Publications

2023

1. Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data

   Jiayu Su ,  Jean-Baptiste Reynier ,  Xi Fu , and 8 more authors

   Genome Biology, 2023

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   Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a unified framework that integrates positional information into non-spatial models via modular priors and losses. In simulated and real datasets, Smoother enables accurate data imputation, cell-type deconvolution, and dimensionality reduction with remarkable efficiency. In colorectal cancer, Smoother-guided deconvolution reveals plasma cell and fibroblast subtype localizations linked to tumor microenvironment restructuring. Additionally, joint modeling of spatial and single-cell human prostate data with Smoother allows for spatial mapping of reference populations with significantly reduced ambiguity.

2. A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures

   Shulin Mao ,  Jiayu Su ,  Longteng Wang , and 3 more authors

   Genome Research, 2023

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   Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the “Mouse Aging Cell Atlas” (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for more than 20 murine tissues and created a multitissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of somatic mutations, and can distinguish subtle differences in aging even in cells of the same chronological age. We further compared SCALE with other transcriptomic and methylation “clocks” in data from aging muscle stem cells, Alzheimer’s disease, and heterochronic parabiosis. Our results confirm that SCALE is more generalizable and reliable in assessing biological aging in aging-related diseases and rejuvenating interventions. Overall, SCALE represents a valuable advancement in our ability to measure aging accurately, robustly, and interpretably in single cells.

3. Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths

   Mariela Cortés-López ,  Paulina Chamely ,  Allegra G Hawkins , and 8 more authors

   Cell Stem Cell, 2023

2022

1. Single-cell multi-omics defines the cell-type specific impact of splicing aberrations in human hematopoietic clonal outgrowths

   Federico Gaiti ,  Paulina Chamely ,  Allegra G Hawkins , and 8 more authors

   bioRxiv, 2022

2021

1. Immunotherapy for breast cancer using EpCAM aptamer tumor-targeted gene knockdown

   Ying Zhang ,  Xuemei Xie ,  Pourya Naderi Yeganeh , and 8 more authors

   Proceedings of the National Academy of Sciences, 2021

2020

1. Single-cell transcriptome profiling reveals neutrophil heterogeneity in homeostasis and infection

   Xuemei Xie ,  Qiang Shi ,  Peng Wu , and 8 more authors

   Nature immunology, 2020

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   The full neutrophil heterogeneity and differentiation landscape remains incompletely characterized. Here, we profiled >25,000 differentiating and mature mouse neutrophils using single-cell RNA sequencing to provide a comprehensive transcriptional landscape of neutrophil maturation, function and fate decision in their steady state and during bacterial infection. Eight neutrophil populations were defined by distinct molecular signatures. The three mature peripheral blood neutrophil subsets arise from distinct maturing bone marrow neutrophil subsets. Driven by both known and uncharacterized transcription factors, neutrophils gradually acquire microbicidal capability as they traverse the transcriptional landscape, representing an evolved mechanism for fine-tuned regulation of an effective but balanced neutrophil response. Bacterial infection reprograms the genetic architecture of neutrophil populations, alters dynamic transitions between subpopulations and primes neutrophils for augmented functionality without affecting overall heterogeneity. In summary, these data establish a reference model and general framework for studying neutrophil-related disease mechanisms, biomarkers and therapeutic targets at single-cell resolution.