A Genetic Strategy for Stochastic Gene Activation with Regulated Sparseness (STARS)

It remains a challenge to establish a straightforward genetic approach for controlling the probability of gene activation or knockout at a desired level. Here, we developed a method termed STARS: stochastic gene activation with genetically regulated sparseness. The stochastic expression was achieved by two cross-linked, mutually-exclusive Cre-mediated recombinations. The stochastic level was further controlled by regulating Cre/lox reaction kinetics through varying the intrachromosomal distance between the lox sites mediating one of the recombinations. In mammalian cell lines stably transfected with a single copy of different STARS transgenes, the activation/knockout of reporter genes was specifically controlled to occur in from 5% to 50% of the cell population. STARS can potentially provide a convenient way for genetic labeling as well as gene expression/knockout in a population of cells with a desired sparseness level

Hoxa9 and Meis1 Cooperatively Induce Addiction to Syk Signaling by Suppressing miR-146a in Acute Myeloid Leukemia

The transcription factor Meis1 drives myeloid leukemogenesis in the context of Hox gene overexpression but is currently considered undruggable. We therefore investigated whether myeloid progenitor cells transformed by Hoxa9 and Meis1 become addicted to targetable signaling pathways. A comprehensive (phospho)proteomic analysis revealed that Meis1 increased Syk protein expression and activity. Syk upregulation occurs through a Meis1-dependent feedback loop. By dissecting this loop, we show that Syk is a direct target of miR-146a, whose expression is indirectly regulated by Meis1 through the transcription factor PU.1. In the context of Hoxa9 overexpression, Syk signaling induces Meis1, recapitulating several leukemogenic features of Hoxa9/Meis1-driven leukemia. Finally, Syk inhibition disrupts the identified regulatory loop, prolonging survival of mice with Hoxa9/Meis1-driven leukemia..O. and T. Berg (BE 4198/1-1 and BE 4198/2-1) are supported by the Deutsche Forschungsgemeinschaft (DFG). K.S. is supported by a Leukemia and Lymphoma Society Scholar Award and by the National Cancer Institute (R01 CA140292). F.C. is supported by an EMBO long-term fellowship (1305-2015 and Marie Curie ActionsLTFCOFUND2013/GA-2013-609409). F.K. was supported by grants from Deutsche Krebshilfe (grant 109420; Max-Eder program), fellowship 2010/04 by the European Hematology Association, and by the DFG (SFB 1074, project A5). A.R. was supported by the DFG (SFB 1074, project A5) and the gender equality program by the DFG (SFB 1074, project Z2), a fellowship from the Canadian Institutes of Health Research, and the Baustein Startförderung Program of the Medical Faculty, Ulm University. Work in the Department of Haematology in Cambridge is supported by Bloodwise (grant ref. 13003), the Wellcome Trust (grant ref. 104710/Z/14/Z), the Medical Research Council (MC_PC_12009), the Kay Kendall Leukemia Fund (KKL952), the Cambridge NIHR Biomedical Research Center (NF-BR-0412-10321), the Cambridge Experimental Cancer Medicine Centre itself receives funding from NIHR (NF-EC-0412-10442), the Leukemia and Lymphoma Society of America (grant ref. 07037), and core support grants from the Wellcome Trust (100140/Z/12/Z and 097922/Z/11/Z) and MRC (MC_PC_12009)

The mammalian gene function resource: the International Knockout Mouse Consortium.

In 2007, the International Knockout Mouse Consortium (IKMC) made the ambitious promise to generate mutations in virtually every protein-coding gene of the mouse genome in a concerted worldwide action. Now, 5 years later, the IKMC members have developed high-throughput gene trapping and, in particular, gene-targeting pipelines and generated more than 17,400 mutant murine embryonic stem (ES) cell clones and more than 1,700 mutant mouse strains, most of them conditional. A common IKMC web portal (www.knockoutmouse.org) has been established, allowing easy access to this unparalleled biological resource. The IKMC materials considerably enhance functional gene annotation of the mammalian genome and will have a major impact on future biomedical research

The mammalian gene function resource: The International Knockout Mouse Consortium

In 2007, the International Knockout Mouse Consortium (IKMC) made the ambitious promise to generate mutations in virtually every protein-coding gene of the mouse genome in a concerted worldwide action. Now, 5 years later, the IKMC members have developed highthroughput gene trapping and, in particular, gene-targeting pipelines and generated more than 17,400 mutant murine embryonic stem (ES) cell clones and more than 1,700 mutant mouse strains, most of them conditional. A common IKMC web portal (www.knockoutmouse.org) has been established, allowing easy access to this unparalleled biological resource. The IKMC materials considerably enhance functional gene annotation of the mammalian genome and will have a major impact on future biomedical research

Conditional gene trapping using the FLEx system.

The knowledge about the complete genome sequences of mouse, human, and other organisms is only the first step toward the functional annotation of all genes. It facilitates the recognition of sequence conservation, which helps to distinguish between important and not important and also coding from noncoding sequence. Nevertheless, approximately only 50% of all mouse genes have been entirely annotated to date. In the postgenomic era, large-scale projects have been initiated to describe also the expression (Emap, Eurexpress) and the function (International Gene Trap Consortium, Eucomm, Norcomm, Komp) of all mouse genes. By building up on these resources, the average amount of time starting from a gene-coding sequence to finally studying its function in a living organism or embryo, has shortened significantly within the last decade. Several recent developments, namely, in bioinformatics and gene synthesis but also in targeted and random mutagenesis have contributed to the current status. This chapter will highlight the milestones that have been undertaken in order to saturate the mouse genome with gene trap mutations. We have no intention to cover the entire field but will instead focus on most recent vectors and protocols, which have turned out to be most useful in order to promote the technology. Therefore, we apologize upfront to the many studies that could not be mentioned here solely owing to space limitations but which nevertheless made significant contributions to our current understanding. This chapter will finally provide guidance on possible uses of conditional gene trap alleles as well as detailed protocols for the application of this recent technology

Resources for proteomics in mouse embryonic stem cells.

no Abstract

Gene in der Falle : Mutagenese des Mausgenoms.

Der Schlüssel zum Verständnis humaner Erkrankungen liegt im Verständnis der Genfunktionen und der Interaktionen der beteiligten Proteine im Kontext des gesamten Organismus. Nur ein kleiner Teil der erblichen Krankheiten ist ausreichend verstanden um erfolgversprechende Ansätze für Therapien entwickeln zu können. Für den Großteil der genetisch bedingten Krankheiten sind die betrof- fenen Gene noch immer unbekannt im besten Fall sind verdächtige Kandidaten identifiziert worden. Um das Verständnis der Genfunktionen zu beschleunigen sind in den letzten Jahren die Genome zahlrei- cher Organismen darunter die des Menschen und der Maus fast vollständig sequenziert worden. Aufgrund der evolu- tionären Konservierung wichtiger Bereiche des Genoms lassen sich allein durch den V ergleich der Genome des Menschen und der Maus häufig die Sequenzen identifi- zieren, die für Proteine codieren oder aber wichtige regulatorische Funktionen besitzen. Zusätzlich werden bereits heute 8 0% der codierenden Sequenzen durch K ombinationen verschiedener Computer- programme identifiziert [1] . Mehrere Milli- onen sogenannte EST’s („expressed sequence tags“; kurze codierende Sequenzen unbekannter Herkunft) sowohl von der Maus als auch vom Menschen können zur Identifikation von Genen herangezogen werden. Computeralgo- rithmen finden jedoch nur die Gene, die den bislang bekannten Regeln folgen. Zudem sagen Sequenz und Struktur eines Gens nur wenig über dessen Funktion aus