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      Cryptic kin discrimination during communal lactation in mice favours cooperation between relatives

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          Abstract

          Breeding females can cooperate by rearing their offspring communally, sharing synergistic benefits of offspring care but risking exploitation by partners. In lactating mammals, communal rearing occurs mostly among close relatives. Inclusive fitness theory predicts enhanced cooperation between related partners and greater willingness to compensate for any partner under-investment, while females are less likely to bias investment towards own offspring. We use a dual isotopic tracer approach to track individual milk allocation when familiar pairs of sisters or unrelated house mice reared offspring communally. Closely related pairs show lower energy demand and pups experience better access to non-maternal milk. Lactational investment is more skewed between sister partners but females pay greater energetic costs per own offspring reared with an unrelated partner. The choice of close kin as cooperative partners is strongly favoured by these direct as well as indirect benefits, providing a driver to maintain female kin groups for communal breeding.

          Abstract

          A dual isotope tracer approach assessed milk allocation when pairs of sisters or unrelated female house mice reared offspring communally, revealing that females pay greater energetic costs when rearing offspring with an unrelated partner.

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          The PRIDE database and related tools and resources in 2019: improving support for quantification data

          Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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            Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

            Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.
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              The genetical evolution of social behaviour. I.

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                Author and article information

                Contributors
                jane.hurst@liverpool.ac.uk
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                15 July 2023
                15 July 2023
                2023
                : 6
                : 734
                Affiliations
                [1 ]GRID grid.10025.36, ISNI 0000 0004 1936 8470, Mammalian Behaviour & Evolution Group, , Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, ; Neston, CH64 7TE UK
                [2 ]GRID grid.10025.36, ISNI 0000 0004 1936 8470, Centre for Proteome Research, , Institute of Systems, Molecular and Integrative Biology, University of Liverpool, ; Crown Street, Liverpool, L69 7ZB UK
                [3 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Present Address: Department of Biology, , University of Oxford, ; 11a Mansfield Road, Oxford, OX1 3SZ UK
                [4 ]GRID grid.42475.30, ISNI 0000 0004 0605 769X, Present Address: MRC Laboratory of Molecular Biology, Francis Crick Avenue, , Cambridge Biomedical Campus, ; Cambridge, CB2 0QH UK
                Author information
                http://orcid.org/0000-0003-0857-495X
                http://orcid.org/0000-0002-3728-9624
                Article
                5115
                10.1038/s42003-023-05115-3
                10349843
                37454193
                6510c152-4014-438c-8f37-c96c6234c46e
                © 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 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 September 2022
                : 7 July 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000270, RCUK | Natural Environment Research Council (NERC);
                Award ID: NE/G018650
                Award ID: NE/G018650
                Award ID: NE/G018650
                Award ID: NE/G018650
                Award ID: NE/G018650
                Award ID: NE/G018650
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                © Springer Nature Limited 2023

                social evolution,animal behaviour
                social evolution, animal behaviour

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