Spongospora subterranea de novo genome assembly project
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ABSTRACT:
PROVIDER: PRJEB25390 | ENA |
REPOSITORIES: ENA
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Project description:Illumina assembly of Spongospora subterranea genome
| PRJEB26377 | ENA
Project description:We report the application of RNA- sequencing technology for high-throughput profiling of histone modifications in mammalian cellsor identification of expressed genes upon infection by Spongospora subterranea. Using RNA-sequencing (RNA-seq), 2058 differentially expressed genes (DEGs) were identified from two potato cultivars (tolerant and susceptible) in response to Sss infection. Analysis of the expression patterns of ten selected defense-response genes was carried out at two different stages of tuber growth using RT-qPCR to validate the RNA-seq data. Several defense related genes showed contrasting expression patterns between the tolerant and susceptible cultivars, including marker genes involved in the salicylic acid hormonal response pathway (StMRNA, StUDP and StWRKY6). Induction of six defense related genes (StWRKY6, StTOSB, StSN2, StLOX, StUDP and StSN1) persisted until harvest of the tubers, while three other genes (StNBS, StMRNA and StPRF) were highly up-regulated during the initial stages of disease development. The results of this study suggested that the tolerant potato cultivar employs quantitative resistance and salicylic acid pathway hormonal responses against tuber infection by Sss. The identified genes have the potential to be used in the development of molecular markers for selection of powdery scab resistant potato lines in marker assisted breeding programs.
2018-12-11 | GSE123545 | GEO
Project description:The Plasmodiophorida (Phytomyxea, Rhizaria) are a group of protists that infect plants. Of this group, Spongospora subterranea causes major problems for the potato industry by causing powdery scab and root galling of potatoes and as vector for the Potato mop-top virus (PMTV) (genus Pomovirus, family Virgaviridae). A single tuber isolate (SSUBK13) of this uncultivable protist was used to generate DNA for Illumina sequencing. The data were assembled to a draft genome of 28.08 Mb consisting of 2,340 contigs and an L50 of 280. A total of 10,778 genes were predicted and 93% of the BUSCO genes were detected. The presented genome assembly is only the second genome of a plasmodiophorid. The data will accelerate functional genomics to study poorly understood interaction of plasmodiophorids and their hosts.
| S-EPMC6443038 | biostudies-literature
Project description:Spongospora subterranea f. sp. subterranea strain:SssMN22-1 | cultivar:Russet Burbank potato plant Genome sequencing
| PRJNA988890 | ENA
Project description:This project is aiming to identify specific root surface proteins from susceptible and resistant potato strains and identify those factors responsible for Spongospora subterranea zoospore binding.
2022-10-13 | PXD022502 | Pride
Project description:Spongospora subterranea f. sp. subterranea (Sss) causes two diseases on potato (Solanum tuberosum), lesions on tubers and galls on roots, which are economically important worldwide. Knowledge of global genetic diversity and population structure of pathogens is essential for disease management including resistance breeding. A combination of microsatellite and DNA sequence data was used to investigate the structure and invasion history of Sss. South American populations (four countries, 132 samples) were consistently more diverse than those from all other regions (15 countries, 566 samples), in agreement with the hypothesis that Sss originated in South America where potato was domesticated. A substantial genetic differentiation was found between root and tuber-derived samples from South America. Estimates of past and recent gene flow suggested that Sss was probably introduced from South America into Europe. Subsequently, Europe is likely to have been the recent source of migrants of the pathogen, acting as a "bridgehead" for further global dissemination. Quarantine measures must continue to be focussed on maintaining low global genetic diversity and avoiding exchange of genetic material between the native and introduced regions. Nevertheless, the current low global genetic diversity of Sss allows potato breeders to select for resistance, which is likely to be durable.
| S-EPMC3695870 | biostudies-literature
Project description:Plants defend themselves from pathogens by producing bioactive defense chemicals. The biochemical mechanisms relating to quantitative resistance of potato to root infection by Spongospora subterranea f. sp. subterranea (Sss) are, however, not understood, and are not efficiently utilized in potato breeding programs. Untargeted metabolomics using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to elucidate the biochemical mechanisms of susceptibility to Sss root infection. Potato roots and root exudate metabolic profiles of five tolerant cultivars were compared with those of five susceptible cultivars, following Sss inoculation, to identify tolerance-related metabolites. Comparison of the relative metabolite abundance of tolerant versus susceptible cultivars revealed contrasting responses to Sss infection. Metabolites belonging to amino acids, organic acids, fatty acids, phenolics, and sugars, as well as well-known cell wall thickening compounds were putatively identified and were especially abundant in the tolerant cultivars relative to the susceptible cultivars. Metabolites known to activate plant secondary defense metabolism were significantly increased in the tolerant cultivars compared to susceptible cultivars following Sss inoculation. Root-exuded compounds belonging to the chemical class of phenolics were also found in abundance in the tolerant cultivars compared to susceptible cultivars. This study illustrated that Sss infection of potato roots leads to differential expression of metabolites in tolerant and susceptible potato cultivars.
| S-EPMC7312161 | biostudies-literature
Project description:BACKGROUND: The very large memory requirements for the construction of assembly graphs for de novo genome assembly limit current algorithms to super-computing environments. METHODS: In this paper, we demonstrate that constructing a sparse assembly graph which stores only a small fraction of the observed k-mers as nodes and the links between these nodes allows the de novo assembly of even moderately-sized genomes (~500 M) on a typical laptop computer. RESULTS: We implement this sparse graph concept in a proof-of-principle software package, SparseAssembler, utilizing a new sparse k-mer graph structure evolved from the de Bruijn graph. We test our SparseAssembler with both simulated and real data, achieving ~90% memory savings and retaining high assembly accuracy, without sacrificing speed in comparison to existing de novo assemblers.
| S-EPMC3369186 | biostudies-literature
Project description:MotivationThere are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater datasets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big datasets and using the overlap graph model is still looked out.ResultsWe propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas, we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland.Availability and implementationALGA is available at http://alga.put.poznan.pl.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC8289375 | biostudies-literature