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<p>Noncanonical small RNAs, such as tRNA-derived (tsRNAs) and rRNA-derived (rsRNAs) fragments, are more abundant than microRNAs and arise from selective cleavage events rather than random degradation. While fragmentation of parental RNAs produces functionally diverse small RNAs, current analytical approaches are limited to abundance measures and cannot systematically quantify differential cleavage signals. Here, we present <i>qMAP</i>, a computational framework profiling differential fragmentation of parental RNAs from small RNA sequencing data. <i>qMAP</i> integrates two complementary models to identify condition-specific fragmentation patterns and includes a dedicated module to pinpoint the small RNA species driving these differences. Using <i>qMAP</i>, we uncover dynamic tRNA and rRNA fragmentation during mouse cell reprogramming, demonstrate the classification power of RNA fragmentation in human ulcerative colitis, develop and validate a blood-based RNA fragmentation signature of recurrent implantation failure, and identify aging-associated RNA fragmentation in sperm, which supports RNA fragmentation as a distinct regulatory dimension beyond expression/abundance information. <i>qMAP</i> enables systematic exploration of the regulatory “RNA fragmentome”, providing a foundational tool for both mechanistic discovery and translational applications of noncanonical small RNAs.</p>

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qMAP decodes RNA fragmentation dynamics in development and disease

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月20日

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  • Hukam C Rawal,
  • Jiancheng Yu,
  • Xudong Zhang,
  • Chen Cai,
  • Qi Chen,
  • Tong Zhou

摘要

Noncanonical small RNAs, such as tRNA-derived (tsRNAs) and rRNA-derived (rsRNAs) fragments, are more abundant than microRNAs and arise from selective cleavage events rather than random degradation. While fragmentation of parental RNAs produces functionally diverse small RNAs, current analytical approaches are limited to abundance measures and cannot systematically quantify differential cleavage signals. Here, we present qMAP, a computational framework profiling differential fragmentation of parental RNAs from small RNA sequencing data. qMAP integrates two complementary models to identify condition-specific fragmentation patterns and includes a dedicated module to pinpoint the small RNA species driving these differences. Using qMAP, we uncover dynamic tRNA and rRNA fragmentation during mouse cell reprogramming, demonstrate the classification power of RNA fragmentation in human ulcerative colitis, develop and validate a blood-based RNA fragmentation signature of recurrent implantation failure, and identify aging-associated RNA fragmentation in sperm, which supports RNA fragmentation as a distinct regulatory dimension beyond expression/abundance information. qMAP enables systematic exploration of the regulatory “RNA fragmentome”, providing a foundational tool for both mechanistic discovery and translational applications of noncanonical small RNAs.