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    Metadata for: ‘Long-read sequencing identifies copy-specific markers of SMN gene conversion in spinal muscular atrophy’

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    Description This DataverseNL item contains the metadata of the Nanopore sequencing dataset and limited clinical data used in ‘Long-read sequencing identifies copy-specific markers of SMN gene conversion in spinal muscular atrophy’. Access to this data is restricted due to privacy regulations; conditions and instructions for access are listed below. Abstract Background: The complex 2 Mb survival motor neuron (SMN) locus on chromosome 5q13, including the spinal muscular atrophy (SMA)-causing gene SMN1 and modifier SMN2, remains incompletely resolved due to numerous segmental duplications. Variation in SMN2 copy number, presumably influenced by SMN1 to SMN2 gene conversion, affects disease severity, though SMN2 copy number alone has insufficient prognostic value due to limited genotype-phenotype correlations. With advancements in newborn screening and SMN-targeted therapies, identifying genetic markers to predict disease progression and treatment response is crucial. Progress has thus far been limited by methodological constraints. Methods: To address this, we developed HapSMA, a method to perform polyploid phasing of the SMN locus to enable copy-specific analysis of SMN and its surrounding genes. We used HapSMA on publicly available Oxford Nanopore Technologies (ONT) sequencing data of 29 healthy controls and performed long-read, targeted ONT sequencing of the SMN locus of 31 patients with SMA. Results: In healthy controls, we identified single nucleotide variants (SNVs) specific to SMN1 and SMN2 haplotypes that could serve as gene conversion markers. Broad phasing including the NAIP gene allowed for a more complete view of SMN locus variation. Genetic variation in SMN2 haplotypes was larger in SMA patients. 42% of SMN2 haplotypes of SMA patients showed varying SMN1 to SMN2 gene conversion breakpoints, serving as direct evidence of gene conversion as a common genetic characteristic in SMA and highlighting the importance of inclusion of SMA patients when investigating the SMN locus. Conclusions: Our findings illustrate that both methodological advances and the analysis of patient samples are required to advance our understanding of complex genetic loci and address critical clinical challenges. Github The code for HapSMA is available at: https://github.com/UMCUGenetics/HapSMA (v1.0.0 was used for analyses in this study, v1.1.0 contains extra support for different types of data input). The code for analyses subsequent to HapSMA and input files used in these analyses are available at: https://github.com/UMCUGenetics/ManuscriptSMNGeneConversion. IRB approval The study protocol (09307/NL29692.041.09) was approved by the Medical Ethical Committee of the University Medical Center Utrecht and registered at the Dutch registry for clinical studies and trials (https://www.ccmo.nl/). Written informed consent was obtained from all adult patients, and from patients and/or parents additionally in case of children younger than 18 years old. Contact information Requests for data can be made by contacting the principal investigators of this study, Ludo van der Pol ([email protected]), Gijs van Haaften ([email protected]) or Ewout Groen ([email protected]) at University Medical Center Utrecht UMC Utrecht Brain Center Heidelberglaan 100 3584 CX Utrecht The Netherlands Expected response time for processing a data sharing agreement is 4 to 6 weeks. <br/

    Ewout van Alphen boert in Tanzania: BD-boerderij met 100 weeskinderen

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    Ewout van Alphen heeft een biologisch-dynamische boerderij in Tanzania, waar hij dagelijks 100 weeskinderen opvangt en te eten geeft. Een reportag

    Restricting access to the NHS for undocumented migrants is bad policy at high cost

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    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Charging migrants for access to health services will not reduce strain on the NHS, say Lilana Keith and Ewout van Ginneke

    Dreams don’t work unless you do: challenges of meaningful technology transfer from research to medtech

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    Technology Transfer Offices are aimed at valorisation and spinning out technology. But what if that happens from within? Switching from a valorisation position to an entrepreneurial one makes sense but is not always the easiest road. Based on the MOLECUBES case study, Dr Ewout Vansteenkiste will give a personal testimonial of what it takes to set-up your own company in the field of preclinical imaging and the growing pains of being part of as well as dealing with Technology Transfer departments, VC’s and Business Angels in the process. &nbsp; https://be.linkedin.com/in/ewoutvansteenkiste</p

    Introduction

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    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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