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      A complementary approach for genetic diagnosis of inborn errors of immunity using proteogenomic analysis

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          Abstract

          Advances in next-generation sequencing technology have identified many genes responsible for inborn errors of immunity (IEI). However, there is still room for improvement in the efficiency of genetic diagnosis. Recently, RNA sequencing and proteomics using peripheral blood mononuclear cells (PBMCs) have gained attention, but only some studies have integrated these analyses in IEI. Moreover, previous proteomic studies for PBMCs have achieved limited coverage (approximately 3000 proteins). More comprehensive data are needed to gain valuable insights into the molecular mechanisms underlying IEI. Here, we propose a state-of-the-art method for diagnosing IEI using PBMCs proteomics integrated with targeted RNA sequencing (T-RNA-seq), providing unique insights into the pathogenesis of IEI. This study analyzed 70 IEI patients whose genetic etiology had not been identified by genetic analysis. In-depth proteomics identified 6498 proteins, which covered 63% of 527 genes identified in T-RNA-seq, allowing us to examine the molecular cause of IEI and immune cell defects. This integrated analysis identified the disease-causing genes in four cases undiagnosed in previous genetic studies. Three of them could be diagnosed by T-RNA-seq, while the other could only be diagnosed by proteomics. Moreover, this integrated analysis showed high protein–mRNA correlations in B- and T-cell-specific genes, and their expression profiles identified patients with immune cell dysfunction. These results indicate that integrated analysis improves the efficiency of genetic diagnosis and provides a deep understanding of the immune cell dysfunction underlying the etiology of IEI. Our novel approach demonstrates the complementary role of proteogenomic analysis in the genetic diagnosis and characterization of IEI.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            limma powers differential expression analyses for RNA-sequencing and microarray studies

            limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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              Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

              The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PNAS Nexus
                PNAS Nexus
                pnasnexus
                PNAS Nexus
                Oxford University Press (US )
                2752-6542
                April 2023
                28 March 2023
                28 March 2023
                : 2
                : 4
                : pgad104
                Affiliations
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics and Developmental Biology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU) , 1-5-45 Yushima, Bunkyo City, Tokyo 113-0034, Japan
                Department of Pediatrics and Developmental Biology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU) , 1-5-45 Yushima, Bunkyo City, Tokyo 113-0034, Japan
                Department of Pediatrics, Kyoto University Graduate School of Medicine , 54 Shogoin Kawaharacho, Sakyo Ward, Kyoto City 606-8507, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, Kyoto University Graduate School of Medicine , 54 Shogoin Kawaharacho, Sakyo Ward, Kyoto City 606-8507, Japan
                Department of Pediatrics, Kyoto University Graduate School of Medicine , 54 Shogoin Kawaharacho, Sakyo Ward, Kyoto City 606-8507, Japan
                Department of Pediatrics, National Defense Medical College , 3-2 Namiki, Tokorozawa City, Saitama 359-8513, Japan
                Kazusa DNA Research Institute , 2-6-7 Kazusakamatari, Kisarazu City, Chiba 292-0818, Japan
                Kazusa DNA Research Institute , 2-6-7 Kazusakamatari, Kisarazu City, Chiba 292-0818, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Department of Pediatrics, National Defense Medical College , 3-2 Namiki, Tokorozawa City, Saitama 359-8513, Japan
                Department of Pediatrics, National Defense Medical College , 3-2 Namiki, Tokorozawa City, Saitama 359-8513, Japan
                Department of Pediatrics, Kyoto University Graduate School of Medicine , 54 Shogoin Kawaharacho, Sakyo Ward, Kyoto City 606-8507, Japan
                Department of Pediatrics, Gifu University Graduate School of Medicine , 1-1 Yanagido, Gifu City 501-1112, Japan
                Department of Pediatrics and Developmental Biology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU) , 1-5-45 Yushima, Bunkyo City, Tokyo 113-0034, Japan
                Kazusa DNA Research Institute , 2-6-7 Kazusakamatari, Kisarazu City, Chiba 292-0818, Japan
                Department of Pediatrics, Hiroshima University Graduate School of Biomedical and Health Sciences , 1-2-3 Kasumi, Minami Ward, Hiroshima 734-8551, Japan
                Author notes
                To whom correspondence should be addressed. Email: sokada@ 123456hiroshima-u.ac.jp ; ohara@ 123456kazusa.or.jp

                Competing Interest: The authors declare no competing interest.

                Author information
                https://orcid.org/0000-0003-1424-2433
                https://orcid.org/0000-0003-0036-451X
                https://orcid.org/0000-0003-3257-5071
                https://orcid.org/0000-0002-3328-9571
                https://orcid.org/0000-0002-4622-5657
                Article
                pgad104
                10.1093/pnasnexus/pgad104
                10109033
                37077884
                2ceaa4b7-08a7-499e-91fc-995dffcb2556
                © The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 November 2022
                : 06 March 2023
                : 17 March 2023
                : 17 April 2023
                Page count
                Pages: 12
                Funding
                Funded by: Japan Agency for Medical Research and Development (AMED), doi 10.13039/100009619;
                Award ID: JP20ek0109480
                Funded by: Japan Society for the Promotion of Science (JSPS) KAKENHI, doi 10.13039/501100001691;
                Award ID: JP18KK0228
                Award ID: 19H03620
                Award ID: 22H03041
                Categories
                Biological, Health, and Medical Sciences
                Immunology and Inflammation
                AcademicSubjects/MED00010
                AcademicSubjects/SCI00010
                AcademicSubjects/SOC00010

                proteomics,inborn errors of immunity,targeted rna sequencing,genetic diagnosis

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