scholarly journals Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

2021 ◽  
Author(s):  
Angela Brooks ◽  
Francisco Pardo-Palacios ◽  
Fairlie Reese ◽  
Silvia Carbonell-Sala ◽  
Mark Diekhans ◽  
...  
Keyword(s):  
De Novo ◽  
Simulated Data ◽  
Model Organisms ◽  
Rna Seq ◽  
Sequencing Platform ◽  
Systematic Assessment ◽  
Sequencing Technologies ◽  
Long Read ◽  
Community Effort ◽  
Transcriptome Analyses

Abstract With increased usage of long-read sequencing technologies to perform transcriptome analyses, there becomes a greater need to evaluate different methodologies including library preparation, sequencing platform, and computational analysis tools. Here, we report the study design of a community effort called the Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium, whose goals are characterizing the strengths and remaining challenges in using long-read approaches to identify and quantify the transcriptomes of both model and non-model organisms. The LRGASP organizers have generated cDNA and direct RNA datasets in human, mouse, and manatee samples using different protocols followed by sequencing on Illumina, Pacific Biosciences, and Oxford Nanopore Technologies platforms. Participants will use the provided data to submit predictions for three challenges: transcript isoform detection with a high-quality genome, transcript isoform quantification, and de novo transcript isoform identification. Evaluators from different institutions will determine which pipelines have the highest accuracy for a variety of metrics using benchmarks that include spike-in synthetic transcripts, simulated data, and a set of undisclosed, manually curated transcripts by GENCODE. We also describe plans for experimental validation of predictions that are platform-specific and computational tool-specific. We believe that a community effort to evaluate long-read RNA-seq methods will help move the field toward a better consensus on the best approaches to use for transcriptome analyses.

scholarly journals The evaluation of RNA-Seq de novo assembly by PacBio long read sequencing

2019 ◽  
Author(s):  
Yifan Yang ◽  
Michael Gribskov
Keyword(s):  
Real Time ◽  
De Novo ◽  
Critical Issue ◽  
Evaluation Methods ◽  
Model Organisms ◽  
Rna Seq ◽  
Long Reads ◽  
Long Read ◽  
Set Up ◽  
Downstream Analysis

AbstractRNA-Seq de novo assembly is an important method to generate transcriptomes for non-model organisms before any downstream analysis. Given many great de novo assembly methods developed by now, one critical issue is that there is no consensus on the evaluation of de novo assembly methods yet. Therefore, to set up a benchmark for evaluating the quality of de novo assemblies is very critical. Addressing this challenge will help us deepen the insights on the properties of different de novo assemblers and their evaluation methods, and provide hints on choosing the best assembly sets as transcriptomes of non-model organisms for the further functional analysis. In this article, we generate a “real time” transcriptome using PacBio long reads as a benchmark for evaluating five de novo assemblers and two model-based de novo assembly evaluation methods. By comparing the de novo assmblies generated by RNA-Seq short reads with the “real time” transcriptome from the same biological sample, we find that Trinity is best at the completeness by generating more assemblies than the alternative assemblers, but less continuous and having more misassemblies; Oases is best at the continuity and specificity, but less complete; The performance of SOAPdenovo-Trans, Trans-AByss and IDBA-Tran are in between of five assemblers. For evaluation methods, DETONATE leverages multiple aspects of the assembly set and ranks the assembly set with an average performance as the best, meanwhile the contig score can serve as a good metric to select assemblies with high completeness, specificity, continuity but not sensitive to misassemblies; TransRate contig score is useful for removing misassemblies, yet often the assemblies in the optimal set is too few to be used as a transcriptome.

scholarly journals Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN)

2021 ◽  
Vol 17 (2) ◽  
pp. e1008716
Author(s):  
Renaud Van Damme ◽  
Martin Hölzer ◽  
Adrian Viehweger ◽  
Bettina Müller ◽  
Erik Bongcam-Rudloff ◽  
...  
Keyword(s):  
De Novo ◽  
Rna Seq ◽  
Kegg Pathways ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Metagenomic Sample ◽  
Long Read ◽  
Biogas Reactor ◽  
Functional Pathway ◽  
Workflow Orchestration

Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used for quantification and annotation by providing RNA-Seq data (optionally). We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and, if provided de novo metatranscript annotations across the metagenomic sample and for each bin. MUFFIN is available on github under GNUv3 licence: https://github.com/RVanDamme/MUFFIN.

scholarly journals The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Xueyi Dong ◽  
Luyi Tian ◽  
Quentin Gouil ◽  
Hasaru Kariyawasam ◽  
Shian Su ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Transcriptomic Analysis ◽  
Statistical Testing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Short Read ◽  
Sequencing Platform ◽  
Long Read

Abstract Application of Oxford Nanopore Technologies’ long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs (‘sequins’) as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

scholarly journals A practical guide to buildde-novoassemblies for single tissues of non-model organisms: the example of a Neotropical frog

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3702 ◽  
Author(s):  
Santiago Montero-Mendieta ◽  
Manfred Grabherr ◽  
Henrik Lantz ◽  
Ignacio De la Riva ◽  
Jennifer A. Leonard ◽  
...  
Keyword(s):  
Defense Mechanisms ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Cost Effective ◽  
Model Organisms ◽  
Rna Seq ◽  
Assembly Pipeline ◽  
Wide Variability ◽  
History Of ◽  
Inexperienced User

Whole genome sequencing (WGS) is a very valuable resource to understand the evolutionary history of poorly known species. However, in organisms with large genomes, as most amphibians, WGS is still excessively challenging and transcriptome sequencing (RNA-seq) represents a cost-effective tool to explore genome-wide variability. Non-model organisms do not usually have a reference genome and the transcriptome must be assembledde-novo. We used RNA-seq to obtain the transcriptomic profile forOreobates cruralis, a poorly known South American direct-developing frog. In total, 550,871 transcripts were assembled, corresponding to 422,999 putative genes. Of those, we identified 23,500, 37,349, 38,120 and 45,885 genes present in the Pfam, EggNOG, KEGG and GO databases, respectively. Interestingly, our results suggested that genes related to immune system and defense mechanisms are abundant in the transcriptome ofO. cruralis. We also present a pipeline to assist with pre-processing, assembling, evaluating and functionally annotating ade-novotranscriptome from RNA-seq data of non-model organisms. Our pipeline guides the inexperienced user in an intuitive way through all the necessary steps to buildde-novotranscriptome assemblies using readily available software and is freely available at:https://github.com/biomendi/TRANSCRIPTOME-ASSEMBLY-PIPELINE/wiki.

scholarly journals CStone: A de novo transcriptome assembler for short-read data that identifies non-chimeric contigs based on underlying graph structure

2021 ◽  
Vol 17 (11) ◽  
pp. e1009631
Author(s):  
Raquel Linheiro ◽  
John Archer
Keyword(s):  
De Novo ◽  
Simulated Data ◽  
Real Data ◽  
Gene Families ◽  
Classification Systems ◽  
Whole Body ◽  
Cdna Libraries ◽  
Sequence Information ◽  
Rna Seq ◽  
High Quality

With the exponential growth of sequence information stored over the last decade, including that of de novo assembled contigs from RNA-Seq experiments, quantification of chimeric sequences has become essential when assembling read data. In transcriptomics, de novo assembled chimeras can closely resemble underlying transcripts, but patterns such as those seen between co-evolving sites, or mapped read counts, become obscured. We have created a de Bruijn based de novo assembler for RNA-Seq data that utilizes a classification system to describe the complexity of underlying graphs from which contigs are created. Each contig is labelled with one of three levels, indicating whether or not ambiguous paths exist. A by-product of this is information on the range of complexity of the underlying gene families present. As a demonstration of CStones ability to assemble high-quality contigs, and to label them in this manner, both simulated and real data were used. For simulated data, ten million read pairs were generated from cDNA libraries representing four species, Drosophila melanogaster, Panthera pardus, Rattus norvegicus and Serinus canaria. These were assembled using CStone, Trinity and rnaSPAdes; the latter two being high-quality, well established, de novo assembers. For real data, two RNA-Seq datasets, each consisting of ≈30 million read pairs, representing two adult D. melanogaster whole-body samples were used. The contigs that CStone produced were comparable in quality to those of Trinity and rnaSPAdes in terms of length, sequence identity of aligned regions and the range of cDNA transcripts represented, whilst providing additional information on chimerism. Here we describe the details of CStones assembly and classification process, and propose that similar classification systems can be incorporated into other de novo assembly tools. Within a related side study, we explore the effects that chimera’s within reference sets have on the identification of differentially expression genes. CStone is available at: https://sourceforge.net/projects/cstone/.

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

2017 ◽  
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.

scholarly journals Improving the Chromosome-Level Genome Assembly of the Siamese Fighting Fish (Betta splendens) in a University Master’s Course

2020 ◽  
Vol 10 (7) ◽  
pp. 2179-2183 ◽  
Author(s):  
Stefan Prost ◽  
Malte Petersen ◽  
Martin Grethlein ◽  
Sarah Joy Hahn ◽  
Nina Kuschik-Maczollek ◽  
...  
Keyword(s):  
Genome Assembly ◽  
High Throughput Sequencing ◽  
Siamese Fighting Fish ◽  
Betta Splendens ◽  
High Quality ◽  
Sequencing Platform ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Chromosome Level

Ever decreasing costs along with advances in sequencing and library preparation technologies enable even small research groups to generate chromosome-level assemblies today. Here we report the generation of an improved chromosome-level assembly for the Siamese fighting fish (Betta splendens) that was carried out during a practical university master’s course. The Siamese fighting fish is a popular aquarium fish and an emerging model species for research on aggressive behavior. We updated the current genome assembly by generating a new long-read nanopore-based assembly with subsequent scaffolding to chromosome-level using previously published Hi-C data. The use of ∼35x nanopore-based long-read data sequenced on a MinION platform (Oxford Nanopore Technologies) allowed us to generate a baseline assembly of only 1,276 contigs with a contig N50 of 2.1 Mbp, and a total length of 441 Mbp. Scaffolding using the Hi-C data resulted in 109 scaffolds with a scaffold N50 of 20.7 Mbp. More than 99% of the assembly is comprised in 21 scaffolds. The assembly showed the presence of 96.1% complete BUSCO genes from the Actinopterygii dataset indicating a high quality of the assembly. We present an improved full chromosome-level assembly of the Siamese fighting fish generated during a university master’s course. The use of ∼35× long-read nanopore data drastically improved the baseline assembly in terms of continuity. We show that relatively in-expensive high-throughput sequencing technologies such as the long-read MinION sequencing platform can be used in educational settings allowing the students to gain practical skills in modern genomics and generate high quality results that benefit downstream research projects.

scholarly journals De novo transcriptomes of 14 gammarid individuals for proteogenomic analysis of seven taxonomic groups

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yannick Cogne ◽  
Davide Degli-Esposti ◽  
Olivier Pible ◽  
Duarte Gouveia ◽  
Adeline François ◽  
...  
Keyword(s):  
Aquatic Ecosystems ◽  
Molecular Diversity ◽  
De Novo ◽  
Model Organisms ◽  
Rna Seq ◽  
Specific Expression ◽  
Gammarus Fossarum ◽  
Male Individual ◽  
Taxonomic Groups ◽  
Whole Transcriptome

Abstract Gammarids are amphipods found worldwide distributed in fresh and marine waters. They play an important role in aquatic ecosystems and are well established sentinel species in ecotoxicology. In this study, we sequenced the transcriptomes of a male individual and a female individual for seven different taxonomic groups belonging to the two genera Gammarus and Echinogammarus: Gammarus fossarum A, G. fossarum B, G. fossarum C, Gammarus wautieri, Gammarus pulex, Echinogammarus berilloni, and Echinogammarus marinus. These taxa were chosen to explore the molecular diversity of transcribed genes of genotyped individuals from these groups. Transcriptomes were de novo assembled and annotated. High-quality assembly was confirmed by BUSCO comparison against the Arthropod dataset. The 14 RNA-Seq-derived protein sequence databases proposed here will be a significant resource for proteogenomics studies of these ecotoxicologically relevant non-model organisms. These transcriptomes represent reliable reference sequences for whole-transcriptome and proteome studies on other gammarids, for primer design to clone specific genes or monitor their specific expression, and for analyses of molecular differences between gammarid species.

scholarly journals rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data

2018 ◽  
Author(s):  
Elena Bushmanova ◽  
Dmitry Antipov ◽  
Alla Lapidus ◽  
Andrey D. Prjibelski
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
Challenging Problem ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Weak Points ◽  
Transcriptome Reconstruction ◽  
Evaluation Approaches ◽  
Genome Assembler

AbstractSummaryPossibility to generate large RNA-seq datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the model organisms with finished and annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing and paralogous genes. In this paper we describe a novel transcriptome assembler called rnaSPAdes, which is developed on top of SPAdes genome assembler and explores surprising computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-Seq datasets, and briefly highlight strong and weak points of different assemblers.Availability and implementationrnaSPAdes is implemented in C++ and Python and is freely available at cab.spbu.ru/software/rnaspades/.

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