Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.705562
Title: Genetic and symptomatic variations in Myotonic Dystrophy Type 1
Author: Nasser, Khalidah K.
ISNI:       0000 0004 6060 536X
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 2016
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Abstract:
Myotonic dystrophy type 1 (DM1) is an extremely variable genetic disorder showing an autosomal dominant inheritance that is characterised by myotonia, insulin resistance, cardiac conduction defects and cataracts. It is caused by a trinucleotide repeat expansion of CTG sequence located in the 3’-untranslated region of the dystrophia myotonica-protein kinase (DMPK) gene on chromosome 19 at q13.3. The severity of symptoms ranges from mild adult onset to severe congenital form. A characteristic clinical feature of DM1 is anticipation phenomenon where disease severity increases and age of onset decreases over successive generations. The DM1 mutation is highly unstable in both the germline and soma, and showed to be an age-dependent, tissue-specific (skeletal muscles comprised the largest allele length of approximately thousand units) and expansion biased. The unaffected level of the repeat sequence falls between ~5-37 repeats whereas the disease associated range starts from ~50 repeats, reaching several thousand units. These properties account for the observed anticipation and contribute toward the tissue-specificity and progressive nature of the symptoms. The manifested phenotypes, symptoms severity and age at onset are extremely variable within and between families. This is mostly accounted for by the progenitor allele length (PAL) passed on from affected parents in addition to the level of somatic instability over time. Though, recent data have shown that additional sequence variations (CCG, CGG variant repeats) within the repeat and immediate flanking DNA are associated with additional symptomatic variation, modified stability and delayed age of onset. Furthermore, individual specific genetic factors have shown to be clustered within and between families as a heritable trait. Therefore, it has been verified that PAL, in addition to individual specific genetic variations are the main modifier of disease onset. More recently, it has been observed that mismatch repair (MMR) genes play a key role in modulating the dynamic of DM1 mutation, and subsequently impact on the age at onset. Therefore, these genes serve as powerful trans-acting modifiers of repeat instability and subsequent severity. Also, sequestration and up-regulation of RNA binding proteins (MBNL1, CELF1 respectively) against the trapped mutant transcripts are the hall mark of DM1 pathogenicity associated with alternative splicing defects that account for the variability of symptoms. Thus, sequence variations within these genes may underlie the genetic and phenotypic variability among DM1 patients. The current diagnostic test for DM1 only provides a qualitative value, and takes no account of the somatic instability and/or the presence of variations within or elsewhere in the genome. Thus, limited prognostic information is delivered to patients and their families. Although more elaborate genotyping approaches that measure the DM1 degree of instability was developed, they remain labour intensive, time consuming and are not suited to routine clinical diagnostics. In this project, we have evaluated the utility of more rapid and higher throughput next generation sequencing (NGS) technologies (Ion PGM and PacBio platforms) to simultaneously sequence the DM1 alleles of the Scottish patients, characterise the immediate flanking variants (5’-extra AAT and 5’-CCG variant repeats), elucidating the possible role of these variants on the DM1 instability, and finally sequencing the potential trans-acting modifiers in a massive customised panel (Ion AmpliSeq). Though, the accurate genotyping of the DM1 allele using NGS method remains challenging and cannot be used at the moment for accurate measurement of allele length. This is due to the sequencing biased nature towards shorter fragments resulting in differences of modal allele length measurement between PacBio and traditional SP-PCR methods. Additionally, Ion PGM platform was not successful at sequencing >20 CTG repeats. To correct for the sequencing biased distribution towards shorter alleles and distinguish between possible somatic variants from sequencing errors, safe sequencing (SafeSeq) method was conducted by tagging each original parental molecule with unique identifier (UID) sequences via PCR followed by sequencing using MiSeq platform. As the UID assignment was successful in tagging different population of repeats lengths, unfortunately we were not able to confidently differentiate between true somatic mutants from possible repeat slippage events in earlier cycles of PCR. Thus, it was decided to modify the incorporation of UID sequences using ligation based approach instead of PCR, and better optimise the method for more accurate results in the future. The identification of the immediate 5’-extra AAT flanking variant of the DM1 allele in a subset of the Scottish DM1 patients with and without CCG variant repeats has led us to speculate the possible presence of a new sub derived DM1 haplotype shared by a recent common ancestor in the Scottish population. In order to address this question, we were able to discriminate the normal allele haplotype of 11-13 repeats from >20 CTG haplotype among 18 DM1 patients whom were previously sequenced by Dr. Saeed Al ghamdi. These data have illustrated the most conserved haplotype around the DM1 allele. Therefore, the corresponding region was included in a customised Ion AmpliSeq sequencing panel for future larger scale haplotype analysis, in order to provide insights about future DM1 prevalence among the Scottish population. The data of this project highlighted the importance of using NGS technologies to characterise the structural pattern of the DM1 allele containing variants that may impact on symptom severity. It also showed the successful sequencing of trans-acting genetic modifiers in massive parallel fashion. Over larger scale analysis, these data could be used for better genotype-phenotype correlation and stratify patients in future clinical trials.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.705562  DOI: Not available
Keywords: QH426 Genetics
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