scholarly journals MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Justin Williams ◽  
Beisi Xu ◽  
Daniel Putnam ◽  
Andrew Thrasher ◽  
Chunliang Li ◽  
...  
Keyword(s):  
Promoter Activity ◽  
Malignant Neoplasms ◽  
Clinical Value ◽  
Individual Gene ◽  
Learning Framework ◽  
Genome Wide ◽  
Gene Level ◽  
Biological Impacts ◽  
The Individual ◽  
Methylation Patterns

AbstractAlthough genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities based on H3K4me3 and H3K27ac enrichment, from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

scholarly journals MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

2020 ◽  
Author(s):  
Justin Williams ◽  
Beisi Xu ◽  
Daniel Putnam ◽  
Andrew Thrasher ◽  
Chunliang Li ◽  
...  
Keyword(s):  
Promoter Activity ◽  
Malignant Neoplasms ◽  
Clinical Value ◽  
Individual Gene ◽  
Learning Framework ◽  
Genome Wide ◽  
Gene Level ◽  
Biological Impacts ◽  
The Individual ◽  
Methylation Patterns

AbstractAlthough genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities (H3K4me3 and H3K27ac enrichment) from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

scholarly journals Technical considerations when designing a gene expression panel for renal transplant diagnosis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
F. Toulza ◽  
K. Dominy ◽  
T. Cook ◽  
J. Galliford ◽  
J. Beadle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Transplant ◽  
Biological Significance ◽  
Tissue Sampling ◽  
Individual Gene ◽  
Antibody Mediated Rejection ◽  
Gene Level ◽  
Diagnostic Panel ◽  
The Individual ◽  
Gene Panels

Abstract Gene expression analysis is emerging as a new diagnostic tool in transplant pathology, in particular for the diagnosis of antibody-mediated rejection. Diagnostic gene expression panels are defined on the basis of their pathophysiological relevance, but also need to be tested for their robustness across different preservatives and analysis platforms. The aim of this study is the investigate the effect of tissue sampling and preservation on candidate genes included in a renal transplant diagnostic panel. Using the NanoString platform, we compared the expression of 219 genes in 51 samples, split for formalin-fixation and paraffin-embedding (FFPE) and RNAlater preservation (RNAlater). We found that overall, gene expression significantly correlated between FFPE and RNAlater samples. However, at the individual gene level, 46 of the 219 genes did not correlate across the 51 matched FFPE and RNAlater samples. Comparing gene expression results using NanoString and qRT-PCR for 18 genes in the same pool of RNA (RNAlater), we found a significant correlation in 17/18 genes. Our study indicates that, in samples from the same routine diagnostic renal transplant biopsy procedure split for FFPE and RNAlater, 21% of 219 genes of potential biological significance do not correlate in expression. Whether this is due to fixatives or tissue sampling, selection of gene panels for routine diagnosis should take this information into consideration.

scholarly journals Deep transcriptomic profiling reveals the similarity between endothelial cells cultured under static and oscillatory shear stress conditions

2016 ◽  
Vol 48 (9) ◽  
pp. 660-666 ◽  
Author(s):  
Congzhen Qiao ◽  
Fan Meng ◽  
Inhwan Jang ◽  
Hanjoong Jo ◽  
Y. Eugene Chen ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Shear Stress ◽  
Endothelial Function ◽  
Stress Conditions ◽  
Individual Gene ◽  
Gene Level ◽  
The Individual ◽  
Oscillatory Shear Stress ◽  
Whole Transcriptome ◽  
Transcriptome Level

Atherosclerosis is a multifactorial disease that preferentially develops in specific regions in the arterial tree. This characteristic is mainly attributed to the unique pattern of hemodynamic shear stress in vivo. High laminar shear stress (LS) found in straight lumen exerts athero-protective effects. Low or oscillatory shear stress (OS) present in regions of lesser curvature and arterial bifurcations predisposes arterial intima to atherosclerosis. Shear stress-regulated endothelial function plays an important role in the process of atherosclerosis. Most in vitro research studies focusing on the molecular mechanisms of endothelial function are performed in endothelial cells (ECs) under cultured static (ST) condition. Some findings, however, are not recapitulated in subsequent translational studies, mostly likely due to the missing biomechanical milieu. Here, we profiled the whole transcriptome of primary human coronary arterial endothelial cells (HCAECs) under different shear stress conditions with RNA sequencing. Among 16,313 well-expressed genes, we detected 8,177 that were differentially expressed in OS vs. LS conditions and 9,369 in ST vs. LS conditions. Notably, only 1,618 were differentially expressed in OS vs. ST conditions. Hierarchical clustering of ECs demonstrated a strong similarity between ECs under OS and ST conditions at the transcriptome level. Subsequent pairwise heat mapping and principal component analysis gave further weight to the similarity. At the individual gene level, expressional analysis of representative well-known genes as well as novel genes showed a comparable amount at mRNA and protein levels in ECs under ST and OS conditions. In conclusion, the present work compared the whole transcriptome of HCAECs under different shear stress conditions at the transcriptome level as well as at the individual gene level. We found that cultured ECs are significantly different from those under LS conditions. Thus using cells under ST conditions is unlikely to elucidate endothelial physiology. Given the revealed high similarities of the endothelial transcriptome under OS and ST conditions, it may be helpful to understand the underlying mechanisms of OS-induced endothelial dysfunction from static cultured endothelial studies.

scholarly journals The good, the bad, and the ugly: Evolutionary and pathological aspects of gene dosage alterations

PLoS Genetics ◽  
2021 ◽  
Vol 17 (12) ◽  
pp. e1009906
Author(s):  
M. Felicia Basilicata ◽  
Claudia Isabelle Keller Valsecchi
Keyword(s):  
Developmental Disorders ◽  
Common Ground ◽  
Gene Dosage ◽  
Paternal Genome ◽  
Individual Gene ◽  
Developmental Progression ◽  
Gene Level ◽  
Heteromorphic Sex Chromosomes ◽  
Genetic Perturbations ◽  
The Individual

Diploid organisms contain a maternal and a paternal genome complement that is thought to provide robustness and allow developmental progression despite genetic perturbations that occur in heterozygosity. However, changes affecting gene dosage from the chromosome down to the individual gene level possess a significant pathological potential and can lead to developmental disorders (DDs). This indicates that expression from a balanced gene complement is highly relevant for proper cellular and organismal function in eukaryotes. Paradoxically, gene and whole chromosome duplications are a principal driver of evolution, while heteromorphic sex chromosomes (XY and ZW) are naturally occurring aneuploidies important for sex determination. Here, we provide an overview of the biology of gene dosage at the crossroads between evolutionary benefit and pathogenicity during disease. We describe the buffering mechanisms and cellular responses to alterations, which could provide a common ground for the understanding of DDs caused by copy number alterations.

scholarly journals Perturbations of Ribosomal Protein Expression Reveal Overlapping Gene Networks between Drosophila Minutes and Human Cancer

2020 ◽  
Author(s):  
Jai A Denton ◽  
Mariana Velasque ◽  
Floyd A Reed
Keyword(s):  
Ribosomal Proteins ◽  
Gene Networks ◽  
Ribosome Biogenesis ◽  
Human Cancer ◽  
Whole Body ◽  
Individual Gene ◽  
Gene Level ◽  
The Individual ◽  
Time Specific

AbstractRibosomal proteins (RPs) are critical to all cellular operations through their key roles in ribosome biogenesis and translation, as well as their extra-ribosomal functions. Although highly tissue- and time-specific in expression, little is known about the macro-level roles of RPs in shaping transcriptomes. A wealth of RP mutants exist, including the Drosophila melanogaster Minutes, with RP encoding genes that vary from greatly under-expressed to greatly over-expressed. Leveraging a subset of these mutants and using whole-body RNA sequencing, we identified the RP macro transcriptome and then sought to compare it with transcriptomes of pathologies associated with failures of ribosomal function. Gene-based analysis revealed highly variable transcriptomes of RP mutations with little overlap in genes that were differentially expressed. In contrast, weighted gene co-expression network analysis (WGCNA) revealed a highly conserved pattern across all RP mutants studied. When we compared network changes in RP mutants, we observed similarities to transcriptome alterations in human cancer, and thus confirming the oncogenic role of RPs. Therefore, what may appear stochastic at the individual gene level, forms clearly predictable patterns when viewed as a whole.

scholarly journals Understanding and using quantitative genetic variation

2010 ◽  
Vol 365 (1537) ◽  
pp. 73-85 ◽  
Author(s):  
William G. Hill
Keyword(s):  
Genetic Variation ◽  
Complex Traits ◽  
Natural Populations ◽  
Multiple Traits ◽  
Individual Gene ◽  
Term Selection ◽  
Laboratory Selection ◽  
Gene Level ◽  
Breeding Programmes ◽  
The Individual

Quantitative genetics, or the genetics of complex traits, is the study of those characters which are not affected by the action of just a few major genes. Its basis is in statistical models and methodology, albeit based on many strong assumptions. While these are formally unrealistic, methods work. Analyses using dense molecular markers are greatly increasing information about the architecture of these traits, but while some genes of large effect are found, even many dozens of genes do not explain all the variation. Hence, new methods of prediction of merit in breeding programmes are again based on essentially numerical methods, but incorporating genomic information. Long-term selection responses are revealed in laboratory selection experiments, and prospects for continued genetic improvement are high. There is extensive genetic variation in natural populations, but better estimates of covariances among multiple traits and their relation to fitness are needed. Methods based on summary statistics and predictions rather than at the individual gene level seem likely to prevail for some time yet.

scholarly journals Integrating Predicted Transcriptome From Multiple Tissues Improves Association Detection

2018 ◽  
Author(s):  
Alvaro N. Barbeira ◽  
Milton D. Pividori ◽  
Jiamao Zheng ◽  
Heather E. Wheeler ◽  
Dan L. Nicolae ◽  
...  
Keyword(s):  
Complex Traits ◽  
Target Genes ◽  
Association Studies ◽  
Test Methods ◽  
Genome Wide Association Studies ◽  
Individual Level ◽  
Genome Wide ◽  
Gene Level ◽  
The Individual ◽  
The Uk

AbstractIntegration of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is needed to improve our understanding of the biological mechanisms underlying GWAS hits, and our ability to identify therapeutic targets. Gene-level association test methods such as PrediXcan can prioritize candidate targets. However, limited eQTL sample sizes and absence of relevant developmental and disease context restricts our ability to detect associations. Here we propose an efficient statistical method that leverages the substantial sharing of eQTLs across tissues and contexts to improve our ability to identify potential target genes: MulTiXcan. MulTiXcan integrates evidence across multiple panels while taking into account their correlation. We apply our method to a broad set of complex traits available from the UK Biobank and show that we can detect a larger set of significantly associated genes than using each panel separately. To improve applicability, we developed an extension to work on summary statistics: S-MulTiXcan, which we show yields highly concordant results with the individual level version. Results from our analysis as well as software and necessary resources to apply our method are publicly available.

scholarly journals Genome-Wide and Experimental Resolution of Relative Translation Elongation Speed at Individual Gene Level in Human Cells

PLoS Genetics ◽  
2016 ◽  
Vol 12 (2) ◽  
pp. e1005901 ◽  
Author(s):  
Xinlei Lian ◽  
Jiahui Guo ◽  
Wei Gu ◽  
Yizhi Cui ◽  
Jiayong Zhong ◽  
...  
Keyword(s):  
Human Cells ◽  
Translation Elongation ◽  
Individual Gene ◽  
Genome Wide ◽  
Gene Level ◽  
Experimental Resolution

scholarly journals CPNE3 moderates the association between anxiety and working memory

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chunhui Chen ◽  
Ziyi Wang ◽  
Chuansheng Chen ◽  
Gui Xue ◽  
Shuzhen Lu ◽  
...  
Keyword(s):  
Working Memory ◽  
Genome Wide Association Study ◽  
Significant Negative Correlation ◽  
Curvilinear Relationship ◽  
Gene Score ◽  
Genome Wide ◽  
Score Analysis ◽  
Gene Level ◽  
And Performance ◽  
The Individual

AbstractMutual influences between anxiety and working memory (WM) have been extensively studied, and their curvilinear relationship resembles the classic Yerkes-Dodson law of arousal and performance. Given the genetic bases of both anxiety and WM, it is likely that the individual differences in the Yerkes-Dodson law of anxiety and WM may have genetic correlates. The current genome wide association study (GWAS) enrolled 1115 healthy subjects to search for genes that are potential moderators of the association between anxiety and WM. Results showed that CPNE3 rs10102229 had the strongest effect, p = 3.38E−6 at SNP level and p = 2.68E−06 at gene level. Anxiety and WM had a significant negative correlation (i.e., more anxious individuals performed worse on the WM tasks) for the TT genotype of rs10102229 (resulting in lower expression of CPNE3), whereas the correlation was positive (i.e., more anxious individuals performed better on the WM tasks) for the CC carriers. The same pattern of results was found at the gene level using gene score analysis. These effects were replicated in an independent sample (N = 330). The current study is the first to report a gene that moderates the relation between anxiety and WM and potentially provides a genetic explanation for the classic Yerkes-Dodson law.

scholarly journals Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Todd R. Robeck ◽  
Zhe Fei ◽  
Ake T. Lu ◽  
Amin Haghani ◽  
Eve Jourdain ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Age Estimation ◽  
Species Conservation ◽  
Genome Wide ◽  
Epigenetic Aging ◽  
Highly Correlated ◽  
Methylation Patterns ◽  
Cg Dinucleotides ◽  
Free Ranging ◽  
Unique Species

AbstractThe development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.

Sign in / Sign up

Export Citation Format

Share Document