scholarly journals Conservation of expression regulation throughout the animal kingdom

2014 ◽  
Author(s):  
Michael Kuhn ◽  
Andreas Beyer
Keyword(s):  
Gene Expression ◽  
Related Species ◽  
Expression Patterns ◽  
Gene Families ◽  
Tissue Expression ◽  
Rate Of Change ◽  
Gene Expression Patterns ◽  
Transfer Of Knowledge ◽  
Tissue Specific ◽  
Wide Range

Following the increase in available sequenced genomes, tissue-specific transcriptomes are being determined for a rapidly growing number of highly diverse species. Traditionally, only the transcriptomes of related species with equivalent tissues have been compared. Such an analysis is much more challenging over larger evolutionary distances when complementary tissues cannot readily be defined. Here, we present a method for the cross-species mapping of tissue-specific and developmental gene expression patterns across a wide range of animals, including many non-model species. Our approach maps gene expression patterns between species without requiring the definition of homologous tissues. With the help of this mapping, gene expression patterns can be compared even across distantly related species. In our survey of 36 datasets across 27 species, we detected conserved expression programs on all taxonomic levels, both within animals and between the animals and their closest unicellular relatives, the choanoflagellates. We found that the rate of change in tissue expression patterns is a property of gene families. Our findings open new avenues of study for the comparison and transfer of knowledge between different species.

scholarly journals Tissue-specific impacts of aging and genetics on gene expression patterns in humans

2021 ◽  
Author(s):  
Ryo Yamamoto ◽  
Ryan Chung ◽  
Juan Manuel Vazquez ◽  
Huanjie Sheng ◽  
Philippa Steinberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Purifying Selection ◽  
Transcript Level ◽  
Gene Expression Patterns ◽  
Opposite Pattern ◽  
Tissue Specific ◽  
Average Contribution ◽  
Primary Risk Factor ◽  
Expression Variance

Age is the primary risk factor for many common human diseases including heart disease, Alzheimer's dementias, cancers, and diabetes. Determining how and why tissues age differently is key to understanding the onset and progression of such pathologies. Here, we set out to quantify the relative contributions of genetics and aging to gene expression patterns from data collected across 27 tissues from 948 humans. We show that gene expression patterns become more erratic with age in several different tissues reducing the predictive power of expression quantitative trait loci. Jointly modelling the contributions of age and genetics to transcript level variation we find that the heritability (h2) of gene expression is largely consistent among tissues. In contrast, the average contribution of aging to gene expression variance varied by more than 20-fold among tissues with R2age > h2 in 5 tissues. We find that the coordinated decline of mitochondrial and translation factors is a widespread signature of aging across tissues. Finally, we show that while in general the force of purifying selection is stronger on genes expressed early in life compared to late in life as predicted by Medawar's hypothesis, a handful of highly proliferative tissues exhibit the opposite pattern. In contrast, gene expression variation that is under genetic control is strongly enriched for genes under relaxed constraint. Together we present a novel framework for predicting gene expression phenotypes from genetics and age and provide insights into the tissue-specific relative contributions of genes and the environment to phenotypes of aging.

scholarly journals Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes

2020 ◽  
Author(s):  
Timothy J. Durham ◽  
Riza M. Daza ◽  
Louis Gevirtzman ◽  
Darren A. Cusanovich ◽  
William Stafford Noble ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Gene Expression Patterns ◽  
Rna Seq ◽  
Cell Type ◽  
Tissue Specific ◽  
C Elegans

AbstractRecently developed single cell technologies allow researchers to characterize cell states at ever greater resolution and scale. C. elegans is a particularly tractable system for studying development, and recent single cell RNA-seq studies characterized the gene expression patterns for nearly every cell type in the embryo and at the second larval stage (L2). Gene expression patterns are useful for learning about gene function and give insight into the biochemical state of different cell types; however, in order to understand these cell types, we must also determine how these gene expression levels are regulated. We present the first single cell ATAC-seq study in C. elegans. We collected data in L2 larvae to match the available single cell RNA-seq data set, and we identify tissue-specific chromatin accessibility patterns that align well with existing data, including the L2 single cell RNA-seq results. Using a novel implementation of the latent Dirichlet allocation algorithm, we leverage the single-cell resolution of the sci-ATAC-seq data to identify accessible loci at the level of individual cell types, providing new maps of putative cell type-specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation in the worm.

scholarly journals Pre-treatment clinical behavioral and blood leukocyte gene expression patterns predict rate of change in response to early intervention in autism

2020 ◽  
Author(s):  
Michael V. Lombardo ◽  
Elena Maria Busuoli ◽  
Laura Schreibman ◽  
Aubyn C. Stahmer ◽  
Tiziano Pramparo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Treatment Outcome ◽  
Early Intervention ◽  
Expression Patterns ◽  
Rate Of Change ◽  
Biological Factor ◽  
Gene Expression Patterns ◽  
Pre Treatment ◽  
Blood Leukocyte ◽  
The Impact

AbstractEarly detection and intervention are believed to be key to facilitating better outcomes in children with autism, yet the impact of age at treatment start on outcome is poorly understood. While clinical traits such as language ability have been shown to predict treatment outcome, whether or not and how information at the genomic level can predict treatment outcome is unknown. Leveraging a cohort of toddlers with autism who all received the same standardized intervention at a very young age and provided a blood sample, here we find that very early treatment engagement (i.e., < 24 months) leads to greater gains while controlling for time in treatment. Pre-treatment clinical behavioral measures predicts 21% of the variance in the rate of skill growth during early intervention. Pre-treatment blood leukocyte gene expression patterns also predicts rate of skill growth, accounting for 13% of the variance treatment slopes. Results indicated that 295 genes can be prioritized as driving this effect. These treatment-relevant genes highly interact at the protein level, are enriched for differentially histone acetylated genes in autism post-mortem cortical tissue, and are normatively highly expressed in variety of subcortical and cortical areas important for social-communication and language development. This work indicates for the first time that gene expression can predict the rate of early intervention response and that a key biological factor linked to treatment outcome could be the susceptibility for epigenetic change via mechanisms such as histone acetylation.

scholarly journals Atlas of tissue-specific and tissue-preferential gene expression in ecologically and economically significant conifer Pinus sylvestris

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11781
Author(s):  
Sandra Cervantes ◽  
Jaana Vuosku ◽  
Tanja Pyhäjärvi
Keyword(s):  
Gene Expression ◽  
Pinus Sylvestris ◽  
Tissue Specificity ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Biological Databases ◽  
Ploidy Levels ◽  
Tissue Specific ◽  
Genomic Resources ◽  
Wide Range

Despite their ecological and economical importance, conifers genomic resources are limited, mainly due to the large size and complexity of their genomes. Additionally, the available genomic resources lack complete structural and functional annotation. Transcriptomic resources have been commonly used to compensate for these deficiencies, though for most conifer species they are limited to a small number of tissues, or capture only a fraction of the genes present in the genome. Here we provide an atlas of gene expression patterns for conifer Pinus sylvestris across five tissues: embryo, megagametophyte, needle, phloem and vegetative bud. We used a wide range of tissues and focused our analyses on the expression profiles of genes at tissue level. We provide comprehensive information of the per-tissue normalized expression level, indication of tissue preferential upregulation and tissue-specificity of expression. We identified a total of 48,001 tissue preferentially upregulated and tissue specifically expressed genes, of which 28% have annotation in the Swiss-Prot database. Even though most of the putative genes identified do not have functional information in current biological databases, the tissue-specific patterns discovered provide valuable information about their potential functions for further studies, as for example in the areas of plant physiology, population genetics and genomics in general. As we provide information on tissue specificity at both diploid and haploid life stages, our data will also contribute to the understanding of evolutionary rates of different tissue types and ploidy levels.

scholarly journals Tissue-specific profiling reveals distinctive regulatory architectures for ubiquitous, germline and somatic genes

2020 ◽  
Author(s):  
Jacques Serizay ◽  
Yan Dong ◽  
Jürgen Jänes ◽  
Michael Chesney ◽  
Chiara Cerrato ◽  
...  
Keyword(s):  
Gene Expression ◽  
Core Promoter ◽  
Regulatory Element ◽  
Expression Patterns ◽  
Somatic Tissue ◽  
Gene Expression Patterns ◽  
Specific Gene ◽  
Detailed Knowledge ◽  
Tissue Specific ◽  
C Elegans

AbstractDespite increasingly detailed knowledge of gene expression patterns, the regulatory architectures that drive them are not well understood. To address this, we compared transcriptional and regulatory element activities across five adult tissues of C. elegans, covering ∼90% of cells, and defined regulatory grammars associated with ubiquitous, germline and somatic tissue-specific gene expression patterns. We find architectural features that distinguish two major promoter types. Germline-specific and ubiquitously-active promoters have well positioned +1 and −1 nucleosomes associated with a periodic 10-bp WW signal. Somatic tissue-specific promoters lack these features, have wider nucleosome depleted regions, and are more enriched for core promoter elements, which surprisingly differ between tissues. A 10-bp periodic WW signal is also associated with +1 nucleosomes of ubiquitous promoters in fly and zebrafish but is not detected in mouse and human. Our results demonstrate fundamental differences in regulatory architectures of germline-active and somatic tissue-specific genes and provide a key resource for future studies.

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