[Opportunities of multi-omics approach for the search for new diagnostic and therapeutic targets in multiple sclerosis]. / Perspektivy primeneniya mul'tiomiksnogo podkhoda dlya poiska novykh diagnosticheskikh assotsiatsii i terapevticheskikh mishenei pri rasseyannom skleroze.

Multiple sclerosis is an extremely heterogeneous disease and, despite intensive research, no selective biomarkers have been identified for this pathology, and therefore its diagnosis in the early stages is still challenging. One of the most powerful tools for studying the pathogenesis of multiple sclerosis is the multi-omics approach, which makes it possible to characterize cells involved in the disease progression in the most detailed and versatile way. This review will describe the current directions of research in multiple sclerosis using high-throughput technologies. Also, an assessment of the demand for the use of a multi-omics approach was carried out.

[A Pipeline for the Error-free Identification of Somatic Alu Insertions in High-throughput Sequencing Data].

Retroelements are considered as one of the important sources of genomic variability in modern humans. It is known that transposition activity of retroelements in germline cells generates new insertions in various genomic loci and sometimes results in genetic diseases. Retroelements activity in somatic cells is restricted by different cellular mechanisms; however, there is an evidence for it in some tissue types. Somatic insertions can trigger tumorigenesis or participate in normal functioning such as generation of neurons' plasticity. In spite of the rapid development of high-throughput sequencing methods a confident detection of somatic insertions is still quite a challenging task. That, in part, is due to the absence of adequate bioinformatic tools for the analysis of sequencing data. Here, we propose an advanced computational pipeline for the identification of somatic insertions in datasets generated by selective amplification and high-throughput sequencing of genomic regions flanking insertions of AluYa5. Particular attention is paid for the identification of various artifacts arising in course of library preparation and the parameters for their filtration. Pipeline sensitivity is confirmed by in silico experiments with artificial datasets. Using the proposed pipeline we remove at least 80% of artifacts and preserve 75% of potentially somatic insertions. The approaches used in this work can be applied for the study of other mobile elements insertion variability.