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231224s2017 xx |||||o 00| ||eng c |
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|a 10.1016/j.clim.2017.03.010
|2 doi
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|a pubmed24n0901.xml
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|a (DE-627)NLM270481397
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|a (NLM)28359783
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|a (PII)S1521-6616(16)30508-3
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Grodecká, Lucie
|e verfasserin
|4 aut
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|a Systematic analysis of splicing defects in selected primary immunodeficiencies-related genes
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|c 2017
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 29.08.2017
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|a Date Revised 02.12.2018
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a Copyright © 2017 Elsevier Inc. All rights reserved.
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|a Both variants affecting splice sites and those in splicing regulatory elements (SREs) can impair pre-mRNA splicing, eventually leading to severe diseases. Despite the availability of many prediction tools, prognosis of splicing affection is not trivial, especially when SREs are involved. Here, we present data on 92 in silico-/55 minigene-analysed variants detected in genes responsible for the primary immunodeficiencies development (namely BTK, CD40LG, IL2RG, SERPING1, STAT3, and WAS). Of 20 splicing-affecting variants, 16 affected splice site while 4 disrupted potential SRE. The presence or absence of splicing defects was confirmed in 30 of 32 blood-derived patients' RNAs. Testing prediction tools performance, splice site disruptions and creations were reliably predicted in contrast to SRE-affecting variants for which just ESRseq, ΔHZEI-scores and EX-SKIP predictions showed promising results. Next, we found an interesting pattern in cryptic splice site predictions. These results might help PID-diagnosticians and geneticists cope with potential splicing-affecting variants
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|a Journal Article
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|a Cryptic splice sites
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|a Primary immunodeficiencies
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|a Splicing prediction
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|a Splicing-affecting variants
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|a CD40LIg fusion protein
|2 NLM
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|a Complement C1 Inactivator Proteins
|2 NLM
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|a Complement C1 Inhibitor Protein
|2 NLM
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|a IL2RG protein, human
|2 NLM
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|a Interleukin Receptor Common gamma Subunit
|2 NLM
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|a RNA, Messenger
|2 NLM
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|a Recombinant Fusion Proteins
|2 NLM
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|a SERPING1 protein, human
|2 NLM
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|a STAT3 Transcription Factor
|2 NLM
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|a STAT3 protein, human
|2 NLM
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|a WAS protein, human
|2 NLM
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|a Wiskott-Aldrich Syndrome Protein
|2 NLM
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|a Protein-Tyrosine Kinases
|2 NLM
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|a EC 2.7.10.1
|2 NLM
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|a Agammaglobulinaemia Tyrosine Kinase
|2 NLM
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|a EC 2.7.10.2
|2 NLM
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|a BTK protein, human
|2 NLM
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|a EC 2.7.10.2
|2 NLM
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|a Hujová, Pavla
|e verfasserin
|4 aut
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|a Kramárek, Michal
|e verfasserin
|4 aut
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|a Kršjaková, Tereza
|e verfasserin
|4 aut
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|a Kováčová, Tatiana
|e verfasserin
|4 aut
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|a Vondrášková, Katarína
|e verfasserin
|4 aut
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|a Ravčuková, Barbora
|e verfasserin
|4 aut
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|a Hrnčířová, Kristýna
|e verfasserin
|4 aut
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|a Souček, Přemysl
|e verfasserin
|4 aut
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|a Freiberger, Tomáš
|e verfasserin
|4 aut
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|i Enthalten in
|t Clinical immunology (Orlando, Fla.)
|d 1999
|g 180(2017) vom: 01. Juli, Seite 33-44
|w (DE-627)NLM098196855
|x 1521-7035
|7 nnns
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|g volume:180
|g year:2017
|g day:01
|g month:07
|g pages:33-44
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|u http://dx.doi.org/10.1016/j.clim.2017.03.010
|3 Volltext
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|a GBV_ILN_11
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|a GBV_ILN_24
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|a GBV_ILN_350
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|a AR
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|d 180
|j 2017
|b 01
|c 07
|h 33-44
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