Genomic Medicine Center, Children's Mercy Research Institute, Children's Mercy Kansas City, Kansas City, Missouri, USA; email:
Department of Biomedical Data Science, Department of Genetics, and Department of Pathology, Stanford University School of Medicine, Stanford, California, USA; email:
Annu Rev Genomics Hum Genet. 2024 Aug;25(1):353-367. doi: 10.1146/annurev-genom-021623-121812. Epub 2024 Aug 6.
RNA sequencing (RNA-seq) enables the accurate measurement of multiple transcriptomic phenotypes for modeling the impacts of disease variants. Advances in technologies, experimental protocols, and analysis strategies are rapidly expanding the application of RNA-seq to identify disease biomarkers, tissue- and cell-type-specific impacts, and the spatial localization of disease-associated mechanisms. Ongoing international efforts to construct biobank-scale transcriptomic repositories with matched genomic data across diverse population groups are further increasing the utility of RNA-seq approaches by providing large-scale normative reference resources. The availability of these resources, combined with improved computational analysis pipelines, has enabled the detection of aberrant transcriptomic phenotypes underlying rare diseases. Further expansion of these resources, across both somatic and developmental tissues, is expected to soon provide unprecedented insights to resolve disease origin, mechanism of action, and causal gene contributions, suggesting the continued high utility of RNA-seq in disease diagnosis.
RNA 测序 (RNA-seq) 可准确测量多种转录组表型，从而模拟疾病变异的影响。技术、实验方案和分析策略的进步正在迅速扩大 RNA-seq 的应用范围，以识别疾病生物标志物、组织和细胞类型特异性影响，以及与疾病相关机制的空间定位。正在进行的国际努力是构建具有不同人群基因组数据匹配的生物库规模转录组存储库，这通过提供大规模规范参考资源进一步提高了 RNA-seq 方法的实用性。这些资源的可用性，加上改进的计算分析管道，使得能够检测罕见疾病潜在的异常转录组表型。预计这些资源在躯体和发育组织中的进一步扩展，将很快提供前所未有的见解，以解决疾病起源、作用机制和因果基因贡献，这表明 RNA-seq 在疾病诊断中的持续高实用性。
