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covid 19 and sars cov responsible for the sars epidemic in 2002 2003 the viruses mp789 and pcov_gx p1e sampled from malayan pangolins from two different chinese provinces and several viruses found in different bat species in the horseshoe bat genus rhinolophus all from china this research was done by rosanne wallin an msc student at vu amsterdam and uva her full thesis as well as all data and results can be found on github the first algorithm we applied to this data set was the treechild algorithm 1 which is one of the methods that take a number of discordant rooted binary trees as input and finds a rooted network containing each input tree minimizing the number of reticulate events in the network to filter out some noise we contracted some poorly supported branches and then resolved multifurcations consistently across the trees using a tool within the treechild algorithm this gave the network below note that the method is restricted to so called tree child networks meaning that certain complex scenarios are excluded where a network node only has reticulate children also note that this is not necessarily the only optimal tree child network and not all topological differences can be distinguished based on the trees 5 figure 1 phylogenetic network constructed by the tree child algorithm blocks_a_len0 01_supp70 the network shows no reticulation in the sars cov 2 clade the bottom four taxa and puts sars cov 2 right next to ratg13 furthermore it shows a reticulation between an ancestor of hku3 1 and a common ancestor of sars cov 2 and ratg13 leading to bat sl covzc45 however it cannot exactly identify which common ancestor of sars cov 2 and ratg13 is the parent leading to multiple branches in red leading into this reticulation all these observations are consistent with previous research 2 importantly we cannot directly conclude that each reticulation corresponds to a recombination event see table 2 1 of david s book 10 for a nice overview of possible causes of reticulation nevertheless based on 2 it does look like at least the reticulation leading to bat sl covzc45 corresponds to a recombination event the second algorithm we applied was trilonet 3 which constructs a rooted network directly from sequence data it is restricted to so called level 1 networks meaning that it cannot construct overlapping cycles this method produced the network below figure 2 phylogenetic network constructed by trilonet at first sight the network may look a bit different from the previous one figure 1 however note that the three observations above also hold for this second network moreover the sars cov 2 clade is identical in both networks this network contains only one reticulation which is most likely due to the level 1 restriction nevertheless we can still use this method to find more putative recombination events to do so we simply exclude the recombinant bat sl covzc45 from the analysis and rerun the algorithm this gives the following network figure 3 phylogenetic network constructed by trilonet after omitting bat sl covzc45 we have now found a second putative recombination event with rf1 as recombinant note that this is also consistent with the network in figure 1 on the other hand also note that the branching order in the sars cov clade the bottom 7 taxa in figure 3 has changed a bit this could mean that more recombination events are present in the sars cov clade as we also see in figure 1 one interesting follow up question is whether the two or more networks produced by trilonet can be combined into a single higher level network in order to show multiple reticulations simultaneously see 4 for an algorithm that could be useful another interesting observation from these networks is that there is no sign of recombination involving the pangolin coronaviruses mp789 and pcov_gx p1e it rather looks like these viruses evolved from common ancestors of sars cov 2 and ratg13 but it is important to note that we cannot exclude a recombination event on the basis of these networks the relationship between sars cov 2 and pangolin coronaviruses is still being debated in the literature 2 7 8 9 some limitations of the algorithms were noticed during this study firstly the depicted networks are purely topological i e the branch lengths do not represent anything adapting these algorithms to take branch length information into account could possibly improve their accuracy for this data set since the extant taxa have precise time stamps and for recent divergence events these times can be estimated quite accurately see 2 another limitation is that we had to remove several taxa from the original data set 6 before the treechild algorithm could find a solution by removing taxa we reduced the number of reticulations needed to display the trees making the treechild algorithm run in reasonable time we made sure to include a diverse set of taxa based on their pairwise distances 6 to represent as much of the subgenus as possible rosanne used several other algorithms taxon selections and also used trees based on genes rather than fixed length blocks which we did above following guido s post see her thesis on github conclusion although rooted phylogenetic network methods are often limited in the number of taxa that can be analysed and or the complexity of the networks that can be constructed we have seen that these methods can be useful for constructing hypothetical evolutionary histories moreover although the constructed networks are not identical we have seen that they share certain key properties which are also consistent with previous research rosanne wallin leo van iersel mark jones steven kelk and leen stougie 1 leo van iersel remie janssen mark jones yukihiro murakami and norbert zeh a practical fixed parameter algorithm for constructing tree child networks from multiple binary trees arxiv 1907 08474 cs dm 2019 2 maciej f boni philippe lemey xiaowei jiang tommy tsan yuk lam blair w perry todd a castoe andrew rambaut and david l robertson evolutionary origins of the sars cov 2 sarbecovirus lineage responsible for the covid 19 pandemic nat microbiol 5 1408 1417 2020 https doi org 10 1038 s41564 020 0771 4 3 james oldman taoyang wu leo van iersel and vincent moulton trilonet piecing together small networks to reconstruct reticulate evolutionary histories molecular biology and evolution 33 8 2151 2162 2016 http dx doi org 10 1093 molbev msw068 postprint 4 yukihiro murakami leo van iersel remie janssen mark jones and vincent moulton reconstructing tree child networks from reticulate edge deleted subnetworks bulletin of mathematical biology 81 10 3823 3863 2019 5 fabio pardi and celine scornavacca reconstructible phylogenetic networks do not distinguish the indistinguishable plos comput biol 11 4 e1004135 2015 6 grimm guido morrison david 2020 harvest and phylogenetic network analysis of sars virus genomes cov 1 and cov 2 figshare dataset https doi org 10 6084 m9 figshare 12046581 v3 7 lam tommy tsan yuk marcus ho hin shum hua chen zhu yi gang tong xue bing ni yun shi liao wei wei et al identifying sars cov 2 related coronaviruses in malayan pangolins nature 583 282 285 2020 https doi org 10 1038 s41586 020 2169 0 8 wang hongru lenore pipes and rasmus nielsen synonymous mutations and the molecular evolution of sars cov 2 origins preprint evolutionary biology april 21 2020 https doi org 10 1101 2020 04 20 052019 9 li xiaojun elena e giorgi manukumar honnayakanahalli marichannegowda brian foley chuan xiao xiang peng kong yue chen s gnanakaran bette korber and feng gao emergence of sars cov 2 through recombination and strong purifying selection science advances vol 6 no 27 2020 https doi org 10 1126 sciadv abb9153 10 david morrison introduction to phylogenetic networks rjr productions uppsala sweden 2011 http www rjr productions org networks index html posted by leo van iersel at 10 45 00 pm 0 comments email this blogthis share to x share to facebook share to pinterest labels 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