RNA-clique: a method for computing genetic distances from RNA-seq data.

BACKGROUND: Although RNA-seq data are traditionally used for quantifying gene expression levels, the same data could be useful in an integrated approach to compute genetic distances as well. Challenges to using mRNA sequences for computing genetic distances include the relatively high conservation of coding sequences and the presence of paralogous and, in some species, homeologous genes. RESULTS: We developed a new computational method, RNA-clique, for calculating genetic distances using assembled RNA-seq data and assessed the efficacy of the method using biological and simulated data. The method employs reciprocal BLASTn followed by graph-based filtering to ensure that only orthologous genes are compared. Each vertex in the graph constructed for filtering represents a gene in a specific sample under comparison, and an edge connects a pair of vertices if the genes they represent are best matches for each other in their respective samples. The distance computation is a function of the BLAST alignment statistics and the constructed graph and incorporates only those genes that are present in some complete connected component of this graph. As a biological testbed we used RNA-seq data of tall fescue (Lolium arundinaceum), an allohexaploid plant ( 2 n = 14 Gb ), and bluehead wrasse (Thalassoma bifasciatum), a teleost fish. RNA-clique reliably distinguished individual tall fescue plants by genotype and distinguished bluehead wrasse RNA-seq samples by individual. In tests with simulated RNA-seq data, the ground truth phylogeny was accurately recovered from the computed distances. Moreover, tests of the algorithm parameters indicated that, even with stringent filtering for orthologs, sufficient sequence data were retained for the distance computations. Although comparisons with an alternative method revealed that RNA-clique has relatively high time and memory requirements, the comparisons also showed that RNA-clique's results were at least as reliable as the alternative's for tall fescue data and were much more reliable for the bluehead wrasse data. CONCLUSION: Results of this work indicate that RNA-clique works well as a way of deriving genetic distances from RNA-seq data, thus providing a methodological integration of functional and genetic diversity studies.

CURatio: Genome-wide phylogenomic analysis method using ratios of total branch lengths.

Evolutionary hypotheses provide important underpinnings of biological and medical sciences, and comprehensive, genome-wide understanding of evolutionary relationships among organisms are needed to test and refine such hypotheses. Theory and empirical evidence clearly indicate that phylogenies (trees) of different genes (loci) should not display precisely matching topologies. The main reason for such phylogenetic incongruence is reticulated evolutionary history of most species due to meiotic sexual recombination in eukaryotes, or horizontal transfers of genetic material in prokaryotes. Nevertheless, many genes should display topologically related phylogenies, and should group into one or more (for genetic hybrids) clusters in poly-dimensional "tree space". Unusual evolutionary histories or effects of selection may result in "outlier" genes with phylogenies that fall outside the main distribution(s) of trees in tree space. We present a new phylogenomic method, CURatio, which uses ratios of total branch lengths in gene trees to help identify phylogenetic outliers in a given set of ortholog groups from multiple genomes. An advantage of CURatio over other methods is that genes absent from and/or duplicated in some genomes can be included in the analysis. We conducted a simulation study under the coalescent model, and showed that, given sufficient species depth and topological difference, these ratios are significantly higher for the "outlier" gene phylogenies. Also, we applied CURatio to a set of annotated genomes of the fungal family, Clavicipitaceae, and identified alkaloid biosynthesis genes as outliers, probably due to a history of duplication and loss. The source code is available at https://github.com/QiwenKang/CURatio, and the empirical data set on Clavicipitaceae and simulated data set are available at Mendeley https://data.mendeley.com/datasets/mrxts7wjrr/1.

Swainsonine Biosynthesis Genes in Diverse Symbiotic and Pathogenic Fungi.

Swainsonine-a cytotoxic fungal alkaloid and a potential cancer therapy drug-is produced by the insect pathogen and plant symbiont Metarhizium robertsii, the clover pathogen Slafractonia leguminicola, locoweed symbionts belonging to Alternaria sect. Undifilum, and a recently discovered morning glory symbiont belonging to order Chaetothyriales. Genome sequence analyses revealed that these fungi share orthologous gene clusters, designated "SWN," which included a multifunctional swnK gene comprising predicted adenylylation and acyltransferase domains with their associated thiolation domains, a ß-ketoacyl synthase domain, and two reductase domains. The role of swnK was demonstrated by inactivating it in M. robertsii through homologous gene replacement to give a ∆swnK mutant that produced no detectable swainsonine, then complementing the mutant with the wild-type gene to restore swainsonine biosynthesis. Other SWN cluster genes were predicted to encode two putative hydroxylases and two reductases, as expected to complete biosynthesis of swainsonine from the predicted SwnK product. SWN gene clusters were identified in six out of seven sequenced genomes of Metarhzium species, and in all 15 sequenced genomes of Arthrodermataceae, a family of fungi that cause athlete's foot and ringworm diseases in humans and other mammals. Representative isolates of all of these species were cultured, and all Metarhizium spp. with SWN clusters, as well as all but one of the Arthrodermataceae, produced swainsonine. These results suggest a new biosynthetic hypothesis for this alkaloid, extending the known taxonomic breadth of swainsonine producers to at least four orders of Ascomycota, and suggest that swainsonine has roles in mutualistic symbioses and diseases of plants and animals.

Host Tissue Environment Directs Activities of an Epichloë Endophyte, While It Induces Systemic Hormone and Defense Responses in Its Native Perennial Ryegrass Host.

Increased resilience of pasture grasses mediated by fungal Epichloë endophytes is crucial to pastoral industries. The underlying mechanisms are only partially understood and likely involve very different activities of the endophyte in different plant tissues and responses of the plant to these. We analyzed the transcriptomes of Epichloë festucae and its host, Lolium perenne, in host tissues of different function and developmental stages. The endophyte contributed approximately 10× more to the transcriptomes than to the biomass of infected tissues. Proliferating mycelium in growing host tissues highly expressed genes involved in hyphal growth. Nonproliferating mycelium in mature plant tissues, transcriptionally equally active, highly expressed genes involved in synthesizing antiherbivore compounds. Transcripts from the latter accounted for 4% of fungal transcripts. Endophyte infection systemically but moderately increased transcription of L. perenne genes with roles in hormone biosynthesis and perception as well as stress and pathogen resistance while reducing expression of genes involved in photosynthesis. There was a good correlation between transcriptome-based observations and physiological observations. Our data indicate that the fitness-enhancing effects of the endophyte are based both on its biosynthetic activities, predominantly in mature host tissues, and also on systemic alteration of the host's hormonal responses and induction of stress response genes. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

A Colletotrichum graminicola mutant deficient in the establishment of biotrophy reveals early transcriptional events in the maize anthracnose disease interaction.

BACKGROUND: Colletotrichum graminicola is a hemibiotrophic fungal pathogen that causes maize anthracnose disease. It progresses through three recognizable phases of pathogenic development in planta: melanized appressoria on the host surface prior to penetration; biotrophy, characterized by intracellular colonization of living host cells; and necrotrophy, characterized by host cell death and symptom development. A "Mixed Effects" Generalized Linear Model (GLM) was developed and applied to an existing Illumina transcriptome dataset, substantially increasing the statistical power of the analysis of C. graminicola gene expression during infection and colonization. Additionally, the in planta transcriptome of the wild-type was compared with that of a mutant strain impaired in the establishment of biotrophy, allowing detailed dissection of events occurring specifically during penetration, and during early versus late biotrophy. RESULTS: More than 2000 fungal genes were differentially transcribed during appressorial maturation, penetration, and colonization. Secreted proteins, secondary metabolism genes, and membrane receptors were over-represented among the differentially expressed genes, suggesting that the fungus engages in an intimate and dynamic conversation with the host, beginning prior to penetration. This communication process probably involves reception of plant signals triggering subsequent developmental progress in the fungus, as well as production of signals that induce responses in the host. Later phases of biotrophy were more similar to necrotrophy, with increased production of secreted proteases, inducers of plant cell death, hydrolases, and membrane bound transporters for the uptake and egress of potential toxins, signals, and nutrients. CONCLUSIONS: This approach revealed, in unprecedented detail, fungal genes specifically expressed during critical phases of host penetration and biotrophic establishment. Many encoded secreted proteins, secondary metabolism enzymes, and receptors that may play roles in host-pathogen communication necessary to promote susceptibility, and thus may provide targets for chemical or biological controls to manage this important disease. The differentially expressed genes could be used as 'landmarks' to more accurately identify developmental progress in compatible versus incompatible interactions involving genetic variants of both host and pathogen.

Genetics, genomics and evolution of ergot alkaloid diversity.

The ergot alkaloid biosynthesis system has become an excellent model to study evolutionary diversification of specialized (secondary) metabolites. This is a very diverse class of alkaloids with various neurotropic activities, produced by fungi in several orders of the phylum Ascomycota, including plant pathogens and protective plant symbionts in the family Clavicipitaceae. Results of comparative genomics and phylogenomic analyses reveal multiple examples of three evolutionary processes that have generated ergot-alkaloid diversity: gene gains, gene losses, and gene sequence changes that have led to altered substrates or product specificities of the enzymes that they encode (neofunctionalization). The chromosome ends appear to be particularly effective engines for gene gains, losses and rearrangements, but not necessarily for neofunctionalization. Changes in gene expression could lead to accumulation of various pathway intermediates and affect levels of different ergot alkaloids. Genetic alterations associated with interspecific hybrids of Epichloë species suggest that such variation is also selectively favored. The huge structural diversity of ergot alkaloids probably represents adaptations to a wide variety of ecological situations by affecting the biological spectra and mechanisms of defense against herbivores, as evidenced by the diverse pharmacological effects of ergot alkaloids used in medicine.

Plant-symbiotic fungi as chemical engineers: multi-genome analysis of the clavicipitaceae reveals dynamics of alkaloid loci.

The fungal family Clavicipitaceae includes plant symbionts and parasites that produce several psychoactive and bioprotective alkaloids. The family includes grass symbionts in the epichloae clade (Epichloë and Neotyphodium species), which are extraordinarily diverse both in their host interactions and in their alkaloid profiles. Epichloae produce alkaloids of four distinct classes, all of which deter insects, and some-including the infamous ergot alkaloids-have potent effects on mammals. The exceptional chemotypic diversity of the epichloae may relate to their broad range of host interactions, whereby some are pathogenic and contagious, others are mutualistic and vertically transmitted (seed-borne), and still others vary in pathogenic or mutualistic behavior. We profiled the alkaloids and sequenced the genomes of 10 epichloae, three ergot fungi (Claviceps species), a morning-glory symbiont (Periglandula ipomoeae), and a bamboo pathogen (Aciculosporium take), and compared the gene clusters for four classes of alkaloids. Results indicated a strong tendency for alkaloid loci to have conserved cores that specify the skeleton structures and peripheral genes that determine chemical variations that are known to affect their pharmacological specificities. Generally, gene locations in cluster peripheries positioned them near to transposon-derived, AT-rich repeat blocks, which were probably involved in gene losses, duplications, and neofunctionalizations. The alkaloid loci in the epichloae had unusual structures riddled with large, complex, and dynamic repeat blocks. This feature was not reflective of overall differences in repeat contents in the genomes, nor was it characteristic of most other specialized metabolism loci. The organization and dynamics of alkaloid loci and abundant repeat blocks in the epichloae suggested that these fungi are under selection for alkaloid diversification. We suggest that such selection is related to the variable life histories of the epichloae, their protective roles as symbionts, and their associations with the highly speciose and ecologically diverse cool-season grasses.

A linear-time algorithm for finding a maximum-length ORF in a splice graph.

We present a linear-time, deterministic algorithm for finding a longest Open Reading Frame (ORF) in an alternatively spliced gene represented by a splice graph. Finding protein-encoding regions is a fundamental problem in genomic and transcriptomic analysis, and in some circumstances long ORFs can provide good predictions of such regions. Splice graphs are a common way of compactly representing what may be exponentially many alternative splicings of a sequence. The efficiency of our algorithm is achieved by pruning the search space so as to bound the number of reading frames considered at any vertex of the splice graph. The algorithm guarantees that the unpruned reading frames contain at least one longest ORF of the gene. We are therefore able to find a longest ORF among all splice variants in time linear in the size of the splice graph, even though the number of potential transcripts may be much larger.

Lifestyle transitions in plant pathogenic Colletotrichum fungi deciphered by genome and transcriptome analyses.

Colletotrichum species are fungal pathogens that devastate crop plants worldwide. Host infection involves the differentiation of specialized cell types that are associated with penetration, growth inside living host cells (biotrophy) and tissue destruction (necrotrophy). We report here genome and transcriptome analyses of Colletotrichum higginsianum infecting Arabidopsis thaliana and Colletotrichum graminicola infecting maize. Comparative genomics showed that both fungi have large sets of pathogenicity-related genes, but families of genes encoding secreted effectors, pectin-degrading enzymes, secondary metabolism enzymes, transporters and peptidases are expanded in C. higginsianum. Genome-wide expression profiling revealed that these genes are transcribed in successive waves that are linked to pathogenic transitions: effectors and secondary metabolism enzymes are induced before penetration and during biotrophy, whereas most hydrolases and transporters are upregulated later, at the switch to necrotrophy. Our findings show that preinvasion perception of plant-derived signals substantially reprograms fungal gene expression and indicate previously unknown functions for particular fungal cell types.

Statistical phylogenetic tree analysis using differences of means.

We propose a statistical method to test whether two phylogenetic trees with given alignments are significantly incongruent. Our method compares the two distributions of phylogenetic trees given by two input alignments, instead of comparing point estimations of trees. This statistical approach can be applied to gene tree analysis for example, detecting unusual events in genome evolution such as horizontal gene transfer and reshuffling. Our method uses difference of means to compare two distributions of trees, after mapping trees into a vector space. Bootstrapping alignment columns can then be applied to obtain p-values. To compute distances between means, we employ a "kernel method" which speeds up distance calculations when trees are mapped in a high-dimensional feature space, e.g., splits or quartets feature space. In this pilot study, first we test our statistical method on data sets simulated under a coalescence model, to test whether two alignments are generated by congruent gene trees. We follow our simulation results with applications to data sets of gophers and lice, grasses and their endophytes, and different fungal genes from the same genome. A companion toolkit, Phylotree, is provided to facilitate computational experiments.

Simulation study of the coil-globule transition of a polymer in solvent.

Molecular dynamics simulations are used to study the coil-globule transition for a system composed of a bead-spring polymer immersed in an explicitly modeled solvent. Two different versions of the model are used, which are differentiated by the nature of monomer-solvent, solvent-solvent, and nonbonded monomer-monomer interactions. For each case, a model parameter lambda determines the degree of hydrophobicity of the monomers by controlling the degree of energy mismatch between the monomers and solvent particles. We consider a lambda-driven coil-globule transition at constant temperature. The simulations are used to calculate average static structure factors, which are then used to determine the scaling exponents of the system in order to determine the theta-point values lambdatheta separating the coil from the globule states. For each model we construct coil-globule phase diagrams in terms of lambda and the particle density rho. The results are analyzed in terms of a simple Flory-type theory of the collapse transition. The ratio of lambdatheta for the two models converges in the high density limit exactly to the value predicted by the theory in the random mixing approximation. Generally, the predicted values of lambdatheta are in reasonable agreement with the measured values at high rho, though the accuracy improves if the average chain size is calculated using the full probability distribution associated with the polymer-solvent free energy, rather than merely using the value obtained from the minimum of the free energy.