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<p>Breast milk composition is a dynamic and adaptive biological system, influenced by maternal and neonatal factors such as gestational age at birth. Here, we present a multi-omics dataset that integrates single-cell RNA sequencing (scRNA-seq) and exosomal miRNA profiling from the same breast milk samples collected from mothers who delivered at varying gestational ages. This dataset provides a detailed snapshot of the cellular landscape and miRNA expression in breast milk, highlighting how these components transform to meet the developmental needs of preterm and term infants. Using scRNA-seq, we characterized the cellular composition of breast milk, identifying immune cells, epithelial cells, and other cell types, while uncovering transcriptomic adaptations associated with gestational age. Simultaneously, we isolated and sequenced exosomal miRNAs to capture their expression profiles, revealing molecular signatures and potential regulatory roles in infant development. By integrating these two omics layers, this dataset enables the exploration of the interplay between cellular heterogeneity and miRNA-mediated regulation in breast milk. This resource provides a unique foundation for advancing research on maternal-neonatal interactions, personalized nutrition, and the developmental needs of preterm infants, enabling integrative analysis across cellular and molecular dimensions.</p>

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A multi-omic dataset of cellular and microRNA profiles in human breast milk across a spectrum of gestational ages

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月24日

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  • Ling Ma,
  • Zhengming Zhan,
  • Kang Zhang,
  • Xia Hong,
  • Yangke Li,
  • Yanyan Huo,
  • Daqian Zhu,
  • Lian Jiang,
  • Fan Yang,
  • Yanjun Zhao,
  • Wenxian Wang,
  • Jiaojiao Song,
  • Junmei Zhou,
  • Jinjin Chen

摘要

Breast milk composition is a dynamic and adaptive biological system, influenced by maternal and neonatal factors such as gestational age at birth. Here, we present a multi-omics dataset that integrates single-cell RNA sequencing (scRNA-seq) and exosomal miRNA profiling from the same breast milk samples collected from mothers who delivered at varying gestational ages. This dataset provides a detailed snapshot of the cellular landscape and miRNA expression in breast milk, highlighting how these components transform to meet the developmental needs of preterm and term infants. Using scRNA-seq, we characterized the cellular composition of breast milk, identifying immune cells, epithelial cells, and other cell types, while uncovering transcriptomic adaptations associated with gestational age. Simultaneously, we isolated and sequenced exosomal miRNAs to capture their expression profiles, revealing molecular signatures and potential regulatory roles in infant development. By integrating these two omics layers, this dataset enables the exploration of the interplay between cellular heterogeneity and miRNA-mediated regulation in breast milk. This resource provides a unique foundation for advancing research on maternal-neonatal interactions, personalized nutrition, and the developmental needs of preterm infants, enabling integrative analysis across cellular and molecular dimensions.