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A comparative study of structural variants detected by 10X linked-read exome and whole exome sequencing in multiple myeloma

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dc.date.accessioned 2020-09-16T08:34:55Z
dc.date.available 2020-09-16T08:34:55Z
dc.date.issued 2020-09-16
dc.identifier.uri http://hdl.handle.net/123456789/31419
dc.title A comparative study of structural variants detected by 10X linked-read exome and whole exome sequencing in multiple myeloma en
ethesis.faculty Lääketieteellinen tiedekunta fi
ethesis.faculty Faculty of Medicine en
ethesis.faculty Medicinska fakulteten sv
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/a4d5aaa2-b5aa-41a7-ba4c-e5e0df7a902d
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingin yliopisto fi
ethesis.university University of Helsinki en
ethesis.university Helsingfors universitet sv
dct.creator Adhikari, Sadiksha
dct.issued 2020
dct.language.ISO639-2 eng
dct.abstract Structural variants comprise a large number of variations occurring in the human genome and are detected in many diseases including cancers. To a limited extent, whole exome sequencing (WES) is capable of detecting structural variations (SVs) using algorithms and tools utilizing local assembly, split-reads, discordant read-pairs and read depth methods. However, due to the significantly large size of SVs compared to the reads produced and the presence of repetitive regions in the genome, identification of SVs presents a major challenge. 10X Genomics has developed a technology that requires very low amounts of DNA and uses a linked-reads approach to produce long reads. Recently, linked-read technology has shown promising results in resolving complex SVs. In this thesis, we aimed to assess whether linked-read exome sequencing is able to infer more comprehensive information in SVs compared to WES in multiple myeloma (MM). The disease model was chosen based on the presence of high numbers of SVs in MM patient tumor cells. Here, we report that linked-read sequencing has led to the identification of a potential novel translocation t(1; 14) that significantly impacts the change in expression of genes and could potentially have impact on the prognosis and treatment of multiple myeloma patients. By Long Ranger analysis we detected t(1;14) in six out of eight samples. Further, to study whether the translocation differentially affects the expression levels of any genes, differential gene expression was performed between t(1;14) positive versus t(1;14) wild type samples. The analysis resulted in 107 differentially expressed genes where 4 upregulated and 103 downregulated genes were found in the translocation positive samples. Among the downregulated genes, we found S100A8 and S100A9 genes which are previously shown to be associated with chemoresistance to PAD (bortezomib, doxorubicin and dexamethasone) therapy. The related breakpoints of the event were identified by Manta tool (SV caller) using both linked-read and WES. Therefore, linked-read information does not appear necessary to detect this event. In this study, we found that linked-read sequencing has certain advantages over WES such as low input DNA, increased number and quality of calls and breakpoint information. However, linked-read sequencing technique is limited to the detection of certain SV types in addition to increased cost of sequencing. These two factors must be considered before choosing linked-read sequencing over WES. Somatic mutations and clinically relevant SV were detected equally efficiently by both techniques. en
dct.subject Structural Variation
dct.subject Whole exome sequencing
dct.subject Linked-read sequencing
dct.subject RNA-sequencing
dct.subject Multiple myeloma
dct.language en
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language englanti fi
ethesis.language English en
ethesis.language engelska sv
ethesis.supervisor Heckman, Caroline
ethesis.supervisor Kumar, Ashwini
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.ethesis E-thesisID:4105b0ff-644c-439c-b8d7-3e685e1e5709
ethesis.degreeprogram.URI none
ethesis-internal.timestamp.reviewStep 2020-08-11 13:55:04:995
dct.identifier.urn URN:NBN:fi:hulib-202009164112
dc.type.dcmitype Text
ethesis.discipline.med Cancer und
ethesis.facultystudyline Cancer fi
ethesis.facultystudyline Cancer en
ethesis.facultystudyline Cancer sv
ethesis.facultystudyline.URI http://data.hulib.helsinki.fi/id/SH_TMED-110
ethesis.mastersdegreeprogram Translationaalisen lääketieteen maisteriohjelma (Translational Medicine) fi
ethesis.mastersdegreeprogram Master's Programme in Translational Medicine en
ethesis.mastersdegreeprogram Magisterprogrammet i translationell medicin sv
ethesis.mastersdegreeprogram.URI http://data.hulib.helsinki.fi/id/MH30_002

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