Browsing by Author "Peters, M."

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DNA methylation alterations—potential cause of endometriosis pathogenesis or a reflection of tissue heterogeneity?
(2018) Salumets, A.; Kaplinski, L.; Saare, M.; Krigul, KL.; Laisk-Podar, T.; Ponandai-Srinivasan, S.; Rahmioglu, N.; Lalit Kumar, PG.; Zondervan, K.; Peters, M.
Alterations in the DNA methylation pattern of endometriotic lesions and endometrium of endometriosis patients have been proposed as one potential factor accompanying the endometriosis development. Although many differentially methylated genes have been associated with the pathogenesis of this disease, the overlap between the results of different studies has remained small. Among other potential confounders, the impact of tissue heterogeneity on the outcome of DNA methylation studies should be considered, as tissues are mixtures of different cell types with their own specific DNA methylation signatures. This review focuses on the results of DNA methylation studies in endometriosis from the cellular heterogeneity perspective. We consider both the studies using highly heterogeneous whole-lesion biopsies and endometrial tissue, as well as pure cell fractions isolated from lesions and endometrium to understand the potential impact of the cellular composition to the results of endometriosis DNA methylation studies. Also, future perspectives on how to diminish the impact of tissue heterogeneity in similar studies are provided.
DNA methylation changes in endometrium and correlation with gene expression during the transition from pre-receptive to receptive phase
(2017) Kukushkina, V.; Modhukur, V.; Suhorutšenko, M.; Peters, M.; Mägi, R.; Rahmioglu, N.; Velthut-Meikas, A.; Altmäe, S.; Esteban, FJ.; Vilo, J.; Zondervan, K.; Salumets, A.; Laisk-Podar, T.
The inner uterine lining (endometrium) is a unique tissue going through remarkable changes each menstrual cycle. Endometrium has its characteristic DNA methylation profile, although not much is known about the endometrial methylome changes throughout the menstrual cycle. The impact of methylome changes on gene expression and thereby on the function of the tissue, including establishing receptivity to implanting embryo, is also unclear. Therefore, this study used genome-wide technologies to characterize the methylome and the correlation between DNA methylation and gene expression in endometrial biopsies collected from 17 healthy fertile-aged women from pre-receptive and receptive phase within one menstrual cycle. Our study showed that the overall methylome remains relatively stable during this stage of the menstrual cycle, with small-scale changes affecting 5% of the studied CpG sites (22,272 out of studied 437,022 CpGs, FDR < 0.05). Of differentially methylated CpG sites with the largest absolute changes in methylation level, approximately 30% correlated with gene expression measured by RNA sequencing, with negative correlations being more common in 5′ UTR and positive correlations in the gene ‘Body’ region. According to our results, extracellular matrix organization and immune response are the pathways most affected by methylation changes during the transition from pre-receptive to receptive phase.
NIPTmer: rapid k-mer-based software package for detection of fetal aneuploidies
(2018) Sauk, M.; Žilina, O.; Kurg, A.; Ustav, EL.; Peters, M.; Paluoja, P.; Roost, AM.; Teder, H.; Palta, P.; Brison, N.; Vermeesch, JR.; Krjutškov, K.; Salumets, A.; Kaplinski, L.
Non-invasive prenatal testing (NIPT) is a recent and rapidly evolving method for detecting genetic lesions, such as aneuploidies, of a fetus. However, there is a need for faster and cheaper laboratory and analysis methods to make NIPT more widely accessible. We have developed a novel software package for detection of fetal aneuploidies from next-generation low-coverage whole genome sequencing data. Our tool – NIPTmer – is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data, and applying linear regression model on the counts. Additionally, the filtering process used for k-mer list creation allows one to take into account the genetic variance in a specific sample, thus reducing the source of uncertainty. The processing time of one sample is less than 10 CPU-minutes on a high-end workstation. NIPTmer was validated on a cohort of 583 NIPT samples and it correctly predicted 37 non-mosaic fetal aneuploidies. NIPTmer has the potential to reduce significantly the time and complexity of NIPT post-sequencing analysis compared to mapping-based methods. For non-commercial users the software package is freely available at http://bioinfo.ut.ee/NIPTMer/.
Variability of genome-wide DNA methylation and mRNA expression profiles in reproductive and endocrine disease related tissues.
(2017) Rahmioglu, N.; Drong, AW.; Lockstone, H.; Tapmeier, T.; Hellner, K.; Saare, M.; Laisk-Podar, T.; Dew, C.; Tough, E.; Nicholson, G.; Peters, M.; Morris, AP.; Lindgren, CM.; Becker, CM.; Zondervan, KT.
Genome-wide association studies in the fields of reproductive medicine and endocrinology are yielding robust genetic variants associated with disease. Integrated genomic, transcriptomic, and epigenomic molecular profiling studies are common methodologies used to understand the biologic pathways perturbed by these variants. However, molecular profiling resources do not include the tissue most relevant to many female reproductive traits, the endometrium, while the parameters influencing variability of results from its molecular profiling are unclear. We investigated the sources of DNA methylation and RNA expression profile variability in endometrium (n = 135), endometriotic disease tissue (endometriosis), and subcutaneous abdominal fat samples from 24 women, quantifying between-individual, within-tissue (cellular heterogeneity), and technical variation. DNA samples (n = 96) were analyzed using Illumina HumanMethlylation450 BeadChip arrays; RNA samples (n = 39) were analyzed using H12-expression arrays. Variance-component analyses showed that, for the top 10–50% variable DNA methylation/RNA expression sites, between-individual variation far exceeded within-tissue and technical variation. Menstrual-phase accounted for most variability in methylation/expression patterns in endometrium (Pm = 7.8 × 10−3, Pe = 8.4 × 10−5) but not in fat and endometriotic tissue; age was significantly associated with DNA methylation profile of endometrium (Pm = 9 × 10−5) and endometriotic disease tissue (Pm = 2.4 × 10−5); and smoking was significantly associated with DNA methylation in adipose tissue (Pm = 1.8 × 10−3). Hierarchical cluster analysis showed significantly different methylation signatures between endometrium and endometriotic tissue enriched for WNT signaling, angiogenesis, cadherin signaling, and gonadotropin-releasing-hormone-receptor pathways. Differential DNA methylation/expression analyses suggested detection of a limited number of sites with large fold changes (FC > 4), but power calculations accounting for different sources of variability showed that for robust detection >500 tissue samples are required. These results enable appropriate study design for large-scale expression and methylation tissue-based profiling relevant to many reproductive and endocrine traits.