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Gene co-expression network connectivity is an important determinant of selective constraint
Umeå University, Faculty of Science and Technology, Department of Plant Physiology. Norwegian Univ Life Sci, Dept Chem Biotechnol & Food Sci, Norway.
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. Centre for Integrative Genetics, Faculty of Biosciences, Norwegian University of Life Sciences, Norway.
Umeå University, Faculty of Science and Technology, Department of Plant Physiology.
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. Swedish Univ Agr Sci, Dept Plant Biol, Uppsala, Sweden.
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2017 (English)In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 13, no 4, article id e1006402Article in journal (Refereed) Published
Abstract [en]

While several studies have investigated general properties of the genetic architecture of natural variation in gene expression, few of these have considered natural, outbreeding populations. In parallel, systems biology has established that a general feature of biological networks is that they are scale-free, rendering them buffered against random mutations. To date, few studies have attempted to examine the relationship between the selective processes acting to maintain natural variation of gene expression and the associated co-expression network structure. Here we utilised RNA-Sequencing to assay gene expression in winter buds undergoing bud flush in a natural population of Populus tremula, an outbreeding forest tree species. We performed expression Quantitative Trait Locus (eQTL) mapping and identified 164,290 significant eQTLs associating 6,241 unique genes (eGenes) with 147,419 unique SNPs (eSNPs). We found approximately four times as many local as distant eQTLs, with local eQTLs having significantly higher effect sizes. eQTLs were primarily located in regulatory regions of genes (UTRs or flanking regions), regardless of whether they were local or distant. We used the gene expression data to infer a co-expression network and investigated the relationship between network topology, the genetic architecture of gene expression and signatures of selection. Within the co-expression network, eGenes were underrepresented in network module cores (hubs) and overrepresented in the periphery of the network, with a negative correlation between eQTL effect size and network connectivity. We additionally found that module core genes have experienced stronger selective constraint on coding and non-coding sequence, with connectivity associated with signatures of selection. Our integrated genetics and genomics results suggest that purifying selection is the primary mechanism underlying the genetic architecture of natural variation in gene expression assayed in flushing leaf buds of P. tremula and that connectivity within the co-expression network is linked to the strength of purifying selection.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2017. Vol. 13, no 4, article id e1006402
National Category
Ecology
Identifiers
URN: urn:nbn:se:umu:diva-137011DOI: 10.1371/journal.pgen.1006402ISI: 000402549200001PubMedID: 28406900OAI: oai:DiVA.org:umu-137011DiVA, id: diva2:1117642
Available from: 2017-06-29 Created: 2017-06-29 Last updated: 2019-02-18Bibliographically approved
In thesis
1. Using systems genetics to explore the complexity of leaf shape variation in Populus tremula
Open this publication in new window or tab >>Using systems genetics to explore the complexity of leaf shape variation in Populus tremula
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Leaves are essential for sustaining humanity as they function as the energy and oxygen-producing organ of plants. Intensive research on physiological processes has contributed immensely to our understanding of the function of leaves. However, comparatively little is known about how leaf size and shape is determined. The aim of my PhD was to assay leaf shape variation among individuals of Populus tremula (European aspen) sampled across the distribution range of Sweden to characterize the genetic architecture underlying variation, including elucidating contributing molecular mechanisms.

In this PhD I employed an integrated systems genetics and systems biology approach to identify genetic components of variation and to assign biological function to these. We integrated population-wide data on leaf shape, gene expression and genome variation from a collection of P. tremula genotypes and used this to perform genome-wide association studies. We then integrated these results with a systems biology transcriptomics study of leaf development to provide developmental and biological context. We demonstrate that our developmental gene expression series captured known homologs of functionally characterized Arabidopsis thaliana genes and biological processes of importance during leaf development. In addition to these known genes of high importance, we also identified many novel candidate genes. Our systems genetics approach identified numerous genes with a potential role in leaf development that was supported by the developmental time series. From our association studies and population analyses we have shown that there are no large-effect loci contributing to variation in leaf shape and that highly ranked loci associated with leaf shape are primarily located in the regulatory regions of genes. Furthermore, we identified loci controlling variation in gene expression and sets of genes with significant differential expression between groups of genotypes with highly contrasting leaf shapes. We show that genes with significant associations influencing expression among genotypes are enriched in the periphery of the corresponding gene co-expression network and that they experience relaxed selective constraint. Taken together, these results suggest that leaf shape is a highly complex trait controlled by a large number of loci, each contributing only a small effect, that those loci likely act via modulation of gene expression and that they do not show signals of adaptive selection. In addition, we adapted and optimized the method of spatial transcriptomics for use in plant species. This method provides a transcriptome-wide in situ, spatially-resolved assay of transcript expression at high spatial resolution.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2019. p. 60
Keywords
Populus, Arabidopsis, systems biology, systems genetics, spatial transcriptomics (ST), single nucleotide polymorphism (SNP), Genome wide associations study (GWAS), expression GWAS (eGWAS)
National Category
Bioinformatics and Systems Biology Genetics
Research subject
Molecular Biology
Identifiers
urn:nbn:se:umu:diva-156464 (URN)978-91-7601-879-8 (ISBN)
Public defence
2019-03-14, Lilla hörsalen, KB.E3.01, KBC-huset, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2019-02-21 Created: 2019-02-18 Last updated: 2019-02-21Bibliographically approved

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Terebieniec, Barbara K.Ingvarsson, Pär K.Street, Nathaniel R.Hvidsten, Torgeir R.

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