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      Exome sequencing links the SUMO protease SENP7 with fatal arthrogryposis multiplex congenita, early respiratory failure and neutropenia

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          Abstract

          Background

          SUMOylation involves the attachment of small ubiquitin-like modifier (SUMO) proteins to specific lysine residues on thousands of substrates with target-specific effects on protein function. Sentrin-specific proteases (SENPs) are proteins involved in the maturation and deconjugation of SUMO. Specifically, SENP7 is responsible for processing polySUMO chains on targeted substrates including the heterochromatin protein 1α (HP1α).

          Methods

          We performed exome sequencing and segregation studies in a family with several infants presenting with an unidentified syndrome. RNA and protein expression studies were performed in fibroblasts available from one subject.

          Results

          We identified a kindred with four affected subjects presenting with a spectrum of findings including congenital arthrogryposis, no achievement of developmental milestones, early respiratory failure, neutropenia and recurrent infections. All died within four months after birth. Exome sequencing identified a homozygous stop gain variant in SENP7c.1474C>T; p.(Gln492*) as the probable aetiology. The proband’s fibroblasts demonstrated decreased mRNA expression. Protein expression studies showed significant protein dysregulation in total cell lysates and in the chromatin fraction. We found that HP1α levels as well as different histones and H3K9me3 were reduced in patient fibroblasts. These results support previous studies showing interaction between SENP7 and HP1α, and suggest loss of SENP7 leads to reduced heterochromatin condensation and subsequent aberrant gene expression.

          Conclusion

          Our results suggest a critical role for SENP7 in nervous system development, haematopoiesis and immune function in humans.

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          Most cited references41

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          The Perseus computational platform for comprehensive analysis of (prote)omics data.

          A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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            The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.

            MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs). The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at http://www.maxquant.org.
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              Selective recognition of methylated lysine 9 on histone H3 by the HP1 chromo domain.

              Heterochromatin protein 1 (HP1) is localized at heterochromatin sites where it mediates gene silencing. The chromo domain of HP1 is necessary for both targeting and transcriptional repression. In the fission yeast Schizosaccharomyces pombe, the correct localization of Swi6 (the HP1 equivalent) depends on Clr4, a homologue of the mammalian SUV39H1 histone methylase. Both Clr4 and SUV39H1 methylate specifically lysine 9 of histone H3 (ref. 6). Here we show that HP1 can bind with high affinity to histone H3 methylated at lysine 9 but not at lysine 4. The chromo domain of HP1 is identified as its methyl-lysine-binding domain. A point mutation in the chromo domain, which destroys the gene silencing activity of HP1 in Drosophila, abolishes methyl-lysine-binding activity. Genetic and biochemical analysis in S. pombe shows that the methylase activity of Clr4 is necessary for the correct localization of Swi6 at centromeric heterochromatin and for gene silencing. These results provide a stepwise model for the formation of a transcriptionally silent heterochromatin: SUV39H1 places a 'methyl marker' on histone H3, which is then recognized by HP1 through its chromo domain. This model may also explain the stable inheritance of the heterochromatic state.
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                Author and article information

                Contributors
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                Journal
                Journal of Medical Genetics
                J Med Genet
                BMJ
                0022-2593
                1468-6244
                October 24 2023
                November 2023
                November 2023
                July 17 2023
                : 60
                : 11
                : 1133-1141
                Article
                10.1136/jmg-2023-109267
                e16f280f-6961-4d55-9d43-41340be99c6b
                © 2023
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