Plant Genomics
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Rescooped by Biswapriya Biswavas Misra from Amazing Science
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Genomic alterations in diverse cell types throughout the body give rise to hundreds of different forms of cancer

Genomic alterations in diverse cell types throughout the body give rise to hundreds of different forms of cancer | Plant Genomics | Scoop.it
Genomic alterations in diverse cell types at different sites in the body give rise to hundreds of different forms of cancer, and the ways in which these changes result in tumors with different biology, pathology and treatment strategies are beginning to be characterized. The TCGA Research Network has catalogued aberrations in the DNA, chromatin and RNA of the genomes of thousands of tumors relative to matched normal cellular genomes and has analyzed their epigenetic and protein consequences. Here the Pan-Cancer initiative examines the similarities and differences among the genomic and cellular alterations found in the first dozen tumor types to be profiled by TCGA. This first look across cancer types offers new tools in genomics and bioinformatics and the prospect of repurposing targeted therapies directed by the molecular pathology of the tumors in addition to their clinical classification.

 

Mutational Drivers • Network models • Environmental exposure/pathogens • Data discovery, transparency and visualization • Future directions


The Cancer Genome Atlas Pan-Cancer analysis projectEmerging landscape of oncogenic signatures across human cancersPan-cancer patterns of somatic copy number alterationMutational heterogeneity in cancer and the search for new cancer-associated genesMutational landscape and significance across 12 major cancer typesThe landscape of viral expression and host gene fusion and adaptation in human cancerInferring tumor purity and stromal and immune cell admixture from expression dataAnalysis of microRNA-target interactions across diverse cancer typesTCPA: a resource for cancer functional proteomics dataThe mutational landscape of phosphorylation signaling in cancerIntOGen-mutations identifies cancer drivers across tumor typesNetwork-based stratification of tumor mutationsEvidence for APOBEC3B mutagenesis in multiple human cancersAn APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancersExploring TCGA Pan-Cancer Data at the UCSC Cancer Genomics BrowserEnabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome AtlasComprehensive identification of mutational cancer driver genes across 12 tumor typesComparisons across cancersComprehensive genomic characterization defines human glioblastoma genes and core pathwaysIntegrated genomic analyses of ovarian carcinomaComprehensive molecular characterization of human colon and rectal cancerComprehensive genomic characterization of squamous cell lung cancersComprehensive molecular portraits of human breast tumoursIntegrated genomic characterization of endometrial carcinomaComprehensive molecular characterization of clear cell renal cell carcinomaThe mutational landscape of chromatin regulatory factors across 4623 tumor samples
Via Dr. Stefan Gruenwald
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Rescooped by Biswapriya Biswavas Misra from Fungal Genetic and Genomics
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Discovering Functions of Unannotated Genes from a Transcriptome Survey of Wild Fungal Isolates

Discovering Functions of Unannotated Genes from a Transcriptome Survey of Wild Fungal Isolates | Plant Genomics | Scoop.it

Most fungal genomes are poorly annotated, and many fungal traits of industrial and biomedical relevance are not well suited to classical genetic screens. Assigning genes to phenotypes on a genomic scale thus remains an urgent need in the field. We developed an approach to infer gene function from expression profiles of wild fungal isolates, and we applied our strategy to the filamentous fungus Neurospora crassa. Using transcriptome measurements in 70 strains from two well-defined clades of this microbe, we first identified 2,247 cases in which the expression of an unannotated gene rose and fell across N. crassa strains in parallel with the expression of well-characterized genes. We then used image analysis of hyphal morphologies, quantitative growth assays, and expression profiling to test the functions of four genes predicted from our population analyses. The results revealed two factors that influenced regulation of metabolism of nonpreferred carbon and nitrogen sources, a gene that governed hyphal architecture, and a gene that mediated amino acid starvation resistance. These findings validate the power of our population-transcriptomic approach for inference of novel gene function, and we suggest that this strategy will be of broad utility for genome-scale annotation in many fungal systems.


Via Bradford Condon, Jie Wang
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