bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.10.01.755969

Long-read PacBio HiFi sequencing resolves the genomic integration site and structure of the Nestin-CreERT2KEisc/J transgene

Charest, A. M.·Charest, A.
View original source ↗Export metadata ↓

Abstract

Random integration transgenesis has been foundational to modern mouse genetics, generating thousands of lines that continue to serve as important tools in biomedical research. Yet for many of these models, the genomic integration site and associated genomic alterations remain unknown, complicating zygosity determination and potentially obscuring disruption of endogenous loci. Mice expressing inducible CreERT2 under rat Nes regulatory elements are widely used for in vivo lineage tracing of neural stem and progenitor cells, yet the genomic integration site of the Tg(Nes-cre/ERT2)KEisc/J transgene has remained undefined. Here, we used PacBio HiFi whole-genome sequencing to resolve its genomic locus and molecular architecture. We reconstructed the complete 13.7-kb transgene and mapped its integration to chromosome 6 within intron 1 of Kcnd2, where insertion was accompanied by deletion of 17.4 kb of endogenous genomic DNA. Identification of the integration junctions further enabled development of an allele-specific PCR assay for direct zygosity determination. Beyond resolving the molecular architecture of a widely used CreERT2 mouse line, this study demonstrates the utility of long-read HiFi sequencing for revisiting legacy transgenic models, uncovering otherwise hidden genomic alterations while enabling precise molecular genotyping.

Explore related subjects

genomicsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Charest, A. M., Charest, A.. 2026-10-02. Long-read PacBio HiFi sequencing resolves the genomic integration site and structure of the Nestin-CreERT2KEisc/J transgene. https://doi.org/10.64898/2026.10.01.755969

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

X-Y divergence of house fly (Musca domestica) proto-sex chromosomes follows distinct evolutionary trajectories despite residing in the same genome

Sex determination systems and sex chromosomes frequently differ between species. One cause of these differences is new sex determining genes that drive evolutionary turnover of sex chromosomes. At the earliest stages of this turnover, X and Y (or Z and W) chromosomes start out as nearly identical homologs, and they can diverge via chromosomal rearrangements (e.g., inversions) that suppress X-Y recombination. However, multiple examples from across animals and plants provide exceptions to this canonical model of sex chromosome evolution. For example, some X-Y pairs remain undifferentiated for long evolutionary time periods, while other sex chromosomes become differentiated without chromosomal rearrangements. How or why these non-canonical trajectories occur remains elusive, despite increasing evidence of their pervasiveness. The house fly, Musca domestica, is a well-suited system to address this gap because all six chromosomes can be a Y, providing multiple replicates of a natural experiment within a single genomic environment. To test for canonical and non-canonical evolutionary trajectories, we generated haplotype-resolved chromosome-level assemblies from five strains of the house fly, each of which carries a different Y chromosome (IM, IIM, IIIM, VM, and YM). We identified an inversion on only one of the sex chromosomes (IIM), which was associated with elevated X-Y divergence but did not capture the male-determining locus. In contrast, there was X-Y divergence across almost the entire length of the IM, IIIM, and VM sex chromosomes, despite no detectable inversions. YM was the only sex chromosome to contain substantial Y-specific sequences, which were limited to a segment on one end of the chromosome containing the male-determining gene. This YM chromosome, and its corresponding X, were highly diverged from the X chromosome found in many other flies (Muller element F), despite a strong cytological resemblance. This study highlights how multiple different canonical and non-canonical modes of sex chromosome evolution can co-exist within a single genome.

genomics↗
bioRxiv2026

Method-dependent biases in cell type detection between single-cell and single-nucleus RNA sequencing in the photosymbiotic acoel Praesagittifera naikaiensis

Background Comparisons of single-cell and single-nucleus RNA sequencing (scRNA-seq and snRNA-seq) data have been described in some mammalian tissues and, subsequently, in Drosophila, but remain unexplored in most invertebrate lineages. The xenacoelomorphs occupy key phylogenetic positions, yet they differ anatomically from mammals. They have a reduced extracellular matrix, high-salt body fluid, and no circulatory system. Despite these differences, they possess a well-developed nervous system. One of the xenacoelomorphs, the photosymbiotic acoel (Praesagittifera naikaiensis) also harbours symbiotic Tetraselmis algae, whose RNA can be co-captured with host RNA. Results We compared scRNA-seq and snRNA-seq data from whole P. naikaiensis specimens. Both methods yielded high-quality data with comparable gene detection but a larger share of scRNA-seq reads derived from symbiotic algae. Gene-level analyses revealed that neural genes were enriched in snRNA-seq relative to non-neural genes. Cross-method label transfer and integration-based validation identified six snRNA-seq clusters, including some neural populations, that lacked a clear scRNA-seq counterpart. In contrast, three cell populations, including muscle and metabolically active clusters, were reciprocally validated as captured by both methods. Conclusions Our results show that key snRNA-seq advantages, particularly the enhanced recovery of neural transcripts, are recapitulated in our dataset, which is consistent with previous reports in mammals. Furthermore, snRNA-seq reduces symbiont-derived reads and recovers several cell populations underrepresented in scRNA-seq. These findings provide practical guidance for cell atlas construction in non-model, symbiotic invertebrates.

genomics↗
bioRxiv2026

ST-DISTAL: Dual-Branch Graph Convolution with Distributional Alignment for Cell-Type Deconvolution

Spatial transcriptomics enables high-throughput gene expression profiling while preserving spatial information, offering valuable insights into tissue architecture and cellular organization. Methods that achieve single-cell or subcellular spatial resolution typically rely on predefined gene panels, which limits genome-wide discovery. In contrast, sequencing-based spatial transcriptomics platforms provide broad transcriptome coverage but measure expression at lower spatial resolution, capturing mixtures of multiple cell types within each spatial location and thereby requiring accurate cell-type deconvolution. Many existing deconvolution methods do not jointly model molecular expression similarity and spatial context, fail to align predicted cell-type compositions with biological priors, and may produce spatially inconsistent results that do not reflect the smooth and structured organization of real tissues. We present ST-DISTAL, a dual-branch graph convolutional framework for cell-type deconvolution in spatial transcriptomics data. ST-DISTAL integrates conventional spatial graph convolution with spectral Chebyshev filtering through an adaptive attention mechanism, enabling the model to capture both local spatial dependencies and global structural patterns. The framework is trained using a composite objective that jointly enforces accurate cell-type proportion estimation, global distributional alignment with reference profiles, and spatial smoothness. Evaluations on three simulated benchmark datasets demonstrate that ST-DISTAL consistently outperforms state-of-the-art methods in both prediction accuracy and distributional alignment. Further validation on a real human embryonic heart dataset and a colorectal cancer dataset shows biologically plausible and spatially coherent cell-type organization.

genomics↗