A Genome-wide View of Microsatellite Instability: Old Stories of Cancer Mutations Revisited with New Sequencing Technologies

Background: Nucleosome organization and DNA methylation are two mechanisms that are important for proper control of mammalian transcription, as well as epigenetic dysregulation associated with cancer. Whole-genome DNA methylation sequencing studies have found that methylation levels in the human genome show periodicities of approximately 190 bp, suggesting a genome-wide relationship between the two marks. A recent report (Chodavarapu et al., 2010) attributed this to higher methylation levels of DNA within nucleosomes. Here, we analyzed a number of published datasets and found a more compelling alternative explanation, namely that methylation levels are highest in linker regions between nucleosomes. Results: Reanalyzing the data from (Chodavarapu et al., 2010), we found that nucleosome-associated methylation could be strongly confounded by known sequence-related biases of the next-generation sequencing technologies. By accounting for these biases and using an unrelated nucleosome profiling technology, NOMe-seq, we found that genome-wide methylation was actually highest within linker regions occurring between nucleosomes in multi-nucleosome arrays. This effect was consistent among several methylation datasets generated independently using two unrelated methylation assays. Linker-associated methylation was most prominent within long Partially Methylated Domains (PMDs) and the positioned nucleosomes that flank CTCF binding sites. CTCF adjacent nucleosomes retained the correct positioning in regions completely devoid of CpG dinucleotides, suggesting that DNA methylation is not required for proper nucleosomes positioning. Conclusions: The biological mechanisms responsible for DNA methylation patterns outside of gene promoters remain poorly understood. We identified a significant genome-wide relationship between nucleosome organization and DNA methylation, which can be used to more accurately analyze and understand the epigenetic changes that accompany cancer and other diseases.

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The first decade of estrogen receptor cistromics in breast cancer

Journal of Endocrinology ◽

10.1530/joe-16-0003 ◽

2016 ◽

Vol 229 (2) ◽

pp. R43-R56 ◽

Cited By ~ 12

Author(s):

Koen D Flach ◽

Wilbert Zwart

Keyword(s):

Breast Cancer ◽

Estrogen Receptor ◽

Transcription Factor ◽

Tiling Array ◽

Estrogen Receptor Α ◽

Sequencing Technologies ◽

Hormone Receptor Positive ◽

Genome Wide ◽

A Genome ◽

On Chip

The advent of genome-wide transcription factor profiling has revolutionized the field of breast cancer research. Estrogen receptor α (ERα), the major drug target in hormone receptor-positive breast cancer, has been known as a key transcriptional regulator in tumor progression for over 30 years. Even though this function of ERα is heavily exploited and widely accepted as an Achilles heel for hormonal breast cancer, only since the last decade we have been able to understand how this transcription factor is functioning on a genome-wide scale. Initial ChIP-on-chip (chromatin immunoprecipitation coupled with tiling array) analyses have taught us that ERα is an enhancer-associated factor binding to many thousands of sites throughout the human genome and revealed the identity of a number of directly interacting transcription factors that are essential for ERα action. More recently, with the development of massive parallel sequencing technologies and refinements thereof in sample processing, a genome-wide interrogation of ERα has become feasible and affordable with unprecedented data quality and richness. These studies have revealed numerous additional biological insights into ERα behavior in cell lines and especially in clinical specimens. Therefore, what have we actually learned during this first decade of cistromics in breast cancer and where may future developments in the field take us?

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DNA methylation marks inter-nucleosome linker regions throughout the human genome

10.7287/peerj.preprints.27v3 ◽

2013 ◽

Author(s):

Benjamin P. Berman ◽

Yaping Liu ◽

Theresa K. Kelly

Keyword(s):

Dna Methylation ◽

Human Genome ◽

Ctcf Binding ◽

Gene Promoters ◽

Cpg Dinucleotides ◽

Sequencing Technologies ◽

Nucleosome Organization ◽

Genome Wide ◽

A Genome ◽

Sequencing Studies

Background: Nucleosome organization and DNA methylation are two mechanisms that are important for proper control of mammalian transcription, as well as epigenetic dysregulation associated with cancer. Whole-genome DNA methylation sequencing studies have found that methylation levels in the human genome show periodicities of approximately 190 bp, suggesting a genome-wide relationship between the two marks. A recent report (Chodavarapu et al., 2010) attributed this to higher methylation levels of DNA within nucleosomes. Here, we analyzed a number of published datasets and found a more compelling alternative explanation, namely that methylation levels are highest in linker regions between nucleosomes. Results: Reanalyzing the data from (Chodavarapu et al., 2010), we found that nucleosome-associated methylation could be strongly confounded by known sequence-related biases of the next-generation sequencing technologies. By accounting for these biases and using an unrelated nucleosome profiling technology, NOMe-seq, we found that genome-wide methylation was actually highest within linker regions occurring between nucleosomes in multi-nucleosome arrays. This effect was consistent among several methylation datasets generated independently using two unrelated methylation assays. Linker-associated methylation was most prominent within long Partially Methylated Domains (PMDs) and the positioned nucleosomes that flank CTCF binding sites. CTCF adjacent nucleosomes retained the correct positioning in regions completely devoid of CpG dinucleotides, suggesting that DNA methylation is not required for proper nucleosomes positioning. Conclusions: The biological mechanisms responsible for DNA methylation patterns outside of gene promoters remain poorly understood. We identified a significant genome-wide relationship between nucleosome organization and DNA methylation, which can be used to more accurately analyze and understand the epigenetic changes that accompany cancer and other diseases.

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ChiRA: an integrated framework for chimeric read analysis from RNA-RNA interactome and RNA structurome data

GigaScience ◽

10.1093/gigascience/giaa158 ◽

2021 ◽

Vol 10 (2) ◽

Author(s):

Pavankumar Videm ◽

Anup Kumar ◽

Oleg Zharkov ◽

Björn Andreas Grüning ◽

Rolf Backofen

Keyword(s):

Rna Structure ◽

Complete Analysis ◽

Published Data ◽

Random Choice ◽

Sequencing Technologies ◽

Genome Wide ◽

A Genome ◽

Interaction Partners ◽

Rna Interaction ◽

New Interactions

Abstract Background With the advances in next-generation sequencing technologies, it is possible to determine RNA-RNA interaction and RNA structure predictions on a genome-wide level. The reads from these experiments usually are chimeric, with each arm generated from one of the interaction partners. Owing to short read lengths, often these sequenced arms ambiguously map to multiple locations. Thus, inferring the origin of these can be quite complicated. Here we present ChiRA, a generic framework for sensitive annotation of these chimeric reads, which in turn can be used to predict the sequenced hybrids. Results Grouping reference loci on the basis of aligned common reads and quantification improved the handling of the multi-mapped reads in contrast to common strategies such as the selection of the longest hit or a random choice among all hits. On benchmark data ChiRA improved the number of correct alignments to the reference up to 3-fold. It is shown that the genes that belong to the common read loci share the same protein families or similar pathways. In published data, ChiRA could detect 3 times more new interactions compared to existing approaches. In addition, ChiRAViz can be used to visualize and filter large chimeric datasets intuitively. Conclusion ChiRA tool suite provides a complete analysis and visualization framework along with ready-to-use Galaxy workflows and tutorials for RNA-RNA interactome and structurome datasets. Common read loci built by ChiRA can rescue multi-mapped reads on paralogous genes without requiring any information on gene relations. We showed that ChiRA is sensitive in detecting new RNA-RNA interactions from published RNA-RNA interactome datasets.

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Comprehensive analysis of epigenetic signatures of mammalian transcription control

Molecular Omics ◽

10.1039/d0mo00130a ◽

2021 ◽

Author(s):

Guillaume Devailly ◽

Anagha Joshi

Keyword(s):

Mammalian Cell ◽

Comprehensive Analysis ◽

Transcription Control ◽

Sequencing Technologies ◽

Transcription Profiles ◽

Genome Wide ◽

A Genome ◽

Epigenetic Signatures ◽

Transcriptional Landscape

Advances in sequencing technologies have enabled exploration of epigenetic and transcription profiles at a genome-wide level. Epigenetic and transcriptional landscape is now available across hundreds of mammalian cell and tissue...

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Genotype–Environment Interactions in Microsatellite Stable/Microsatellite Instability-Low Colorectal Cancer: Results from a Genome-Wide Association Study

Cancer Epidemiology Biomarkers & Prevention ◽

10.1158/1055-9965.epi-10-0675 ◽

2011 ◽

Vol 20 (5) ◽

pp. 758-766 ◽

Cited By ~ 41

Author(s):

Jane C. Figueiredo ◽

Juan Pablo Lewinger ◽

Chi Song ◽

Peter T. Campbell ◽

David V. Conti ◽

...

Keyword(s):

Colorectal Cancer ◽

Microsatellite Instability ◽

Association Study ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome

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Dense and accurate whole-chromosome haplotyping of individual genomes

10.1101/126136 ◽

2017 ◽

Cited By ~ 1

Author(s):

David Porubsky ◽

Shilpa Garg ◽

Ashley D. Sanders ◽

Jan O. Korbel ◽

Victor Guryev ◽

...

Keyword(s):

Target Genes ◽

Chromosome Length ◽

Single Individual ◽

Sequencing Data ◽

Individual Genome ◽

Sequencing Technologies ◽

Biological Phenomena ◽

Genome Wide ◽

A Genome ◽

Long Read

ABSTRACTThe diploid nature of the genome is neglected in many analyses done today, where a genome is perceived as a set of unphased variants with respect to a reference genome. Many important biological phenomena such as compound heterozygosity and epistatic effects between enhancers and target genes, however, can only be studied when haplotype-resolved genomes are available. This lack of haplotype-level analyses can be explained by a dearth of methods to produce dense and accurate chromosome-length haplotypes at reasonable costs. Here we introduce an integrative phasing strategy that combines global, but sparse haplotypes obtained from strand-specific single cell sequencing (Strand-seq) with dense, yet local, haplotype information available through long-read or linked-read sequencing. Our experiments provide comprehensive guidance on favorable combinations of Strand-seq libraries and sequencing coverages to obtain complete and genome-wide haplotypes of a single individual genome (NA12878) at manageable costs. We were able to reliably assign > 95% of alleles to their parental haplotypes using as few as 10 Strand-seq libraries in combination with 10-fold coverage PacBio data or, alternatively, 10X Genomics linked-read sequencing data. We conclude that the combination of Strand-seq with different sequencing technologies represents an attractive solution to chart the unique genetic variation of diploid genomes.

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DNA methylation marks inter-nucleosome linker regions throughout the human genome

10.7287/peerj.preprints.27v2 ◽

2013 ◽

Author(s):

Benjamin P. Berman ◽

Yaping Liu ◽

Theresa K. Kelly

Keyword(s):

Dna Methylation ◽

Human Genome ◽

Ctcf Binding ◽

Gene Promoters ◽

Cpg Dinucleotides ◽

Sequencing Technologies ◽

Nucleosome Organization ◽

Genome Wide ◽

A Genome ◽

Sequencing Studies

Background: Nucleosome organization and DNA methylation are two mechanisms that are important for proper control of mammalian transcription, as well as epigenetic dysregulation associated with cancer. Whole-genome DNA methylation sequencing studies have found that methylation levels in the human genome show periodicities of approximately 190 bp, suggesting a genome-wide relationship between the two marks. A recent report (Chodavarapu et al., 2010) attributed this to higher methylation levels of DNA within nucleosomes. Here, we analyzed a number of published datasets and found a more compelling alternative explanation, namely that methylation levels are highest in linker regions between nucleosomes. Results: Reanalyzing the data from (Chodavarapu et al., 2010), we found that nucleosome-associated methylation could be strongly confounded by known sequence-related biases of the next-generation sequencing technologies. By accounting for these biases and using an unrelated nucleosome profiling technology, NOMe-seq, we found that genome-wide methylation was actually highest within linker regions occurring between nucleosomes in multi-nucleosome arrays. This effect was consistent among several methylation datasets generated independently using two unrelated methylation assays. Linker-associated methylation was most prominent within long Partially Methylated Domains (PMDs) and the positioned nucleosomes that flank CTCF binding sites. CTCF adjacent nucleosomes retained the correct positioning in regions completely devoid of CpG dinucleotides, suggesting that DNA methylation is not required for proper nucleosomes positioning. Conclusions: The biological mechanisms responsible for DNA methylation patterns outside of gene promoters remain poorly understood. We identified a significant genome-wide relationship between nucleosome organization and DNA methylation, which can be used to more accurately analyze and understand the epigenetic changes that accompany cancer and other diseases.

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Targeted resequencing identifies genes with recurrent variation in cerebral palsy

npj Genomic Medicine ◽

10.1038/s41525-019-0101-z ◽

2019 ◽

Vol 4 (1) ◽

Cited By ~ 3

Author(s):

C. L. van Eyk ◽

M. A. Corbett ◽

M. S. B. Frank ◽

D. L. Webber ◽

M. Newman ◽

...

Keyword(s):

Cerebral Palsy ◽

Rare Variants ◽

Neurodevelopmental Disorder ◽

Genetic Determinants ◽

Zebrafish Model ◽

Sequencing Technologies ◽

Genome Wide ◽

A Genome ◽

Significant Burden ◽

Generation Sequencing

Abstract A growing body of evidence points to a considerable and heterogeneous genetic aetiology of cerebral palsy (CP). To identify recurrently variant CP genes, we designed a custom gene panel of 112 candidate genes. We tested 366 clinically unselected singleton cases with CP, including 271 cases not previously examined using next-generation sequencing technologies. Overall, 5.2% of the naïve cases (14/271) harboured a genetic variant of clinical significance in a known disease gene, with a further 4.8% of individuals (13/271) having a variant in a candidate gene classified as intolerant to variation. In the aggregate cohort of individuals from this study and our previous genomic investigations, six recurrently hit genes contributed at least 4% of disease burden to CP: COL4A1, TUBA1A, AGAP1, L1CAM, MAOB and KIF1A. Significance of Rare VAriants (SORVA) burden analysis identified four genes with a genome-wide significant burden of variants, AGAP1, ERLIN1, ZDHHC9 and PROC, of which we functionally assessed AGAP1 using a zebrafish model. Our investigations reinforce that CP is a heterogeneous neurodevelopmental disorder with known as well as novel genetic determinants.

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