46 research outputs found
LuxRep: a technical replicate-aware method for bisulfite sequencing data analysis
Background:Â DNA methylation is commonly measured using bisulfite sequencing (BS-seq). The quality of a BS-seq library is measured by its bisulfite conversion efficiency. Libraries with low conversion rates are typically excluded from analysis resulting in reduced coverage and increased costs.Results:Â We have developed a probabilistic method and software, LuxRep, that implements a general linear model and simultaneously accounts for technical replicates (libraries from the same biological sample) from different bisulfite-converted DNA libraries. Using simulations and actual DNA methylation data, we show that including technical replicates with low bisulfite conversion rates generates more accurate estimates of methylation levels and differentially methylated sites. Moreover, using variational inference speeds up computation time necessary for whole genome analysis.Conclusions:Â In this work we show that taking into account technical replicates (i.e. libraries) of BS-seq data of varying bisulfite conversion rates, with their corresponding experimental parameters, improves methylation level estimation and differential methylation detection.</p
Karyotypically abnormal human ESCs are sensitive to HDAC inhibitors and show altered regulation of genes linked to cancers and neurological diseases
AbstractGenomic abnormalities may accumulate in human embryonic stem cells (hESCs) during in vitro maintenance. Characterization of the mechanisms enabling survival and expansion of abnormal hESCs is important due to consequences of genetic changes for the therapeutic utilization of stem cells. Furthermore, these cells provide an excellent model to study transformation in vitro. We report here that the histone deacetylase proteins, HDAC1 and HDAC2, are increased in karyotypically abnormal hESCs when compared to their normal counterparts. Importantly, similar to many cancer cell lines, we found that HDAC inhibitors repress proliferation of the karyotypically abnormal hESCs, whereas normal cells are more resistant to the treatment. The decreased proliferation correlates with downregulation of HDAC1 and HDAC2 proteins, induction of the proliferation inhibitor, cyclin-dependent kinase inhibitor 1A (CDKN1A), and altered regulation of tumor suppressor protein Retinoblastoma 1 (RB1). Through genome-wide transcriptome analysis we have identified genes with altered expression and responsiveness to HDAC inhibition in abnormal cells. Most of these genes are linked to severe developmental and neurological diseases and cancers. Our results highlight the importance of epigenetic mechanisms in the regulation of genomic stability of hESCs, and provide valuable candidates for targeted and selective growth inhibition of karyotypically abnormal cells
Evaluation of tools for identifying large copy number variations from ultra-low-coverage whole-genome sequencing data
BackgroundDetection
of copy number variations (CNVs) from high-throughput next-generation
whole-genome sequencing (WGS) data has become a widely used research
method during the recent years. However, only a little is known about
the applicability of the developed algorithms to ultra-low-coverage
(0.0005–0.8×) data that is used in various research and clinical
applications, such as digital karyotyping and single-cell CNV detection.ResultHere,
the performance of six popular read-depth based CNV detection
algorithms (BIC-seq2, Canvas, CNVnator, FREEC, HMMcopy, and QDNAseq) was
studied using ultra-low-coverage WGS data. Real-world array- and
karyotyping kit-based validation were used as a benchmark in the
evaluation. Additionally, ultra-low-coverage WGS data was simulated to
investigate the ability of the algorithms to identify CNVs in the sex
chromosomes and the theoretical minimum coverage at which these tools
can accurately function. Our results suggest that while all the methods
were able to detect large CNVs, many methods were susceptible to
producing false positives when smaller CNVs (< 2 Mbp) were detected.
There was also significant variability in their ability to identify CNVs
in the sex chromosomes. Overall, BIC-seq2 was found to be the best
method in terms of statistical performance. However, its significant
drawback was by far the slowest runtime among the methods (> 3 h)
compared with FREEC (~ 3 min), which we considered the second-best
method.ConclusionsOur
comparative analysis demonstrates that CNV detection from
ultra-low-coverage WGS data can be a highly accurate method for the
detection of large copy number variations when their length is in
millions of base pairs. These findings facilitate applications that
utilize ultra-low-coverage CNV detection.</div
Expression profiles of long non-coding RNAs located in autoimmune disease-associated regions reveal immune cell-type specificity
Background: Although genome-wide association studies (GWAS) have identified hundreds of variants associated with a risk for autoimmune and immune-related disorders (AID), our understanding of the disease mechanisms is still limited. In particular, more than 90% of the risk variants lie in non-coding regions, and almost 10% of these map to long non-coding RNA transcripts (lncRNAs). lncRNAs are known to show more cell-type specificity than protein-coding genes. Methods: We aimed to characterize lncRNAs and protein-coding genes located in loci associated with nine AIDs which have been well-defined by Immunochip analysis and by transcriptome analysis across seven populations of peripheral blood leukocytes (granulocytes, monocytes, natural killer (NK) cells, B cells, memory T cells, naive CD4(+) and naive CD8(+) T cells) and four populations of cord blood-derived T-helper cells (precursor, primary, and polarized (Th1, Th2) T-helper cells). Results: We show that lncRNAs mapping to loci shared between AID are significantly enriched in immune cell types compared to lncRNAs from the whole genome (a <0.005). We were not able to prioritize single cell types relevant for specific diseases, but we observed five different cell types enriched (a <0.005) in five AID (NK cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, and psoriasis; memory T and CD8(+) T cells in juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, and rheumatoid arthritis; Th0 and Th2 cells for inflammatory bowel disease, juvenile idiopathic arthritis, primary biliary cirrhosis, psoriasis, and rheumatoid arthritis). Furthermore, we show that co-expression analyses of lncRNAs and protein-coding genes can predict the signaling pathways in which these AID-associated lncRNAs are involved. Conclusions: The observed enrichment of lncRNA transcripts in AID loci implies lncRNAs play an important role in AID etiology and suggests that lncRNA genes should be studied in more detail to interpret GWAS findings correctly. The co-expression results strongly support a model in which the lncRNA and protein-coding genes function together in the same pathways
DNA methylation and Transcriptome Changes Associated with Cisplatin Resistance in Ovarian Cancer
High-grade serous
ovarian cancer is the most common ovarian cancer type. Although the combination
of surgery and platinum-taxane chemotherapy provide an effective treatment,
drug resistance frequently occurs leading to poor outcome. In order to clarify
the molecular mechanisms of drug resistance, the DNA methylation and
transcriptomic changes, associated with the development of drug resistance in
high-grade serous ovarian cancer, were examined from patient derived malignant ascites
cells. In parallel with large-scale transcriptome
changes, cisplatin resistance was associated with loss of hypermethylation at
several CpG sites primarily localized in the intergenic regions of the genome.
The transcriptome and CpG methylome changes in response to cisplatin treatment
of both sensitive and resistant cells were minimal, indicating the importance
of post-translational mechanisms in regulating death or survival of the cells. The
response of resistant cells to high concentrations of cisplatin revealed
transcriptomic changes in potential key drivers of drug resistance, such as KLF4. Among the strongest changes was induction
of IL6 in the resistant cells, with
its expression further increased in response to cisplatin. Also, several other
components of IL6 signaling were affected, further supporting previous
observations on its importance in malignant transformation and development of
drug resistance in ovarian cancer.  </p
Umbilical cord blood DNA methylation in children who later develop type 1 diabetes
Aims/hypothesis Distinct DNA methylation patterns have recently been observed to precede type 1 diabetes in whole blood collected from young children. Our aim was to determine whether perinatal DNA methylation is associated with later progression to type 1 diabetes. Methods Reduced representation bisulphite sequencing (RRBS) analysis was performed on umbilical cord blood samples collected within the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study. Children later diagnosed with type 1 diabetes and/or who tested positive for multiple islet autoantibodies (n = 43) were compared with control individuals (n = 79) who remained autoantibody-negative throughout the DIPP follow-up until 15 years of age. Potential confounding factors related to the pregnancy and the mother were included in the analysis. Results No differences in the umbilical cord blood methylation patterns were observed between the cases and controls at a false discovery rate Conclusions/interpretation Based on our results, differences between children who progress to type 1 diabetes and those who remain healthy throughout childhood are not yet present in the perinatal DNA methylome. However, we cannot exclude the possibility that such differences would be found in a larger dataset.Peer reviewe
RNA Polymerase III Subunit POLR3G Regulates Specific Subsets of PolyA+ and SmallRNA Transcriptomes and Splicing in Human Pluripotent Stem Cells
POLR3G is expressed at high levels in human pluripotent stem cells
(hPSCs) and is required for maintenance of stem cell state through
mechanisms not known in detail. To explore how POLR3G regulates stem
cell state, we carried out deep-sequencing analysis of polyA+
and smallRNA transcriptomes present in hPSCs and regulated in
POLR3G-dependent manner. Our data reveal that POLR3G regulates a
specific subset of the hPSC transcriptome, including multiple transcript
types, such as protein-coding genes, long intervening non-coding RNAs,
microRNAs and small nucleolar RNAs, and affects RNA splicing. The
primary function of POLR3G is in the maintenance rather than repression
of transcription. The majority of POLR3G polyA+ transcriptome
is regulated during differentiation, and the key pluripotency factors
bind to the promoters of at least 30% of the POLR3G-regulated
transcripts. Among the direct targets of POLR3G, POLG is potentially
important in sustaining stem cell status in a POLR3G-dependent manner.</p
Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer's disease
Background Alzheimer's disease 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. Environmental and lifestyle factors largely modulate the disease risk and may influence the pathogenesis through epigenetic mechanisms, such as DNA methylation. As environmental and lifestyle factors may affect multiple tissues of the body, we hypothesized that the disease-associated DNA methylation signatures are detectable in the peripheral blood of discordant twin pairs. Results Comparison of 23 disease discordant Finnish twin pairs with reduced representation bisulfite sequencing revealed peripheral blood DNA methylation differences in 11 genomic regions with at least 15.0% median methylation difference and FDR adjusted p valuePeer reviewe
Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer's disease
Background Alzheimer's disease 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. Environmental and lifestyle factors largely modulate the disease risk and may influence the pathogenesis through epigenetic mechanisms, such as DNA methylation. As environmental and lifestyle factors may affect multiple tissues of the body, we hypothesized that the disease-associated DNA methylation signatures are detectable in the peripheral blood of discordant twin pairs. Results Comparison of 23 disease discordant Finnish twin pairs with reduced representation bisulfite sequencing revealed peripheral blood DNA methylation differences in 11 genomic regions with at least 15.0% median methylation difference and FDR adjusted p value Conclusions DNA methylation differences can be detected in the peripheral blood of twin pairs discordant for Alzheimer's disease. These DNA methylation signatures may have value as disease markers and provide insights into the molecular mechanisms of pathogenesis. We found no evidence that the DNA methylation marks would be associated with gene expression in blood. Further studies are needed to elucidate the potential importance of the associated genes in neuronal functions and to validate the prognostic or diagnostic value of the individual marks or marker panels.</p