Realizing the potential of full-length transcriptome sequencing

Long-read sequencing holds great potential for transcriptome analysis because it offers researchers an affordable method to annotate the transcriptomes of non-model organisms. This, in turn, will greatly benefit future work on less-researched organisms like unicellular eukaryotes that cannot rely on large consortia to generate these transcriptome annotations. However, to realize this potential, several remaining molecular and computational challenges will have to be overcome. In this review, we have outlined the limitations of short-read sequencing technology and how long-read sequencing technology overcomes these limitations. We have also highlighted the unique challenges still present for long-read sequencing technology and provided some suggestions on how to overcome these challenges going forward. This article is part of a discussion meeting issue ‘Single cell ecology’.

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Long-Read Sequencing of the Zebrafish Genome Reorganizes Genomic Architecture

10.1101/2021.08.27.457855 ◽

2021 ◽

Author(s):

Yelena Chernyavskaya ◽

Xiaofei Zhang ◽

Jinze Liu ◽

Jessica S. Blackburn

Keyword(s):

Low Complexity ◽

Zebrafish Genome ◽

Nanopore Sequencing ◽

Sequencing Technology ◽

Short Read ◽

Short Read Sequencing ◽

Genomic Landscape ◽

Long Reads ◽

Long Read ◽

Sequencing Platforms

Nanopore sequencing technology has revolutionized the field of genome biology with its ability to generate extra-long reads that can resolve regions of the genome that were previously inaccessible to short-read sequencing platforms. Although long-read sequencing has been used to resolve several vertebrate genomes, a nanopore-based zebrafish assembly has not yet been released. Over 50% of the zebrafish genome consists of difficult to map, highly repetitive, low complexity elements that pose inherent problems for short-read sequencers and assemblers. We used nanopore sequencing to improve upon and resolve the issues plaguing the current zebrafish reference assembly (GRCz11). Our long-read assembly improved the current resolution of the reference genome by identifying 1,697 novel insertions and deletions over 1Kb in length and placing 106 previously unlocalized scaffolds. We also discovered additional sites of retrotransposon integration previously unreported in GRCz11 and observed their expression in adult zebrafish under physiologic conditions, implying they have active mobility in the zebrafish genome and contribute to the ever-changing genomic landscape.

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Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1806447115 ◽

2018 ◽

Vol 115 (39) ◽

pp. 9726-9731 ◽

Cited By ~ 65

Author(s):

Roger Volden ◽

Theron Palmer ◽

Ashley Byrne ◽

Charles Cole ◽

Robert J. Schmitz ◽

...

Keyword(s):

Single Cell ◽

Full Length ◽

Long Distance ◽

Distance Information ◽

Short Read ◽

Transcript Isoforms ◽

Short Read Sequencing ◽

Sequencing Method ◽

Long Read ◽

Rna Transcript

High-throughput short-read sequencing has revolutionized how transcriptomes are quantified and annotated. However, while Illumina short-read sequencers can be used to analyze entire transcriptomes down to the level of individual splicing events with great accuracy, they fall short of analyzing how these individual events are combined into complete RNA transcript isoforms. Because of this shortfall, long-distance information is required to complement short-read sequencing to analyze transcriptomes on the level of full-length RNA transcript isoforms. While long-read sequencing technology can provide this long-distance information, there are issues with both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) long-read sequencing technologies that prevent their widespread adoption. Briefly, PacBio sequencers produce low numbers of reads with high accuracy, while ONT sequencers produce higher numbers of reads with lower accuracy. Here, we introduce and validate a long-read ONT-based sequencing method. At the same cost, our Rolling Circle Amplification to Concatemeric Consensus (R2C2) method generates more accurate reads of full-length RNA transcript isoforms than any other available long-read sequencing method. These reads can then be used to generate isoform-level transcriptomes for both genome annotation and differential expression analysis in bulk or single-cell samples.

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Highly accurate barcode and UMI error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing

10.1101/2021.01.18.427145 ◽

2021 ◽

Author(s):

Martin Philpott ◽

Jonathan Watson ◽

Anjan Thakurta ◽

Tom Brown ◽

...

Keyword(s):

Single Cell ◽

Nanopore Sequencing ◽

Short Read ◽

Short Read Sequencing ◽

Single Cell Sequencing ◽

Base Calling ◽

Novel Approach ◽

Long Read ◽

First Time ◽

Insight Into

AbstractDroplet-based single-cell sequencing techniques have provided unprecedented insight into cellular heterogeneities within tissues. However, these approaches only allow for the measurement of the distal parts of a transcript following short-read sequencing. Therefore, splicing and sequence diversity information is lost for the majority of the transcript. The application of long-read Nanopore sequencing to droplet-based methods is challenging because of the low base-calling accuracy currently associated with Nanopore sequencing. Although several approaches that use additional short-read sequencing to error-correct the barcode and UMI sequences have been developed, these techniques are limited by the requirement to sequence a library using both short- and long-read sequencing. Here we introduce a novel approach termed single-cell Barcode UMI Correction sequencing (scBUC-seq) to efficiently error-correct barcode and UMI oligonucleotide sequences synthesized by using blocks of dimeric nucleotides. The method can be applied to correct either short-read or long-read sequencing, thereby allowing users to recover more reads per cell and permits direct single-cell Nanopore sequencing for the first time. We illustrate our method by using species-mixing experiments to evaluate barcode assignment accuracy and evaluate differential isoform usage and fusion transcripts using myeloma and sarcoma cell line models.

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scCAT-seq:single-cell identification and quantification of mRNA isoforms by cost-effective short-read sequencing of cap and tail

10.1101/2019.12.11.873505 ◽

2019 ◽

Author(s):

Youjin Hu ◽

Jiawei Zhong ◽

Yuhua Xiao ◽

Zheng Xing ◽

Katherine Sheu ◽

...

Keyword(s):

Single Cell ◽

Learning Algorithm ◽

Single Cells ◽

Full Length ◽

Translation Efficiency ◽

Mrna Isoforms ◽

Short Read ◽

Short Read Sequencing ◽

Long Read ◽

Identification And Quantification

AbstractThe differences in transcription start sites (TSS) and transcription end sites (TES) among gene isoforms can affect the stability, localization, and translation efficiency of mRNA. Isoforms also allow a single gene different functions across various tissues and cells However, methods for efficient genome-wide identification and quantification of RNA isoforms in single cells are still lacking. Here, we introduce single cell Cap And Tail sequencing (scCAT-seq). In conjunction with a novel machine learning algorithm developed for TSS/TES characterization, scCAT-seq can demarcate transcript boundaries of RNA transcripts, providing an unprecedented way to identify and quantify single-cell full-length RNA isoforms based on short-read sequencing. Compared with existing long-read sequencing methods, scCAT-seq has higher efficiency with lower cost. Using scCAT-seq, we identified hundreds of previously uncharacterized full-length transcripts and thousands of alternative transcripts for known genes, quantitatively revealed cell-type specific isoforms with alternative TSSs/TESs in dorsal root ganglion (DRG) neurons, mature oocytes and ageing oocytes, and generated the first atlas of the non-human primate cornea. The approach described here can be widely adapted to other short-read or long-read methods to improve accuracy and efficiency in assessing RNA isoform dynamics among single cells.

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R2C2: Improving nanopore read accuracy enables the sequencing of highly-multiplexed full-length single-cell cDNA

10.1101/338020 ◽

2018 ◽

Cited By ~ 1

Author(s):

Roger Volden ◽

Theron Palmer ◽

Ashley Byrne ◽

Charles Cole ◽

Robert J Schmitz ◽

...

Keyword(s):

Quantitative Analysis ◽

Single Cell ◽

Cancer Biology ◽

Full Length ◽

Short Read ◽

Transcript Isoforms ◽

Short Read Sequencing ◽

Sequencing Method ◽

Long Read ◽

Rna Transcript

AbstractHigh-throughput short-read sequencing has revolutionized how transcriptomes are quantified and annotated. However, while Illumina short-read sequencers can be used to analyze entire transcriptomes down to the level of individual splicing events with great accuracy, they fall short of analyzing how these individual events are combined into complete RNA transcript isoforms. Because of this shortfall, long-read sequencing is required to complement short-read sequencing to analyze transcriptomes on the level of full-length RNA transcript isoforms. However, there are issues with both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) long-read sequencing technologies that prevent their widespread adoption. Briefly, PacBio sequencers produce low numbers of reads with high accuracy, while ONT sequencers produce higher numbers of reads with lower accuracy. Here we introduce and validate a new long-read ONT based sequencing method. At the same cost, our Rolling Circle Amplification to Concatemeric Consensus (R2C2) method generates more accurate reads of full-length RNA transcript isoforms than any other available long-read sequencing method. These reads can then be used to generate isoform-level transcriptomes for both genome annotation and differential expression analysis in bulk or single cell samples.Significance StatementSubtle changes in RNA transcript isoform expression can have dramatic effects on cellular behaviors in both health and disease. As such, comprehensive and quantitative analysis of isoform-level transcriptomes would open an entirely new window into cellular diversity in fields ranging from developmental to cancer biology. The R2C2 method we are presenting here is the first method with sufficient throughput and accuracy to make the comprehensive and quantitative analysis of RNA transcript isoforms in bulk and single cell samples economically feasible.

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Depletion of hemoglobin transcripts and long read sequencing improves the transcriptome annotation of the polar bear (Ursus maritimus)

10.1101/527978 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ashley Byrne ◽

Megan A. Supple ◽

Roger Volden ◽

Kristin L. Laidre ◽

Beth Shapiro ◽

...

Keyword(s):

Transcriptome Analysis ◽

Whole Blood ◽

Polar Bear ◽

Ursus Maritimus ◽

Full Length ◽

The Arctic ◽

Model Organisms ◽

Short Read ◽

Full Length Cdna ◽

Long Read

AbstractTranscriptome studies evaluating whole blood and tissues are often confounded by overrepresentation of highly abundant transcripts. These abundant transcripts are problematic as they compete with and prevent the detection of rare RNA transcripts, obscuring their biological importance. This issue is more pronounced when using long-read sequencing technologies for isoform-level transcriptome analysis, as they have relatively lower throughput compared to short-read sequencers. As a result long-read based transcriptome analysis is prohibitively expensive for non-model organisms. While there are off-the-shelf kits available for select model organisms capable of depleting highly abundant transcripts for alpha (HBA) and beta (HBB) hemoglobin, they are unsuitable for non-model organisms. To address this, we have adapted the recent CRISPR/Cas9 based depletion method (Depletion of Abundant Sequences by Hybridization) for long-read full-length cDNA sequencing approaches that we call Long-DASH. Using a recombinant Cas9 protein with appropriate guide RNAs, full-length hemoglobin transcripts can be depleted in-vitro prior to performing any short- and long-read sequencing library preparations. Using this method, we sequenced depleted full-length cDNA in parallel using both our Oxford Nanopore Technology (ONT) based R2C2 long-read approach, as well as the Illumina short-read based Smart-seq2 approach. To showcase this, we have applied our methods to create an isoform-level transcriptome from whole blood samples derived from three polar bears (Ursus maritimus). Using Long-DASH, we succeeded in depleting hemoglobin transcripts and generated deep Smart-seq2 Illumina datasets and 3.8 million R2C2 full-length cDNA consensus reads. Applying Long-DASH with our isoform identification pipeline, Mandalorion we discovered ~6,000 high-confidence isoforms and a number of novel genes. This indicates there is a high diversity of gene isoforms within Ursus maritimus not yet reported. This reproducible and straightforward approach has not only improved the polar bear transcriptome annotations but will serve as the foundation for future efforts to investigate transcriptional dynamics within the 19 polar bear subpopulations around the Arctic.

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A Single-Molecule Long-Read Survey of Human Transcriptomes using LoopSeq Synthetic Long Read Sequencing

10.1101/532135 ◽

2019 ◽

Cited By ~ 5

Author(s):

Indira Wu ◽

Tuval Ben-Yehezkel

Keyword(s):

Single Molecule ◽

Transcriptome Sequencing ◽

Splice Variants ◽

Error Rates ◽

Full Length ◽

Tissue Samples ◽

Short Read ◽

Short Read Sequencing ◽

Long Read ◽

Sequence Reconstruction

AbstractState-of-the-art short-read transcriptome sequencing methods employ unique molecular identifier (UMI) to accurately classify and count mRNA transcripts. A fundamental limitation of UMI-based short-read transcriptome sequencing is that each read typically covers a small fraction of the transcript sequence. Efforts to accurately characterize splicing isoforms, arguably the largest source of variation in Human gene expression, using short read sequencing have therefore largely relied on computational predictions of transcript isoforms based on indirect observations. Here we describe a transcript counting, synthetic long read method for sequencing whole transcriptomes using short read sequencing platforms and no additional hardware. The method enables full-length mRNA sequence reconstruction at single-nucleotide resolutions with high-throughput, low error rates and UMI based transcript counting using any Illumina sequencer. We describe results from whole transcriptome sequencing from total RNA extracted from 3 human tissue samples: brain, liver, and blood. Reconstructed transcript sequences are characterized and annotated using SQANTI, an analysis pipeline for assessing the sequence quality of long-read transcriptomes. Our results demonstrate that LoopSeq synthetic long-read sequencing can reconstruct contigs up to 3,900nt full-length transcripts using tissue extracted RNA, as well as identify novel splice variants of known junction donors and acceptors.

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Biosynthetic potential of uncultured Antarctic soil bacteria revealed through long-read metagenomic sequencing

The ISME Journal ◽

10.1038/s41396-021-01052-3 ◽

2021 ◽

Author(s):

Valentin Waschulin ◽

Chiara Borsetto ◽

Robert James ◽

Kevin K. Newsham ◽

Stefano Donadio ◽

...

Keyword(s):

Genome Mining ◽

Gene Clusters ◽

Biosynthetic Gene Cluster ◽

Full Length ◽

Metagenomic Sequencing ◽

Short Read ◽

Short Read Sequencing ◽

Rich Diversity ◽

Long Read ◽

The Rich

AbstractThe growing problem of antibiotic resistance has led to the exploration of uncultured bacteria as potential sources of new antimicrobials. PCR amplicon analyses and short-read sequencing studies of samples from different environments have reported evidence of high biosynthetic gene cluster (BGC) diversity in metagenomes, indicating their potential for producing novel and useful compounds. However, recovering full-length BGC sequences from uncultivated bacteria remains a challenge due to the technological restraints of short-read sequencing, thus making assessment of BGC diversity difficult. Here, long-read sequencing and genome mining were used to recover >1400 mostly full-length BGCs that demonstrate the rich diversity of BGCs from uncultivated lineages present in soil from Mars Oasis, Antarctica. A large number of highly divergent BGCs were not only found in the phyla Acidobacteriota, Verrucomicrobiota and Gemmatimonadota but also in the actinobacterial classes Acidimicrobiia and Thermoleophilia and the gammaproteobacterial order UBA7966. The latter furthermore contained a potential novel family of RiPPs. Our findings underline the biosynthetic potential of underexplored phyla as well as unexplored lineages within seemingly well-studied producer phyla. They also showcase long-read metagenomic sequencing as a promising way to access the untapped genetic reservoir of specialised metabolite gene clusters of the uncultured majority of microbes.

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Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

10.1101/2020.05.31.126490 ◽

2020 ◽

Author(s):

Andrew J. Page ◽

Nabil-Fareed Alikhan ◽

Michael Strinden ◽

Thanh Le Viet ◽

Timofey Skvortsov

Keyword(s):

Mycobacterium Tuberculosis ◽

State Of The Art ◽

Sequence Data ◽

Human Pathogen ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Long Reads ◽

Long Read

AbstractSpoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.

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Co-culture of functionally enriched cancer stem-like cells and cancer-associated fibroblasts for single-cell whole transcriptome analysis

Integrative Biology ◽

10.1093/intbio/zyz029 ◽

2019 ◽

Vol 11 (9) ◽

pp. 353-361 ◽

Cited By ~ 5

Author(s):

Yu-Chih Chen ◽

Seungwon Jung ◽

Zhixiong Zhang ◽

Max S Wicha ◽

Euisik Yoon

Keyword(s):

Breast Cancer ◽

Single Cell ◽

Transcriptome Analysis ◽

Stromal Cells ◽

Transcriptome Sequencing ◽

Functional Enrichment ◽

Cancer Associated Fibroblasts ◽

Tumor Initiation ◽

Whole Transcriptome Analysis ◽

Whole Transcriptome

Abstract Considerable evidence suggests that breast cancer development and metastasis are driven by cancer stem-like cells (CSCs). Due to their unique role in tumor initiation, the interaction between CSCs and stromal cells is especially critical. In this work, we developed a platform to reliably isolate single cells in suspension and grow single-cell-derived spheres for functional enrichment of CSCs. The platform also allows adherent culture of stromal cells for cancer-stromal interaction. As a proof of concept, we grew SUM149 breast cancer cells and successfully formed single-cell-derived spheres. Cancer-associated fibroblasts (CAFs) as stromal cells were found to significantly enhance the formation and growth of cancer spheres, indicating elevated tumor-initiation potential. After on-chip culture for 14 days, we retrieved single-cell derived spheres with and without CAF co-culture for single-cell transcriptome sequencing. Whole transcriptome analysis highlights that CAF co-culture can boost cancer stemness especially ALDHhigh CSCs and alter epithelial/mesenchymal status. Single-cell resolution allows identification of individual CSCs and investigation of cancer cellular heterogeneity. Incorporating whole transcriptome sequencing data with public patient database, we discovered novel genes associated with cancer-CAF interaction and critical to patient survival. The preliminary works demonstrated a reliable platform for enrichment of CSCs and studies of cancer-stromal interaction.

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