Dataset Information

Building bridges to move recombination complexes.

ABSTRACT: A central feature of meiosis is pairing of homologous chromosomes, which occurs in two stages: coalignment of axes followed by installation of the synaptonemal complex (SC). Concomitantly, recombination complexes reposition from on-axis association to the SC central region. We show here that, in the fungus Sordaria macrospora, this critical transition is mediated by robust interaxis bridges that contain an axis component (Spo76/Pds5), DNA, plus colocalizing Mer3/Msh4 recombination proteins and the Zip2-Zip4 mediator complex. Mer3-Msh4-Zip2-Zip4 colocalizing foci are first released from their tight axis association, dependent on the SC transverse-filament protein Sme4/Zip1, before moving to bridges and thus to a between-axis position. Ensuing shortening of bridges and accompanying juxtaposition of axes to 100 nm enables installation of SC central elements at sites of between-axis Mer3-Msh4-Zip2-Zip4 complexes. We show also that the Zip2-Zip4 complex has an intrinsic affinity for chromosome axes at early leptotene, where it localizes independently of recombination, but is dependent on Mer3. Then, later, Zip2-Zip4 has an intrinsic affinity for the SC central element, where it ultimately localizes to sites of crossover complexes at the end of pachytene. These and other findings suggest that the fundamental role of Zip2-Zip4 is to mediate the recombination/structure interface at all post-double-strand break stages. We propose that Zip2-Zip4 directly mediates a molecular handoff of Mer3-Msh4 complexes, from association with axis components to association with SC central components, at the bridge stage, and then directly mediates central region installation during SC nucleation.

SUBMITTER: Dubois E

PROVIDER: S-EPMC6589682 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Building bridges to move recombination complexes.

Dubois Emeline E De Muyt Arnaud A Soyer Jessica L JL Budin Karine K Legras Mathieu M Piolot Tristan T Debuchy Robert R Kleckner Nancy N Zickler Denise D Espagne Eric E

Proceedings of the National Academy of Sciences of the United States of America 20190530 25

A central feature of meiosis is pairing of homologous chromosomes, which occurs in two stages: coalignment of axes followed by installation of the synaptonemal complex (SC). Concomitantly, recombination complexes reposition from on-axis association to the SC central region. We show here that, in the fungus <i>Sordaria macrospora</i>, this critical transition is mediated by robust interaxis bridges that contain an axis component (Spo76/Pds5), DNA, plus colocalizing Mer3/Msh4 recombination protein ...[more]

PMID: 31147459

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Project description:OBJECTIVE:Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to (1) infer phenotypic topics within patient populations and (2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems. METHODS:We adapt a generative topic modeling strategy, based on latent Dirichlet allocation, to infer phenotypic topics. We utilize a variance analysis to assess the projection of a patient population from one healthcare system onto the topics learned from another system. The consistency of learned phenotypic topics was evaluated using (1) the similarity of topics, (2) the stability of a patient population across topics, and (3) the transferability of a topic across sites. We evaluated our approaches using four months of inpatient data from two geographically distinct healthcare systems: (1) Northwestern Memorial Hospital (NMH) and (2) Vanderbilt University Medical Center (VUMC). RESULTS:The method learned 25 phenotypic topics from each healthcare system. The average cosine similarity between matched topics across the two sites was 0.39, a remarkably high value given the very high dimensionality of the feature space. The average stability of VUMC and NMH patients across the topics of two sites was 0.988 and 0.812, respectively, as measured by the Pearson correlation coefficient. Also the VUMC and NMH topics have smaller variance of characterizing patient population of two sites than standard clinical terminologies (e.g., ICD9), suggesting they may be more reliably transferred across hospital systems. CONCLUSIONS:Phenotypic topics learned from EHR data can be more stable and transferable than billing codes for characterizing the general status of a patient population. This suggests that EHR-based research may be able to leverage such phenotypic topics as variables when pooling patient populations in predictive models.

Dataset Information

Building bridges to move recombination complexes.

Publications

Building bridges to move recombination complexes.

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