scholarly journals Transcriptome profiling of mouse samples using nanopore sequencing of cDNA and RNA molecules

2019 ◽  
Author(s):  
Camille Sessegolo ◽  
Corinne Cruaud ◽  
Corinne Da Silva ◽  
Audric Cologne ◽  
Marion Dubarry ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Transcriptome Profiling ◽  
Transcript Level ◽  
Full Length ◽  
Read Length ◽  
Rna Seq ◽  
Expression Levels ◽  
Short Reads ◽  
Rna Molecules ◽  
Oxford Nanopore

AbstractOur vision of DNA transcription and splicing has changed dramatically with the introduction of short-read sequencing. These high-throughput sequencing technologies promised to unravel the complexity of any transcriptome. Generally gene expression levels are well-captured using these technologies, but there are still remaining caveats due to the limited read length and the fact that RNA molecules had to be reverse transcribed before sequencing. Oxford Nanopore Technologies has recently launched a portable sequencer which offers the possibility of sequencing long reads and most importantly RNA molecules. Here we generated a full mouse transcriptome from brain and liver using the Oxford Nanopore device. As a comparison, we sequenced RNA (RNA-Seq) and cDNA (cDNA-Seq) molecules using both long and short reads technologies and tested the TeloPrime preparation kit, dedicated to the enrichment of full-length transcripts. Using spike-in data, we confirmed that expression levels are efficiently captured by cDNA-Seq using short reads. More importantly, Oxford Nanopore RNA-Seq tends to be more efficient, while cDNA-Seq appears to be more biased. We further show that the cDNA library preparation of the Nanopore protocol induces read truncation for transcripts containing internal runs of T’s. This bias is marked for runs of at least 15 T’s, but is already detectable for runs of at least 9 T’s and therefore concerns more than 20% of expressed transcripts in mouse brain and liver. Finally, we outline that bioinformatics challenges remain ahead for quantifying at the transcript level, especially when reads are not full-length. Accurate quantification of repeat-associated genes such as processed pseudogenes also remains difficult, and we show that current mapping protocols which map reads to the genome largely over-estimate their expression, at the expense of their parent gene. The entire dataset is available from http://www.genoscope.cns.fr/externe/ONT_mouse_RNA.

scholarly journals Transcriptome profiling of mouse samples using nanopore sequencing of cDNA and RNA molecules

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Camille Sessegolo ◽  
Corinne Cruaud ◽  
Corinne Da Silva ◽  
Audric Cologne ◽  
Marion Dubarry ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Transcriptome Profiling ◽  
Transcript Level ◽  
Full Length ◽  
Read Length ◽  
Rna Seq ◽  
Expression Levels ◽  
Short Reads ◽  
Rna Molecules ◽  
Oxford Nanopore

Abstract Our vision of DNA transcription and splicing has changed dramatically with the introduction of short-read sequencing. These high-throughput sequencing technologies promised to unravel the complexity of any transcriptome. Generally gene expression levels are well-captured using these technologies, but there are still remaining caveats due to the limited read length and the fact that RNA molecules had to be reverse transcribed before sequencing. Oxford Nanopore Technologies has recently launched a portable sequencer which offers the possibility of sequencing long reads and most importantly RNA molecules. Here we generated a full mouse transcriptome from brain and liver using the Oxford Nanopore device. As a comparison, we sequenced RNA (RNA-Seq) and cDNA (cDNA-Seq) molecules using both long and short reads technologies and tested the TeloPrime preparation kit, dedicated to the enrichment of full-length transcripts. Using spike-in data, we confirmed that expression levels are efficiently captured by cDNA-Seq using short reads. More importantly, Oxford Nanopore RNA-Seq tends to be more efficient, while cDNA-Seq appears to be more biased. We further show that the cDNA library preparation of the Nanopore protocol induces read truncation for transcripts containing internal runs of T’s. This bias is marked for runs of at least 15 T’s, but is already detectable for runs of at least 9 T’s and therefore concerns more than 20% of expressed transcripts in mouse brain and liver. Finally, we outline that bioinformatics challenges remain ahead for quantifying at the transcript level, especially when reads are not full-length. Accurate quantification of repeat-associated genes such as processed pseudogenes also remains difficult, and we show that current mapping protocols which map reads to the genome largely over-estimate their expression, at the expense of their parent gene.

scholarly journals Identification of dominant transcripts in oxidative stress response by a full-length transcriptome analysis

2020 ◽  
Author(s):  
Akihito Otsuki ◽  
Yasunobu Okamura ◽  
Yuichi Aoki ◽  
Noriko Ishida ◽  
Kazuki Kumada ◽  
...  
Keyword(s):  
Stress Response ◽  
Target Genes ◽  
Transcriptome Profiling ◽  
Transcript Level ◽  
Full Length ◽  
Rna Seq ◽  
Short Read ◽  
Expression Levels ◽  
Long Read ◽  
Electrophilic Stress

Our body responds to environmental stress by changing the expression levels of a series of cytoprotective enzymes/proteins through multilayered regulatory mechanisms, including the KEAP1-NRF2 system. While NRF2 upregulates the expression of many cytoprotective genes, there are fundamental limitations in short-read RNA sequencing (RNA-Seq), resulting in confusion regarding interpreting the effectiveness of cytoprotective gene induction at transcript level. To precisely delineate isoform usage in the stress response, we conducted independent full-length transcriptome profiling (isoform sequencing; Iso-Seq) analyses of lymphoblastoid cells from three volunteers under normal and electrophilic stress-induced conditions. We first determined the first exon usage in KEAP1 and NFE2L2 (encoding NRF2) and found the presence of transcript diversity. We then examined changes in isoform usage of NRF2 target genes under stress conditions and identified a few isoforms dominantly expressed in the majority of NRF2 target genes. The expression levels of isoforms determined by Iso-Seq analyses showed striking differences from those determined by short-read RNA-Seq; the latter could be misleading in regards to the abundance of transcripts. These results support that transcript usage is tightly regulated to produce functional proteins under electrophilic stress. Our present study strongly argues that there are important benefits that can be achieved by long-read transcriptome sequencing.

scholarly journals Baiting out a full length sequence from unmapped RNA-seq data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Dongwei Li ◽  
Qitong Huang ◽  
Lei Huang ◽  
Jikai Wen ◽  
Jing Luo ◽  
...  
Keyword(s):  
Reverse Transcription ◽  
Sanger Sequencing ◽  
High Throughput Sequencing ◽  
Full Length ◽  
Rna Seq ◽  
Power Law Distribution ◽  
Full Length Sequence ◽  
Insertion Mutations ◽  
Generation Sequencing ◽  
Unmapped Reads

Abstract Background As a powerful tool, RNA-Seq has been widely used in various studies. Usually, unmapped RNA-seq reads have been considered as useless and been trashed or ignored. Results We develop a strategy to mining the full length sequence by unmapped reads combining with specific reverse transcription primers design and high throughput sequencing. In this study, we salvage 36 unmapped reads from standard RNA-Seq data and randomly select one 149 bp read as a model. Specific reverse transcription primers are designed to amplify its both ends, followed by next generation sequencing. Then we design a statistical model based on power law distribution to estimate its integrality and significance. Further, we validate it by Sanger sequencing. The result shows that the full length is 1556 bp, with insertion mutations in microsatellite structure. Conclusion We believe this method would be a useful strategy to extract the sequences information from the unmapped RNA-seq data. Further, it is an alternative way to get the full length sequence of unknown cDNA.

ISOFORM ABUNDANCE INFERENCE PROVIDES A MORE ACCURATE ESTIMATION OF GENE EXPRESSION LEVELS IN RNA-SEQ

2010 ◽  
Vol 08 (supp01) ◽  
pp. 177-192 ◽  
Author(s):  
XI WANG ◽  
ZHENGPENG WU ◽  
XUEGONG ZHANG
Keyword(s):  
Gene Expression ◽  
High Throughput Sequencing ◽  
Transcript Abundance ◽  
Accurate Estimation ◽  
Rna Seq ◽  
Estimation Errors ◽  
Expression Levels ◽  
Or Gene ◽  
Read Distribution ◽  
Gene Expression Levels

Due to its unprecedented high-resolution and detailed information, RNA-seq technology based on next-generation high-throughput sequencing significantly boosts the ability to study transcriptomes. The estimation of genes' transcript abundance levels or gene expression levels has always been an important question in research on the transcriptional regulation and gene functions. On the basis of the concept of Reads Per Kilo-base per Million reads (RPKM), taking the union-intersection genes (UI-based) and summing up inferred isoform abundance (isoform-based) are the two current strategies to estimate gene expression levels, but produce different estimations. In this paper, we made the first attempt to compare the two strategies' performances through a series of simulation studies. Our results showed that the isoform-based method gives not only more accurate estimation but also has less uncertainty than the UI-based strategy. If taking into account the non-uniformity of read distribution, the isoform-based method can further reduce estimation errors. We applied both strategies to real RNA-seq datasets of technical replicates, and found that the isoform-based strategy also displays a better performance. For a more accurate estimation of gene expression levels from RNA-seq data, even if the abundance levels of isoforms are not of interest, it is still better to first infer the isoform abundance and sum them up to get the expression level of a gene as a whole.

Transcriptome profiling analysis of tea plant (Camellia sinensis) using Oxford Nanopore long-read RNA-Seq technology

Gene ◽  
2021 ◽  
Vol 769 ◽  
pp. 145247
Author(s):  
Fen Wang ◽  
Zhi Chen ◽  
Huimin Pei ◽  
Zhiyou Guo ◽  
Di Wen ◽  
...  
Keyword(s):  
Camellia Sinensis ◽  
Transcriptome Profiling ◽  
Tea Plant ◽  
Rna Seq ◽  
Oxford Nanopore ◽  
Long Read ◽  
Profiling Analysis

scholarly journals Transcriptome profiling for floral development in reblooming cultivar ‘High Noon’ of Paeonia suffruticosa

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yanting Chang ◽  
Tao Hu ◽  
Wenbo Zhang ◽  
Lin Zhou ◽  
Yan Wang ◽  
...  
Keyword(s):  
Flower Development ◽  
Floral Development ◽  
Developmental Stages ◽  
Transcriptome Profiling ◽  
Full Length ◽  
Rna Seq ◽  
Paeonia Suffruticosa ◽  
Tree Peony ◽  
Flower Bud ◽  
High Noon

Abstract Tree peony (Paeonia suffruticosa Andrew) is a popular ornamental plant due to its large, fragrant and colorful flowers. The floral development is the most important event in its lifecycle. To explore the mechanism that regulate flower development, we sequenced the flower bud transcriptomes of ‘High Noon’, a reblooming cultivar of P. suffruticosa × P. lutea, using both full-length isoform-sequencing (ISO-seq) and RNA-seq were sequenced. A total of 15.94 Gb raw data were generated in full-length transcriptome sequencing of the 3 floral developmental stages, resulting 0.11 M protein-coding transcripts. Over 457.0 million reads were obtained by RNA-seq in the 3 floral buds. Here, we openly released the full-length transcriptome database of ‘High Noon’ and RNA-seq database of floral development. These databases can provide a fundamental genetic information of tree peony to investigate its transcript structure, variants and evolution. Data will facilitate to deep analyses of the transcriptome for flower development.

scholarly journals RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Alessandro La Ferlita ◽  
Salvatore Alaimo ◽  
Sebastiano Di Bella ◽  
Emanuele Martorana ◽  
Georgios I. Laliotis ◽  
...  
Keyword(s):  
Data Analysis ◽  
Transcriptome Profiling ◽  
Biological Species ◽  
Third Party ◽  
Rna Seq ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Cross Platform ◽  
Cloud Environments ◽  
User Friendly

Abstract Background RNA-Seq is a well-established technology extensively used for transcriptome profiling, allowing the analysis of coding and non-coding RNA molecules. However, this technology produces a vast amount of data requiring sophisticated computational approaches for their analysis than other traditional technologies such as Real-Time PCR or microarrays, strongly discouraging non-expert users. For this reason, dozens of pipelines have been deployed for the analysis of RNA-Seq data. Although interesting, these present several limitations and their usage require a technical background, which may be uncommon in small research laboratories. Therefore, the application of these technologies in such contexts is still limited and causes a clear bottleneck in knowledge advancement. Results Motivated by these considerations, we have developed RNAdetector, a new free cross-platform and user-friendly RNA-Seq data analysis software that can be used locally or in cloud environments through an easy-to-use Graphical User Interface allowing the analysis of coding and non-coding RNAs from RNA-Seq datasets of any sequenced biological species. Conclusions RNAdetector is a new software that fills an essential gap between the needs of biomedical and research labs to process RNA-Seq data and their common lack of technical background in performing such analysis, which usually relies on outsourcing such steps to third party bioinformatics facilities or using expensive commercial software.

scholarly journals Transcriptome Profiling of Epstein-Barr Virus Using Nanopore Sequencing

2020 ◽  
Author(s):  
Norbert Moldován ◽  
Kálmán Szenthe ◽  
Ferenc Bánáti ◽  
Ádám Fülöp ◽  
Zsolt Csabai ◽  
...  
Keyword(s):  
Epstein Barr Virus ◽  
Transcriptome Profiling ◽  
Open Reading Frames ◽  
Splice Isoforms ◽  
Rna Molecules ◽  
Barr Virus ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Epstein Barr

Abstract Epstein-Barr virus (EBV) is an important human pathogenic gammaherpesvirus with carcinogenic potential. The EBV transcriptome has previously been analyzed using both Illumina-based short read- and Pacific Biosciences RS II-based long-read sequencing technologies. In this work, we use the Oxford Nanopore Technologies MinION platform for the characterization of the EBV transcriptomic architecture. Both amplified and non-amplified cDNA sequencings were applied for the generation of transcription reads, including both oligo-d(T) and random oligonucleotide-primed reverse transcription. EBV transcripts are identified and annotated using the LoRTIA software suite developed in our laboratory. This study detected novel short genes (embedded into longer host genes) containing 5’-truncated in-frame open reading frames (ORFs), which might encode N-terminally truncated proteins. We also detected a number of novel non-coding RNAs and transcript length isoforms encoded by the same genes but differing in their start and/or end sites. This study also reports the discovery of novel splice isoforms, many of which may represent altered coding potential, and of novel Ori-associated RNA molecules. Additionally, novel mono- and polycistronic, as well as complex transcripts have been uncovered. An intricate meshwork of transcriptional overlaps has also been revealed.

scholarly journals Nanopore sequencing of RNA and cDNA molecules in Escherichia coli

RNA ◽  
2021 ◽  
pp. rna.078937.121
Author(s):  
Felix Grünberger ◽  
Sébastien Ferreira-Cerca ◽  
Dina Grohmann
Keyword(s):  
Escherichia Coli ◽  
Rna Sequencing ◽  
Single Molecule ◽  
High Throughput Sequencing ◽  
Model Organism ◽  
Cost Effective ◽  
Rna Seq ◽  
Sequencing Platform ◽  
Quantitative Measurements ◽  
Oxford Nanopore

High-throughput sequencing dramatically changed our view of transcriptome architectures and allowed for ground-breaking discoveries in RNA biology. Recently, sequencing of full-length transcripts based on the single-molecule sequencing platform from Oxford Nanopore Technologies (ONT) was introduced and is widely employed to sequence eukaryotic and viral RNAs. However, experimental approaches implementing this technique for prokaryotic transcriptomes remain scarce. Here, we present an experimental and bioinformatic workflow for ONT RNA-seq in the bacterial model organism Escherichia coli, which can be applied to any microorganism. Our study highlights critical steps of library preparation and computational analysis and compares the results to gold standards in the field. Furthermore, we comprehensively evaluate the applicability and advantages of different ONT-based RNA sequencing protocols, including direct RNA, direct cDNA, and PCR-cDNA. We find that (PCR)-cDNA-seq offers improved yield and accuracy compared to direct RNA sequencing. Notably, (PCR)-cDNA-seq is suitable for quantitative measurements and can be readily used for simultaneous and accurate detection of transcript 5'and 3' boundaries, analysis of transcriptional units and transcriptional heterogeneity. In summary, based on our comprehensive study, we show that Nanopore RNA-seq to be a ready-to-use tool allowing rapid, cost-effective, and accurate annotation of multiple transcriptomic features. Thereby Nanopore RNA-seq holds the potential to become a valuable alternative method for RNA analysis in prokaryotes.

scholarly journals Direct nanopore sequencing of mRNA reveals landscape of transcript isoforms in apicomplexan parasites

2020 ◽  
Author(s):  
V Vern Lee ◽  
Louise M. Judd ◽  
Aaron R. Jex ◽  
Kathryn E. Holt ◽  
Christopher J. Tonkin ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Rna Sequencing ◽  
Intron Retention ◽  
Transcript Level ◽  
Full Length ◽  
Sequencing Platform ◽  
Apicomplexan Parasites ◽  
Oxford Nanopore ◽  
Long Read ◽  
Widespread Phenomenon

AbstractAlternative splicing is a widespread phenomenon in metazoans by which single genes are able to produce multiple isoforms of the gene product. However, this has been poorly characterised in apicomplexans, a major phylum of some of the most important global parasites. Efforts have been hampered by atypical transcriptomic features, such as the high AT content of Plasmodium RNA, but also the limitations of short read sequencing in deciphering complex splicing events. In this study, we utilised the long read direct RNA sequencing platform developed by Oxford Nanopore Technologies (ONT) to survey the alternative splicing landscape of Toxoplasma gondii and Plasmodium falciparum. We find that while native RNA sequencing has a reduced throughput, it allows us to obtain full-length or near full-length transcripts with comparable quantification to Illumina sequencing. By comparing this data with available gene models, we find widespread alternative splicing, particular intron retention, in these parasites. Most of these transcripts contain premature stop codons, suggesting that in these parasites, alternative splicing represents a pathway to transcriptomic diversity, rather than expanding proteomic diversity. Moreover, alternative splicing rates are comparable between parasites, suggesting a shared splicing machinery, despite notable transcriptomic differences between the parasites. This work highlights a strategy in using long read sequencing to understand splicing events at the whole transcript level, and has implications in future interpretation of RNA-seq studies.

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