A team at Nuffield Department of Orthopaedic Rheumatology and Musculoskeletal Sciences (NDORMS) has developed a new approach to significantly improve the accuracy of Ribonucleic acid (RNA) sequencing. They pinpoint the primary source of inaccurate quantification in both short and long-read RNA sequencing, and have introduced the concept of “majority vote” error correction leading to a substantial improvement in RNA molecular counting.
Accurate sequencing of genetic material is crucial in modern biology, particularly for comprehending and addressing diseases linked to genetic anomalies. However, current methodologies encounter substantial constraints. In a landmark study, an international consortium of researchers, led by Adam Cribbs, Associate Prof in Computational Biology, and Jianfeng Sun, Postdoctoral Research Associate at the Botnar Institute for Musculoskeletal Sciences (NDORMS), have developed an innovative method to correct errors in PCR amplification – a widely used technique used in high-throughput sequencing. By pinpointing PCR artefacts as the primary source of inaccurate quantification, the research, published in Nature Methods, addresses a long-standing challenge in generating accurate absolute counts of RNA molecules, which is crucial for various applications in genomics research.
The researchers focused on Unique Molecular Identifiers (UMIs), which are random oligonucleotide sequences used to remove biases introduced during PCR amplification. While UMIs have been widely adopted in sequencing methods, the study reveals that PCR errors can undermine the accuracy of molecular quantification, particularly across different sequencing platforms.
Jianfeng explained: ‘PCR amplification, essential for most RNA sequencing techniques, can introduce errors, compromising data integrity. We tackled this by synthesising UMI barcodes using homotrimer nucleotide blocks, enhancing error correction and enabling near-absolute RNA molecule quantification, markedly improving molecular counting accuracy.’