NANUQ: a method for inferring species networks from gene trees under the coalescent model.
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ABSTRACT:
SUBMITTER: Allman ES
PROVIDER: S-EPMC6896299 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
NANUQ: a method for inferring species networks from gene trees under the coalescent model.
Allman Elizabeth S ES Baños Hector H Rhodes John A JA
Algorithms for molecular biology : AMB 20191206
Species networks generalize the notion of species trees to allow for hybridization or other lateral gene transfer. Under the network multispecies coalescent model, individual gene trees arising from a network can have any topology, but arise with frequencies dependent on the network structure and numerical parameters. We propose a new algorithm for statistical inference of a level-1 species network under this model, from data consisting of gene tree topologies, and provide the theoretical justif ...[more]
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Project description:BackgroundNovel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities.ResultsWe propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods.ConclusionsREGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate areas of the search space favoring to infer localized similarities over a more global similarity. Furthermore, experimental results show the good performance of REGNET.
| S-EPMC2978221 | biostudies-literature
Project description:The multispecies coalescent provides an elegant theoretical framework for estimating species trees and species demographics from genetic markers. However, practical applications of the multispecies coalescent model are limited by the need to integrate or sample over all gene trees possible for each genetic marker. Here we describe a polynomial-time algorithm that computes the likelihood of a species tree directly from the markers under a finite-sites model of mutation effectively integrating over all possible gene trees. The method applies to independent (unlinked) biallelic markers such as well-spaced single nucleotide polymorphisms, and we have implemented it in SNAPP, a Markov chain Monte Carlo sampler for inferring species trees, divergence dates, and population sizes. We report results from simulation experiments and from an analysis of 1997 amplified fragment length polymorphism loci in 69 individuals sampled from six species of Ourisia (New Zealand native foxglove).
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| S-EPMC5680165 | biostudies-literature
Project description:The phylogenies of allopolyploids take the shape of networks and cannot be adequately represented as bifurcating trees. Especially for high polyploids (i.e., organisms with more than six sets of nuclear chromosomes), the signatures of gene homoeolog loss, deep coalescence, and polyploidy may become confounded, with the result that gene trees may be congruent with more than one species network. Herein, we obtained the most parsimonious species network by objective comparison of competing scenarios involving polyploidization and homoeolog loss in a high-polyploid lineage of violets (Viola, Violaceae) mostly or entirely restricted to North America, Central America, or Hawaii. We amplified homoeologs of the low-copy nuclear gene, glucose-6-phosphate isomerase (GPI), by single-molecule polymerase chain reaction (PCR) and the chloroplast trnL-F region by conventional PCR for 51 species and subspecies. Topological incongruence among GPI homoeolog subclades, owing to deep coalescence and two instances of putative loss (or lack of detection) of homoeologs, were reconciled by applying the maximum tree topology for each subclade. The most parsimonious species network and the fossil-based calibration of the homoeolog tree favored monophyly of the high polyploids, which has resulted from allodecaploidization 9-14 Ma, involving sympatric ancestors from the extant Viola sections Chamaemelanium (diploid), Plagiostigma (paleotetraploid), and Viola (paleotetraploid). Although two of the high-polyploid lineages (Boreali-Americanae, Pedatae) remained decaploid, recurrent polyploidization with tetraploids of section Plagiostigma within the last 5 Ma has resulted in two 14-ploid lineages (Mexicanae, Nosphinium) and one 18-ploid lineage (Langsdorffianae). This implies a more complex phylogenetic and biogeographic origin of the Hawaiian violets (Nosphinium) than that previously inferred from rDNA data and illustrates the necessity of considering polyploidy in phylogenetic and biogeographic reconstruction.
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Project description:BackgroundThe California Floristic Province is a biodiversity hotspot, reflecting a complex geologic history, strong selective gradients, and a heterogeneous landscape. These factors have led to high endemic diversity across many lifeforms within this region, including the richest diversity of mygalomorph spiders (tarantulas, trapdoor spiders, and kin) in North America. The trapdoor spider genus Aliatypus encompasses twelve described species, eleven of which are endemic to California. Several Aliatypus species show disjunct distributional patterns in California (some are found on both sides of the vast Central Valley), and the genus as a whole occupies an impressive variety of habitats.Methodology/principal findingsWe collected specimens from 89 populations representing all described species. DNA sequence data were collected from seven gene regions, including two newly developed for spider systematics. Bayesian inference (in individual gene tree and species tree approaches) recovered a general "3 clade" structure for the genus (A. gulosus, californicus group, erebus group), with three other phylogenetically isolated species differing slightly in position across different phylogenetic analyses. Because of extremely high intraspecific divergences in mitochondrial COI sequences, the relatively slowly evolving 28S rRNA gene was found to be more useful than mitochondrial data for identification of morphologically indistinguishable immatures. For multiple species spanning the Central Valley, explicit hypothesis testing suggests a lack of monophyly for regional populations (e.g., western Coast Range populations). Phylogenetic evidence clearly shows that syntopy is restricted to distant phylogenetic relatives, consistent with ecological niche conservatism.Conclusions/significanceThis study provides fundamental insight into a radiation of trapdoor spiders found in the biodiversity hotspot of California. Species relationships are clarified and undescribed lineages are discovered, with more geographic sampling likely to lead to additional species diversity. These dispersal-limited taxa provide novel insight into the biogeography and Earth history processes of California.
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Project description:Recent work in estimating species relationships from gene trees has included inferring networks assuming that past hybridization has occurred between species. Probabilistic models using the multispecies coalescent can be used in this framework for likelihood-based inference of both network topologies and parameters, including branch lengths and hybridization parameters. A difficulty for such methods is that it is not always clear whether, or to what extent, networks are identifiable-that is whether there could be two distinct networks that lead to the same distribution of gene trees. For cases in which incomplete lineage sorting occurs in addition to hybridization, we demonstrate a new representation of the species network likelihood that expresses the probability distribution of the gene tree topologies as a linear combination of gene tree distributions given a set of species trees. This representation makes it clear that in some cases in which two distinct networks give the same distribution of gene trees when sampling one allele per species, the two networks can be distinguished theoretically when multiple individuals are sampled per species. This result means that network identifiability is not only a function of the trees displayed by the networks but also depends on allele sampling within species. We additionally give an example in which two networks that display exactly the same trees can be distinguished from their gene trees even when there is only one lineage sampled per species. [gene tree, hybridization, identifiability, maximum likelihood, species tree, phylogeny.].
| S-EPMC5837799 | biostudies-literature