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Scalable Transcriptome Preparation for Massive Parallel Sequencing
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Gene Technology.
KTH, School of Biotechnology (BIO), Gene Technology.ORCID iD: 0000-0003-4313-1601
2011 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 6, no 7, e21910- p.Article in journal (Refereed) Published
Abstract [en]

Background: The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity. Methodology: In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation. Conclusion/Significance: The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods.

Place, publisher, year, edition, pages
2011. Vol. 6, no 7, e21910- p.
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-37159DOI: 10.1371/journal.pone.0021910ISI: 000292655400026Scopus ID: 2-s2.0-79960041380OAI: oai:DiVA.org:kth-37159DiVA: diva2:432390
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note
QC 20110803Available from: 2011-08-03 Created: 2011-08-02 Last updated: 2017-12-08Bibliographically 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)
Opponent
Supervisors
Note
QC 20111115Available from: 2011-11-15 Created: 2011-11-01 Last updated: 2011-11-15Bibliographically approved
2. Interpreting the human transcriptome
Open this publication in new window or tab >>Interpreting the human transcriptome
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The human body is made of billions of cells and nearly all have the same genome. However, there is a high diversity of cells, resulted from what part of the genome the cells use, i.e. which RNA molecules are expressed. Rapid advances within the field of sequencing allow us to determine the RNA molecules expressed in a specific cell at a certain time. The use of the new technologies has expanded our view of the human transcriptome and increased our understanding of when, where, and how each RNA molecule is expressed.

The work presented in this thesis focuses on analysis of the human transcriptome. In Paper I, we describe an automated approach for sample preparation. This protocol was compared with the standard manual protocol, and we demonstrated that the automated version outperformed the manual process in terms of sample throughput while maintaining high reproducibility. Paper II addresses the impact of nuclear transcripts on gene expression. We compared total RNA from whole cells and from cytoplasm, showing that transcripts with long, structured 3’- and 5’-untranslated regions and transcripts with long protein coding sequences tended to be retained in the nucleus. This resulted in increased complexity of the total RNA fraction and fewer reads per unique transcript. Papers III and IV describe dynamics of the human muscle transcriptome. For Paper III, we systematically investigated the transcriptome and found remarkably high tissue homogeneity, however a large number of genes and isoforms were differentially expressed between genders. Paper IV describes transcriptome differences in response to repeated training. No transcriptome-based memory was observed, however a large number of isoforms and genes were affected by training. Paper V describes a transcript profiling protocol based on the method Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification. We designed the method for a few selected transcripts whose expression patterns are important for detecting breast cancer cells, and optimized the method for single cell analysis. We successfully detected cells in human blood samples and applied the method to single cells, confirming the heterogeneity of a cell population.

Abstract [sv]

Människokroppen är uppbyggd av miljarder celler och nästan alla innehåller samma arvsmassa. Trots detta finns det många olika celler med olika funktioner vilket är en följd av vilken del av arvsmassan som cellerna använder, dvs vilka RNA-molekyler som finns i varje cell. Den snabba utvecklingen av sekvenseringstekniker har gjort det möjligt att studera när, var och hur varje RNA-molekyl är uttryckt och att få en djupare förståelse för hur människans celler fungerar.

Arbetet som presenteras i denna avhandling fokuserar på analys av RNA-molekyler i människans celler. I artikel I beskriver vi en automatiserad metod för att förbereda cellprov för RNA-sekvensering. Det automatiserade protokollet jämfördes med det manuella protokollet, och vi visade att det automatiserade protokollet överträffade det manuella när det gällde provkapacitet samtidigt som en höga reproducerbarheten behölls. I artikel II undersökte vi effekterna som RNA-molekyler från en del av cellen (cellkärnan) har på den totala mängden uttryckta RNA-molekyler. Vi jämförde RNA från hela cellen och från en del av cellen (cytoplasman) och visade att RNA-molekyler med långa och strukturerade 3'- och 5'-otranslaterade regioner och RNA-molekyler med långa proteinkodande sekvenser tenderade att hållas kvar i cellkärnan till en högre grad. Detta resulterade i en ökad komplexitet av RNA-molekylerna i hela cellen, medan vi i cytoplasma-fraktionen lättare kunde hitta de korta och svagt uttryckta RNA-molekyler. I Artikel III och IV studerar vi RNA-molekyler i människans skelettmuskler. I artikel III visar vi att andelen RNA-molekyler uttryckta i skelettmuskler är väldigt lika mellan muskler och mellan olika personer, men att ett stort antal RNA-molekyler var uttryckta i olika nivåer hos kvinnor och män. Artikel IV beskriver RNA-nivåer som svar på upprepade perioder av uthållighetsträning. Artikel V beskriver en metod för att studera ett fåtal utvalda RNA-molekyler. Vi valde RNA-molekyler vars uttryck är viktigt vid analys av bröstcancerceller, och optimerade metoden för analys av enskilda celler. Vi analyserade cancerceller från blodprov och använde metoden för att titta på RNA-nivåer i enskilda celler från en grupp av celler och visade på skillnader i RNA-nivåer inom gruppen.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. 52 p.
Series
TRITA-BIO-Report, ISSN 1654-2312 ; 2015:1
Keyword
Transcriptome, RNA sequencing, high-throughput sequencing, gene expression profiling, multiplex amplification
National Category
Cell and Molecular Biology
Research subject
Biotechnology
Identifiers
urn:nbn:se:kth:diva-158320 (URN)978-91-7595-413-4 (ISBN)
Public defence
2015-02-06, Air & Fire, Science for Life laboratory, Tomtebodavägen 23A, Solna, 10:29 (English)
Opponent
Supervisors
Funder
Swedish Research CouncilSwedish Cancer SocietyEU, FP7, Seventh Framework Programme, FP7‐ICT‐257743
Note

QC 20150115

Available from: 2015-01-15 Created: 2015-01-07 Last updated: 2015-01-15Bibliographically approved

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