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Transcript nuclear retention effects quantification of gene expression levels
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0001-7034-0850
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

The majority of published differential gene expression studies have used RNA isolated from whole cell extracts (total RNA), overlooking the potential impact of including the nuclear transcriptome in the analyses. It has not been firmly established that the contribution of nuclear RNA is negligible or how the inclusion of it affects quantification of gene expression. Previous studies have estimated that the nuclear transcriptome is five to ten times more complex than the cytoplasmic [1]. Hence, RNA purified solely from the cytoplasm should have fewer unique transcripts, resulting in more sequence counts per transcript and resulting in increased power to detect remaining transcripts. In this study, cytoplasmic and total mRNA have been prepared from three human cell‐lines and sequenced using massive parallel sequencing. The resulting sequence data was analyzed regarding the effect of number of biological replicates, read length and transcripts fractionation on calling differentially detected genes. In addition, the impact of length and secondary structure of mRNAs un‐translated regions (UTRs), and coding sequence length on nucleus to cytoplasm transportation rates of mRNAs was studied. We observe that the number of differentially detected genes was not significantly increased by adding more than three biological replicates or by increasing the sequence read length > 35bp. More differentially detected genes were found in the cytoplasmic RNA compared to the total RNA and a nuclear retention effect was observed for transcripts with long and structured 5’‐ and 3’‐UTR or long protein coding sequences.

Keyword [en]
RNA, RNA-Seq, transcriptome, nuclear retention
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-48039OAI: oai:DiVA.org:kth-48039DiVA: diva2:456657
Note
QS 2011Available from: 2011-11-15 Created: 2011-11-15 Last updated: 2011-11-15Bibliographically approved
In thesis
1. Enabling massive genomic and transcriptomic analysis
Open this publication in new window or tab >>Enabling massive genomic and transcriptomic analysis
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In recent years there have been tremendous advances in our ability to rapidly and cost-effectively sequence DNA. This has revolutionized the fields of genetics and biology, leading to a deeper understanding of the molecular events in life processes. The rapid advances have enormously expanded sequencing opportunities and applications, but also imposed heavy strains on steps prior to sequencing, as well as the subsequent handling and analysis of the massive amounts of sequence data that are generated, in order to exploit the full capacity of these novel platforms. The work presented in this thesis (based on six appended papers) has contributed to balancing the sequencing process by developing techniques to accelerate the rate-limiting steps prior to sequencing, facilitating sequence data analysis and applying the novel techniques to address biological questions.

 

Papers I and II describe techniques to eliminate expensive and time-consuming preparatory steps through automating library preparation procedures prior to sequencing. The automated procedures were benchmarked against standard manual procedures and were found to substantially increase throughput while maintaining high reproducibility. In Paper III, a novel algorithm for fast classification of sequences in complex datasets is described. The algorithm was first optimized and validated using a synthetic metagenome dataset and then shown to enable faster analysis of an experimental metagenome dataset than conventional long-read aligners, with similar accuracy. Paper IV, presents an investigation of the molecular effects on the p53 gene of exposing human skin to sunlight during the course of a summer holiday. There was evidence of previously accumulated persistent p53 mutations in 14% of all epidermal cells. Most of these mutations are likely to be passenger events, as the affected cell compartments showed no apparent growth advantage. An annual rate of 35,000 novel sun-induced persistent p53 mutations was estimated to occur in sun-exposed skin of a human individual.  Paper V, assesses the effect of using RNA obtained from whole cell extracts (total RNA) or cytoplasmic RNA on quantifying transcripts detected in subsequent analysis. Overall, more differentially detected genes were identified when using the cytoplasmic RNA. The major reason for this is related to the reduced complexity of cytoplasmic RNA, but also apparently due (at least partly) to the nuclear retention of transcripts with long, structured 5’- and 3’-untranslated regions or long protein coding sequences. The last paper, VI, describes whole-genome sequencing of a large, consanguineous family with a history of Leber hereditary optic neuropathy (LHON) on the maternal side. The analysis identified new candidate genes, which could be important in the aetiology of LHON. However, these candidates require further validation before any firm conclusions can be drawn regarding their contribution to the manifestation of LHON.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. 45 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 2011:24
Keyword
DNA, RNA, sequencing, massively parallel sequencing, alignment, assembly, single nucleotide polymorphism, LHON
National Category
Biological Sciences
Identifiers
urn:nbn:se:kth:diva-45957 (URN)978-91-7501-164-6 (ISBN)
Public defence
2011-12-02, Petrén‐salen, Nobels väg 12B, Karolinska Institute Campus Solna, Stockholm, 13:00 (English)
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Supervisors
Note
QC 20111115Available from: 2011-11-15 Created: 2011-11-01 Last updated: 2011-11-15Bibliographically approved

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Lundberg, Emma

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