach for the identification of contributing variants in known laterality defect genes (N = 115) in the exome/genome sequencing (ES/GS) data from individuals with clinically diagnosed laterality defects. The unsolved ES/GS data were analyzed from three CHD cohorts: Baylor College of Medicine-Genomics Research to Elucidate the Genetics of Rare Diseases (BCM-GREGoR; N = 247 proband ES), Gabriella Miller Kids First Pediatric Research program (Kids First; N = 158 trio GS), and Pediatric Cardiac Genomics Consortium (PCGC; N = 163 trio ES), and trans-heterozygous digenic variants were identified in 2.8% (inherited digenic variants in 0.4%), 8.2%, and 13.5% cases respectively, which was significantly higher as compared to 602 control trios provided by the 1000 Genomes Project (p = 0.001, 1.4e-07, and 8.9e-13, respectively). Trans-heterozygous digenic variants were also identified in 0.4%, and 1.4% cases with non-laterality CHD in Kids First and PCGC datasets, respectively, which was not statistically significant as compared to control trios ( p = 1, and 0.059, respectively). Altogether, in laterality cohorts, 23% of digenic pairs were in the same structural complex of motile cilia. Out of 39 unique digenic pairs in laterality CHD, 29 are more likely to be potential digenic hits as predicted by DiGePred tool. These findings provide further evidence that digenic epistatic interaction can contribute to the complex genetics of laterality defects.

Left-right patterning disturbance can cause severe birth defects, but it remains least understood of the three body axes. We uncovered an unexpected role for metabolic regulation in left-right patterning. Analysis of the first spatial transcriptome profile of left-right patterning revealed global activation of glycolysis, accompanied by right-sided expression of Bmp7 and genes regulating insulin growth factor signaling. Cardiomyocyte differentiation was left-biased, which may underlie the specification of heart looping orientation. This is consistent with known Bmp7 stimulation of glycolysis and glycolysis suppression of cardiomyocyte differentiation. Liver/lung laterality may be specified via similar metabolic regulation of endoderm differentiation. Myo1d , found to be left-sided, was shown to regulate gut looping in mice, zebrafish, and human. Together these findings indicate metabolic regulation of left-right patterning. This could underlie high incidence of heterotaxy-related birth defects in maternal diabetes, and the association of PFKP, allosteric enzyme regulating glycolysis, with heterotaxy. This transcriptome dataset will be invaluable for interrogating birth defects involving laterality disturbance.