Abstract 2232: Optimizing Performance of Whole Transcriptome RNA-Seq Reference
| العنوان: | Abstract 2232: Optimizing Performance of Whole Transcriptome RNA-Seq Reference |
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| المؤلفون: | Jessica Dickens, Rajeswari Vemula, Matthew G. Butler, Catherine Huang, Bharathi Anekella, Omoshile Clement, Yves Konigshofer |
| المصدر: | Cancer Research. 81:2232-2232 |
| بيانات النشر: | American Association for Cancer Research (AACR), 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Transcriptome, Cancer Research, Oncology, RNA-Seq, Computational biology, Biology |
| الوصف: | Purpose: Whole transcriptome RNA-sequencing (RNA-Seq) has emerged as one of the most effective methods for detection of genomic rearrangements in cancer. Enrichment for poly(A) + RNA as part of library preparation is a standard method to select for mRNAs, but ribosomal RNA depletion and exon capture methods may be preferred for samples of suboptimal RNA quality, such as FFPE. Regardless of the selection and library preparation procedure, RNA-Seq for clinical use requires well characterized reference materials for assay quality control and fusion detection verification. However, reference materials developed for targeted NGS panels performed sub-optimally on RNA-Seq. This study was undertaken to design, optimize and improve RNA-Seq performance with a novel transcriptome-scale RNA Fusion reference material. Procedure: Seraseq® Fusion RNA Mix is highly multiplexed with 18 clinically relevant fusion RNAs and is designed for targeted NGS panels. The biosynthetic fusions are targeted to 60 copies per nanogram of total RNA from GM24385 human reference cell line and contain poly-A tail of ~37 templated A's. We tested whether increasing the length of the poly-A tail would improve the efficiency of binding to an oligo dT column and improve performance in total RNA-Seq NGS assays that use poly(A) + selection. E. coli Poly(A) Polymerase was used to extend tails, and efficiency of RNA recovery from oligo-dT columns was assessed visually by gel analysis. The fusion RNAs (with standard or lengthened poly-A tails) were mixed with total RNA from GM24385 human reference cell line. Since GM24385 is a lymphoid cell line, highly abundant immune transcripts may reduce the prevalence of the fusion RNAs in the selected RNAs. Therefore, mixtures were made at the normal concentration (~60 copies/ng, or 1X) as well as at 3-fold and 10-fold concentrations. Fusion detection was performed using Illumina TruSeq Stranded mRNA(polyA) kit and Illumina HiSeq, run in 2 × 150bp mode. Results: The proportional recovery was improved with the longer (>100 A's) tail length. This translated to improvement in NGS detection with longer poly-A tail length giving from 10% to 50% more fusion reads. Increasing the Fusion RNA concentration led to a proportion increase in fusion reads per million total reads. The increase from 5 fusion reads/million resulted in more robust and consistent fusion detection. Conclusions: These studies indicate that reference materials similar to the Seraseq Fusion RNA mix reference material, but with greater concentration of Fusion RNAs (3 - 10 fold higher concentration) and with longer polyA tail length will be applicable quality control materials for whole transcriptome RNA-Seq NGS assays. These novel reference materials may aid clinical labs in developing sensitive new RNA-Seq Fusion detection assays and tuning their bioinformatics pipeline to more precise selection of therapeutic strategies for patients. Citation Format: Catherine Huang, Matthew G. Butler, Yves Konigshofer, Jessica Dickens, Rajeswari Vemula, Omoshile Clement, Bharathi Anekella. Optimizing Performance of Whole Transcriptome RNA-Seq Reference [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2232. |
| تدمد: | 1538-7445 0008-5472 |
| DOI: | 10.1158/1538-7445.am2021-2232 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::1fa964ca0c93fd9e8c9ee43c933c31ad https://doi.org/10.1158/1538-7445.am2021-2232 |
| رقم الانضمام: | edsair.doi...........1fa964ca0c93fd9e8c9ee43c933c31ad |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15387445 00085472 |
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| DOI: | 10.1158/1538-7445.am2021-2232 |