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Lähdesmäki, H.

Publications and source records attributed to Lähdesmäki, H..

21 records · Page 2Linked to original sources

LuxUS: Detecting differential DNA methylation using generalized linear mixed model with spatial correlation structure

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSDNA methylation is an important epigenetic modification, which has multiple functions. DNA methylation and its connections to diseases have been extensively studied in recent years. It is known that DNA methylation levels of neighboring cytosines are correlated and that differential DNA methylation typically occurs rather as regions instead of individual cytosine level. ResultsWe have developed a generalized linear mixed model, LuxUS, that makes use of the correlation between neighboring cytosines to facilitate analysis of differential methylation. LuxUS implements a likelihood model for bisulfite sequencing data that accounts for experimental variation in underlying biochemistry. LuxUS can model both binary and continuous covariates, and mixed model formulation enables including replicate and cytosine random effects. Spatial correlation is included to the model through a cytosine random effect correlation structure. We show with simulation experiments that by utilizing the spatial correlation we gain more power to the statistical testing of differential DNA methylation. Results with real bisulfite sequencing data set show that LuxUS is able to detect biologically significant differentially methylated cytosines. AvailabilityThe tool is available at https://github.com/hallav/LuxUS. Supplementary informationSupplementary data are available at bioRxiv.

bioinformatics↗

Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer’s disease

Alzheimers disease (AD) results from a neurodegenerative process that starts well before the diagnosis can be made. New prognostic or diagnostic markers enabling early intervention into the disease process would be highly valuable. As life style factors largely modulate the disease risk, we hypothesised that the disease associated DNA methylation signatures are detectable in the peripheral blood of discordant twin pairs. Reduced Representation Bisulfite Sequencing, single cell RNA-sequencing and gene array data were utilised to examine DNA methylation signatures and associated gene expression changes in blood and hippocampus, and targeted bisulfite sequencing in cross cohort validation. Our results reveal that discordant twin pairs have disease associated differences in their peripheral blood epigenomes. A subset of affected genes, e.g. ADARB2 contain differentially methylated sites also in anterior hippocampus. The DNA methylation differences seem to influence gene expression in brain rather than in blood cells. The affected genes are associated with neuronal functions and pathologies. These DNA methylation signatures are valuable disease marker candidates and may provide insights into the molecular mechanisms of pathogenesis.

genomics↗

LuxRep: a technical replicate-aware method for bisulfite sequencing data analysis

DNA methylation is measured using bisulfite sequencing (BS-seq). Bisulfite conversion can have low efficiency and a DNA sample is then processed multiple times generating DNA libraries with different bisulfite conversion rates. Libraries with low conversion rates are excluded from analysis resulting in reduced coverage and increased costs. We present a method and software, LuxRep, that accounts for technical replicates from different bisulfite-converted DNA libraries. We show that including replicates with low bisulfite conversion rates generates more accurate estimates of methylation levels and differentially methylated sites.\n\nAvailabilityAn implementation of the method is available at https://github.com/tare/LuxGLM/tree/master/LuxRep\n\nContactmaia.malonzo@aalto.fi

bioinformatics↗