SYNPHONI: scale-free and phylogeny-aware reconstruction of synteny conservation and transformation across animal genomes.
Ontology highlight
ABSTRACT: Summary
Current approaches detect conserved genomic order either at chromosomal (macrosynteny) or at subchromosomal scales (microsynteny). The latter generally requires collinearity and hard thresholds on syntenic region size, thus excluding a major proportion of syntenies with recent expansions or minor rearrangements. 'SYNPHONI' bridges the gap between micro- and macrosynteny detection, providing detailed information on both synteny conservation and transformation throughout the evolutionary history of animal genomes.Availability and implementation
Source code is freely available at https://github.com/nsmro/SYNPHONI, implemented in Python 3.9.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Robert NSM
PROVIDER: S-EPMC9750109 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature
Publications
SYNPHONI: scale-free and phylogeny-aware reconstruction of synteny conservation and transformation across animal genomes.
Robert Nicolas Serge Matthieu NSM Sarigol Fatih F Zieger Elisabeth E Simakov Oleg O
Bioinformatics (Oxford, England) 20221201 24
<h4>Summary</h4>Current approaches detect conserved genomic order either at chromosomal (macrosynteny) or at subchromosomal scales (microsynteny). The latter generally requires collinearity and hard thresholds on syntenic region size, thus excluding a major proportion of syntenies with recent expansions or minor rearrangements. 'SYNPHONI' bridges the gap between micro- and macrosynteny detection, providing detailed information on both synteny conservation and transformation throughout the evolut ...[more]
Similar Datasets
Project description:BACKGROUND:Comparisons between the genomes of the closely related nematodes Caenorhabditis elegans and Caenorhabditis briggsae reveal high rates of rearrangement, with a bias towards within-chromosome events. To assess whether this pattern is true of nematodes in general, we have used genome sequence to compare two nematode species that last shared a common ancestor approximately 300 million years ago: the model C. elegans and the filarial parasite Brugia malayi. RESULTS:An 83 kb region flanking the gene for Bm-mif-1 (macrophage migration inhibitory factor, a B. malayi homolog of a human cytokine) was sequenced. When compared to the complete genome of C. elegans, evidence for conservation of long-range synteny and microsynteny was found. Potential C. elegans orthologs for II of the 12 protein-coding genes predicted in the B. malayi sequence were identified. Ten of these orthologs were located on chromosome I, with eight clustered in a 2.3 Mb region. While several, relatively local, intrachromosomal rearrangements have occurred, the order, composition, and configuration of two gene clusters, each containing three genes, was conserved. Comparison of B. malayi BAC-end genome survey sequence to C. elegans also revealed a bias towards intrachromosome rearrangements. CONCLUSIONS:We suggest that intrachromosomal rearrangement is a major force driving chromosomal organization in nematodes, but is constrained by the interdigitation of functional elements of neighboring genes.
| S-EPMC134624 | biostudies-literature
Project description:The oomycetes are a class of microscopic, filamentous eukaryotes within the Stramenopiles-Alveolata-Rhizaria (SAR) supergroup which includes ecologically significant animal and plant pathogens, most infamously the causative agent of potato blight Phytophthora infestans. Single-gene and concatenated phylogenetic studies both of individual oomycete genera and of members of the larger class have resulted in conflicting conclusions concerning species phylogenies within the oomycetes, particularly for the large Phytophthora genus. Genome-scale phylogenetic studies have successfully resolved many eukaryotic relationships by using supertree methods, which combine large numbers of potentially disparate trees to determine evolutionary relationships that cannot be inferred from individual phylogenies alone. With a sufficient amount of genomic data now available, we have undertaken the first whole-genome phylogenetic analysis of the oomycetes using data from 37 oomycete species and 6 SAR species. In our analysis, we used established supertree methods to generate phylogenies from 8,355 homologous oomycete and SAR gene families and have complemented those analyses with both phylogenomic network and concatenated supermatrix analyses. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and individual clades within the problematic Phytophthora genus. Support for the resolution of the inferred relationships between individual Phytophthora clades varies depending on the methodology used. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. IMPORTANCE The oomycetes are a class of eukaryotes and include ecologically significant animal and plant pathogens. Single-gene and multigene phylogenetic studies of individual oomycete genera and of members of the larger classes have resulted in conflicting conclusions concerning interspecies relationships among these species, particularly for the Phytophthora genus. The onset of next-generation sequencing techniques now means that a wealth of oomycete genomic data is available. For the first time, we have used genome-scale phylogenetic methods to resolve oomycete phylogenetic relationships. We used supertree methods to generate single-gene and multigene species phylogenies. Overall, our supertree analyses utilized phylogenetic data from 8,355 oomycete gene families. We have also complemented our analyses with superalignment phylogenies derived from 131 single-copy ubiquitous gene families. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and clades. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes.
| S-EPMC5390094 | biostudies-literature
Project description:BackgroundThe Rosaceae encompass a large number of economically-important diploid and polyploid fruit and ornamental species in many different genera. The basic chromosome numbers of these genera are x = 7, 8 and 9 and all have compact and relatively similar genome sizes. Comparative mapping between distantly-related genera has been performed to a limited extent in the Rosaceae including a comparison between Malus (subfamily Maloideae) and Prunus (subfamily Prunoideae); however no data has been published to date comparing Malus or Prunus to a member of the subfamily Rosoideae. In this paper we compare the genome of Fragaria, a member of the Rosoideae, to Prunus, a member of the Prunoideae.ResultsThe diploid genomes of Prunus (2n = 2x = 16) and Fragaria (2n = 2x = 14) were compared through the mapping of 71 anchor markers - 40 restriction fragment length polymorphisms (RFLPs), 29 indels or single nucleotide polymorphisms (SNPs) derived from expressed sequence tags (ESTs) and two simple-sequence repeats (SSRs) - on the reference maps of both genera. These markers provided good coverage of the Prunus (78%) and Fragaria (78%) genomes, with maximum gaps and average densities of 22 cM and 7.3 cM/marker in Prunus and 32 cM and 8.0 cM/marker in Fragaria.ConclusionOur results indicate a clear pattern of synteny, with most markers of each chromosome of one of these species mapping to one or two chromosomes of the other. A large number of rearrangements (36), most of which produced by inversions (27) and the rest (9) by translocations or fission/fusion events could also be inferred. We have provided the first framework for the comparison of the position of genes or DNA sequences of these two economically valuable and yet distantly-related genera of the Rosaceae.
| S-EPMC2442709 | biostudies-literature
Project description:Accurate orthologue identification is a vital component of bacterial comparative genomic studies, but many popular sequence-similarity-based approaches do not scale well to the large numbers of genomes that are now generated routinely. Furthermore, most approaches do not take gene synteny into account, which is useful information for disentangling paralogues. Here, we present SynerClust, a user-friendly synteny-aware tool based on synergy that can process thousands of genomes. SynerClust was designed to analyse genomes with high levels of local synteny, particularly prokaryotes, which have operon structure. SynerClust's run-time is optimized by selecting cluster representatives at each node in the phylogeny; thus, avoiding the need for exhaustive pairwise similarity searches. In benchmarking against Roary, Hieranoid2, PanX and Reciprocal Best Hit, SynerClust was able to more completely identify sets of core genes for datasets that included diverse strains, while using substantially less memory, and with scalability comparable to the fastest tools. Due to its scalability, ease of installation and use, and suitability for a variety of computing environments, orthogroup clustering using SynerClust will enable many large-scale prokaryotic comparative genomics efforts.
| S-EPMC6321874 | biostudies-literature
Project description:Whole-genome comparisons provide insight into genome evolution by informing on gene repertoires, gene gains/losses, and genome organization. Most of our knowledge about eukaryotic genome evolution is derived from studies of multicellular model organisms. The eukaryotic phylum Apicomplexa contains obligate intracellular protist parasites responsible for a wide range of human and veterinary diseases (e.g., malaria, toxoplasmosis, and theileriosis). We have developed an in silico protein-encoding gene based pipeline to investigate synteny across 12 apicomplexan species from six genera. Genome rearrangement between lineages is extensive. Syntenic regions (conserved gene content and order) are rare between lineages and appear to be totally absent across the phylum, with no group of three genes found on the same chromosome and in the same order within 25 kb up- and downstream of any orthologous genes. Conserved synteny between major lineages is limited to small regions in Plasmodium and Theileria/Babesia species, and within these conserved regions, there are a number of proteins putatively targeted to organelles. The observed overall lack of synteny is surprising considering the divergence times and the apparent absence of transposable elements (TEs) within any of the species examined. TEs are ubiquitous in all other groups of eukaryotes studied to date and have been shown to be involved in genomic rearrangements. It appears that there are different criteria governing genome evolution within the Apicomplexa relative to other well-studied unicellular and multicellular eukaryotes.
| S-EPMC3176833 | biostudies-literature
Project description:UnlabelledBackgroundWith the progress of modern sequencing technologies a large number of complete genomes are now available. Traditionally the comparison of two related genomes is carried out by sequence alignment. There are cases where these techniques cannot be applied, for example if two genomes do not share the same set of genes, or if they are not alignable to each other due to low sequence similarity, rearrangements and inversions, or more specifically to their lengths when the organisms belong to different species. For these cases the comparison of complete genomes can be carried out only with ad hoc methods that are usually called alignment-free methods.MethodsIn this paper we propose a distance function based on subword compositions called Underlying Approach (UA). We prove that the matching statistics, a popular concept in the field of string algorithms able to capture the statistics of common words between two sequences, can be derived from a small set of "independent" subwords, namely the irredundant common subwords. We define a distance-like measure based on these subwords, such that each region of genomes contributes only once, thus avoiding to count shared subwords a multiple number of times. In a nutshell, this filter discards subwords occurring in regions covered by other more significant subwords.ResultsThe Underlying Approach (UA) builds a scoring function based on this set of patterns, called underlying. We prove that this set is by construction linear in the size of input, without overlaps, and can be efficiently constructed. Results show the validity of our method in the reconstruction of phylogenetic trees, where the Underlying Approach outperforms the current state of the art methods. Moreover, we show that the accuracy of UA is achieved with a very small number of subwords, which in some cases carry meaningful biological information.Availabilityhttp://www.dei.unipd.it/∼ciompin/main/underlying.html.
| S-EPMC3549825 | biostudies-literature
Project description:BackgroundHomology inference is pivotal to evolutionary biology and is primarily based on significant sequence similarity, which, in general, is a good indicator of homology. Algorithms have also been designed to utilize conservation in gene order as an indication of homologous regions. We have developed GenFamClust, a method based on quantification of both gene order conservation and sequence similarity.ResultsIn this study, we validate GenFamClust by comparing it to well known homology inference algorithms on a synthetic dataset. We applied several popular clustering algorithms on homologs inferred by GenFamClust and other algorithms on a metazoan dataset and studied the outcomes. Accuracy, similarity, dependence, and other characteristics were investigated for gene families yielded by the clustering algorithms. GenFamClust was also applied to genes from a set of complete fungal genomes and gene families were inferred using clustering. The resulting gene families were compared with a manually curated gold standard of pillars from the Yeast Gene Order Browser. We found that the gene-order component of GenFamClust is simple, yet biologically realistic, and captures local synteny information for homologs.ConclusionsThe study shows that GenFamClust is a more accurate, informed, and comprehensive pipeline to infer homologs and gene families than other commonly used homology and gene-family inference methods.
| S-EPMC4893229 | biostudies-literature
Project description:BackgroundIn the past decade or more, the emphasis for reconstructing species phylogenies has moved from the analysis of a single gene to the analysis of multiple genes and even completed genomes. The simplest method of scaling up is to use familiar analysis methods on a larger scale and this is the most popular approach. However, duplications and losses of genes along with horizontal gene transfer (HGT) can lead to a situation where there is only an indirect relationship between gene and genome phylogenies. In this study we examine five widely-used approaches and their variants to see if indeed they are more-or-less saying the same thing. In particular, we focus on Conditioned Reconstruction as it is a method that is designed to work well even if HGT is present.ResultsWe confirm a previous suggestion that this method has a systematic bias. We show that no two methods produce the same results and most current methods of inferring genome phylogenies produce results that are significantly different to other methods.ConclusionWe conclude that genome phylogenies need to be interpreted differently, depending on the method used to construct them.
| S-EPMC2592249 | biostudies-literature
Project description:MotivationToday, we know the function of only a small fraction of the protein sequences predicted from genomic data. This problem is even more salient for bacteria, which represent some of the most phylogenetically and metabolically diverse taxa on Earth. This low rate of bacterial gene annotation is compounded by the fact that most function prediction algorithms have focused on eukaryotes, and conventional annotation approaches rely on the presence of similar sequences in existing databases. However, often there are no such sequences for novel bacterial proteins. Thus, we need improved gene function prediction methods tailored for prokaryotes. Recently, transformer-based language models - adopted from the natural language processing field - have been used to obtain new representations of proteins, to replace amino acid sequences. These representations, referred to as protein embeddings, have shown promise for improving annotation of eukaryotes, but there have been only limited applications on bacterial genomes.ResultsTo predict gene functions in bacteria, we developed SAP, a novel synteny-aware gene function prediction tool based on protein embeddings from state-of-the-art protein language models. SAP also leverages the unique operon structure of bacteria through conserved synteny. SAP outperformed both conventional sequence-based annotation methods and state-of-the-art methods on multiple bacterial species, including for distant homolog detection, where the sequence similarity to the proteins in the training set was as low as 40%. Using SAP to identify gene functions across diverse enterococci, of which some species are major clinical threats, we identified 11 previously unrecognized putative novel toxins, with potential significance to human and animal health.
| S-EPMC10187222 | biostudies-literature
Project description:Word-based or 'alignment-free' sequence comparison has become an active research area in bioinformatics. While previous word-frequency approaches calculated rough measures of sequence similarity or dissimilarity, some new alignment-free methods are able to accurately estimate phylogenetic distances between genomic sequences. One of these approaches is Filtered Spaced Word Matches. Here, we extend this approach to estimate evolutionary distances between complete or incomplete proteomes; our implementation of this approach is called Prot-SpaM. We compare the performance of Prot-SpaM to other alignment-free methods on simulated sequences and on various groups of eukaryotic and prokaryotic taxa. Prot-SpaM can be used to calculate high-quality phylogenetic trees for dozens of whole-proteome sequences in a matter of seconds or minutes and often outperforms other alignment-free approaches. The source code of our software is available through Github: https://github.com/jschellh/ProtSpaM.
| S-EPMC6436989 | biostudies-literature