Biology subjects

Hayrynen, S.

Publications and source records attributed to Hayrynen, S..

3 recordsLinked to original sources

bioRxiv2022

Integrative DNA methylation analysis of pediatric brain tumors reveals tumor type-specific developmental trajectories and epigenetic signatures of malignancy

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness, exceptionally low mutation rate, and aberrant but still unresolved epigenetic regulation. To evaluate methylation associated regulation in AT/RTs, we compared them to medulloblastomas and choroid plexus tumors by integrating DNA methylation (507 samples), gene expression (120 samples), and public transcription factor (TF) binding data. We showed that elevated DNA methylation masks the binding sites of TFs driving neural development and is associated with reduced transcription for specific neural regulators in AT/RTs. Part of the hypermethylated sites behaved similarly in AT/RTs and pluripotent stem cells, revealing DNA methylation -driven halted cell differentiation. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 members, like EZH2, and linked to suppressed genes with a role in neural development and tumorigenesis. The obtained results highlight and characterize these DNA methylation programs as drivers of AT/RT malignancy.

cancer biology↗

bioRxiv2019

Challenges and opportunities for strain verification by whole-genome sequencing

Laboratory strains, cell lines, and other genetic materials change hands frequently in the life sciences. Despite evidence that such materials are subject to mix-ups, contamination, and accumulation of secondary mutations, verification of strains and samples is not an established part of many experimental workflows. With the plummeting cost of next generation technologies, it is conceivable that whole genome sequencing (WGS) could be applied to routine strain and sample verification in the future. To demonstrate the need for strain validation by WGS, we sequenced haploid yeast segregants derived from a popular commercial mutant collection and identified several unexpected mutations. We determined that available bioinformatics tools may be ill-suited for verification and highlight the importance of finishing reference genomes for commonly-used laboratory strains.

bioinformatics↗

bioRxiv2018

Data-driven characterization of molecular phenotypes across heterogenous sample collections

The existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on their molecular profile. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensional reduction algorithm t-SNE with multi-center and multi-platform data representing hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation of molecular disease subtypes, comparison of sample groups between separate t-SNE representations, or maps, and characterization of the obtained clusters based on pathway databases and additional multi-omics data. In the example application, our approach revealed differential activity of SAM-dependent DNA methylation pathway in the acute myeloid leukemia patient cluster characterized with CEBPA mutations that accordingly was validated to have globally elevated DNA methylation levels.

bioinformatics↗