5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition

      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

          Background

          The oocyte-to-embryo transition (OET) converts terminally differentiated gametes into a totipotent embryo and is critically controlled by maternal mRNAs and proteins, while the genome is silent until zygotic genome activation. How the transcriptome, translatome, and proteome are coordinated during this critical developmental window remains poorly understood.

          Results

          Utilizing a highly sensitive and quantitative mass spectrometry approach, we obtain high-quality proteome data spanning seven mouse stages, from full-grown oocyte (FGO) to blastocyst, using 100 oocytes/embryos at each stage. Integrative analyses reveal distinct proteome reprogramming compared to that of the transcriptome or translatome. FGO to 8-cell proteomes are dominated by FGO-stockpiled proteins, while the transcriptome and translatome are more dynamic. FGO-originated proteins frequently persist to blastocyst while corresponding transcripts are already downregulated or decayed. Improved concordance between protein and translation or transcription is observed for genes starting translation upon meiotic resumption, as well as those transcribed and translated only in embryos. Concordance between protein and transcription/translation is also observed for proteins with short half-lives. We built a kinetic model that predicts protein dynamics by incorporating both initial protein abundance in FGOs and translation kinetics across developmental stages.

          Conclusions

          Through integrative analyses of datasets generated by ultrasensitive methods, our study reveals that the proteome shows distinct dynamics compared to the translatome and transcriptome during mouse OET. We propose that the remarkably stable oocyte-originated proteome may help save resources to accommodate the demanding needs of growing embryos. This study will advance our understanding of mammalian OET and the fundamental principles governing gene expression.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13059-023-02997-8.

          Related collections

          Most cited references66

          • 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

            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

              A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
                Bookmark

                Author and article information

                Contributors
                xiewei121@tsinghua.edu.cn
                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1474-7596
                1474-760X
                13 July 2023
                13 July 2023
                2023
                : 24
                : 166
                Affiliations
                [1 ]GRID grid.12527.33, ISNI 0000 0001 0662 3178, Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, , Tsinghua University, ; Beijing, 100084 China
                [2 ]GRID grid.452723.5, ISNI 0000 0004 7887 9190, Tsinghua-Peking Center for Life Sciences, ; Beijing, China
                [3 ]GRID grid.12527.33, ISNI 0000 0001 0662 3178, School of Life Sciences, , Tsinghua University, ; Beijing, China
                [4 ]GRID grid.49470.3e, ISNI 0000 0001 2331 6153, School of Mathematics and Statistics, , Wuhan University, ; Wuhan, China
                [5 ]GRID grid.49470.3e, ISNI 0000 0001 2331 6153, Hubei Key Laboratory of Computational Science, , Wuhan University, ; Wuhan, China
                [6 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Academy for Advanced Interdisciplinary Studies, , Peking University, ; Beijing, 100871 China
                [7 ]GRID grid.452661.2, ISNI 0000 0004 1803 6319, Zhejiang Provincial Key Laboratory of Pancreatic Disease, School of Medicine, , the First Affiliated Hospital, Zhejiang University, ; Hangzhou, 310002 China
                Author information
                http://orcid.org/0000-0003-2126-3849
                Article
                2997
                10.1186/s13059-023-02997-8
                10347836
                37443062
                780df4d6-b5c5-4fb5-922b-c4f4ba31d94a
                © The Author(s) 2023

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 14 September 2022
                : 27 June 2023
                Funding
                Funded by: National Key R&D Program of China
                Award ID: 2022YFC2702300
                Award ID: 2019YFA0508900
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31988101
                Award ID: 31830047
                Award ID: 31725018
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100009592, Beijing Municipal Science and Technology Commission;
                Award ID: Z181100001318006
                Award Recipient :
                Funded by: Tsinghua-Peking Center for Life Sciences
                Funded by: HHMI International Research Scholar award
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Genetics
                proteome,translatome,transcriptome,oocyte-to-embryo transition,oet,early embryo development
                Genetics
                proteome, translatome, transcriptome, oocyte-to-embryo transition, oet, early embryo development

                Comments

                Comment on this article