Global network analysis in Schizosaccharomyces pombe reveals three distinct consequences of the common 1-kb deletion causing juvenile CLN3 disease.
Global network analysis in Schizosaccharomyces pombe reveals three distinct consequences of the common 1-kb deletion causing juvenile CLN3 disease.
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DOI：
10.1038/s41598-021-85471-4
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发表时间：
2021-03-18
影响因子：
4.6
通讯作者：
Mole SE
中科院分区：
文献类型：
--
作者：
Minnis CJ;Townsend S;Petschnigg J;Tinelli E;Bähler J;Russell C;Mole SE
幼年型CLN 3疾病是一种遗传性神经退行性疾病，大多数患者的CLN 3基因内缺失为1-kb纯合子。btn 1基因是粟酒裂殖酵母CLN 3的直向同源物。在这里，我们扩展了合成基因阵列（SGA）分析的使用，以描绘除了btn 1完全缺失之外的两种不同致病突变的功能特征。我们表明，遗传相互作用的签名可以不同的突变在同一个基因，这有助于剖析其独特的功能效应。与1-kb缺失（btn 1102 - 208 del）产生的次要转录物等同的突变显示出不同的相互作用模式。两者合计，我们的研究结果表明，轻微的1-kb缺失转录有三个后果CLN 3：既失去和保留一些固有的功能，并获得异常的特性。这对青少年CLN 3疾病的治疗开发具有特别的意义。此外，这一概念的证明可以应用于其他孟德尔疾病的保守基因或任何感兴趣的基因，帮助解剖其功能结构域，解开疾病发病机制的全球后果，并澄清基因型-表型相关性。在这样做的过程中，这个细节将提高个性化医疗的目标，以改善治疗结果和减少不良事件。
Juvenile CLN3 disease is a recessively inherited paediatric neurodegenerative disorder, with most patients homozygous for a 1-kb intragenic deletion in CLN3. The btn1 gene is the Schizosaccharomyces pombe orthologue of CLN3. Here, we have extended the use of synthetic genetic array (SGA) analyses to delineate functional signatures for two different disease-causing mutations in addition to complete deletion of btn1. We show that genetic-interaction signatures can differ for mutations in the same gene, which helps to dissect their distinct functional effects. The mutation equivalent to the minor transcript arising from the 1-kb deletion (btn1102–208del) shows a distinct interaction pattern. Taken together, our results imply that the minor 1-kb deletion transcript has three consequences for CLN3: to both lose and retain some inherent functions and to acquire abnormal characteristics. This has particular implications for the therapeutic development of juvenile CLN3 disease. In addition, this proof of concept could be applied to conserved genes for other mendelian disorders or any gene of interest, aiding in the dissection of their functional domains, unpacking the global consequences of disease pathogenesis, and clarifying genotype–phenotype correlations. In doing so, this detail will enhance the goals of personalised medicine to improve treatment outcomes and reduce adverse events.
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影响因子：
11
作者：
Clark, Michael B.;Wrzesinski, Tomasz;Tunbridge, Elizabeth M.
通讯作者：
Tunbridge, Elizabeth M.
影响因子：
3.5
作者：
Elshatory, Y;Brooks, AI;Pearce, DA
通讯作者：
Pearce, DA
影响因子：
64.5
作者：
FINLEY, D;OZKAYNAK, E;VARSHAVSKY, A
通讯作者：
VARSHAVSKY, A
影响因子：
25
作者：
Brichta, Lars;Shin, William;Greengard, Paul
通讯作者：
Greengard, Paul
DOI：
10.1093/bioinformatics/btp101
发表时间：
2009-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Bindea G;Mlecnik B;Hackl H;Charoentong P;Tosolini M;Kirilovsky A;Fridman WH;Pagès F;Trajanoski Z;Galon J
通讯作者：
Galon J