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      Variant-specific pathophysiological mechanisms of AFF3 differently influence transcriptome profiles

      Preprint
      research-article
      1 , 1 , 2 , 3 , 1 , 4 , 5 , 6 , 5 , 6 , 7 , 7 , 7 , 8 , 9 , 10 , 10 , 10 , 11 , 11 , 12 , 12 , 12 , 13 , 14 , 14 , 15 , 16 , 16 , 17 , 18 , 18 , 18 , 19 , 20 , 21 , 18 , 21 , 22 , 22 , 23 , 24 , 25 , 25 , 26 , 26 , 27 , 27 , 28 , 29 , 29 , 30 , 28 , 29 , 31 , 32 , 31 , 33 , 33 , 34 , 2 , 3 , 2 , 3 , 1
      medRxiv
      Cold Spring Harbor Laboratory
      mesomelic dysplasia, horseshoe kidney, intellectual disability, transcriptome, exome

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          Abstract

          Background

          We previously described the KINSSHIP syndrome, an autosomal dominant disorder associated with intellectual disability (ID), mesomelic dysplasia and horseshoe kidney,caused by de novo variants in the degron of AFF3. Mouse knock-ins and overexpression in zebrafish provided evidence for a dominant-negative (DN) mode-of-action, wherein an increased level of AFF3 resulted in pathological effects.

          Methods

          Evolutionary constraints suggest that other mode-of-inheritance could be at play. We challenged this hypothesis by screening ID cohorts for individuals with predicted-to-be deleterious variants in AFF3. We used both animal and cellular models to assess the deleteriousness of the identified variants.

          Results

          We identified an individual with a KINSSHIP-like phenotype carrying a de novo partial duplication of AFF3 further strengthening the hypothesis that an increased level of AFF3 is pathological. We also detected seventeen individuals displaying a milder syndrome with either heterozygous LoF or biallelic missense variants in AFF3. Consistent with semi-dominance, we discovered three patients with homozygous LoF and one compound heterozygote for a LoF and a missense variant, who presented more severe phenotypes than their heterozygous parents. Matching zebrafish knockdowns exhibit neurological defects that could be rescued by expressing human AFF3 mRNA, confirming their association with the ablation of aff3. Conversely, some of the human AFF3 mRNAs carrying missense variants identified in affected individuals did not complement. Overexpression of mutated AFF3 mRNAs in zebrafish embryos produced a significant increase of abnormal larvae compared to wild-type overexpression further demonstrating deleteriousness. To further assess the effect of AFF3 variation, we profiled the transcriptome of fibroblasts from affected individuals and engineered isogenic cells harboring +/+, DN/DN, LoF/+, LoF/LoF or DN/LoF AFF3 genotypes. The expression of more than a third of the AFF3 bound loci is modified in either the DN/DN or the LoF/LoF lines. While the same pathways are affected, only about one-third of the differentially expressed genes are common to these homozygote datasets, indicating that AFF3 LoF and DN variants largely modulate transcriptomes differently, e.g. the DNA repair pathway displayed opposite modulation.

          Conclusions

          Our results and the high pleiotropy shown by variation at this locus suggest that minute changes in AFF3 function are deleterious.

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          Most cited references61

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          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.
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            Fiji: an open-source platform for biological-image analysis.

            Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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              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/.
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                Author and article information

                Journal
                medRxiv
                MEDRXIV
                medRxiv
                Cold Spring Harbor Laboratory
                17 January 2024
                : 2024.01.14.24301100
                Affiliations
                [1 ]Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
                [2 ]Bioinformatics Competence Center, University of Lausanne, Lausanne, Switzerland
                [3 ]Bioinformatics Competence Center, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
                [4 ]Biostatistics platform, University of Lausanne, Lausanne, Switzerland
                [5 ]Department of Neurosciences Rita Levi-Montalcini, University of Turin, 10126 Turin, Italy
                [6 ]Medical Genetics Unit, Città della Salute e della Scienza University Hospital, 10126 Turin, Italy
                [7 ]Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
                [8 ]Department of Pediatrics, Centre for Neuromedicine, Gemeinschaftskrankenhaus Herdecke Gerhard-Kienle-Weg, Herdecke, Germany
                [9 ]Genomics Analysis 396, ARUP Laboratories, Salt Lake City, Utah, USA
                [10 ]Pediatric Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
                [11 ]Department of Pediatrics, Medical Center North, Vanderbilt University Medical Center, Nashville, Tennessee, USA
                [12 ]Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands
                [13 ]Center for genetic developmental disorders southwest, Zuidwester, Middelharnis, The Netherlands
                [14 ]Department of Medical Genetics, University Hospital of North Norway, Tromsø, Norway
                [15 ]Department of Pediatric Rehabilitation, University Hospital of North Norway, Tromsø, Norway
                [16 ]Greenwood Genetic Center, Greenwood, South Carolina, USA
                [17 ]Pacific Northwest Research Institute (PNRI), Broadway, Seattle, Washington, USA
                [18 ]Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
                [19 ]Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
                [20 ]Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
                [21 ]Texas Children’s Hospital, Houston, Texas, USA
                [22 ]Hospital Ángeles Puebla, Puebla, Mexico
                [23 ]CHU Lille, Clinique de génétique, F-59000 Lille, France
                [24 ]Inserm UMR1231, University of Burgundy, 21000 Dijon, France
                [25 ]GeneDx, Gaithersburg, Maryland, USA
                [26 ]Department of Genetics, Cook Children’s Medical Center, Cook Children’s Health Care System, Fort Worth, Texas, USA
                [27 ]Institute for Human Genetics, University Hospital Muenster, Muenster, Germany
                [28 ]Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132, Genoa, Italy
                [29 ]Medical Genetics Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy
                [30 ]Child and Adolescent Neuropsychiatry Unit, Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
                [31 ]Clinical Institute of Genomic Medicine, University Medical Centre Ljubljana, Ljubljana, Slovenia
                [32 ]Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
                [33 ]Department of Genomics, Turku University Hospital, Turku, Finland; University of Turku, Turku, Finland
                [34 ]Department of Pediatric Neurology, Turku University Hospital, Turku, Finland; University of Turku, Turku, Finland
                Author notes
                [*]

                Institute of Medical Genetics, University of Zurich, Zurich, Switzerland

                [$]

                Department of Molecular Medicine, University of Pavia, Pavia, Italy and Medical Genetics Unit, IRCCS San Matteo Foundation, Pavia, Italy

                [+]

                Mayo Clinic, Rochester, Minnesota, USA

                [#]

                Sophia Genetics, St Sulpice, Switzerland

                Authors contributions

                SB, JC, NV, BY engineered and phenotyped animal and cell models. GA, FS and CI analyzed transcriptomes profiles. NG 3D-modeled missense variants. AB, FS, LT, SS, RAJ, J-US, DD, PB-T, GRN, KNW, LD, MM, CG, LELMV, RP, RK, HY, GÅMH, CJ, MFS, KMB, MJL, CMBC, CZ, JRL, LP, LF-G, RM-T, FP, AT, HZE, LM, MK, OK, JH, MS, MI, FO, FZ, KW, AM, MKH, PP and HA collected clinical information and genomic DNAs, sequenced and analyzed exomes and/or genomes. AR and SB conceived the study and wrote the manuscript. All other authors commented on the manuscript.

                Correspondence to : Alexandre Reymond, Center for Integrative Genomics, University of Lausanne, Genopode building, CH-1015 Lausanne, Switzerland, alexandre.reymond@ 123456unil.ch
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                Article
                10.1101/2024.01.14.24301100
                10827271
                38293053
                6b97588c-4ee0-4464-9cbe-fed0b97ce1ad

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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                mesomelic dysplasia,horseshoe kidney,intellectual disability,transcriptome,exome

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