Yehezkel, T. B. | Search bioRxiv

bioRxiv2020

Targeted Transcriptome Analysis using Synthetic Long Read Sequencing Uncovers Isoform Reprograming in the Progression of Colon Cancer

Diversity in human gene expression stems, to a large extent, from splicing exons into multiple mRNA isoforms. Characterization of isoforms requires accurate long-read sequencing. However, read lengths, high error rates, low throughput and large input requirements are some of the challenges that remain to be addressed in sequencing technologies. In this study, we used a barcoding-based synthetic long read (SLR) isoform sequencing approach, LoopSeq, to generate sequencing reads sufficiently long and accurate to identify isoforms using standard short read Illumina sequencers. The method identifies isoforms from control RNA samples with 99.4% accuracy and a 0.01% per-base error rate, exceeding the accuracy reported for other long-read sequencing technologies. Applied to targeted transcriptome sequencing of over 10,000 genes from colon cancers and their metastatic counterparts, LoopSeq revealed large scale isoform redistributions from benign colon mucosa to primary colon cancer and metastatic cancer and identified several novel gene fusion isoforms in the colon cancer samples. Strikingly, our data showed that most single nucleotide variants (SNVs) occurred dominantly in specific isoforms and that some SNVs underwent isoform switching in cancer progression. The ability to use short read sequencers to generate accurate long-read isoform information as the raw unit of transcriptional information holds promise as a new and widely accessible approach in RNA isoform analyses.

genomics↗

bioRxiv2020

Ultra-accurate Microbial Amplicon Sequencing with Synthetic Long Reads

Out of the many pathogenic bacterial species that are known, only a fraction are readily identifiable directly from a complex microbial community using standard next generation DNA sequencing technology. Long-read sequencing offers the potential to identify a wider range of species and to differentiate between strains within a species, but attaining sufficient accuracy in complex metagenomes remains a challenge. Here, we describe and analytically validate LoopSeq, a commercially-available synthetic long-read (SLR) sequencing technology that generates highly-accurate long reads from standard short reads. LoopSeq reads are sufficiently long and accurate to identify microbial genes and species directly from complex samples. LoopSeq applied to full-length 16S rRNA genes from known strains in a microbial community perfectly recovered the full diversity of full-length exact sequence variants in a known microbial community. Full-length LoopSeq reads had a per-base error rate of 0.005%, which exceeds the accuracy reported for other long-read sequencing technologies. 18S-ITS and genomic sequencing of fungal and bacterial isolates confirmed that LoopSeq sequencing maintains that accuracy for reads up to 6 kilobases in length. Analysis of rinsate from retail meat samples demonstrated that LoopSeq full-length 16S rRNA synthetic long-reads could accurately classify organisms down to the species level, and could differentiate between different strains within species identified by the CDC as potential foodborne pathogens. The order-of-magnitude improvement in both length and accuracy over standard Illumina amplicon sequencing achieved with LoopSeq enables accurate species-level and strain identification from complex and low-biomass microbiome samples. The ability to generate accurate and long microbiome sequencing reads using standard short read sequencers will accelerate the building of quality microbial sequence databases and removes a significant hurdle on the path to precision microbial genomics.Competing Interest StatementMichael Balamotis and Tuval Ben Yehezkel are employees of Loop Genomics, the vendor for the synthetic long-read sequencing technology analyzed in this manuscript.View Full Text

microbiology↗