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Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression.

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Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression.

Trends Genet. 2018 Jun 11;:

Authors: Hou J, van Leeuwen J, Andrews BJ, Boone C

Abstract
The phenotypic consequences of a given mutation can vary across individuals. This so-called background effect is widely observed, from mutant fitness of loss-of-function variants in model organisms to variable disease penetrance and expressivity in humans; however, the underlying genetic basis often remains unclear. Taking insights gained from recent large-scale surveys of genetic interaction and suppression analyses in yeast, we propose that the genetic network context for a given mutation may shape its propensity of exhibiting background-dependent phenotypes. We argue that further efforts in systematically mapping the genetic interaction networks beyond yeast will provide not only key insights into the functional properties of genes, but also a better understanding of the background effects and the (un)predictability of traits in a broader context.

PMID: 29903533 [PubMed - as supplied by publisher]



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Neural stem cell heterogeneity in the mammalian forebrain.

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Neural stem cell heterogeneity in the mammalian forebrain.

Prog Neurobiol. 2018 Jun 11;:

Authors: Adams KV, Morshead CM

Abstract
The brain was long considered an organ that underwent very little change after development. It is now well established that the mammalian central nervous system contains neural stem cells that generate progeny that are capable of making new neurons, astrocytes, and oligodendrocytes throughout life. The field has advanced rapidly as it strives to understand the basic biology of these precursor cells, and explore their potential to promote brain repair. The purpose of this review is to present current knowledge about the diversity of neural stem cells in vitro and in vivo, and highlight distinctions between neural stem cell populations, throughout development, and within the niche. A comprehensive understanding of neural stem cell heterogeneity will provide insights into the cellular and molecular regulation of neural development and lifelong neurogenesis, and will guide the development of novel strategies to promote regeneration and neural repair.

PMID: 29902499 [PubMed - as supplied by publisher]



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Map of synthetic rescue interactions for the Fanconi anemia DNA repair pathway identifies USP48.

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Map of synthetic rescue interactions for the Fanconi anemia DNA repair pathway identifies USP48.

Nat Commun. 2018 06 11;9(1):2280

Authors: Velimezi G, Robinson-Garcia L, Muñoz-Martínez F, Wiegant WW, Ferreira da Silva J, Owusu M, Moder M, Wiedner M, Rosenthal SB, Fisch KM, Moffat J, Menche J, van Attikum H, Jackson SP, Loizou JI

Abstract
Defects in DNA repair can cause various genetic diseases with severe pathological phenotypes. Fanconi anemia (FA) is a rare disease characterized by bone marrow failure, developmental abnormalities, and increased cancer risk that is caused by defective repair of DNA interstrand crosslinks (ICLs). Here, we identify the deubiquitylating enzyme USP48 as synthetic viable for FA-gene deficiencies by performing genome-wide loss-of-function screens across a panel of human haploid isogenic FA-defective cells (FANCA, FANCC, FANCG, FANCI, FANCD2). Thus, as compared to FA-defective cells alone, FA-deficient cells additionally lacking USP48 are less sensitive to genotoxic stress induced by ICL agents and display enhanced, BRCA1-dependent, clearance of DNA damage. Consequently, USP48 inactivation reduces chromosomal instability of FA-defective cells. Our results highlight a role for USP48 in controlling DNA repair and suggest it as a potential target that could be therapeutically exploited for FA.

PMID: 29891926 [PubMed - indexed for MEDLINE]



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The budding yeast RSC complex maintains ploidy by promoting spindle pole body insertion.

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The budding yeast RSC complex maintains ploidy by promoting spindle pole body insertion.

J Cell Biol. 2018 Jun 06;:

Authors: Sing TL, Hung MP, Ohnuki S, Suzuki G, San Luis BJ, McClain M, Unruh JR, Yu Z, Ou J, Marshall-Sheppard J, Huh WK, Costanzo M, Boone C, Ohya Y, Jaspersen SL, Brown GW

Abstract
Ploidy is tightly regulated in eukaryotic cells and is critical for cell function and survival. Cells coordinate multiple pathways to ensure replicated DNA is segregated accurately to prevent abnormal changes in chromosome number. In this study, we characterize an unanticipated role for the Saccharomyces cerevisiae "remodels the structure of chromatin" (RSC) complex in ploidy maintenance. We show that deletion of any of six nonessential RSC genes causes a rapid transition from haploid to diploid DNA content because of nondisjunction events. Diploidization is accompanied by diagnostic changes in cell morphology and is stably maintained without further ploidy increases. We find that RSC promotes chromosome segregation by facilitating spindle pole body (SPB) duplication. More specifically, RSC plays a role in distributing two SPB insertion factors, Nbp1 and Ndc1, to the new SPB. Thus, we provide insight into a role for a SWI/SNF family complex in SPB duplication and ploidy maintenance.

PMID: 29875260 [PubMed - as supplied by publisher]



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Transfer learning for biomedical named entity recognition with neural networks.

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Transfer learning for biomedical named entity recognition with neural networks.

Bioinformatics. 2018 Jun 01;:

Authors: Giorgi JM, Bader GD

Abstract
Motivation: The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases, and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER.
Results: We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target data sets with a small number of labels (approximately 6000 or less).
Availability and implementation: Source code for the LSTM-CRF is available athttps://github.com/Franck-Dernoncourt/NeuroNER/ and links to the corpora are available athttps://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/.
Contact: john.giorgi@utoronto.ca.
Supplementary information: Supplementary data are available at Bioinformatics online.

PMID: 29868832 [PubMed - as supplied by publisher]



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Modulating cell state to enhance suspension expansion of human pluripotent stem cells.

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Modulating cell state to enhance suspension expansion of human pluripotent stem cells.

Proc Natl Acad Sci U S A. 2018 06 19;115(25):6369-6374

Authors: Lipsitz YY, Woodford C, Yin T, Hanna JH, Zandstra PW

Abstract
The development of cell-based therapies to replace missing or damaged tissues within the body or generate cells with a unique biological activity requires a reliable and accessible source of cells. Human pluripotent stem cells (hPSC) have emerged as a strong candidate cell source capable of extended propagation in vitro and differentiation to clinically relevant cell types. However, the application of hPSC in cell-based therapies requires overcoming yield limitations in large-scale hPSC manufacturing. We explored methods to convert hPSC to alternative states of pluripotency with advantageous bioprocessing properties, identifying a suspension-based small-molecule and cytokine combination that supports increased single-cell survival efficiency, faster growth rates, higher densities, and greater expansion than control hPSC cultures. ERK inhibition was found to be essential for conversion to this altered state, but once converted, ERK inhibition led to a loss of pluripotent phenotype in suspension. The resulting suspension medium formulation enabled hPSC suspension yields 5.7 ± 0.2-fold greater than conventional hPSC in 6 d, for at least five passages. Treated cells remained pluripotent, karyotypically normal, and capable of differentiating into all germ layers. Treated cells could also be integrated into directed differentiated strategies as demonstrated by the generation of pancreatic progenitors (NKX6.1+/PDX1+ cells). Enhanced suspension-yield hPSC displayed higher oxidative metabolism and altered expression of adhesion-related genes. The enhanced bioprocess properties of this alternative pluripotent state provide a strategy to overcome cell manufacturing limitations of hPSC.

PMID: 29866848 [PubMed - indexed for MEDLINE]



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The role of biomaterials in overcoming barriers to regeneration in the central nervous system.

The role of biomaterials in overcoming barriers to regeneration in the central nervous system.

Biomed Mater. 2018 Jun 04;13(5):050201

Authors: Führmann T, Shoichet MS

PMID: 29864020 [PubMed - in process]



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Patient Similarity Networks for Precision Medicine.

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Patient Similarity Networks for Precision Medicine.

J Mol Biol. 2018 May 31;:

Authors: Pai S, Bader GD

Abstract
Clinical research and practice in the 21st century is poised to be transformed by analysis of computable electronic medical records and population-level genome-scale patient profiles. Genomic data captures genetic and environmental state, providing information about heterogeneity in disease and treatment outcome, but genomic-based clinical risk scores are limited. Achieving the goal of routine precision medicine that takes advantage of this rich genomics data will require computational methods that support heterogeneous data, have excellent predictive performance, and ideally, provide biologically-interpretable results. Traditional machine-learning approaches excel at performance, but often have limited interpretability. Patient similarity networks are an emerging paradigm for precision medicine, in which patients are clustered or classified based on their similarities in various features, including genomic profiles. This strategy is analogous to standard medical diagnosis, has excellent performance, is interpretable, and can preserve patient privacy. We review new methods based on patient similarity networks, including Similarity Network Fusion for patient clustering and netDx for patient classification. While these methods are already useful, much work is required to improve their scalability for contemporary genetic cohorts, optimize parameters, and incorporate a wide range of genomics and clinical data. The coming five years will provide an opportunity to assess the utility of network-based algorithms for precision medicine.

PMID: 29860027 [PubMed - as supplied by publisher]



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Antibody-Antisense Oligonucleotide Conjugate Downregulates a Key Gene in Glioblastoma Stem Cells.

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Antibody-Antisense Oligonucleotide Conjugate Downregulates a Key Gene in Glioblastoma Stem Cells.

Mol Ther Nucleic Acids. 2018 Jun 01;11:518-527

Authors: Arnold AE, Malek-Adamian E, Le PU, Meng A, Martínez-Montero S, Petrecca K, Damha MJ, Shoichet MS

Abstract
Glioblastoma stem cells (GSCs) are invasive, treatment-resistant brain cancer cells that express downregulated in renal cell carcinoma (DRR), also called FAM107A, a genetic driver of GSC invasion. We developed antibody-antisense oligonucleotide (AON) conjugates to target and reduce DRR/FAM107A expression. Specifically, we used antibodies against antigens expressed on the GSCs, such as CD44 and EphA2, conjugated to chemically modified AONs against DRR/FAM107A, which were designed as chimeras of DNA and 2'-deoxy-2'-fluoro-beta-D-arabinonucleic acid (FANA) for increased nuclease stability and mRNA affinity. We demonstrate that these therapeutic conjugates successfully internalize, accumulate, and reduce DRR/FAM107A expression in patient-derived GSCs. This is the first example of an antibody-antisense strategy against cancer stem cells.

PMID: 29858087 [PubMed]



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Mapping DNA damage-dependent genetic interactions in yeast via party mating and barcode fusion genetics.

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Mapping DNA damage-dependent genetic interactions in yeast via party mating and barcode fusion genetics.

Mol Syst Biol. 2018 05 28;14(5):e7985

Authors: Díaz-Mejía JJ, Celaj A, Mellor JC, Coté A, Balint A, Ho B, Bansal P, Shaeri F, Gebbia M, Weile J, Verby M, Karkhanina A, Zhang Y, Wong C, Rich J, Prendergast D, Gupta G, Öztürk S, Durocher D, Brown GW, Roth FP

Abstract
Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via en masse "party" mating can also be monitored en masse for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1, SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53.

PMID: 29807908 [PubMed - indexed for MEDLINE]



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