Bootstrap-based Support of HGT Inferred by Maximum Parsimony

Background  

Maximum parsimony is one of the most commonly used criteria for reconstructing phylogenetic trees. Recently, Nakhleh and co-workers extended this criterion to enable reconstruction of phylogenetic networks, and demonstrated its application to detecting reticulate evolutionary relationships. However, one of the major problems with this extension has been that it favors more complex evolutionary relationships over simpler ones, thus having the potential for overestimating the amount of reticulation in the data. An ad hoc solution to this problem that has been used entails inspecting the improvement in the parsimony length as more reticulation events are added to the model, and stopping when the improvement is below a certain threshold.     

The Involvement of Immune Semaphorins in the Pathogenesis of Inflammatory Bowel Diseases (IBDs)

ResultsThe percentage (%) of T regulatory cells (Tregs) expressing sema3A in patients with active CD (64.5% ±14.49%) and active UC (49.8% ±16.45%) was significantly lower when compared to that of healthy controls (88.7% ±3.6%, p< 0.001 and p< 0.0001, respectively). This expression was seen to be in negative correlation with CD activity. Serum levels of Sema4A were significantly lower in patients with CD and UC when compared to that of controls (5.69±1.48ng\ml for CD, 5.26±1.23 ng/ml for UC patients vs 9.74±2.73ng/ml for normal controls, P<0.001). Sema4A was highly expressed in lymphocytes of the lamina propria of CD and UC patients but absent in patients with diverticulitis or in normal individuals.ConclusionsAltered % of Tregs expressing sema3A in patients with inflammatory bowel diseases (IBD) is partially responsible for their failure in preventing CD4+ effector T cell induced inflammation in IBD in peripheral blood. The increased expression of sema4A in bowel biopsies from CD and UC patients is suggestive of its central role in regulating local tissue inflammation in the bowel.     

Confounding factors in HGT detection: statistical error, coalescent effects, and multiple solutions.

Prokaryotic organisms share genetic material across species boundaries by means of a process known as horizontal gene transfer (HGT). This process has great significance for understanding prokaryotic genome diversification and unraveling their complexities. Phylogeny-based detection of HGT is one of the most commonly used methods for this task, and is based on the fundamental fact that HGT may cause gene trees to disagree with one another, as well as with the species phylogeny. Using these methods, we can compare gene and species trees, and infer a set of HGT events to reconcile the differences among these trees. In this paper, we address three factors that confound the detection of the true HGT events, including the donors and recipients of horizontally transferred genes. First, we study experimentally the effects of error in the estimated gene trees (statistical error) on the accuracy of inferred HGT events. Our results indicate that statistical error leads to overestimation of the number of HGT events, and that HGT detection methods should be designed with unresolved gene trees in mind. Second, we demonstrate, both theoretically and empirically, that based on topological comparison alone, the number of HGT scenarios that reconcile a pair of species/gene trees may be exponential. This number may be reduced when branch lengths in both trees are estimated correctly. This set of results implies that in the absence of additional biological information, and/or a biological model of how HGT occurs, multiple HGT scenarios must be sought, and efficient strategies for how to enumerate such solutions must be developed. Third, we address the issue of lineage sorting, how it confounds HGT detection, and how to incorporate it with HGT into a single stochastic framework that distinguishes between the two events by extending population genetics theories. This result is very important, particularly when analyzing closely related organisms, where coalescent effects may not be ignored when reconciling gene trees. In addition to these three confounding factors, we consider the problem of enumerating all valid coalescent scenarios that constitute plausible species/gene tree reconciliations, and develop a polynomial-time dynamic programming algorithm for solving it. This result bears great significance on reducing the search space for heuristics that seek reconciliation scenarios. Finally, we show, empirically, that the locality of incongruence between a pair of trees has an impact on the numbers of HGT and coalescent reconciliation scenarios.     

Inferring phylogenetic networks by the maximum parsimony criterion: a case study

Horizontal gene transfer (HGT) may result in genes whose evolutionary histories disagree with each other, as well as with the species tree. In this case, reconciling the species and gene trees results in a network of relationships, known as the "phylogenetic network" of the set of species. A phylogenetic network that incorporates HGT consists of an underlying species tree that captures vertical inheritance and a set of edges which model the "horizontal" transfer of genetic material. In a series of papers, Nakhleh and colleagues have recently formulated a maximum parsimony (MP) criterion for phylogenetic networks, provided an array of computationally efficient algorithms and heuristics for computing it, and demonstrated its plausibility on simulated data. In this article, we study the performance and robustness of this criterion on biological data. Our findings indicate that MP is very promising when its application is extended to the domain of phylogenetic network reconstruction and HGT detection. In all cases we investigated, the MP criterion detected the correct number of HGT events required to map the evolutionary history of a gene data set onto the species phylogeny. Furthermore, our results indicate that the criterion is robust with respect to both incomplete taxon sampling and the use of different site substitution matrices. Finally, our results show that the MP criterion is very promising in detecting HGT in chimeric genes, whose evolutionary histories are a mix of vertical and horizontal evolution. Besides the performance analysis of MP, our findings offer new insights into the evolution of 4 biological data sets and new possible explanations of HGT scenarios in their evolutionary history.     

Maximum likelihood of phylogenetic networks

Bioinformatics (2006) 22(21), 2604–2611 The authors would like to apologize for errors of graph misplacementin Figures 4–6, and an     

Annotation-free delineation of prokaryotic homology groups

Phylogenomic studies of prokaryotic taxa often assume conserved marker genes are homologous across their length. However, processes such as horizontal gene transfer or gene duplication and loss may disrupt this homology by recombining only parts of genes, causing gene fission or fusion. We show using simulation that it is necessary to delineate homology groups in a set of bacterial genomes without relying on gene annotations to define the boundaries of homologous regions. To solve this problem, we have developed a graph-based algorithm to partition a set of bacterial genomes into Maximal Homologous Groups of sequences (MHGs) where each MHG is a maximal set of maximum-length sequences which are homologous across the entire sequence alignment. We applied our algorithm to a dataset of 19 Enterobacteriaceae species and found that MHGs cover much greater proportions of genomes than markers and, relatedly, are less biased in terms of the functions of the genes they cover. We zoomed in on the correlation between each individual marker and their overlapping MHGs, and show that few phylogenetic splits supported by the markers are supported by the MHGs while many marker-supported splits are contradicted by the MHGs. A comparison of the species tree inferred from marker genes with the species tree inferred from MHGs suggests that the increased bias and lack of genome coverage by markers causes incorrect inferences as to the overall relationship between bacterial taxa.     

Population genomics in bacteria: a case study of Staphylococcus aureus

We analyzed the genome-wide pattern of single nucleotide polymorphisms (SNPs) in a sample with 12 strains of Staphylococcus aureus. Population structure of S. aureus seems to be complex, and the 12 strains were divided into five groups, named A, B, C, D, and E. We conducted a detailed analysis of the topologies of gene genealogies across the genomes and observed a high rate and frequency of tree-shape switching, indicating extensive homologous recombination. Most of the detected recombination occurred in the ancestral population of A, B, and C, whereas there are a number of small regions that exhibit evidence for homologous recombination with a distinct related species. As such regions would contain a number of novel mutations, it is suggested that homologous recombination would play a crucial role to maintain genetic variation within species. In the A-B-C ancestral population, we found multiple lines of evidence that the coalescent pattern is very similar to what is expected in a panmictic population, suggesting that this population is suitable to apply the standard population genetic theories. Our analysis showed that homologous recombination caused a dramatic decay in linkage disequilibrium (LD) and there is almost no LD between SNPs with distance more than 10 kb. Coalescent simulations demonstrated that a high rate of homologous recombination-a relative rate of 0.6 to the mutation rate with an average tract length of about 10 kb-is required to produce patterns similar to those observed in the S. aureus genomes. Our results call for more research into the evolutionary role of homologous recombination in bacterial populations.     

Convergent evolution of modularity in metabolic networks through different community structures

ABSTRACT: BACKGROUND: It has been reported that the modularity of metabolic networks of bacteria is closely relatedto the variability of their living habitats. However, given the dependency of the modularityscore on the community structure, it remains unknown whether organisms achieve certainmodularity via similar or different community structures. RESULTS: In this work, we studied the relationship between similarities in modularity scores andsimilarities in community structures of the metabolic networks of 1021 species. Bothsimilarities are then compared against the genetic distances. We revisited the associationbetween modularity and variability of the microbial living environments and extended theanalysis to other aspects of their life style such as temperature and oxygen requirements. Wealso tested both topological and biological intuition of the community structures identifiedand investigated the extent of their conservation with respect to the taxomony. CONCLUSIONS: We find that similar modularities are realized by different community structures. We findthat such convergent evolution of modularity is closely associated with the number of(distinct) enzymes in the organism's metabolome, a consequence of different life styles ofthe species. We find that the order of modularity is the same as the order of the number ofthe enzymes under the classification based on the temperature preference but not on theoxygen requirement. Besides, inspection of modularity-based communities reveals thatthese communities are graph-theoretically meaningful yet not reflective of specificbiological functions. From an evolutionary perspective, we find that the communitystructures are conserved only at the level of kingdoms. Our results call for moreinvestigation into the interplay between evolution and modularity: how evolution shapesmodularity, and how modularity affects evolution (mainly in terms of fitness andevolvability). Further, our results call for exploring new measures of modularity andnetwork communities that better correspond to functional categorizations.     

The strength of chemical linkage as a criterion for pruning metabolic graphs

MOTIVATION: A metabolic graph represents the connectivity patterns of a metabolic system, and provides a powerful framework within which the organization of metabolic reactions can be analyzed and elucidated. A common practice is to prune (i.e. remove nodes and edges) the metabolic graph prior to any analysis in order to eliminate confounding signals from the representation. Currently, this pruning process is carried out in an ad hoc fashion, resulting in discrepancies and ambiguities across studies. RESULTS: We propose a biochemically informative criterion, the strength of chemical linkage (SCL), for a systematic pruning of metabolic graphs. By analyzing the metabolic graph of Escherichia coli, we show that thresholding SCL is powerful in selecting the conventional pathways' connectivity out of the raw network connectivity when the network is restricted to the reactions collected from these pathways. Further, we argue that the root of ambiguity in pruning metabolic graphs is in the continuity of the amount of chemical content that can be conserved in reaction transformation patterns. Finally, we demonstrate how biochemical pathways can be inferred efficiently if the search procedure is guided by SCL.