Project description:The Periconia genus belongs to the phylum Ascomycota, order Pleosporales, family Periconiaceae. Periconia is widespread in many habitats but little is known about its ecology. Several species produce bioactive molecules, among them, Periconia digitata extracts were shown to be deadly active against the pine wilt nematode. The strain CNCM I-4278, here identified as P. digitata was able to inhibit the plant pathogen Phytophthora parasitica. Since P. digitata has great potential as biocontrol agent and the only other genome available in the Periconiaceae family is that of Periconia macrospinosa, which is quite fragmentary, we generated long-read genomic data for P. digitata. Thanks to the PacBio Hifi sequencing technology, we obtained a high-quality genome with a total length of 38,967,494 bp, represented by 13 haploid chromosomes. The transcriptomic and proteomic data strengthen and support the genome annotation. Besides representing a new reference genome within the Periconiaceae, this work will also contribute in our understanding of the Eukaryotic tree of life. Not least, opens new possibilities to the biotechnological use of the species.
Project description:The Periconia genus belongs to the phylum Ascomycota, order Pleosporales, family Periconiaceae. Periconia is widespread in many habitats but little is known about its ecology. Several species produce bioactive molecules, among them, Periconia digitata extracts were shown to be deadly active against the pine wilt nematode. The strain CNCM I-4278, here identified as P. digitata was able to inhibit the plant pathogen Phytophthora parasitica. Since P. digitata has great potential as biocontrol agent and the only other genome available in the Periconiaceae family is that of Periconia macrospinosa, which is quite fragmentary, we generated long-read genomic data for P. digitata. Thanks to the PacBio Hifi sequencing technology, we obtained a high-quality genome with a total length of 38,967,494 bp, represented by 13 haploid chromosomes. The transcriptomic and proteomic data strengthen and support the genome annotation. Besides representing a new reference genome within the Periconiaceae, this work will also contribute in our understanding of the Eukaryotic tree of life. Not least, opens new possibilities to the biotechnological use of the species.
Project description:The study is intended to collect specimens to support the application of genome analysis technologies, including large-scale genome sequencing. This study will ultimately provide cancer researchers with specimens that they can use to develop comprehensive catalogs of genomic information on at least 50 types of human cancer. The study will create a resource available to the worldwide research community that could be used to identify and accelerate the development of new diagnostic and prognostic markers, new targets for pharmaceutical interventions, and new cancer prevention and treatment strategies. This study will be a competitive enrollment study conducted at multiple institutions.
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
Project description:Nematodes encompass over 24,000 described species, which were discovered in almost every ecological habitat, and make up over 80% of metazoan taxonomic diversity in soils. The last common ancestor of nematodes is believed to date back to around 650–750 million years, generating a large and phylogenetically diverse group to be explored. However, for most species high quality gene annotations are incomprehensive or missing. Combining short-read RNA sequencing with mass spectrometry-based proteomics and machine learning quality control in an approach called proteotranscriptomics, we improve gene annotations for 9 genome-sequenced nematode species and provide new gene annotations for 3 additional species without genome assemblies. Emphasizing the sensitivity of our methodology, we provide evidence for two hitherto undescribed genes in the model organism Caenorhabditis elegans. Extensive phylogenetic systems analysis using this comprehensive proteome annotation provides new insights into evolutionary processes of this metazoan group.
Project description:In order to more accurately discover the cause of drug resistance in tumor treatment, and to provide a new basis for precise treatment.
Therefore, based on the umbrella theory of precision medicine, we carried out this single-center, prospective, and observational study to include patients with liver metastases from colorectal cancer. By combining genome, transcriptome, and proteomic sequencing data, we established a basis for colorectal cancer liver Transfer the multi-omics data of the sample, describe the reason for the resistance of the first-line treatment, and search for new therapeutic targets.