Browsing by Subject "nanopore sequencing"

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  • Malmsten, Kim (Helsingin yliopisto, 2021)
    Genomic structural variants are large events that change the structure of the genome. These can cause changes in the functions of cells by breaking genes and genomic regulatory regions. Multiple factors are known to affect the formation of structural variants and previous studies have shown that often the sequence content in a genomic region plays a role in their formation. This study aims to characterize the sequence content around structural variant breakpoints from structural variants which have been detected from human tissue samples which have been whole genome sequenced with nanopore sequencing. The characterization was done by looking at the genomic repetitive elements found around the breakpoints, by analyzing the GC-content around the breakpoints, and by studying what kind of enriched DNA motifs were found in the sequences around the breakpoints and how these were located in these sequences. Multiple different repetitive elements were seen to occur near the breakpoint regions, and it was also observed that there were differences in what kind of repetitive elements were seen around different types of structural variants. Around the sequences of different kinds of structural variants there was also distinct differences in what kind of GC-content profiles the sequences had. In addition, various different enriched motifs were also found from the sequences and many of these showed distinct variation on how they were located around the breakpoints. These results support the previous findings showing that also here the sequence content does play a role in the formation of structural variants, but still all of the results here could not be directly explained by previous studies. In these results, it was seen that the GC-content was higher in sequences that have been affected by an event that causes structural variant formation. Also, many of the found DNA motifs were distinctly skewed around the breakpoint sequences, possibly hinting that the sequences containing these motifs would be prone to the formation of structural variants.
  • Johansson, Tiira; Koskela, Satu; Yohannes, Dawit A.; Partanen, Jukka; Saavalainen, Paivi (2021)
    Identification of human leukocyte antigen (HLA) alleles from next-generation sequencing (NGS) data is challenging because of the high polymorphism and mosaic nature of HLA genes. Owing to the complex nature of HLA genes and consequent challenges in allele assignment, Oxford Nanopore Technologies' (ONT) single-molecule sequencing technology has been of great interest due to its fitness for sequencing long reads. In addition to the read length, ONT's advantages are its portability and possibility for a rapid real-time sequencing, which enables a simultaneous data analysis. Here, we describe a targeted RNA-based method for HLA typing using ONT sequencing and SeqNext-HLA SeqPilot software (JSI Medical Systems GmbH). Twelve classical HLA genes were enriched from cDNA of 50 individuals, barcoded, pooled, and sequenced in 10 MinION R9.4 SpotON flow cell runs producing over 30,000 reads per sample. Using barcoded 2D reads, SeqPilot assigned HLA alleles to two-field typing resolution or higher with the average read depth of 1750x. Sequence analysis resulted in 99-100% accuracy at low-resolution level (one-field) and in 74-100% accuracy at high-resolution level (two-field) with the expected alleles. There are still some limitations with ONT RNA sequencing, such as noisy reads, homopolymer errors, and the lack of robust algorithms, which interfere with confident allele assignment. These issues need to be inspected carefully in the future to improve the allele call rates. Nevertheless, here we show that sequencing of multiplexed cDNA amplicon libraries on ONT MinION can produce accurate high-resolution typing results of 12 classical HLA loci. For HLA research, ONT RNA sequencing is a promising method due to its capability to sequence full-length HLA transcripts. In addition to HLA genotyping, the technique could also be applied for simultaneous expression analysis.