Nanopore Full-length transcriptome overviewThird-generation Sequencing
What’s new of full-length transcriptome ?Traditional 2nd generation transcriptome sequencing can only analyze the regulatory mechanism at the gene level to find the key genes related to traits. Genes can produce multiple transcripts at certain time or situation, the richness and complexity of the transcripts are the direct cause of protein diversity, which will eventually lead to a variety of phenotypes. The full-length transciptome sequencing on 3rd generation platform does not need to break mRNA randomly, the transcript can be sequenced from 5' end to 3' UTR region at once. 3rd generation full-length transcriptome sequencing can tell the complex transcription in organisms, it can reveal the real structure of sequences during transcription, such as alternative splicing, APA, fusion genes, etc.
High cost performance, high throughput, accurate quantification at transcriptome level, low efficiency of multiple alignment
No need to break sequences and gene structure, alternative splicing, fusion gene and other structural characteristics can be identified accurately
Long sequencing reads, no GC specificity amd bases bias
Identification of differential expressed genes (DEGs) and differential expressed transcripts (DETs), functional annotation analysis, in-depth exploration of the regulatory mechanism of functional genes and key pathways
Gene structure identification
Alternative splicing, non-coding RNA, gene family, evolution relationship
Genome annotation quality promotion
Novel genes, gene structure of new alternative splicesome
Practical data display
Sequencing amount is around 2 Gb~20 Gb, the N50 length is around 1500 bp, the mean sequencing length is 1~2 kb and the mean Q score is above Q10.
|Species||Sample Number||Reads Number||Base Number||N50||Average Length||Max Length||Data Quality control|
True cases of Nanopore full-length transcriptome data
Data saturation: Compared to NGS, Nanopore technology needs less data amount to cover the same amount transcripts.
Accurate quantification, low GC bias, low multiple alignment, differential expressed genes (DEG) and differential expressed transcripts (DET) can be handled at once
2 Gb Nanopore data and 6 Gb Illumina data have almost the same count of detected genes, the shared identified differential expressed genes have the same up & down-regulation relationships
|Background||Data amount||Common DEGs||Consensus up-regulated genes||Consensus down-regulated genes|
|Plant with 27,628 genes and 48,332 transcipts||2 Gb||628||174||454|
DEGs identification on ONT and Illumina platforms with the same amount of data
Transcripts number and species identification
|Species||Full-length Rate||Mapping Rate||Known Transcripts||New Transcripts||Known Genes||New Transcripts for
|New Genes||Transcripts for
Full-length transcripts identification of different species
Gene structure identification
Comparison of transcriptome data between Nanopore and Pacbio sequencing platforms
|Background: A Plant with 27,628 genes and 48,332 transcripts|
|Data amount||Identified full-length sequences||Redundant-removed transcripts||Known full-length transcripts||Novel full-length transcripts||Identified genes||Identified
|Comparison of full-length transcripts on ONT and PB platforms|
Analysis of classic cases
Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D. (Nucleic Acids Research, 2018, IF=11.561)
1 Use Nanopore to do full-length transcriptome sequencing for Saccharomyces cerevisiae
2 ~509 MB (59X) data were obtained from yeast under glucose condition. Total ~623 MB (72X) data were obtained from yeast under alcohol condition. MinION sequencing depth 64X, Illumina sequencing depth 118X. Mean coverage is very similar between the two platforms.
3 Differential expression and functional enrichment analysis show that the up-regulated genes in glucose culture were enriched to terms related to transcription and translation processes, which was consistent with the phenotype of faster growth in glucose culture. Under the condition of ethanol culture, the up-regulated genes were mainly enriched in TCA cycle, glyoxylic acid pathway and mitochondrial electron transport.
Figure 3. Summary of the direct RNA sequencing data. (A) The histogram plot shows the distribution of read length of high quality reads obtained from yeast cell growth ethanol (magenta) and glucose (cyan), respectively, with the distribution of expected transcript lengths derived fromthe ORFs annotation. (B) Bar plots of the detected highly expressed transcripts are presented as an average normalized count with standard error over four biological replicates for each growth condition. The constitutively expressed, highly expressed in ethanol growth and highly expressed in glucose growth are illustrated in the left middle and right box, respectively. (C) The bubble scatter plots show the relationship between the fraction of detected full-length transcripts by the direct RNA sequencing with the transcript length and the level transcript expression. The violin-boxplots on the right show the overall distribution of the fraction of detected full-length transcripts.
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Flow chart for Genome-guided Full-length Transcriptome Analysis Platform (GFTAP)
Easy to use
* Online graphical operation and no need to know Linux/programming language
* Tasks can be delivered in 1 minute and be delivered in anywhere with Internet
* A single flow for all intergrated analysis
* Multi-groups-analysis can be delivered in a single submission
* Reference genomes be updated weekly and personalized references are surported
Fast and efficient
* 6 samples be analyzed in 24 hours (gold account)
* 18 main analysis items were integrated in a single flow
* Both NGS and Nanopore fastq data are supported
* DEG, PCA, WGCNA and more analysis items were integrated in a single flow
* Both private and public data are supported
Friendly to personalized demands
* Personalized parameters are supported in tasks submission
* Majority (90%+) of the parameters are open after reports been generated
* Continuous updating and results can be updated after APP been updated
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