Abstract Over the last two decades, advancements in sequencing technology and data science have significantly deepened the study of transcriptomics, especially non-coding transcriptomics, leading to substantial developments in forensic applications. During the 2000s, forensic transcriptomics analysis technology evolved from targeted messenger ribonucleic acid (mRNA) typing to massive parallel sequencing and deoxyribonucleic acid (DNA) microarray. This progression facilitated the source tracing and degradation dynamics of biomaterials from crime scenes, as well as transcriptomic changes associated with cadavers, injuries and toxicology, thereby providing additional clues for solving forensic cases. In the next decade, the development of high-throughput sequencing technology further expanded the research frontiers of forensic transcriptomics from mRNA to non-coding RNAs (ncRNAs). These molecules have been demonstrated to exhibit unique functions in expression regulation and epigenetic modifications, showing great potential in forensic practices such as forensic polymorphism studies, tissue and body fluid tracing, forensic RNA molecular clock, death & wound analyses, as well as forensic toxicology. Modern transcriptomics combined with deep learning and multimodal analysis through multidisciplinary integration can potentially characterize the dynamic spatiotemporal panoramic features of forensic biological samples. However, these technologies will face bottlenecks such as standardization, sample collection and processing, ethics, and evidence interpretation in forensic practice. Breaking through these obstacles will be the core task of forensic transcriptomics in the next ten years. This integrative review, building on bibliometric analysis, details the new paradigms and latest advances in forensic transcriptomics across multiple forensic fields, demonstrating its wide-ranging prospects in practical applications.
Lei et al. (Wed,) studied this question.