BACKGROUND: Retroelements (REs) occupy a significant part of all eukaryotic genomes including humans. The majority of retroelements in the human genome are inactive and unable to retrotranspose. Dozens of active copies are repressed in most normal tissues by various cellular mechanisms. These copies can become active in normal germline and brain tissues or in cancer, leading to new retroposition events. The consequences of such events and their role in normal cell functioning and carcinogenesis are not yet fully understood. If new insertions occur in a small portion of cells they can be found only with the use of specific methods based on RE enrichment and high-throughput sequencing. The downside of the high sensitivity of such methods is the presence of various artifacts imitating real insertions, which in many cases cannot be validated due to lack of the initial template DNA. For this reason, adequate assessment of rare (< 1%) subclonal cancer specific RE insertions is complicated. RESULTS: Here we describe a new copy-capture technique which we implemented in a method called SeqURE for Sequencing Unknown of Retroposition Events that allows for efficient and reliable identification of new genomic RE insertions. The method is based on the capture of copies of target molecules (copy-capture), selective amplification and sequencing of genomic regions adjacent to active RE insertions from both sides. Importantly, the template genomic DNA remains intact and can be used for validation experiments. In addition, we applied a novel system for testing method sensitivity and precisely showed the ability of the developed method to reliably detect insertions present in 1 out of 100 cells and a substantial portion of insertions present in 1 out of 1000 cells. Using advantages of the method we showed the absence of somatic Alu insertions in colorectal cancer samples bearing tumor-specific L1HS insertions. CONCLUSIONS: This study presents the first description and implementation of the copy-capture technique and provides the first methodological basis for the quantitative assessment of RE insertions present in a small portion of cells.

• Publikační typ
• časopisecké články MeSH

Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.

• MeSH
• adaptivní imunita genetika   MeSH
• antigeny virové MeSH
• antigeny MeSH
• hypervariabilní oblasti genetika   fyziologie   MeSH
• imunoterapie MeSH
• lidé MeSH
• receptory antigenů T-buněk imunologie   metabolismus   fyziologie   MeSH
• sekvenční analýza DNA metody   MeSH
• shluková analýza MeSH
• vysoce účinné nukleotidové sekvenování metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH