Sika Zheng

Background/aim: Fibroblast Growth Factor Receptor (FGFR) gene fusions are recognized as pivotal oncogenic drivers, contributing to cancer initiation and progression across diverse malignancies. These fusions often represent significant therapeutic targets, particularly in challenging malignancies like cholangiocarcinoma. This study aimed to characterize the novel FGFR2::SHTN1 fusion, identify it as a de novo chimeric protein, and elucidate its precise oncogenic mechanism. Materials and methods: FGFR2::SHTN1 fusions were identified via cancer genomics databases and modeled using AlphaFold and HADDOCK. SHTN1 variants were expressed in Neuro-2a cells for coimmunoprecipitation, purification, and native polyacrylamide gel electrophoresis to assess oligomerization. Structural modeling included membrane embedding with Chemistry at HARvard Macromolecular Mechanics–Graphical User Interface (CHARMM–GUI). Results: We found that FGFR2::SHTN1 is an in-frame fusion formed by the joining of upstream FGFR2 exons 1–17 with downstream SHTN1 exons 7–17 in human, resulting in a chimeric protein retaining the intact FGFR2 tyrosine kinase domain. Our analyses revealed that Shootin1 inherently forms oligomers through its coiled–coil domains, which, within the fusion, mediate ligand-independent dimerization and constitutive activation of FGFR2. Conclusion: Our findings establish FGFR2::SHTN1 as a potent oncogenic driver in various cancers, particularly in cholangiocarcinoma, highlighting a unique mechanism of constitutive activation mediated by Shootin1’s CCD-II domain. This study represents the first molecular characterization of the FGFR2::SHTN1 fusion, advances understanding of FGFR2 fusion biology, and identifies a particular target for future diagnostic and therapeutic strategies in relevant malignancies.

Mammalian maximum lifespan (MLS) varies over a hundred-fold, yet the molecular mechanisms underlying this diversity remain unclear. We present a cross-species analysis of alternative splicing (AS) across six tissues in 26 mammals, identifying hundreds of conserved AS events significantly associated with MLS, with the brain containing twice as many tissue-specific events as peripheral tissues. MLS-AS events are enriched in pathways related to mRNA processing, stress response, neuronal functions, and epigenetic regulation, and are largely distinct from genes whose expression correlates with MLS, indicating that AS captures unique lifespan-related signals. The brain exhibits certain associations divergent from peripheral tissues and reduced overlap with body mass (BM)-associated splicing; neither is observed at the gene expression level. While MLS- and age-associated AS events show limited overlap, the shared events are enriched in intrinsically disordered protein regions, suggesting a role in protein flexibility and stress adaptability. Furthermore, MLS-associated AS events display stronger RNA-binding protein (RBP) motif coordination than age-associated ones, highlighting a more genetically programmed adaptation for lifespan determination, in contrast to the more variable splicing changes seen with chronological aging. These findings suggest alternative splicing as a distinct, transcription-independent axis of lifespan regulation, offering insights into the molecular basis of longevity.

Astrocyte-to-neuron reprogramming via depletion of PTBP1, a potent repressor of neuronal splicing, has been proposed as a therapeutic strategy, but its efficacy remains debated. While some reported successful conversion, others disputed this, citing a lack of neuronal gene expression as evidence of failed reprogramming. This interpretation was further challenged, attributed to incomplete PTBP1 inactivation, fueling ongoing controversy. Mechanistic understanding of the conversion, or the lack thereof, requires investigating, in conjunction with lineage tracing, the effect of Ptbp1 loss of function in mature astrocytes on RNA splicing, which has not yet been examined. Here, we genetically ablated PTBP1 in adult Aldh1l1-Cre/ERT2 Ai14 mice to determine whether lineage-traced Ptbp1 knockout astrocytes exhibited RNA splicing alterations congruent with neuronal differentiation. We found no widespread induction of neurons, despite a minuscule fraction of knockout cells showing neuron-like transcriptomic signatures. Importantly, PTBP1 loss in mature astrocytes induced splicing alterations unlike neuronal splicing patterns. These findings suggest that targeting PTBP1 alone is ineffective to drive neuronal reprogramming and highlight the need for combining splicing and lineage analyses. Loss of astrocytic PTBP1 is insufficient to induce neuronal splicing, contrasting with its well-known role in other non-neuronal cells, and instead affects a distinct astrocytic splicing program.

Astrocyte-to-neuron reprogramming via depletion of PTBP1, a potent repressor of neuronal splicing, has been proposed as a therapeutic strategy, but its efficacy remains debated. While some reported successful conversion, others disputed this, citing a lack of neuronal gene expression as evidence of failed reprogramming. This interpretation was further challenged, attributed to incomplete PTBP1 inactivation, fueling ongoing controversy. Mechanistic understanding of the conversion, or the lack thereof, requires investigating, in conjunction with lineage tracing, the effect of Ptbp1 loss of function in mature astrocytes on RNA splicing, which has not yet been examined. Here, we genetically ablated PTBP1 in adult Aldh1l1-Cre/ERT2 Ai14 mice to determine whether lineage traced Ptbp1 knockout astrocytes exhibited RNA splicing alterations congruent with neuronal differentiation. We found no widespread induction of neurons, despite a minuscule fraction of knockout cells showing neuron-like transcriptomic signatures. Importantly, PTBP1 loss in mature astrocytes induced splicing alterations unlike neuronal splicing patterns. These findings suggest that targeting PTBP1 alone is ineffective to drive neuronal reprogramming and highlight the need for combining splicing and lineage analyses. Loss of astrocytic PTBP1 is insufficient to induce neuronal splicing, contrasting with its well-known role in other non-neuronal cells, and instead affects a distinct astrocytic splicing program.

Mammalian maximum lifespan (MLS) varies over a hundred-fold, yet the molecular mechanisms underlying this diversity remain unclear. We present a cross-species analysis of alternative splicing (AS) across six tissues in 26 mammals, identifying hundreds of conserved AS events significantly associated with MLS, with the brain containing twice as many tissue-specific events as peripheral tissues. MLS-AS events are enriched in pathways related to mRNA processing, stress response, neuronal functions, and epigenetic regulation, and are largely distinct from genes whose expression correlates with MLS, indicating that AS captures unique lifespan-related signals. The brain exhibits certain associations divergent from peripheral tissues and reduced overlap with body mass (BM)-associated splicing; neither is observed at the gene expression level. While MLS- and age-associated AS events show limited overlap, the shared events are enriched in intrinsically disordered protein regions, suggesting a role in protein flexibility and stress adaptability. Furthermore, MLS-associated AS events display stronger RNA-binding protein (RBP) motif coordination than age-associated ones, highlighting a more genetically programmed adaptation for lifespan determination, in contrast to the more variable splicing changes seen with chronological aging. These findings suggest alternative splicing as a distinct, transcription-independent axis of lifespan regulation, offering new insights into the molecular basis of longevity.

Astrocyte-to-neuron reprogramming via depletion of PTBP1, a potent repressor of neuronal splicing, has been proposed as a therapeutic strategy, but its efficacy remains debated. While some reported successful conversion, others disputed this, citing a lack of neuronal gene expression as evidence of failed reprogramming. This interpretation was further challenged, attributed to incomplete PTBP1 inactivation, fueling ongoing controversy. Mechanistic understanding of the conversion, or the lack thereof, requires investigating, in conjunction with lineage tracing, the effect of Ptbp1 loss of function in mature astrocytes on RNA splicing, which has not yet been examined. Here, we genetically ablated PTBP1 in adult Aldh1l1-Cre/ERT2 Ai14 mice to determine whether lineage traced Ptbp1 knockout astrocytes exhibited RNA splicing alterations congruent with neuronal differentiation. We found no widespread induction of neurons, despite a minuscule fraction of knockout cells showing neuron-like transcriptomic signatures. Importantly, PTBP1 loss in mature astrocytes induced splicing alterations unlike neuronal splicing patterns. These findings suggest that targeting PTBP1 alone is ineffective to drive neuronal reprogramming and highlight the need for combining splicing and lineage analyses. Loss of astrocytic PTBP1 is insufficient to induce neuronal splicing, contrasting with its well-known role in other non-neuronal cells, and instead affects a distinct astrocytic splicing program.

Alternative pre-mRNA splicing (AS) is a fundamental regulatory process that generates transcript diversity and cell type variation. We developed Shiba, a comprehensive method that integrates transcript assembly, splicing event identification, read counting, and differential splicing analysis across RNA-seq platforms. Shiba excels in capturing annotated and unannotated AS events with superior accuracy, sensitivity, and reproducibility. It addresses the often-overlooked issue of junction read imbalance, significantly reducing false positives to aid target prioritization and downstream analyses. Unlike other tools that require large numbers of biological replicates or resulting in low sensitivity and high false positives, Shiba's statistics framework is agnostic to sample size, as demonstrated by simulated data and its effective application to real n= 1 RNA-seq datasets. To extend its utility to single-cell RNA-seq, we developed scShiba, which applies Shiba's pseudobulk approach to analyze splicing at the cluster level. scShiba successfully revealed AS regulation in developmental dopaminergic neurons and differences between excitatory and inhibitory neurons. Both Shiba and scShiba are available in Docker/Singularity containers and Snakemake pipelines, ensuring reproducibility. With their comprehensive capabilities, Shiba and scShiba enable systematic quantification of alternative splicing events across various platforms, laying a solid foundation for mechanistic exploration of the functional complexity in RNA splicing.

Alternative pre-mRNA splicing (AS) is a fundamental regulatory process that generates transcript diversity and cell type variation. We developed Shiba, a comprehensive method that integrates transcript assembly, splicing event identification, read counting, and differential splicing analysis across RNA-seq platforms. Shiba excels in capturing annotated and unannotated AS events with superior accuracy, sensitivity, and reproducibility. It addresses the often-overlooked issue of junction read imbalance, significantly reducing false positives to aid target prioritization and downstream analyses. Unlike other tools that require large numbers of biological replicates or resulting in low sensitivity and high false positives, Shiba’s statistics framework is agnostic to sample size, as demonstrated by simulated data and its effective application to real n =1 RNA-seq datasets. To extend its utility to single-cell RNA-seq, we developed scShiba, which applies Shiba’s pseudobulk approach to analyze splicing at the cluster level. scShiba successfully revealed AS regulation in developmental dopaminergic neurons and differences between excitatory and inhibitory neurons. Both Shiba and scShiba are available in Docker/Singularity containers and Snakemake pipelines, ensuring reproducibility. With their comprehensive capabilities, Shiba and scShiba enable systematic quantification of alternative splicing events across various platforms, laying a solid foundation for mechanistic exploration of the functional complexity in RNA splicing.