A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer

Liu, Zhi; Dong, Xiao; Li, Yixue

doi:10.3389/fgene.2018.00570

Cited by 28 publications

(24 citation statements)

References 54 publications

(66 reference statements)

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“…We further identified that loss of allelic replication was associated with expression down-regulation at three colon cancer-related gene loci that are also monoallelically expressed. Monoallelic expression has also been reported to differ in frequency between grades of brain tumours (Walker et al, 2012) and occur at different genes in colorectal tumours compared to normal tissue (Liu et al, 2018), suggesting that cancer cells can acquire ectopic allele-specific expression during transformation. Together, our results suggest that altered allelic replication, induced by global changes in DNA methylation, may be a mechanism of gene deregulation within cancer cells.…”

Section: Discussionmentioning

confidence: 99%

DNA methylation is required to maintain DNA replication timing precision and 3D genome integrity

Smith

Luu

et al. 2020

Preprint

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DNA replication timing and three-dimensional (3D) genome organisation are associated with distinct epigenome patterns across large domains during differentiation and cancer progression. However, it is unclear if alternations in the epigenome, in particular cancer-associated DNA hypomethylation, can directly promote higher order genome architectural alterations. Here, we use Hi-C and single cell Repli-Seq, in the colorectal cancer DNMT1 and DNMT3B DNA methyltransferases double knockout model, to determine the impact of DNA hypomethylation on replication timing and 3D genome organisation. First, we find that the hypomethylated cells show a striking loss of replication timing precision with gain of intra-population replication timing heterogeneity and loss of 3D genome compartmentalisation. Second, hypomethylated regions that undergo a large change in replication timing also show loss of allelic replication timing, including at cancer-related genes. Finally, we observe the striking formation of ectopic H3K4me3-H3K9me3 domains across hypomethylated regions where late replication is maintained, which we propose serve to prevent aberrant transcription and loss of genome organisation after DNA demethylation. Together, our results highlight a previously underappreciated role for DNA methylation in the maintenance of 3D genome architecture.

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Section: Discussionmentioning

confidence: 99%

DNA methylation is required to maintain DNA replication timing precision and 3D genome integrity

Smith

Luu

et al. 2020

Preprint

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“…Notably, ERASE uses all ASEs rather than summarizing information across a gene, thus retaining ASEs generated due to splicing QTLs. Given the growing popularity of ASE analyses [59][60][61][62] and the increased interest in splicing, ERASE's ability to detect enrichment in small ASE datasets and multiple annotations has the potential to add significantly to biological knowledge. This accounts for biases in ASE discovery due to high read depth and exonic structure.…”

Section: Discussionmentioning

confidence: 99%

ERASE: Extended Randomization for assessment of annotation enrichment in ASE datasets

D’Sa

Guelfi

et al. 2019

Preprint

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Genome-wide association studies (GWAS) have identified thousands of genetic variants 24 associated with various human phenotypes and many of these loci are thought to act at a molecular 25 level by regulating gene expression. Detection of allele specific expression (ASE), namely 26 preferential usage of an allele at a transcribed locus, is an increasingly important means of studying 27 the genetic regulation of gene expression. However, there are currently a paucity of tools available 28 to link ASE sites with GWAS risk loci. Existing integration methods first use ASE sites to infer 29 cis-acting expression quantitative trait loci (eQTL) and then apply eQTL-based approaches. 30ERASE is a method that assesses the enrichment of risk loci amongst ASE sites directly. 31 Furthermore, ERASE enables additional biological insights to be made through the addition of 32 other SNP level annotations. ERASE is based on a randomization approach and controls for read 33 depth, a significant confounder in ASE analyses. In this paper, we demonstrate that ERASE can 34 efficiently detect the enrichment of eQTLs and risk loci within ASE data and that it remains 35 sensitive even when used with underpowered GWAS datasets. Finally, using ERASE in 36 combination with GWAS data for Parkinson's disease and data on the splicing potential of 37 individual SNPs, we provide evidence to suggest that risk loci for Parkinson's disease are enriched 38 amongst ASEs likely to affect splicing. Thus, we show that ERASE is an important new tool for 39 the integration of ASE and GWAS data, capable of providing novel insights into the 40 pathophysiology of complex diseases. 41 42 43 44 Over the last decade our understanding of complex genetic disorders has been transformed by the 45 use of genome-wide association studies (GWAS) with 71,673 SNP-trait associations reported in 46 the latest release of the NHGRI-EBI GWAS catalogue 1 . Complex neurological and 47 neuropsychiatric disorders are no exception. The most recent GWAS for Parkinson's disease (PD) 48 reported 78 risk loci 2 , while that for schizophrenia 3 reported 145. While there is a lag in terms of 49 understanding the underlying biological processes involved in contributing to disease risk, it is 50 thought that risk loci largely act by regulating gene expression as opposed to changing protein 51 function 4 . This observation has led to an increasing interest in the genetic regulation of gene 52 expression and the identification of expression quantitative trait loci (eQTLs, genetic variants that 53are associated with variation in gene expression) across the genome. eQTL studies have helped in 54 the interpretation of GWAS findings across a range of disorders 5; 6 . However, one limitation of 55 eQTL analyses is the requirement for large sample sizes. Since this can be difficult to achieve for 56 some human tissues, such as specific brain regions, alternative approaches more robust to small 57 sample sets are required. 58Allele specific expression (ASE) analysis is another means of studying ...

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“…The AEI quantifies the stoichiometric difference in the expression of the two alleles of a genetic locus [ 26 , 27 , 28 ] or two haplotypes of a diploid individual which can be distinguished at heterozygous variation sites [ 29 ]. Compared to gene expression analysis, AEI has the advantage of using two alleles of one gene within individuals and thus better controlling the genetic background and environmental effects, and therefore can sensitively and accurately detect the genetic and epigenetic differences in highly heterocellular samples such as tumors [ 30 , 31 ]. AEI has been applied to detect driver mutations in various human cancers including colorectal and breast cancer [ 32 , 33 ].…”

Section: Introductionmentioning

confidence: 99%

Allelic Expression Imbalance Analysis Identified YAP1 Amplification in p53- Dependent Osteosarcoma

Niu

Bak

Nusselt

et al. 2021

Cancers

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Osteosarcoma (OS) is a primary bone malignancy that mainly occurs during adolescent growth, suggesting that bone growth plays an important role in the aetiology of the disease. Genetic factors, such as heritable mutations of Rb1 and TP53, are associated with an increased risk of OS. Identifying driver mutations for OS has been challenging due to the complexity of bone growth-related pathways and the extensive intra-tumoral heterogeneity of this cancer. We previously generated pigs carrying a mutated TP53 gene, which develop OS at high frequency. RNA sequencing and allele expression imbalance (AEI) analysis of OS and matched healthy control samples revealed a highly significant AEI (p = 2.14 × 10−39) for SNPs in the BIRC3-YAP1 locus on pig chromosome 9. Analysis of copy number variation showed that YAP1 amplification is associated with the AEI and the progression of OS. Accordingly, the inactivation of YAP1 inhibits proliferation, migration, and invasion, and leads to the silencing of TP63 and reconstruction of p16 expression in p53-deficient porcine OS cells. Increased p16 mRNA expression correlated with lower methylation of its promoter. Altogether, our study provides molecular evidence for the role of YAP1 amplification in the progression of p53-dependent OS.

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A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer

Cited by 28 publications

References 54 publications

DNA methylation is required to maintain DNA replication timing precision and 3D genome integrity

DNA methylation is required to maintain DNA replication timing precision and 3D genome integrity

ERASE: Extended Randomization for assessment of annotation enrichment in ASE datasets

Allelic Expression Imbalance Analysis Identified YAP1 Amplification in p53- Dependent Osteosarcoma

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