A pluralistic account of homology: adapting the models to the data

Gene novelty and gene family expansion in the early evolution of Lepidoptera

BACKGROUND

Almost 10% of all known animal species belong to Lepidoptera: moths and butterflies. To understand how this incredible diversity evolved we assess the role of gene gain in driving early lepidopteran evolution. Here, we compared the complete genomes of 115 insect species, including 99 Lepidoptera, to search for novel genes coincident with the emergence of Lepidoptera.

RESULTS

We find 217 orthogroups or gene families which emerged on the branch leading to Lepidoptera; of these 177 likely arose by gene duplication followed by extensive sequence divergence, 2 are candidates for origin by horizontal gene transfer, and 38 have no known homology outside of Lepidoptera and possibly arose via de novo gene genesis. We focus on two new gene families that are conserved across all lepidopteran species and underwent extensive duplication, suggesting important roles in lepidopteran biology. One encodes a family of sugar and ion transporter molecules, potentially involved in the evolution of diverse feeding behaviours in early Lepidoptera. The second encodes a family of unusual propeller-shaped proteins that likely originated by horizontal gene transfer from Spiroplasma bacteria; we name these the Lepidoptera propellin genes.

CONCLUSION

We provide the first insights into the role of genetic novelty in the early evolution of Lepidoptera. This gives new insight into the rate of gene gain during the evolution of the order as well as providing context on the likely mechanisms of origin. We describe examples of new genes which were retained and duplicated further in all lepidopteran species, suggesting their importance in Lepidoptera evolution.

Hierarchical community structure in networks

Modular and hierarchical community structures are pervasive in real-world complex systems. A great deal of effort has gone into trying to detect and study these structures. Important theoretical advances in the detection of modular have included identifying fundamental limits of detectability by formally defining community structure using probabilistic generative models. Detecting hierarchical community structure introduces additional challenges alongside those inherited from community detection. Here we present a theoretical study on hierarchical community structure in networks, which has thus far not received the same rigorous attention. We address the following questions. (1) How should we define a hierarchy of communities? (2) How do we determine if there is sufficient evidence of a hierarchical structure in a network? (3) How can we detect hierarchical structure efficiently? We approach these questions by introducing a definition of hierarchy based on the concept of stochastic externally equitable partitions and their relation to probabilistic models, such as the popular stochastic block model. We enumerate the challenges involved in detecting hierarchies and, by studying the spectral properties of hierarchical structure, present an efficient and principled method for detecting them.

Ab Initio Construction and Evolutionary Analysis of Protein-Coding Gene Families with Partially Homologous Relationships: Closely Related Drosophila Genomes as a Case Study

How have genes evolved within a well-known genome phylogeny? Many protein-coding genes should have evolved as a whole at the gene level, and some should have evolved partly through fragments at the subgene level. To comprehensively explore such complex homologous relationships and better understand gene family evolution, here, with de novo-identified modules, the subgene units which could consecutively cover proteins within a set of closely related species, we applied a new phylogeny-based approach that considers evolutionary models with partial homology to classify all protein-coding genes in nine Drosophila genomes. Compared with two other popular methods for gene family construction, our approach improved practical gene family classifications with a more reasonable view of homology and provided a much more complete landscape of gene family evolution at the gene and subgene levels. In the case study, we found that most expanded gene families might have evolved mainly through module rearrangements rather than gene duplications and mainly generated single-module genes through partial gene duplication, suggesting that there might be pervasive subgene rearrangement in the evolution of protein-coding gene families. The use of a phylogeny-based approach with partial homology to classify and analyze protein-coding gene families may provide us with a more comprehensive landscape depicting how genes evolve within a well-known genome phylogeny.

Modeling the evolution of interconnected processes: It is the song and the singers: Tracking units of selection with interaction networks

Recently, Doolittle and Inkpen formulated a thought provoking theory, asserting that evolution by natural selection was responsible for the sideways evolution of two radically different kinds of selective units (also called Domains). The former entities, termed singers, correspond to the usual objects studied by evolutionary biologists (gene, genomes, individuals, species, etc.), whereas the later, termed songs, correspond to re-produced biological and ecosystemic functions, processes, information, and memes. Singers perform songs through selected patterns of interactions, meaning that a wealth of critical phenomena might receive novel evolutionary explanations. However, this theory did not provide an empirical approach to study evolution in such a broadened context. Here, we show that analyzing songs and singers, using patterns of interaction networks as a common ontology for both, offers a novel, actionable, inclusive and mathematical way to analyze not only the re-production but also the evolution and fitness of biological and ecosystemic interconnected processes.

Rich Repertoire of Quorum Sensing Protein Coding Sequences in CPR and DPANN Associated with Interspecies and Interkingdom Communication

The selection of predicted genes for interspecies communication within the CPR and DPANN genomes sheds some light onto the underlying mechanisms supporting their inferred symbiotic lifestyle. Also, considering the lack of core pathways such as the de novo synthesis of nucleotides or amino acids in the CPR and DPANN lineages, the persistence of these genes highlights how determinant social traits can be for the survival of some microorganisms. Finally, the considerable number of variants of QS proteins identified among the 69 CPR and DPANN phyla substantially expands our knowledge of prokaryotic communication across the tree of life and suggests that the multiplicity of “dialects” in the microbial world is probably larger than previously appreciated.

The bacterial candidate phyla radiation (CPR) and the archaeal DPANN superphylum are two novel lineages that have substantially expanded the tree of life due to their large phylogenetic diversity. Because of their ultrasmall size, reduced genome, and lack of core biosynthetic capabilities, most CPR and DPANN members are predicted to be sustained through their interactions with other species. How the few characterized CPR and DPANN symbionts achieve these critical interactions is, however, poorly understood. Here, we conducted an in silico analysis on 2,597 CPR/DPANN genomes to test whether these ultrasmall microorganisms might encode homologs of reference proteins involved in the synthesis and/or the detection of 26 different types of communication molecules (quorum sensing [QS] signals), since QS signals are well-known mediators of intra- and interorganismic relationships. We report the discovery of 5,693 variants of QS proteins distributed across 63 CPR and 6 DPANN phyla and associated with 14 distinct types of communication molecules, most of which were characterized as interspecies QS signals.

IMPORTANCE The selection of predicted genes for interspecies communication within the CPR and DPANN genomes sheds some light onto the underlying mechanisms supporting their inferred symbiotic lifestyle. Also, considering the lack of core pathways such as the de novo synthesis of nucleotides or amino acids in the CPR and DPANN lineages, the persistence of these genes highlights how determinant social traits can be for the survival of some microorganisms. Finally, the considerable number of variants of QS proteins identified among the 69 CPR and DPANN phyla substantially expands our knowledge of prokaryotic communication across the tree of life and suggests that the multiplicity of “dialects” in the microbial world is probably larger than previously appreciated.

Eukaryote Genes Are More Likely than Prokaryote Genes to Be Composites

The formation of new genes by combining parts of existing genes is an important evolutionary process. Remodelled genes, which we call composites, have been investigated in many species, however, their distribution across all of life is still unknown. We set out to examine the extent to which genomes from cells and mobile genetic elements contain composite genes. We identify composite genes as those that show partial homology to at least two unrelated component genes. In order to identify composite and component genes, we constructed sequence similarity networks (SSNs) of more than one million genes from all three domains of life, as well as viruses and plasmids. We identified non-transitive triplets of nodes in this network and explored the homology relationships in these triplets to see if the middle nodes were indeed composite genes. In total, we identified 221,043 (18.57%) composites genes, which were distributed across all genomic and functional categories. In particular, the presence of composite genes is statistically more likely in eukaryotes than prokaryotes.

Carbon Fixation by Marine Ultrasmall Prokaryotes

Autotrophic carbon fixation is a crucial process for sustaining life on Earth. To date, six pathways, the Calvin–Benson–Bassham cycle, the reductive tricarboxylic acid cycle, the 3-hydroxypropionate bi-cycle, the Wood–Ljungdahl pathway, the dicarboxylate/4-hydroxybutyrate cycle, and the 4-hydroxybutyrate cycle, have been described. Nano-organisms such as members of the Candidate Phyla Radiation (CPR) bacterial superphylum and the Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohalorchaeota (DPANN) archaeal superphylum could deeply impact carbon cycling and carbon fixation in ways that are still to be determined. CPR and DPANN are ubiquitous in the environment but understudied; their gene contents are not exhaustively described; and their metabolisms are not yet fully understood. Here, the completeness of each of the above pathways was quantified and tested for the presence of all key enzymes in nano-organisms from across the World Ocean. The novel marine ultrasmall prokaryotes were demonstrated to collectively harbor the genes required for carbon fixation, in particular the “energetically efficient” dicarboxylate/4-hydroxybutyrate pathway and the 4-hydroxybutyrate pathway. This contrasted with the known carbon metabolic pathways associated with CPR members in aquifers, where they are described as degraders (Castelle CJ, et al. 2015. Genomic expansion of domain archaea highlights roles for organisms from new phyla in anaerobic carbon cycling. Curr Biol. 25(6):690–701; Castelle CJ, et al. 2018. Biosynthetic capacity, metabolic variety and unusual biology in the CPR and DPANN radiations. Nat Rev Microbiol. 16(10):629–645; Anantharaman K, et al. 2016. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 7:13219.). Our findings suggest that nano-organisms have a broader contribution to carbon fixation and cycling than currently assumed. Furthermore, CPR and DPANN superphyla are possibly not the only nanosized prokaryotes; therefore, the discovery of new autotrophic marine nano-organisms by future single cell genomics is anticipated.

CompositeSearch: A Generalized Network Approach for Composite Gene Families Detection

Genes evolve by point mutations, but also by shuffling, fusion, and fission of genetic fragments. Therefore, similarity between two sequences can be due to common ancestry producing homology, and/or partial sharing of component fragments. Disentangling these processes is especially challenging in large molecular data sets, because of computational time. In this article, we present CompositeSearch, a memory-efficient, fast, and scalable method to detect composite gene families in large data sets (typically in the range of several million sequences). CompositeSearch generalizes the use of similarity networks to detect composite and component gene families with a greater recall, accuracy, and precision than recent programs (FusedTriplets and MosaicFinder). Moreover, CompositeSearch provides user-friendly quality descriptions regarding the distribution and primary sequence conservation of these gene families allowing critical biological analyses of these data.

Tracking the Rules of Transmission and Introgression with Networks

Understanding how an animal organism and its gut microbes form an integrated biological organization, known as a holobiont, is becoming a central issue in biological studies. Such an organization inevitably involves a complex web of transmission processes that occur on different scales in time and space, across microbes and hosts. Network-based models are introduced in this chapter to tackle aspects of this complexity and to better take into account vertical and horizontal dimensions of transmission. Two types of network-based models are presented, sequence similarity networks and bipartite graphs. One interest of these networks is that they can consider a rich diversity of important players in microbial evolution that are usually excluded from evolutionary studies, like plasmids and viruses. These methods bring forward the notion of "gene externalization," which is defined as the presence of redundant copies of prokaryotic genes on mobile genetic elements (MGEs), and therefore emphasizes a related although distinct process from lateral gene transfer between microbial cells. This chapter introduces guidelines to the construction of these networks, reviews their analysis, and illustrates their possible biological interpretations and uses. The application to human gut microbiomes shows that sequences present in a higher diversity of MGEs have both biased functions and a broader microbial and human host range. These results suggest that an "externalized gut metagenome" is partly common to humans and benefits the gut microbial community. We conclude that testing relationships between microbial genes, microbes, and their animal hosts, using network-based methods, could help to unravel additional mechanisms of transmission in holobionts.

DeCoSTAR: Reconstructing the Ancestral Organization of Genes or Genomes Using Reconciled Phylogenies

DeCoSTAR is a software that aims at reconstructing the organization of ancestral genes or genomes in the form of sets of neighborhood relations (adjacencies) between pairs of ancestral genes or gene domains. It can also improve the assembly of fragmented genomes by proposing evolutionary-induced adjacencies between scaffolding fragments. Ancestral genes or domains are deduced from reconciled phylogenetic trees under an evolutionary model that considers gains, losses, speciations, duplications, and transfers as possible events for gene evolution. Reconciliations are either given as input or computed with the ecceTERA package, into which DeCoSTAR is integrated. DeCoSTAR computes adjacency evolutionary scenarios using a scoring scheme based on a weighted sum of adjacency gains and breakages. Solutions, both optimal and near-optimal, are sampled according to the Boltzmann–Gibbs distribution centered around parsimonious solutions, and statistical supports on ancestral and extant adjacencies are provided. DeCoSTAR supports the features of previously contributed tools that reconstruct ancestral adjacencies, namely DeCo, DeCoLT, ART-DeCo, and DeClone. In a few minutes, DeCoSTAR can reconstruct the evolutionary history of domains inside genes, of gene fusion and fission events, or of gene order along chromosomes, for large data sets including dozens of whole genomes from all kingdoms of life. We illustrate the potential of DeCoSTAR with several applications: ancestral reconstruction of gene orders for Anopheles mosquito genomes, multidomain proteins in Drosophila, and gene fusion and fission detection in Actinobacteria.

Availability:http://pbil.univ-lyon1.fr/software/DeCoSTAR (Last accessed April 24, 2017).

The role of public goods in planetary evolution

Biological public goods are broadly shared within an ecosystem and readily available. They appear to be widespread and may have played important roles in the history of life on Earth. Of particular importance to events in the early history of life are the roles of public goods in the merging of genomes, protein domains and even cells. We suggest that public goods facilitated the origin of the eukaryotic cell, a classic major evolutionary transition. The recognition of genomic public goods challenges advocates of a direct graph view of phylogeny, and those who deny that any useful phylogenetic signal persists in modern genomes. Ecological spillovers generate public goods that provide new ecological opportunities.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Transmission as a basic process in microbial biology. Lwoff Award Prize Lecture

Transmission is a basic process in biology and evolution, as it communicates different biological entities within and across hierarchical levels (from genes to holobionts) both in time and space. Vertical descent, replication, is transmission of information across generations (in the time dimension), and horizontal descent is transmission of information across compartments (in the space dimension). Transmission is essentially a communication process that can be studied by analogy of the classic information theory, based on 'emitters', 'messages' and 'receivers'. The analogy can be easily extended to the triad 'emigration', 'migration' and 'immigration'. A number of causes (forces) determine the emission, and another set of causes (energies) assures the reception. The message in fact is essentially constituted by 'meaningful' biological entities. A DNA sequence, a cell and a population have a semiotic dimension, are 'signs' that are eventually recognized (decoded) and integrated by receiver biological entities. In cis-acting or unenclosed transmission, the emitters and receivers correspond to separated entities of the same hierarchical level; in trans-acting or embedded transmission, the information flows between different, but frequently nested, hierarchical levels. The result (as in introgressive events) is constantly producing innovation and feeding natural selection, influencing also the evolution of transmission processes. This review is based on the concepts presented at the André Lwoff Award Lecture in the FEMS Microbiology Congress in Maastricht in 2015.

Community detection in sequence similarity networks based on attribute clustering

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs, for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments.

The ground truth about metadata and community detection in networks

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks' links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures.

Molecular Phylogenetics and the Perennial Problem of Homology

The concept of homology has a long history, during much of which the issue has been how to reconcile similarity and common descent when these are not coextensive. Although thinking molecular phylogeneticists have learned not to say "percent homology," the problems are deeper than that and unresolved.

Not So Simple After All: Bacteria, Their Population Genetics, and Recombination

The pervasive nature of bacterial recombination has become clear. Despite this, the population genetics of bacteria persist in being viewed as simple. Here, I argue against that characterization. After summarizing the history of the topic, I survey the evidence for remarkable and unexplained variation in recombination rate among and within bacterial species. I finally argue that despite recent assertions that recombination means bacterial genes are "public goods," in bacteria the level of selection is the gene, and genes can be understood to have niches with dimensions including the other contents of the genome in which they find themselves.

Horizontal gene flow from Eubacteria to Archaebacteria and what it means for our understanding of eukaryogenesis

The origin of the eukaryotic cell is considered one of the major evolutionary transitions in the history of life. Current evidence strongly supports a scenario of eukaryotic origin in which two prokaryotes, an archaebacterial host and an α-proteobacterium (the free-living ancestor of the mitochondrion), entered a stable symbiotic relationship. The establishment of this relationship was associated with a process of chimerization, whereby a large number of genes from the α-proteobacterial symbiont were transferred to the host nucleus. A general framework allowing the conceptualization of eukaryogenesis from a genomic perspective has long been lacking. Recent studies suggest that the origins of several archaebacterial phyla were coincident with massive imports of eubacterial genes. Although this does not indicate that these phyla originated through the same process that led to the origin of Eukaryota, it suggests that Archaebacteria might have had a general propensity to integrate into their genomes large amounts of eubacterial DNA. We suggest that this propensity provides a framework in which eukaryogenesis can be understood and studied in the light of archaebacterial ecology. We applied a recently developed supertree method to a genomic dataset composed of 392 eubacterial and 51 archaebacterial genera to test whether large numbers of genes flowing from Eubacteria are indeed coincident with the origin of major archaebacterial clades. In addition, we identified two potential large-scale transfers of uncertain directionality at the base of the archaebacterial tree. Our results are consistent with previous findings and seem to indicate that eubacterial gene imports (particularly from δ-Proteobacteria, Clostridia and Actinobacteria) were an important factor in archaebacterial history. Archaebacteria seem to have long relied on Eubacteria as a source of genetic diversity, and while the precise mechanism that allowed these imports is unknown, we suggest that our results support the view that processes comparable to those through which eukaryotes emerged might have been common in archaebacterial history.

The ring of life hypothesis for eukaryote origins is supported by multiple kinds of data

The literature is replete with manuscripts describing the origin of eukaryotic cells. Most of the models for eukaryogenesis are either autogenous (sometimes called slow-drip), or symbiogenic (sometimes called big-bang). In this article, we use large and diverse suites of 'Omics' and other data to make the inference that autogeneous hypotheses are a very poor fit to the data and the origin of eukaryotic cells occurred in a single symbiosis.

Protein networks identify novel symbiogenetic genes resulting from plastid endosymbiosis

The integration of foreign genetic information is central to the evolution of eukaryotes, as has been demonstrated for the origin of the Calvin cycle and of the heme and carotenoid biosynthesis pathways in algae and plants. For photosynthetic lineages, this coordination involved three genomes of divergent phylogenetic origins (the nucleus, plastid, and mitochondrion). Major hurdles overcome by the ancestor of these lineages were harnessing the oxygen-evolving organelle, optimizing the use of light, and stabilizing the partnership between the plastid endosymbiont and host through retargeting of proteins to the nascent organelle. Here we used protein similarity networks that can disentangle reticulate gene histories to explore how these significant challenges were met. We discovered a previously hidden component of algal and plant nuclear genomes that originated from the plastid endosymbiont: symbiogenetic genes (S genes). These composite proteins, exclusive to photosynthetic eukaryotes, encode a cyanobacterium-derived domain fused to one of cyanobacterial or another prokaryotic origin and have emerged multiple, independent times during evolution. Transcriptome data demonstrate the existence and expression of S genes across a wide swath of algae and plants, and functional data indicate their involvement in tolerance to oxidative stress, phototropism, and adaptation to nitrogen limitation. Our research demonstrates the "recycling" of genetic information by photosynthetic eukaryotes to generate novel composite genes, many of which function in plastid maintenance.

Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution

The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts.

Introgressive processes shape the microbial world at all levels of organisation.

This reticulated evolution is increasingly studied by sequence-similarity networks.

They provide an inclusive accurate multilevel framework to study the web of life.

Networks enhance analyses of microbial genes, genomes, communities, and of symbiosis.

Highly divergent ancient gene families in metagenomic samples are compatible with additional divisions of life

Background

Microbial genetic diversity is often investigated via the comparison of relatively similar 16S molecules through multiple alignments between reference sequences and novel environmental samples using phylogenetic trees, direct BLAST matches, or phylotypes counts. However, are we missing novel lineages in the microbial dark universe by relying on standard phylogenetic and BLAST methods? If so, how can we probe that universe using alternative approaches? We performed a novel type of multi-marker analysis of genetic diversity exploiting the topology of inclusive sequence similarity networks.

Results

Our protocol identified 86 ancient gene families, well distributed and rarely transferred across the 3 domains of life, and retrieved their environmental homologs among 10 million predicted ORFs from human gut samples and other metagenomic projects. Numerous highly divergent environmental homologs were observed in gut samples, although the most divergent genes were over-represented in non-gut environments. In our networks, most divergent environmental genes grouped exclusively with uncultured relatives, in maximal cliques. Sequences within these groups were under strong purifying selection and presented a range of genetic variation comparable to that of a prokaryotic domain.

Conclusions

Many genes families included environmental homologs that were highly divergent from cultured homologs: in 79 gene families (including 18 ribosomal proteins), Bacteria and Archaea were less divergent than some groups of environmental sequences were to any cultured or viral homologs. Moreover, some groups of environmental homologs branched very deeply in phylogenetic trees of life, when they were not too divergent to be aligned. These results underline how limited our understanding of the most diverse elements of the microbial world remains, and encourage a deeper exploration of natural communities and their genetic resources, hinting at the possibility that still unknown yet major divisions of life have yet to be discovered.

Reviewers

This article was reviewed by Eugene Koonin, William Martin and James McInerney.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-015-0092-3) contains supplementary material, which is available to authorized users.

Inferring horizontal gene transfer

Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based ("parametric") methods search for deviations from the genomic average, whereas evolutionary history-based ("phylogenetic") approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events.

Fungal metabolic gene clusters-caravans traveling across genomes and environments

Metabolic gene clusters (MGCs), physically co-localized genes participating in the same metabolic pathway, are signature features of fungal genomes. MGCs are most often observed in specialized metabolism, having evolved in individual fungal lineages in response to specific ecological needs, such as the utilization of uncommon nutrients (e.g., galactose and allantoin) or the production of secondary metabolic antimicrobial compounds and virulence factors (e.g., aflatoxin and melanin). A flurry of recent studies has shown that several MGCs, whose functions are often associated with fungal virulence as well as with the evolutionary arms race between fungi and their competitors, have experienced horizontal gene transfer (HGT). In this review, after briefly introducing HGT as a source of gene innovation, we examine the evidence for HGT's involvement on the evolution of MGCs and, more generally of fungal metabolism, enumerate the molecular mechanisms that mediate such transfers and the ecological circumstances that favor them, as well as discuss the types of evidence required for inferring the presence of HGT in MGCs. The currently available examples indicate that transfers of entire MGCs have taken place between closely related fungal species as well as distant ones and that they sometimes involve large chromosomal segments. These results suggest that the HGT-mediated acquisition of novel metabolism is an ongoing and successful ecological strategy for many fungal species.