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- Moghadam, Behrooz Torabi, et al.
(författare)
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Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods
- 2019
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Ingår i: Journal of Psychiatric Research. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0022-3956 .- 1879-1379. ; 114, s. 41-47
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Tidskriftsartikel (refereegranskat)abstract
- Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigenetic analyses have yielded ambiguous and sometimes conflicting results. Here, we analyzed fresh frozen post-mortem brain tissue from a cohort of 73 subjects diagnosed with schizophrenia and 52 control samples, using the Illumina Infinium HumanMethylation450 Bead Chip, to investigate genome-wide DNA methylation patterns in the two groups. Analysis of differential methylation was performed with the Bioconductor Minfi package and modern machine-learning and visualization techniques, which were shown previously to be successful in detecting and highlighting differentially methylated patterns in case-control studies. In this dataset, however, these methods did not uncover any significant signals discerning the patient group and healthy controls, suggesting that if there are methylation changes associated with schizophrenia, they are heterogeneous and complex with small effect.
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| 2. |
- Torabi Moghadam, Behrooz, et al.
(författare)
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Analyzing DNA methylation patterns in Schizophrenic patients using machine learning methods
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Schizophrenia is common mental disorder with known genetic component involved. Since the association of environmental factors and schizophrenia has been reported, we analyzed a cohort of 75 schizophrenic and 50 control samples to investigate DNA methylation patterns, as one of the key players of epigenetic gene regulation.Here we applied machine-learning and visualization methods, which were shown previously to be successful in detecting and highlighting differentially methylated patterns between cases and controls. On this data set, however, these methods did not uncover any signal discerning schizophrenia patients and healthy controls, suggesting that if a link exists, it is heterogeneous and complex.
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| 3. |
- Zaghlool, Ammar, 1980-, et al.
(författare)
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Efficient cellular fractionation improves RNA sequencing analysis of mature and nascent transcripts from human tissues
- 2013
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Ingår i: BMC Biotechnology. - : Springer Science and Business Media LLC. - 1472-6750. ; 13, s. 99-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The starting material for RNA sequencing (RNA-seq) studies is usually total RNA or polyA+ RNA. Both forms of RNA represent heterogeneous pools of RNA molecules at different levels of maturation and processing. Such heterogeneity, in addition to the biases associated with polyA+ purification steps, may influence the analysis, sensitivity and the interpretation of RNA-seq data. We hypothesize that subcellular fractions of RNA may provide a more accurate picture of gene expression. Results: We present results for sequencing of cytoplasmic and nuclear RNA after cellular fractionation of tissue samples. In comparison with conventional polyA+ RNA, the cytoplasmic RNA contains a significantly higher fraction of exonic sequence, providing increased sensitivity in expression analysis and splice junction detection, and in improved de novo assembly of RNA-seq data. Conversely, the nuclear fraction shows an enrichment of unprocessed RNA compared with total RNA-seq, making it suitable for analysis of nascent transcripts and RNA processing dynamics. Conclusion: Our results show that cellular fractionation is a more rapid and cost effective approach than conventional polyA+ enrichment when studying mature RNAs. Thus, RNA-seq of separated cytosolic and nuclear RNA can significantly improve the analysis of complex transcriptomes from mammalian tissues.
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