Takara Bio is proud to be presenting four scientific posters at AACR 2025!

Researchers seeking to study complete transcriptomes and identify complex isoforms, alternative splicing events, and structural variants (gene fusions, splice junctions, etc.,) from critical low-input samples currently do not have a commercially available, long-read sequencing option. With this poster, Dr. Bryan Bell showcased the SMART-Seq mRNA Long Read (SSmRNA LR) Kit, the first commercial solution for low-input transcriptome analysis with LR sequencing. Using both single cells and low-input amounts of total RNA, we demonstrated the kit’s ability to reliably sequence at an average length (N50) of 2 kb and detect full-length transcripts as long as 10 kb. Furthermore, our data provided a more complete picture of isoform-specific changes compared to other commercially available technologies. With the ability to process up to 96 samples at a time, this technology will enable the processing of rare or valuable samples to uncover novel biomarkers beyond gene expression. 

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Single-cell omics has been widely applied in oncology research for biomarker discovery, providing an in-depth understanding of cancer heterogeneity. While bulk sequencing methods lack the specificity afforded by single-cell studies, single-cell applications miss insights due to trade-offs for sensitivity at scale. Current-high throughput single-cell DNA-seq applications are limited to targeted sequencing approaches, while scaled single-cell RNA-seq applications are limited to 3’ or 5’ end counting methods or only capture polyadenylated RNA transcripts. In this poster, Shuwen Chen, PhD, discussed two automated, single-cell technologies that address these challenges—the Shasta Whole-Genome Amplification Kit and the Shasta Total RNA-Seq Kit. We demonstrated the application of these two technologies in the discovery of key biomarkers in representative oncological samples, including human lung cancer cell lines and primary cells dissociated from clear cell renal cell carcinoma. Furthermore, we highlighted the advantages of datasets generated from the above single-cell technologies, which, when paired with an unbiased, non-targeted approach, enable the discovery of novel genomic and transcriptomic biomarkers in oncological samples at an unprecedented scale and resolution.

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In this poster, Cedric R. Uytingco, PhD, discussed the advantages of spatial information in understanding tumor microenvironments (TME), which is crucial for evaluating tumor progression, immune infiltration, and therapeutic targets. Conventional single-cell sequencing lacks spatial context, but the FFPE-enabled Trekker single-cell spatial mapping kit adds to sequencing workflows by using Slide-tags to spatially label nuclei within tissue sections, enabling high-resolution spatial transcriptomics without the need for complex segmentation or deconvolution algorithms. Applied to archived FFPE breast cancer and other tumor samples, this tool allows for precise characterization of cellular heterogeneity and interactions, advancing disease analysis and therapeutic development.

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In this poster, Wanxin Wang, PhD, described the technique for easily obtaining spatial data from fresh/frozen human breast cancer tissues using the Trekker technology. We applied this technology to existing single-nuclei (sn) ATACseq and sn-V(D)J assays, enabling previously unattainable spatial exploration of gene expression and epigenetic regulation in tumors. Joint unsupervised clustering on sn-RNAseq and sn-ATACseq data identified spatially defined tumor, stromal, immune, and vasculature cell types driven by both transcriptomic and epigenetic signatures. The findings demonstrated the potential of Trekker technology to advance oncology and immunotherapy by providing a comprehensive spatial view of tumor ecosystems.

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