Combined analysis of genome-wide expression and copy number profiles to identify key altered genomic regions in cancer.
Ontology highlight
ABSTRACT: Background
Analysis of DNA copy number alterations and gene expression changes in human samples have been used to find potential target genes in complex diseases. Recent studies have combined these two types of data using different strategies, but focusing on finding gene-based relationships. However, it has been proposed that these data can be used to identify key genomic regions, which may enclose causal genes under the assumption that disease-associated gene expression changes are caused by genomic alterations.
SUBMITTER: Fontanillo C
PROVIDER: S-EPMC3476997 | biostudies-literature | 2012
REPOSITORIES: biostudies-literature
Publications
Combined analysis of genome-wide expression and copy number profiles to identify key altered genomic regions in cancer.
Fontanillo Celia C Aibar Sara S Sanchez-Santos Jose Manuel JM De Las Rivas Javier J
BMC genomics 20121019
<h4>Background</h4>Analysis of DNA copy number alterations and gene expression changes in human samples have been used to find potential target genes in complex diseases. Recent studies have combined these two types of data using different strategies, but focusing on finding gene-based relationships. However, it has been proposed that these data can be used to identify key genomic regions, which may enclose causal genes under the assumption that disease-associated gene expression changes are cau ...[more]
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Project description:Somatic mutations accumulate with age and are associated closely with human health, their characterization in longevity cohorts remains largely unknown. Here, by analyzing whole genome somatic mutation profiles in 73 centenarians and 51 younger controls in China, we found that centenarian genomes are characterized by a markedly skewed distribution of somatic mutations, with many genomic regions being specifically conserved but displaying a high function potential. This, together with the observed more efficient DNA repair ability in the long-lived individuals, supports the existence of key genomic regions for human survival during aging, with their integrity being of essential to human longevity.
| S-EPMC10776117 | biostudies-literature
Project description:Supernumerary teats (SNTs) or nipples often emerge around the mammary line. This study performed a genome-wide selective sweep analysis (GWS) at the copy number variant (CNV) level using two selected signal calculation methods (VST and FST) to identify candidate genes associated with SNTs in goats. A total of 12,310 CNVs were identified from 37 animals and 123 CNVs, with the top 1% VST values including 84 candidate genes (CDGs). Of these CDGs, minichromosome maintenance complex component 3, ectodysplasin A receptor associated via death domain, and cullin 5 demonstrated functions closely related to mammary gland development. In addition, 123 CNVs with the top 1% FST values were annotated to 97 CDGs. 5-Hydroxytryptamine receptor 2A, CCAAT/enhancer-binding protein alpha, and the polymeric immunoglobulin receptor affect colostrum secretion through multiple signaling pathways. Two genes, namely, RNA-binding motif protein 46 and β-1,3-galactosyltransferase 5, showed a close relation to mammary gland development. Six CNVs were identified and annotated to five genes by intersecting the top 1% of candidate CNVs with both parameters. These genes include LOC102185621, LOC102190481, and UDP-glucose pyrophosphorylase 2, which potentially affect the occurrence of BC through multiple biological processes, such as cell detoxification, glycogen synthesis, and phospholipid metabolism. In conclusion, we discovered numerous genes related to mammary development and breast cancer (BC) through a GWS, which suggests the mechanism of SNTs in goats and a certain association between mammary cancer and SNTs.
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Project description:Protein copy numbers constrain systems-level properties of regulatory networks, but proportional proteomic data remain scarce compared to RNA-seq. We related mRNA to protein statistically using best-available data from quantitative proteomics-transcriptomics for 4366 genes in 369 cell lines. The approach starts with a protein's median copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model linking mRNAs to protein. For dozens of cell lines and primary samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, empirical protein-to-mRNA ratios, and a proteogenomic DREAM challenge winner. The optimal mRNA-to-protein relationships capture biological processes along with hundreds of known protein-protein complexes, suggesting mechanistic relationships. We use the method to identify a viral-receptor abundance threshold for coxsackievirus B3 susceptibility from 1489 systems-biology infection models parameterized by protein inference. When applied to 796 RNA-seq profiles of breast cancer, inferred copy-number estimates collectively reclassify 26-29% of luminal tumors. By adopting a gene-centered perspective of mRNA-protein covariation across different biological contexts, we achieve accuracies comparable to the technical reproducibility of contemporary proteomics.
| S-SCDT-10_1038-S44320-024-00064-3 | biostudies-other
Project description:SummarySelecting the optimal cancer cell line for an experiment can be challenging given the diversity of lines available. Here, we present CNpare, which identifies similar cell line models based on genome-wide DNA copy number.Availability and implementationCNpare is available as an R package at https://github.com/macintyrelab/CNpare. All analysis performed in the manuscript can be reproduced via the code found at https://github.com/macintyrelab/CNpare_analyses.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Copy number variants (CNVs), defined as losses and gains of segments of genomic DNA, are a major source of genomic variation.In this study, we identified over 2,000 human CNVs that overlap with orthologous chimpanzee or orthologous macaque CNVs. Of these, 170 CNVs overlap with both chimpanzee and macaque CNVs, and these were collapsed into 34 hotspot regions of CNV formation. Many of these hotspot regions of CNV formation are functionally relevant, with a bias toward genes involved in immune function, some of which were previously shown to evolve under balancing selection in humans. The genes in these primate CNV formation hotspots have significant differential expression levels between species and show evidence for positive selection, indicating that they have evolved under species-specific, directional selection.These hotspots of primate CNV formation provide a novel perspective on divergence and selective pressures acting on these genomic regions.
| S-EPMC3219974 | biostudies-literature
Project description:Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.
| S-EPMC8552909 | biostudies-literature
Project description:BackgroundDuring cancer progression, malignant cells accumulate somatic mutations that can lead to genetic aberrations. In particular, evolutionary events akin to segmental duplications or deletions can alter the copy-number profile (CNP) of a set of genes in a genome. Our aim is to compute the evolutionary distance between two cells for which only CNPs are known. This asks for the minimum number of segmental amplifications and deletions to turn one CNP into another. This was recently formalized into a model where each event is assumed to alter a copy-number by 1 or -1, even though these events can affect large portions of a chromosome.ResultsWe propose a general cost framework where an event can modify the copy-number of a gene by larger amounts. We show that any cost scheme that allows segmental deletions of arbitrary length makes computing the distance strongly NP-hard. We then devise a factor 2 approximation algorithm for the problem when copy-numbers are non-zero and provide an implementation called cnp2cnp. We evaluate our approach experimentally by reconstructing simulated cancer phylogenies from the pairwise distances inferred by cnp2cnp and compare it against two other alternatives, namely the MEDICC distance and the Euclidean distance.ConclusionsThe experimental results show that our distance yields more accurate phylogenies on average than these alternatives if the given CNPs are error-free, but that the MEDICC distance is slightly more robust against error in the data. In all cases, our experiments show that either our approach or the MEDICC approach should preferred over the Euclidean distance.
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Project description:Genomic copy number variants (CNVs) have been implicated in multiple psychiatric disorders, but not much is known about their influence on anxiety disorders specifically. Using next-generation sequencing (NGS) and two additional array-based genotyping approaches, we detected CNVs in a mouse model consisting of two inbred mouse lines showing high (HAB) and low (LAB) anxiety-related behavior, respectively. An influence of CNVs on gene expression in the central (CeA) and basolateral (BLA) amygdala, paraventricular nucleus (PVN), and cingulate cortex (Cg) was shown by a two-proportion Z-test (p = 1.6 x 10-31), with a positive correlation in the CeA (p = 0.0062), PVN (p = 0.0046) and Cg (p = 0.0114), indicating a contribution of CNVs to the genetic predisposition to trait anxiety in the specific context of HAB/LAB mice. In order to confirm anxiety-relevant CNVs and corresponding genes in a second mouse model, we further examined CD-1 outbred mice. We revealed the distribution of CNVs by genotyping 64 CD 1 individuals using a high-density genotyping array (Jackson Laboratory). 78 genes within those CNVs were identified to show nominally significant association (48 genes), or a statistical trend in their association (30 genes) with the time animals spent on the open arms of the elevated plus-maze (EPM). Fifteen of them were considered promising candidate genes of anxiety-related behavior as we could show a significant overlap (permutation test, p = 0.0051) with genes within HAB/LAB CNVs. Thus, here we provide what is to our knowledge the first extensive catalogue of CNVs in CD-1 mice and potential corresponding candidate genes linked to anxiety-related behavior in mice.
| S-EPMC4444327 | biostudies-literature