Quality control recommendations for RNASeq using FFPE samples based on pre-sequencing lab metrics and post-sequencing bioinformatics metrics. Quality control recommendations for RNASeq using FFPE samples based on pre-sequencing lab metrics and post-sequencing bioinformatics metrics

Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data. We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.. Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples. We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis. Overall design: A study set of 130 FFPE biopsies from women with benign breast disease along with 7 additional FFPE and Fresh Frozen replicates were prepped and sequenced using Illumina’s TruSeq RNA Exome and NEBNext rRNA Depletion protocols.

福尔马林固定石蜡包埋（Formalin-fixed, paraffin-embedded, FFPE）组织在风险生物标志物鉴定领域具备多重优势，包括样本可及性广、可支持长期随访终点研究。然而，存档FFPE样本来源的RNA质量普遍受限。本研究旨在明确可成功实现RNA提取、文库制备并获得可用RNA测序（RNA sequencing, RNAseq）数据的FFPE样本相关参数。我们利用7对FFPE与新鲜冰冻对照样本，优化了适配FFPE样本的文库制备流程；随后以130例良性乳腺疾病女性的FFPE活检样本作为研究队列，对优化后的流程进行验证。收集RNA提取与制备环节的各项指标，并与生物信息学测序汇总统计结果开展对比分析。最终构建决策树模型，以揭示测序前实验室指标与基于生物信息学指标确定的质控（Quality Control, QC）合格/不合格状态之间的关联。生物信息学质控不合格的样本，在队列内的样本间中位相关系数偏低（斯皮尔曼相关系数为4）。质控不合格样本的中位RNA浓度与捕获前文库Qubit定量值分别为18.9 ng/μl与2.08 ng/μl，显著低于质控合格样本（40.8 ng/μl与5.82 ng/μl）。我们基于输入RNA浓度与输入文库Qubit值构建决策树模型，在预测FFPE样本质控状态（合格/不合格）时的F分数达0.848。本研究针对乳腺组织FFPE样本，提出了结合生物信息学与样本指标的质控建议。结果显示，若要获取可用于下游生物信息学分析的合格RNA测序数据，用于文库制备的FFPE来源RNA最低浓度应为25 ng/μl，且捕获前文库的最低产出量应为1.7 ng/μl。总体设计：本研究共纳入130例良性乳腺疾病女性的FFPE活检样本，外加7对FFPE与新鲜冰冻对照样本，采用Illumina TruSeq RNA外显子组试剂盒与NEBNext核糖体RNA去除试剂盒完成文库制备并开展测序。