Attomole-level Genomics with Single-molecule Direct DNA, cDNA and RNA Sequencing Technologies

AbstractThe development of single cell RNA sequencing technologies has emerged as a powerful means of profiling the transcriptional behavior of single cells, leveraging the breadth of sequencing measurements to make inferences about cell type. However, there is still little understanding of how well these methods perform at measuring single cell variability for small sets of genes and what “transcriptome coverage” (e.g. genes detected per cell) is needed for accurate measurements. Here, we use single molecule RNA FISH measurements of 26 genes in thousands of melanoma cells to provide an independent reference dataset to assess the performance of the DropSeq and Fluidigm single cell RNA sequencing platforms. We quantified the Gini coefficient, a measure of rare-cell expression variability, and find that the correspondence between RNA FISH and single cell RNA sequencing for Gini, unlike for mean, increases markedly with per-cell library complexity up to a threshold of ∼2000 genes detected. A similar complexity threshold also allows for robust assignment of multi-genic cell states such as cell cycle phase. Our results provide guidelines for selecting sequencing depth and complexity thresholds for single cell RNA sequencing. More generally, our results suggest that if the number of genes whose expression levels are required to answer any given biological question is small, then greater transcriptome complexity per cell is likely more important than obtaining very large numbers of cells.

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Blind exploration of the unreferenced transcriptome reveals novel RNAs for prostate cancer diagnosis

10.1101/644104 ◽

2019 ◽

Author(s):

M. Pinskaya ◽

Z. Saci ◽

M. Gallopin ◽

N. H. Nguyen ◽

M. Gabriel ◽

...

Keyword(s):

Prostate Cancer ◽

Rna Sequencing ◽

Single Molecule ◽

The Cancer Genome Atlas ◽

Diagnostic Tools ◽

Bench Test ◽

Specific Expression ◽

High Coverage ◽

Sequencing Technologies ◽

Tissue Specimens

AbstractThe broad use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens is restricted by the limited power of conventional reference-based protocols relying on uniquely mapped reads and transcript annotations. Here, we implemented a blind reference-free computational protocol, DE-kupl, to directly infer RNA variations of any origin, including yet unreferenced RNAs, from high coverage total stranded RNA-sequencing datasets of tissue origin. As a bench test, this protocol was powered for detection of RNA subsequences embedded into unannotated putative long noncoding (lnc)RNAs expressed in prostate cancer tissues. Through filtering and visual inspection of 1,179 candidates, we defined 21 lncRNA probes that were further validated for robust tumor-specific expression by NanoString single molecule-based RNA measurements in 144 tissue specimens. Predictive modeling yielded a restricted probe panel enabling over 90% of true positive detection of cancer in an independent dataset from The Cancer Genome Atlas. Remarkably, this clinical signature made of only 9 unannotated lncRNAs largely outperformed PCA3, the only RNA biomarker approved by the Food and Drug Administration agency, specifically, in detection of high-risk prostate tumors. The proposed reference-free computational workflow is modular, highly sensitive and robust and can be applied to any pathology and any clinical application.

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Trans-NanoSim characterizes and simulates nanopore RNA-sequencing data

GigaScience ◽

10.1093/gigascience/giaa061 ◽

2020 ◽

Vol 9 (6) ◽

Cited By ~ 1

Author(s):

Saber Hafezqorani ◽

Chen Yang ◽

Theodora Lo ◽

Ka Ming Nip ◽

René L Warren ◽

...

Keyword(s):

Rna Sequencing ◽

Single Molecule ◽

Rapid Development ◽

Cost Effective ◽

Third Generation ◽

Sequencing Data ◽

Complementary Dna ◽

Sequencing Technologies ◽

Analytical Tools ◽

Generation Sequencing

Abstract Background Compared with second-generation sequencing technologies, third-generation single-molecule RNA sequencing has unprecedented advantages; the long reads it generates facilitate isoform-level transcript characterization. In particular, the Oxford Nanopore Technology sequencing platforms have become more popular in recent years owing to their relatively high affordability and portability compared with other third-generation sequencing technologies. To aid the development of analytical tools that leverage the power of this technology, simulated data provide a cost-effective solution with ground truth. However, a nanopore sequence simulator targeting transcriptomic data is not available yet. Findings We introduce Trans-NanoSim, a tool that simulates reads with technical and transcriptome-specific features learnt from nanopore RNA-sequncing data. We comprehensively benchmarked Trans-NanoSim on direct RNA and complementary DNA datasets describing human and mouse transcriptomes. Through comparison against other nanopore read simulators, we show the unique advantage and robustness of Trans-NanoSim in capturing the characteristics of nanopore complementary DNA and direct RNA reads. Conclusions As a cost-effective alternative to sequencing real transcriptomes, Trans-NanoSim will facilitate the rapid development of analytical tools for nanopore RNA-sequencing data. Trans-NanoSim and its pre-trained models are freely accessible at https://github.com/bcgsc/NanoSim.

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Comparative Transcriptome Profiling of Disruptive Technology, Single- Molecule Direct RNA Sequencing

Current Bioinformatics ◽

10.2174/1574893614666191017154427 ◽

2020 ◽

Vol 15 (2) ◽

pp. 165-172

Author(s):

Chaithra Pradeep ◽

Dharam Nandan ◽

Arya A. Das ◽

Dinesh Velayutham

Keyword(s):

Rna Sequencing ◽

Single Molecule ◽

Transcriptome Assembly ◽

Transcriptome Profiling ◽

Read Length ◽

Complex Nature ◽

Disruptive Technology ◽

Sequencing Technology ◽

Sequencing Technologies ◽

Long Read

Background: The standard approach for transcriptomic profiling involves high throughput short-read sequencing technology, mainly dominated by Illumina. However, the short reads have limitations in transcriptome assembly and in obtaining full-length transcripts due to the complex nature of transcriptomes with variable length and multiple alternative spliced isoforms. Recent advances in long read sequencing by the Oxford Nanopore Technologies (ONT) offered both cDNA as well as direct RNA sequencing and has brought a paradigm change in the sequencing technology to greatly improve the assembly and expression estimates. ONT enables molecules to be sequenced without fragmentation resulting in ultra-long read length enabling the entire genes and transcripts to be fully characterized. The direct RNA sequencing method, in addition, circumvents the reverse transcription and amplification steps. Objective: In this study, RNA sequencing methods were assessed by comparing data from Illumina (ILM), ONT cDNA (OCD) and ONT direct RNA (ODR). Methods: The sensitivity & specificity of the isoform detection was determined from the data generated by Illumina, ONT cDNA and ONT direct RNA sequencing technologies using Saccharomyces cerevisiae as model. Comparative studies were conducted with two pipelines to detect the isoforms, novel genes and variable gene length. Results: Mapping metrics and qualitative profiles for different pipelines are presented to understand these disruptive technologies. The variability in sequencing technology and the analysis pipeline were studied.

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Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

Molecular Biology and Evolution ◽

10.1093/molbev/msab037 ◽

2021 ◽

Cited By ~ 1

Author(s):

Chen Cao ◽

Jingni He ◽

Lauren Mak ◽

Deshan Perera ◽

Devin Kwok ◽

...

Keyword(s):

Single Molecule ◽

Human Genetics ◽

Real Data ◽

Sequencing Technologies ◽

Bacterial Genomics ◽

Physical Linkage ◽

Pooled Sequencing ◽

Computational Reconstruction ◽

Host Genetic ◽

Host Evolution

Abstract DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

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Survey of the Bradysia odoriphaga Transcriptome Using PacBio Single-Molecule Long-Read Sequencing

Genes ◽

10.3390/genes10060481 ◽

2019 ◽

Vol 10 (6) ◽

pp. 481 ◽

Cited By ~ 1

Author(s):

Chen ◽

Lin ◽

Xie ◽

Zhong ◽

Zhang ◽

...

Keyword(s):

Insecticide Resistance ◽

Single Molecule ◽

Functional Categories ◽

Genetic Studies ◽

Sequencing Technologies ◽

Clusters Of Orthologous Groups ◽

Long Read ◽

Main Gene ◽

First Time ◽

Main Factor

The damage caused by Bradysia odoriphaga is the main factor threatening the production of vegetables in the Liliaceae family. However, few genetic studies of B. odoriphaga have been conducted because of a lack of genomic resources. Many long-read sequencing technologies have been developed in the last decade; therefore, in this study, the transcriptome including all development stages of B. odoriphaga was sequenced for the first time by Pacific single-molecule long-read sequencing. Here, 39,129 isoforms were generated, and 35,645 were found to have annotation results when checked against sequences available in different databases. Overall, 18,473 isoforms were distributed in 25 various Clusters of Orthologous Groups, and 11,880 isoforms were categorized into 60 functional groups that belonged to the three main Gene Ontology classifications. Moreover, 30,610 isoforms were assigned into 44 functional categories belonging to six main Kyoto Encyclopedia of Genes and Genomes functional categories. Coding DNA sequence (CDS) prediction showed that 36,419 out of 39,129 isoforms were predicted to have CDS, and 4319 simple sequence repeats were detected in total. Finally, 266 insecticide resistance and metabolism-related isoforms were identified as candidate genes for further investigation of insecticide resistance and metabolism in B. odoriphaga.

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Hapo-G, haplotype-aware polishing of genome assemblies with accurate reads

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab034 ◽

2021 ◽

Vol 3 (2) ◽

Author(s):

Jean-Marc Aury ◽

Benjamin Istace

Keyword(s):

Single Molecule ◽

Direct Consequence ◽

High Quality ◽

Sequencing Errors ◽

Coding Regions ◽

Sequencing Technologies ◽

Long Reads ◽

Oxford Nanopore ◽

Long Read ◽

Genome Assemblies

Abstract Single-molecule sequencing technologies have recently been commercialized by Pacific Biosciences and Oxford Nanopore with the promise of sequencing long DNA fragments (kilobases to megabases order) and then, using efficient algorithms, provide high quality assemblies in terms of contiguity and completeness of repetitive regions. However, the error rate of long-read technologies is higher than that of short-read technologies. This has a direct consequence on the base quality of genome assemblies, particularly in coding regions where sequencing errors can disrupt the coding frame of genes. In the case of diploid genomes, the consensus of a given gene can be a mixture between the two haplotypes and can lead to premature stop codons. Several methods have been developed to polish genome assemblies using short reads and generally, they inspect the nucleotide one by one, and provide a correction for each nucleotide of the input assembly. As a result, these algorithms are not able to properly process diploid genomes and they typically switch from one haplotype to another. Herein we proposed Hapo-G (Haplotype-Aware Polishing Of Genomes), a new algorithm capable of incorporating phasing information from high-quality reads (short or long-reads) to polish genome assemblies and in particular assemblies of diploid and heterozygous genomes.

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Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

BMC Genomics ◽

10.1186/s12864-021-07791-z ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Ratanond Koonchanok ◽

Swapna Vidhur Daulatabad ◽

Quoseena Mir ◽

Khairi Reda ◽

Sarath Chandra Janga

Keyword(s):

Single Molecule ◽

Visual Analytics ◽

Visual Analysis ◽

Direct Sequencing ◽

Visual Exploration ◽

Nanopore Sequencing ◽

Sequencing Data ◽

Rna Sequences ◽

Sequencing Technologies ◽

Signal Features

Abstract Background Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data. Result Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization. Conclusions Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

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Single molecule real time (SMRT) full length RNA-sequencing reveals novel and distinct mRNA isoforms in human bone marrow cell subpopulations

10.1101/555326 ◽

2019 ◽

Cited By ~ 1

Author(s):

Anne Deslattes Mays ◽

Marcel O. Schmidt ◽

Garrett T. Graham ◽

Elizabeth Tseng ◽

Primo Baybayan ◽

...

Keyword(s):

Bone Marrow ◽

Real Time ◽

Rna Sequencing ◽

Single Molecule ◽

Marrow Cell ◽

Full Length ◽

Protein Isoforms ◽

Mrna Isoforms ◽

Transcript Isoforms ◽

Cell Subpopulations

AbstractHematopoietic cells are continuously replenished from progenitor cells that reside in the bone marrow. To evaluate molecular changes during this process, we analyzed the transcriptomes of freshly harvested human bone marrow progenitor (lineage-negative) and differentiated (lineage-positive) cells by single molecule, real time (SMRT) full length RNA sequencing. This analysis revealed a ∼5-fold higher number of transcript isoforms than previously detected and showed a distinct composition of individual transcript isoforms characteristic for bone marrow subpopulations. A detailed analysis of mRNA isoforms transcribed from the ANXA1 and EEF1A1 loci confirmed their distinct composition. The expression of proteins predicted from the transcriptome analysis was validated by mass spectrometry and validated previously unknown protein isoforms predicted e.g. for EEF1A1. These protein isoforms distinguished the lineage negative cell population from the lineage positive cell population. Finally, transcript isoforms expressed from paralogous gene loci (e.g. CFD, GATA2, HLA-A, B & C) also distinguished cell subpopulations but were only detectable by full length RNA sequencing. Thus, qualitatively distinct transcript isoforms from individual genomic loci separate bone marrow cell subpopulations indicating complex transcriptional regulation and protein isoform generation during hematopoiesis.

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Mapping and phasing of structural variation in patient genomes using nanopore sequencing

10.1101/129379 ◽

2017 ◽

Cited By ~ 4

Author(s):

Mircea Cretu Stancu ◽

Markus J. van Roosmalen ◽

Ivo Renkens ◽

Marleen Nieboer ◽

Sjors Middelkamp ◽

...

Keyword(s):

Single Molecule ◽

De Novo ◽

Structural Variants ◽

Human Genetic Disease ◽

Structural Genomic ◽

Short Read ◽

Sequencing Technologies ◽

Genome Wide ◽

Long Read ◽

Complex Structural

AbstractStructural genomic variants form a common type of genetic alteration underlying human genetic disease and phenotypic variation. Despite major improvements in genome sequencing technology and data analysis, the detection of structural variants still poses challenges, particularly when variants are of high complexity. Emerging long-read single-molecule sequencing technologies provide new opportunities for detection of structural variants. Here, we demonstrate sequencing of the genomes of two patients with congenital abnormalities using the ONT MinION at 11x and 16x mean coverage, respectively. We developed a bioinformatic pipeline - NanoSV - to efficiently map genomic structural variants (SVs) from the long-read data. We demonstrate that the nanopore data are superior to corresponding short-read data with regard to detection of de novo rearrangements originating from complex chromothripsis events in the patients. Additionally, genome-wide surveillance of SVs, revealed 3,253 (33%) novel variants that were missed in short-read data of the same sample, the majority of which are duplications < 200bp in size. Long sequencing reads enabled efficient phasing of genetic variations, allowing the construction of genome-wide maps of phased SVs and SNVs. We employed read-based phasing to show that all de novo chromothripsis breakpoints occurred on paternal chromosomes and we resolved the long-range structure of the chromothripsis. This work demonstrates the value of long-read sequencing for screening whole genomes of patients for complex structural variants.

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