TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting

Hindrek Teder,Mariann Koel,Viktorija Kukuškina,Tatjana Jatsenko,Kaarel Krjutškov,Agne Velthut-Meikas,Andres Salumets,Kadri Rekker,Olga Fjodorova,Priit Palta,Maire Peters,Triin Laisk-Podar,Priit Paluoja,Juha Kere

doi:10.1038/s41525-018-0072-5

Abstract

Targeted next-generation sequencing (NGS) methods have become essential in medical research and diagnostics. In addition to NGS sensitivity and high-throughput capacity, precise biomolecule counting based on unique molecular identifier (UMI) has potential to increase biomolecule detection accuracy. Although UMIs are widely used in basic research its introduction to clinical assays is still in progress. Here, we present a robust and cost-effective TAC-seq (Targeted Allele Counting by sequencing) method that uses UMIs to estimate the original molecule counts of mRNAs, microRNAs, and cell-free DNA. We applied TAC-seq in three different clinical applications and compared the results with standard NGS. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX, +21) genomic DNA. TAC-seq mRNA profiling showed identical clustering results to transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard NGS. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant (p = 7.6 × 10−4) excess of chromosome 21 molecules at 10% fetal fraction level. Based on three proof-of-principle applications we demonstrate that TAC-seq is an accurate and highly potential biomarker profiling method for advanced medical research and diagnostics.

Highlights

Physiological and pathophysiological disease conditions can be often characterized by the precise quantification of specific nucleic acid biomarkers
These results suggested that conservative unique molecular identifier (UMI) thresholds (n ≥ 3 molecules required in this case, Fig. 1c) are justified and applicable for high-coverage sequencing, in which the unfiltered read numbers are significantly higher than the UMI corrected outcome.[18]
TAC-seq is an advanced ligation-based next-generation sequencing (NGS) method that differs from existing ligation-PCR assays such as MLPA6, MLPA-seq[5], TempO-Seq[4], RASL-seq[7] and DANSR.[8]

Summary

INTRODUCTION

Physiological and pathophysiological disease conditions can be often characterized by the precise quantification of specific nucleic acid biomarkers. (Templated Oligo assay with Sequencing readout) and MLPAseq[5] are advancement of the well-known MLPA6 (Multiplex Ligation-dependent Probe Amplification) Both methods overcome original MLPA multiplexing and detection limitations, and enable to apply sensitivity of NGS and analyze up to 20,000 RNA and 200 genomic DNA (gDNA) targets, respectively. Principal component analysis of these data showed identical clustering of samples when applied to RNAseq results and two different TAC-seq assays, carried out with high- (denoted as TAC-seqhigh, average 25.7 × 106 reads per sample) and low-coverage (TAC-seqlow, average 1.23 × 106 reads per sample) sequencing (Fig. 2a) In these analyses, the first component described most of the sample variability The same sample grouping was confirmed by hierarchical clustering: four pre-receptive samples clustered

RESULTS

Teder et al 3

DISCUSSION

METHODS

Findings

Code availability