Functional divergence of duplicate genes several million years after gene duplication in Arabidopsis

AbstractLineage-specifically duplicated genes likely contribute to the phenotypic divergence in closely related species. However, neither the frequency of duplication events nor the degree of selective pressures immediately after gene duplication is clear in the speciation process. Plants have substantially higher gene duplication rates than most other eukaryotes. Here, using Illumina short reads from Arabidopsis halleri, which has highly qualified plant genomes in close species (Brassica rapa, A. thaliana and A. lyrata), we succeeded in generating orthologous gene groups among B. rapa, A. thaliana, A. lyrata and A. halleri. The frequency of duplication events in the Arabidopsis lineage was approximately 10 times higher than the frequency inferred by comparative genomics of Arabidopsis, poplar, rice and moss. Of the currently retained genes in A. halleri, 11–24% had undergone gene duplication in the Arabidopsis lineage. To examine the degree of selective pressure for duplicated genes, we calculated the ratios of nonsynonymous to synonymous substitution rates (KA/KS) in the A. halleri-lyrata and A. halleri lineages. Using a maximum-likelihood framework, we examined positive (KA/KS > 1) and purifying selection (KA/KS < 1) at a significant level (P < 0.01). Duplicate genes tended to have a higher proportion of positive selection compared with non-duplicated genes. More interestingly, we found that functional divergence of duplicated genes was accelerated several million years after gene duplication at a higher proportion than immediately after gene duplication.

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Learning retention mechanisms and evolutionary parameters of duplicate genes from their expression data

10.1101/2020.06.19.162107 ◽

2020 ◽

Author(s):

Michael DeGiorgio ◽

Raquel Assis

Keyword(s):

Gene Expression ◽

Gene Duplication ◽

Statistical Learning ◽

Gene Evolution ◽

Functional Divergence ◽

Duplicate Gene ◽

Duplicate Genes ◽

Evolutionary Mechanisms ◽

Retention Mechanisms ◽

Gene Copies

AbstractLearning about the roles that duplicate genes play in the origins of novel phenotypes requires an understanding of how their functions evolve. To date, only one method—CDROM—has been developed with this goal in mind. In particular, CDROM employs gene expression distances as proxies for functional divergence, and then classifies the evolutionary mechanisms retaining duplicate genes from comparisons of these distances in a decision tree framework. However, CDROM does not account for stochastic shifts in gene expression or leverage advances in contemporary statistical learning for performing classification, nor is it capable of predicting the underlying parameters of duplicate gene evolution. Thus, here we develop CLOUD, a multi-layer neural network built upon a model of gene expression evolution that can both classify duplicate gene retention mechanisms and predict their underlying evolutionary parameters. We show that not only is the CLOUD classifier substantially more powerful and accurate than CDROM, but that it also yields accurate parameter predictions, enabling a better understanding of the specific forces driving the evolution and long-term retention of duplicate genes. Further, application of the CLOUD classifier and predictor to empirical data from Drosophila recapitulates many previous findings about gene duplication in this lineage, showing that new functions often emerge rapidly and asymmetrically in younger duplicate gene copies, and that functional divergence is driven by strong natural selection. Hence, CLOUD represents the best available method for classifying retention mechanisms and predicting evolutionary parameters of duplicate genes, thereby also highlighting the utility of incorporating sophisticated statistical learning techniques to address long-standing questions about evolution after gene duplication.

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Learning Retention Mechanisms and Evolutionary Parameters of Duplicate Genes from Their Expression Data

Molecular Biology and Evolution ◽

10.1093/molbev/msaa267 ◽

2020 ◽

Author(s):

Michael DeGiorgio ◽

Raquel Assis

Keyword(s):

Gene Expression ◽

Gene Duplication ◽

Statistical Learning ◽

Gene Evolution ◽

Functional Divergence ◽

Duplicate Gene ◽

Previous Method ◽

Duplicate Genes ◽

Evolutionary Mechanisms ◽

Retention Mechanisms

Abstract Learning about the roles that duplicate genes play in the origins of novel phenotypes requires an understanding of how their functions evolve. A previous method for achieving this goal, CDROM, employs gene expression distances as proxies for functional divergence and then classifies the evolutionary mechanisms retaining duplicate genes from comparisons of these distances in a decision tree framework. However, CDROM does not account for stochastic shifts in gene expression or leverage advances in contemporary statistical learning for performing classification, nor is it capable of predicting the parameters driving duplicate gene evolution. Thus, here we develop CLOUD, a multi-layer neural network built on a model of gene expression evolution that can both classify duplicate gene retention mechanisms and predict their underlying evolutionary parameters. We show that not only is the CLOUD classifier substantially more powerful and accurate than CDROM, but that it also yields accurate parameter predictions, enabling a better understanding of the specific forces driving the evolution and long-term retention of duplicate genes. Further, application of the CLOUD classifier and predictor to empirical data from Drosophila recapitulates many previous findings about gene duplication in this lineage, showing that new functions often emerge rapidly and asymmetrically in younger duplicate gene copies, and that functional divergence is driven by strong natural selection. Hence, CLOUD represents a major advancement in classifying retention mechanisms and predicting evolutionary parameters of duplicate genes, thereby highlighting the utility of incorporating sophisticated statistical learning techniques to address long-standing questions about evolution after gene duplication.

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In situ dissecting the evolution of gene duplication with different histone modification patterns based on high-throughput data analysis in Arabidopsis thaliana

PeerJ ◽

10.7717/peerj.10426 ◽

2021 ◽

Vol 9 ◽

pp. e10426

Author(s):

Jingjing Wang ◽

Yuriy L. Orlov ◽

Xue Li ◽

Yincong Zhou ◽

Yongjing Liu ◽

...

Keyword(s):

Arabidopsis Thaliana ◽

Gene Duplication ◽

Histone Modification ◽

Functional Divergence ◽

Genetic Regulation ◽

Sequence Divergence ◽

Single Copy ◽

Duplicate Genes ◽

Expression Divergence ◽

Sequencing Data

Background Genetic regulation is known to contribute to the divergent expression of duplicate genes; however, little is known about how epigenetic modifications regulate the expression of duplicate genes in plants. Methods The histone modification (HM) profile patterns of different modes of gene duplication, including the whole genome duplication, proximal duplication, tandem duplication and transposed duplication were characterized based on ChIP-chip or ChIP-seq datasets. In this study, 10 distinct HM marks including H2Bub, H3K4me1, H3K4me2, H3K4me3, H3K9ac, H3K9me2, H3K27me1, H3K27me3, H3K36me3 and H3K14ac were analyzed. Moreover, the features of gene duplication with different HM patterns were characterized based on 88 RNA-seq datasets of Arabidopsis thaliana. Results This study showed that duplicate genes in Arabidopsis have a more similar HM pattern than single-copy genes in both their promoters and protein-coding regions. The evolution of HM marks is found to be coupled with coding sequence divergence and expression divergence after gene duplication. We found that functionally selective constraints may impose on epigenetic evolution after gene duplication. Furthermore, duplicate genes with distinct functions have more divergence in histone modification compared with the ones with the same function, while higher expression divergence is found with mutations of chromatin modifiers. This study shows the role of epigenetic marks in regulating gene expression and functional divergence after gene duplication in plants based on sequencing data.

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Systematic evidence from gene duplication and regulation

Australian Systematic Botany ◽

10.1071/sb9900145 ◽

1990 ◽

Vol 3 (1) ◽

pp. 145

Author(s):

DJ Colgan

Keyword(s):

Gene Duplication ◽

Evolutionary History ◽

Tandem Duplication ◽

Fragment Length Polymorphism ◽

Duplicate Genes ◽

Polymorphism Analysis ◽

Multiple Origins ◽

The Family ◽

History Of ◽

Phylogenetic Hypotheses

This paper is a review of the use of information regarding the presence of duplicate genes and their regulation in systematics. The review concentrates on data derived from protein electrophoresis and restriction fragment length polymorphism analysis. The appearance of a duplication in a subset of a group of species implies that the members of the subset belong to the same clade. Suppression of the duplication may render this clade apparently paraphyletic, but may itself be informative of relations within the lineage through patterns of loss of expression in all, or some tissues, or through restrictions of the formation of functional heteropolymers in polymeric enzymes. Examples are given of studies which have used such information to establish phylogenetic hypotheses at the family level, to identify an auto- or allo-polyploid origin of polyploid species and to determine whether there have been single or multiple origins of such species. The likelihood of homoplasy in the patterns of appearance and regulation of duplicates depends on the molecular basis of the duplication. In particular, the contrast between the expected consequences of tandem duplication and the expression of pseudogenes emphasises the value of determining the mechanism of the original duplication. Many instances of sporadic gene duplication are now known, and polyploidisation is a common event in the evolutionary history of both plants and animals. So the opportunities to discover duplicationrelated characters will arise in many systematic studies. A program is presented to increase the chances that such useful information will be recognisable during the studies.

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Identification of residue inversions in large phylogenies of duplicated proteins

10.1101/2021.11.04.467263 ◽

2021 ◽

Author(s):

Stefano Pascarelli ◽

Paola Laurino

Keyword(s):

Gene Duplication ◽

Protein Sequence ◽

Protein Function ◽

High Throughput Sequencing ◽

Functional Divergence ◽

Growth Factor Receptor ◽

Sequence Evolution ◽

Protein Database ◽

Sequencing Studies ◽

Homology Relationship

Connecting protein sequence to function is becoming increasingly relevant since high-throughput sequencing studies accumulate large amounts of genomic data. Protein database annotation helps to bridge this gap; however, it is fundamental to understand the mechanisms underlying functional inheritance and divergence. If the homology relationship between proteins is known, can we determine whether the function diverged? In this work, we analyze different possibilities of protein sequence evolution after gene duplication and identify "residue inversions", i.e., sites where the relationship between the ancestry and the functional signal is decoupled. Residues in these sites play a role in functional divergence and could indicate a shift in protein function. We develop a method to recognize residue inversions in a phylogeny and test it on real and simulated datasets. In a dataset built from the Epidermal Growth Factor Receptor (EGFR) sequences found in 88 fish species, we identify 19 positions that went through inversion after gene duplication, mostly located at the ligand-binding extracellular domain.

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