50
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Pre- and peri-implantation Zika virus infection impairs fetal development by targeting trophectoderm cells

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Zika virus (ZIKV) infection results in an increased risk of spontaneous abortion and poor intrauterine growth although the underlying mechanisms remain undetermined. Little is known about the impact of ZIKV infection during the earliest stages of pregnancy, at pre- and peri-implantation, because most current ZIKV pregnancy studies have focused on post-implantation stages. Here, we demonstrate that trophectoderm cells of pre-implantation human and mouse embryos can be infected with ZIKV, and propagate virus causing neural progenitor cell death. These findings are corroborated by the dose-dependent nature of ZIKV susceptibility of hESC-derived trophectoderm cells. Single blastocyst RNA-seq reveals key transcriptional changes upon ZIKV infection, including nervous system development, prior to commitment to the neural lineage. The pregnancy rate of mice is >50% lower in pre-implantation infection than infection at E4.5, demonstrating that pre-implantation ZIKV infection leads to miscarriage. Cumulatively, these data elucidate a previously unappreciated association of pre- and peri-implantation ZIKV infection and microcephaly.

          Abstract

          Here, using human cells and mouse models, the authors show that Zika virus can infect preimplantation trophectoderm. Pre-implantation infection can affect nervous system development and survival of neural progenitors, and can result in miscarriage or spontaneous abortion.

          Related collections

          Most cited references62

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

              Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
                Bookmark

                Author and article information

                Contributors
                hes2011@med.cornell.edu
                res2025@med.cornell.edu
                shc2034@med.cornell.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                13 September 2019
                13 September 2019
                2019
                : 10
                : 4155
                Affiliations
                [1 ]ISNI 000000041936877X, GRID grid.5386.8, Department of Surgery, , Weill Cornell Medical College, ; 1300 York Ave, New York, NY 10065 USA
                [2 ]ISNI 000000041936877X, GRID grid.5386.8, Department of Cell and Developmental Biology, , Weill Cornell Medical College, ; 1300 York Ave, New York, NY 10065 USA
                [3 ]ISNI 0000 0001 2171 9952, GRID grid.51462.34, The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, , Sloan Kettering Institute, ; 1275 York Avenue, New York, NY 10065 USA
                [4 ]ISNI 000000041936877X, GRID grid.5386.8, Physiology Biophysics and Systems Biology, , Weill Cornell Medical College, ; 1300 York Ave, New York, NY 10065 USA
                [5 ]ISNI 000000041936877X, GRID grid.5386.8, Genomics Resources Core Facility, , Weill Cornell Medical College, ; 1300 York Ave, New York, NY 10065 USA
                [6 ]ISNI 0000 0004 5906 3313, GRID grid.430819.7, New York Stem Cell Foundation, ; 619 W 54th St, New York, NY 10019 USA
                [7 ]ISNI 0000 0004 1937 0247, GRID grid.5841.8, Department of Physiology, Cellular Biology and Immunology, Faculty of Biology, , University of Barcelona, ; Diagonal 643, Barcelona, 08028 Spain
                Author information
                http://orcid.org/0000-0002-8473-4911
                http://orcid.org/0000-0001-5396-918X
                http://orcid.org/0000-0002-1850-1642
                http://orcid.org/0000-0001-7217-768X
                Article
                12063
                10.1038/s41467-019-12063-2
                6744420
                31519912
                d3d5128e-95c0-41f3-a799-b6eda6327253
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 August 2018
                : 19 August 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000062, U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases);
                Award ID: DP3DK111907-01
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100012636, New York State Stem Cell Science (NYSTEM);
                Award ID: C029156
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                embryology,viral pathogenesis,translational research
                Uncategorized
                embryology, viral pathogenesis, translational research

                Comments

                Comment on this article