Gene Duplication Models Research Articles

AleRax: a tool for gene and species tree co-estimation and reconciliation under a probabilistic model of gene duplication, transfer, and loss.

Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree. We present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as duplication, transfer, and loss probabilities for genome-scale datasets with hundreds of taxa. GNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz.

Expression attenuation as a mechanism of robustness against gene duplication

Gene duplication is ubiquitous and a major driver of phenotypic diversity across the tree of life, but its immediate consequences are not fully understood. Deleterious effects would decrease the probability of retention of duplicates and prevent their contribution to long-term evolution. One possible detrimental effect of duplication is the perturbation of the stoichiometry of protein complexes. Here, we measured the fitness effects of the duplication of 899 essential genes in the budding yeast using high-resolution competition assays. At least 10% of genes caused a fitness disadvantage when duplicated. Intriguingly, the duplication of most protein complex subunits had small to nondetectable effects on fitness, with few exceptions. We selected four complexes with subunits that had an impact on fitness when duplicated and measured the impact of individual gene duplications on their protein-protein interactions. We found that very few duplications affect both fitness and interactions. Furthermore, large complexes such as the 26S proteasome are protected from gene duplication by attenuation of protein abundance. Regulatory mechanisms that maintain the stoichiometric balance of protein complexes may protect from the immediate effects of gene duplication. Our results show that a better understanding of protein regulation and assembly in complexes is required for the refinement of current models of gene duplication.

The Effects of Gene Duplication Modes on the Evolution of Regulatory Divergence in Wild and Cultivated Soybean.

Regulatory changes include divergence in both cis-elements and trans-factors, which play roles in organismal evolution. Whole genome duplications (WGD) followed by diploidization are a recurrent feature in the evolutionary history of angiosperms. Prior studies have shown that duplicated genes have different evolutionary fates due to variable selection constraints and results in genomic compositions with hallmarks of paleopolyploidy. The recent sequential WGDs and post-WGD evolution in the common ancestor of cultivated soybean (Glycine max) and wild soybean (Glycine soja), together with other models of gene duplication, have resulted in a highly duplicated genome. In this study, we investigated the transcriptional changes in G. soja and G. max. We identified a sizable proportion of interspecific differentially expressed genes (DEGs) and found parental expression level dominance of G. max in their F1 hybrids. By classifying genes into different regulatory divergence types, we found the trans-regulatory changes played a predominant role in transcriptional divergence between wild and cultivated soybean. The same gene ontology (GO) and protein family (Pfam) terms were found to be over-represented in DEGs and genes of cis-only between JY47 and GS, suggesting the substantial contribution of cis-regulatory divergences to the evolution of wild and cultivated soybeans. By further dissecting genes into five different duplication modes, we found genes in different duplication modes tend to accumulate different types of regulatory differences. A relatively higher proportion of cis-only regulatory divergences was detected in singleton, dispersed, proximal, and tandem duplicates than WGD duplicates and genome-wide level, which is in line with the prediction of gene balance hypothesis for the differential fates of duplicated genes post-WGD. The numbers of cis-only and trans-only regulated genes were similar for singletons, whereas there were more genes of trans-only than cis-only in the rest duplication types, especially in WGD in which there were two times more trans-only genes than that in cis-only type. Tandem duplicates showed the highest proportion of trans-only genes probably due to some special features of this class. In summary, our results demonstrate that genes in different duplication modes have different fates in transcriptional evolution underpinned by cis- or trans-regulatory divergences in soybean and likely in other paleopolyploid higher organisms.

FastMulRFS: fast and accurate species tree estimation under generic gene duplication and loss models.

MotivationSpecies tree estimation is a basic part of biological research but can be challenging because of gene duplication and loss (GDL), which results in genes that can appear more than once in a given genome. All common approaches in phylogenomic studies either reduce available data or are error-prone, and thus, scalable methods that do not discard data and have high accuracy on large heterogeneous datasets are needed.ResultsWe present FastMulRFS, a polynomial-time method for estimating species trees without knowledge of orthology. We prove that FastMulRFS is statistically consistent under a generic model of GDL when adversarial GDL does not occur. Our extensive simulation study shows that FastMulRFS matches the accuracy of MulRF (which tries to solve the same optimization problem) and has better accuracy than prior methods, including ASTRAL-multi (the only method to date that has been proven statistically consistent under GDL), while being much faster than both methods.Availability and impementationFastMulRFS is available on Github (https://github.com/ekmolloy/fastmulrfs).Supplementary information Supplementary data are available at Bioinformatics online.

Duplications in Corneous Beta Protein Genes and the Evolution of Gecko Adhesion.

Corneous proteins are an important component of the tetrapod integument. Duplication and diversification of keratins and associated proteins are linked with the origin of most novel integumentary structures like mammalian hair, avian feathers, and scutes covering turtle shells. Accordingly, the loss of integumentary structures often coincides with the loss of genes encoding keratin and associated proteins. For example, many hair keratins in dolphins and whales have become pseudogenes. The adhesive setae of geckos and anoles are composed of both intermediate filament keratins (IF-keratins, formerly known as alpha-keratins) and corneous beta-proteins (CBPs, formerly known as beta-keratins) and recent whole genome assemblies of two gecko species and an anole uncovered duplications in seta-specific CBPs in each of these lineages. While anoles evolved adhesive toepads just once, there are two competing hypotheses about the origin(s) of digital adhesion in geckos involving either a single origin or multiple origins. Using data from three published gecko genomes, I examine CBP gene evolution in geckos and find support for a hypothesis where CBP gene duplications are associated with the repeated evolution of digital adhesion. Although these results are preliminary, I discuss how additional gecko genome assemblies, combined with phylogenies of keratin and associated protein genes and gene duplication models, can provide rigorous tests of several hypotheses related to gecko CBP evolution. This includes a taxon sampling strategy for sequencing and assembly of gecko genomes that could help resolve competing hypotheses surrounding the origin(s) of digital adhesion.

The Evolution of Venom by Co-option of Single-Copy Genes

The classic model for the evolution of novel gene function is through gene duplication followed by evolution of a new function by one of the copies (neofunctionalization) [1, 2]. However, other modes have also been found, such as novel genes arising from non-coding DNA, chimeric fusions, and lateral gene transfers from other organisms [3-7]. Here we use the rapid turnover of venom genes in parasitoid wasps to study how new gene functions evolve. In contrast to the classic gene duplication model, we find that a common mode of acquisition of new venom genes in parasitoid wasps is co-option of single-copy genes from non-venom progenitors. Transcriptome and proteome sequencing reveal that recruitment and loss of venom genes occur primarily by rapid cis-regulatory expression evolution in the venom gland. Loss of venom genes is primarily due to downregulation of expression in the gland rather than gene death through coding sequence degradation. While the majority of venom genes have specialized expression in the venom gland, recent losses of venom function occur primarily among genes that show broader expression in development, suggesting that they can more readily switch functional roles. We propose that co-option of single-copy genes may be a common but relatively understudied mechanism of evolution for new gene functions, particularly under conditions of rapid evolutionary change.

Gene Duplication Models and Reconstruction of Gene Regulatory Network Evolution from Network Structure

The work was supported by Latvian Council of Science grant 258/2012 and Latvian State Research programme project NexIT (2014-2017).

Opsins have evolved under the permanent heterozygote model: insights from phylotranscriptomics of Odonata.

Gene duplication plays a central role in adaptation to novel environments by providing new genetic material for functional divergence and evolution of biological complexity. Several evolutionary models have been proposed for gene duplication to explain how new gene copies are preserved by natural selection, but these models have rarely been tested using empirical data. Opsin proteins, when combined with a chromophore, form a photopigment that is responsible for the absorption of light, the first step in the phototransduction cascade. Adaptive gene duplications have occurred many times within the animal opsins' gene family, leading to novel wavelength sensitivities. Consequently, opsins are an attractive choice for the study of gene duplication evolutionary models. Odonata (dragonflies and damselflies) have the largest opsin repertoire of any insect currently known. Additionally, there is tremendous variation in opsin copy number between species, particularly in the long-wavelength-sensitive (LWS) class. Using comprehensive phylotranscriptomic and statistical approaches, we tested various evolutionary models of gene duplication. Our results suggest that both the blue-sensitive (BS) and LWS opsin classes were subjected to strong positive selection that greatly weakens after multiple duplication events, a pattern that is consistent with the permanent heterozygote model. Due to the immense interspecific variation and duplicability potential of opsin genes among odonates, they represent a unique model system to test hypotheses regarding opsin gene duplication and diversification at the molecular level.

Genome-scale phylogenetic analysis finds extensive gene transfer among fungi.

Although the role of lateral gene transfer is well recognized in the evolution of bacteria, it is generally assumed that it has had less influence among eukaryotes. To explore this hypothesis, we compare the dynamics of genome evolution in two groups of organisms: cyanobacteria and fungi. Ancestral genomes are inferred in both clades using two types of methods: first, Count, a gene tree unaware method that models gene duplications, gains and losses to explain the observed numbers of genes present in a genome; second, ALE, a more recent gene tree-aware method that reconciles gene trees with a species tree using a model of gene duplication, loss and transfer. We compare their merits and their ability to quantify the role of transfers, and assess the impact of taxonomic sampling on their inferences. We present what we believe is compelling evidence that gene transfer plays a significant role in the evolution of fungi.

Plp1 gene duplication inhibits airway responsiveness and induces lung inflammation

Mice with Plp1 gene duplication model the most common form of Pelizaeus-Merzbacher disease (PMD), a CNS disease in which patients may suffer respiratory complications. We hypothesized that affected mice would lack airway responsiveness compared to wild-type and carrier mice during methacholine challenge. Wild-type (n = 10), carrier female (n = 6) and affected male (n = 8) mice were anesthetized-paralyzed, tracheostomized and ventilated. Respiratory mechanics were recorded at baseline and during escalating doses of nebulized methacholine followed by albuterol. Lung resistance (RL) was the primary endpoint. Lung tissues were assayed for inflammatory and histological differences. At baseline, phase angles were higher in carrier and affected mice than wild-type. Dose-response RL curves in affected and carrier mice indicated a lack of methacholine response. Albuterol reduced RL in wild-type and carrier, but not affected mice. Affected mice exhibited lower interleukin (IL)-6 tissue levels and alveolar inflammatory infiltrates. Affected and carrier mice, compared to wild-type, lacked airway reactivity during methacholine challenge, but only affected mice exhibited decreased lung tissue levels of IL-6 and inflammation.

Tempo and mode of gene duplication in mammalian ribosomal protein evolution.

Gene duplication has been widely recognized as a major driver of evolutionary change and organismal complexity through the generation of multi-gene families. Therefore, understanding the forces that govern the evolution of gene families through the retention or loss of duplicated genes is fundamentally important in our efforts to study genome evolution. Previous work from our lab has shown that ribosomal protein (RP) genes constitute one of the largest classes of conserved duplicated genes in mammals. This result was surprising due to the fact that ribosomal protein genes evolve slowly and transcript levels are very tightly regulated. In our present study, we identified and characterized all RP duplicates in eight mammalian genomes in order to investigate the tempo and mode of ribosomal protein family evolution. We show that a sizable number of duplicates are transcriptionally active and are very highly conserved. Furthermore, we conclude that existing gene duplication models do not readily account for the preservation of a very large number of intact retroduplicated ribosomal protein (RT-RP) genes observed in mammalian genomes. We suggest that selection against dominant-negative mutations may underlie the unexpected retention and conservation of duplicated RP genes, and may shape the fate of newly duplicated genes, regardless of duplication mechanism.

Topological properties of robust biological and computational networks.

Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields.

Following gene duplication, paralog interference constrains transcriptional circuit evolution.

Most models of gene duplication assume that the ancestral functions of the preduplication gene are independent and can therefore be neatly partitioned between descendant paralogs. However, many gene products, such as transcriptional regulators, are components within cooperative assemblies; here, we show that a natural consequence of duplication and divergence of such proteins can be competitive interference between the paralogs. Our example is based on the duplication of the essential MADS-box transcriptional regulator Mcm1, which is found in all fungi and regulates a large set of genes. We show that a set of historical amino acid sequence substitutions minimized paralog interference in contemporary species and, in doing so, increased the molecular complexity of this gene regulatory network. We propose that paralog interference is a common constraint on gene duplicate evolution, and its resolution, which can generate additional regulatory complexity, is needed to stabilize duplicated genes in the genome.

Asymmetric Functional Divergence of Young, Dispersed Gene Duplicates in Arabidopsis thaliana

One prediction of the classic Ohno model of gene duplication predicts that new genes form from the asymmetric functional divergence of a newly arisen, redundant duplicate locus. In order to understand the mechanisms which give rise to functional divergence of newly formed dispersed duplicates, we assessed the expression and molecular evolutionary divergence of a suite of 19 highly similar dispersed duplicates in Arabidopsis thaliana. These duplicates have a K sil equal to or less than 5% and are specific to the A. thaliana lineage; thus, they predictably represent some of the youngest duplicates in the A. thaliana genome. We found that the majority of young duplicate loci exhibit asymmetric expression patterns, with the daughter locus exhibiting reduced expression across all tissues analyzed relative to the progenitor locus or simply not expressed. Furthermore, daughter loci, on the whole, have significantly more nonsynonymous substitutions than the progenitor loci. We also identified four pairs of loci which exhibit significant (P<0.05) evolutionary rate asymmetry, three of which exhibit elevated dN/dS in the duplicate copy. We suggest, based on these data, that functional diversification initially takes the form of asymmetric regulatory divergence that can be a direct consequence of the mode of duplication. The reduced and/or absence of expression in the daughter copy relaxes functional constraint on its protein coding sequence leading to the asymmetric accumulation of nonsynonymous mutations. Thus, our data both affirm Ohno's prediction while explaining the mechanism by which functional divergence initially occurs following duplication for dispersed gene duplicates.

A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Correction: Limitations of Gene Duplication Models: Evolution of Modules in Protein Interaction Networks

Figure 2 in the PDF does not precisely match the image of Figure 2 in the online version of the article. The online version is correct.

Limitations of gene duplication models: evolution of modules in protein interaction networks.

It has been generally acknowledged that the module structure of protein interaction networks plays a crucial role with respect to the functional understanding of these networks. In this paper, we study evolutionary aspects of the module structure of protein interaction networks, which forms a mesoscopic level of description with respect to the architectural principles of networks. The purpose of this paper is to investigate limitations of well known gene duplication models by showing that these models are lacking crucial structural features present in protein interaction networks on a mesoscopic scale. This observation reveals our incomplete understanding of the structural evolution of protein networks on the module level.

Multiple Routes to Subfunctionalization and Gene Duplicate Specialization

Gene duplication is arguably the most significant source of new functional genetic material. A better understanding of the processes that lead to the stable incorporation of gene duplications into the genome is important both because it relates to interspecific differences in genome composition and because it can shed light on why some classes of gene are more prone to duplication than others. Typically, models of gene duplication consider the periods before duplication, during the spread and fixation of a new duplicate, and following duplication as distinct phases without a common underlying selective environment. I consider a scenario where a gene that is initially expressed in multiple contexts can undergo mutations that alter its expression profile or its functional coding sequence. The selective regime that acts on the functional output of the allele copies carried by an individual is constant. If there is a potential selective benefit to having different coding sequences expressed in each context, then, regardless of the constraints on functional variation at the single-locus gene, the waiting time until a gene duplication is incorporated goes down as population size increases.

Replica procedure for probabilistic algorithms as a model of gene duplication

In the present paper we propose to describe gene networks in biological systems using probabilistic algorithms. We describe gene duplication in the process of biological evolution using introduction of the replica procedure for probabilistic algorithms. We construct the examples of such a replica procedure for hidden Markov models. We introduce the family of hidden Markov models where the set of hidden states is a finite additive group with a p-adic metric and build the replica procedure for this family of markovian models.

Dynamics of gene duplication and transposons in microbial genomes following a sudden environmental change

The impact of gene duplication on evolution is as ubiquitous as point mutation, but this realization is not yet reflected in our quantitative models of population genetics. In this Commentary article, we explore the implications of such models of gene duplication, specifically expanding on our previous work. We lay down a framework for understanding the impact of gene duplications on the evolution a biological network and give an analytical argument based on the concept of mutational error threshold for the necessity of gene duplications for the evolution of complex networks. In other words, by realizing that the impact of mutations must act appropriately in order to allow for the maintenance of complex networks, we develop a mathematical scaling argument that shows why gene duplication provides the types of mutations more favorable to increasing complexity. In the process of doing so, we seek to explain the relationship between per base pair mutation rates and genome size.