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| Status |
Public on Oct 11, 2021 |
| Title |
Partitioning RNAs by length improves transcriptome reconstruction from short-read RNA-seq data |
| Organism |
Mus musculus |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
The accuracy of methods for assembling transcripts from short-read RNA sequencing data is limited by the lack of long-range information. Here we introduce Ladder-seq, an approach that separates transcripts according to their lengths prior to sequencing and uses the additional information to improve the quantification and assembly of transcripts. Using simulated data, we demonstrate that a kallisto algorithm extended to process Ladder-seq data quantifies transcripts of complex genes with substantially higher accuracy than conventional kallisto. For reference-based assembly, a modified StringTie2 algorithm reconstructs a single transcript with 30.8% higher precision than its conventional counterpart and is >30% more sensitive for complex genes. For de novo assembly, a modified Trinity algorithm correctly assembles 78% more transcripts than conventional Trinity, while improving precision by 78%. In experimental data, Ladder-seq reveals 40% more genes harboring isoform switches compared with conventional RNA-seq and unveils widespread changes in isoform usage upon m6A depletion by Mettl14 knock-out.
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| Overall design |
RNA sequencing of neural progenitor cells from Mettl14 wild type and conditional knock-out mice with four replicates per genotype. Prior to sequencing mRNA from each sample was separated by length into 7 distinct bands. Each band from each sample has a unique barcode.
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| Contributor(s) |
Ringeling FR, Canzar S |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
| |
| Submission date |
Oct 04, 2020 |
| Last update date |
Oct 13, 2021 |
| Contact name |
Francisca Rojas Ringeling |
| Organization name |
Ludwig Maximilian University of Munich
|
| Department |
Biochemistry
|
| Lab |
Stefan Canzar
|
| Street address |
Feodor-Lynen-Straße 25, 81377
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| City |
Munich |
| ZIP/Postal code |
81377 |
| Country |
Germany |
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| Platforms (3) |
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| Samples (19)
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| Relations |
| BioProject |
PRJNA667257 |
| SRA |
SRP286301 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE158985_ONT_cDNA_KO_flair.gtf.gz |
4.2 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_cDNA_KO_stringTie.gtf.gz |
5.9 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_cDNA_WT_flair.gtf.gz |
4.8 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_cDNA_WT_stringTie.gtf.gz |
6.2 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_native_KO_flair.gtf.gz |
2.2 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_native_KO_stringTie.gtf.gz |
2.4 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_native_WT_flair.gtf.gz |
2.3 Mb |
(ftp)(http) |
GTF |
| GSE158985_ONT_native_WT_stringTie.gtf.gz |
2.9 Mb |
(ftp)(http) |
GTF |
| GSE158985_RAW.tar |
20.6 Mb |
(http)(custom) |
TAR (of TSV) |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
| Processed data are available on Series record |
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