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Populus transcriptomics: from noise to biology
Umeå University, Faculty of Science and Technology, Plant Physiology.
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [sv]

Mikromatriser handlar numera inte bara om att alstra genuttrycksdata i snabb takt, utan det är minst lika viktigt att effektivt ta hand om informationen efteråt. I den här avhandlingen presenteras ett arbetsflöde för att mäta, lagra och analysera genuttrycksdata i asp och poppel (Populus spp.). En Populus} mikromatrisdatabas - UPSC--BASE - tillgänglig för alla intresserade, utvecklades i syfte att samla in och lagra genuttrycksdata. Flertalet analysverktyg gjordes samtidigt tillgängliga, för att möjliggöra ett smidigt arbetsflöde från rådata till biologiska slutsatser.

En av de stora utmaningarna i analys av mikromatriser är att kunna särskilja bruset från värdefull biologisk information. Att studera träd som växer utomhus är komplext eftersom de interagerar med omgivningen i mycket större utsträckning än vad som är fallet i växthusets kontrollerade miljö. Det här arbetet visar att det är möjligt, med hjälp av avancerad statistik och god försöksplanering, att följa och jämföra genuttrycket i blad från aspar utomhus under flera år för att dra värdefulla slutsatser om geners reglering.

Den lagrade biologiska informationen i UPSC-BASE är avsedd att vara en värdefull tillgång för växtfältet i stort. I databasen finns nästan hundra olika experiment som innefattar alltifrån unga blad till ved, insektsangrepp, kyla och torka samt studier av genmodifierade växter. Informationen kan användas både för jämförande studier inom olika aspförsök, men också för att jämföra med andra växter. För att illustrera möjligheterna, studerades och grupperades gener i blad baserat på hur de uppträder över alla dessa experiment. Dessa grupperingar användes sedan för att definiera gener som är viktiga i bladutvecklingen. Sammanfattningsvis ger arbetet som presenteras i denna avhandling tillgång till verktyg och kunskap för storskaliga studier av genuttryck och den lagrade informationen har bevisats vara en värdefull tillgång för mer ingående studier av geners reglering.

Abstract [en]

DNA microarray analysis today is not just generation of high-throughput data, much more attention is paid to the subsequent efficient handling of the generated information. In this thesis, a pipeline to generate, store and analyse Populus transcriptional data is presented A public Populus microarray database - UPSC--BASE - was developed to gather and store transcriptomic data. In addition, several tools were provided to facilitate microarray analysis without requirements for expert-level knowledge. The aim has been to streamline the workflow from raw data through to biological interpretation.

Differentiating noise from valuable biological information is one of the challenges in DNA microarray analysis. Studying gene regulation in free-growing aspen trees represents a complex analysis scenario as the trees are exposed to, and interacting with, the environment to a much higher extent than under highly controlled conditions in the greenhouse. This work shows that, by using multivariate statistics and experimental planning, it is possible to follow and compare gene expression in leaves from multiple growing seasons, and draw valuable conclusions about gene expression from field-grown samples.

The biological information in UPSC-BASE is intended to be a valuable transcriptomic resource also for the wider plant community. The database provides information from almost a hundred different experiments, spanning different developmental stages, tissue types, abiotic and biotic stresses and mutants. The information can potentially be used for both cross-experiment analysis and for comparisons against other plants, such as Arabidopsis or rice. As a demonstration of this, microarray experiments performed on Populus leaves were merged and genes preferentially expressed in leaves were organised in to regulons of co-regulated genes. Those regulons were used to define genes of importance in leaf development in Populus. Taken together, the work presented in this thesis provides tools and knowledge for large-scale transcriptional studies and the stored gene expression information has been proven to be a valuable information resource for in-depth studies about gene regulation.

Place, publisher, year, edition, pages
Umeå: Fysiologisk botanik , 2007. , 50 p.
Keyword [en]
Populus, microarray, transcriptomics, UPSC-BASE, leaf development
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:umu:diva-1423ISBN: 978-91-7264-442-7 (print)OAI: oai:DiVA.org:umu-1423DiVA: diva2:141001
Public defence
2007-11-30, Hörsal, Arbetslivsinstitutet, Umeå universitet, 10:00 (English)
Opponent
Supervisors
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2009-12-03Bibliographically approved
List of papers
1. MASQOT: a method for cDNA microarray spot quality control.
Open this publication in new window or tab >>MASQOT: a method for cDNA microarray spot quality control.
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2005 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 6, 250- p.Article in journal (Refereed) Published
Abstract [en]

Background

cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more.

Results

A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies.

Conclusion

The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process.

Keyword
Automatic Data Processing/instrumentation/methods, Data Interpretation; Statistical, Discriminant Analysis, Microarray Analysis/*instrumentation/methods, Multivariate Analysis, Oligonucleotide Array Sequence Analysis/*standards, Quality Control, ROC Curve, Software
National Category
Biological Sciences
Identifiers
urn:nbn:se:umu:diva-15817 (URN)doi:10.1186/1471-2105-6-250 (DOI)16223442 (PubMedID)
Available from: 2007-08-02 Created: 2007-08-02 Last updated: 2017-12-14
2. MASQOT-GUI: spot quality assessment for the two-channel microarray platform
Open this publication in new window or tab >>MASQOT-GUI: spot quality assessment for the two-channel microarray platform
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2006 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 22, no 20, 2554-2555 p.Article in journal (Refereed) Published
Abstract [en]

MASQOT-GUI provides an open-source, platform-independent software pipeline for two-channel microarray spot quality control. This includes gridding, segmentation, quantification, quality assessment and data visualization. It hosts a set of independent applications, with interactions between the tools as well as import and export support for external software. The implementation of automated multivariate quality control assessment, which is a unique feature of MASQOT-GUI, is based on the previously documented and evaluated MASQOT methodology. Further abilities of the application are outlined and illustrated. AVAILABILITY: MASQOT-GUI is Java-based and licensed under the GNU LGPL. Source code and installation files are available for download at http://masqot-gui.sourceforge.net/

Keyword
Computer Graphics, In Situ Hybridization; Fluorescence/instrumentation/methods/standards, Information Storage and Retrieval/*methods, Oligonucleotide Array Sequence Analysis/*instrumentation/*methods/standards, Quality Control, Software, Spectrometry; Fluorescence/instrumentation/*methods/standards, User-Computer Interface
National Category
Biological Sciences
Identifiers
urn:nbn:se:umu:diva-11102 (URN)doi:10.1093/bioinformatics/btl434 (DOI)16899490 (PubMedID)
Available from: 2007-08-09 Created: 2007-08-09 Last updated: 2017-12-14
3. Orthogonal projections to latent structures as a strategy for microarray data normalization
Open this publication in new window or tab >>Orthogonal projections to latent structures as a strategy for microarray data normalization
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2007 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 8, no 207Article in journal (Refereed) Published
Abstract [en]

Background

During generation of microarray data, various forms of systematic biases are frequently introduced which limits accuracy and precision of the results. In order to properly estimate biological effects, these biases must be identified and discarded.

Results

We introduce a normalization strategy for multi-channel microarray data based on orthogonal projections to latent structures (OPLS); a multivariate regression method. The effect of applying the normalization methodology on single-channel Affymetrix data as well as dual-channel cDNA data is illustrated. We provide a parallel comparison to a wide range of commonly employed normalization methods with diverse properties and strengths based on sensitivity and specificity from external (spike-in) controls. On the illustrated data sets, the OPLS normalization strategy exhibits leading average true negative and true positive rates in comparison to other evaluated methods.

Conclusions

The OPLS methodology identifies joint variation within biological samples to enable the removal of sources of variation that are non-correlated (orthogonal) to the within-sample variation. This ensures that structured variation related to the underlying biological samples is separated from the remaining, bias-related sources of systematic variation. As a consequence, the methodology does not require any explicit knowledge regarding the presence or characteristics of certain biases. Furthermore, there is no underlying assumption that the majority of elements should be non-differentially expressed, making it applicable to specialized boutique arrays.

National Category
Biological Sciences
Identifiers
urn:nbn:se:umu:diva-14868 (URN)doi:10.1186/1471-2105-8-207 (DOI)
Available from: 2007-08-14 Created: 2007-08-14 Last updated: 2017-12-14
4. UPSC-BASE: Populus transcriptomics online
Open this publication in new window or tab >>UPSC-BASE: Populus transcriptomics online
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2006 (English)In: The Plant Journal, ISSN 0960-7412, E-ISSN 1365-313X, Vol. 48, no 5, 806-817 p.Article in journal (Refereed) Published
Abstract [en]

The increasing accessibility and use of microarrays in transcriptomics has accentuated the need for purpose-designed storage and analysis tools. Here we present UPSC-BASE, a database for analysis and storage of Populus DNA microarray data. A microarray analysis pipeline has also been established to allow consistent and efficient analysis (from small to large scale) of samples in various experimental designs. A range of optimized experimental protocols is provided for each step in generating the data. Within UPSC-BASE, researchers can perform standard and advanced microarray analysis procedures in a user-friendly environment. Background corrections, normalizations, quality-control tools, visualizations, hypothesis tests and export tools are provided without requirements for expert-level knowledge. Although the database has been developed primarily for handling Populus DNA microarrays, most of the tools are generic and can be used for other types of microarray. UPSC-BASE is also a repository of Populus microarray information, providing data from 21 experiments on a total of 407 microarray hybridizations in the public domain of the database. There are also an additional 10 experiments containing 347 hybridizations, where the automatically analysed data are searchable.

 

Place, publisher, year, edition, pages
Oxford: Blackwell, 2006
Keyword
Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Plant, Internet, Populus/*genetics
Identifiers
urn:nbn:se:umu:diva-2741 (URN)10.1111/j.1365-313X.2006.02920.x (DOI)
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2017-12-14Bibliographically approved
5. Global expression profiling in leaves of free-growing aspen
Open this publication in new window or tab >>Global expression profiling in leaves of free-growing aspen
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2008 (English)In: BMC Plant Biology, ISSN 1471-2229, E-ISSN 1471-2229, Vol. 8, 61- p.Article in journal (Other academic) Published
Abstract [en]

Background

Genomic studies are routinely performed on young plants in controlled environments which is very different from natural conditions. In reality plants in temperate countries are exposed to large fluctuations in environmental conditions, in the case of perennials over several years. We have studied gene expression in leaves of a free-growing aspen (Populus tremula) throughout multiple growing seasons.

Results

We show that gene expression during the first month of leaf development was largely determined by a developmental program although leaf expansion, chlorophyll accumulation and the speed of progression through this program was regulated by the temperature. We were also able to define "transcriptional signatures" for four different substages of leaf development. In mature leaves, weather factors were important for gene regulation.

Conclusions

This study shows that multivariate methods together with high throughput transcriptional methods in the field can provide additional, novel information as to plant status under changing environmental conditions that is impossible to mimic in laboratory conditions. We have generated a dataset that could be used to e.g. identify marker genes for certain developmental stages or treatments, as well as to assess natural variation in gene expression.

National Category
Biological Sciences
Identifiers
urn:nbn:se:umu:diva-2742 (URN)10.1186/1471-2229-8-61 (DOI)18500984 (PubMedID)
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2017-12-14
6. A cross-species transcriptomics approach to identify genes involved in leaf development
Open this publication in new window or tab >>A cross-species transcriptomics approach to identify genes involved in leaf development
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2008 (English)In: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 9, no 1, 539- p.Article in journal (Other (popular science, discussion, etc.)) Published
Abstract [en]

Background

We have made use of publicly available gene expression data to identify transcription factors and transcriptional modules (regulons) associated with leaf development in Populus. Different tissue types were compared to identify genes informative in the discrimination of leaf and non-leaf tissues. Transcriptional modules within this set of genes were identified in a much wider set of microarray data collected from leaves in a number of developmental, biotic, abiotic and transgenic experiments.

Results

Transcription factors that were over represented in leaf EST libraries and that were useful for discriminating leaves from other tissues were identified, revealing that the C2C2-YABBY, CCAAT-HAP3 and 5, MYB, and ZF-HD families are particularly important in leaves. The expression of transcriptional modules and transcription factors was examined across a number of experiments to select those that were particularly active during the early stages of leaf development. Two transcription factors were found to collocate to previously published Quantitative Trait Loci (QTL) for leaf length. We also found that miRNA family 396 may be important in the control of leaf development, with three members of the family collocating with clusters of leaf development QTL.

Conclusion

This work provides a set of candidate genes involved in the control and processes of leaf development. This resource can be used for a wide variety of purposes such as informing the selection of candidate genes for association mapping or for the selection of targets for reverse genetics studies to further understanding of the genetic control of leaf size and shape.

National Category
Bioinformatics and Systems Biology
Identifiers
urn:nbn:se:umu:diva-2743 (URN)10.1186/1471-2164-9-589 (DOI)19061504 (PubMedID)
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2017-12-14

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