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Gene co-expression network connectivity is an important determinant of selective constraint

View ORCID ProfileNiklas Mähler, View ORCID ProfileJing Wang, Barbara K Terebieniec, View ORCID ProfilePär K Ingvarsson, View ORCID ProfileNathaniel R Street, View ORCID ProfileTorgeir R Hvidsten
doi: https://doi.org/10.1101/078188
Niklas Mähler
1Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
2Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
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Jing Wang
3Umeå Plant Science Centre, Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden
4Centre for Integrative Genetics, Faculty of Biosciences, Norwegian University of Life Sciences, Ås, Norway
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Barbara K Terebieniec
2Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
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Pär K Ingvarsson
3Umeå Plant Science Centre, Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden
5Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
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Nathaniel R Street
2Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
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  • For correspondence: nathaniel.street@umu.se
Torgeir R Hvidsten
1Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
2Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden
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Abstract

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 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, and 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.

Author summary Numerous studies have shown that many genomic polymorphisms contributing to phenotypic variation are located outside of protein coding regions, suggesting that they act by modulating gene expression. Furthermore, phenotypes are seldom explained by individual genes, but rather emerge from networks of interacting genes. The effect of regulatory variants and the interaction of genes can be described by co-expression networks, which are known to contain a small number of highly connected nodes and many more lowly connected nodes, making them robust to random mutation. While previous studies have examined the genetic architecture of gene expression variation, few were performed in natural populations with fewer still integrating the co-expression network.

We undertook a study using a natural population of European aspen (Populus tremula), showing that highly connected genes within the co-expression network had lower levels of polymorphism, had polymorphisms segregating at lower frequencies and with lower than average effect sizes, suggesting purifying selection acts on central components of the network. Furthermore, the most highly connected genes within co-expression network hubs were underrepresented for identified expression quantitative trait loci, suggesting that purifying selection on individual SNPs is driven by stabilising selecting on gene expression. In contrast, genes in the periphery of the network displayed signatures of relaxed selective constraint. Highly connected genes are therefore buffered against large expression modulation, providing a mechanistic link between selective pressures and network toplogy, which act in cohort to maintain the robustness at the population level of the co-expression network derived from flushing buds in P. tremula.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted March 29, 2017.
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Gene co-expression network connectivity is an important determinant of selective constraint
Niklas Mähler, Jing Wang, Barbara K Terebieniec, Pär K Ingvarsson, Nathaniel R Street, Torgeir R Hvidsten
bioRxiv 078188; doi: https://doi.org/10.1101/078188
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Gene co-expression network connectivity is an important determinant of selective constraint
Niklas Mähler, Jing Wang, Barbara K Terebieniec, Pär K Ingvarsson, Nathaniel R Street, Torgeir R Hvidsten
bioRxiv 078188; doi: https://doi.org/10.1101/078188

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