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Sexual reproduction remains an understudied feature of oomycete biology. To expand our knowledge of this process, we used RNA-seq and quantitative proteomics to examine matings in Phytophthora infestans. Exhibiting significant changes in mRNA abundance in three matings between different A1 and A2 strains compared to nonmating controls were 1170 genes, most being mating-induced. Rising by >10-fold in at least one cross were 455 genes, and 182 in all three crosses. Most genes had elevated expression in a self-fertile strain. Many mating-induced genes were associated with cell wall biosynthesis, which may relate to forming the thick-walled sexual spore (oospore). Several gene families were induced during mating including one encoding histidine, serine, and tyrosine-rich putative wall proteins, and another encoding prolyl hydroxylases which may strengthen the extracellular matrix. The sizes of these families vary >10-fold between Phytophthora species and one exhibits concerted evolution, highlighting two features of genome dynamics within the genus. Proteomic analyses of mature oospores and nonmating hyphae using isobaric tags for quantification identified 835 shared proteins, with 5% showing >2-fold changes in abundance between the tissues. Enriched in oospores were β-glucanases potentially involved in digesting the oospore wall during germination. Despite being dormant, oospores contained a mostly normal complement of proteins required for core cellular functions. The RNA-seq data generated here and in prior studies were used to identify new housekeeping controls for gene expression studies that are more stable than existing normalization standards. We also observed >2-fold variation in the fraction of polyA+ RNA between life stages, which should be considered when quantifying transcripts and may also be relevant to understanding translational control during development.
Pubmed ID: 29897992
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Web application to search nucleotide databases using a nucleotide query. Algorithms: blastn, megablast, discontiguous megablast.
View all literature mentionsSoftware for identifying the optimal normalization gene among a set of candidates. It ranks the set of candidate normalization genes according to their expression stability in a given sample set and given experimental design. It can analyze expression data obtained through any quantitative method e.g. real time RT-PCR and microarray based expression analysis. NormFinder.xla adds the NormFinder functionality directly to Excel. A version for R is also available.
View all literature mentionsSoftware ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.
View all literature mentionsSoftware to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.
View all literature mentionsGOstat is a tool that allows you to find statistically overrepresented Gene Ontologies within a group of genes. The Gene-Ontology database (GO: http://www.geneontology.org) provides a useful tool to annotate and analyze the function of large numbers of genes. Modern experimental techniques, as e.g. DNA microarrays, often result in long lists of genes. To learn about the biology in this kind of data it is desirable to find functional annotation or Gene-Ontology groups which are highly represented in the data. This program (GOstat) should help in the analysis of such lists and will provide statistics about the GO terms contained in the data and sort the GO annotations giving the most representative GO terms first. Run GOstat: * Go to search form - Computes GO statistics of a list of genes selected from a microarray. * GOstat Display - You can store results from a previously run and view them here, either by uploading them as a file or putting them on a selected URL. * Upload Custom GO Annotations - This allows you to upload your own GO annotation database and use it with GOstat. Variants of GOstat: * Rank GOstat - Takes input from all genes on microarray instead of using a fixed cutoff and uses ranks using a Wilcoxon test or either ranks or pvalues to score GOs using Kolmogorov-Smirnov statistics. * Gene Abundance GOstats - Takes input from all genes on microarray and sums up the gene abundances for each GO to compute statistics. * Two list GOstat - Compares GO statistics in two independent lists of genes, not necessarily one of them being the complete list the other list is sampled from. Platform: Online tool
View all literature mentionsMultiple sequence alignment method with reduced time and space complexity.Multiple sequence alignment with high accuracy and high throughput. Data analysis service for multiple sequence comparison by log- expectation.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE.Documented on February 28,2023. Software program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsWeb phylogeny server based on the maximum-likelihood principle.
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