During the last decade high throughput DNA sequencing of single cells has evolved from an idea to one of the most high profile fields of research. Much of this development has been possible due to the dramatic reduction in costs for massively parallel sequencing. The four papers included in this thesis describe or evaluate technological advancements for high throughput DNA sequencing of single cells and single molecules. As the sequencing technologies improve, more samples are analyzed in parallel. In paper 1, an automated procedure for preparation of samples prior to massively parallel sequencing is presented. The method has been applied to several projects and further development by others has enabled even higher sample throughputs. Amplification of single cell genomes is a prerequisite for sequence analysis. Paper 2 evaluates four commercially available kits for whole genome amplification of single cells. The results show that coverage of the genome differs significantly among the protocols and as expected this has impact on the downstream analysis. In Paper 3, single cell genotyping by exome sequencing is used to confirm the presence of fat cells derived from donated bone marrow within the recipients’ fat tissue. Close to hundred single cells were exome sequenced and a subset was validated by whole genome sequencing. In the last paper, a new method for phasing (i.e. determining the physical connection of variant alleles) is presented. The method barcodes amplicons from single molecules in emulsion droplets. The barcodes can then be used to determine which variants were present on the same original DNA molecule. The method is applied to two variable regions in the bacterial 16S gene in a metagenomic sample. Thus, two of the papers (1 and 4) present development of new methods for increasing the throughput and information content of data from massively parallel sequencing. Paper 2 evaluates and compares currently available methods and in paper 3, a biological question is answered using some of these tools. / <p>QC 20160127</p>
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-181059 |
Date | January 2016 |
Creators | Borgström, Erik |
Publisher | KTH, Genteknologi, Stockholm |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | TRITA-BIO-Report, 1654-2312 ; 2016:1 |
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