A high-throughput method to detect RNA profiling by integration of RT-MLPA with next generation sequencing technology

// Jing Wang 1, * , Xue Yang 1, * , Haofeng Chen 2 , Xuewei Wang 1 , Xiangyu Wang 1 , Yi Fang 1 , Zhenyu Jia 3 and Jidong Gao 1 1 Department of Breast Surgical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China 2 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China 3 Department of Botany and Plant Sciences, University of California, Riverside, California, United States * These authors have contributed equally to this work Correspondence to: Jidong Gao, email: gaojidong@cicams.ac.cn Yi Fang, email: fangyi0501@vip.sina.com Zhenyu Jia, email: zhenyuj@ucr.edu Keywords: breast cancer, next generation sequencing, RNA expression, MLPA, 21-gene Received: January 17, 2017     Accepted: March 28, 2017     Published: May 02, 2017 ABSTRACT RNA in formalin-fixed and paraffin-embedded (FFPE) tissues provides large amount of information indicating disease stages, histological tumor types and grades, as well as clinical outcomes. However, Detection of RNA expression levels in formalin-fixed and paraffin-embedded samples is extremely difficult due to poor RNA quality. Here we developed a high-throughput method, Reverse Transcription-Multiple Ligation-dependent Probe Sequencing (RT-MLPSeq), to determine expression levels of multiple transcripts in FFPE samples. By combining Reverse Transcription-Multiple Ligation-dependent Amplification method and next generation sequencing technology, RT-MLPSeq overcomes the limit of probe length in multiplex ligation-dependent probe amplification assay and thus could detect expression levels of transcripts without quantitative limitations. We proved that different RT-MLPSeq probes targeting on the same transcripts have highly consistent results and the starting RNA/cDNA input could be as little as 1 ng. RT-MLPSeq also presented consistent relative RNA levels of selected 13 genes with reverse transcription quantitative PCR. Finally, we demonstrated the application of the new RT-MLPSeq method by measuring the mRNA expression levels of 21 genes which can be used for accurate calculation of the breast cancer recurrence score – an index that has been widely used for managing breast cancer patients.