Spatial isoform analysis of the neonatal mouse heart reveals transcript-level patterns masked in gene-level analyses

Spatial transcriptomics has advanced the study of gene expression in tissues, but most current approaches rely on 3′-end sequencing and provide limited information on alternative splicing (AS). Spatially resolved isoform analysis can be achieved by combining microtissue sampling with Smart-seq2 RNA sequencing. Using 100-µm microtissues obtained from a single neonatal mouse heart (postnatal day 1; P01), we identified spatially variable transcript isoforms that are not readily detectable by conventional gene-level analyses. Although gene- and transcript-level clustering produced broadly similar spatial patterns, several genes exhibited isoform-level variation. For example, transcripts of Tnni1 and Ckb suggested spatial variation that was less structured than that of Pdlim5 , while Pdlim5 isoforms displayed distinct spatial distributions near the left ventricle. Comparison with postnatal day 7 (P07) hearts provided developmental context, suggesting that these spatial isoform patterns may undergo further remodeling during postnatal maturation. These results demonstrate the technical feasibility of spatial isoform analysis using a Smart-seq2-based workflow and provide a proof-of-principle framework for investigating spatial regulation of transcript isoforms during tissue development. Representative transcript-level observations were independently supported by isoform-specific qPCR. Although the biological findings require validation in independent samples, this approach establishes a practical strategy for transcript-level spatial analysis beyond conventional gene-level studies.

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Journal
Scientific Reports
Published
2026-09-15
DOI
https://doi.org/10.1038/s41598-026-71382-9
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Spatial isoform analysis of the neonatal mouse heart reveals transcript-level patterns masked in gene-level analyses

Hiroko Matsunaga, Haruko Takeyama, Ryota Wagatsuma, Kaori Sugiyama et al.
Scientific Reports
Single-cell and spatial transcriptomics
article

Spatial isoform analysis of the neonatal mouse heart reveals transcript-level patterns masked in gene-level analyses

Hiroko Matsunaga, Haruko Takeyama, Ryota Wagatsuma, Kaori Sugiyama, Yuki Makino
article en

Abstract

Spatial transcriptomics has advanced the study of gene expression in tissues, but most current approaches rely on 3′-end sequencing and provide limited information on alternative splicing (AS). Spatially resolved isoform analysis can be achieved by combining microtissue sampling with Smart-seq2 RNA sequencing. Using 100-µm microtissues obtained from a single neonatal mouse heart (postnatal day 1; P01), we identified spatially variable transcript isoforms that are not readily detectable by conventional gene-level analyses. Although gene- and transcript-level clustering produced broadly similar spatial patterns, several genes exhibited isoform-level variation. For example, transcripts of Tnni1 and Ckb suggested spatial variation that was less structured than that of Pdlim5 , while Pdlim5 isoforms displayed distinct spatial distributions near the left ventricle. Comparison with postnatal day 7 (P07) hearts provided developmental context, suggesting that these spatial isoform patterns may undergo further remodeling during postnatal maturation. These results demonstrate the technical feasibility of spatial isoform analysis using a Smart-seq2-based workflow and provide a proof-of-principle framework for investigating spatial regulation of transcript isoforms during tissue development. Representative transcript-level observations were independently supported by isoform-specific qPCR. Although the biological findings require validation in independent samples, this approach establishes a practical strategy for transcript-level spatial analysis beyond conventional gene-level studies.

Scientific Reports
Waseda University (JP)
Openalex Percentile: Top 18%
Single-cell and spatial transcriptomics
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Spatial isoform analysis of the neonatal mouse heart reveals transcript-level patterns masked in gene-level analyses — Hiroko Matsunaga, Haruko Takeyama, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS