scholarly journals Computational approach to identifying universal macrophage biomarker

2019 ◽  
Author(s):  
Dharanidhar Dang ◽  
Sahar Taheri ◽  
Soumita Das ◽  
Pradipta Ghosh ◽  
Lawrence S. Prince ◽  
...  
Keyword(s):  
Expression Patterns ◽  
Computational Approach ◽  
Biological Data ◽  
Specific Expression ◽  
Cellular Debris ◽  
Mouse Tissues ◽  
Gene Expression Dynamics ◽  
Reliable Marker ◽  
Multiple Species ◽  
Human And Mouse

ABSTRACTMacrophages are a type of white blood cell, of the immune system, that engulfs and digests cellular debris, cancer cells, and anything else that does not have the type of proteins specific to healthy body cells on its surface. Understanding gene expression dynamics in macrophages are crucial for studying human diseases. Recent advances in high-throughput technologies have enabled the collection of immense amounts of biological data. A reliable marker of macrophage is essential to study their function. Traditional approaches use a number of markers that may have tissue specific expression patterns. To identify universal biomarker of macrophage, we used a previously published computational approach called BECC (Boolean Equivalent Correlated Clusters) that was originally used to identify universal cell cycle genes. We performed BECC analysis on a seed gene CD14, a known macrophage marker. FCER1G and TYROBP were among the top candidates which were validated as strong candidates for universal biomarkers for macrophages in human and mouse tissues. To our knowledge, such a finding is first of its kind.CONTRIBUTIONS TO THE FIELDWe have developed a computational approach to identify universal biomarkers of different entities in a biological system. We applied this approach to study macrophages and identified universal biomarkers of this particular cell type. FCER1G and TYROBP were among the top candidates which were validated as strong candidates for universal biomarkers for macrophages in human and mouse tissues. The expression patterns of TYROBP and FCER1G are found to be more homogeneous compared to currently used biomarkers such as ITGAM, EMR1 (F4/80), and CD68. Further, we demonstrated that this homogeneity extends to all the tissues currently profiled in the public domain in multiple species including human and mouse. FCER1G and TYROBP expression patterns were also found to be extremely specific to macrophages found in various tissues. They are strongly co-expressed together. We believe that these two genes are the most reliable candidates of universal biomarker for macrophages.

scholarly journals FOXP2 exhibits projection neuron class specific expression, but is not required for multiple aspects of cortical histogenesis

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Ryan J Kast ◽  
Alexandra L Lanjewar ◽  
Colton D Smith ◽  
Pat Levitt
Keyword(s):  
Expression Patterns ◽  
Projection Neuron ◽  
Specific Expression ◽  
Neuron Populations ◽  
Mouse Cortex ◽  
Molecular Studies ◽  
Multiple Species ◽  
Molecular Phenotypes ◽  
And Function

The expression patterns of the transcription factor FOXP2 in the developing mammalian forebrain have been described, and some studies have tested the role of this protein in the development and function of specific forebrain circuits by diverse methods and in multiple species. Clinically, mutations in FOXP2 are associated with severe developmental speech disturbances, and molecular studies indicate that impairment of Foxp2 may lead to dysregulation of genes involved in forebrain histogenesis. Here, anatomical and molecular phenotypes of the cortical neuron populations that express FOXP2 were characterized in mice. Additionally, Foxp2 was removed from the developing mouse cortex at different prenatal ages using two Cre-recombinase driver lines. Detailed molecular and circuit analyses were undertaken to identify potential disruptions of development. Surprisingly, the results demonstrate that Foxp2 function is not required for many functions that it has been proposed to regulate, and therefore plays a more limited role in cortical development than previously thought.

scholarly journals Comparison of human and mouse tissues with focus on genes with no 1-to-1 homology

2021 ◽  
Author(s):  
Jieun Jeong ◽  
Manolis Kellis
Keyword(s):  
Immune Response ◽  
Target Genes ◽  
Expression Patterns ◽  
Adaptive Immune Response ◽  
Mouse Skin ◽  
Rna Seq ◽  
Therapy Targets ◽  
Mouse Tissues ◽  
Tissues Expression ◽  
Human And Mouse

We assembled a panel of 28 tissue pairs of human and mouse with RNA-Seq data on gene expression. We focused on genes with no 1-to-1 homology, because they pose special challenges. In this way, we identified expression patterns that identify and explain differences between the two species and suggest target genes for therapeutic applications. Here we mention three examples. One pattern is observed by defining the aggregate expression of immunoglobulin genes (which have no homology) as a measure of different levels of an immune response. In Lung, we used this statistic to find genes that have significantly higher expression in low/moderate response, and thus they may be therapy targets: increasing their expression or mimicking their function with medications may help in recovery from inflammation in the lungs. Some of the observed associations are common to human and mouse; other associations involve genes involved in cell-to-cell signaling or in regeneration but were not known to be important in Lung. Second pattern is that in the Small Intestine, mouse expresses much less antimicrobial defensins, while it has much higher expression of enzymes that are found to improve adaptive immune response. Such enzymes may be tested if they improve probiotic supplements that help in gut inflammation and other diseases. Another pattern involves a many-to-many homology group of defensins that did not have a described function. In human tissues, expression of its genes was found only in a study of a disease of hair covered skin, but several of its genes are highly expressed in two tissues of our panel: mouse Skin and to a lesser degree mouse Vagina. This suggests that those genes or their homologs in other species may provide non-antibiotic medications for hair covered skin and other tissues with microbiome that includes fungi.

Microarray-based discovery of highly expressed olfactory mucosal genes: potential roles in the various functions of the olfactory system

2003 ◽  
Vol 16 (1) ◽  
pp. 67-81 ◽  
Author(s):  
Mary Beth Genter ◽  
Paul P. Van Veldhoven ◽  
Anil G. Jegga ◽  
Bhuvana Sakthivel ◽  
Sue Kong ◽  
...  
Keyword(s):  
Neuronal Differentiation ◽  
Expression Pattern ◽  
Expression Patterns ◽  
Paraoxonase 1 ◽  
Specific Gene ◽  
Specific Expression ◽  
Mouse Cdna ◽  
Mouse Tissues ◽  
Cell Type Specific Expression ◽  
Gene Transcripts

We sought to gain a global view of tissue-specific gene expression in the olfactory mucosa (OM), the major site of neurogenesis and neuroregeneration in adult vertebrates, by examination of its overexpressed genes relative to that in 81 other developing and adult mouse tissues. We used a combination of statistical and fold-difference criteria to identify the top 269 cloned cDNAs from an array of 8,734 mouse cDNA elements on the Incyte Mouse GEM1 array. These clones, representing known and poorly characterized gene transcripts, were grouped according to their relative expression patterns across the other tissues and then further examined with respect to gene ontology categories. Approximately one-third of the 269 genes were also highly expressed in developing and/or adult central nervous system tissues. Several of these have been suggested or demonstrated to play roles in neurogenesis, neuronal differentiation, and/or neuronal migration, further suggesting that many of the unknown genes that share this expression pattern may play similar roles. Highly OM-specific genes included a palate, lung, and nasal epithelium carcinoma-associated gene ( Plunc); sphingosine phosphate lyase ( Sgpl1), and paraoxonase 1 ( Pon1). Cell-type-specific expression within OM was established using in situ hybridization for several representative expression pattern clusters. Using the ENSEMBL-assembled mouse genome and comparative genomics analyses to the human genome, we assigned many of the unknown expressed sequence tags (ESTs) and poorly characterized genes to either novel or known gene products and provided predictive classification. Further exploration of this database will provide additional insights into genes and pathways critical for olfactory neurogenesis, neuronal differentiation, olfaction, and mucosal defense.

scholarly journals tsRBase: a comprehensive database for expression and function of tsRNAs in multiple species

2020 ◽  
Vol 49 (D1) ◽  
pp. D1038-D1045
Author(s):  
Yuanli Zuo ◽  
Lei Zhu ◽  
Zhixin Guo ◽  
Wenrong Liu ◽  
Jiting Zhang ◽  
...  
Keyword(s):  
Small Rnas ◽  
Expression Patterns ◽  
Biological Significance ◽  
Biological Processes ◽  
Rna Seq ◽  
Specific Expression ◽  
Spatiotemporal Expression ◽  
Multiple Species ◽  
And Function ◽  
Diverse Data

Abstract tRNA-derived small RNAs (tsRNAs) are a class of novel small RNAs, ubiquitously present in prokaryotes and eukaryotes. It has been reported that tsRNAs exhibit spatiotemporal expression patterns and can function as regulatory molecules in many biological processes. Current tsRNA databases only cover limited organisms and ignore tsRNA functional characteristics. Thus, integrating more relevant tsRNA information is helpful for further exploration. Here, we present a tsRNA database, named tsRBase, which integrates the expression pattern and functional information of tsRNAs in multiple species. In tsRBase, we identified 121 942 tsRNAs by analyzing more than 14 000 publicly available small RNA-seq data covering 20 species. This database collects samples from different tissues/cell-lines, or under different treatments and genetic backgrounds, thus helps depict specific expression patterns of tsRNAs under different conditions. Importantly, to enrich our understanding of biological significance, we collected tsRNAs experimentally validated from published literatures, obtained protein-binding tsRNAs from CLIP/RIP-seq data, and identified targets of tsRNAs from CLASH and CLEAR-CLIP data. Taken together, tsRBase is the most comprehensive and systematic tsRNA repository, exhibiting all-inclusive information of tsRNAs from diverse data sources of multiple species. tsRBase is freely available at http://www.tsrbase.org.

scholarly journals FOXP2 exhibits projection neuron class specific expression, but is not required for multiple aspects of cortical histogenesis

2019 ◽  
Author(s):  
Ryan J Kast ◽  
Alexandra L Lanjewar ◽  
Colton D Smith ◽  
Pat Levitt
Keyword(s):  
Expression Patterns ◽  
Projection Neuron ◽  
Specific Expression ◽  
Neuron Populations ◽  
Mouse Cortex ◽  
Molecular Studies ◽  
Multiple Species ◽  
Molecular Phenotypes ◽  
And Function

AbstractThe expression patterns of the transcription factor FOXP2 in the developing mammalian forebrain have been described, and some studies have tested the role of this protein in the development and function of specific forebrain circuits by diverse methods and in multiple species. Clinically, mutations in FOXP2 are associated with severe developmental speech disturbances, and molecular studies indicate that impairment of Foxp2 may lead to dysregulation of genes involved in forebrain histogenesis. Here, anatomical and molecular phenotypes of the cortical neuron populations that express FOXP2 were characterized in mice. Additionally, Foxp2 was removed from the developing mouse cortex at different prenatal ages using two Cre-recombinase driver lines. Detailed molecular and circuit analyses were undertaken to identify potential disruptions of development. Surprisingly, the results demonstrate that Foxp2 function is not required for many functions that it has been proposed to regulate, and therefore plays a more limited role in cortical development than previously thought.

scholarly journals Comparative transcriptome profiling of the human and mouse dorsal root ganglia: An RNA-seq-based resource for pain and sensory neuroscience research

2017 ◽  
Author(s):  
Pradipta Ray ◽  
Andrew Torck ◽  
Lilyana Quigley ◽  
Andi Wangzhou ◽  
Matthew Neiman ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Rna Sequencing ◽  
Dorsal Root Ganglia ◽  
Dorsal Root ◽  
Expression Patterns ◽  
Rna Seq ◽  
Sequencing Data ◽  
Mouse Tissues ◽  
Human And Mouse ◽  
Insight Into

AbstractMolecular neurobiological insight into human nervous tissues is needed to generate next generation therapeutics for neurological disorders like chronic pain. We obtained human Dorsal Root Ganglia (DRG) samples from organ donors and performed RNA-sequencing (RNA-seq) to study the human DRG (hDRG) transcriptional landscape, systematically comparing it with publicly available data from a variety of human and orthologous mouse tissues, including mouse DRG (mDRG). We characterized the hDRG transcriptional profile in terms of tissue-restricted gene co-expression patterns and putative transcriptional regulators, and formulated an information-theoretic framework to quantify DRG enrichment. Our analyses reveal an hDRG-enriched protein-coding gene set (~140), some of which have not been described in the context of DRG or pain signaling. A majority of these show conserved enrichment in mDRG, and were mined for known drug - gene product interactions. Comparison of hDRG and tibial nerve transcriptomes suggest pervasive mRNA transport of sensory neuronal genes to axons in adult hDRG, with potential implications for mechanistic insight into chronic pain in patients. Relevant gene families and pathways were also analyzed, including transcription factors (TFs), g-protein coupled receptors (GCPRs) and ion channels. We present our work as an online, searchable repository (http://www.utdallas.edu/bbs/painneurosciencelab/DRGtranscriptome), creating a valuable resource for the community. Our analyses provide insight into DRG biology for guiding development of novel therapeutics, and a blueprint for cross-species transcriptomic analyses.SummaryWe generated RNA sequencing data from human DRG samples and comprehensively compared this transcriptome to other human tissues and a matching panel of mouse tissues. Our analysis uncovered functionally enriched genes in the human and mouse DRG with important implications for understanding sensory biology and pain drug discovery.

scholarly journals Tissue‐specific expression and post‐transcriptional regulation of the ATPase inhibitory factor 1 (IF1) in human and mouse tissues

2018 ◽  
Vol 33 (2) ◽  
pp. 1836-1851 ◽  
Author(s):  
Pau B. Esparza-Moltó ◽  
Cristina Nuevo-Taρioles ◽  
Margarita Chamorro ◽  
Laura Nájera ◽  
Laura Torresano ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Inhibitory Factor ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression ◽  
Mouse Tissues ◽  
Post Transcriptional Regulation ◽  
Human And Mouse ◽  
Inhibitory Factor 1

scholarly journals ExTraMapper: Exon- and Transcript-level mappings for orthologous gene pairs

2018 ◽  
Author(s):  
Ferhat Ay ◽  
Abhijit Chakraborty ◽  
Ramana V. Davuluri
Keyword(s):  
Large Scale ◽  
Gene Annotation ◽  
Orthologous Gene ◽  
Transcript Level ◽  
Specific Expression ◽  
Gene Pairs ◽  
Link Type ◽  
Mouse Tissues ◽  
Gene Level ◽  
Human And Mouse

ABSTRACTAccess to large-scale genomics and transcriptomics data from various tissues and cell lines allowed the discovery of wide-spread alternative splicing events and alternative promoter usage in mammalians. However, evolutionary studies primarily focus on gene-level orthology relationships, which hinders the importance of transcript-level diversity. Between human and mouse, gene-level orthology is currently present for nearly 16k protein-coding genes spanning a diverse repertoire of over 200k total transcript isoforms. Here we describe a novel method, ExTraMapper, which leverages sequence conservation between exons of a pair of organisms and identifies a fine-scale orthology mapping at the exon and then transcript level. ExTraMapper identifies more than 250k exon, as well as 30k transcript mappings between human and mouse using only sequence and gene annotation information. We demonstrate that ExTraMapper identifies a larger number of exon and transcript mappings compared to previous methods. Further, it identifies exon fusions, splits, and losses due to splice site mutations, and finds mappings between microexons that are previously missed. By reanalysis of RNA-seq data from 13 matched human and mouse tissues, we show that ExTraMapper improves the correlation of transcript-specific expression levels suggesting a more accurate mapping of human and mouse transcripts. ExTraMapper also reports better transcript-level mappings compared to Ensembl orthology for the human proto-oncogene BRAF and its mouse ortholog as well as several other example genes with important isoform-specific functions. ExTraMapper is applicable to any pair of organisms that have orthologous gene pairs and is available at https://github.com/ay-lab/ExTraMapper and http://ay-lab-tools.lji.org/extramapper

Tissue-specific expression patterns of nuclear receptors

2013 ◽  
Author(s):  
AL Bookout ◽  
Y Jeong ◽  
M Downes ◽  
RT Yu ◽  
RM Evans ◽  
...  
Keyword(s):  
Nuclear Receptors ◽  
Expression Patterns ◽  
Specific Expression ◽  
Tissue Specific ◽  
Tissue Specific Expression
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