Package: wgd
wgd v2: a suite tool of WGD inference and timingHengchi Chen, Arthur Zwaenepoel, Yves Van de PeerBioinformatics & Evolutionary Genomics Group, VIB-UGent Center for Plant Systems BiologyIntroduction|Installation|Parameters|Usage|Illustration|Documentation|Citationwgd v2is a python package upgraded from the originalwgdpackage aiming for the inference and timing of ancient whole-genome duplication (WGD) events. For the propose of illustrating the principle and usage ofwgd v2, we compiled this documentation. Below we first gave an introduction over the scope and mechanism ofwgd v2and then the practical information pertaining to the installation and usage. An examplar workflow is provided in the tutorial section on how to seek evidence for a putative WGD event and perform proper timing with a freshly obtained genome assembly in hand. For those who are interested in more theoretical details, we recommend turning to our paper and book chapter for more detailed description and insightful discussions. If you usewgd v2in your research, please cite us as suggested inCitationsection.IntroductionPolyploidizations, the evolutionary process that the entire genome of an organism is duplicated, also named as whole-genome duplications (WGDs), occur recurrently across the tree of life. There are two modes of polyploidizations, autopolyploidizations and allopolyploidizations. Autopolyploidizations are the duplication of the same genome, resulting in two identical subgenomes at the time it emerged. While the allopolyploidizations are normally achieved in two steps, first the hybridization between two different species, resulting in the arising of transient homoploidy,second the duplication of the homoploidy, resulting in the emergence of allopolyploidy. Due to the unstability and unbalanced tetrasomic inheritance, for instance the nuclear-cytoplasmic incompatibility, the polyploidy genome will then experience a process called diploidization, also named as fractionation, during which a large portion of gene duplicates will get lost and only a fraction can be retained. The traces of polyploidizations can be thus unearthed from these retained gene duplicates. Three approaches based on gene duplicates, namely,KSmethod, gene tree - species tree reconciliation method and synteny method, are commonly used in detecting evidence for WGDs. The gene tree - species tree reconciliation method is not within the scope ofwgd v2, but we kindly refer readers who are interested to the phylogenomic program developed by Arthur Zwaenepoel namedWHALEand the associatedpaperfor more technical and theoretical details.TheKSmethod is established on a model of gene family evolution that each gene family is allowed to evolve via gene duplication and loss. Note that the gene family here is assumed to be the cluster of all genes descended from an ancestral gene in a single genome. Recovering the gene tree of such gene family informs the timing, scilicet the age, of gene duplication events. The age refered here, is not in real geological time, but in the unit of evolutionary distance, i.e., the number of substitutions per site. When the evolutionary rate remains approximately constant, the evolutionary distance is then supposed to be proportional to the real evolutionary time. The synonymous distanceKS, the number of synonymous substitutions per synonymous site, is such candidate that synonymous substitutions would not incur the change of amino acid and are thus regarded as neutral, which according to the neutral theory should occur in constant rate. Given a model of gene family that allows the gene to duplicate and get lost in a fixed rate, one can derive that the probability density function of theKSage distribution of retained gene duplicates is a quasi-exponential function that most retained gene duplicates are recently borned with ~0 age while as the age going older the associated number of retained gene duplicates decay quasi-exponentially. Therefore, the occurance of large-scale gene duplication events, for instane WGDs, with varied retention rate, will leave an age peak from the burst of gene duplicates in a short time-frame upon the initial age distribution, and can be unveiled from mixture modeling analysis. However, WGDs identified from the paralogousKSage distributions can only inform the WGD timing in the time-scale of that specific species, which is not comparable in the phylogenetic context. Only with the orthologousKSage distributions, which convert the estimated body from paralogues to orthologues and inform the relative timing of speciation events, can we decipher the phylogenetic placement of WGDs after proper rate correction.wgd v2is such program that helps users construct paralogous and orthologousKSage distributions and realize both the identification and placement of WGDs.In the premise of phylogenetically located WGDs, the absolute age (in geological time) of WGDs can also be inferred from those WGD-retained gene duplicates, although there has been no easy or straightforward pipeline for this job so far. Inwgd v2, we developed a feasible integrated pipleline for absolute dating of WGDs. The pipeline can be roughly divided into three main steps. 1) The construction of anchorKSdistribution and the delineation of crediableKSrange adopted for phylogenetic dating, usingwgd dmd,wgd ksd,wgd synandwgd peak. Note that here we only consider genome assembly because for transcriptome assembly it's impossible to distinguish WGD-derived duplicates from small-scale duplication-derived duplicates, which happened in a continuous time-frame instead of only a separate short time-frame and thus reflects the duration of that branch rather than the time at which WGD occurred. 2) The formulation of a starting tree used in the phylogenetic dating, composed of a few species and annotated with fossil calibration information. This step is essential for the result of absolute WGD dating that we suggest users of taking great caution to assure the tree topology and proper bounds for fossil calibrations. 3) The construction of orthogroups consisting of collinear duplicates of the focal species and their reciprocal best hits (RBHs) against other species in the starting tree and the phylogenetic dating using a molecular dating program for instancemcmctree, via programwgd dmdandwgd focus. We recommend the usage of Bayesian molecular dating programmcmctree, which provides a variety of different substitution and rate models. Nonetheless, we urge users to set prior distribution of different parameters with caution and assure adequate sampling of different parameters.InstallationThe easiest way to installwgd v2is using PYPI. Note that if you want to get the latest update, we suggest installing from the source, since the update on PYPI will be delayed compared to here of source.pip install wgdTo installwgd v2in a virtual environment, the following command lines could be used.git clone <wgd repo>
cd wgd
virtualenv -p=python3 ENV (or python3 -m venv ENV)
source ENV/bin/activate
pip install -r requirements.txt
pip install .When met with permission problem in installation, please try the following command line.pip install -e .If multiply versions ofwgdwere installed in the system, please add the right path of interested version into the environment variables, for exampleexport PATH="$PATH:~/.local/bin/wgd"Note that the version ofnumpyis important (for many other packages are the same of course), especially forfastclusterpackage. In our test, thenumpy1.19.0 works fine onpython3.6/8. If you met some errors or warnings aboutnumpy, maybe considering pre-installnumpyas 1.19.0 or other close-by versions before you installwgd.ParametersThere are 7 main programs inwgd v2:dmd,focus,ksd,mix,peak,syn,viz. Hereafter we will provide a detailed elucidation on each of the program and its associated parameters. Please refer to theUsagefor the scenarios to which each parameter applies.The programwgd dmdcan realize the delineation of whole paranome, RBHs (Reciprocal Best Hits), MRBHs (Multiple Reciprocal Best Hits), orthogroups and some other orthogroup-related functions, including circumscription of nested single-copy orthogroups (NSOGs), unbiased test of single-copy orthogroups (SOGs) over missing inparalogs, construction of BUSCO-guided single-copy orthogroups (SOGs),and the collinear coalescence inference of phylogeny.wgd dmd sequences (option)
--------------------------------------------------------------------------------
-o, --outdir, the output directory, default wgd_dmd
-t, --tmpdir, the temporary working directory, default None, if None was given, the tmpdir would be assigned random names in current directory and automately removed at the completion of program, else the tmpdir would be kept
-c, --cscore, the c-score to restrict the homolog similarity of MRBHs, default None, if None was given, the c-score funcion wouldn't be activated, else expecting a decimal within the range of 0 and 1
-I, --inflation, the inflation factor for MCL program, default 2.0, with higher value leading to more but smaller clusters
-e, --eval, the e-value cut-off for similarity in diamond and/or hmmer, default 1e-10
--to_stop, flag option, whether to translate through STOP codons, if the flag was set, translation will be terminated at the first in-frame stop codon, else a full translation continuing on passing any stop codons would be initiated
--cds, flag option, whether to only translate the complete CDS that starts with a valid start codon and only contains a single in-frame stop codon at the end and must be dividable by three, if the flag was set, only the complete CDS would be translated
-f, --focus, the species to be merged on local MRBHs, default None, if None was given, the local MRBHs wouldn't be inferred
-ap, --anchorpoints, the anchor points data file from i-adhore for constructing the orthogroups with anchor pairs, default None
-sm, --segments, the segments data file used in collinear coalescence analysis if initiated, default None
-le, --listelements, the listsegments data file used in collinear coalescence analysis if initiated, default None
-gt, --genetable, the gene table datafile used in collinear coalescence analysis if initiated, default None
-coc, --collinearcoalescence, flag option, whether to initiate the collinear coalescence analysis, if the flag was set, the analysis would be initiated
-kf, --keepfasta, flag option, whether to output the sequence information of MRBHs, if the flag was set, the sequences of MRBHs would be in output
-kd, --keepduplicates, flag option, whether to allow the same gene to occur in different MRBHs (only meaningful when the cscore was used), if the flag was set, the same gene could be assigned to different MRBHs
-gm, --globalmrbh, flag option, whether to initiate global MRBHs construction, if the flag was set, the --focus option would be ignored and only global MRBHs would be built
-n, --nthreads, the number of threads to use, default 4
-oi, --orthoinfer, flag option, whether to initiate orthogroup infernece, if the flag was set, the orthogroup infernece program would be initiated
-oo, --onlyortho, flag option, whether to only conduct orthogroup infernece, if the flag was set, only the orthogroup infernece pipeline would be performed while the other analysis wouldn't be initiated
-gn, --getnsog, flag option, whether to initiate the searching for nested single-copy gene families (NSOGs) (only meaningful when the orthogroup infernece pipeline was activated), if the flag was set, additional NSOGs analysis would be performed besides the basic orthogroup infernece
-tree, --tree_method, which gene tree inference program to invoke (only meaningful when the collinear coalescence, gene-to-family assignment or NSOGs analysis were activated), default fasttree
-ts, --treeset, the parameters setting for gene tree inference, default None, this option can be provided multiple times
-mc, --msogcut, the ratio cutoff for mostly single-copy family (meaningful when activating the orthogroup infernece pipeline) and species representation in collinear coalescence analysis, default 0.8.
-ga, --geneassign, flag option, whether to initiate the gene-to-family assignment analysis, if the flag was set, the analysis would be initiated
-sa, --seq2assign, the queried sequences data file in gene-to-family assignment analysis, default None, this option can be provided multiple times
-fa, --fam2assign, the queried familiy data file in gene-to-family assignment analysis, default None
-cc, --concat, flag option, whether to initiate the concatenation pipeline for orthogroup infernece, if the flag was set, the analysis would be initiated
-te, --testsog, flag option, whether to initiate the unbiased test of single-copy gene families, if the flag was set, the analysis would be initiated
-bs, --bins, the number of bins divided in the gene length normalization, default 100
-np, --normalizedpercent, the percentage of upper hits used for gene length normalization, default 5
-nn, --nonormalization, flag option, whether to call off the normalization, if the flag was set, no normalization would be conducted
-bsog, --buscosog, flag option, whether to initiate the busco-guided single-copy gene family analysis, if the flag was set, the analysis would be initiated
-bhmm, --buscohmm, the HMM profile datafile in the busco-guided single-copy gene family analysis, default None
-bctf, --buscocutoff, the HMM score cutoff datafile in the busco-guided single-copy gene family analysis, default NoneThe programwgd focuscan realize the concatenation-based and coalescence-based phylogenetic inference and phylogenetic dating of WGDs etc.wgd focus families sequences (option)
--------------------------------------------------------------------------------
-o, --outdir, the output directory, default wgd_focus
-t, --tmpdir, the temporary working directory, default None, if None was given, the tmpdir will be assigned random names in current directory and automately removed at the completion of program, else the tmpdir would be kept
-n, --nthreads, the number of threads to use, default 4
--to_stop, flag option, whether to translate through STOP codons, if the flag was set, translation will be terminated at the first in-frame stop codon, else a full translation continuing on past any stop codons would be initiated
--cds, flag option, whether to only translate the complete CDS that starts with a valid start codon and only contains a single in-frame stop codon at the end and must be dividable by three, if the flag was set, only the complete CDS would be translated
--strip_gaps, flag option, whether to drop all gaps in multiple sequence alignment, if the flag was set, all gaps would be dropped
-a, --aligner, which alignment program to use, default mafft
-tree, --tree_method, which gene tree inference program to invoke, default fasttree
-ts, --treeset, the parameters setting for gene tree inference, default None, this option can be provided multiple times
--concatenation, flag option, whether to initiate the concatenation-based species tree inference, if the flag was set, concatenation-based species tree would be infered
--coalescence, flag option, whether to initiate the coalescence-based species tree inference, if the flag was set, coalescence-based species tree would be infered
-sp, --speciestree, species tree datafile for dating, default None
-d, --dating, which molecular dating program to use, default none
-ds, --datingset, the parameters setting for dating program, default None, this option can be provided multiple times
-ns, --nsites, the nsites information for r8s dating, default None
-ot, --outgroup, the outgroup information for r8s dating, default None
-pt, --partition, flag option, whether to initiate partition dating analysis for codon, if the flag was set, an additional partition dating analysis would be initiated
-am, --aamodel, which protein model to be used in mcmctree, default poisson
-ks, flag option, whether to initiate Ks calculation for homologues in the provided orthologous gene family
--annotation, which annotation program to use, default None
--pairwise, flag option, whether to initiate pairwise Ks estimation, if the flag was set, pairwise Ks values would be estimated
-ed, --eggnogdata, the eggnog annotation datafile, default None
--pfam, which option to use for pfam annotation, default None
--dmnb, the diamond database for annotation, default None
--hmm, the HMM profile for annotation, default None
--evalue, the e-value cut-off for annotation, default 1e-10
--exepath, the path to the interproscan executable, default None
-f, --fossil, the fossil calibration information in Beast, default ('clade1;clade2', 'taxa1,taxa2;taxa3,taxa4', '4;5', '0.5;0.6', '400;500')
-rh, --rootheight, the root height calibration info in Beast, default (4,0.5,400)
-cs, --chainset, the parameters of MCMC chain in Beast, default (10000,100)
--beastlgjar, the path to beastLG.jar, default None
--beagle, flag option, whether to use beagle in Beast, if the flag was set, beagle would be used
--protcocdating, flag option, whether to only initiate the protein-concatenation-based dating analysis, if the flag was set, the analysis would be initiated
--protdating, flag option, whether to only initiate the protein-based dating analysis, if the flag was set, the analysis would be initiatedThe programwgd ksdcan realize the construction ofKSage distribution and rate correction.wgd ksd families sequences (option)
--------------------------------------------------------------------------------
-o, --outdir, the output directory, default wgd_ksd
-t, --tmpdir, the temporary working directory, default None, if None was given, the tmpdir will be assigned random names in current directory and automately removed at the completion of program, else the tmpdir would be kept
-n, --nthreads, the number of threads to use, default 4
--to_stop, flag option, whether to translate through STOP codons, if the flag was set, translation will be terminated at the first in-frame stop codon, else a full translation continuing on past any stop codons would be initiated
--cds, flag option, whether to only translate the complete CDS that starts with a valid start codon and only contains a single in-frame stop codon at the end and must be dividable by three, if the flag was set, only the complete CDS would be translated
--pairwise, flag option, whether to initiate pairwise Ks estimation, if the flag was set, pairwise Ks values would be estimated
--strip_gaps, flag option, whether to drop all gaps in multiple sequence alignment, if the flag was set, all gaps would be dropped
-a, --aligner, which alignment program to use, default mafft 
-tree, --tree_method, which gene tree inference program to invoke, default fasttree
--tree_options, options in tree inference as a comma separated string, default None
--node_average, flag option, whether to initiate node-average way of de-redundancy instead of node-weighted, if the flag was set, the node-averaging de-redundancy would be initiated
-sr, --spair, the species pair to be plotted, default None, this option can be provided multiple times
-sp, --speciestree, the species tree to perform rate correction, default None, if None was given, the rate correction analysis would be called off
-rw, --reweight, flag option, whether to recalculate the weight per species pair, if the flag was set, the weight would be recalculated
-or, --onlyrootout, flag option, whether to only conduct rate correction using the outgroup at root as outgroup, if the flag was set, only the outgroup at root would be used as outgroup
-epk, --extraparanomeks, extra paranome Ks data to plot in the mixed Ks distribution, default None
-ap, --anchorpoints, anchorpoints.txt file to plot anchor Ks in the mixed Ks distribution, default None
-pk, --plotkde, flag option, whether to plot kde curve of orthologous Ks distribution over histogram in the mixed Ks distribution, if the flag was set, the kde curve would be plotted
-pag, --plotapgmm, flag option, whether to perform and plot mixture modeling of anchor Ks in the mixed Ks distribution, if the flag was set, the mixture modeling of anchor Ks would be plotted
-pem, --plotelmm, flag option, whether to perform and plot elmm mixture modeling of paranome Ks in the mixed Ks distribution, if the flag was set, the elmm mixture modeling of paranome Ks would be plotted
-c, --components, the range of the number of components to fit in anchor Ks mixture modeling, default (1,4)
-xl, --xlim, the x axis limit of Ks distribution
-yl, --ylim, the y axis limit of Ks distribution
-ado, --adjustortho, flag option, whether to adjust the histogram height of orthologous Ks as to match the height of paralogous Ks, if the flag was set, the adjustment would be conducted
-adf, --adjustfactor, the adjustment factor of orthologous Ks, default 0.5
-oa, --okalpha, the opacity of orthologous Ks distribution in mixed plot, default 0.5
-fa, --focus2all, set focal species and let species pair to be between focal and all the remaining species, default None
-ks, --kstree, flag option, whether to infer Ks tree, if the flag was set, the Ks tree inference analysis would be initiated
-ock, --onlyconcatkstree, flag option, whether to only infer Ks tree under concatenated alignment, if the flag was set, only the Ks tree under concatenated alignment would be calculated
-cs, --classic, flag option, whether to draw mixed Ks plot in a classic manner where the full orthologous Ks distribution is drawed, if the flag was set, the classic mixed Ks plot would be drawn
-ta, --toparrow, flag option, whether to adjust the arrow to be at the top of the plot, instead of being coordinated as the KDE of the orthologous Ks distribution, if the flag was set, the arrow would be set at the topThe programwgd mixcan realize the mixture model clustering analysis ofKSage distribution.wgd mix ks_datafile (option)
--------------------------------------------------------------------------------
-f, --filters, the cutoff alignment length, default 300
-r, --ks_range, the Ks range to be considered, default (0, 5)
-b, --bins, the number of bins in Ks distribution, default 50
-o, --outdir, the output directory, default wgd_mix
--method, which mixture model to use, default gmm
-n, --components, the range of the number of components to fit, default (1, 4)
-g, --gamma, the gamma parameter for bgmm models, default 0.001
-ni, --n_init, the number of k-means initializations, default 200
-mi, --max_iter, the maximum number of iterations, default 200The programwgd peakcan realize the search of crediableKSrange used in WGD dating.wgd peak ks_datafile (option)
--------------------------------------------------------------------------------
-ap, --anchorpoints, the anchor points datafile, default None
-sm, --segments, the segments datafile, default None
-le, --listelements, the listsegments datafile, default None 
-mp, --multipliconpairs, the multipliconpairs datafile, default None
-o, --outdir, the output directory, default wgd_peak
-af, --alignfilter, cutoff for alignment identity, length and coverage, default 0.0, 0, 0.0
-r, --ksrange, range of Ks to be analyzed, default (0, 5)
-bw, --bin_width, bandwidth of Ks distribution, default 0.1
-ic, --weights_outliers_included, flag option, whether to include Ks outliers, if the flag was set, Ks outliers would be included in the analysis
-m, --method, which mixture model to use, default gmm
--seed, random seed given to initialization, default 2352890
-ei, --em_iter, the number of EM iterations to perform, default 200
-ni, --n_init, the number of k-means initializations, default 200
-n, --components, the range of the number of components to fit, default (1, 4)
-g, --gamma, the gamma parameter for bgmm models, default 1e-3
--boots, the number of bootstrap replicates of kde, default 200
--weighted, flag option, whether to use node-weighted method of de-redundancy, if the flag was set, the node-weighted method would be used
-p, --plot, the plotting method to be used, default identical
-bm, --bw_method, the bandwidth method to be used in analyzing the peak of WGD dates, default silverman
--n_medoids, the number of medoids to fit, default 2
-km, --kdemethod, the kde method to be used in analyzing the peak of WGD dates, kmedoids analysis or the basic Ks plotting, default scipy
--n_clusters, the number of clusters to plot Elbow loss function, default 5
--kmedoids, flag option, whether to initiate K-Medoids clustering analysis, if the flag was set, the analysis would be initiated
-gd, --guide, the regime residing anchors, default segment
-prct, --prominence_cutoff, the prominence cutoff of acceptable peaks in peak finding steps, default 0.1
-rh, --rel_height, the relative height at which the peak width is measured, default 0.4
-kd, --kstodate, the range of Ks to be dated in heuristic search, default (0.5, 1.5)
-xl, --xlim, the x axis limit of GMM Ks distribution
-yl, --ylim, the y axis limit of GMM Ks distribution
--manualset, flag option, whether to output anchor pairs with manually set Ks range, if the flag was set, manually set Ks range would be outputted
--ci, the confidence level of log-normal distribution to date, default 95
--hdr, the highest density region (HDR) applied in the segment-guided anchor pair Ks distribution, default 95
--heuristic, flag option, whether to initiate heuristic method of defining CI for dating, if the flag was set, the heuristic method would be initiated
-kc, --kscutoff, the Ks saturation cutoff in dating, default 5
--showci, flag option, whether to show CI for the original anchor Ks GMM analysis, if the flag was set, it would be showed
--keeptmpfig, flag option, whether to keep temporary figures in peak finding process, if the flag was set, those figures would be keptThe programwgd syncan realize the intra- and inter-specific synteny inference.wgd syn families gffs (option)
--------------------------------------------------------------------------------
-ks, --ks_distribution, ks distribution datafile, default None
-o, --outdir, the output directory, default wgd_syn
-f, --feature, the feature for parsing gene IDs from GFF files, default gene
-a, --attribute, the attribute for parsing the gene IDs from the GFF files, default ID
-atg, --additionalgffinfo, the feature and attribute information of additional gff3 files if different in the format of (feature;attribute)', default None
-ml, --minlen, the minimum length of a scaffold to be included in dotplot, default -1, if -1 was set, the 10% of the longest scaffold would be set
-ms, --maxsize, the maximum family size to be included, default 200
-r, --ks_range, the Ks range in colored dotplot, default (0, 5)
--iadhore_options, the parameter setting in iadhore, default as a string of length zero
-mg, --minseglen, the minimum length of segments to include in ratio if <= 1, default 10000
-kr, --keepredun, flag option, whether to keep redundant multiplicons, if the flag was set, the redundant multiplicons would be kept
-mgn, --mingenenum, the minimum number of genes for a segment to be considered, default 30
-ds, --dotsize, the dot size in dot plot, default 0.3
-aa, --apalpha, the opacity of anchor dots, default 1
-ha, --hoalpha, the opacity of homolog dots, default 0
-srt, --showrealtick, flag option, whether to show the real tick in genes or bases, if the flag was set, the real tick would be showed
-tls, --ticklabelsize, the label size of tick, default 5The programwgd vizcan realize the visualization ofKSage distribution and synteny.wgd viz (option)
--------------------------------------------------------------------------------
-d, --datafile, the Ks datafile, default None
-o, --outdir, the output directory, default wgd_viz
-sr, --spair, the species pair to be plotted, default None, this option can be provided multiple times
-fa, --focus2all, set focal species and let species pair to be between focal and all the remaining species, default None
-gs, --gsmap, the gene name-species name map, default None
-sp, --speciestree, the species tree to perform rate correction, default None, if None was given, the rate correction analysis would be called off
-pk, --plotkde, flag option, whether to plot kde curve upon histogram, if the flag was set, kde curve would be added
-rw, --reweight, flag option, whether to recalculate the weight per species pair, if the flag was set, the weight would be recalculated
-or, --onlyrootout, flag option, whether to only conduct rate correction using the outgroup at root as outgroup, if the flag was set, only the outgroup at root would be used as outgroup
-iter, --em_iterations, the maximum EM iterations, default 200
-init, --em_initializations, the maximum EM initializations, default 200
-prct, --prominence_cutoff, the prominence cutoff of acceptable peaks, default 0.1
-rh, --rel_height, the relative height at which the peak width is measured, default 0.4
-sm, --segments, the segments data file, default None
-ml, --minlen, the minimum length of a scaffold to be included in dotplot, default -1, if -1 was set, the 10% of the longest scaffolds will be set
-ms, --maxsize, the maximum family size to be included, default 200
-ap, --anchorpoints, the anchor points datafile, default None
-mt, --multiplicon, the multiplicons datafile, default None
-gt, --genetable, the gene table datafile, default None
-mg, --minseglen, the minimum length of segments to include, in ratio if <= 1, default 10000
-mgn, --mingenenum, the minimum number of genes for a segment to be considered, default 30
-kr, --keepredun, flag option, whether to keep redundant multiplicons, if the flag was set, the redundant multiplicons would be kept
-epk, --extraparanomeks, extra paranome Ks data to plot in the mixed Ks distribution, default None
-pag, --plotapgmm, flag option, whether to conduct and plot mixture modeling of anchor Ks in the mixed Ks distribution, if the flag was set, the mixture modeling of anchor Ks would be conducted and plotted
-pem, --plotelmm, flag option, whether to conduct and plot elmm mixture modeling of paranome Ks in the mixed Ks distribution, if the flag was set, the elmm mixture modeling of paranome Ks would be conducted and plotted
-c, --components, the range of the number of components to fit in anchor Ks mixture modeling, default (1,4)
-psy, --plotsyn, flag option, whether to initiate the synteny plot, only when the flag was set, the synteny plot would be produced
-ds, --dotsize, the dot size in dot plot, default 0.3
-aa, --apalpha, the opacity of anchor dots, default 1
-ha, --hoalpha, the opacity of homolog dots, default 0
-srt, --showrealtick, flag option, whether to show the real tick in genes or bases, if the flag was set, the real tick would be showed
-tls, --ticklabelsize, the label size of tick, default 5
-xl, --xlim, the x axis limit of Ks distribution
-yl, --ylim, the y axis limit of Ks distribution
-ado, --adjustortho, flag option, whether to adjust the histogram height of orthologous Ks as to match the height of paralogous Ks, if the flag was set, the adjustment would be conducted
-adf, --adjustfactor, the adjustment factor of orthologous Ks, default 0.5
-oa, --okalpha, the opacity of orthologous Ks distribution in mixed plot, default 0.5
-cs, --classic, flag option, whether to draw mixed Ks plot in a classic manner where the full orthologous Ks distribution is drawed, if the flag was set, the classic mixed Ks plot would be drawn
-ta, --toparrow, flag option, whether to adjust the arrow to be at the top of the plot, instead of being coordinated as the KDE of the orthologous Ks distribution, if the flag was set, the arrow would be set at the top
-na, --nodeaveraged, flag option, whether to use node-averaged method for de-redundancy, if the flag was set, the node-averaged method would be initiatedUsageHere we provided the basic usage for each program and the relevant parameters and suggestions on parameterization.wgd dmdThe delineation of whole paranomewgd dmd Aquilegia_coerulea -I 2 -e 1e-10 -bs 100 -np 5 (-nn) (--to_stop) (--cds) (-o wgd_dmd) (-t working_tmp)Note that we don't provide the data of this coding sequence (cds) fileAquilegia_coeruleabut it can be easily downloaded atPhytozome(same for other Usage doc). Note that in the issues some users didn't download theAcoerulea_322_v3.1.cds_primaryTranscriptOnly.fa.gzbut instead theAcoerulea_322_v3.1.cds.fa.gzfile. For the construction of whole paranomeKSdistribution,only one transcript (the primary one) per gene should be includedsuch that theKSis really indicating the age of gene duplication event, instead of alternative splicing. Transcriptome data should be carefully treated with de-redundancy so as to reduce the false positive duplication bump caused by pervasive alternative splicing. Here the inflation factor parameter, given by-Ior--inflation, affects the granularity or resolution of the clustering outcome and implicitly controlls the number of clusters, with low values such as 1.3 or 1.4 leading to fewer but larger clusters and high values such as 5 or 6 leading to more but smaller clusters. We set the default value as 2 as suggested byMCL. The e-value cut-off for sequence similarity, given by-eor--eval, which denotes the expected value of the hit quantifies the number of alignments of similar or better quality that you expect to find searching this query against a database of random sequences the same size as the actual target database, is the key parameter measuring the significance of a hit, which is set here as default 1e-10. Note thatDIAMONDitself by default only reports all alignments with e-value < 0.001. The percentage of upper hits used for gene length normalization, given by-npor--normalizedpercent, which determines the upper percentile of hits per bin (categorized by gene length) used in the fit of linear regression, considering that not all hits per bin show apparent linear relationship, is set as default 5, indicating the usage of top 5% hits per bin. The number of bins divided in gene length normalization, given by-bsor--bins, determines the number of bins to categorize the gene length, is set as default 100. The parameter-nnor--nonormalizationcan be set to call off the normalization process, although it's suggested to conduct the normalization to acquire more accurate gene family clustering result. The parameters--to_stopand--cdscontrol the behaviour of translating coding sequence into amino acid sequence. If the--to_stopwas set, the translation would be terminated at the first in-frame stop codon, otherwise the translation would simply skip any stop codons. If the--cdswas set, sequences that doesn't start with a valid start codon, or contains more than one in-frame stop codon, or is not dividable by 3, would be simply dropped, such that only strict complete coding sequences would be included in the subsequent analysis. The directory of output or intermediate files is determined by the parameter-oor--outdir, and-tor--tmpdir, which will be created by the program itself and be overwritten if the folder has already been created. Note that the softwarediamondshould be pre-installed and set in the environment path in all the analysis performed bywgd dmdexcept for the collinear coalescence analysis.We suggest that the default setting in which the inflation factor is set as 2, e-value cut-off as 1e-10 and other parameters in default is a good starting point, unless you specifically want to explore the effects of different parameters.Such that the command for the delineation of whole paranome is simply as below.wgd dmd Aquilegia_coeruleaThe delineation of RBHswgd dmd sequence1 sequence2 -e 1e-10 -bs 100 -np 5 (-nn) (-n 4) (-c 0.9) (--to_stop) (--cds) (-o wgd_dmd) (-t working_tmp)To delineate RBHs between two cds sequence files, the relevant parameter is mostly the same as whole paranome inference, except for the parameter-cor--cscore, which ranges between 0 and 1 and is used to relax the similarity cutoff from the exclusive reciprocal best hits to a certain ratio as to the best hits. For instance, if the gene b1 from genome B has the best hit gene a1 from genome A with the bit score as 100, which is a scoring matrix independent measure of the (local) similarity of the two aligned sequences, with larger values indicating higher similarities, given the-c 0.9, genes from genome A which has the bit score with gene b1 higher than 0.9x100 will also be written in the result file, which in a sense are not RBHs anymore of course, but the highly similar homologue pairs. If more than 2 sequence files were provided, every pair-wise RBHs would be calculated except for querying the same sequence itself. The number of parallel threads to booster the running speed can be set by-nor--nthreads.The suggested command to start with is also under the default setting with the command shown belowwgd dmd sequence1 sequence2The delineation of local MRBHswgd dmd sequence1 sequence2 sequence3 -f sequence1 -e 1e-10 -bs 100 -np 5 (-nn) (-n 4) (-kf) (-kd) (-c 0.9) (--to_stop) (--cds) (-o wgd_dmd) (-t working_tmp)The distinction between local and global (hereunder) MRBHs is that local MRBHs are the results of merged RBHs on a joint focal species, for instance in a three species system (A,(B,C)), the local MRBHs of A only require the calculation of RBHs between A and C (denoted as AC) and AB and then the merging of AB and AC at the axis of A, while the gloabl MRBHs are independent of focal species in that it just calls the calculations of all possible species pair (not self to self species pair), such that AB, AC, and BC are all to be calculated and merged.Two types of MRBHs as intepretated above can be delineated bywgd dmd, the local MRBHs and the global MRBHs. The local MRBHs are constructed by merging all the relevant RBHs only with the focal species, which is set by-for--focus. The parameter-kfor--keepfastacan be set to retain the sequence information of each MRBH. The parameter-kdor--keepduplicatesdetermines whether the same genes can appear in different local MRBHs. Normally there will be no duplicates in the local MRBHs but if users set the-cas 0.9 (or any value smaller than 1), it's likely that the same gene will have chance to appear multiple times in different local MRBHs. That is to say, the parameter-kdis meaningful only when it's set together with the parameter-c.A suggested starting run is under the default parameter with the command shown as below.wgd dmd sequence1 sequence2 sequence3 -f sequence1The delineation of global MRBHswgd dmd sequence1 sequence2 sequence3 -gm -e 1e-10 -bs 100 -np 5 (-nn) (-n 4) (-kf) (-kd) (-c 0.9) (--to_stop) (--cds) (-o wgd_dmd) (-t working_tmp)The global MRBHs is constructed by exhaustively merging all the possible pair-wise RBHs except for querying the sequence itself, which can be initiated by add the flag-gmor--globalmrbh. The rest of relevant parameters stays the same as the local MRBHs.A suggested starting run is under the default parameter with the command shown as below.wgd dmd sequence1 sequence2 sequence3 -gmThe delineation of orthogroupswgd dmd sequence1 sequence2 sequence3 -oi -oo -e 1e-10 -bs 100 -np 5 (-nn) (-cc) (-te) (-mc 0.8) (-gn) (-tree 'fasttree') (-ts '-fastest') (-n 4) (--to_stop) (--cds) (-o wgd_dmd) (-t working_tmp)Inwgd v2, we also implemented an algorithm of delineating orthogroups, which can be initiated with the parameter-oior--orthoinfer. Two ways of delineation can be chosen, the concatenation way (set by the parameter-ccor--concat) or the non-concatenation (default) way. In brief, the concatenation way of delineating orthogroups starts with concatenating all the sequences into a single sequence file and then inferring the whole paranome of this single sequence file with the clustering results mapped back to the belonging species. While the non-concatenation way starts with respective pair-wise diamond search (including querying the same sequence itself) and then all the sequence similarity tables will be concatenated and clustered into orthogroups. Some other possibly useful post-clustering functions can be initiated, including the parameter-teor--testsog, which can be set to start the unbiased test of single-copy gene families (note that this function needshmmer(v3.1b2) to be installed in the environment path), the parameter-mcor--msogcut, ranging between 0 to 1, which can be set to search the so-called mostly single-copy family which has higher than certain cut-off percentage of species coverage, the parameter-gnor--getnsog, which can be set to search for nested single-copy gene families (NSOGs) which is originally multiy-copy but has a (mostly) single-copy branch (which requires the chosen tree-inference program set by-treeor--tree_methodto be pre-installed in the environment path with the parameters setting for gene tree inference controlled by-tsor--treeset). The programwgd dmdwould still conduct the RBHs calculation unless the parameter-ooor--onlyorthowas set. If one only wants to infer the orthogroups, it's suggested to add the flag-ooto just implement the orthogroups delineation analysis.The default setting of parameters is a reasonable starting point with the command as below.wgd dmd sequence1 sequence2 sequence3 -oi -ooThe collinear coalescence inference of phylogenywgd dmd sequence1 sequence2 sequence3 -ap apdata -sm smdata -le ledata -gt gtdata -coc (-tree 'fasttree') (-ts '-fastest') (-n 4) (--to_stop) (--cds) (-o wgd_dmd) (-t working_tmp)A novel phylogenetic inference method named "collinear coalescence inference" is also implemented inwgd v2. For this analysis, users need to provide the anchor points file by-apor--anchorpoints, the collinear segments file by-smor--segments, the listsegments file by-leor--listelements, and the gene table file by-gtor--genetable, all of which can be produced in the programwgd syn. The parameter-cocor--collinearcoalescenceneeds to be set to start this analysis. The tree-inference program and the associated parameters can be set just as above by-treeor--tree_methodand-tsor--treeset. Please also make sure the chosen tree-inference program is installed in the environment path. The programastral-prois required to be installed in the environment path too. Note that there should be no duplicated gene IDs in the sequence file.A suggested starting run of this analysis is with the simple command below.wgd dmd sequence1 sequence2 sequence3 -ap apdata -sm smdata -le ledata -gt gtdata -cocwgd focusThe concatenation-based/coalescence-based phylogenetic inferencewgd focus families sequence1 sequence2 sequence3 (--concatenation) (--coalescence) (-tree 'fasttree') (-ts '-fastest') (-n 4) (--to_stop) (--cds) (-o wgd_focus) (-t working_tmp)The programwgd focusimplemented two basic phylogenetic inference methods, i.e., concatenation-based and coalescence-based methods. To initiate these analysis, users need to set the flag option--concatenationor--coalescence. The concatenation-based method includes a few major steps, i.e., the multiple sequence alignment (MSA) of each gene family, the concatenation of all gene families and then the gene tree (also species tree in this case) inference. The coalescence-based method will instead perform the MSA of each gene family and the gene tree inference based on each MSA, and then infer the species tree based on these individual gene trees. The tree-inference program and the associated parameters can be set just as above by-treeor--tree_methodand-tsor--treeset. Please also make sure the chosen tree-inference program is installed in the environment path. The programastral-prois required to be installed in the environment path if the coalescence-based method is chosen.A suggested starting run of this analysis is with the simple command below.wgd focus families sequence1 sequence2 sequence3 --concatenation
wgd focus families sequence1 sequence2 sequence3 --coalescenceThe functional annotation of gene familieswgd focus families sequence1 sequence2 sequence3 --annotation eggnog -ed eddata --dmnb dbdataThe programwgd focusalso added some wrapping functions for functional annotation of gene families on the hood of databases and softwares for instanceEggNOGandEggNOG-mapper. For the annotation usingEggNOG-mapper, users need to provide the path to the eggNOG annotation database via the option-ed, the path to the diamond-compatible database via the option--dmnd_dband the option--annotationset as "eggnog". The manner how PFAM annotation will be performed can be controlled via the optionpfam, either "none", "realign" or "denovo", the detailed explanation can be found at the wiki ofEggNOG-mapper. Please pre-install theEggNOG-mapperpython package if using this function. For the annotation usinghmmscan, what is implemented inwgd v2is a simple bundle function to performhmmscananalysis for a given hmm profile and set of gene families such that users need to set the option--annotationas "hmmpfam" and provide the hmmprofile via the option--hmm. For the annotation usinginterproscan, users need to provide the path to the interproscan installation folder where there is ainterproscan.shfile via the option--exepathand set the the option--annotationas "interproscan".A suggested starting run of this analysis can be with the command below.wgd focus families sequence1 sequence2 sequence3 --annotation eggnog -ed eddata --dmnb dbdata
wgd focus families sequence1 sequence2 sequence3 --annotation hmmpfam --hmm hmmdata
wgd focus families sequence1 sequence2 sequence3 --annotation interproscan --exepath $PATHThe phylogenetic dating of WGDswgd focus families sequence1 sequence2 sequence3 -d mcmctree -sp spdataThe absolute dating of WGDs is a specific pipeline implemented inwgd v2using the method of phylogenetic dating. The families used in this step can be produced fromwgd dmdandwgd peak. Note that here we only discuss how to date WGDs with genome assembly, instead of transcriptome assembly (which will be discussed in a separate section hereunder). The assumption we made here is that not all anchor pairs (collinear duplicates) are suitable for phylogenetic dating, for instance those fastly or slowly evolving gene duplicates, because they're prone to give biased dating estimation. So as to retrieve the "reliable" anchor pairs, we implemented some methods of identifying crediable anchor pairs based on their Ks values and/or residing collinear segments. For a genome with clear signals of putative WGDs, such as theAquilegia coeruleain the example, a heuristic method that applies the principle of howksratesfind the initial peaks and their parameters was implemented to find the 95% confidence level of the assumed lognormal distribution of the anchor pairKSage distribution to filter anchor pairs with too high or lowKSages, the examplar command of which is showed in thewgd peaksection ofIllustration. If this heuristic method failed to give reasonable results, which is usually due to the effect of multiple adjacent WGDs that blurs the peak-finding process, users can turn to the collinear segments-guided anchor pair clustering implemented inwgd v2, in which a collinear segment-wise GMM clustering will be first conducted based on the "so-called" segmentKSage represented by the medianKSage of all the residing syntelogs (note that the gene duplicate pairs adopted in this step is from the filemultiplicon_pairs.txtwhich contains the full set of syntelogs), instead of the smaller gene set of anchor pairs. The distinction between anchor pairs and syntelogs is that the latter refers to multiple sets of genes derived from the same ancestral genomic region while the former implies the latter but requires additionally the conserved gene order, both of which are, within a genome, assumed to be originated from the duplication of a common ancestral genomic region and as such deemed evidence for WGD. Then the syntelogs will be mapped back according to the clustering results of their affiliated segments. Since the Gaussian shape of the segment cluster doesn't necessarily imitate the shape of the residing syntelogs, so as to retrieve the "reliable" gene sets for phylogenetic dating, we adpoted the (95%) highest density region (HDR) of the syntelogKSage distribution for the phylogenetic dating, the calculation of the (95%) HDR in the functioncalculateHPDseeks the shortestKSrange (a,b) which satisfies the requirement of spanning more than (95%) of all theKSvalues. On the premise of identified anchor pairs (note that the syntelogs are also referred as anchor pairs hereafter), we implemented in the programwgd dmdthe so-called anchor-aware local MRBHs or orthogroups, in which the original local MRBHs are further merged with anchor pairs such that each orthogroup contains the anchor pair and the orthologues. With this orthogroup, users then need one starting tree file (as shown in theIllustrationpart) indicating the tree topology and fossil calibration information for the final phylogenetic dating using the programwgd focus. Users can set the flag option--protcocdatingto only conduct the dating of the concatenation protein MSA or the flag option--protdatingto only conduct the dating of the protein MSAs, noted that these two options only work for themcmctreeoption so far.A suggested starting run can be with the command below.wgd focus families sequence1 sequence2 sequence3 -d mcmctree -sp spdata
wgd focus families sequence1 sequence2 sequence3 -d r8s -sp spdata --nsites nsiteinfo
wgd focus families sequence1 sequence2 sequence3 -d beast --fossil fossilinfo --rootheight --rootheightinfo --chainset --chainsetinfo --beastlgjar $PATHwgd ksdThe construction of whole paranomeKSage distributionwgd ksd families sequence (-o wgd_ksd -t wgd_ksd_tmp --nthreads 4 --to_stop --cds --pairwise --strip_gaps --aligner mafft --tree_method fasttree --node_average)The programwgd ksd, as impied by its name, is for the construction ofKSage distribution. Except for the aforementioned parameters such as--to_stopand--cds, there are some important parameters that have crucial impact on theKSestimation. The option--pairwiseis a very important parameter for theKSestimation, with which theCODEMLwill calculate theKSfor each gene pair separately based on the alignment of only these two genes instead of the whole alignment of the family, such that less gaps are expected and thus the alignment in the consideration ofCODEMLwill be longer (becauseCODEMLwill automately skip every column with gap, regardless of whether it's an overall or partial gap), without which theCODEMLwill calculate theKSbased on the whole alignment of the family, which might have noKSresult at all if the stripped alignment length (removing all gap-containing columns) was zero, a cause of different number ofKSestimates between "pairwise mode" and "non-pairwise mode". It's difficult to say which mode is more ideal, although the "non-pairwise mode" (default setting) which runs on the whole alignment instead of a local alignment, might be more biologically conserved in that it assures the evolution of each column to be started from the root of the family and all the gene duplicates are taken into account in theKSestimation process. The option--strip_gapscan remove all the gap-containing columns, with or without which the result of "non-pairwise mode" won't be affected, while with which the result of "pairwise mode" will be altered. The option--alignerand--aln_optionswhich decide which alignment program to be used and which parameter to be set, will have impact on theKSresults, noted that the default program ismafftand the parameter is--auto. The option--tree_methodand--tree_optionsdecide which gene tree inference program to be used and which parameter to be set, won't affect theKSestimation itself but the result of de-redundancy, noted that we implemented a built-in gene tree inference method based on the Average Linkage Clustering (ALC) (thus a distance-based tree) with the--tree_methodset as "cluster". Two methods of de-redundancy are implemented inwgd v2, namely node-weighted and node-averaged methods. The node-weighted method achieves the de-redundancy via weighing theKSvalue associated with each gene pair such that the weight of a single duplication event sums up to 1 (noted that the number ofKSestimation remains the same) while the node-averaged method realizes the de-redundancy via calculating per gene tree node one averagedKSvalue to represent the age of each duplication event. The option--node_averagecan be set to choose the node-averaged way of de-redundancy. Different methods of de-redundancy will have impact on the detection of WGD signals, which has been investigated in thisliterature.A suggested starting run can use command as belowwgd ksd families sequenceThe construction of orthologousKSage distributionwgd ksd families sequence1 sequence2 (--reweight)From paralogous to orthologousKSage distribution, users only need to provide more cds files. Note that with orthologous gene families the weighting method can be set to be calculated per species pair instead of considering the whole family because when plotting orthologousKSage distribution between two species the weight calculated from this specific species pair should be conserved while the one calculated from the whole family will vary with the number of species. To initiate the weighting per species pair, the option--reweightcan be set.A suggested starting run can use command as belowwgd ksd families sequence1 sequence2The construction ofKSage distribution with rate correctionwgd ksd families sequence1 sequence2 sequence3 --focus2all sequence1 -sp spdataInspired by the rate correction algorithm inksrates, we implemented the rate correction analysis also inwgd v2, which is mostly the same asksratesbut differs in the calculation of the standard deviation of rescaledKSages. To perform the rate correction analysis, users can use both thewgd ksdandwgd vizprogram. For thewgd ksdprogram, users need to provide a species tree via the option--speciestreeon which rate correction can be conducted. The set of species pairs to be shown is flexible that the most convenient option is--focus2allwhich simply shows all the possible focal-sister species pairs, or users can manually set the species pairs via the option--spair. Note that if the species pairs were manually set, it would be needed to set the option--classic. The optiononlyrootoutcan be set to only consider outgroup at the root, instead of all the possible outgroups per focal-sister species pair, which has impact on the final correctedKSages. Some other options which have no impact on the rate correction but add more layers or change the appearance on the mixedKSage distribution, includeplotapgmmandplotelmmetc. The optionplotapgmmcan be set to call the GMM analysis upon the anchor pairKSage distribution and plot the clustering result upon the mixedKSage distribution, which has to be co-set with the option--anchorpointsproviding the anchor pairs information. The option--plotelmmcan be set to call the ELMM analysis upon the paralogousKSage distribution.There are 21 columns in the result*ks.tsvfile besides the index columnspairas the unique identifier for each gene pair. TheN,S,dN,dN/dS,dS,landtare from the codeml results, representing the N estimate, the S estimate, the dN estimate, the dN/dS (omega) estimate, the dS estimate, the log-likelihood and the t estimate, respectively. Thealignmentcoverage,alignmentidentityandalignmentlengthare the information pertaining to the alignment for each family, representing the ratio of the stripped alignment length compared to the full alignment length, the ratio of columns with identical nucleotides compared to the overall columns of the stripped alignment, and the length of the full alignment, respectively.wgd mixThe mixture model clustering analysis ofKSage distributionwgd mix ksdataThis part of mixture modeling analysis is inherited from the originalwgdprogram, but add some more minor visualizations options.wgd peakThe search of crediableKSrange used in WGD datingwgd peak ksdata -ap apdata -sm smdata -le ledata -mp mpdataNote that users can add the flag--heuristicto implement the heuristic search analysiswgd synThe intra-specific synteny inferencewgd syn families gffThe inter-specific synteny inferencewgd syn families gff1 gff2wgd vizThe visualization ofKSage distributionwgd viz -d ksdataThe visualization ofKSage distribution with rate correctionwgd viz -d ksdata -sr srdata -sp spdata -gs gsdataThe visualization of syntenywgd viz -ap apdata -sm smdata -mt mtdata -gt gtdata --plotsynIllustrationWe illustrate our program on an exemplary WGD inference and dating upon speciesAquilegia coerulea.TheAquilegia coeruleawas reported to experience an paleo-polyploidization event after the divergence of core eudicots, which is likely shared by all Ranunculales.First above all, let's delineate the whole paranomeKSage distribution and have a basic observation for potentially conceivable WGDs, using the command line below.wgd dmd Aquilegia_coerulea
wgd ksd wgd_dmd/Aquilegia_coerulea.tsv Aquilegia_coeruleaThe constructed whole paranomeKSage distribution ofAquilegia coeruleais as below, we can see that there seems to be a hump atKS1 but not clear.We then construct the anchorKSage distribution using the command line below.wgd syn -f mRNA -a Name wgd_dmd/Aquilegia_coerulea.tsv Aquilegia_coerulea.gff3 -ks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsvAs shown below, there are some retained anchor pairs withKSbetween 1 and 2, which seems to suggest a WGD event.The associateddupStackplot shows that there are numerous duplicated segments across most of the chromosomes.We implemented two types of dot plots in oxford grid: one in the unit of bases and the other in the unit of genes, which can be colored byKSvalues givenKSdata.As shown above, the dot plot in the unit of genes presents numerous densely aggregated (line-like) anchor points at most of the chromosomes with consistentKSage between 1 and 2. The dot plot in the unit of bases shows the same pattern, as manifested below.The dot plots withoutKSannotation will also be automately produced, as shown below.Note that the opacity of anchor dots and all homolog dots can be set by the optionapalphaandhoalphaseparately. If one just wants to see the anchor dots, setting thehoalphaas 0 (or other minuscule values) will do. If one wants to see the distribution of whole dots better, setting thehoalphahigher (andapalphalower) will do. Thedotsizeoption can be called to adjust the size of dots.A further associated Syndepth plot shows that there are more than 80 duplicated segments, which dominates the whole collinear ratio category.We can fit an ELMM mixture model upon the whole paranomeKSage distribution to see more accurately the significance and location of potential WGDs, using the command line below.wgd viz -d wgd_ksd/Aquilegia_coerulea.tsv.ks.tsvThe result of ELMM mixture model clustering shows that there is a likely WGD component atKS1.19.Let's do a mixture model clustering for anchorKStoo, using the command line below.wgd peak wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv --anchorpoints wgd_syn/iadhore-out/anchorpoints.txt --segments wgd_syn/iadhore-out/segments.txt --listelements wgd_syn/iadhore-out/list_elements.txt --multipliconpairs wgd_syn/iadhore-out/multiplicon_pairs.txt --weightedThe anchorKSage distribution also has a likely WGD component with mode 1.28.Now that we have seen the evidence of numerous duplicated segments and the aggregation of duplicates age inKSaround 1.2 for anchor pairs and non-anchor pairs throughout the whole genome. We can claim with some confidence thatAquilegia coeruleamight have experienced a paleo-polyploidization event. Next, Let's have a further look about its phylogenetic location. We know that there are uncertainties about whether this putative paleo-polyploidization event is shared with all eudicots or not. We can choose some other eudicot genomes to see the ordering of speciation and polyploidization events. Here we chooseVitis vinifera,Protea cynaroidesandAcorus americanusin the followingKSanalysis. First, we built a global MRBH family using the command below.wgd dmd --globalmrbh Aquilegia_coerulea Protea_cynaroides Acorus_americanus Vitis_vinifera -o wgd_globalmrbhIn the global MRBH family, every pair of orthologous genes is the reciprocal best hit, suggesting true orthologous relationships. We would use theKSvalues associated with these orthologous pairs to delimit the divergenceKSpeak. Together with the whole paranomeKSdistribution, we conduct the rate correction using the command below.!!Sincewgdversion 2.0.24, we rewrote a cleaner and quicker way of doing substitution rate correction. It's not required to type in any speices pair and a series ofKSplots will be produced. The required files are orthologousKStable, paralogousKStable, a species tree and a focused species (the one inputted with paralogousKSdata). Users can choose to add one more layer of elmm modeling on paralogousKSvalues and/or gmm modeling on anchorKSvalues. The orthologousKSvalues can be calculated using the command below.wgd ksd wgd_globalmrbh/global_MRBH.tsv seqs* -o wgd_globalmrbh_ksWith the calculated orthologousKStable, we can use the command below to conduct the rate correction and/or mixture modeling analysis.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv -fa Aquilegia_coerulea -epk Aquilegia_coerulea.ks.tsv -ap anchorpoints.txt -sp speciestree.nw -o wgd_viz_mixed_Ks --plotelmm --plotapgmmwgd ksd wgd_globalmrbh/global_MRBH.tsv seqs* --extraparanomeks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -sp speciestree.nw --reweight -o wgd_globalmrbh_ks --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Aquilegia_coerulea;Aquilegia_coerulea" --plotkde (-ap wgd_syn/iadhore-out/anchorpoints.txt)The filespeciestree.nwis the text file of species tree in newick that rate correction would be conducted on. Its content is as below. Users need to provide the species pairs to be plotted. We suggest adding the option--reweightto recalculate the weight per species pair such that the weight of orthologous gene pairs will become 1 as the paralogous gene pairs. The flag--plotkdecan be added when the kde curve of orthologousKSis desired. Extra collinear data can be added by the option-ap.(((Vitis_vinifera,Protea_cynaroides),Aquilegia_coerulea),Acorus_americanus);As shown above, because of the higher substitution rate ofAquilegia coerulea, the original orthologousKSvalues were actually underestimated in the time-frame ofAquilegia coerulea. When we recovered the divergence substitution distance in terms of two times of the branch-specific contribution ofAquilegia coeruleasince its divergence with the sister species plus the shared substitution distance before divergence (in relative to the outgroup), the correctedKSmode became larger.If one had the orthologousKSdata already, one could also apply the programwgd vizto conduct the rate correction analysis using the command below. Note that the order of givenspairoptions decides the color of theKSdistribution of each species pair. The additional optionfocus2allinwgd ksdandwgd vizcan be used to tell the program that the species pairs are between the focus species and all the other species such that users don't need to type in each pair individually.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv --extraparanomeks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -sp speciestree.nw --reweight -ap wgd_syn/iadhore-out/anchorpoints.txt -o wgd_viz_mixed_Ks --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Aquilegia_coerulea;Aquilegia_coerulea" --plotkde (--gsmap gene_species.map)With the optionfocus2all, the command can be also like this, same withwgd ksd.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv --extraparanomeks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -sp speciestree.nw --reweight -ap wgd_syn/iadhore-out/anchorpoints.txt -o wgd_viz_mixed_Ks --focus2all Aquilegia_coerulea --plotkdeNote that we can easily show thatAquilegia coeruleahas higher substitution rate thanProtea cynaroidesandVitis viniferaby comparing their substitution distance in regard to the same divergence event with outgroup speciesAcorus_americanus, using command below.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv -sp speciestree.nw --reweight -o wgd_viz_Compare_rate --spair "Acorus_americanus;Protea_cynaroides" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Vitis_vinifera;Acorus_americanus" --gsmap gene_species.map --plotkdeAs displayed above, the orthologousKSvalues bewteenAquilegia coeruleaandAcorus americanushas the highest mode, indicatingthe faster substitution rate ofAquilegia coeruleacompared toProtea cynaroidesandVitis vinifera.Before v2.0.21, the gene-species map file is neccessarily needed for its implementation inwgd viz, which should be automately produced by the lastwgd ksdstep given thespairandspeciestreeparameters. Thegene_species.maphas contents as below in which each line is the joined string of gene name and species name by space. After v2.0.21 (included), the gene-species map file is not neccessarily needed anymore.Aqcoe6G057800.1 Aquilegia_coerulea
Vvi_VIT_201s0011g01530.1 Vitis_vinifera
Pcy_Procy01g08510 Protea_cynaroides
Aam_Acora.04G142900.1 Acorus_americanusA more complex plot can be made by add the flag--plotelmmsuch that the ELMM mixture modeling of provided paranomeKScan be superimposed, using the command below.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv --extraparanomeks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -sp speciestree.nw --reweight -ap wgd_syn/iadhore-out/anchorpoints.txt -o wgd_viz_mixed_Ks_elmm --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Aquilegia_coerulea;Aquilegia_coerulea" --gsmap gene_species.map --plotkde --plotelmmFrom the mixedKSplot above, we can see that the optimized lognormal component b with mode 1.2 is younger than the corrected orthologousKSmode withProtea cynaroidesandVitis vinifera(1.39 and 1.47, respectively).Besides, we can also add the GMM mixture modeling of anchorKSvalues with the flag--plotapgmm, using the command below.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv --extraparanomeks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -sp speciestree.nw --reweight -ap wgd_syn/iadhore-out/anchorpoints.txt -o wgd_viz_mixed_Ks_elmm --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Aquilegia_coerulea;Aquilegia_coerulea" --gsmap gene_species.map --plotkde --plotapgmmmAs manifested above, the anchorKScomponent 2 with mode 1.28 is also younger than the corrected orthologousKSmode withProtea cynaroidesandVitis vinifera. But we need to be of course cautious that such distinction comes with the uncertainties introduced from the applied mixture modeling methodology in terms of for instance different initialization points and the issue of overfitting and the sister speciess adopted in that there might be species with more disparate substitution rates than the one we chose.Adding both ELMM result for paranome and GMM result for anchorKScan be achieved just by add the two flags mentioned above, using the command below.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv --extraparanomeks wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -sp speciestree.nw --reweight -ap wgd_syn/iadhore-out/anchorpoints.txt -o wgd_viz_mixed_Ks_elmm --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Aquilegia_coerulea;Aquilegia_coerulea" --gsmap gene_species.map --plotkde --plotelmm --plotapgmmmAn alternative way to calculate the orthologousKSis to directly use the orthogroups instead of global MRBH family. That way we don't use the pre-inferred paranomeKSbut the paralogous gene pairs inside each orthogroup instead. To achieve that, we first need to infer orthogroups using the command below.wgd dmd Aquilegia_coerulea Protea_cynaroides Acorus_americanus Vitis_vinifera --orthoinfer -o wgd_ortho (--onlyortho)Users can decide to only conduct the orthogroup analysis while skipping other analysis by adding the flag--onlyortho. Next step is the same with global MRBH family except that we don't use the extra pre-inferred paranomeKSanymore. We infer theKSusing the command below. Note that the programwgd vizcan plot the same just as shown above.wgd ksd wgd_ortho/Orthogroups.sp.tsv -sp speciestree.nw --reweight -o wgd_ortho_ks --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --spair "Aquilegia_coerulea;Aquilegia_coerulea" --plotkde (-ap wgd_syn/iadhore-out/anchorpoints.txt)As shown above, the number of both paralogous gene pairs and orthologous gene pairs is different than the one from global MRBH family in that here we plotted all orthologous gene pairs instead of only global MRBH and potentially new paralogous gene pairs might be produced in the orthogroup inference step, together with different recalculated weights.If one only wanted to plot the orthologousKSdistribution, as we have already shown above, it can be easily achieved by removing the paralogous species pairAquilegia_coerulea;Aquilegia_coerulea, using the command below.wgd viz -d wgd_globalmrbh_ks/global_MRBH.tsv.ks.tsv -sp speciestree.nw --reweight -o wgd_globalmrbh_onlyortho_ks --spair "Aquilegia_coerulea;Protea_cynaroides" --spair "Aquilegia_coerulea;Vitis_vinifera" --spair "Aquilegia_coerulea;Acorus_americanus" --gsmap gene_species.mapWe can clearly see thatVitis viniferahas higher substitution rate thanProtea cynaroidesin that their orthologousKSpeaks withAquilegia coerulea, although representing the same divergence event, differed in substitution distance.After the phylogenetic timing of the Ranunculales WGD, we can further infer its absolute age. First we infer the credible range of anchor pairs byKSheuristically using the programwgd peak.wgd peak --heuristic wgd_ksd/Aquilegia_coerulea.tsv.ks.tsv -ap wgd_syn/iadhore-out/anchorpoints.txt -sm wgd_syn/iadhore-out/segments.txt -le wgd_syn/iadhore-out/list_elements.txt -mp wgd_syn/iadhore-out/multiplicon_pairs.txt -o wgd_peakAs shown above, we assumed a lognormal distribution at the peak location detected by thesignalmodule ofscipylibrary. The 95% confidence level of the lognormal distribution was applied, i.e., 0.68-2.74, in further molecular dating. The fileAquilegia_coerulea.tsv.ks.tsv_95%CI_AP_for_dating_weighted_format.tsvis what we need for next step. To build the orthogroups used in phylogenetic dating, we need to select some species and form a starting tree with proper fossil calibrations. We provide one in mcmctree format as below.17 1
((((Potamogeton_acutifolius,(Spirodela_intermedia,Amorphophallus_konjac)),(Acanthochlamys_bracteata,(Dioscorea_alata,Dioscorea_rotundata))'>0.5600<1.2863')'>0.8360<1.2863',(Acorus_americanus,Acorus_tatarinowii))'>0.8360<1.2863',((((Tetracentron_sinense,Trochodendron_aralioides),(Buxus_austroyunnanensis,Buxus_sinica))'>1.1080<1.2863',(Nelumbo_nucifera,(Telopea_speciosissima,Protea_cynaroides)))'>1.1080<1.2863',(Aquilegia_coerulea_ap1,Aquilegia_coerulea_ap2))'>1.1080<1.2863')'>1.2720<2.4720';As presented above, the focus species that is about to be dated needs to be replaced with(Aquilegia_coerulea_ap1,Aquilegia_coerulea_ap2). With this starting tree and predownloaded cds files of all the species, we can build the orthogroup used in the final molecular dating using the command as below.wgd dmd -f Aquilegia_coerulea -ap wgd_peak/Aquilegia_coerulea.tsv.ks.tsv_95%CI_AP_for_dating_weighted_format.tsv -o wgd_dmd_ortho Potamogeton_acutifolius Spirodela_intermedia Amorphophallus_konjac Acanthochlamys_bracteata Dioscorea_alata Dioscorea_rotundata Acorus_americanus Acorus_tatarinowii Tetracentron_sinense Trochodendron_aralioides Buxus_austroyunnanensis Buxus_sinica Nelumbo_nucifera Telopea_speciosissima Protea_cynaroides Aquilegia_coeruleaThe result filemerge_focus_ap.tsvis what we need for the final step of molecular dating in programwgd focus.wgd focus --protdating --aamodel lg wgd_dmd_ortho/merge_focus_ap.tsv -sp dating_tree.nw -o wgd_dating -d mcmctree -ds 'burnin = 2000' -ds 'sampfreq = 1000' -ds 'nsample = 20000' Potamogeton_acutifolius Spirodela_intermedia Amorphophallus_konjac Acanthochlamys_bracteata Dioscorea_alata Dioscorea_rotundata Acorus_americanus Acorus_tatarinowii Tetracentron_sinense Trochodendron_aralioides Buxus_austroyunnanensis Buxus_sinica Nelumbo_nucifera Telopea_speciosissima Protea_cynaroides Aquilegia_coeruleaHere we only implemented the concatenation analysis using protein sequence by adding the flag--protdatingand we set the parameter formcmctreevia the option-ds. Note that other dating program such asr8sandbeastare also available given some mandatory parameters. The final log of the successful run is as below.16:04:25 INFO     Running mcmctree using Hessian matrix of LG+Gamma  core.py:967
                  for protein model
23:49:37 INFO     Posterior mean for the ages of wgd is 1.128945 mcmctree.py:296
                  billion years from Concatenated peptide
                  alignment and 95% credibility intervals (CI)
                  is 1.01224-1.23121 billion years
         INFO     Total run time: 29175s                              cli.py:241
         INFO     Done                                                cli.py:242To visualize the date, we also provided a python script to plot the WGD dates in thewgdfolder. Users need to extract the raw dates from themcmc.txtfor the WGD node first and save it as filedates.txt(or whatever preferred name). An example command is as below.python $PATH/postplot.py postdis dates.txt --percentile 90 --title "WGD date" --hpd -o "Ranunculales_WGD_date.svg"The posterior mean, median and mode of the Ranunculales WGD age is 112.92, 113.44 and 112.54 mya, with 90% HPD 105.07 - 122.32 mya as manifested above.KstreeIn addition to pairwiseKSestimation, aKStree with branch length inKSunit can also be derived from the programwgd ksdgiven the option--kstreeand--speciestree. Note that the additional option--onlyconcatkstreewill only call theKSestimation for the concatenated alignment rather than all the alignments. Users need to provide a preset species tree for theKStree inference of the concatenated alignment while the remaining alignments will be against an automately inferred tree fromfasttreeoriqtree. In the end, users will get aKStree, aKAtree and a ω tree per fam and for the concatenated alignment.wgd ksd data/kstree_data/fam.tsv data/kstree_data/Acorus_tatarinowii data/kstree_data/Amborella_trichopoda data/kstree_data/Aquilegia_coerulea data/kstree_data/Aristolochia_fimbriata data/kstree_data/Cycas_panzhihuaensi --kstree --speciestree data/kstree_data/species_tree1.nw --onlyconcatkstree -o wgd_kstree_topology1Above we used three alternative topologies to infer theKStree which led to different branch length estimation. Note that the families we used were only two global MRBH families for the purpose of illustration. To acquire an accurate profile of the substitution rate variation, orthologues at the whole genome scale should be used.CitationPlease cite us athttps://doi.org/10.1007/978-1-0716-2561-3_1.Hengchi Chen, Arthur Zwaenepoel (2023). Inference of Ancient Polyploidy from Genomic Data. In: Van de Peer, Y. (eds) Polyploidy. Methods in Molecular Biology, vol 2545. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2561-3_1For citation of the tools used in wgd, please consult the documentation athttps://wgdv2.readthedocs.io/en/latest/citation.html.