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Genetic Interaction Network as an Important Determinant of Gene Order in Genome Evolution.

ABSTRACT: Although it is generally accepted that eukaryotic gene order is not random, the basic principles of gene arrangement on a chromosome remain poorly understood. Here, we extended existing population genetics theories that were based on two-locus models and proposed a hypothesis that genetic interaction networks drive the evolution of eukaryotic gene order. We predicted that genes with positive epistasis would move toward each other in evolution, during which a negative correlation between epistasis and gene distance formed. We tested and confirmed our prediction with computational simulations and empirical data analyses. Importantly, we demonstrated that gene order in the budding yeast could be successfully predicted from the genetic interaction network. Taken together, our study reveals the role of the genetic interaction network in the evolution of gene order, extends our understanding of the encoding principles in genomes, and potentially offers new strategies to improve synthetic biology.

SUBMITTER: Yang YF

PROVIDER: S-EPMC5850728 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Genetic Interaction Network as an Important Determinant of Gene Order in Genome Evolution.

Yang Yu-Fei YF Cao Wenqing W Wu Shaohuan S Qian Wenfeng W

Molecular biology and evolution 20171201 12

Although it is generally accepted that eukaryotic gene order is not random, the basic principles of gene arrangement on a chromosome remain poorly understood. Here, we extended existing population genetics theories that were based on two-locus models and proposed a hypothesis that genetic interaction networks drive the evolution of eukaryotic gene order. We predicted that genes with positive epistasis would move toward each other in evolution, during which a negative correlation between epistasi ...[more]

PMID: 29029158

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Project description: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.

Project description:Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom+ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod+ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom+ genes have an unexpectedly high centrality when compared with a reference distribution (P=0.008, for Eigenvalue centrality). Moreover, the frequency of Prom+ genes increases from the periphery to the center of the protein network (P=0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.

Dataset Information

Genetic Interaction Network as an Important Determinant of Gene Order in Genome Evolution.

Publications

Genetic Interaction Network as an Important Determinant of Gene Order in Genome Evolution.

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