Synteny block identification aims to identify homologous chromosomal regions and relations between genomes. The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, even when no such gene is present. This capability means that synteny-based methods are far more effective than sequence similarity-based methods in identifying true-negatives, a necessity for studying gene loss and gene transposition.
Combines gene content and gene order information of homologous genomic segments into profiles to detect highly degenerated homology relations within and between genomes. Unlike other tools, i-ADHoRe can process the Ensembl data set, containing 49 species, in 1 h. Furthermore, the profile search is more sensitive to detect degenerate genomic homology than chaining pairwise collinearity information based on transitive homology. Due to the further optimization of many algorithmic steps, the current version of i-ADHoRe 3.0 is roughly 30 times faster than the previous version. In addition, i-ADHoRe 3.0 can now take advantage of a parallel computing platform, reducing the runtime even further.
A software package for detecting, displaying, and querying syntenic relationships between sequenced chromosomes and/or fingerprint contig physical maps. SyMAP uses MUMmer to compute the raw hits between the two genomes, which are then clustered and filtered using the optional gene annotation. The filtered hits are input to the synteny algorithm, which was designed to discover duplicated regions and form larger-scale synteny blocks, where intervening micro-rearrangements are allowed. SyMAP provides extensive interactive Java displays at all levels of resolution along with simultaneous displays of multiple aligned pairs. The synteny blocks from multiple chromosomes may be displayed in a high-level dot plot or three-dimensional view, and the user may then drill down to see the details of a region, including the alignments of the hits to the gene annotation.
Scans multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and aligns these regions using genes as anchors. MCscan takes the predicted pairwise segments from dynamic programming (DAGchainer in particular) and then try to build consensus segments from a set of related, overlapping segments. It is intended as an easy-to-use and quick way to identify conserved gene arrays both within the same genome and across different genomes.
A toolkit that implements an adjusted MCScan algorithm for detection of synteny and collinearity and incorporates 14 computer programs for visualizing and analyzing identified synteny and collinearity. MCScanX scans multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and aligns these regions using genes as anchors. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families.
Simplifies studies on comparative genomics. Synteny Portal is an online application offering easy construction of synteny blocks, intuitive graphical representation with a high-quality image format and easy-to-use querying and browsing functionalities. It enables a user with a lack of computational skills to perform comparative genomic analyses and to download the details of these analyses.
A multiple alignment tool for whole genomes. Mugsy uses Nucmer for pairwise alignment, a custom graph based segmentation procedure for identifying collinear regions, and the segment-based progressive multiple alignment strategy from Seqan::TCoffee. Mugsy does not require a reference sequence, can align mixtures of assembled draft and completed genome data, and is robust in identifying a rich complement of genetic variation including duplications, rearrangements, and large-scale gain and loss of sequence.
It is able to quickly match a set of contigs onto a related genome, order the contigs according to their matches and display the result in an interactive synteny plot. The matching, however, is not restricted to contigs, such that the program can also be used to visualize the synteny of two finished genomes. The software is open source and available within the Comparative Genomics – Contig Arrangement Toolsuite (CG-CAT) on the Bielefeld Bioinformatics Server (BiBiServ).
Computes chains of syntenic genes found within complete genome sequences. Given the positions of protein-coding genes along genomic sequence and probability values for protein alignments between genes, DAGchainer identifies chains of gene pairs sharing conserved order between genomic regions, by identifying paths through a directed acyclic graph (DAG). These chains of collinear gene pairs can represent segmentally duplicated regions and genes within a single genome or syntenic regions between related genomes.
A flexible dynamic programming algorithm for the identification of segments having multiple homologous features. We model the probability of observing putative segmental homologies by chance and incorporate our findings into the parameterization of the algorithm and the statistical evaluation of its output. Combined, these findings allow segmental homologies to be identified in comparisons within and between genomic maps in a rigorous, rapid, and automated fashion.
Most synteny block reconstruction algorithms use genes shared over all genomes to construct the synteny blocks for multiple genomes. However, the number of genes shared among all genomes quickly decreases with the increase in the number of genomes. We propose DRIMM-Synteny to address this bottleneck. The algorithm devises the first A-Bruijn graph approach that does not require a threading step and substituting it with an alternative genome transformation step.
An interactive web server for automatic multi-species comparative genomics analyses based on personal datasets or pre-inserted public datasets. AutoGRAPH automatically identifies conserved segments (CS) and breakpoint regions, assesses the conservation of marker/gene order between organisms, constructs synteny maps for two to three species and generates high-quality, interactive displays facilitating the identification of chromosomal rearrangements. AutoGRAPH can also be used for the integration and comparison of several types of genomic resources (meiotic maps, radiation hybrid maps and genome sequences) for a single species, making AutoGRAPH a versatile tool for comparative genomics analysis.
Allows users to analyze the evolution of orthologous archaeal and bacterial gene clusters. Absynte is designed to display local syntenies in completely sequenced prokaryotic chromosomes. It assists users to extract, compare and predict orthologous gene clusters originating from any combination of sequenced prokaryotic organisms. This software can be used to calculate synteny maps and to provide contextual gene information.
Uses a novel scoring scheme based on stochastic models. OSfinder takes as input the positions of short homologous regions (also referred to as anchors) and explicitly discriminates orthologous anchors from non-orthologous anchors by using Markov chain models which represent respective geometric distributions of lengths of orthologous and non-orthologous anchors. Such stochastic modeling makes it possible to optimize parameter values by maximizing the likelihood of the input dataset, and to automate the setting of the optimal parameter values. OSfinder can be applied not only in pairwise genome comparisons, but also in multiple genome comparisons. There is no limit to the number of genomes which can be compared.
Detects synteny between diverged genomes. Proteny operates on the amino acid sequence level to be insensitive to codon usage adaptations and clusters groups of exons disregarding order to handle diversity in genomic ordering between genomes. Furthermore, Proteny assigns significance levels to the syntenic clusters such that they can be selected on statistical grounds. Finally, Proteny provides novel ways to visualize results at different scales, facilitating the exploration and interpretation of syntenic regions.
Enables the discovery, ranking, and clustering of colinear syntenic blocks (CSBs) identified in large genomic datasets. CSBFinder includes a graphical user interface for uploading dataset files, for setting the parameters, and for visualizing the obtained results. It can also be executed through a command line interface.
A fast, efficient and user-friendly tool to reconstruct synteny blocks between (complex) genomes harboring different levels of synteny conservation. Its main properties are the followings: (i) it makes multiple pairwise comparisons and traces information shared by each pair of genomes; (ii) it defines syntenic homologous genes by computing protein sequence similarity (with fastp and blastp) and by taking into account the gene order information; (iii) it reconstructs synteny blocks based on syntenic homologous genes and not on DNA alignment; (iv) and it allows synteny blocks to be overlapping, included in one another or duplicated. SynChro is a simple algorithm that is not meant to bring new theoretical advances over existing and more sophisticated tools in the field of synteny block identification. The interests of SynChro lie in the all in one package with few parameters, rapid execution time and several useful visualization tools that are more flexible than that of other existing methods.
Identifies all syntenic regions to a given gene in a user-selected set of genomes, regardless of whether the gene is still present in that region. SynFind is powered by an algorithm that calculates synteny score between a pair of regions. Performance-wise, SynFind has higher sensitivity but lower purity compared with competing tools when validated against manually curated sets. Integrated with the CoGe online platform and powered by the iPlant project, syntenic queries can now be performed in an interactive manner and retrieved for downstream analyses through SynFind in a scalable and reproducible manner. SynFind is an important tool for assessing genome dynamics including gene transpositions, impact of genome duplications, and correlation to functional changes across a set of related taxa of interest.
A flexible and scalable tool for the identification of conserved gene orders across multiple species over long evolutionary distances. CYNTENATOR does not depend on nucleotide-level alignments and a priori homology assignment. It implements an improved scoring function that utilizes the underlying phylogeny. CYNTENATOR represents a flexible tool to study chromosome rearrangements and genome evolution.
Provides an open source platform to take advantage of long patterns, cluster computing, and novel hash algorithms to produce accurate anchors across multiple genomes with computational efficiency significantly greater than existing methods. Two advanced features of Murasaki are (1) adaptive hash function generation, which enables efficient use of arbitrary mismatch patterns (spaced seeds) and therefore the comparison of multiple mammalian genomes in a practical amount of computation time, and (2) parallelizable execution that decreases the required wall-clock and CPU times. Murasaki can perform a sensitive anchoring of eight mammalian genomes (human, chimp, rhesus, orangutan, mouse, rat, dog, and cow) in 21 hours CPU time (42 minutes wall time).
Compares multiple genomes and performs sensitivity analysis for synteny block detection and for the subsequent computation of reversal distances. Cinteny can also be used to interactively browse syntenic blocks conserved in multiple genomes, to facilitate genome annotation and validation of assemblies for newly sequenced genomes, and to construct and assess phylogenomic trees. In particular, Cinteny provides: i) integration of synteny browsing with assessment of evolutionary distances for multiple genomes; ii) flexibility to adjust the parameters and re-compute the results on-the-fly; iii) ability to work with user provided data, such as orthologous genes, sequence tags or other conserved markers.