Abstract The interplay between variations in transcriptome profiles and disease progression is an important area of study emerging in cancer diagnostics. Whole-genome or targeted sequencing are conventional methods for somatic tumor assessment, but RNA sequencing has emerged as a powerful tool that can provide additional information on translation events in tumorigenesis. Transcriptome dynamics reflect cell state and can reveal key features in the evolution of disease. RNA sequencing (RNA-seq) has transformed cancer research by providing a more comprehensive view of the tumor especially in comparison to adjacent tissue allowing for advances in characterization and therapeutic options. Using streamlined RNA library preparation workflows in combination with a target enrichment approach can provide quick and cost-effective surveillance of samples, with the addition of sensitivity achieved with targeted sequencing. In this study, we compare bulk RNA-seq datasets with and without target enrichment and assess the power of each data type. They can be used in combination with other DNA based screening methods for biomarker detection in somatic tumors. RNA extracted from paired tumor and normal tissue samples were collected and prepared for Illumina sequencing using the NEBNext UltraExpress RNA Library Prep Kit. Target enrichment panels from Twist Bioscience were utilized to enrich specific transcripts and fusion-gene targets using the same Illumina libraries. Comparison of the whole transcriptome RNA-seq data with the target enrichment dataset for the same libraries reveals the strengths of each approach. The non-enriched RNA-seq library dataset provides a view of transcript levels, and can also be used to call SNVs and short structural variants, as well as splice variants and fusion genes. Target-enriched RNA-seq datasets provide more consistent depth and enhance sensitivity for low-level allele variants in targeted regions. The combination of both methods highlights the synergy between datasets in revealing well-known pathogenic mutations and gene fusions as well as rare or novel events. These sequencing methods, in combination with well validated bioinformatic pipelines, have the power to reveal genetic variations that may otherwise be omitted in more conventional detection methods. Citation Format: Chelsea Pinegar, Chen Song, Gautam Naishadham, Jian Sun, Bradley W. Langhorst, Keerthana Krishnan. RNA-seq for somatic tumor detection reveals synergy between whole transcriptome and targeted RNA library preparation methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1421.