Full-length transcriptome reconstruction reveals a large diversity of RNA and protein isoforms in rat hippocampus

Xi Wang (), Xintian You, Julian D. Langer, Jingyi Hou, Fiona Rupprecht, Irena Vlatkovic, Claudia Quedenau, Georgi Tushev, Irina Epstein, Bernhard Schaefke, Wei Sun, Liang Fang, Guipeng Li, Yuhui Hu, Erin M. Schuman and Wei Chen ()
Additional contact information
Xi Wang: Max Delbrück Center for Molecular Medicine
Xintian You: Max Delbrück Center for Molecular Medicine
Julian D. Langer: Max Planck Institute for Brain Research
Jingyi Hou: Max Delbrück Center for Molecular Medicine
Fiona Rupprecht: Max Planck Institute for Brain Research
Irena Vlatkovic: Max Planck Institute for Brain Research
Claudia Quedenau: Max Delbrück Center for Molecular Medicine
Georgi Tushev: Max Planck Institute for Brain Research
Irina Epstein: Max Planck Institute for Brain Research
Bernhard Schaefke: Southern University of Science and Technology
Wei Sun: Southern University of Science and Technology
Liang Fang: Southern University of Science and Technology
Guipeng Li: Southern University of Science and Technology
Yuhui Hu: Southern University of Science and Technology
Erin M. Schuman: Max Planck Institute for Brain Research
Wei Chen: Southern University of Science and Technology

Nature Communications, 2019, vol. 10, issue 1, 1-15

Abstract: Abstract Gene annotation is a critical resource in genomics research. Many computational approaches have been developed to assemble transcriptomes based on high-throughput short-read sequencing, however, only with limited accuracy. Here, we combine next-generation and third-generation sequencing to reconstruct a full-length transcriptome in the rat hippocampus, which is further validated using independent 5´ and 3´-end profiling approaches. In total, we detect 28,268 full-length transcripts (FLTs), covering 6,380 RefSeq genes and 849 unannotated loci. Based on these FLTs, we discover co-occurring alternative RNA processing events. Integrating with polysome profiling and ribosome footprinting data, we predict isoform-specific translational status and reconstruct an open reading frame (ORF)-eome. Notably, a high proportion of the predicted ORFs are validated by mass spectrometry-based proteomics. Moreover, we identify isoforms with subcellular localization pattern in neurons. Collectively, our data advance our knowledge of RNA and protein isoform diversity in the rat brain and provide a rich resource for functional studies.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-019-13037-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13037-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-019-13037-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().