| 61. |
- 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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| 62. |
- Torabi Moghadam, Behrooz, et al.
(författare)
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Combinatorial identification of DNA methylation patterns over age in the human brain
- 2016
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Background: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. Results: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. Conclusion: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease.
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| 63. |
- Torabi Moghadam, Behrooz
(författare)
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Computational discovery of DNA methylation patterns as biomarkers of ageing, cancer, and mental disorders : Algorithms and Tools
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Epigenetics refers to the mitotically heritable modifications in gene expression without a change in the genetic code. A combination of molecular, chemical and environmental factors constituting the epigenome is involved, together with the genome, in setting up the unique functionality of each cell type.DNA methylation is the most studied epigenetic mark in mammals, where a methyl group is added to the cytosine in a cytosine-phosphate-guanine dinucleotides or a CpG site. It has been shown to have a major role in various biological phenomena such as chromosome X inactivation, regulation of gene expression, cell differentiation, genomic imprinting. Furthermore, aberrant patterns of DNA methylation have been observed in various diseases including cancer.In this thesis, we have utilized machine learning methods and developed new methods and tools to analyze DNA methylation patterns as a biomarker of ageing, cancer subtyping and mental disorders.In Paper I, we introduced a pipeline of Monte Carlo Feature Selection and rule-base modeling using ROSETTA in order to identify combinations of CpG sites that classify samples in different age intervals based on the DNA methylation levels. The combination of genes that showed up to be acting together, motivated us to develop an interactive pathway browser, named PiiL, to check the methylation status of multiple genes in a pathway. The tool enhances detecting differential patterns of DNA methylation and/or gene expression by quickly assessing large data sets.In Paper III, we developed a novel unsupervised clustering method, methylSaguaro, for analyzing various types of cancers, to detect cancer subtypes based on their DNA methylation patterns. Using this method we confirmed the previously reported findings that challenge the histological grouping of the patients, and proposed new subtypes based on DNA methylation patterns. In Paper IV, we investigated the DNA methylation patterns in a cohort of schizophrenic and healthy samples, using all the methods that were introduced and developed in the first three papers.
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| 64. |
- Torabi Moghadam, Behrooz, 1982-, et al.
(författare)
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PiiL : visualization of DNA methylation and gene expression data in gene pathways
- 2017
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels.Results: PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas.Conclusion: At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways.PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git.
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| 65. |
- Weise, Anja, et al.
(författare)
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High-throughput sequencing of microdissected chromosomal regions.
- 2010
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Ingår i: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 18:4, s. 457-62
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Tidskriftsartikel (refereegranskat)abstract
- The linkage of disease gene mapping with DNA sequencing is an essential strategy for defining the genetic basis of a disease. New massively parallel sequencing procedures will greatly facilitate this process, although enrichment for the target region before sequencing remains necessary. For this step, various DNA capture approaches have been described that rely on sequence-defined probe sets. To avoid making assumptions on the sequences present in the targeted region, we accessed specific cytogenetic regions in preparation for next-generation sequencing. We directly microdissected the target region in metaphase chromosomes, amplified it by degenerate oligonucleotide-primed PCR, and obtained sufficient material of high quality for high-throughput sequencing. Sequence reads could be obtained from as few as six chromosomal fragments. The power of cytogenetic enrichment followed by next-generation sequencing is that it does not depend on earlier knowledge of sequences in the region being studied. Accordingly, this method is uniquely suited for situations in which the sequence of a reference region of the genome is not available, including population-specific or tumor rearrangements, as well as previously unsequenced genomic regions such as centromeres.
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| 66. |
- Weissensteiner, Matthias H.
(författare)
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Evolutionary genomics in Corvids : – From single nucleotides to structural variants
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Heritable genetic variation is the raw material of evolution and can occur in many different forms, from altering single nucleotides to rearranging stretches of millions at once. DNA mutations that result in phenotypic differences are the basis upon which natural selection can act, leading to a shift of the frequency of those mutations.In this thesis I aim to comprehensively characterize and quantify genetic variation in a natural system, the songbird genus Corvus. First, we expand on previous work from a hybrid zone of different populations of Eurasian crows. All black carrion crows and black-and-grey hooded crows meet in a narrow hybrid zone in central Europe, and also in central and Southeast Asia. Comparing population genetic data acquired from these three hybrid zones yielded no single genetic region as a candidate responsible for phenotypic divergence, yet a parallelism in sets of genes and gene networks was evident.Second, we capitalize on varying evolutionary timescales to investigate the driver of the heterogeneous genetic differentiation landscape observed in multiple avian species. Genetic diversity, and thus differentiation, seems to be correlated both between populations within single species and between species which diverged 50 million years ago. This pattern is best explained by conserved broad-scale recombination rate variation, which is in turn likely associated with chromosomal features such as centromeres and telomeres.Third, we introduce a de-novo assembly of the hooded crow based on long-read sequencing and optical mapping. The use of this technology allowed a glimpse into previously hidden regions of the genome, and uncovered large-scale tandem repeat arrays consisting of a 14-kbp satellite repeat or its 1.2-kpb subunit. Furthermore, these tandem repeat arrays are associated with regions of reduced recombination rate.Lastly, we extend the population genetic analysis to structural genomic variation, such as insertions and deletions. A large-scale population re-sequencing data set based on short-read and long-read technologies, spread across the entire genus is the foundation of a fine-scale genome-wide map of structural variation. A differentiation outlier approach between all-black carrion and black-and-grey hooded crows identified a 2.25-kilobase LTR retrotransposon inserted 20-kb upstream of the NDP gene. The element, which is fixed in the hooded crow population, is associated with decreased expression of NDP and may be responsible for differences in plumage color.
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| 67. |
- Yang, Yu, et al.
(författare)
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RiBoSOM : Rapid bacterial genome identification using self-organizing map implemented on the synchoros SiLago platform
- 2018
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Ingår i: ACM International Conference Proceeding Series. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450364942 ; , s. 105-114
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Konferensbidrag (refereegranskat)abstract
- Artificial Neural Networks have been applied to many traditional machine learning applications in image and speech processing. More recently, ANNs have caught attention of the bioinformatics community for their ability to not only speed up by not having to assemble genomes but also work with imperfect data set with duplications. ANNs for bioinformatics also have the added attraction of better scaling for massive parallelism compared to traditional bioinformatics algorithms. In this paper, we have adapted Self-organizing Maps for rapid identification of bacterial genomes called BioSOM. BioSOM has been implemented on a design of two coarse grain reconfigurable fabrics customized for dense linear algebra and streaming scratchpad memory respectively. These fabrics are implemented in a novel synchoros VLSI design style that enables composition by abutment. The synchoricity empowers rapid and accurate synthesis from Matlab models to create near ASIC like efficient solution. This platform, called SiLago (Silicon Lego) is benchmarked against a GPU implementation. The SiLago implementation of BioSOMs in four different dimensions, 128, 256, 512 and 1024 Neurons, were trained for two E Coli strains of bacteria with 40K training vectors. The results of SiLago implementation were benchmarked against a GPU GTX 1070 implementation in the CUDA framework. The comparison reveals 4 to 140X speed up and 4 to 5 orders of improvement in energy-delay product compared to implementation on GPU. This extreme efficiency comes with the added benefit of automated generation of GDSII level design from Matlab by using the Synchoros VLSI design style.
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| 68. |
- 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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| 69. |
- Zamani, Neda, et al.
(författare)
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A universal genomic coordinate translator for comparative genomics
- 2014
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 15, s. 227-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N-2 with the number of available genomes, N. Results: Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across species. Conclusions: Kraken is a computational genome coordinate translator that facilitates cross-species comparisons, distinguishes orthologs from paralogs, and does not require costly all-to-all whole genome mappings. Kraken is freely available under LPGL from http://github.com/nedaz/kraken.
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| 70. |
- Zamani, Neda, et al.
(författare)
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Unsupervised genome-wide recognition of local relationship patterns
- 2013
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 14, s. 347-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUNDPhenomena such as incomplete lineage sorting, horizontal gene transfer, gene duplication and subsequent sub- and neo-functionalisation can result in distinct local phylogenetic relationships that are discordant with species phylogeny. In order to assess the possible biological roles for these subdivisions, they must first be identified and characterised, preferably on a large scale and in an automated fashion.RESULTSWe developed Saguaro, a combination of a Hidden Markov Model (HMM) and a Self Organising Map (SOM), to characterise local phylogenetic relationships among aligned sequences using cacti, matrices of pair-wise distance measures. While the HMM determines the genomic boundaries from aligned sequences, the SOM hypothesises new cacti in an unsupervised and iterative fashion based on the regions that were modelled least well by existing cacti. After testing the software on simulated data, we demonstrate the utility of Saguaro by testing two different data sets: (i) 181 Dengue virus strains, and (ii) 5 primate genomes. Saguaro identifies regions under lineage-specific constraint for the first set, and genomic segments that we attribute to incomplete lineage sorting in the second dataset. Intriguingly for the primate data, Saguaro also classified an additional ~3% of the genome as most incompatible with the expected species phylogeny. A substantial fraction of these regions was found to overlap genes associated with both the innate and adaptive immune systems.CONCLUSIONSSaguaro detects distinct cacti describing local phylogenetic relationships without requiring any a priori hypotheses. We have successfully demonstrated Saguaro's utility with two contrasting data sets, one containing many members with short sequences (Dengue viral strains: n = 181, genome size = 10,700 nt), and the other with few members but complex genomes (related primate species: n = 5, genome size = 3 Gb), suggesting that the software is applicable to a wide variety of experimental populations. Saguaro is written in C++, runs on the Linux operating system, and can be downloaded from http://saguarogw.sourceforge.net/.
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