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The cohesin complex (consisting of Rad21, Smc1a, Smc3, and Stag2 proteins) is critically important for proper sister chromatid separation during mitosis. Mutations in the cohesin complex were recently identified in a variety of human malignancies including acute myeloid leukemia (AML). To address the potential tumor-suppressive function of cohesin in vivo, we generated a series of shRNA mouse models in which endogenous cohesin can be silenced inducibly. Notably, silencing of cohesin complex members did not have a deleterious effect on cell viability. Furthermore, knockdown of cohesin led to gain of replating capacity of mouse hematopoietic progenitor cells. However, cohesin silencing in vivo rapidly altered stem cells homeostasis and myelopoiesis. Likewise, we found widespread changes in chromatin accessibility and expression of genes involved in myelomonocytic maturation and differentiation. Finally, aged cohesin knockdown mice developed a clinical picture closely resembling myeloproliferative disorders/neoplasms (MPNs), including varying degrees of extramedullary hematopoiesis (myeloid metaplasia) and splenomegaly. Our results represent the first successful demonstration of a tumor suppressor function for the cohesin complex, while also confirming that cohesin mutations occur as an early event in leukemogenesis, facilitating the potential development of a myeloid malignancy.
Pubmed ID: 26438359
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A desktop application for the analysis, visualization and data-mining of large-scale genomic data. It is a versatile microarray tool, incorporating sophisticated algorithms for clustering, visualization, classification, statistical analysis and biological theme discovery. MeV generates informative and interrelated displays of expression and annotation data from single or multiple experiments. A huge array of alrogithms are included in MeV modules, and are available at a button-click, such as K-means clustering, Hierarchical clustering, t-Tests, Significance Analysis of Microarrays, Gene Set Enrichment Analysis, and EASE. Extensive documentation is available for helping new users get started with MeV. A Quickstart Guide provides the tutorial a brand new person will need to get their first dataset loaded and displayed in the program. Returning MEV users will want to check out the release notes to see what new features are available in the latest versions of the program. Tutorials have been written about several of its more involved features.
View all literature mentionsCommercial antibody supplier and developer for biomedical research. These products are compatible with use in flow cytometry and mass cytometry, immunoprecipitation and chip, western blotting, immunofluorescence microscopy, and quantitative multiplexing.
View all literature mentionsA statistical framework for genomic data fusion is a computational framework for integrating and drawing inferences from a collection of genome-wide measurements. Each dataset is represented via a kernel function, which defines generalized similarity relationships between pairs of entities, such as genes or proteins. The kernel representation is both flexible and efficient, and can be applied to many different types of data. Furthermore, kernel functions derived from different types of data can be combined in a straightforward fashion. Recent advances in the theory of kernel methods have provided efficient algorithms to perform such combinations in a way that minimizes a statistical loss function. These methods exploit semidefinite programming techniques to reduce the problem of finding optimizing kernel combinations to a convex optimization problem. Computational experiments performed using yeast genome-wide datasets, including amino acid sequences, hydropathy profiles, gene expression data and known protein-protein interactions, demonstrate the utility of this approach. A statistical learning algorithm trained from all of these data to recognize particular classes of proteins--membrane proteins and ribosomal proteins--performs significantly better than the same algorithm trained on any single type of data. Matlab code to center a kernel matrix and Matlab code for normalization are available.
View all literature mentionsA commercial organization which provides assay technologies to isolate DNA, RNA, and proteins from any biological sample. Assay technologies are then used to make specific target biomolecules, such as the DNA of a specific virus, visible for subsequent analysis.
View all literature mentionsSoftware that estimates expression at transcript-level resolution and controls for variability evident across replicate libraries.
View all literature mentionsA peak-calling software program for DNAseI-seq data.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.
View all literature mentionsSoftware tool for fast and high throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies. Fast splice junction mapper for RNA-Seq reads. Aligns RNA-Seq reads to mammalian-sized genomes using ultra high-throughput short read aligner Bowtie, and then analyzes mapping results to identify splice junctions between exons.TopHat2 is accurate alignment of transcriptomes in presence of insertions, deletions and gene fusions.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsLaser capture microdissection system that includes infrared lasers. It can be used for laser capture microdissection LCM, ultraviolet UV laser cutting, sanger sequencing, next generation sequencing, and quantitative PCR.
View all literature mentionsCell line HEK293T is a Transformed cell line with a species of origin Homo sapiens (Human)
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